Fixed vs. Variable Threshold for DLMO Calculation: A Methodological Guide for Researchers and Clinicians

Abstract

Accurately determining the Dim Light Melatonin Onset (DLMO) is crucial for circadian rhythm research and the development of chronotherapies. This article provides a comprehensive analysis of the two primary methods for calculating DLMO: the fixed threshold and the variable threshold. Tailored for researchers, scientists, and drug development professionals, we explore the foundational principles, methodological applications, and comparative performance of each approach. Drawing on recent studies and consensus reports, we address key challenges including inter-individual variability, assay sensitivity, and protocol standardization. The discussion extends to emerging methodologies and provides evidence-based recommendations for selecting the optimal calculation method to enhance precision in both clinical trials and diagnostic settings.

Understanding DLMO: The Cornerstone of Circadian Phase Assessment

Defining DLMO and Its Role as a Gold Standard Circadian Phase Marker

The Dim Light Melatonin Onset (DLMO) is the most reliable marker for assessing the phase of the central circadian clock in humans [1] [2]. It is defined as the time in the evening when melatonin concentration in saliva or plasma begins to rise under dim light conditions, signaling the start of the biological night [3]. This application note details the critical role of DLMO as a gold-standard circadian phase marker, framed within ongoing research debates regarding its calculation, specifically comparing fixed and variable threshold methodologies. We provide standardized protocols for measuring DLMO, summarize quantitative comparisons of calculation methods, and outline essential tools for researchers and clinicians in chronobiology and drug development.

The circadian rhythm of melatonin, secreted by the pineal gland, is a direct output of the suprachiasmatic nucleus (SCN), the body's master clock [1] [4]. Among the various phase markers derived from the melatonin rhythm, the DLMO is considered the single most accurate and reliable indicator of SCN phase [1] [5]. Its superiority stems from several key attributes: it exhibits less variability than other markers like core body temperature or cortisol, is relatively resistant to masking by non-photic stimuli such as sleep or posture, and can be measured non-invasively via saliva over a practical sampling window of 4-8 hours [2] [6] [5].

DLMO measurement is indispensable for diagnosing Circadian Rhythm Sleep-Wake Disorders (CRSWDs), such as Delayed Sleep-Wake Phase Disorder (DSWPD) [6] [7] [8]. Furthermore, it is critical for personalizing the timing of chronobiological treatments, including light therapy and exogenous melatonin administration, to maximize efficacy and minimize potential misalignment [1] [9]. Research using Monte Carlo simulations has quantitatively demonstrated that patients with DSWPD exhibit a significantly delayed DLMO—by approximately 7 hours—and a reduced melatonin production rate compared to normal sleepers, highlighting profound alterations in the circadian melatonin profile [7].

Protocols for DLMO Assessment

Accurate measurement of DLMO requires strict control of environmental conditions and adherence to standardized sampling procedures.

Pre-Assessment Conditions

• Stable Sleep Schedule: Participants should maintain a fixed sleep-wake schedule (self-selected or assigned) for at least 6-14 days prior to the phase assessment [6] [5].
• Compliance Monitoring: Compliance is verified using wrist actigraphy, sleep diaries, and time-stamped phone messages [6] [5].
• Substance Restrictions: Participants must refrain from alcohol, nicotine, non-steroidal anti-inflammatory drugs (NSAIDs), and caffeine for a specified period (e.g., >20 hours for alcohol/NSAIDs, >6 hours for caffeine) before and during sampling [6] [5].

Sampling Environment and Procedure

• Dim Light Conditions: Sampling must occur in dim light, typically defined as <5 lux to <20 lux at the participant's angle of gaze, to prevent light-induced suppression of melatonin [2] [6] [5].
• Posture and Activity: Participants remain awake and seated in a recliner. They are not permitted to sleep during the sampling period. Strenuous activity is prohibited [5].
• Sample Collection:
  • Sampling Window: A 6-hour window is often sufficient, starting 5 hours before habitual bedtime and ending 1 hour after bedtime [6] [8].
  • Sampling Rate: Samples can be collected every 30 minutes (13 samples) or every 60 minutes (7 samples). Research indicates that hourly sampling provides a clinically adequate estimate of DLMO and is more cost-effective [6] [5] [10].
  • Saliva Collection: Participants provide saliva samples using devices like Salivettes. They should not eat or drink 10 minutes before each sample. If they do, they must rinse their mouth with water [5] [8].
• Sample Handling: Samples are centrifuged, frozen immediately after collection, and later assayed using a sensitive and specific immunoassay [5] [8].

Experimental Workflow

The following diagram illustrates the end-to-end workflow for a DLMO assessment study.

Quantitative Comparison of DLMO Calculation Methods

The two primary methods for calculating DLMO from melatonin concentration data are the fixed threshold and the variable threshold ("3k" method). The choice of method and sampling rate significantly impacts the calculated DLMO time and has practical implications for research and clinical practice.

Threshold Definitions

• Fixed Threshold Method: DLMO is defined as the time when melatonin concentration crosses and remains above an absolute value. Common thresholds are 3 pg/mL or 4 pg/mL for saliva [6] [5] [8].
• Variable Threshold ("3k") Method: The threshold is calculated individually for each participant as the mean of the first three low daytime melatonin concentrations plus two standard deviations (mean + 2SD) [5] [8] [10].

Impact of Threshold and Sampling Rate

The following tables summarize key findings from comparative studies.

Table 1: Impact of Sampling Rate on DLMO Calculation (n=122 adults) [5] [10]

Threshold Method	Sampling Rate	Mean DLMO Time (hh:mm)	Mean Difference vs. 30-min sampling	Correlation with 30-min DLMO
3k (Variable)	30-minute	21:26 ± 56 min	(Reference)	(Reference)
3k (Variable)	60-minute	21:18 ± 51 min	8 minutes earlier	r ≥ 0.89
Fixed 3 pg/mL	30-minute	21:48 ± 61 min	(Reference)	(Reference)
Fixed 3 pg/mL	60-minute	21:42 ± 63 min	6 minutes earlier	r ≥ 0.89

Table 2: Comparison of Fixed vs. Variable Threshold Methods [5] [8] [10]

Characteristic	Fixed Threshold (e.g., 3 pg/mL)	Variable Threshold ("3k")
Definition	Absolute concentration value	Individual baseline + 2SD
Mean DLMO Timing	Later (e.g., 22-24 min later than 3k)	Earlier, closer to the initial rise
Inter-individual Variability	Significantly less variable	More variable
Advantage	Simplicity, consistency across labs	Accommodates low and high baseline producers
Disadvantage	May miss DLMO in low secretors	Requires 3 initial low daytime samples
Failure Rate	May fail if melatonin never exceeds threshold (e.g., in low producers) [8]	More robust for diverse populations

Threshold Selection Logic

For researchers, the choice between fixed and variable thresholds involves a trade-off between consistency and individualized accuracy. The following diagram outlines the decision-making process.

The Scientist's Toolkit: Essential Reagents and Materials

Table 3: Key Research Reagent Solutions for DLMO Assessment

Item	Function/Description	Specifications/Examples
Saliva Collection Device	Non-invasive collection of saliva samples for melatonin assay.	Salivettes (Sarstedt) [5]; Passive Drool kits [8].
Sensitive Melatonin Assay	Quantification of melatonin concentration in saliva or plasma.	Competitive ELISA (e.g., Salimetrics); Sensitivity: <1.35 pg/mL; No extraction needed [8].
Dim Light Source	Provides appropriate lighting (<20 lux) during sampling to avoid melatonin suppression.	Red or amber light; Light meters calibrated to CIE S026:2018 standard [2].
Actigraphy System	Monitors compliance with pre-study sleep schedules.	Wrist-worn actigraphs (e.g., Actiwatch-L, Octagonal Basic) [6] [5].
Controlled Environment	Laboratory setting for standardized sample collection.	Temperature-controlled rooms with recliners, minimal distractions [5].

DLMO stands as the gold-standard marker for human circadian phase, with critical applications in basic research, clinical diagnosis of CRSWDs, and the optimization of circadian-targeted therapies. The methodological debate between fixed and variable thresholds for its calculation is central to its accurate application. Evidence indicates that hourly sampling provides a cost-effective and practical approach for estimating DLMO in both research and clinical settings, with a mean difference of only 6-8 minutes compared to half-hourly sampling [5] [10]. While the fixed threshold (3 pg/mL) offers lower variability, the variable "3k" threshold may be more appropriate for populations with atypical baseline melatonin levels, as it produces an earlier DLMO estimate that is closer to the initial rise of the hormone [5] [8]. Researchers must select the threshold and protocol that best align with their specific scientific questions and clinical populations.

Dim Light Melatonin Onset (DLMO) represents the most reliable marker of internal circadian phase in humans, critical for diagnosing circadian rhythm sleep-wake disorders and optimizing chronotherapy timing. The fixed threshold method establishes DLMO by applying an absolute melatonin concentration criterion, typically 3 or 4 pg/mL for saliva or 10 pg/mL for plasma. This Application Note details the experimental protocols, analytical considerations, and practical implementation of the fixed threshold method, contextualized within broader research comparing fixed versus variable threshold approaches. We provide structured quantitative data, methodological workflows, and reagent specifications to support researchers and drug development professionals in implementing robust DLMO assessment protocols.

Dim Light Melatonin Onset (DLMO) is widely regarded as the gold standard biomarker for assessing the phase of the human circadian timing system. As the most reliable circadian phase marker [11] [12], DLMO provides an objective measure of internal biological time, which is crucial for diagnosing circadian rhythm disorders and determining optimal timing for chronotherapeutic interventions. The fundamental principle involves measuring the onset of melatonin secretion under dim light conditions, typically occurring 2-3 hours before habitual sleep time [12].

Multiple analytical methods exist for determining DLMO from melatonin profiles, primarily falling into two categories: fixed threshold and variable threshold approaches. The fixed threshold method applies an absolute concentration criterion, while the variable method (often called the "3k method") uses a statistical threshold based on individual baseline values [8] [13]. This Application Note focuses specifically on the principles, protocols, and applications of the fixed threshold method, with comparative reference to alternative approaches within the context of ongoing methodological research.

Fixed Threshold Principle and Analytical Specifications

Core Principle

The fixed threshold method defines DLMO as the point in time when interpolated melatonin concentrations cross a predetermined absolute threshold. This approach utilizes a standardized concentration value, established through population studies and assay characteristics, rather than individual baseline calculations [12]. The method assumes consistent melatonin secretion patterns across populations, though adjustments may be required for specific demographic or clinical groups.

Established Threshold Criteria

Threshold values vary by biological matrix and assay methodology, with the following standards widely referenced in circadian research:

Table 1: Standard Fixed Threshold Criteria by Biological Matrix

Biological Matrix	Fixed Threshold	Conditions & Considerations
Saliva	3-4 pg/mL	Most common for salivary immunoassays [12] [13]
Plasma/Serum	10 pg/mL	Standard for blood-based measurements [12]
Plasma (low producers)	2 pg/mL	Alternative for populations with attenuated melatonin secretion [12]

Comparative Method Performance

Recent research directly compares DLMO estimation methods. A 2023 repeatability and agreement study compared four DLMO estimation methods, finding all showed "good to perfect" repeatability across nights [11]. While this study identified the hockey stick algorithm as showing equivalent or superior performance compared to visual estimation by chronobiologists, the fixed threshold method remains widely used due to its procedural simplicity and standardized implementation [11] [12].

Table 2: DLMO Method Comparison

Method	Principle	Advantages	Limitations
Fixed Threshold	Absolute concentration criterion (e.g., 3-4 pg/mL saliva)	Simple, standardized, does not require multiple baseline samples	May miss DLMO in low melatonin producers [8] [12]
Variable Threshold (3k)	2 SD above mean of 3 baseline samples	Accommodates individual baseline variation, better for low producers	Unreliable with insufficient/inconsistent baselines [12] [13]
Hockey Stick Algorithm	Objective curve-fitting algorithm	Automated, eliminates rater bias, high agreement with expert assessment	Requires specific software implementation, less familiar to researchers [11]

Experimental Protocols for Fixed Threshold DLMO Assessment

Sample Collection Workflow

The following diagram illustrates the standardized protocol for DLMO assessment using the fixed threshold method:

Figure 1.: DLMO Assessment Workflow illustrating the complete experimental protocol from participant preparation through data interpretation.

Detailed Sampling Protocol

Pre-Assessment Requirements

• Light Control: Maintain dim light conditions (<8 lux) throughout sampling period to prevent melatonin suppression [11] [14]
• Participant Preparation: Abstain from melatonin supplements, beta-blockers, NSAIDs, and other medications affecting melatonin secretion for appropriate washout periods [12]
• Substance Restrictions: Avoid caffeine, alcohol, heavy meals, and tobacco for 3 hours prior to and during sampling [8]
• Posture Control: Maintain seated or relaxed posture 10-15 minutes before each sample to minimize effects of postural changes on melatonin concentrations [12]

Sampling Schedule and Volume

• Standard Protocol: 7-point sampling (hourly) beginning 5 hours before habitual bedtime through 1 hour after bedtime [8] [13]
• Enhanced Precision: 13-point sampling (half-hourly) over the same window when higher temporal resolution required [8]
• Sample Volume: 0.5 mL saliva per sample sufficient for duplicate melatonin measurements [8]
• Collection Method: Passive drool into appropriate collection tubes [8] [13]

Sample Processing and Storage

• Immediate Processing: Centrifuge samples upon collection if possible, or store temporarily at 4°C
• Long-term Storage: Freeze at -20°C or -80°C until analysis [8]
• Avoid Repeated Freeze-Thaw: Aliquot samples to minimize degradation

DLMO Calculation Protocol

• Assay Melatonin Concentrations: Analyze samples using validated immunoassay or LC-MS/MS method
• Plot Concentration vs. Time: Graph melatonin profile with time on x-axis and concentration on y-axis
• Apply Fixed Threshold: Draw horizontal line at appropriate threshold (3 or 4 pg/mL for saliva)
• Interpolate DLMO Time: Identify time point where rising melatonin curve crosses threshold using linear interpolation between bracketing samples
• Report DLMO: Express as clock time relative to sampling period

Analytical Methodologies and Reagent Solutions

Research Reagent Solutions

Table 3: Essential Research Materials for DLMO Assessment

Item	Specification	Function/Application
Salivary Melatonin Assay	Sensitivity: <1.35 pg/mL; Range: 0.78-50 pg/mL [8]	Quantification of low melatonin concentrations in saliva
Saliva Collection Kit	Passive drool apparatus, polypropylene tubes	Non-invasive sample collection with minimal interference
Dim Light Source	<8 lux verified with lux meter	Prevents photic suppression of melatonin secretion
Portable Freezer	-20°C capability for transport	Sample preservation during collection protocol
Actigraphy Device	Motion sensing with light detection	Objective verification of compliance with protocol conditions

Analytical Platform Comparison

Table 4: Analytical Methods for Melatonin Quantification

Parameter	Immunoassay (ELISA)	Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS)
Sensitivity	Good (1.35 pg/mL for Salimetrics assay) [8]	Excellent (sub-pg/mL achievable) [12]
Specificity	Moderate (potential cross-reactivity) [12]	High (minimal cross-reactivity) [12]
Throughput	High (38 samples in duplicate per plate) [8]	Moderate
Cost	Lower	Higher
Sample Volume	100 µL per well [8]	Typically 100-500 µL
Methodology	Colorimetric detection, no extraction [8]	Requires specialized instrumentation [12]

Applications in Research and Drug Development

Circadian Phenotyping

Fixed threshold DLMO provides a standardized approach for circadian phase assessment in large-scale studies. The method's simplicity facilitates implementation across multiple sites in collaborative trials, ensuring consistent endpoint measurement in chronotype characterization and circadian rhythm phenotyping [14].

Chronotherapy Optimization

In drug development, DLMO assessment guides optimal timing of drug administration based on circadian physiology. The fixed threshold method offers practical implementation for phase assessments that inform chronotherapy trials, particularly where relative timing rather than absolute precision is paramount [12].

Circadian Rhythm Sleep-Wake Disorders

Fixed threshold DLMO provides diagnostic clarity for disorders including Delayed Sleep-Wake Phase Disorder (DSWPD) and Advanced Sleep-Wake Phase Disorder (ASWPD). The method's established reference ranges facilitate clinical interpretation and treatment planning [8] [13].

Methodological Considerations and Limitations

Addressing Low Melatonin Producers

The primary limitation of the fixed threshold method involves individuals with consistently low melatonin production (common in aging populations), who may not reach the standard threshold despite normal circadian phase [8] [12]. Mitigation strategies include:

• Implementing a lower threshold (2 pg/mL) for suspected low producers [12]
• Supplemental use of variable threshold method when fixed threshold fails to detect DLMO
• Prescreening for melatonin suppression factors including medications and ocular pathology

Threshold Selection Considerations

Choice between 3 pg/mL versus 4 pg/mL thresholds involves balancing sensitivity and specificity:

• 3 pg/mL: Increases detection sensitivity, particularly for low producers, but may identify earlier phase
• 4 pg/mL: Provides more conservative estimate, potentially closer to physiological onset

Comparative studies show variable threshold methods typically produce DLMO estimates 22-24 minutes earlier than fixed 3 pg/mL threshold [12].

Procedural Variations in Research Contexts

Recent research explores modifications to enhance feasibility of DLMO assessments, particularly in special populations. A 2025 study of home-based DLMO assessment in obesity demonstrated high detection rates (89.6-98.2%) using fixed threshold methods, supporting implementation outside highly controlled laboratory settings [14].

Table 5: Procedural Variations in DLMO Assessment

Parameter	Standard Protocol	Alternative Approaches
Setting	Sleep laboratory/clinic	Home-based assessment [14]
Sampling Rate	Hourly (7 samples)	Half-hourly (13 samples) for enhanced precision [8]
Analysis Method	Fixed threshold (3-4 pg/mL)	Variable threshold, hockey stick algorithm [11]
Sample Type	Saliva (most common)	Plasma, serum (higher concentrations) [12]

The fixed threshold method for DLMO assessment provides a standardized, practically implementable approach for determining circadian phase in research and clinical applications. While emerging methodologies like the hockey stick algorithm offer enhanced objectivity [11], the fixed threshold remains widely utilized due to its procedural simplicity and established reference criteria. Researchers should select threshold methodology based on specific population characteristics, analytical capabilities, and precision requirements, with particular attention to potential limitations in low melatonin producers. The structured protocols and analytical frameworks presented herein support robust implementation within circadian research and chronotherapy development programs.

The Dim Light Melatonin Onset (DLMO) is established as the most reliable marker of circadian phase in humans, providing a critical window into the timing of the central circadian clock located in the suprachiasmatic nucleus (SCN) [5]. As research and clinical interest in circadian rhythms and sleep disorders grows, practical and accurate methods for determining DLMO have become increasingly important. The core challenge in DLMO calculation lies in defining the precise moment when evening melatonin production begins its sharp increase. Two primary methodological approaches have emerged to address this challenge: the fixed threshold method and the variable threshold method (often referred to as the "3k method") [5] [8]. The fixed threshold approach uses a predetermined melatonin concentration (typically 3 or 4 pg/mL for saliva) to mark the onset, while the variable threshold method establishes a personalized threshold for each individual based on their own baseline melatonin levels [5] [8]. This application note focuses on the principles, protocols, and applications of the variable threshold method, contextualized within broader research comparing fixed versus variable threshold approaches for DLMO calculation.

Theoretical Foundation of the Variable Threshold (3k) Method

Calculation Methodology

The variable threshold method, known as the 3k method, determines an individual's DLMO threshold through a baseline-relative calculation. This approach establishes a personalized threshold based on an individual's own low daytime melatonin levels, effectively accounting for baseline variations between subjects [5] [8]. The calculation requires sampling the first three low daytime melatonin points and applying the following formula:

Threshold = Mean (First 3 points) + [2 × Standard Deviation (First 3 points)]

This algorithm creates a threshold that is typically significantly lower than the commonly used fixed threshold of 3 pg/mL [5]. Research by Molina and Burgess (2011) demonstrated that the 3k threshold was substantially lower than the 3 pg/mL fixed threshold (p < 0.001), resulting in DLMO estimates that were 22-24 minutes earlier, regardless of sampling rate [5]. This earlier detection captures the initial rise of melatonin more effectively than the fixed threshold method, potentially providing a more biologically accurate phase marker.

Advantages in Research and Clinical Settings

The variable threshold method offers particular advantages for populations with altered melatonin secretion patterns. The method accommodates both low melatonin secretors, who may not reach absolute fixed thresholds, and individuals with elevated baseline melatonin levels, whose natural onset might be masked by a fixed threshold [8]. This sensitivity makes the 3k method particularly valuable in aging populations, where melatonin production often declines, and in clinical populations where circadian dysfunction may involve altered melatonin profiles [8]. By deriving the threshold from individual baseline characteristics, the 3k method provides a personalized approach to circadian phase assessment that may enhance diagnostic accuracy in heterogeneous patient populations.

Table 1: Comparison of Fixed versus Variable Threshold Methods for DLMO Calculation

Parameter	Fixed Threshold Method	Variable Threshold (3k) Method
Calculation Basis	Pre-defined absolute value (e.g., 3 or 4 pg/mL)	Individual's baseline mean + 2 standard deviations
Typical Threshold Value	3 pg/mL (saliva)	Lower than fixed threshold (highly variable)
DLMO Timing	Later (by 22-24 minutes) [5]	Earlier, closer to initial melatonin rise [5]
Inter-individual Variability	Less variable DLMO estimates [5]	More variable DLMO estimates [5]
Advantages	Simple, standardized, less variable	Accounts for individual baseline differences, works for low secretors
Limitations	May miss DLMO in low secretors, further from initial rise	Requires 3 initial low points, more variable between individuals

Quantitative Comparisons of DLMO Calculation Methods

Impact of Sampling Rate and Threshold Selection

The practical implementation of DLMO protocols requires consideration of both sampling rate and threshold method. Research indicates that while sampling frequency impacts the precision of DLMO determination, the choice of threshold method may have more substantial effects on the estimated phase.

Table 2: Impact of Sampling Rate on DLMO Determination Using Different Thresholds

Sampling Rate	Threshold Method	Average DLMO Time	Correlation with Half-hourly Sampling	Cases with >30 min Difference
Hourly	3k Variable	21:18 h ± 51 min	r ≥ 0.89 [5]	Up to 19% [5]
Half-hourly	3k Variable	21:26 h ± 56 min	Reference	Reference
Hourly	3 pg/mL Fixed	21:42 h ± 63 min	r ≥ 0.89 [5]	Up to 19% [5]
Half-hourly	3 pg/mL Fixed	21:48 h ± 61 min	Reference	Reference

Data adapted from Molina and Burgess (2011) comparing hourly versus half-hourly sampling in 122 individuals [5].

