Analysis of 553 sleep clinic patients establishes a novel, six-endotype classification system for circadian phase assessment, reinforcing the clinical value of at-home salivary DLMO testing
CARLSBAD, Calif., July 21, 2026 /PRNewswire/ — Salimetrics LLC, a leading provider of saliva-based bioscience research and clinical testing, today announced the publication of a peer-reviewed study in Sleep Medicine detailing results from its home-based Circadian Phase Assessment program, one of the first real-world clinical implementations of its kind
Can at-home salivary DLMO assessments support a pragmatic alternative to costly, burdensome in-clinic testing?
Dim Light Melatonin Onset (DLMO), the evening rise in melatonin that marks the biological onset of night, has long been considered the gold-standard physiological marker for assessing the circadian phase. Traditionally, however, DLMO testing required hours of in-clinic supervision and repeated blood draws, making it impractical for routine care. Since 2022, Salimetrics has offered sleep-health providers a lower-burden alternative: a physician-supervised, at-home salivary collection protocol supported by structured patient education, optional telehealth guidance, and CLIA-certified laboratory processing.
The newly published research analyzed data from two consecutive studies encompassing 553 patients referred by 66 sleep health providers across 18 clinics in North America, making it among the largest real-world evaluations of home-based DLMO testing published to date
Key findings
- Patient melatonin profiles could be reliably sorted into a six-endotype classification framework (Predicted Onset Window/Typical, Delayed Onset, Advanced Onset, Hypermelatoninemia, Hypomelatoninemia, and Irregular/Multipeak), developed and validated with high inter-rater reliability (92.3% agreement across categories).
- Roughly one in three patients showed a circadian profile within the expected timing window, while the remainder displayed a range of atypical patterns, underscoring substantial biological heterogeneity within sleep clinic populations.
- Among patients with atypical profile patterns who reported symptoms prior to testing, objective circadian data were concordant with at least one presenting complaint in 94.3% of cases, while also revealing that self-reported symptoms alone frequently could not predict a patient’s true underlying circadian phase.
- Notably, a substantial share of patients reporting “delayed sleep” as their primary complaint were found to have advanced, irregular, or amplitude-altered melatonin profiles rather than a delayed circadian phase, a finding the authors say highlights the added diagnostic value of objective testing over symptom-based assessment alone.
What does this mean for clinicians and patients?
“These findings reinforce that symptom presentation alone is often insufficient to characterize a patient’s underlying circadian physiology,” said the study authors¹. “Home-based DLMO testing, implemented pragmatically and at scale, can surface biologically meaningful subgroups that would otherwise go unrecognized, helping clinicians target therapies like light exposure or timed melatonin more precisely.”
The study’s authors note that the observed distribution of endotypes reflects the profiles seen within this specific clinical service model, rather than a population-level prevalence estimate, and they call for prospective research to examine whether endotype-informed treatment decisions will further advance precision sleep medicine and improve patient outcomes
The full publication, “Dim light melatonin onset profile endotypes in a real-world clinical population with home-based, self-collected salivary assessments: Identification, distribution, and potential clinical relevance,” was authored by researchers from Salimetrics, Rebis Health, the University of Colorado’s BioFrontiers Center, and Beth Israel Deaconess Medical Center, and is now available via Sleep Medicine (https://doi.org/10.1016/j.sleep.2026.109053).
¹Ellen R. Stothard, Chris S. Schwartz, Michele L. Okun, Steve W. Granger, Brittany M. Aldrich, Benjamin C. Wiegand , Yannan Liu, David E. McCarty, Robert J. Thomas
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