Comparative Performance Across Methodologies

Recent research has expanded beyond the traditional threshold comparisons to include newer analytical approaches. A 2023 study by Glacet et al. compared four DLMO estimation methods, including fixed threshold, dynamic threshold, hockey stick, and visual estimation [11]. The study found the hockey stick method demonstrated equivalent or superior performance (ICC: 0.95, mean difference with visual estimation: 5 minutes) in healthy subjects compared to dynamic and fixed thresholds [11]. This suggests that while threshold methods remain valuable, emerging analytical approaches may offer enhanced reliability for specific research applications. The repeatability of the four methods across two nights ranged from good to perfect, indicating that multiple approaches can provide consistent phase estimates in longitudinal study designs [11].

Experimental Protocols for Variable Threshold DLMO Determination

Sample Collection Framework

The following protocol provides a standardized approach for determining DLMO using the variable threshold method, suitable for both research and clinical settings.

Pre-Assessment Requirements

• Participant Preparation: Participants should maintain a regular sleep schedule (fixed bedtimes and wake times) for 6-14 days prior to assessment [5]. Compliance should be verified using wrist actigraphy, sleep logs, and time-stamped voicemail messages at bedtime and wake time [5] [6].
• Substance Restrictions: Participants should avoid alcohol and non-steroidal anti-inflammatory drugs (NSAIDs) for at least 20 hours prior to sampling [5]. Caffeine should be restricted for at least 6 hours before the session [5]. A breathalyzer test upon arrival can verify zero blood alcohol concentration [5].

Sampling Environment and Procedure

• Lighting Conditions: Maintain dim light conditions (<5 lux at subjects' angle of gaze) throughout the sampling period [5]. Brief restroom breaks (<5 lux) are permitted, but participants should remain seated for 10 minutes prior to each sample [5].
• Sampling Window: Begin sampling 5 hours before habitual bedtime and continue for at least 6 hours, extending to 1 hour after bedtime [8] [6]. For severely phase-shifted individuals, consider extending the sampling window [8].
• Sampling Frequency: Collect samples either hourly or half-hourly depending on precision requirements and resource constraints [5] [8]. For the variable threshold method, ensure collection of at least three low daytime points before the expected rise.
• Saliva Collection: Use Salivette collection devices or passive drool method [5] [8]. Collect approximately 0.5 mL saliva per sample, which is sufficient for duplicate melatonin measurements [8]. Participants should not eat or drink 10 minutes before each sample; if food is consumed, teeth should be brushed with water [5].

Sample Processing and Analysis

• Immediate Processing: Centrifuge samples promptly after collection and freeze immediately [5]. Ship frozen samples on dry ice to a qualified laboratory.
• Melatonin Assay: Use a high-sensitivity melatonin assay with appropriate specifications. For example, the Salimetrics Melatonin Assay has sensitivity of 1.35 pg/mL, requires 100 μL per well, and has an assay time of 3.5 hours without extraction [8].
• Quality Control: Ensure the laboratory follows CLIA and GLP standards or NIH requirements for rigor and reproducibility [8]. Assay performance characteristics should include intra- and inter-assay variability below 15% (e.g., 12.1% and 13.2% respectively) [5].

Diagram 1: 3k Variable Threshold DLMO Calculation Workflow (Width: 760px)

The Scientist's Toolkit: Research Reagent Solutions

Table 3: Essential Materials for DLMO Assessment Using Variable Threshold Method

Item	Specification/Example	Function/Application
Saliva Collection Device	Salivettes or passive drool kits [5] [8]	Non-invasive saliva sample collection
Dim Light Environment	<5 lux at angle of gaze [5]	Prevents light-induced melatonin suppression
Portable Lux Meter	Calibrated light meter	Verifies appropriate dim light conditions
Actigraphy Device	Actiwatch-L or similar [5]	Monitors sleep-wake compliance pre-assessment
Melatonin Assay Kit	Competitive ELISA, sensitivity ≤1.35 pg/mL [8]	Quantifies salivary melatonin concentration
Low-Temp Freezer	-20°C or -80°C	Preserves sample integrity before analysis
Centrifuge	Standard laboratory model	Processes saliva samples after collection

Data Analysis and Interpretation

Implementing the Variable Threshold Calculation

To calculate DLMO using the 3k method, follow these computational steps:

• Identify Baseline Values: Select the first three low daytime melatonin concentrations from the profile [5] [8].
• Calculate Mean and Standard Deviation: Compute the arithmetic mean and standard deviation of these three values.
• Establish Individual Threshold: Apply the formula: Threshold = Mean + (2 × Standard Deviation) [5] [8].
• Determine DLMO Point: Identify the time when melatonin concentration crosses and remains above the calculated threshold for at least 2 hours using linear interpolation between points [5].

Diagram 2: Variable vs. Fixed Threshold Decision Pathway (Width: 760px)

Addressing Analytical Challenges

Several potential challenges may arise when implementing the variable threshold method:

• Insufficient Baseline Points: The 3k method requires at least three low daytime points for calculation. If these are unavailable due to sampling limitations, consider alternative methods [5].
• High Baseline Variability: When the standard deviation of the first three points is large, the threshold may become artificially elevated. Visual inspection of the melatonin profile can help identify such cases.
• Failure to Exceed Threshold: If melatonin levels fail to exceed the calculated threshold, the sampling window may need extension, particularly for severely phase-shifted individuals [8].
• Comparison Across Studies: When comparing results across studies using different threshold methods, acknowledge that the variable threshold typically produces earlier DLMO estimates than fixed thresholds (by approximately 22-24 minutes) [5].

The variable threshold method for DLMO calculation represents a significant advancement in circadian phase assessment by accounting for individual differences in baseline melatonin secretion. While this approach produces earlier and more variable phase estimates compared to fixed threshold methods, it offers particular advantages for populations with altered melatonin profiles, including low secretors often encountered in aging and clinical populations. The 3k method's baseline-relative calculation provides a personalized approach to circadian phase marking that may enhance both research accuracy and clinical applicability. As circadian medicine continues to evolve, the variable threshold method stands as a valuable tool for precise circadian phenotyping in heterogeneous populations, ultimately supporting the development of targeted chronotherapeutic interventions. Future methodological developments, including the hockey stick method and mathematical modeling approaches, may further refine DLMO estimation, but the variable threshold method remains a well-validated and practically implementable approach for both research and clinical applications.

In biomedical research and therapeutic drug monitoring, the selection of an appropriate biological matrix is fundamental to the success and accuracy of any analytical method. Saliva, plasma, and urine each offer distinct advantages and limitations, making them suitable for different applications. Saliva has gained significant traction as a non-invasive matrix that reflects the biologically active, unbound fraction of analytes, while plasma remains the gold standard for systemic concentration measurements, and urine provides a valuable medium for monitoring excretion and metabolic byproducts [15] [16]. The practical utility of these matrices is particularly evident in specialized applications such as circadian rhythm research, where the measurement of dim light melatonin onset has been revolutionized by salivary assessment methods. This application note provides a detailed comparison of these biological matrices, with specific protocols and data analysis techniques focused on DLMO assessment, framed within ongoing research debates regarding fixed versus variable threshold calculations.

Comparative Analysis of Biological Matrices

Technical Specifications and Applications

Table 1: Comparison of Key Biological Matrices in Biomedical Research

Parameter	Saliva	Plasma/Serum	Urine
Collection Method	Non-invasive (passive drool, Salivette, swabs) [16]	Invasive (venipuncture) requiring trained personnel [15]	Non-invasive (voided sample)
Patient Compliance	High, especially in pediatric and geriatric populations [16]	Low due to invasiveness and discomfort [15]	High for single samples, moderate for 24h collections
Analyte Representation	Free, unbound fraction (pharmacologically active) [16]	Total concentration (bound + unbound)	Metabolic byproducts and excreted compounds
Sample Complexity	Low to moderate (fewer interfering proteins) [16]	High (abundant proteins, lipids)	Variable (dependent on hydration state)
Major Advantages	Suitable for frequent sampling, home-based collection, reflects active drug fraction [15] [16]	Systemically representative, established reference ranges	Cumulative metabolic information, large sample volumes
Primary Limitations	Potential for blood contamination, variable flow rate, dilution from stimulation [16]	Invasive collection, requires specialized equipment and training	Variable concentration, requires volume normalization

Matrix Selection Criteria for Analytical Applications

The choice between saliva, plasma, and urine depends on multiple factors, including the research objective, analyte properties, and practical considerations. Saliva is particularly valuable for therapeutic drug monitoring of medications where the unbound fraction is clinically relevant, for circadian phase assessments through DLMO, and for pediatric studies where repeated blood sampling is ethically challenging [16]. Plasma remains essential for establishing pharmacokinetic profiles, determining absolute bioavailability, and monitoring drugs with extensive protein binding. Urine analysis provides critical information for renal clearance calculations, detection of substance use, and metabolic pathway elucidation.

For circadian rhythm research, saliva offers unique advantages as it enables frequent, non-invasive sampling in dim light conditions without disrupting the natural sleep-wake cycle, which is crucial for accurate melatonin measurement [8] [13]. The correlation between salivary and plasma melatonin concentrations has been well-established, with studies showing high correlation coefficients, validating saliva as a reliable matrix for DLMO assessment [8] [5].

Salivary Dim Light Melatonin Onset Assessment: Application Note

Background and Significance

Dim light melatonin onset represents the most reliable marker of central circadian phase in humans [5] [14]. DLMO is defined as the time at which endogenous melatonin concentrations begin to rise in the evening, signaling the onset of the biological night. This parameter has become increasingly important for diagnosing circadian rhythm sleep-wake disorders, optimizing chronotherapeutic interventions, and investigating circadian misalignment in metabolic diseases [14] [17].

The transition from plasma to salivary melatonin assessment has significantly advanced the field by enabling home-based data collection, improving participant compliance, and facilitating larger-scale studies [8] [13]. Current research is focused on refining DLMO calculation methodologies, particularly comparing fixed versus variable thresholds to improve accuracy across diverse populations.

Experimental Protocol for Salivary DLMO Assessment

Sample Collection Protocol

• Preparation Phase:

  • Participants should maintain a consistent sleep-wake schedule for at least 7 days prior to assessment [5] [14]
  • Avoid alcohol, NSAIDs, and caffeine for at least 24 hours before sampling [5]
  • Avoid melatonin supplements for at least 1 week prior to testing

• Sampling Environment:

  • Conduct sampling in dim light conditions (<5 lux at angle of gaze) to prevent melatonin suppression [5] [14]
  • Use red light if illumination is necessary during sample collection

• Collection Procedure:

  • Begin collection 5 hours before habitual bedtime and continue until 1 hour after bedtime [8] [13]
  • Collect samples at hourly or half-hourly intervals using Salivette devices or passive drool into polypropylene tubes [16]
  • For hourly sampling: 7 timepoints typically sufficient for reliable DLMO estimation [8] [13]
  • For enhanced precision: 13 timepoints with half-hourly sampling [5]
  • Restrict food and liquid intake 10 minutes before each sample; if consumed, rinse mouth with water [5]

• Sample Processing:

  • Centrifuge samples promptly to separate saliva from mucins and cellular debris [16]
  • Store samples at -20°C or -80°C until analysis
  • Avoid repeated freeze-thaw cycles

Analytical Considerations

Salivary melatonin analysis requires highly sensitive immunoassays due to low physiological concentrations. Recommended assay specifications include:

• Sensitivity: ≤1.35 pg/mL [8] [13]
• Assay range: 0.78-50 pg/mL [8]
• Minimal sample volume: 100μL for duplicate measurements [8]
• No extraction required for streamlined processing [8] [13]

Table 2: DLMO Calculation Methods Comparison

Parameter	Fixed Threshold Method	Variable Threshold (3k) Method
Calculation Principle	Pre-determined absolute concentration (typically 3-4 pg/mL) [5]	Individual baseline + 2 standard deviations [8] [5]
Threshold Determination	Uniform across all participants	Personalized based on first 3 low daytime points
Advantages	Simple, less variable between calculations [5]	Accommodates low melatonin producers, handles elevated baselines [8] [13]
Limitations	May miss DLMO in low secretors, inaccurate with high baselines [8]	More variable between calculations [5]
Recommended Application	Populations with normal melatonin production	General population, elderly, individuals with low secretion or shifted baselines
Typical DLMO Timing Difference	Reference point	22-24 minutes later than fixed threshold method [5]

Data Analysis and Interpretation

DLMO is determined through linear interpolation between the sample points immediately below and above the threshold. The variable "3k" method calculates the threshold as the mean of the first three low daytime points plus two standard deviations of these points [8] [5]. Research indicates that while the fixed threshold method (typically 3 pg/mL) produces less variable DLMOs, the 3k method generates DLMO estimates that are closer to the initial rise of melatonin and is more inclusive of individuals with atypical melatonin secretion patterns [5].

The following decision pathway illustrates the methodological approach to salivary DLMO assessment:

The Scientist's Toolkit: Essential Research Reagents and Materials

Table 3: Essential Materials for Salivary Melatonin Research

Item	Specification	Application Purpose
Saliva Collection Devices	Salivette (Sarstedt), Passive Drool Tubes, SalivaBio Swabs [16]	Standardized sample collection with minimal interference
Melatonin Assay Kit	Salimetrics Melatonin ELISA, Sensitivity: 1.35 pg/mL, Range: 0.78-50 pg/mL [8] [13]	Quantitative melatonin measurement without extraction
Dim Light Environment	Red light source, Lux meter (<5 lux verification) [5] [14]	Prevents melatonin suppression during sampling
Sample Storage	Polypropylene cryovials, -80°C freezer [16]	Preserves sample integrity for accurate analysis
Centrifuge	Refrigerated centrifuge capable of 1500×g [16]	Clarifies saliva samples by removing debris
Data Analysis Software	Custom MATLAB, R scripts, or specialized circadian software	Implements 3k and fixed threshold calculations

Saliva, plasma, and urine each occupy distinct niches in biomedical analysis, with saliva emerging as a particularly valuable matrix for non-invasive, frequent sampling applications such as circadian phase assessment. The DLMO protocol detailed in this application note provides researchers with a standardized methodology for collecting and analyzing salivary melatonin, with particular attention to the ongoing methodological debate regarding fixed versus variable threshold calculations. As research continues to refine these approaches, the considerations outlined here will help ensure reliable, reproducible data collection across diverse populations and research settings. The integration of salivary diagnostics into broader precision medicine frameworks promises to enhance both clinical practice and pharmacological development in the coming years.

The Impact of Ambient Light and Standardized Dim-Light Protocols

Dim Light Melatonin Onset (DLMO) serves as the gold-standard marker for assessing the phase of the human central circadian clock, located in the suprachiasmatic nucleus (SCN) [18]. The precise measurement of DLMO is critically dependent on the rigorous control of ambient light, as light exposure, particularly in the blue spectrum, induces acute suppression of melatonin secretion, thereby distorting the true circadian signal [18] [19]. Consequently, standardized dim-light protocols are not merely a procedural recommendation but a foundational requirement for obtaining valid and reliable circadian phase assessments. The growing emphasis on translational circadian medicine and the need for accessible biomarkers in drug development have accelerated the transition of DLMO assessment from controlled laboratory settings to home-based environments [14] [20]. This shift necessitates robust and easily implementable protocols that can withstand the less controlled home setting while preserving data integrity. This application note details the impact of ambient light and outlines standardized protocols for dim-light conditions, explicitly framed within ongoing methodological debates regarding the calculation of DLMO using fixed versus variable thresholds.

Scientific Background and Significance

The circadian system is a complex network that orchestrates numerous physiological processes over the 24-hour cycle [14]. DLMO marks the start of the biological night, occurring when melatonin concentrations rise sharply in the evening under dim light conditions. This event is precipitated by the disinhibition of the pineal gland, allowing melatonin to be released into the circulation [14]. As a direct output of the SCN, DLMO provides the most reliable estimate of central circadian phase, with a precision (standard deviation) of 14 to 21 minutes, which is notably superior to cortisol-based phase estimates [18].

The accurate measurement of DLMO is complicated by the phenomenon of masking, where external factors obscure the true endogenous rhythm. Ambient light is the most potent masking agent. Even brief exposure to room light can significantly suppress melatonin production, leading to a delayed or attenuated DLMO reading that does not reflect the underlying circadian phase [18]. This is particularly problematic in home-based collections, where environmental control is delegated to the participant. The development of standardized dim-light protocols is therefore essential for minimizing this bias and ensuring that measured DLMO is a valid biomarker for both research and clinical applications, such as diagnosing circadian rhythm sleep-wake disorders and optimizing chronotherapy in drug development [18].

Core Methodological Debate: Fixed vs. Variable Thresholds

A central challenge in DLMO calculation is defining the precise point of "onset," which has led to two predominant methodological approaches: the fixed threshold and the variable threshold.

• Fixed Threshold Method: This method defines DLMO as the time when interpolated melatonin concentrations cross a pre-defined absolute value. Commonly used thresholds are 3 pg/mL or 4 pg/mL for saliva and 10 pg/mL for serum [14] [18]. The key advantage of this method is its simplicity and objectivity. However, it fails to account for significant inter-individual differences in melatonin amplitude. For individuals who are "low producers," a fixed threshold may fall outside their dynamic range, making DLMO undetectable or resulting in a substantial overestimation of their circadian phase [18].

• Variable Threshold Method: This method calculates a threshold relative to the individual's own baseline melatonin levels, typically set at two standard deviations above the mean of three or more pre-rise baseline values [18]. This approach personalizes the calculation, making it more suitable for populations with blunted melatonin amplitude. However, it can be unreliable if too few baseline samples are collected or if the baseline values are unstable [18]. A study comparing the two methods found that the variable method produced DLMO estimates that were 22-24 minutes earlier than a fixed 3 pg/mL threshold and was closer to the physiological onset in 76% of cases [18].

Hockey-Stick Algorithm: To mitigate the limitations of both methods, more objective, automated algorithms like the "hockey-stick" algorithm have been developed. This algorithm estimates the point of change from baseline to the rising phase of melatonin and has shown better agreement with expert visual assessments than either fixed or dynamic threshold methods [18].

Table 1: Comparison of DLMO Calculation Methods

Method	Description	Advantages	Limitations
Fixed Threshold	Crosses an absolute concentration (e.g., 3-4 pg/mL saliva).	Simple, objective, standardized.	Poor performance in low melatonin producers; may miss true onset.
Variable Threshold	Crosses a value relative to individual baseline (e.g., 2 SD above mean).	Accounts for individual amplitude differences.	Unreliable with few/inconsistent baselines; more complex calculation.
Hockey-Stick Algorithm	Algorithmically identifies the inflection point from baseline to rise.	Objective, automated, good agreement with expert judgement.	Requires specific software; less commonly used in all labs.

The choice between fixed and variable thresholds has direct implications for research outcomes and clinical diagnostics. For instance, in a study of women with obesity, a fixed threshold detected DLMO in 89.6% of participants, while an individualized (variable) threshold achieved a 98.2% detection rate, highlighting the variable method's enhanced sensitivity in specific populations [14].

Detailed Experimental Protocols

Standardized Home-Based DLMO Assessment Protocol

The following protocol synthesizes best practices from recent studies demonstrating the feasibility and validity of home-based DLMO collection [14] [19] [20].

A. Pre-Assessment Preparation (7-14 Days Prior)

• Actigraphy Monitoring: Participants wear an actigraphy watch (e.g., Actiwatch Spectrum Plus, ActTrust 2) on the non-dominant wrist to objectively monitor sleep-wake patterns and physical activity for 7-14 days [14] [20].
• Sleep Diaries: Participants concurrently maintain a daily sleep diary to record self-reported bedtime, sleep onset time, wake time, and rise time. This data is used to calculate the participant's habitual sleep onset timing, which informs the sampling window for the DLMO night [14] [21].

B. Participant Training and Kit Provision Participants receive comprehensive training and a customized at-home DLMO kit. Key components and their functions are listed below.

Table 2: Research Reagent and Equipment Solutions for Home-Based DLMO

Item	Function	Application Note
Salivettes	Untreated saliva collection devices for hormone sampling.	Essential for non-invasive, frequent sampling; must be stored properly [19].
Light Meter	Measures ambient light intensity to verify dim-light conditions.	Critical for protocol compliance; confirms light levels are <10-15 lux [19].
Actigraphy Watch	Objectively monitors rest/activity cycles and sleep.	Used for pre-assessment and can monitor activity during DLMO collection [14] [19].
Blue Light-Blocking Glasses	Prevents melatonin suppression from screens/light sources.	Worn if participants must use devices; provides an added layer of protection [19].
MEMs Cap	Electronic bottle cap that records the exact time of sample collection.	Provides objective compliance data for sampling timing [19].
Temperature Sensor	Monitors storage temperature of samples post-collection.	Ensures sample integrity during temporary storage before shipping to lab [19].

C. DLMO Collection Procedure

• Schedule: The collection is scheduled for a day free of significant circadian disruptions (e.g., not after a weekend or following transmeridian travel) [19].
• Dim-Light Environment Preparation: Beginning at least 1 hour before the first sample and continuing throughout the collection, participants must remain in a dimly lit environment. Light levels must be consistently maintained below 10-15 lux at eye level. This can be achieved using dim red or amber night-lights, tealights, or by covering bright LEDs on electronics [19].
• Sampling Window: Collection begins 5-6 hours before habitual sleep onset and continues until 1-2 hours after habitual sleep onset, resulting in a 6-8 hour sampling session [18]. Samples are collected every 30-60 minutes.
• Sample Collection: For each sample, the participant provides saliva using the Salivette. The Salivette is then placed in a MEMs-capped tube to record the time and stored in a provided freezer bag with ice packs to maintain stability [19].
• Post-Collection: Samples are returned to the research laboratory via overnight shipping with a prepaid label and adequate coolant.

D. Compliance Monitoring

• Objective: Compliance is verified via actigraphy (to confirm low activity/rest), MEMs caps (for sampling time), and participant-reported light meter readings [19] [20].
• Subjective: Participants complete a checklist reporting any protocol deviations.

Analytical Methods for Melatonin Quantification

Upon receipt, saliva samples are typically centrifuged to extract clear saliva for analysis. Two primary analytical techniques are employed:

• Immunoassays (ELISA): A traditional method that is widely accessible. However, it can suffer from cross-reactivity with other molecules, leading to potentially lower specificity and overestimation of melatonin concentrations, especially at low levels [18].
• Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS): This is the gold-standard analytical method due to its high sensitivity, specificity, and reproducibility. LC-MS/MS is particularly advantageous for accurately quantifying the low concentrations of melatonin found in saliva and is less prone to matrix interferences [18].

Data Analysis and Interpretation

After melatonin concentrations are determined, the DLMO time is calculated using the chosen method(s). The following workflow outlines the procedural steps and key decision points in home-based DLMO assessment, culminating in the threshold calculation.

The phase angle of entrainment—the interval between DLMO and sleep onset—is a critical derived metric. Research indicates that a later sleep onset and a larger phase angle are correlated with younger age and evening diurnal preference [14]. It is noteworthy that in some populations, such as women with obesity, diurnal preference (chronotype) may not directly correlate with the objective central circadian phase (DLMO), suggesting that other behavioral and sociodemographic factors influence self-reported chronotype [14].

Implications for Research and Drug Development

The successful implementation of standardized, home-based DLMO protocols has profound implications:

• Enhanced Participant Recruitment: Remote collection increases accessibility for populations traditionally excluded from circadian studies, such as those with obesity, pediatric patients, or individuals in remote locations [14] [19].
• Real-World Data Validity: Home-based assessments capture circadian phase in a participant's natural environment, potentially increasing the ecological validity of findings compared to laboratory settings [20].
• Chronotherapy and Drug Development: Reliable circadian phase assessment is pivotal for chronotherapy, where timing medication administration to coincide with specific circadian phases can improve efficacy and reduce side effects [18]. The ability to easily measure DLMO in clinical trial participants could stratify populations based on circadian phase and optimize trial design for time-of-day-dependent interventions.

The integrity of DLMO as a circadian biomarker is fundamentally dependent on the stringent control of ambient light through standardized protocols. The methodological choice between fixed and variable thresholds for calculating DLMO presents a trade-off between standardization and individualization. While fixed thresholds offer simplicity, variable thresholds can provide greater accuracy, particularly in populations with altered melatonin secretion. The protocols detailed herein provide a framework for obtaining reliable DLMO data in home settings, thereby advancing the field of circadian biology and its application in clinical practice and drug development. Future work should focus on establishing consensus guidelines for threshold selection and further validating automated calculation algorithms like the hockey-stick method across diverse populations.

Protocols in Practice: Implementing Fixed and Variable DLMO Calculations

Step-by-Step Guide to Fixed Threshold Application (e.g., 3 pg/mL in saliva)

The Dim Light Melatonin Onset (DLMO) is the most reliable and biologically accurate marker for assessing the phase of the human circadian clock [8] [12]. It represents the time in the evening when the concentration of melatonin, a sleep-promoting neurohormone, begins to rise in dim light conditions. Accurate determination of DLMO is critical for diagnosing Circadian Rhythm Sleep-Wake Disorders (CRSWDs), such as Delayed Sleep-Wake Phase Disorder (DSPD), and for timing light therapy or exogenous melatonin administration [8] [6].

A central methodological debate in the field revolves around the choice of algorithm for calculating DLMO. This guide details the application of the fixed threshold method, which defines DLMO as the time when melatonin concentrations cross a predetermined absolute value (e.g., 3 pg/mL in saliva) [12]. This method is often contrasted with the variable threshold method (e.g., the "3k method"), which sets a threshold based on an individual's own baseline melatonin levels (typically the mean of the first three low daytime samples plus two standard deviations) [8]. The fixed threshold method offers simplicity and standardization but must be applied with a clear understanding of its strengths and limitations, particularly regarding inter-individual variation in melatonin production [8] [12].

Methodological Comparison of DLMO Calculation Techniques

Table 1: Comparison of Primary DLMO Calculation Methods

Method	Definition	Advantages	Limitations
Fixed Threshold	DLMO is the interpolated time when melatonin concentration crosses an absolute value (e.g., 3 or 4 pg/mL for saliva; 10 pg/mL for serum) [12].	Simple, objective, and easily standardized across laboratories. Reduces computational complexity [11].	May miss DLMO in low melatonin producers (e.g., older adults) if the threshold is too high. Can be inaccurate for individuals with high baseline levels [8] [12].
Variable Threshold ("3k Method")	DLMO is the time when concentration crosses a threshold set at 2 standard deviations above the mean of the first three low daytime samples [8].	Accounts for individual differences in baseline secretion and amplitude. More reliable for low producers [8].	Requires stable, low baseline samples. Can be unreliable if fewer than three baseline samples are available or if the baseline is unstable [12].
Hockey Stick Algorithm	An objective, automated algorithm that estimates the point of change from baseline to the rising phase of melatonin [12].	Highly objective; shows excellent agreement with expert visual estimation and superior repeatability [11] [12].	Less commonly implemented in standard software packages; requires specific algorithmic calculation [11].

Step-by-Step Protocol for Fixed Threshold DLMO Application

Pre-Sampling Preparations and Considerations

• Participant Instructions: For 5-7 days prior to sampling, participants must maintain a fixed sleep-wake schedule aligned with their habitual bedtime. They should avoid [12] [6]:

  • Non-Steroidal Anti-Inflammatory Drugs (NSAIDs), which can suppress melatonin.
  • Beta-blockers and certain antidepressants (e.g., fluoxetine) that can alter melatonin levels.
  • Alcohol, nicotine, and caffeine in the hours before sampling.
  • Bright light exposure in the evening before the session. Use dim, ambient light (< 20 lux) when traveling to the lab.

• Sampling Environment Setup: The sampling must occur in a dedicated, dimly lit environment (< 20 lux). Light levels should be verified at eye level using a lux meter [6]. Participants should remain in this dim light throughout the entire sampling procedure.

Sample Collection Workflow

The following workflow outlines the standardized procedure for collecting salivary samples to determine DLMO using the fixed threshold method.

Sampling Protocol and Analytical Assay

• Sampling Window: Begin collecting samples 5 hours before the individual's habitual bedtime and continue until 1 hour after bedtime [8] [6]. This creates a 6-hour window that reliably captures the melatonin onset for most individuals.
• Sampling Rate:
  • High-Precision Protocol: Collect samples every 30 minutes. This yields 13 samples and provides the most accurate curve definition [8].
  • Cost-Effective Protocol: Collect samples every 60 minutes. This yields 7 samples and has been validated to provide DLMO estimates within ±1 hour of the 30-minute protocol when using a fixed threshold [6].
• Sample Handling: Collect at least 0.5 mL of saliva per sample using the passive drool method. Samples should be stored immediately at ≤ -20°C until assayed. Transport to the testing laboratory should be done on dry ice to maintain sample integrity [8].
• Hormone Assay: Use a high-sensitivity, salivary melatonin immunoassay (ELISA) or the gold-standard LC-MS/MS [12]. The assay must have sufficient sensitivity to reliably detect concentrations at and below the 3 pg/mL threshold, as low concentrations are critical for accurate DLMO determination [8] [12].

Data Analysis and DLMO Calculation

• Data Preparation: Plot the measured melatonin concentration against the sample collection time for each participant.
• Application of Fixed Threshold: The DLMO is the interpolated time at which the rising melatonin concentration curve crosses the pre-defined fixed threshold.
  • The most common fixed thresholds for salivary melatonin are 3 pg/mL and 4 pg/mL [12] [6].
• Interpretation: The calculated DLMO time represents the onset of the biological night. In healthy adults, this typically occurs 2-3 hours before sleep onset [12].

Essential Research Reagent Solutions

Table 2: Key Materials and Reagents for DLMO Assessment

Item	Function/Description	Example Specification / Note
Salivary Melatonin Assay Kit	For quantitative measurement of melatonin concentration in saliva.	Salimetrics Melatonin ELISA: Sensitivity of 1.35 pg/mL, range 0.78–50 pg/mL. No extraction needed [8].
LC-MS/MS Platform	Gold-standard method for hormone quantification; offers superior specificity and sensitivity.	Allows for simultaneous analysis of cortisol and other biomarkers [12].
Saliva Collection Aid	Facilitates hygienic and efficient sample collection.	Passive drool kits (tubes, straws). Polystyrene cryogenic vials are suitable [8].
Dim Light Environment	A controlled space where light intensity is maintained below a critical level to prevent melatonin suppression.	< 20 lux, verified with a calibrated lux meter [6].
Low-Lux Lux Meter	To accurately measure and monitor ambient light intensity at participant's eye level.	Essential for protocol compliance and data validity [6].
Ultra-Low Temperature Freezer	For stable, long-term storage of saliva samples prior to analysis.	Should maintain ≤ -20°C [8].

Critical Discussion in the Context of Threshold Methodology

The choice between fixed and variable thresholds has significant implications for research and clinical practice. The primary advantage of the fixed threshold method is its simplicity and ease of standardization, making it a pragmatic choice for multi-site trials or clinics [11]. However, its major weakness is handling inter-individual variability. For example, a "low melatonin producer" may never reach a 4 pg/mL threshold, leading to a missed DLMO and an inability to assess circadian phase [8] [12]. Conversely, an individual with high baseline melatonin levels may cross a fixed threshold earlier than the true physiological onset, resulting in a phase advance error.

The variable threshold ("3k") method was developed to address this by tailoring the threshold to each individual's baseline. Salimetrics recommends this method for including low producers and for cases where daytime levels are above the standard fixed threshold [8]. A comparative study found that the variable method typically produces DLMO estimates that are 22–24 minutes earlier than a fixed 3 pg/mL threshold and may be closer to the physiological onset in a majority of cases [12]. Nevertheless, this method can be unstable if the baseline samples are too few or show a steep incline [12].

Recent evidence suggests that the "hockey stick" algorithm may offer a superior balance of objectivity and reliability. A 2023 comparison of four methods found that the hockey stick method showed equivalent or better performance than dynamic and fixed thresholds, with excellent agreement with visual estimation by chronobiologists (mean difference: 5 minutes) and high repeatability [11]. This positions it as a promising candidate for a future standardized approach.

Table 3: Impact of Sampling Protocol on Fixed Threshold DLMO

Protocol Factor	Impact on Fixed Threshold DLMO	Recommendation
Sampling Rate (30-min vs. 60-min)	In a 6-hour window, 60-min sampling can produce DLMOs within ±1 hour of 30-min sampling when using a fixed threshold [6].	For a cost-effective protocol in healthy populations, 60-min sampling is acceptable. For clinical populations or high precision, use 30-min sampling.
Sampling Window Timing	A window set 5 hours before to 1 hour after habitual bedtime is generally effective. Severely phase-shifted individuals may require an extended window [8].	Set the window based on habitual sleep times, not arbitrary clock times [6].
Assay Sensitivity	An insensitive assay will fail to accurately measure concentrations near the critical threshold, invalidating the fixed threshold method.	Use an assay with sensitivity well below the chosen threshold (e.g., sensitivity < 1.5 pg/mL for a 3 pg/mL threshold) [8] [12].

The fixed threshold method for determining DLMO provides a straightforward and standardized protocol that is suitable for many research and clinical scenarios, particularly in healthy populations with normal melatonin production. Its successful application is contingent upon a rigorous sampling protocol in dim light, a well-timed sampling window, and a highly sensitive melatonin assay. Researchers and clinicians must be aware of its limitation in handling low melatonin producers. The ongoing methodological research, including the development of robust algorithms like the "hockey stick" method, continues to refine best practices for circadian phase assessment, pushing the field toward more objective and reliable measurement standards.

Step-by-Step Guide to Variable Threshold Calculation (Mean + 2SD)

The accurate determination of circadian phase is a cornerstone of chronobiological research, particularly in the study of sleep disorders and the timing of therapeutic interventions. The dim light melatonin onset (DLMO) is the gold-standard marker for assessing the timing of the central circadian clock in humans [1]. A critical step in establishing DLMO is setting a threshold to pinpoint the time at which melatonin concentration reliably rises in the evening. This process distinguishes between two primary methodologies: the fixed threshold method and the variable threshold method.

The fixed threshold method uses a pre-defined concentration (e.g., 3 or 4 pg/mL in saliva) to identify DLMO. While simple, this approach carries a significant risk of misclassifying individuals who are naturally low melatonin producers, a common occurrence in aging populations or certain patient groups [8]. In contrast, the variable threshold method, often referred to as the "3k method" or the mean + 2 standard deviations (SD) method, calculates a personalized threshold based on an individual's own baseline melatonin levels. This method is recommended for its ability to provide a more accurate and reliable DLMO estimation across a wider range of secretory profiles [8] [14].

This guide provides a detailed protocol for implementing the variable threshold calculation, supporting robust and reproducible circadian phase assessment in research and clinical drug development.

Theoretical Foundation: The Variable Threshold (3k) Method

The variable threshold method overcomes the limitations of a one-size-fits-all fixed value by deriving a threshold that is specific to an individual's low daytime melatonin baseline. The core principle involves calculating a threshold that is two standard deviations above the mean of an individual's initial, low-concentration daytime samples.

This method, as cited in Salimetrics' application notes, was developed by Voultsios et al. (1997) and subsequently validated by Molina and Burgess (2011) [8]. It establishes a threshold based on the mean of the first three low daytime samples, with the threshold set at 2 Standard Deviations above this mean. The "3k" name reflects this use of three baseline points [8]. The key advantage is that it automatically adjusts for an individual's baseline secretion level, effectively handling both low secretors and individuals whose daytime levels may already be above a fixed threshold [8].

Table: Comparison of Fixed vs. Variable Threshold Methods for DLMO Calculation

Feature	Fixed Threshold Method	Variable Threshold (Mean + 2SD) Method
Principle	Uses a universal concentration (e.g., 3 or 4 pg/mL)	Uses a threshold based on individual's baseline mean + 2SD
Handling of Low Secretors	Poor; may miss DLMO if threshold is not reached	Excellent; threshold scales to the individual's baseline
Standardization	High across labs using the same fixed value	High, as the calculation rule is standardized
Recommended Use	Populations with consistent, normal melatonin secretion	General use, particularly in populations with varied secretion (e.g., aging, obesity)
Key Reference	Common in earlier literature	Voultsios et al. (1997); Molina and Burgess (2011) [8]

Step-by-Step Variable Threshold Calculation Protocol

Sample Collection and Data Acquisition

Protocol: Dim Light Melatonin Onset (DLMO) Assessment

• Participant Preparation: Instruct participants to avoid bright light for the duration of the sample collection. Samples must be collected under dim light conditions (< 50 lux) to prevent light-induced melatonin suppression [8] [14].
• Sampling Schedule: Collect saliva samples hourly, beginning 5 hours before habitual bedtime and continuing until at least 1 hour after habitual bedtime. This typically results in a 7-point collection protocol [8].
  • For higher precision, a 13-point collection (samples every 30 minutes) can be used, though the difference in DLMO estimation is often not significant [8].
• Sample Handling: Use a passive drool technique or similar. A volume of 0.5 mL is generally sufficient for duplicate melatonin assays. Store samples at -20°C or colder until analysis [8].
• Melatonin Assay: Analyze samples using a highly sensitive and specific salivary melatonin immunoassay (e.g., Salimetrics Melatonin ELISA). Assay specifications should include:
  • Sensitivity: < 2.0 pg/mL
  • Assay Range: Sufficient to cover expected nighttime rise (e.g., 0.78 – 50 pg/mL)
  • Samples are typically run in duplicate to ensure reproducibility [8].

Calculation of the Variable Threshold

Follow these steps to calculate the DLMO using the variable threshold method.

Step 1: Identify Baseline Samples Select the first three low-concentration samples from the time series. These are typically the first three samples collected 5, 4, and 3 hours before bedtime.

Step 2: Calculate the Baseline Mean (µ) Calculate the arithmetic mean of these three baseline samples. Formula: µ = (S₁ + S₂ + S₃) / 3 Where S₁, S₂, S₃ are the melatonin concentrations of the first three samples.

Step 3: Calculate the Baseline Standard Deviation (SD) Calculate the standard deviation of the same three baseline samples. Formula: SD = √[ ( (S₁ - µ)² + (S₂ - µ)² + (S₃ - µ)² ) / (3 - 1) ] Note: The denominator is (n-1) for a sample standard deviation.

Step 4: Determine the Individualized Threshold Set the threshold at two standard deviations above the baseline mean. Formula: Threshold = µ + 2SD

Step 5: Identify DLMO Plot all melatonin concentration values against their collection times. The DLMO is defined as the first time point at which the melatonin concentration crosses and remains above the individualized threshold for at least two consecutive samples [8]. Linear interpolation between time points can be used for greater precision.

Diagram 1: Workflow for variable threshold DLMO calculation.

Essential Reagents and Materials

A successful DLMO assessment requires the following key materials:

Table: Research Reagent Solutions for DLMO Assessment

Item	Function / Specification	Example / Note
Salivary Melatonin Assay Kit	Quantifies melatonin concentration in saliva. Must be sensitive and validated for saliva.	Salimetrics Melatonin ELISA (Sensitivity: 1.35 pg/mL) [8]
Dim Light Melatonin Onset (DLMO) Kit	All-inclusive kit for at-home or in-clinic sample collection.	Salimetrics At-Home DLMO Kit [8]
Saliva Collection Aid	Enables non-invasive, standardized saliva collection.	Passive drool kit, swabs (e.g., Salimetrics Oral Swab)
Light Meter	Verifies dim light conditions (< 50 lux) to prevent melatonin suppression.	Critical for protocol validity [8] [14]
High-Quality Laboratory	Provides accurate and reproducible assay results.	Should follow CLIA, GLP, or NIH rigor standards [8]

Application in Research and Drug Development

The variable threshold method is particularly vital in clinical trials and research involving populations with known variations in melatonin secretion. For instance, a 2025 study demonstrated the high feasibility of home-based DLMO assessment in individuals with obesity, where the variable threshold method successfully detected DLMO in 98.2% of participants, compared to only 89.6% when a standardized threshold was used [14]. This highlights the method's utility in ensuring data integrity in diverse cohorts.

Furthermore, DLMO serves as a critical reference point for chronotherapy—the timing of treatments to align with the body's circadian rhythms to maximize efficacy and minimize adverse effects [22] [23]. In drug development, using an accurately determined DLMO allows researchers to define optimal dosing schedules for circadian-modulated drugs, such as those used in cancer therapy [23]. The reliability of the variable threshold method makes it an indispensable tool for defining circadian phenotypes in studies investigating the links between circadian timing, disease, and therapeutic response.

Diagram 2: Research and clinical applications of variable threshold DLMO.

Dim Light Melatonin Onset (DLMO) is established as the most reliable circadian phase marker in humans, serving as a critical metric for diagnosing Circadian Rhythm Sleep-Wake Disorders (CRSDs) and determining the optimal timing of chronotherapies [8] [11]. As a master regulator of circadian rhythm, the neurohormone melatonin provides a biological basis for assessing circadian phase shifts that can result in poor concentration, diminished cognitive performance, and broader health concerns [8]. Accurate DLMO assessment is therefore paramount for both clinical and research applications, with sampling strategy forming a foundational methodological choice influencing data quality, reliability, and cost.

The core challenge in DLMO estimation lies in capturing the precise time at which endogenous melatonin concentration begins its nocturnal rise under dim light conditions. This process inherently involves a trade-off between sampling density (which impacts precision and participant burden) and practical constraints (including cost, compliance, and laboratory resources). This analysis directly addresses these trade-offs within the specific context of research comparing fixed versus variable threshold calculation methods, providing structured protocols and quantitative comparisons to guide researcher decision-making.

DLMO Calculation Methods: Fixed vs. Variable Threshold

The methodological framework for determining DLMO centers on two primary approaches, each with distinct advantages and limitations that can interact with the chosen sampling interval.

Fixed Threshold Method

The fixed threshold method establishes a single, pre-defined melatonin concentration value (typically 3 or 4 pg/mL for saliva) as the DLMO marker [8] [11]. The DLMO time is identified as the point when the rising melatonin curve crosses this threshold. The primary advantage of this method is its operational simplicity and straightforward interpretation. However, a significant limitation is its failure to account for individual differences in basal melatonin levels, potentially missing DLMO entirely in low melatonin producers (a common issue in aging populations) or misidentifying it in individuals with high daytime baselines [8].

Variable Threshold Method

In contrast, the variable threshold method (often referred to as the "3k method" or "dynamic threshold") individualizes the threshold for each subject [8]. This method calculates the mean and standard deviation of the first three low daytime melatonin samples, setting the threshold at 2 Standard Deviations above this personal mean. This approach accommodates both low secretors and individuals with elevated baseline levels, enhancing its robustness across diverse populations [8]. Recent comparative studies have also highlighted the "hockey stick" method, an objective algorithm showing superior reliability and agreement with expert visual estimation compared to threshold-based methods [11].

The choice between fixed and variable thresholds can be influenced by sampling density. Hourly sampling may provide insufficient resolution for the variable threshold method in individuals with a rapid onset, whereas half-hourly sampling offers a denser data curve for more precise inflection point identification.

Experimental Protocols for DLMO Assessment

Core Saliva Collection Protocol

Salivary melatonin measurement is the preferred method for modern DLMO profiles due to its non-invasive nature, which allows for frequent sampling without disrupting sleep or requiring cannulation [8]. This promotes higher participant compliance and enables home-based collection, significantly expanding research feasibility and reducing costs.

• Sample Collection Medium: Passive drool into appropriate tubes.
• Sample Volume: 0.5 mL is typically more than sufficient for duplicate melatonin assays [8].
• Light Conditions: Sampling must occur under dim light conditions (< 8 lux) to prevent melatonin suppression [11].
• Timing Relative to Bedtime: Sampling should encompass the period beginning 5 hours before habitual bedtime and extending through one hour past bedtime [8].

Protocol A: Hourly Sampling (7-point)

This protocol is designed for broader studies where participant burden and cost are primary considerations.

• Procedure:
  • Collect saliva samples every hour, starting 5 hours before the individual's reported habitual bedtime.
  • Continue collection until one hour after habitual bedtime, resulting in a total of 7 samples per participant.
  • Immediately freeze samples after collection unless being assayed immediately.
• Suitability: The scientific literature confirms that this 7-point collection provides a reliable DLMO estimation for most research purposes and is the generally recommended starting point [8].

Protocol B: Half-Hourly Sampling (13-point)

This intensive protocol is recommended for clinical applications or research requiring maximum precision, particularly in populations with known or suspected severe phase shifts.

• Procedure:
  • Collect saliva samples every 30 minutes, starting 5 hours before habitual bedtime.
  • Continue collection until one hour after habitual bedtime, resulting in a total of 13 samples per participant.
  • Maintain strict dim light conditions throughout the extended collection period.
• Suitability: While this method offers higher temporal resolution, the difference in DLMO estimation between half-hourly and hourly sampling is often not statistically significant in most study contexts, though the increased cost and participant burden are substantial [8].

Quantitative Comparison: Hourly vs. Half-Hourly Sampling

The choice between sampling intervals involves a direct trade-off between data resolution and practical research constraints. The following table summarizes the key quantitative and qualitative differences.

Table 1: Cost-Benefit Analysis of Sampling Intervals for DLMO Studies

Factor	Hourly Sampling (7-point)	Half-Hourly Sampling (13-point)
Total Samples per Session	7	13
Temporal Resolution	60 minutes	30 minutes
Assay Cost (Relative)	Base Cost (1x)	~1.86x Base Cost
Participant Burden	Lower	Higher
Risk of Missing Onset	Moderate	Low
Recommended Context	Large-scale studies, exploratory research, low-budget projects	Clinical diagnosis, phase-response curve mapping, severely phase-shifted individuals
Data Fidelity	Sufficient for most research questions [8]	Enhanced; potentially critical for variable threshold in rapid-onset cases

The Scientist's Toolkit: Essential Research Reagents and Materials

Accurate DLMO assessment requires specific laboratory materials and assays designed for high-sensitivity melatonin detection.

Table 2: Essential Research Reagents and Materials for Salivary Melatonin Analysis

Item	Function/Description	Specification Example
Salivary Melatonin Assay Kit	Quantifies melatonin concentration in saliva samples.	Competitive ELISA (colorimetric); Sensitivity: <1.35 pg/mL; Range: 0.78-50 pg/mL; No extraction needed [8].
Passive Drool Collection Tubes	Non-invasive saliva collection.	Sufficient for collecting 0.5 mL volumes.
Dim Red Light Source	Maintains dim light conditions (<8 lux) during sample collection to prevent melatonin suppression.	< 8 lux intensity [11].
-20°C Freezer	For sample storage until analysis.	N/A
High-Quality Laboratory	Conducts assays adhering to standards for rigor and reproducibility.	Follows NIH rigor standards or CLIA/GLP regulations [8].

Integrated Workflow for DLMO Study Design and Execution

The following diagram illustrates the logical decision pathway and experimental workflow for designing and executing a DLMO study, from initial design choices to final calculation.

DLMO Study Workflow

The selection between hourly and half-hourly sampling intervals, combined with the choice of a fixed or variable DLMO calculation threshold, should be a deliberate decision based on study objectives, population characteristics, and resource availability.

For large-scale research and studies where statistical power and participant recruitment are prioritized, the hourly sampling (7-point) protocol combined with the variable threshold (3k) method offers a robust and cost-effective balance, providing reliable DLMO estimation for most group-level analyses [8]. This combination effectively controls for individual baseline differences without the prohibitive cost of half-hourly assays.

For clinical diagnostics, phase-response curve studies, or investigations involving populations with known severe phase shifts (e.g., totally blind individuals with Non-24-Hour Sleep-Wake Disorder), the half-hourly sampling (13-point) protocol is justified [8]. The increased resolution ensures that rapid onsets are accurately captured, which is critical for individual-level diagnosis and intervention timing. In these contexts, pairing intensive sampling with the more robust variable threshold or hockey stick method provides the highest level of accuracy and reliability, minimizing the risk of mischaracterizing a patient's circadian phase [11].

Ultimately, the interaction between sampling density and calculation method underscores the importance of aligning methodological rigor with specific research goals to optimize the validity, generalizability, and cost-efficiency of circadian research.

The selection of an appropriate analytical platform is a critical determinant of success in biological research and drug development. This application note provides a systematic comparison of immunoassay and liquid chromatography-tandem mass spectrometry (LC-MS/MS) platforms, with a specific focus on analytical sensitivity. Framed within methodological research on Dim Light Melatonin Onset (DLMO) calculation—contrasting fixed versus variable thresholds—this document delineates the operational parameters, capabilities, and limitations of each technology. Data presented herein demonstrate that while modern immunoassays offer robust, high-throughput capabilities, LC-MS/MS generally provides superior specificity and sensitivity for small molecules, albeit with greater operational complexity. These comparisons offer a foundational guide for scientists selecting platforms for the quantification of biomarkers, pharmaceuticals, and endogenous compounds.

In biomedical research and clinical chemistry, the accurate quantification of analytes is paramount. For decades, immunoassays have been the cornerstone technique for detecting proteins, hormones, and drugs due to their efficiency, adaptability, and established credibility [24]. However, techniques such as liquid chromatography-tandem mass spectrometry (LC-MS/MS) are increasingly adopted for applications demanding higher specificity and sensitivity, such as the precise measurement of low-abundance metabolites and the discrimination of structurally similar compounds [25]. The choice between these platforms directly impacts the reliability of experimental data, influencing downstream interpretations and conclusions.

This technical evaluation is contextualized within ongoing research investigating the optimal method for calculating the Dim Light Melatonin Onset (DLMO), a crucial circadian phase marker. The core methodological debate centers on using a fixed threshold (e.g., 3 or 4 pg/mL for salivary melatonin) versus a variable threshold (e.g., the "3k method," which is calculated as the mean plus two standard deviations of an individual's baseline daytime melatonin levels) [5] [8]. The variable threshold method accounts for individual differences in baseline secretion, potentially offering a more personalized and accurate phase marker, particularly for low melatonin producers [8]. The analytical platform's sensitivity and specificity are intrinsically linked to the validity of this threshold determination, making the comparison between immunoassays and LC-MS/MS not merely technical but fundamentally methodological.

Platform Comparison: Immunoassays vs. LC-MS/MS

Immunoassays are biochemical methods that rely on the specific binding between an antibody and its target analyte. The resulting signal, which can be colorimetric, fluorescent, or chemiluminescent, is measured and compared to a standard curve for quantification [24]. Common formats include:

• Enzyme-Linked Immunosorbent Assay (ELISA): Often configured as a sandwich assay, it uses two antibodies for high specificity and is widely used for protein quantification [24].
• Chemiluminescence Immunoassays (CLIA): Utilize light-emitting reactions for detection, offering enhanced sensitivity [26].
• Electrochemiluminescence (e.g., MSD): Employ electrodes to induce a signal, providing a very wide dynamic range and low background [24].

In contrast, LC-MS/MS is a physicochemical technique that separates compounds in a sample via liquid chromatography and then identifies and quantifies them based on their mass-to-charge ratio in a tandem mass spectrometer. This two-stage mass analysis provides a high degree of specificity [25].

The workflow for both techniques, from sample to answer, is fundamentally different, as summarized below.

Quantitative Performance Data

Sensitivity and specificity are key differentiators between these platforms. The following table summarizes comparative performance data for various analytes, highlighting the consistent trend of LC-MS/MS offering superior specificity and often greater sensitivity.

Table 1: Analytical Performance Comparison of Immunoassays vs. LC-MS/MS

Analyte	Platform / Assay	Reported Sensitivity	Key Performance Findings	Source
Urinary Free Cortisol	Four New Immunoassays (Autobio, Mindray, Snibe, Roche)	Not Specified	Strong correlation with LC-MS/MS (Spearman r=0.950-0.998), but with a consistent positive bias.	[26]
	LC-MS/MS (Reference)	Not Specified	Used as the reference method for its higher specificity.	[26]
Benzodiazepines in Urine	Immunoassay (ARK HS)	Varies by cut-off	Sensitivity >0.90; high cross-reactivity for lorazepam and 7-aminoclonazepam.	[27]
	LC-MS/MS (Multi-analyte)	Varies by compound	Gold standard for confirming 25 traditional and designer benzodiazepines.	[27]
General Low MW Analytes	Immunoassays (Chemiluminescence)	10–100 pg/mL	Susceptible to cross-reactivity from structurally similar molecules.	[25]
	LC-MS/MS	1–10 pg/mL	Superior analytical sensitivity and specificity for most small molecules.	[25]
Salivary Melatonin	Salimetrics Immunoassay	1.35 pg/mL	Sufficient for DLMO calculation using fixed (e.g., 3-4 pg/mL) or variable thresholds.	[8]

The data in Table 1 illustrate a common theme: while modern immunoassays show strong correlation with LC-MS/MS, they can suffer from proportional bias and cross-reactivity [26] [25]. For example, a 2025 study on urinary free cortisol found all four evaluated immunoassays exhibited a positive bias compared to LC-MS/MS, despite strong correlations [26]. The superior specificity of LC-MS/MS is attributed to its reliance on physical-chemical properties (mass and chromatographic retention) rather than immunological recognition, which can be affected by cross-reacting antibodies [27] [25].

Advantages and Limitations

The choice between platforms involves balancing multiple operational factors.

Table 2: Comparative Advantages and Limitations of Each Platform

Factor	Immunoassays	LC-MS/MS
Throughput	High, amenable to full automation [24].	Lower, but can be multiplexed [24].
Cost	Lower initial instrument cost; higher reagent cost [24].	High initial capital investment; lower reagent cost per test [25].
Ease of Use	Relatively simple protocols; readily transferable [24].	High technical expertise required for operation and maintenance [25].
Multiplexing	Possible with technologies like Luminex and MSD [24].	Inherently multiplexable; can monitor hundreds of analytes simultaneously [24].
Specificity	Subject to cross-reactivity from homologous proteins or metabolites [24] [27].	High specificity due to separation by mass and charge [25].
Reagent Development	Requires production of high-affinity antibodies, which can be time-consuming [24].	Requires optimization of chromatography and mass spectrometry parameters [25].
Regulatory Status	Many FDA/CE-marked tests available [25].	Fewer approved tests; often lab-developed [25].

Experimental Protocols

Protocol: Determining DLMO Using Salivary Melatonin Immunoassay

This protocol is adapted from established methodologies for circadian phase assessment [5] [8].

I. Sample Collection

• Participant Preparation: Instruct participants to avoid alcohol, non-steroidal anti-inflammatory drugs (NSAIDs), and caffeine for at least 20 hours prior to and during sampling. Avoid toothpaste or mouthwash with red dye or caffeine immediately before sampling [5].
• Lighting Conditions: Conduct sample collection in dim light (<5 lux at eye level) to suppress melatonin production [5] [8].
• Sampling Schedule:
  • Hourly Sampling (Cost-Effective): Collect saliva samples every hour, beginning 5 hours before habitual bedtime and continuing until at least 1 hour after bedtime [8]. This provides a reliable estimate of DLMO [5].
  • Half-Hourly Sampling (High Precision): Collect samples every 30 minutes over the same period for a more precise DLMO determination [5] [8].
• Collection Method: Use appropriate salivettes or passive drool. Centrifuge samples immediately after collection and store the supernatant at -80°C until analysis [5].

II. Melatonin Analysis via Immunoassay

• Assay Selection: Use a sensitive and validated salivary melatonin immunoassay (e.g., Salimetrics Melatonin ELISA, Sensitivity: 1.35 pg/mL) [8].
• Procedure: Follow the manufacturer's instructions. Typically, this involves:
  • Pipetting 100 µL of standards, controls, and samples into appropriate wells.
  • Adding melatonin conjugate and antibody to each well.
  • Incubating the plate (e.g., 3.5 hours total).
  • Washing the plate to remove unbound material.
  • Adding a substrate to generate a colorimetric signal.
  • Stopping the reaction and reading the absorbance.
• Quantification: Interpolate melatonin concentrations for unknown samples from a standard curve run on the same plate [8].

III. DLMO Calculation: Fixed vs. Variable Threshold The analytical sensitivity of the assay directly impacts the choice and reliability of the DLMO threshold method. The decision pathway for this calculation is outlined below.

• Fixed Threshold Method: The DLMO is the point at which the melatonin concentration rises and remains above an absolute threshold (e.g., 3 or 4 pg/mL) for at least two consecutive samples [5]. This method is less variable but may miss the onset in individuals who are low melatonin producers [5] [8].
• Variable Threshold ("3k") Method: Calculate the mean and standard deviation of the first three low daytime melatonin concentrations. The DLMO is the point at which the melatonin concentration crosses and remains above a threshold set at the mean plus two standard deviations [5] [8]. This method accounts for individual baseline differences and is recommended for low secretors [8].

Protocol: LC-MS/MS for Specific Small Molecule Quantification (e.g., Benzodiazepines)

This protocol is based on clinical toxicology applications for multiplexed drug detection [27].

I. Sample Preparation

• Hydrolysis (if needed): For urine samples, enzymatically hydrolyze with β-glucuronidase (e.g., from E. coli) at 37°C for 12 hours to deconjugate glucuronidated metabolites, which increases detection sensitivity for certain benzodiazepines [27].
• Sample Clean-up: Perform a solid-phase or liquid-liquid extraction to remove matrix interferents and concentrate the analytes.
• Internal Standard Addition: Add a known amount of a stable isotope-labeled internal standard (e.g., cortisol-d4 for cortisol assays) to each sample to correct for variations in sample processing and ionization efficiency [26].

II. Liquid Chromatography (LC)

• Column: Use a reverse-phase C8 or C18 column (e.g., ACQUITY UPLC BEH C8, 2.1 x 100 mm, 1.7 µm) [26].
• Mobile Phase: Employ a binary gradient, typically water (mobile phase A) and methanol or acetonitrile (mobile phase B).
• Separation: Inject a processed sample aliquot (e.g., 10 µL) and elute the analytes using a gradient that increases the organic solvent proportion over time, separating compounds based on hydrophobicity [26].

III. Tandem Mass Spectrometry (MS/MS)

• Ionization: The LC eluent is ionized using electrospray ionization (ESI) in positive or negative mode.
• Mass Filtering (Q1): The first quadrupole (Q1) selects ions with the specific mass-to-charge ratio (m/z) of the target analyte (precursor ion).
• Fragmentation (Q2): The selected ions are passed into a collision cell (Q2) and fragmented using an inert gas (e.g., argon) into product ions.
• Detection (Q3): The second quadrupole (Q3) filters one or more characteristic product ions.
• Data Acquisition: Operate the mass spectrometer in Multiple Reaction Monitoring (MRM) mode for high sensitivity and specificity. For example, cortisol can be detected by monitoring the transition 363.2 → 121.0 [26].

The Scientist's Toolkit: Essential Research Reagents and Materials

Table 3: Key Reagents and Materials for Immunoassay and LC-MS/MS workflows

Item	Function	Example / Specification
High-Affinity Antibodies	Critical reagent for immunoassays; binds specifically to the target analyte.	Monoclonal or polyclonal antibodies with low cross-reactivity; lot-to-lot consistency is crucial [24].
Purified Protein Standard	Used to generate the calibration curve for quantitative immunoassays.	Isolated from trait-specific tissue or heterologously expressed; must be characterized and pure [24].
Stable Isotope-Labeled Internal Standard	Added to samples in LC-MS/MS to correct for matrix effects and recovery variations.	e.g., Cortisol-d4; identical chemical behavior to the analyte but distinguishable by mass [26] [25].
LC-MS/MS Calibrators & Controls	Used to establish the quantitative calibration curve and ensure assay accuracy.	Should be traceable to reference materials; prepared in a matrix similar to the sample [25].
Solid-Phase Extraction (SPE) Plates	For rapid sample clean-up and concentration prior to LC-MS/MS analysis.	Various chemistries (C18, mixed-mode) to selectively bind analytes of interest [27].
Saliva Collection Device	Non-invasive sample collection for hormones like melatonin and cortisol.	Salivettes or passive drool kits; must be non-interfering with the assay [5] [8].
β-Glucuronidase Enzyme	Hydrolyzes glucuronide conjugates in urine/serum to free the parent drug or metabolite.	From E. coli; used to increase detection sensitivity for conjugated benzodiazepines [27].

The comparative analysis presented in this application note underscores that there is no universally superior analytical platform. The decision between immunoassay and LC-MS/MS is contingent on the specific research requirements, including the required level of sensitivity and specificity, throughput needs, available budget, and technical expertise. Within the context of DLMO research, highly sensitive immunoassays are generally sufficient and more practical for large-scale studies. However, LC-MS/MS may be warranted for verifying assay specificity, resolving discrepancies, or investigating low-level metabolites. Ultimately, a clear understanding of the capabilities and limitations of each platform, as detailed herein, empowers researchers to make informed decisions that ensure the integrity and reliability of their scientific data.

Within circadian biology and clinical sleep research, the Dim Light Melatonin Onset (DLMO) serves as the gold-standard marker for assessing an individual's endogenous circadian phase [11]. Accurate determination of DLMO is critical for diagnosing Circadian Rhythm Sleep-Wake Disorders and for timing chronotherapies. However, traditional DLMO assessment protocols are methodologically heterogeneous and resource-intensive, typically requiring sample collection over many hours under controlled dim-light conditions, which limits their practical application in large-scale studies and clinical trials [28]. This creates a significant methodological tension between the fixed threshold approach, which applies a universal melatonin concentration cutoff, and variable threshold methods, which calculate a threshold based on individual melatonin profiles [11].

The central challenge lies in defining a sampling window that is both efficient and capable of capturing the DLMO with high fidelity, regardless of the calculation method employed. This protocol proposes a standardized framework for a targeted 5-hour sampling window, designed for application within a broader research thesis comparing fixed versus variable threshold DLMO calculations. By integrating wearable device data and mathematical modeling, this approach aims to enhance protocol efficiency while maintaining scientific rigor for researcher and drug development applications.

Background and Scientific Rationale

DLMO as a Circadian Phase Marker

Melatonin secretion from the pineal gland is a robust endogenous rhythm, tightly controlled by the suprachiasmatic nucleus. DLMO marks the point in the evening when melatonin concentrations begin to rise, signaling the onset of the biological night. Its primacy as a phase marker stems from its relative immunity to manipulation by non-photic stimuli, unlike other markers such as core body temperature. Precise DLMO calculation is therefore foundational to circadian medicine, which seeks to optimize treatment timing based on individual biological time [28].

The Threshold Calculation Debate

The methodological debate between fixed and variable threshold calculations centers on reliability, objectivity, and inter-individual variability.

• Fixed Threshold Method: This approach defines DLMO as the time when melatonin concentration crosses a pre-defined absolute value (e.g., 3 pg/mL or 10 pg/mL). While simple and objective, its major limitation is its failure to account for differences in overall melatonin amplitude between individuals. A one-size-fits-all threshold may miss the true onset in individuals with low-amplitude rhythms or lead to premature calls in those with high baseline levels.

• Variable Threshold Methods: These include the dynamic threshold (often a percentage of the peak amplitude) and the hockey stick method, which uses segmented regression to identify the breakpoint in the concentration curve [11]. These methods are theoretically more attuned to individual physiology but can be more complex to calculate and may be influenced by sampling duration and noise.

A recent repeatability and agreement study by Glacet et al. (2023) compared these methods and found the hockey stick method demonstrated "equivalent or superior performance" with a mean difference of just 5 minutes compared to visual estimation by experts, suggesting it may provide the most reliable DLMO estimate [11]. The development of a shortened sampling protocol must be robust enough to accommodate these different analytical techniques.

Proposed 5-Hour Targeted Sampling Protocol

The following protocol outlines a novel, efficient method for DLMO assessment, validated for use in shift workers—a population with notoriously hard-to-capture circadian rhythms [28].

Principle

This protocol reduces the traditional >8-hour DLMO sampling window to a targeted 5-hour window by leveraging actigraphy data from wearable devices and a mathematical model to prospectively predict the individual's DLMO. The sampling window is precisely defined as the period from 3 hours before the predicted DLMO to 2 hours after the predicted DLMO [28].

Materials and Equipment

Table 1: Essential Research Reagents and Equipment

Item	Specification/Function
Salivary Melatonin Collection Kits	Including low-binding tubes for sample collection.
Dim Red Light Source	Light wavelength >600 nm to prevent melatonin suppression.
Centrifuge	For processing saliva samples.
Freezer (-20°C or lower)	For sample storage prior to analysis.
Melatonin Assay	Validated immunoassay (ELISA or RIA) for quantifying salivary melatonin.
Wearable Actigraphs	Devices to collect continuous sleep-wake pattern data (e.g., motion, light exposure).
Data Analysis Software	Capable of running the mathematical model for DLMO prediction and performing the chosen threshold calculation (fixed, dynamic, or hockey stick).

Experimental Workflow

The following diagram illustrates the end-to-end workflow for the targeted DLMO sampling protocol, integrating both data collection and analysis phases.

Step-by-Step Procedure

• Actigraphy Data Collection (Pre-Study):

  • Participants wear a validated activity monitor on the non-dominant wrist for a minimum of 7-14 days under free-living conditions to establish habitual sleep-wake patterns.

• DLMO Prediction and Window Definition:

  • Process actigraphy data using a validated mathematical model to prospectively predict the individual's DLMO time.
  • Calculate the targeted 5-hour sampling window as: Start Time = Predicted DLMO - 3 hours; End Time = Predicted DLMO + 2 hours.

• Pre-Sampling Controls:

  • Participants must avoid caffeine, alcohol, and heavy physical activity for a defined period (e.g., 8-12 hours) prior to sampling.
  • Ensure the sampling environment is in dim light (< 8 lux) for at least one hour before the first sample and throughout the entire collection period [11]. Verify light levels at eye level.

• Saliva Sample Collection:

  • Begin collection at the calculated "Start Time."
  • Collect saliva samples at regular intervals (every 30 minutes) throughout the 5-hour window.
  • Follow standard salivary collection procedures: participants should not eat or drink (except water) 10 minutes before each sample. Samples are centrifuged and frozen at -20°C or lower until assay.

• Melatonin Assay and DLMO Calculation:

  • Quantify melatonin concentrations in all samples using a validated assay.
  • Calculate the final DLMO using one or more of the following methods, as required by the research question:
    • Fixed Threshold: The interpolated time when melatonin concentration crosses a pre-set absolute value (e.g., 3 pg/mL or 10 pg/mL).
    • Variable Threshold (Dynamic): The interpolated time when melatonin concentration crosses a threshold defined as a percentage (e.g., 2 standard deviations) above the average of the first few baseline samples.
    • Hockey Stick Method: The time of the breakpoint identified by segmented regression analysis of the melatonin curve [11].

Data Interpretation and Comparative Analysis

Application of Different Threshold Methods

The shortened protocol is designed to be compatible with the primary methods for DLMO calculation. The targeted window ensures that the critical rising phase of the melatonin rhythm is captured, which is necessary for all analytical techniques.

Table 2: Comparison of DLMO Calculation Methods Within the 5-Hour Protocol

Method	Key Principle	Data Requirements from 5-Hr Window	Advantages	Limitations
Fixed Threshold	Crosses an absolute concentration (e.g., 3 pg/mL).	The rising phase must cross the fixed threshold.	Simple, objective, widely used.	Fails for individuals with low-amplitude rhythms; threshold choice is arbitrary.
Dynamic Threshold	Crosses a value relative to individual baseline (e.g., 2SD above mean).	Requires stable baseline samples at the start of the window.	Accounts for individual baseline variation.	Sensitive to baseline noise; definition of "baseline" can vary.
Hockey Stick	Identifies the breakpoint from baseline to rise via regression.	Captures the curvilinear shape of the rise.	Objective, models the data shape directly, high agreement with expert estimation [11].	Requires specialized software; assumes a two-phase linear model.

Validation and Performance

This 5-hour protocol has been tested in challenging populations. A study by Lim et al. (2025) successfully identified DLMO in 19 shift workers, a cohort where traditional methods failed in over 40% of participants [28]. This demonstrates the protocol's robustness, particularly for individuals with atypical or delayed circadian rhythms. When applying different threshold methods, researchers should note that the hockey stick method has shown excellent repeatability and agreement with visual estimation, making it a strong candidate for reliable DLMO estimation in shortened protocols [11].

Discussion

Protocol Advantages in Research and Drug Development

The primary advantage of this targeted sampling protocol is its dramatic increase in efficiency, reducing laboratory resource use, participant burden, and overall cost. This makes it particularly suitable for large-scale cohort studies [29] and multi-center clinical trials, such as those investigating sleep disturbances in conditions like Post-Acute Sequelae of SARS-CoV-2 Infection (PASC) [30]. Furthermore, by integrating objective actigraphy data, the protocol moves towards a more personalized and precise measurement of circadian phase, aligning with the goals of precision medicine.

Considerations and Troubleshooting

• Model Accuracy: The success of the protocol hinges on the accuracy of the initial DLMO prediction. The mathematical model must be trained and validated on a population similar to the study cohort.
• Handling of Outliers: If the observed melatonin rise occurs near the very beginning or end of the 5-hour window, the sample set may be insufficient for an accurate DLMO calculation, particularly for variable threshold methods. In such cases, the data should be flagged, and the participant may require re-testing with an adjusted window.
• Method Selection: The choice of DLMO calculation method (fixed vs. variable threshold) should be pre-specified in the study protocol. For research directly comparing these methods, it is critical to ensure the 5-hour window captures sufficient data for all intended analyses, particularly a stable baseline for dynamic methods.

Navigating Challenges and Optimizing DLMO Calculation Accuracy

Within circadian biology and sleep medicine, the dim light melatonin onset (DLMO) serves as the gold-standard marker for assessing the timing of the central circadian clock [5] [8]. Accurate DLMO calculation is therefore critical for diagnosing Circadian Rhythm Sleep-Wake Disorders (CRSWDs) and timing light or melatonin therapies [6] [11]. The method used to determine the DLMO from a melatonin profile—specifically, the choice between a fixed or variable threshold—profoundly impacts the result. This application note details the significant pitfalls of using fixed thresholds, which can fail to accurately capture the circadian phase of low melatonin producers, and provides validated protocols for robust DLMO assessment suitable for all patient populations, including these challenging cases.

Pitfalls of Fixed Thresholds in DLMO Calculation

The fixed threshold method defines DLMO as the time when melatonin concentration crosses a predetermined absolute value, commonly 3 pg/mL or 4 pg/mL for saliva [6] [5]. While this method is simple and produces less variable DLMOs in populations with normal melatonin production [5], it has a critical flaw: it does not account for individual differences in baseline melatonin levels or amplitude.

This flaw is most apparent in low melatonin producers, a group that includes a significant portion of the population. An estimated 1–5% of adults have very low melatonin levels with no clear circadian rhythm [31]. Furthermore, melatonin production declines dramatically during childhood and continues to decrease with age [31]. In low producers, the overall melatonin profile may never reach a fixed threshold of 3 or 4 pg/mL, leading to a failed DLMO assessment [8]. Conversely, some individuals may have daytime melatonin levels that already exceed the low fixed threshold, making it impossible to identify a true "onset" [8].

Table 1: Impact of Threshold Method on DLMO Timing and Success Rate

Threshold Method	Definition	Advantages	Disadvantages	Impact on Low Melatonin Producers
Fixed Threshold	Crosses an absolute value (e.g., 3 or 4 pg/mL) [5].	Simple to calculate; less variable in normal producers [5].	Does not individualize for baseline levels; may miss DLMO in low producers [8].	High risk of missing DLMO entirely if peak production is below threshold [8].
Variable Threshold (3k Method)	Mean of first 3 low daytime points + 2 standard deviations [5] [8].	Individualized; accounts for low secretors and high baselines [8].	Requires well-timed low daytime samples; more variable in timing [5].	Enables DLMO estimation by setting a threshold relative to the individual's own baseline [8].

Quantitative Comparison of DLMO Methods

Research consistently shows that the choice of threshold method results in systematically different DLMO estimates, which is a critical consideration for longitudinal studies or clinical trials where consistent timing is paramount.

One study found that DLMOs calculated with the variable 3k method were significantly earlier (by 22–24 minutes) than those calculated with a 3 pg/mL fixed threshold, regardless of whether sampling occurred every 30 or 60 minutes [5]. This demonstrates that the threshold method itself introduces a systematic bias in the phase estimate.

A more recent comparison of four DLMO calculation methods, including fixed and dynamic thresholds as well as the "hockey stick" method, highlighted that the hockey stick method showed equivalent or superior performance in healthy subjects [11]. It demonstrated excellent agreement with visual estimation by experts (mean difference of 5 minutes) and high reliability across nights [11]. While the hockey stick method was identified as highly reliable, the variable threshold remains a well-validated and more accessible method for accommodating low producers.

Table 2: Comparison of DLMO Estimates from Different Methodologies

Study Reference	Sampling Rate	Fixed Threshold (3 pg/mL) Mean DLMO	Variable Threshold (3k) Mean DLMO	Mean Difference (3k - Fixed)
Burgess et al. (2011) [5]	30-minute	21:48 h ± 61 min	21:26 h ± 56 min	-22 min
Burgess et al. (2011) [5]	60-minute	21:42 h ± 63 min	21:18 h ± 51 min	-24 min

Recommended Protocols for Robust DLMO Assessment

Saliva Collection Protocol for DLMO

The following protocol is optimized for reliability and participant compliance, balancing cost and accuracy for both research and clinical settings.

• Preparation: Participants must maintain a fixed sleep schedule for at least 7 days prior to sampling, with compliance verified by actigraphy and sleep diaries [6] [5]. On the day of sampling, avoid NSAIDs, alcohol, nicotine, and caffeine for specified periods before and during collection [5]. Vigorous exercise should also be avoided.
• Sampling Environment: Sample collection must occur in dim light (<20 lux, ideally <5 lux) at the participant's angle of gaze to prevent melatonin suppression [6] [5] [32]. Participants should remain seated, and eating or drinking must be prohibited for 10 minutes before each sample [5].
• Sampling Window and Rate:
  • Window: Begin sampling 5 hours before habitual bedtime and continue until 1 hour after bedtime (a 6-hour window) [6] [8].
  • Rate: Hourly sampling (7 samples) provides a cost-effective and practical estimate that is generally within ±1 hour of the more intensive 30-minute sampling (13 samples), particularly when using an absolute threshold [6]. For higher precision or in research contexts, 30-minute sampling is recommended [8].
• Sample Handling: Use Salivette or passive drool collection devices. Saliva should be centrifuged and frozen immediately after collection [5].

DLMO Calculation: Implementing the Variable Threshold (3k) Method

For reliable estimation of DLMO, especially in low melatonin producers, the variable threshold is the recommended method.

• Establish Baseline: Identify the first three low daytime melatonin concentrations from the profile [5] [8].
• Calculate Threshold: Compute the mean (µ) and standard deviation (SD) of these three points. The DLMO threshold is set at µ + 2SD [5] [8].
• Identify DLMO: The DLMO is the point at which the melatonin concentration crosses and remains above this individualized threshold for at least the next two samples. The exact time is determined by linear interpolation between the point immediately below and the point immediately above the threshold [5].

The Scientist's Toolkit

Table 3: Essential Research Reagents and Materials for Salivary DLMO Assessment

Item	Function/Description	Example/Specification
Saliva Collection Device	Non-invasive sample collection.	Salivettes or passive drool tubes [5].
Dim Light Environment	Prevents suppression of melatonin secretion during sampling.	<20 lux (clinically practical) to <5 lux (research ideal) at angle of gaze [6] [5].
Actigraph	Monitors compliance with fixed sleep schedule prior to sampling.	Wrist-worn device (e.g., Actiwatch) [6] [5].
Melatonin Assay Kit	Quantifies melatonin concentration in saliva.	High-sensitivity ELISA (e.g., Salimetrics kit, sensitivity: 1.35 pg/mL) [8].
Light Meter	Verifies dim light conditions are maintained throughout collection.	Calibrated lux meter.
Freezer (-20°C or -80°C)	Preserves sample integrity post-collection until analysis.	Standard laboratory freezer [5].

The accurate measurement of DLMO is foundational for circadian research and effective clinical management of CRSWDs. Reliance on fixed thresholds poses a significant risk for mischaracterizing the circadian phase of low melatonin producers, including children, older adults, and individuals with pathologically low secretion. Adopting the described protocols—utilizing a 6-hour sampling window with hourly samples and calculating DLMO via the individualized variable threshold (3k) method—ensures a more reliable, inclusive, and biologically valid phase assessment for all populations.

Dim Light Melatonin Onset (DLMO) is a crucial circadian phase marker, serving as the gold standard for diagnosing Circadian Rhythm Sleep-Wake Disorders (CRSWDs) and determining optimal timing for chronotherapies [11]. The accurate calculation of DLMO is therefore fundamental for both clinical and research applications. Methodologies for determining DLMO predominantly fall into two categories: fixed threshold and variable threshold methods. While variable thresholds can offer personalized benchmarks, this application note examines their significant pitfalls, particularly their susceptibility to unstable baselines and insufficient data points, within the broader context of fixed versus variable threshold DLMO calculation research. Establishing clear and validated guidelines for DLMO assessment is critical for diagnostic accuracy and treatment efficacy [11].

Quantitative Comparison of DLMO Threshold Methods

The choice of DLMO calculation method significantly impacts the resulting phase marker. The following table summarizes the core characteristics, advantages, and disadvantages of the primary methods discussed in the literature, highlighting the specific vulnerabilities of variable thresholds.

Table 1: Comparison of DLMO Calculation Methods

Method	Description	Key Advantages	Key Disadvantages & Pitfalls
Fixed Threshold	DLMO is the time at which melatonin concentration crosses a pre-defined absolute value (e.g., 3 pg/mL or 4 pg/mL for saliva) [8] [19].	Simplicity and high inter-study comparability [33].	Fails to account for individual differences in melatonin amplitude; risks missing DLMO in low secretors and is invalid for individuals with high daytime baselines [8].
Variable Threshold (e.g., 3k Method)	Threshold is set relative to an individual's baseline, typically 2 standard deviations above the mean of the first three low daytime samples [8].	Personalized; accommodates both low and high melatonin producers, increasing applicability across diverse populations [8].	Pitfall: Unstable Baselines - Nocturnal melatonin secretion can be influenced by various environmental and behavioral factors [8]. Pitfall: Insufficient Data Points - Relies on a small number of initial samples; an outlier or noisy data point can disproportionately skew the baseline mean and standard deviation, leading to an inaccurate threshold [8].
Hockey Stick Method	A data-driven, model-fitting approach that identifies the point of maximum curvature where melatonin levels begin to rise steeply [11].	Objective nature; superior reliability and agreement with expert visual estimation compared to fixed and dynamic thresholds; does not require a predefined threshold [11].	Computationally more complex than threshold-based methods.

A recent repeatability and agreement study provides quantitative evidence for the performance of these methods. The findings strongly support the use of the hockey stick method as a robust alternative to threshold-based approaches.

Table 2: Performance Comparison of DLMO Methods from Glacet et al. (2023) [11]

Method	Mean Difference with Visual Estimation	Intraclass Correlation Coefficient (ICC) with Visual Estimation	Repeatability Across Nights
Fixed Threshold	Not Specified	Not Specified	Good to Perfect
Dynamic Threshold	Not Specified	Not Specified	Good to Perfect
Hockey Stick	5 minutes	0.95	Good to Perfect

Detailed Experimental Protocols for DLMO Assessment

Protocol for Salivary DLMO Collection

This protocol is adapted from standard methodologies for at-home or in-clinic sample collection, as detailed by Salimetrics and recent research into remote collections [8] [19].

Objective: To collect saliva samples for the accurate determination of Dim Light Melatonin Onset (DLMO).

Materials:

• Salivettes or similar saliva collection aids.
• Cooling Kit: Freezer bag with ice packs or a dedicated freezer for sample storage at ≤ -20°C.
• Dim Light Environment: Prepared room with < 50 lux. Light meters are recommended for verification.
• Light-Blocking Glasses: For participants who must use electronic devices.
• MEMs (Medication Event Monitoring System) Cap: To timestamp each sample collection objectively.
• Salivary Melatonin Assay Kit: A highly sensitive and specific assay, such as a competitive ELISA (e.g., Salimetrics Melatonin Assay, Sensitivity: 1.35 pg/mL) [8].

Procedure:

• Preparation: Participants should avoid alcohol, caffeine, and heavy meals for at least 2 hours before collection. They must not brush their teeth or use mouthwash for at least 1 hour prior. Adherence to dim light conditions (< 50 lux) must begin at least 1 hour before the first sample.
• Sample Collection Timing: Begin collection 5-6 hours before the participant's habitual bedtime and continue until 1-2 hours after bedtime.
• Sampling Schedule (Standard): Collect saliva samples every hour [8]. This yields a 7-8 point profile suitable for multiple calculation methods.
• Sampling Schedule (High Precision): For enhanced DLMO estimation, particularly for research, collect samples every 30 minutes [8]. This yields a 13-14 point profile, which is more robust against the "Insufficient Data Points" pitfall.
• Sample Handling: Immediately after collection, samples should be stored on ice packs and frozen at ≤ -20°C within 24 hours until assayed.

Protocol for DLMO Calculation and Comparison

Objective: To calculate DLMO using different methods and compare the results to evaluate the impact of methodological choice.

Materials:

• Processed salivary melatonin concentration data (in pg/mL) with corresponding clock times.
• Statistical software (e.g., R, Python, GraphPad Prism) capable of nonlinear regression for the hockey stick method.

Procedure:

• Data Preparation: Organize melatonin concentration data against sample collection time.
• Fixed Threshold Calculation:
  • Plot melatonin concentration over time.
  • Identify the time point at which the concentration curve crosses a fixed threshold of 3 pg/mL or 4 pg/mL [8] [33]. This is DLMO_fixed.
• Variable Threshold (3k Method) Calculation:
  • Calculate the mean (M) and standard deviation (SD) of the first three baseline samples (typically the first three time points).
  • Set the variable threshold as M + 2SD.
  • Identify the first time point after which the melatonin concentration consistently remains above this threshold. This is DLMO_variable [8].
• Hockey Stick Method Calculation:
  • Use a software tool to fit a piecewise or nonlinear regression model (e.g., two connecting lines) to the melatonin data.
  • The DLMO_hockey is defined as the breakpoint or the point of maximum curvature in the fitted model, representing the onset of the sustained melatonin rise [11].
• Comparison and Analysis:
  • Compare the DLMO times derived from the three methods (DLMO_fixed, DLMO_variable, DLMO_hockey).
  • Note discrepancies, particularly instances where DLMO_variable is significantly earlier or later than the other measures, which may indicate an unstable baseline.

Visualization of DLMO Calculation Workflows

The following diagrams illustrate the logical workflows for the variable threshold and hockey stick DLMO calculation methods, highlighting where critical pitfalls can occur.

Variable Threshold DLMO calculation workflow and its associated pitfalls.

Hockey Stick DLMO calculation workflow and its advantages.

The Scientist's Toolkit: Essential Research Reagents & Materials

The following table details key materials required for implementing a rigorous DLMO study, particularly one designed to compare calculation methodologies.

Table 3: Essential Research Reagents and Materials for DLMO Studies

Item	Function / Application	Key Considerations
Salivary Melatonin Assay Kit	Quantifies melatonin concentration in saliva samples.	Must be highly sensitive (e.g., detection limit <2 pg/mL) and validated for saliva. ELISA kits are commonly used [8].
Salivettes	Provides a standardized, hygienic system for passive drool collection.	Untreated polyester/polyethylene sleeves are typical. Eases collection and processing [19].
Portable Lux Meter	Objectively verifies adherence to dim-light conditions (< 50 lux) during sample collection.	Critical for protocol compliance and data validity [19].
Actigraphy Watch with Light Sensor	Objectively monitors activity and light exposure for 1-2 weeks before collection.	Helps determine habitual sleep/wake patterns and verifies pre-collection lighting compliance. Data can also be used for DLMO prediction models [19] [33].
MEMs (Medication Event Monitoring System) Caps	Electronically timestamps each sample collection event.	Provides objective compliance data, crucial for validating at-home collection protocols and ensuring accurate timing [19].
Blue Light-Blocking Glasses	Protective measure to prevent accidental light exposure if participants must use screens during collection.	An additional safeguard to maintain dim-light conditions [19].
Statistical Software with Nonlinear Regression	For implementing advanced DLMO calculation methods like the hockey stick.	Software like R or Python is required for fitting the complex models involved in this method [11].

The accurate determination of the Dim Light Melatonin Onset (DLMO) is paramount for assessing an individual's circadian phase in both research and clinical practice. This assessment is typically achieved by applying a threshold to melatonin concentration profiles, with methodologies divided into fixed threshold and variable (or dynamic) threshold approaches [12]. A fixed threshold defines DLMO as the time when melatonin concentration crosses a predetermined absolute value (e.g., 3 or 4 pg/mL in saliva) [12]. In contrast, a variable threshold sets the DLMO relative to an individual's own baseline, often as the time when melatonin levels exceed two standard deviations above the mean of three or more pre-rise samples [12] [18].

The choice between these methods is not merely analytical; it is deeply influenced by physiological and environmental confounding factors that can alter melatonin concentrations and compromise the accuracy of phase estimation. Key among these factors are medication use, body posture, and ambient light exposure. These confounders can introduce significant variability, potentially affecting the reliability of fixed thresholds differently than variable ones. This document outlines detailed protocols to control for these factors, ensuring the collection of high-fidelity data for robust DLMO calculation within circadian rhythm research and drug development.

The Impact of Medications on Melatonin Secretion and Assay Specificity

Various medications can significantly interfere with melatonin physiology, either by suppressing or stimulating its endogenous production, or by causing analytical interference in immunoassays.

Medications as Confounding Factors

The following table categorizes common medications known to affect melatonin levels:

Table 1: Impact of Medications on Melatonin Secretion and Measurement

Medication Class	Specific Examples	Effect on Melatonin	Mechanism of Action	Implications for DLMO
Anti-inflammatory	Non-steroidal anti-inflammatory drugs (NSAIDs)	Suppression [12]	Inhibition of prostaglandin synthesis, which is involved in melatonin production [12]	May delay or blunt the melatonin rise, leading to a later DLMO estimate.
Cardiovascular	Beta-blockers (e.g., propranolol)	Suppression [12] [18]	Beta-adrenergic receptor antagonism, reducing norepinephrine's stimulatory effect on the pineal gland [12]	Can significantly suppress melatonin amplitude, complicating threshold detection.
Antidepressants	Selective Serotonin Reuptake Inhibitors (SSRIs), Monoamine Oxidase Inhibitors (MAOIs)	Artificial Elevation [12]	Modulation of serotonin, a precursor to melatonin [12]	May cause an earlier DLMO estimate; variable thresholds may be more robust.
Hormonal	Oral Contraceptives	Artificial Elevation [12]	Modulation of serotonin, a precursor to melatonin [12]	Can elevate baseline levels, potentially affecting fixed-threshold calculations.
Supplemental	Exogenous Melatonin	Artificial Elevation [12]	Direct addition of melatonin to the bloodstream [12]	Causes direct analytical interference; requires a washout period before testing.

Experimental Protocol: Managing Pharmacological Confounders

Objective: To minimize the impact of medications on DLMO assessment. Materials: Subject medical history forms, LC-MS/MS equipment [12]. Procedure:

• Pre-Study Screening: During participant recruitment, conduct a thorough review of all prescription, over-the-counter, and supplemental medications.
• Washout Period: Where ethically and medically feasible, implement a washout period for confounding medications prior to the study. The duration must be determined in consultation with a physician and based on the drug's half-life. Note: Sudden cessation of medication can be dangerous and must never be done without medical supervision.
• Documentation: Record all medications, including doses and timing, throughout the study period for use as covariates in statistical analysis.
• Analytical Specificity: Use liquid chromatography-tandem mass spectrometry (LC-MS/MS) for melatonin quantification due to its superior specificity and sensitivity compared to immunoassays, thereby reducing the risk of analytical interference from drug metabolites [12].

The Effects of Posture and Physical Activity

Body posture and physical activity influence melatonin concentration by altering its distribution volume and metabolism, primarily through effects on hepatic blood flow [12].

Posture as a Confounding Factor

Transitioning from an upright to a supine position decreases hepatic blood flow, which can reduce the metabolic clearance of melatonin. This leads to an increase in plasma melatonin concentrations without a change in its secretion rate. During DLMO protocols, if a subject is upright and active before sampling and then rests in a supine position, the resulting rise in melatonin levels could be misinterpreted as the physiological onset of secretion.

Experimental Protocol: Standardizing Posture and Activity

Objective: To control for posture-induced changes in melatonin kinetics. Materials: Reclining chairs or beds, low-light environment. Procedure:

• Pre-Sampling Rest: Mandate that participants remain in a supine or semi-recumbent position for a minimum of 15-20 minutes before each saliva or blood sample is collected [12].
• Restricted Activity: During this rest period, prohibit strenuous physical activity. Subjects may engage in quiet, sedentary activities such as listening to audio books or podcasts.
• Consistency: Maintain the standardized rest period before every sample throughout the DLMO assessment to ensure consistent physiological conditions.

The Critical Role of Light Exposure

Light is the primary zeitgeber (time cue) for the human circadian system. Even low levels of light, particularly in the blue spectrum, can potently suppress melatonin secretion and shift the circadian phase.

Light as a Confounding Factor

Exposure to light in the evening, during the DLMO sampling window, can delay the onset of melatonin production or suppress its amplitude. This directly confounds the measurement of the endogenous circadian phase. The "Dim Light" in DLMO is a strict experimental requirement to avoid this suppression.

Experimental Protocol: Controlling Ambient Light

Objective: To ensure melatonin secretion reflects the endogenous circadian pacemaker without suppression from ambient light. Materials: <5 lux light meter (e.g., spectrophotometer), dim red or orange light sources (wavelengths >600 nm), blackout curtains. Procedure:

• Light Level Validation: Prior to and during the study, use a calibrated light meter to confirm that ambient light levels at the participant's eye level are <5 lux [12]. This is typically the intensity of a very dim room.
• Safe Lighting: All lighting in the environment where the participant is located during the sampling period must be dim and long-wavelength (red or orange). These wavelengths have minimal impact on the melanopsin photoreceptors in the retina that mediate circadian phototransduction.
• Subject Guidance: Instruct participants to avoid looking directly at any light source, including dim safety lights. For periods outside the lab, advise them to wear blue-light-blocking glasses and minimize exposure to bright screens (phones, TVs, tablets) during the evening before and during the sampling period.

Integrated Workflow for Controlled DLMO Assessment

The following diagram illustrates the sequential protocol for managing confounders during a DLMO study, from participant preparation to final analysis.

Comparison of Fixed vs. Variable Thresholds in the Context of Confounders

The presence of confounders can differentially impact the two primary methods for DLMO calculation.

Table 2: Impact of Confounders on Fixed vs. Variable DLMO Thresholds

Confounding Factor	Impact on Fixed Threshold	Impact on Variable Threshold	Considerations for Method Selection
Medications (Suppressive)	High impact. May cause DLMO to be missed if rise does not cross the absolute threshold [12].	Moderate impact. Relies on a relative rise from baseline, which may still be detectable even with suppression.	Variable threshold may be more robust for studies involving participants on suppressive medications.
Medications (Elevating)	High impact. Elevated baselines may cause earlier, false DLMO estimate.	Lower impact. The threshold is calculated relative to the individual's own (elevated) baseline.	Variable threshold is preferred when baseline levels are artificially high.
Posture Changes	High impact. A posture-induced rise could be misinterpreted as DLMO.	Moderate impact. The algorithm may partially account for this if baseline is stable.	Strict posture control is critical for both methods.
Light Exposure	Affects both methods equally, as it suppresses the actual physiological secretion of melatonin.		Controlling light is non-negotiable, regardless of the calculation method.

The Scientist's Toolkit: Essential Research Reagents and Materials

Table 3: Key Materials for DLMO Studies

Item	Function/Application	Specification Notes
Salivette Tubes	Collection of saliva samples for hormone analysis.	Inert synthetic swabs are preferred over cotton, which can interfere with some assays.
LC-MS/MS System	Gold-standard quantification of melatonin and cortisol [12].	Provides high specificity and sensitivity, minimizing cross-reactivity.
Calibrated Light Meter	Verification of ambient light conditions.	Must be capable of accurately measuring low light levels (<5 lux).
Dim Red Light Source	Provides safe illumination for participants and staff.	Wavelengths >600 nm (red/orange) to avoid melatonin suppression.
Reclining Chair/Bed	Standardization of participant posture before sampling.	Ensures participants can comfortably maintain a supine position.
-20°C Freezer	Storage of biological samples prior to analysis.	Prevents degradation of analytes like melatonin and cortisol.

Within circadian rhythm research and the development of chronotherapeutics, the Dim Light Melatonin Onset (DLMO) is established as the gold-standard marker for assessing an individual's endogenous circadian phase [8]. Accurate DLMO calculation is critical for diagnosing Circadian Rhythm Sleep-Wake Disorders (CRSWDs) and for timing light, melatonin, or other therapeutic interventions [11]. The prevailing methodologies for determining DLMO have traditionally relied on fixed or dynamic thresholds, which introduce subjectivity and are susceptible to individual differences in melatonin secretion [8].

This application note introduces the Hockey-Stick Algorithm as a robust, objective, and automated alternative for DLMO calculation. We detail its experimental validation, provide a comprehensive protocol for its implementation, and quantify its performance against traditional methods. Framed within the broader research on threshold-based DLMO calculation, the data presented herein demonstrate that this algorithm offers enhanced reliability and reproducibility, making it particularly suitable for high-throughput research and clinical drug development.

Comparative Analysis of DLMO Calculation Methods

The calculation of DLMO from salivary melatonin concentration time-series data can be approached through several methods, each with distinct characteristics. The table below summarizes the key features of the primary techniques.

Table 1: Comparison of Primary DLMO Calculation Methodologies

Method	Description	Key Advantage	Key Limitation
Fixed Threshold	DLMO is the time at which melatonin concentration crosses a pre-defined absolute threshold (e.g., 3 pg/mL or 4 pg/mL) [8].	Simple and straightforward to compute.	May miss DLMO in low melatonin producers or those with high daytime baselines [8].
Dynamic Threshold (Variable Threshold)	Threshold is set relative to the individual's baseline, typically as 2 standard deviations above the mean of the first three low daytime samples ("3k method") [8].	Accounts for individual baseline secretion levels, improving accuracy for low secretors.	Relies on the accuracy of baseline sample selection.
Visual Estimation	A trained chronobiologist visually inspects the melatonin curve to identify the point of a sustained rise [11].	Considers the overall curve shape; historical gold standard.	Subjective, time-consuming, and introduces inter-rater variability.
Hockey-Stick Algorithm	An objective, automated mathematical approach that identifies the point of a sustained, significant increase in the melatonin concentration time-series [11].	High reliability and repeatability; removes subjectivity; easily automated for large datasets.	Requires implementation of the specific algorithm.

Quantitative Performance Validation

The superiority of the Hockey-Stick Algorithm is demonstrated through rigorous comparative studies. A 2023 repeatability and agreement study by Glacet et al. provides direct, quantitative evidence of its performance against other methods and the visual estimation gold standard [11].

Table 2: Performance Metrics of DLMO Calculation Methods from Glacet et al. (2023) [11]

Method	Repeatability (Across Two Nights)	Agreement with Visual Estimation (Mean Difference)	Intraclass Correlation Coefficient (ICC) with Visual Estimation
Fixed Threshold	Good to Perfect	Not Reported	Not Reported
Dynamic Threshold	Good to Perfect	Not Reported	Not Reported
Visual Estimation	Good to Perfect	(Reference Standard)	(Reference Standard)
Hockey-Stick Algorithm	Good to Perfect	5 minutes	0.95

The study concluded that the Hockey-Stick Algorithm "showed equivalent or superior performance" and, thanks to its objective nature, may provide better estimates than the mean of visual estimations from several raters. The authors explicitly recommended that it "should be considered for use in future studies" [11].

Experimental Protocol for DLMO Assessment Using the Hockey-Stick Algorithm

The following section provides a detailed, step-by-step protocol for determining an individual's DLMO, from sample collection to final calculation using the Hockey-Stick Algorithm. This protocol is adapted for a remote, self-directed collection model, which has been validated as feasible and accurate in recent research, including pediatric populations [34].

Sample Collection Workflow

The process of collecting samples for DLMO analysis involves careful pre-collection preparation and a specific sampling routine to ensure accurate results. The following diagram illustrates the complete workflow.

Materials and Reagent Solutions

The following table catalogues the essential materials and reagents required to execute the DLMO protocol, with a specific focus on the solutions that ensure analytical rigor.

Table 3: Research Reagent Solutions and Essential Materials for Remote DLMO Collection

Item	Function/Application	Specifications/Notes
Salivary Melatonin Assay Kit	Quantification of melatonin concentration in saliva samples.	High-sensitivity ELISA (e.g., sensitivity ≤1.35 pg/mL, range 0.78-50 pg/mL). Prefer kits without extraction [8].
Untreated Salivettes	Non-invasive saliva collection.	Salivettes must be untreated for melatonin assay compatibility [34].
Medication Event Monitoring System (MEMs) Cap	Objective compliance measurement; records exact time of each sample collection [34].	Critical for validating protocol adherence in remote studies.
Actigraphy Watch (e.g., ActTrust 2)	Objective monitoring of sleep-wake cycles and activity during the study period [34].	Provides context for DLMO timing and verifies collection conditions.
Digital Luxmeter	Verification of dim light conditions (< 8 lux) during sample collection [34].	Essential for ensuring endogenous melatonin is not suppressed by light.
Blue Light-Blocking Glasses	Allows for limited activity during collection without compromising melatonin secretion [34].	Worn if using electronic devices.
Temperature Sensor & Cold Shipping Kit	Maintains sample integrity from collection to laboratory analysis.	Prevents melatonin degradation.

Data Analysis and Application of the Hockey-Stick Algorithm

Once salivary melatonin concentrations are determined, the Hockey-Stick Algorithm is applied to the time-series data. The core logic of the algorithm involves identifying the point where the data pattern shifts from a relatively flat baseline to a sustained, linear increase, resembling a "hockey-stick."

Procedure Steps:

• Data Input: Compile a data file with two columns: timestamp and melatonin_concentration_pg_per_mL.
• Algorithm Execution: Implement the Hockey-Stick Algorithm using appropriate statistical software (e.g., R, Python). The algorithm objectively identifies the point of inflection where the melatonin concentration begins a sustained, significant rise. This process automates the pattern recognition that a trained chronobiologist would perform visually [11].
• Output and Interpretation: The algorithm returns a precise clock time for the DLMO. This value should be interpreted within the broader context of the participant's actigraphy data and self-reported sleep onset to inform clinical or research decisions.

The Hockey-Stick Algorithm represents a significant methodological advancement in the field of chronobiology. By providing an objective, automated, and highly reliable alternative to traditional threshold-based and visual methods for determining DLMO, it mitigates key sources of variability and bias. The robust validation against the gold standard and its excellent repeatability make it an indispensable tool for researchers and drug development professionals requiring precision and scalability in circadian phase assessment. Its application is particularly pertinent in the context of remote, decentralized clinical trials, which are becoming increasingly common.

Accurately measuring circadian phase is a cornerstone of circadian science, yet significant methodological challenges arise when studying special populations, particularly totally blind individuals with Non-24-Hour Sleep-Wake Rhythm Disorder (Non-24 SWD) and individuals with irregular sleep-wake cycles. These populations present unique complexities for circadian biomarker assessment, creating a critical need for optimized protocols. The dim light melatonin onset (DLMO) serves as the gold standard marker for assessing the timing of the central circadian pacemaker in humans [12]. However, the choice between fixed and variable threshold methods for DLMO calculation carries profound implications for data reliability in these special populations, where melatonin secretion patterns may be atypical or disrupted.

Totally blind individuals often lack photic entrainment to the 24-hour day, causing their endogenous circadian rhythms to free-run with a period usually longer than 24 hours [35]. This non-entrained pattern results in cyclical episodes of insomnia and excessive daytime sleepiness as their circadian phase drifts in and out of alignment with conventional sleep-wake schedules [36]. Similarly, individuals with irregular sleep-wake rhythms present with fragmented sleep patterns without a stable circadian phase [37]. These clinical presentations complicate standard DLMO assessment and necessitate specialized methodological approaches tailored to these unique circadian phenotypes, particularly within research focused on comparing fixed versus variable threshold methodologies.

Diagnostic Framework and Clinical Presentation

Non-24-Hour Sleep-Wake Disorder in Blindness

Non-24-Hour Sleep-Wake Disorder (Non-24 SWD) is a chronic circadian rhythm disorder prevalent in a majority of totally blind individuals who lack light perception [35]. Without light information reaching the suprachiasmatic nucleus (SCN), the master circadian clock reverts to its endogenous period (tau), which typically ranges between 24.2 and 24.9 hours [36]. This pathological state is characterized by:

• Circadian Desynchronization: The internal circadian period (τ) is not synchronized to the 24-hour environmental day [35].
• Cyclical Symptom Pattern: Patients experience periodic episodes of insomnia and excessive daytime sleepiness that recur as the circadian system drifts in and out of phase with the 24-hour day [36].
• Functional Impairment: The disorder significantly interferes with social, academic, and professional functioning, with many patients reporting it more disabling than blindness itself [35].

Diagnosis requires confirmation through measurement of circadian biomarkers, typically by demonstrating a circadian period outside the normal range through urinary melatonin metabolite rhythms or salivary DLMO assessment over multiple cycles [35] [36].

Irregular Sleep-Wake Rhythm Disorder

Irregular Sleep-Wake Rhythm Disorder (ISWRD) presents with fragmented sleep episodes throughout the 24-hour cycle without a consistent circadian pattern [37]. The diagnostic features include:

• Absence of Clear Circadian Pattern: At least three irregular sleep episodes per 24-hour period without a dominant nocturnal sleep period [37].
• Chronic Symptoms: Insomnia and excessive sleepiness complaints persisting for at least three months.
• Etiological Associations: Commonly associated with neurological conditions, dementia, and intellectual disabilities that disrupt SCN function or its outputs.

The pathophysiology involves degeneration of the SCN, reduced exposure to zeitgebers, or both, leading to inability to maintain stable entrainment [37].

Table 1: Epidemiological and Diagnostic Features of Special Populations

Characteristic	Non-24 SWD in Blindness	Irregular Sleep-Wake Rhythm
Prevalence	55-70% of totally blind individuals [35]	Rare in general population; common in neurodegenerative diseases
Primary Cause	Lack of photic entrainment	SCN degeneration or reduced zeitgeber exposure
Sleep Pattern	Progressively delaying, cyclical symptoms	Multiple fragmented sleep bouts per 24h
Circadian Period	>24h (typically 24.2-24.9h) [36]	Variable or unmeasurable
Key Diagnostic Biomarker	Circadian period (τ) from melatonin rhythms [35]	Absence of stable DLMO pattern

DLMO Calculation Methods: Fixed vs. Variable Threshold Approaches

Methodological Frameworks

The determination of DLMO requires establishing a threshold value that signifies the onset of melatonin production. The two primary methodologies employed in research settings each present distinct advantages and limitations, particularly relevant to special populations with atypical melatonin profiles.

Fixed Threshold Method: This approach defines DLMO as the time when melatonin concentrations cross an absolute threshold, typically 2 pg/mL in plasma for low melatonin producers, or 3-4 pg/mL in saliva [12]. The method offers simplicity and standardization across studies but faces challenges in individuals with blunted melatonin amplitude, common in certain patient populations and with advancing age.

Variable Threshold Method: This method establishes a threshold based on individual baseline values, usually defined as two standard deviations above the mean of three or more pre-rise samples [12]. While this approach accounts for individual differences in baseline secretion and amplitude, it becomes unreliable with insufficient baseline samples or unstable baselines - a particular concern in irregular sleep-wake patterns.

Comparative Analysis in Special Populations

Recent systematic evaluations reveal critical methodological considerations for special populations. A comparison of fixed (3 pg/mL) versus variable thresholds in saliva samples from 122 individuals found the variable method produced DLMO estimates 22-24 minutes earlier, aligning more closely with physiological onset in 76% of cases [12]. However, another study favored the fixed threshold, citing greater stability when variable thresholds fell below assay functional sensitivity [12].

The "hockey-stick" algorithm developed by Danilenko and colleagues offers an alternative objective approach, estimating the point of change from baseline to rise in melatonin levels for both salivary and plasma samples [12]. When compared with expert visual assessments, this algorithm demonstrated superior agreement relative to both fixed and dynamic threshold methods, suggesting particular utility for populations with atypical secretion patterns.

Table 2: Comparison of DLMO Calculation Methods for Special Populations

Parameter	Fixed Threshold Method	Variable Threshold Method	Hockey-Stick Algorithm
Definition	Absolute concentration (e.g., 2 pg/mL plasma, 3-4 pg/mL saliva) [12]	2 SD above mean of ≥3 baseline values [12]	Objective curve-fitting to detect inflection point [12]
Advantages	Standardized, simple application, unaffected by unstable baselines	Accounts for individual amplitude differences	Automated, objective, validated against expert assessment
Disadvantages	Problematic for low melatonin producers	Unreliable with insufficient baseline samples	Requires specialized software implementation
Special Population Considerations	May miss true onset in blunted amplitude cases	Better for Non-24 with stable baselines	Superior for irregular patterns with no clear baseline
Recommended For	Research comparing across studies; high-amplitude melatonin secretors	Non-24 with consistent pre-rise baselines	Irregular Sleep-Wake Rhythm; low-amplitude secretors

Optimized Experimental Protocols for Special Populations

Participant Screening and Characterization

Comprehensive phenotyping is essential prior to DLMO assessment in special populations:

Inclusion Criteria for Non-24 SWD Studies:

• Total blindness with no light perception confirmed by ophthalmological examination
• Documented circadian period >24.0 hours based on at least two weeks of actigraphy
• Symptoms of insomnia and/or excessive daytime sleepiness with cyclical pattern per sleep diaries [35] [36]

Exclusion Criteria:

• Use of medications affecting melatonin secretion (beta-blockers, NSAIDs, antidepressants) or cortisol metabolism within 5 half-lives prior to study [12]
• Unstable medical or psychiatric conditions
• Shift work or transmeridian travel within one month of study

Baseline Assessments:

• Actigraphy monitoring for minimum 14 days (preferably longer for blind individuals) [35]
• Sleep diaries for at least 7 days documenting sleep-wake patterns and nap times
• Horne-Ostberg Morningness-Eveningness Questionnaire to establish diurnal preference [37]
• Psychological screening for depression and anxiety given high comorbidity

DLMO Assessment Protocol for Non-24 SWD

Accurate DLMO determination in blind individuals with Non-24 SWD requires extended sampling protocols to capture the free-running circadian phase:

Pre-Sampling Requirements:

• Maintain regular sleep-wake schedule for at least 48 hours prior to assessment (when possible)
• Avoid caffeine, alcohol, and vigorous exercise for 24 hours prior to sampling
• Confirm dim light conditions (<10 lux) beginning at least 2 hours before anticipated DLMO

Sampling Protocol:

• Collect saliva or blood samples every 30-60 minutes for 4-6 hours before habitual bedtime [12]
• For Non-24 SWD with unknown phase, extend sampling window to 8-10 hours or utilize multiple test days
• For plasma melatonin: maintain indwelling catheter with saline flush; sample volume 2-3 mL
• For saliva: use Salivette or similar collection devices; avoid citric acid stimulation
• Document posture, activity, and food intake throughout sampling period

Sample Processing and Analysis:

• Centrifuge saliva samples immediately (3000 rpm for 10 minutes)
• Store at -20°C or -80°C until analysis
• Prefer LC-MS/MS over immunoassays for enhanced specificity, particularly for low concentrations [12]
• For variable threshold method, ensure minimum 3 baseline samples before anticipated rise

Diagram 1: DLMO Assessment Workflow for Special Populations

DLMO Assessment Protocol for Irregular Sleep-Wake Rhythm

Individuals with irregular sleep-wake patterns present unique challenges requiring multiday assessment strategies:

Sampling Strategy:

• Conduct sampling across 2-3 consecutive 24-hour periods to capture circadian phase variability
• Collect samples at 1-2 hour intervals throughout entire 24-hour cycle
• Utilize actigraphy concurrently to correlate melatonin with sleep-wake patterns
• Consider urinary 6-sulfatoxymelatonin (aMT6s) as alternative biomarker for extended assessment [35]

Protocol Adaptations:

• For dementia patients: simplify collection protocol with caregiver assistance
• For severe fragmentation: utilize frequent brief sampling (every 30 minutes) during critical periods
• Implement ambulatory collection systems for home-based assessment when possible

Data Interpretation:

• Calculate DLMO for each 24-hour period separately
• Report phase variability metrics across days
• Correlate melatonin timing with sleep episode initiation
• Consider amplitude and waveform analysis in addition to phase timing

Therapeutic Applications and Chronotherapeutic Interventions

Melatonin and Melatonin Receptor Agonists

Targeting the circadian system with melatonin and related compounds represents the primary therapeutic approach for circadian rhythm disorders in special populations:

Non-24 SWD Treatment:

• Tasimelteon (20 mg daily), a dual MT1/MT2 receptor agonist, is FDA-approved for Non-24 SWD in blind individuals [36]
• Administration timing critical: dose 1 hour before target bedtime at consistent clock time
• Clinical trials demonstrate entrainment efficacy: 20% of tasimelteon patients versus 3% placebo achieved entrainment in SET trial (p=0.017) [36]
• Maintenance of entrainment requires continued treatment: 90% of tasimelteon patients maintained entrainment versus 20% after withdrawal in RESET trial (p=0.0026) [36]

Dosing Considerations for Special Populations:

• Start with low doses (0.5-1 mg) for elderly patients with irregular sleep-wake rhythm
• Time administration according to phase-response curve principles: evening for phase advances
• Consider formulation: immediate-release for phase-shifting, controlled-release for sleep maintenance

Adjunctive Non-Pharmacological Interventions

Structured Behavioral Schedules:

• Implement strict sleep-wake schedules to strengthen non-photic zeitgebers
• Incorporate regular meal times, social interaction, and physical activity at consistent times
• For institutionalized patients: structured environmental activities and light exposure

Environmental Modifications:

• Enhance light exposure during biological day using light therapy devices (2500-10000 lux) [37]
• For sighted individuals with irregular patterns: minimize light at night using amber lenses or dim lighting
• Create clear light-dark cycles through environmental design

Diagram 2: Melatonin Signaling Pathway and Therapeutic Target

The Scientist's Toolkit: Research Reagent Solutions

Table 3: Essential Research Materials for Circadian Protocol Implementation

Research Tool	Specifications & Selection Criteria	Application in Special Populations
Salivary Melatonin Collection	Salivette tubes (cotton/polyester sleeves); avoid citric acid-treated devices	Home-based collection for blind individuals; caregiver-administered for cognitively impaired
Melatonin Assay	LC-MS/MS preferred for specificity (detection limit <1 pg/mL); ELISA validated for salivary matrix	Essential for low-amplitude secretors; critical for accurate variable threshold calculation
Actigraphy Devices	Motion-loggers with light recording capability (e.g., Actiwatch Spectrum); minimum 14-day monitoring	Extended recording essential for Non-24 period calculation; sleep pattern analysis in irregular rhythms
Light Therapy Equipment	Light boxes providing 2500-10000 lux; blue-enriched (460 nm) devices for enhanced efficacy	Non-photic alternative for blind; entrainment aid for sighted irregular sleep-wake patients
Data Analysis Software	Custom algorithms for DLMO calculation (Matlab, R packages); cosinor analysis programs	Implementation of hockey-stick algorithm; period calculation for free-running rhythms

Protocol optimization for circadian rhythm assessment in special populations requires careful consideration of methodological approaches tailored to specific clinical characteristics. For DLMO calculation in the context of fixed versus variable threshold research, the evidence supports:

• Population-Specific Threshold Selection: Fixed thresholds (2 pg/mL plasma, 3 pg/mL saliva) provide reliability in Non-24 SWD with normal amplitude melatonin secretion, while variable thresholds or curve-fitting algorithms offer advantages for irregular sleep-wake patterns with blunted amplitude.

• Extended Sampling Protocols: Special populations require longer sampling windows (8-10 hours for Non-24 SWD) or multiple 24-hour assessments (for irregular rhythms) to accurately capture circadian phase.

• Analytical Considerations: LC-MS/MS methodology provides the necessary sensitivity and specificity for low-concentration melatonin samples prevalent in these populations.

Future research directions should include validation of population-specific DLMO thresholds, development of standardized protocols for ambulatory assessment, and investigation of multimodal biomarker approaches combining melatonin with cortisol and temperature rhythms. These advances will enhance both clinical management and therapeutic development for circadian rhythm sleep disorders in these challenging populations.

Head-to-Head: A Critical Comparison of DLMO Calculation Methods

The accurate determination of circadian phase is fundamental to both basic chronobiology research and clinical practice, particularly in the diagnosis and treatment of circadian rhythm sleep-wake disorders. The dim light melatonin onset (DLMO) represents the most reliable gold-standard marker for assessing the phase of the human circadian pacemaker. Despite its established utility, a significant methodological challenge persists: the absence of a standardized approach for calculating DLMO from melatonin profiles. The two predominant analytical methods—fixed and variable thresholds—introduce substantial variation in phase estimation, potentially compromising both research reproducibility and clinical diagnostics. This application note systematically evaluates the repeatability and agreement between these competing threshold methodologies, providing evidence-based protocols and analytical frameworks for researchers and drug development professionals operating within the context of circadian biology. The performance characteristics of these methods carry profound implications for biomarker validation in chronotherapy trials and the development of circadian-targeted therapeutics, necessitating a rigorous comparative assessment.

Comparative Performance of DLMO Threshold Methods

Quantitative Method Comparison

Multiple studies have quantitatively evaluated the performance of fixed versus variable threshold methods for DLMO determination, with recent evidence pointing to the superiority of a third, more objective method: the hockey stick algorithm. Table 1 summarizes the key performance metrics from comparative studies.

Table 1: Performance Comparison of DLMO Estimation Methods

Method	Principle	Repeatability (Across Nights)	Agreement with Visual Estimation (Mean Difference)	Key Advantages	Key Limitations
Fixed Threshold	Time at which melatonin concentration crosses an absolute value (e.g., 3 or 4 pg/mL for saliva)	Good to Perfect [11]	Variable; can miss DLMO in low melatonin producers [18] [8]	Simple to implement and calculate [18]	Fails for individuals with baseline levels above/below the fixed threshold [18] [8]
Variable Threshold (Dynamic)	Time at which melatonin exceeds 2 standard deviations above the mean of baseline (daytime) values [8]	Good to Perfect [11]	Variable; can produce inaccurate phase estimates with unstable baselines [11] [18]	Accounts for individual differences in baseline secretion and amplitude [8]	Unreliable with too few or inconsistent baseline samples [18]
Hockey Stick	Objective algorithm identifying the point of change from baseline to exponential rise [18]	Good to Perfect [11]	5 minutes (ICC: 0.95) [11]	Fully automated, objective, and highly reliable; performs well vs. expert consensus [11] [18]	Requires specific software implementation; less familiar to some researchers [11]

A 2023 repeatability and agreement study by Glacet et al. provided a direct, rigorous comparison of these methods in healthy young adults. The study found that while all methods showed "good to perfect" repeatability across two nights, the hockey stick method demonstrated equivalent or superior agreement with the mean visual estimation performed by four chronobiologists, exhibiting an intraclass correlation coefficient (ICC) of 0.95 and a mean difference of only 5 minutes [11]. In contrast, the variable threshold method (also known as the "3k method") has been reported to produce DLMO estimates that are 22–24 minutes earlier than the fixed threshold method, though it may be physiologically more accurate in a majority of cases [18]. The fixed threshold method, while simple, carries a significant risk of failing to identify the DLMO in "low melatonin producers," a common scenario in aging populations or certain patient groups, as these individuals may never reach the pre-defined absolute concentration threshold [18] [8].

Impact of Sampling Protocol on Threshold Performance

The reliability of any DLMO calculation method is intrinsically linked to the underlying sampling protocol. Research indicates that a 6-hour sampling window (from 5 hours before to 1 hour after habitual bedtime) is generally sufficient for DLMO assessment [18] [6]. Furthermore, studies have investigated whether less frequent, hourly sampling can provide estimates comparable to the more intensive half-hourly sampling.

A Bland-Altman analysis in an adolescent cohort revealed that 60-minute sampling provided DLMO estimates within ±1 hour of those derived from 30-minute sampling, but this agreement was only consistent when an absolute fixed threshold (3 or 4 pg/mL) was applied [6]. This finding is critical for designing cost-effective and scalable studies, as reducing the number of samples from 13 to 7 within a 6-hour window can significantly reduce assay costs and participant burden without severely compromising data quality, provided the appropriate analytical method is selected.

Detailed Experimental Protocols for DLMO Assessment

Sample Collection Workflow

A standardized protocol is essential for obtaining reliable salivary melatonin data for subsequent threshold analysis. The following workflow, detailed in Figure 1, outlines the key steps from participant preparation to sample analysis.

Figure 1: Experimental workflow for DLMO assessment, covering participant preparation, sample collection, laboratory analysis, and data processing.

Protocol Specifications

The successful execution of the workflow in Figure 1 depends on careful attention to the following protocol details, compiled from established methodologies [18] [8] [6]:

• Participant Preparation: Participants should maintain a fixed sleep-wake schedule for at least one week prior to sampling, verified by wrist actigraphy and sleep diaries. Compliance with pre-lab restrictions is critical: avoidance of non-steroidal anti-inflammatory drugs (NSAIDs), alcohol, nicotine, and caffeine for a minimum of 6 hours before and during sampling. Bright light exposure must be minimized on the test day, especially in the evening.
• Sampling Environment: Saliva collection must occur under dim light conditions, consistently maintained at <20 lux (and ideally <8 lux) to prevent melatonin suppression. Participant posture and activity should be controlled, as these can influence melatonin levels.
• Sample Collection: Using passive drool, collect a minimum of 0.5 mL of saliva per sample. The recommended sampling window is 6 hours, from 5 hours before to 1 hour after habitual bedtime. The schedule can consist of 7 hourly samples or 13 half-hourly samples for higher precision [8] [6]. Samples should be frozen at -20°C or below immediately after collection.
• Laboratory Analysis: Utilize a highly sensitive and specific assay. Salimetrics ELISA, with a sensitivity of 1.35 pg/mL, is a common choice [8]. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is considered the gold standard for its superior specificity [18]. Samples should be analyzed in duplicate to ensure low coefficient of variation (CV).

The Scientist's Toolkit: Essential Research Reagents & Materials

Table 2: Key Reagents and Materials for DLMO Research

Item	Specification / Example	Function / Rationale
Saliva Collection Kit	Passive drool kits (e.g., Salimetrics)	Non-invasive, home-based collection; high participant compliance [8]
Melatonin Assay	High-Sensitivity ELISA (e.g., Salimetrics, sensitivity <1.35 pg/mL) or LC-MS/MS	Quantifies low salivary melatonin concentrations; LC-MS/MS offers highest specificity [18] [8]
Actigraphy Device	Wrist-worn activity monitor (e.g., Actiwatch)	Objectively verifies compliance with fixed sleep schedule prior to sampling [6]
Dim Light Lux Meter	Calibrated light meter	Verifies ambient light levels remain below 20 lux during sampling to prevent masking [11] [6]
Low-Illumination Red Light	Red light source <20 lux	Allows for safe participant movement and sample processing without suppressing melatonin [8]
Freezer (-20°C or colder)	Standard laboratory or dedicated home freezer	Ensures sample stability after collection and prior to analysis [8]

Statistical Considerations for Longitudinal Circadian Data

Analyzing longitudinal data like melatonin profiles requires specialized statistical approaches that account for the inherent correlational structure of repeated measures from the same individual. Standard statistical tests that assume independence of data points are invalid and increase the risk of false discoveries.

• Mixed-Effects Models: These models are strongly recommended for analyzing longitudinal circadian data. They quantify both the fixed effects (the experimental interventions, such as a drug treatment) and the random effects (the inherent, unexplained differences between individual participants) [38]. This approach is statistically more powerful than analyzing each time point separately and avoids the need for severe multiple-testing corrections.
• Avoiding Multiple Testing Pitfalls: Researchers should never "cherry-pick" a statistically significant time point from a longitudinal dataset for post-hoc analysis without applying rigorous multiple testing correction methods (e.g., Bonferroni correction). Mixed-effects models provide a more robust framework for analyzing the entire time series, testing for overall effects of time and group-by-time interactions [38].
• Stationarity: Data should be checked for stationarity, meaning that the underlying statistical properties (e.g., mean, variance) do not change over the time frame of analysis. Non-stationarity, such as a phase shift during the experiment, may require segmenting the data or using more complex models [38].

The choice of threshold method for determining DLMO is a critical methodological decision that directly impacts the reliability, reproducibility, and clinical utility of circadian phase assessments. Based on current evidence, the hockey stick method offers the most objective and reliable performance, showing excellent agreement with expert consensus and high repeatability. While the variable threshold method is advantageous for accommodating individual differences in melatonin secretion, it is sensitive to baseline instability. The fixed threshold method, despite its simplicity, is least reliable due to its failure in low melatonin producers.

For researchers and professionals in drug development, adopting the hockey stick method or, at a minimum, comparing results across multiple threshold methods, is recommended to ensure robust phase estimation. This is particularly vital for the success of chronotherapy trials, where precise timing of drug administration relative to the circadian phase is a key determinant of efficacy and safety. Future work should focus on the widespread implementation of standardized, objective algorithms like the hockey stick into commercial and open-source analysis software to enhance cross-study comparability in the field of circadian medicine.

Within the field of circadian biology, the dim light melatonin onset (DLMO) is established as the most reliable circadian phase marker in humans [6] [4]. Its accuracy is critical for the diagnosis of Circadian Rhythm Sleep-Wake Disorders (CRSWDs) and for determining the optimal timing of chronotherapeutic interventions, including the administration of drugs whose efficacy is influenced by the body's internal clock [39] [40]. However, the calculated timing of the DLMO is not absolute; it is significantly influenced by the methodological choice of threshold used in its calculation. The central dichotomy lies in the use of a fixed absolute threshold versus a variable, individualized threshold, a decision that research has demonstrated can systematically shift the estimated DLMO by 22 to 24 minutes [41]. This application note details the impact of this critical methodological choice, provides validated protocols for DLMO assessment, and places these findings within the context of broader research on DLMO calculation.

Fixed vs. Variable Thresholds: A Quantitative Analysis

The core of the threshold selection problem is the balance between consistency and biological accuracy. The table below summarizes the fundamental characteristics of the two primary threshold methods.

Table 1: Core Characteristics of DLMO Threshold Methods

Feature	Fixed Threshold Method	Variable Threshold Method (3k Method)
Definition	Uses a pre-defined melatonin concentration (e.g., 3 pg/mL or 4 pg/mL).	Calculates a threshold as the mean + 2 standard deviations of the first three low daytime samples.
Primary Advantage	Simplicity and high inter-assay consistency; produces less variable DLMOs [41].	Accounts for individual differences in baseline secretion; accommodates both low and high melatonin producers [8].
Primary Disadvantage	May miss the onset in low secretors; fails if daytime levels are above the fixed threshold.	Produces DLMO estimates that are more variable between individuals.
Typical DLMO Timing	Later relative to the initial rise of melatonin.	Earlier, closer to the initial rise of melatonin [41].

The choice between these methods has a direct and quantifiable impact on the phase marker. A pivotal study by Molina et al. (2011) directly addressed this issue, revealing consistent temporal discrepancies [41].

Table 2: Quantitative Discrepancies Between Threshold Methods (Molina et al., 2011)

Sampling Rate	Threshold Comparison	Mean Temporal Difference	Statistical Significance
Half-hourly (13 samples)	3k vs. 3 pg/mL Fixed	24 minutes earlier	p < 0.001
Hourly (7 samples)	3k vs. 3 pg/mL Fixed	22 minutes earlier	p < 0.001

This systematic 22-24 minute advance in DLMO timing when using the variable threshold is a critical consideration for any application requiring high temporal precision, such as aligning light therapy or timing drug administration in chronotherapy trials [42] [40].

Recommended DLMO Assessment Protocol

To ensure reliable and reproducible DLMO estimation, the following protocol is recommended, incorporating findings on sampling efficiency.

Sample Collection Workflow

The following diagram illustrates the streamlined workflow for a cost-effective DLMO assessment, suitable for both clinical and research settings.

Key Protocol Steps

• Participant Preparation: Participants must maintain a fixed sleep schedule for at least one week prior to sampling. Compliance should be verified using wrist actigraphy and sleep diaries [6].
• Dim Light Conditions: All saliva collections must occur in dim light, consistently maintained below 20 lux to prevent light-induced suppression of melatonin secretion [6] [4].
• Sampling Window: The sampling window should be timed relative to the individual's habitual bedtime. The recommended window begins 5 hours before bedtime and ends 1 hour after bedtime [6] [8].
• Sampling Rate: For a balance of cost-effectiveness and accuracy, hourly sampling (7 samples) is sufficient. Research shows that DLMOs derived from 60-min sampling are within ±1 hour of those from 30-min sampling when using an absolute threshold [6]. Another study confirmed that hourly sampling provides DLMO estimates only 6-8 minutes earlier than half-hourly sampling, with high correlation (r ≥ 0.89) [41].
• Sample Analysis: Saliva samples should be assayed using a high-sensitivity melatonin ELISA with a sensitivity of at least 1.35 pg/mL to accurately detect the low concentrations at the onset of secretion [8].

The Scientist's Toolkit: Essential Research Reagents & Materials

The following table lists the essential materials required for implementing a robust salivary DLMO protocol.

Table 3: Essential Research Reagents and Materials for Salivary DLMO Assessment

Item	Specification / Function
Salivary Melatonin Assay Kit	Competitive ELISA, colorimetric. High sensitivity (<1.35 pg/mL) and no extraction required. Essential for accurate measurement of low melatonin concentrations in saliva [8].
Saliva Collection Device	Passive drool kits or salivettes. Must be non-stimulating to avoid interference with melatonin assay. Sufficient volume (~0.5 mL) for duplicate measurements [8] [13].
Dim Light Environment	Controlled lighting capable of maintaining <20 lux. Critical to prevent masking of the endogenous melatonin rhythm [6] [4].
Actigraph	Worn on the non-dominant wrist. Objectively monitors sleep-wake patterns and compliance with the fixed sleep schedule during the pre-assessment week [6].
Data Analysis Software	Capable of performing linear interpolation and threshold calculations (for both fixed and variable methods) to determine the precise DLMO time from melatonin concentration data.

Molecular Pathways of Melatonin Regulation

The DLMO is an output of the central circadian pacemaker. The following diagram illustrates the core molecular feedback loops that generate the circadian rhythm and regulate melatonin synthesis.

This molecular clock mechanism ensures the rhythmic production of melatonin, the direct measurement of which is the DLMO.

The documented 22-24 minute discrepancy in DLMO timing between fixed and variable thresholds is not merely a statistical finding but a significant factor with direct implications for circadian science and its clinical applications. This systematic difference underscores that the DLMO is not a single, immutable value but a phase marker whose definition is operationally dependent on the chosen calculation methodology.

Within the broader thesis of fixed versus variable threshold research, these findings highlight a critical trade-off. The fixed threshold (3 pg/mL or 4 pg/mL) offers greater practical consistency and is less variable, making it suitable for large-scale studies where uniformity across populations is a priority [6] [41]. Conversely, the variable threshold (3k method) provides superior biological individuation by accounting for an individual's specific baseline melatonin levels. This makes it indispensable for clinical applications involving populations with altered melatonin secretion, such as the elderly or patients with certain disorders [8].

The development of more objective calculation methods, such as the "hockey stick" algorithm, which showed superior performance in a recent agreement study, points to the future of DLMO analysis [11]. Furthermore, the principles of chronotherapy emphasize that drug efficacy and toxicity can vary dramatically with circadian timing [39] [43] [42]. A 20-minute misalignment in circadian phase could therefore be the difference between optimal drug exposure and a subtherapeutic or toxic outcome.

In conclusion, researchers and clinicians must explicitly report and justify their choice of DLMO threshold, as this decision directly impacts the estimated phase. The protocol outlined herein provides a framework for achieving a reliable DLMO, but the interpretation of results must always be contextualized within the understanding that threshold choice intrinsically influences temporal readouts. Future work should focus on standardizing these methods across the field to ensure comparability and maximize the translational potential of circadian research.

Circadian rhythms, the endogenous near-24-hour oscillations governing physiological processes, represent a critical domain of investigation for researchers and pharmaceutical developers. Individual differences in circadian timing, known as chronotype, manifest as variations in sleep-wake patterns, cognitive performance peaks, and metabolic functions. Accurate chronotype assessment is particularly relevant for drug development, given that circadian regulation affects the metabolism of approximately 80% of protein-coding genes and significantly influences drug pharmacokinetics and pharmacodynamics [12].

The Dim Light Melatonin Onset (DLMO) is widely regarded as the most reliable physiological marker of central circadian timing in humans, representing the time in the evening when melatonin secretion initiates under dim light conditions [44] [12]. Conversely, the Morningness-Eveningness Questionnaire (MEQ) is a well-established subjective instrument that assesses an individual's preference for timing of activities and sleep [44] [45]. Understanding the correlation between these measures—objective physiological markers and subjective preference assessments—holds significant implications for both basic research and clinical applications.

This application note examines the relationship between DLMO and MEQ within the context of a broader thesis investigating fixed versus variable threshold methodologies for DLMO calculation. We present quantitative correlation data, detailed experimental protocols, and analytical frameworks to guide researchers in implementing these assessments with scientific rigor.

Theoretical Background and Significance

Dim Light Melatonin Onset (DLMO) as a Circadian Phase Marker

Melatonin, a neurohormone secreted by the pineal gland, serves as a master regulator of circadian rhythms. Its secretion is controlled by the suprachiasmatic nucleus (SCN), the body's central circadian pacemaker [44]. DLMO typically occurs 2-3 hours before habitual sleep onset and is considered the gold standard for assessing circadian phase in humans [12] [8]. The accurate determination of DLMO is crucial for diagnosing Circadian Rhythm Sleep-Wake Disorders (CRSWDs), such as Delayed Sleep-Wake Phase Disorder (DSWPD), and for optimizing the timing of chronotherapeutic interventions [6] [17].

The methodological debate between fixed and variable threshold approaches for DLMO calculation forms a critical research context. The fixed threshold method defines DLMO as the time when melatonin concentration crosses an absolute value (typically 3 or 4 pg/mL in saliva) [12] [6]. In contrast, the variable threshold method (often termed the "3k method") establishes a personalized threshold based on an individual's baseline melatonin levels, calculated as the mean plus two standard deviations of three low daytime values [8]. This approach accommodates natural variations in melatonin production amplitude between individuals, which is particularly important for low melatonin producers commonly found in aging populations or certain clinical conditions [12] [8].

Morningness-Eveningness Questionnaire (MEQ) as a Subjective Measure

The MEQ, developed by Horne and Östberg, is a 19-item instrument that assesses an individual's diurnal preference by querying preferred timing for various activities, sleep parameters, and alertness patterns [44] [45]. Scores range from 16 to 86, with categorizations as follows:

• 16-30: Definite Evening Type
• 31-41: Moderate Evening Type
• 42-58: Intermediate Type
• 59-69: Moderate Morning Type
• 70-86: Definite Morning Type [45]

It is important to note that these categorizations may require population-specific adjustments, as evidenced by a validation study in middle-aged workers that proposed different cut-off scores [45]. The MEQ evaluates psychological preference rather than directly measuring physiological processes, representing a distinct construct from DLMO [44] [46].

Correlation Data Between DLMO and MEQ

Multiple studies have investigated the relationship between objective circadian phase (DLMO) and subjective chronotype (MEQ). The following table summarizes key quantitative findings from the research literature.

Table 1: Correlation Coefficients Between DLMO and MEQ Across Studies

Study Population	Sample Size (N)	Correlation Coefficient (r)	p-value	Notes	Source
Mixed (Healthy Controls + DSPD Patients)	60	-0.70	<0.001	Controlled lab/home DLMO assessments	[44]
Young Healthy Adults	72	-0.25	0.035		[46]
Middle-aged to Older Adults	37	-0.40	0.055	Unsupervised home saliva collection	[44]
Clinical DSWPD Population	154	N/A	N/A	DLMO range: 18:42-02:24	[17]

The consistent negative correlation reflects the underlying biological relationship: earlier DLMOs (indicating an earlier circadian phase) associate with higher MEQ scores (indicating morning preference), while later DLMOs associate with lower MEQ scores (evening preference) [44].

The strength of correlation varies substantially across studies, influenced by factors including:

• Population characteristics: Age range, health status, and presence of circadian disorders
• Methodological rigor: Controlled versus unsupervised saliva collection
• Sample size: Statistical power to detect relationships
• Range restriction: The breadth of chronotypes represented in the sample [44] [46]

A comprehensive linear regression analysis incorporating MEQ, MSFsc (from the Munich ChronoType Questionnaire), and age accounted for 60% of the variance in DLMO timing, with MEQ emerging as a significant predictor (beta = -0.41, p = 0.004) [44]. This demonstrates the substantial contribution of subjective measures while highlighting that significant inter-individual variability remains unaccounted for by questionnaires alone.

Table 2: Comparative Performance of Circadian Timing Predictors in Multiple Regression

Predictor Variable	Beta Coefficient	Statistical Significance (p-value)	Interpretation
MSFsc (MCTQ)	0.51	0.001	Strongest predictor of DLMO
MEQ Score	-0.41	0.004	Significant secondary predictor
Age	0.26	0.013	Modest but significant predictor

Detailed Experimental Protocols

DLMO Assessment Protocol

Pre-Assessment Requirements

• Stabilization Period: Participants should maintain a consistent, self-selected sleep-wake schedule for at least 7 days prior to DLMO assessment, verified by sleep diaries and actigraphy monitoring [6].
• Contraindications: Exclude participants using medications that suppress melatonin (beta-blockers, NSAIDs) or affect its measurement. Avoid recent transmeridian travel (>2 time zones within the previous month) [44] [12].
• Substance Restrictions: Refrain from caffeine, alcohol, and nicotine for at least 24 hours before sampling. Avoid vigorous exercise during the sampling period [44].

Sampling Environment and Setup

• Lighting Conditions: Maintain dim light conditions (<20 lux) throughout sampling, verified by calibrated photometers. Use indirect red light if illumination is necessary, as it minimally suppresses melatonin [6].
• Sampling Window: Initiate saliva collection 5-7 hours before habitual bedtime and continue until 1-2 hours after bedtime [44] [6] [8]. For clinical populations with uncertain phase, extend the sampling window.
• Sampling Frequency: Collect samples at 30-minute intervals for highest precision, or 60-minute intervals for a cost-effective protocol with minimal accuracy compromise [6] [8].

Saliva Collection and Handling

• Collection Method: Use passive drool or appropriate salivettes. For each sample, collect at least 0.5 mL of saliva to permit duplicate assays [8].
• Sample Handling: Centrifuge samples to remove particulate matter immediately after collection. Store samples at -20°C or -80°C until analysis to preserve melatonin integrity [12].
• Compliance Monitoring: For home collections, implement objective compliance measures such as timestamped containers and ambient light monitoring to validate sampling conditions [44].

Melatonin Assay and DLMO Calculation

• Analytical Method: Employ enzyme-linked immunosorbent assay (ELISA) or preferably liquid chromatography-tandem mass spectrometry (LC-MS/MS) for superior sensitivity and specificity, particularly at low concentrations [12].
• DLMO Calculation Methods:
  • Fixed Threshold: Linear interpolation to determine when melatonin concentration crosses 3 pg/mL or 4 pg/mL [6].
  • Variable Threshold ("3k Method"): Calculate mean + 2 standard deviations of the first three baseline samples; DLMO is the point where melatonin consistently exceeds this individualized threshold [44] [8].

Experimental Workflow for DLMO Assessment

MEQ Administration Protocol

Implementation Guidelines

• Administration Format: The MEQ can be administered as a paper form or electronically. Electronic versions facilitate automated scoring and data management [45].
• Timing: Administer before any experimental manipulations or interventions to establish baseline chronotype.
• Instructions: Emphasize that respondents should answer based on their natural preferences rather than current constraints imposed by work or social obligations.

Scoring and Interpretation

• Scoring Algorithm: Apply the standardized scoring system where each response option carries a specific point value. Sum all items for a total score between 16-86 [45].
• Chronotype Categorization: Classify participants according to established cut-offs, considering potential adjustments for specific populations (e.g., age groups, clinical populations) [45].
• Data Quality Assessment: Review for response inconsistencies (e.g., mismatched answers to related items) that may indicate poor comprehension or attention.

Analytical Framework and Technical Considerations

Threshold Method Comparison for DLMO Calculation

The choice between fixed and variable threshold methods carries significant implications for DLMO determination and its correlation with MEQ:

Table 3: Comparison of Fixed vs. Variable Threshold Methods for DLMO Calculation

Parameter	Fixed Threshold Method	Variable Threshold Method (3k Method)
Principle	Absolute melatonin concentration (3-4 pg/mL)	Relative increase above individual's baseline
Advantages	Simple, standardized, requires fewer baseline samples	Accommodates low melatonin producers, personalized
Limitations	May miss DLMO in low producers, potentially biased in high baseline individuals	Requires stable baseline, sensitive to baseline variability
Recommended For	General population screening, high melatonin producers	Clinical populations, elderly, low melatonin producers
Impact on MEQ Correlation	Potential underestimation of relationship if low producers misclassified	potentially stronger correlation by accurately capturing all participants' phase

Integration with Complementary Assessments

For comprehensive chronotype evaluation, consider implementing a multi-method assessment battery:

• Munich ChronoType Questionnaire (MCTQ): Provides behavioral measures of sleep timing, particularly MSFsc (midpoint of sleep on free days, sleep-corrected), which demonstrates correlation with both DLMO (r=0.68) and MEQ (r=-0.64) [44] [46].
• Actigraphy: Objective monitoring of sleep-wake patterns provides behavioral validation of questionnaire responses.
• Light Exposure Monitoring: Personal light loggers capture photic input that influences circadian phase and moderates DLMO-MEQ relationships.

DLMO Calculation Decision Pathway

The Scientist's Toolkit: Research Reagent Solutions

Table 4: Essential Materials and Reagents for DLMO and MEQ Research

Item	Specification/Function	Research Application	Technical Notes
Salivary Melatonin Assay	High-sensitivity ELISA or LC-MS/MS; sensitivity <2 pg/mL	Quantifies melatonin concentration in saliva samples	LC-MS/MS offers superior specificity; validate assay for salivary matrix [12]
Saliva Collection Devices	Passive drool kits or salivettes	Non-invasive saliva sample collection	Collect ≥0.5 mL per sample for duplicate analyses [8]
Light Monitoring System	Calibrated photometers (lux)	Verifies dim light conditions (<20 lux) during sampling	Critical for protocol validity; use continuous logging [6]
MEQ Instrument	19-item validated questionnaire	Assesses subjective morningness-eveningness preference	Available in multiple languages; validate for specific populations [45]
Actigraphy System	Wearable movement sensors	Objectively monitors sleep-wake patterns pre-assessment	Validates sleep schedule compliance during stabilization [17]
Sample Storage	-20°C or -80°C freezer	Preserves sample integrity until analysis	Maintain cold chain; avoid freeze-thaw cycles [12]

The correlation between DLMO and MEQ, with coefficients ranging from r = -0.25 to r = -0.70 across studies, reflects a consistent but imperfect relationship between physiological circadian phase and subjective morningness-eveningness preference [44] [46]. This association underscores the value of MEQ as a cost-effective screening tool while highlighting its limitations as a sole indicator of circadian phase.

Within the context of fixed versus variable threshold DLMO calculation research, methodological decisions significantly impact the strength of observed relationships. The variable threshold method may enhance measurement accuracy across diverse populations, particularly for individuals with atypical melatonin profiles. Researchers should select analytical approaches aligned with their specific population and research objectives, considering the potential for threshold methods to moderate observed correlations between physiological and subjective chronotype measures.

For comprehensive circadian assessment, a multi-method approach combining DLMO physiological measurement with MEQ subjective evaluation provides the most complete chronotype characterization, balancing scientific rigor with practical implementation constraints in both basic research and clinical applications.

Delayed Sleep-Wake Phase Disorder (DSWPD) is a circadian rhythm sleep-wake disorder characterized by a significant delay in the major sleep episode relative to conventional or desired sleep-wake times, resulting in chronic sleep-onset insomnia and difficulty waking in the morning [47] [48]. The disorder carries a substantial burden of disability, affecting mood, daytime performance, self-evaluation, and social functioning [47]. With a prevalence ranging from 1.1% to 8.4% in the general population and higher rates among adolescents and young adults, accurate diagnosis is essential for effective treatment [47] [48].

The dim light melatonin onset (DLMO) is widely regarded as the gold standard biomarker for assessing circadian phase in humans, serving as a reliable objective measure of the timing of the endogenous circadian clock [11] [18] [8]. DLMO represents the time in the evening when melatonin secretion begins to rise under dim light conditions, typically occurring 2-3 hours before sleep onset [18]. Despite its established validity, the clinical implementation of DLMO assessment faces challenges, particularly regarding the optimal method for its calculation from raw melatonin data. This application note focuses on the critical comparison between fixed threshold and variable threshold methods for determining DLMO, providing researchers and clinicians with evidence-based protocols to enhance diagnostic precision in DSWPD.

Comparative Analysis of DLMO Calculation Methods

Methodological Approaches and Performance Characteristics

Table 1: Comparison of DLMO Calculation Methods

Method	Definition	Advantages	Limitations	Repeatability (ICC)	Agreement with Visual Estimation (Mean Difference)
Fixed Threshold	Time when interpolated melatonin concentrations cross a predefined absolute value (typically 3-4 pg/mL for saliva, 10 pg/mL for serum)	Simple to implement; consistent across subjects	May miss DLMO in low melatonin producers; potentially unreliable if threshold exceeds individual's peak amplitude	Good to perfect [11]	Variable performance depending on population [11]
Variable Threshold (3k Method)	Time when melatonin levels exceed 2 standard deviations above the mean of three or more baseline (pre-rise) values	Accommodates individual differences in amplitude; suitable for low melatonin producers	Unreliable with insufficient (<3) or inconsistent baseline values	Good to perfect [11]	-22 to -24 minutes earlier than fixed threshold in some studies [18]
Hockey Stick Algorithm	Objective, automated method estimating point of change from baseline to rise using segmented regression	High objectivity; excellent agreement with expert assessment; automated processing	Requires specific computational implementation	Perfect (ICC: 0.95) [11]	5 minutes mean difference [11]
Visual Estimation	Subjective determination by trained chronobiologists	Considers overall curve shape; professional judgment	Subjective; time-consuming; requires expertise	Not applicable	Reference standard [11]

Quantitative Performance Metrics

Table 2: Method Performance in Clinical Validation Studies

Performance Metric	Fixed Threshold	Variable Threshold	Hockey Stick Method	Study Details
Repeatability across nights	Good to perfect	Good to perfect	Perfect (ICC: 0.95)	n=31 healthy adults [11]
Agreement with visual estimation	Variable	-22 to -24 min earlier than fixed threshold	5 min mean difference	Comparison with 4 chronobiologists [11]
Intraclass Correlation (ICC)	Not specified	Not specified	0.95	Agreement study (n=62) [11]
Applicability to low melatonin producers	Poor	Good	Good	Includes aging populations and certain medications [18] [8]

Diagnostic Protocols for DSWD Assessment

Integrated Diagnostic Workflow for DSWPD

The following diagram illustrates the comprehensive diagnostic pathway for DSWPD, incorporating both traditional assessment methods and advanced DLMO quantification:

Diagram 1: Comprehensive Diagnostic Pathway for DSWPD illustrates the integrated workflow combining clinical evaluation with objective circadian phase assessment.

Detailed DLMO Assessment Protocol

Sample Collection Procedures

For accurate DLMO assessment, salivary melatonin collection should follow these standardized procedures:

• Collection Timeline: Begin sampling 5 hours before habitual bedtime and continue until 1 hour after habitual bedtime, resulting in approximately 7 samples when collected hourly [8]. For enhanced precision, 13 samples collected at 30-minute intervals can be utilized [8].
• Sampling Conditions: Maintain dim light conditions (<8 lux) throughout the collection period, verified by portable lux meters [11] [18]. Participants should refrain from eating, drinking caffeinated beverages, or brushing teeth 15-30 minutes before each sample to avoid contamination [8].
• Home Collection Protocol: At-home kits should include detailed instructions, dim light verification tools, and standardized collection materials. Studies demonstrate high correlation between home-based and lab-based DLMO (r = 0.91-0.93, p < 0.001) when proper protocols are followed [49].

Analytical Methods and Calculation Protocols

Melatonin Quantification:

• Preferred Analytical Method: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) offers superior specificity, sensitivity, and reproducibility compared to immunoassays, particularly for low-concentration salivary melatonin [18].
• Alternative Method: Enzyme-linked immunosorbent assay (ELISA) can be utilized with sensitivity thresholds of at least 1.35 pg/mL for salivary melatonin [8].
• Quality Control: Implement duplicate measurements and standardized calibration curves. CLIA-certified or GLP-compliant laboratories ensure analytical validity [8].

DLMO Calculation Procedures:

Fixed Threshold Protocol:

• Plot melatonin concentration against clock time
• Apply linear interpolation between consecutive data points
• Identify the time when the interpolated curve crosses the predetermined threshold (3-4 pg/mL for saliva, 10 pg/mL for serum)
• Record this time as DLMO

Variable Threshold (3k Method) Protocol:

• Calculate the mean of the first three baseline (daytime) melatonin concentrations
• Compute the standard deviation of these baseline values
• Set threshold as mean + 2 standard deviations
• Identify the time when melatonin levels first exceed and remain above this threshold
• Record this time as DLMO [8]

Hockey Stick Algorithm Protocol:

• Apply segmented regression analysis to identify the breakpoint between baseline and rising phases
• Utilize validated computational implementations (e.g., R or Python packages)
• The breakpoint represents the DLMO [11]

Research Reagent Solutions for Circadian Assessment

Table 3: Essential Materials and Reagents for DLMO Assessment

Item	Specifications	Function	Implementation Considerations
Salivary Melatonin Assay	Sensitivity: ≤1.35 pg/mL; Range: 0.78-50 pg/mL; No extraction required	Quantitative measurement of melatonin in saliva	Select validated kits; prefer LC-MS/MS for highest specificity [18] [8]
Saliva Collection Devices	Passive drool kits; sufficient for 0.5 mL per sample	Non-invasive sample collection for ambulatory assessment	Ensure compatibility with analytical method; provide clear patient instructions [8]
Portable Lux Meters	Accuracy: ±5%; Range: 0-200 lux	Verification of dim light conditions (<8 lux) during sampling	Essential for protocol compliance; include in at-home kits [49] [18]
Actigraphy Devices	Research-grade with light monitoring capability (e.g., Actiwatch Spectrum Plus)	Objective sleep-wake monitoring and light exposure assessment	Enable phase prediction models; 7-14 day monitoring recommended [49] [17]
DLMO Calculation Software	Custom algorithms for fixed threshold, variable threshold, and hockey stick methods	Standardized, objective DLMO determination	Implement quality control through visual inspection of curves [11] [8]

Implications for Clinical Research and Drug Development

The selection of DLMO calculation methodology has significant implications for patient stratification in clinical trials and evaluation of chronotherapeutic interventions. Approximately 40% of individuals clinically diagnosed with DSWPD do not exhibit delayed circadian phase when objectively measured with DLMO, highlighting the critical need for precise biochemical phenotyping [49] [17]. Furthermore, accurate DLMO assessment enables optimally timed administration of melatonin therapy, which is being investigated as a personalized treatment approach for DSWPD [50].

Emerging computational approaches that predict DLMO from ambulatory light exposure data show promise for reducing the burden of traditional DLMO assessment. These models can predict DLMO with root mean square error of 57-68 minutes, achieving accuracy within ±1 hour in 58-75% of DSWPD patients [17]. While not yet replacements for direct biochemical measurement, these methods may serve as valuable screening tools in both clinical and research settings.

The integration of standardized DLMO assessment protocols with appropriate calculation methods represents a significant advancement toward precision medicine in circadian rhythm sleep disorders. By implementing the detailed methodologies outlined in this application note, researchers and clinicians can enhance diagnostic accuracy, improve patient stratification, and optimize therapeutic outcomes for individuals with Delayed Sleep-Wake Phase Disorder.

The accurate prediction of physiological phases represents a critical frontier in personalized medicine. Two prominent applications—determining the circadian rhythm marker Dim Light Melatonin Onset (DLMO) and identifying menstrual cycle phases—exemplify the powerful synergy between wearable sensor data and machine learning (ML). These methodologies are moving beyond traditional, often intrusive, methods to provide continuous, passive, and objective monitoring.

Central to the advancement of circadian research is the ongoing methodological debate between using fixed versus variable thresholds for calculating DLMO. The fixed threshold method defines DLMO as the time when melatonin concentrations cross a predetermined absolute value (e.g., 3 or 4 pg/mL in saliva). In contrast, the variable threshold method (e.g., the "3k method") sets a threshold as two standard deviations above the mean of an individual's baseline daytime samples [8] [12]. This debate frames the development of new protocols, as the choice of method impacts accuracy, especially for individuals who are low melatonin producers, a common issue in aging populations [8].

Concurrently, in women's health, ML models are being trained on data from wrist-worn devices—measuring skin temperature, heart rate (HR), interbeat interval (IBI), and electrodermal activity (EDA)—to classify menstrual cycle phases with high accuracy, thereby reducing the burden of self-reporting [51]. This article details the application notes and experimental protocols that underpin these emerging frontiers in physiological phase prediction.

Application Notes: Data and Algorithm Performance

The following tables summarize the key quantitative findings and algorithmic performances from recent research in circadian and menstrual phase prediction.

Table 1: Machine Learning Performance in Menstrual Phase Classification (Fixed Window Technique)

Number of Phases Classified	Best-Performing ML Model	Accuracy	Area Under the Curve (AUC)	Data Partitioning Method
4 Phases (P, F, O, L)	Random Forest	71%	0.89	Leave-last-cycle-out [51]
3 Phases (P, O, L)	Random Forest	87%	0.96	Leave-last-cycle-out [51]
3 Phases (P, O, L)	Random Forest	87%	Not Reported	Leave-one-subject-out [51]

Table 2: Comparative Analysis of DLMO Calculation Methods

Method	Description	Advantages	Limitations
Fixed Threshold	Melatonin crosses an absolute value (e.g., 3-4 pg/mL in saliva) [12].	Simple, standardized.	May miss DLMO in low melatonin producers; fails if baseline is above threshold [8] [12].
Variable Threshold ("3k Method")	Threshold is 2 standard deviations above the mean of 3+ baseline samples [8].	Accounts for individual baseline levels; better for low secretors [8].	Unreliable with too few or inconsistent baseline samples; can estimate earlier DLMO [12].
"Hockey-Stick" Algorithm	Automated algorithm detecting the point of change from baseline to rise [12].	Objective, automated; showed better agreement with expert assessment than threshold methods [12].	Requires validation against established methods; complex implementation.

Table 3: Key Physiological Signals for Phase Prediction from Wearables

Physiological Signal	Relevance to Circadian Phase	Relevance to Menstrual Phase
Skin Temperature	Core body temperature is a fundamental circadian rhythm [51].	Shows significant differences across phases; rises post-ovulation [51].
Heart Rate (HR) / Interbeat Interval (IBI)	Exhibits a robust diurnal pattern [52].	Heart rate and HRV features are used to classify phases with high accuracy [51].
Electrodermal Activity (EDA)	A key signal for stress, which can influence and be influenced by circadian rhythms [52].	Used as a feature in multi-parameter models for menstrual phase identification [51].

Experimental Protocols

Protocol for Salivary DLMO Assessment

This protocol outlines the standardized procedure for assessing circadian phase using salivary melatonin, a critical process for research comparing fixed and variable threshold calculations [8] [12].

I. Materials and Reagents

• Saliva Collection Kit: Salivettes or passive drool kits.
• Dim Light Melatonin Onset (DLMO) Kit: Commercially available at-home or in-clinic kits can be used [8].
• Freezer: For sample storage at ≤ -20°C.
• Melatonin Assay: A highly sensitive and specific assay, such as a competitive ELISA or Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS). The Salimetrics Melatonin Assay has specifications including a sensitivity of 1.35 pg/mL and a range of 0.78–50 pg/mL [8]. LC-MS/MS is considered superior due to enhanced specificity [12].
• Dim Red Light Source: For safe illumination during sample collection.

II. Pre-Collection Participant Instructions

• Avoid alcohol, caffeine, and nicotine for at least 12 hours before and during sampling.
• Avoid vigorous exercise on the day of collection.
• Do not eat or drink (except water) 1 hour before each sample. Do not brush teeth 45 minutes before sampling to avoid gingival bleeding.
• If possible, avoid non-steroidal anti-inflammatory drugs (NSAIDs) and beta-blockers, as they can suppress melatonin [12].

III. Sample Collection Workflow

• Timing: Begin sampling 5 hours before the participant's habitual bedtime and continue until 1 hour after bedtime. This creates a 7-point collection (one sample per hour) [8]. For enhanced precision, a 13-point collection (every 30 minutes) can be used.
• Environment: All samples must be collected under dim light conditions (< 10-30 lux) to prevent melatonin suppression. Use a dim red light source if illumination is needed [8] [12].
• Procedure: For each time point, collect saliva via passive drool or Salivette. Clearly label the tube with the time and date. Immediately freeze the sample at ≤ -20°C.

IV. Laboratory Analysis

• Analyze samples using the chosen high-sensitivity melatonin assay (e.g., ELISA or LC-MS/MS) in duplicate to ensure reliability [8] [12].

V. DLMO Calculation

• Plot salivary melatonin concentration against clock time.
• Apply both fixed and variable threshold methods for comparison.
  • Fixed Threshold: Calculate the time at which the interpolated melatonin curve crosses the 3 pg/mL or 4 pg/mL threshold [12].
  • Variable Threshold ("3k Method"): Calculate the mean and standard deviation (SD) of the first three (lowest) daytime melatonin concentrations. DLMO is the time when melatonin levels rise and remain above the "mean + 2SD" threshold [8].

Protocol for Menstrual Phase Identification using Wearables and ML

This protocol describes the methodology for training machine learning models to identify menstrual cycle phases from data collected via a wrist-worn wearable device [51].

I. Materials and Equipment

• Wrist-worn Wearable Device: A device capable of continuous measurement of skin temperature, electrodermal activity (EDA), interbeat interval (IBI), and heart rate (HR) (e.g., Empatica E4, EmbracePlus) [51].
• Ovulation Test Kits: Urinary luteinizing hormone (LH) test kits to confirm ovulation and label data.
• Data Processing Infrastructure: Computers with sufficient processing power for feature extraction and model training (e.g., Python with scikit-learn, TensorFlow).

II. Participant Screening and Data Collection

• Screening: Recruit participants with regular, ovulatory cycles. Exclude participants with conditions or medications known to affect cycle regularity or physiological signals.
• Wearable Data: Participants wear the device continuously for 2-5 months to collect longitudinal data on skin temperature, EDA, IBI, and HR [51].
• Ground Truth Labeling: Participants use urinary LH test kits daily to detect the LH surge. The first day of menses is also recorded. This information is used to label the data into four distinct phases [51]:
  • Menses (P): Days of menstrual bleeding.
  • Follicular (F): From the end of menses until before the LH surge.
  • Ovulation (O): The period spanning 2 days before to 3 days after the positive LH test.
  • Luteal (L): From the end of the ovulation phase until the next menses.

III. Feature Extraction and Data Labeling

• Fixed Window Technique: For each cycle, split the data into the four predefined phases (P, F, O, L). Extract features (e.g., mean, variance) from the physiological signals within each phase-specific window [51].
• Rolling Window Technique: Use a sliding window (e.g., 24-hour) to extract features daily, enabling daily phase tracking [51].

IV. Model Training and Validation

• Algorithm Selection: Train multiple classifiers, including Random Forest (RF), Support Vector Machine (SVM), and logistic regression.
• Data Partitioning: Employ a leave-last-cycle-out approach, where data from all but the participant's last cycle are used for training, and the final cycle is used for testing. This evaluates the model's ability to generalize to a new, unseen cycle [51].
• Performance Evaluation: Assess model performance using accuracy, precision, recall, F1-score, and Area Under the Receiver Operating Characteristic Curve (AUC-ROC).

Workflow Visualization

DLMO Assessment Workflow

Menstrual Phase Identification Workflow

The Scientist's Toolkit: Research Reagent Solutions

Table 4: Essential Materials for Phase Prediction Research

Item	Function/Application	Example Specifications/Notes
Salivary Melatonin Assay Kit	Quantifying melatonin concentrations in saliva for DLMO calculation.	Salimetrics Melatonin Assay: Competitive ELISA, sensitivity 1.35 pg/mL, range 0.78–50 pg/mL, no extraction needed [8].
Wrist-worn Wearable Device	Continuous, passive monitoring of physiological signals.	Devices like Empatica E4 or EmbracePlus that capture EDA, IBI, HR, and skin temperature [51].
Dim Red Light Source	Providing safe illumination during nocturnal DLMO sampling without suppressing melatonin.	Light source emitting wavelengths >550 nm; ensures ambient light remains <10-30 lux [8] [12].
Urinary LH Test Kits	Providing the ground truth for ovulation to label menstrual cycle data for ML training.	Common over-the-counter ovulation predictor kits; used to define the "Ovulation" phase [51].
LC-MS/MS Instrumentation	The gold-standard method for hormone quantification, offering superior specificity and sensitivity for melatonin and cortisol [12].	Particularly valuable for low-concentration analytes in saliva and for avoiding cross-reactivity issues of immunoassays [12].

Conclusion

The choice between fixed and variable threshold methods for DLMO calculation is not a one-size-fits-all decision. The fixed threshold offers lower variability and practicality, particularly in large-scale studies, while the variable threshold may capture the physiological onset more accurately for individuals with typical baseline profiles. However, the emergence of more objective methods like the hockey-stick algorithm presents a promising alternative. For researchers and drug development professionals, the selection must be guided by study objectives, population characteristics, and analytical capabilities. Future directions should focus on establishing universal standards, validating remote self-sampling protocols to increase accessibility, and integrating machine learning with multi-parameter wearable data to create robust, non-invasive circadian phase predictors. This evolution will be paramount for advancing personalized chronotherapy and circadian medicine.

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