{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T19:02:30Z","timestamp":1772132550348,"version":"3.50.1"},"posted":{"date-parts":[[2026,2,24]]},"group-title":"Endocrinology (including Diabetes Mellitus and Metabolic Disease)","reference-count":25,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T00:00:00Z","timestamp":1771891200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,2,24]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:p>The daily cortisol cycle is a critical indicator of hypothalamic-pituitary-adrenal (HPA) axis function. The current analytical approaches produce several outputs difficult to integrate into simple statistical models, clinical workflows, and ML\/AI pipelines requiring single-value inputs. We developed the Cortisol Sine Score (CSS), a model-free scalar metric that quantifies daily cortisol exposure by computing a weighted sum of cortisol measurements across the day, using sine-transformed time-of-day weights. The CSS produces positive values for morning-dominant patterns, negative values for evening-shifted profiles, and near-zero values for flattened rhythms characteristic of chronic stress and circadian disruption. We validated the CSS performance in 3,006 samples from 501 pregnant women enrolled in the March of Dimes program, with cortisol values measured at 6 time points per day collected during the second trimester of pregnancy. The CSS showed strong correlations with observed and model-estimated amplitude and acrophase from Cosinor regression and JTK_CYCLE approaches, with excellent classifying performance (AUC=0.89, high versus low). The CSS successfully captured established associations between social disadvantage and cortisol dysregulation, and demonstrated utility in predicting gut microbiome composition in metagenomic analyses. Importantly, the CSS maintains excellent fidelity to the full 6-sample protocol with as few as 3-4 daily measurements. The 4-sample protocol achieves great performance (r = 0.952, MAE = 0.087) while reducing participant burden. The 06:00 time point was identified as essential for accurate CSS quantification. The CSS bridges the gap between circadian analysis and practical implementation by providing a simple, interpretable, and robust assessment of cortisol daily cycle in large-scale epidemiological studies, clinical screening, and biomedical sensors.<\/jats:p>\n                <jats:sec>\n                  <jats:title>Highlights<\/jats:title>\n                  <jats:list list-type=\"bullet\">\n                    <jats:list-item>\n                      <jats:p>Current state-of-the-art approaches estimating the daily cortisol exposures produce multi-output information difficult to implement in simple statistical analyses or ML\/AI multi-omics approaches<\/jats:p>\n                    <\/jats:list-item>\n                    <jats:list-item>\n                      <jats:p>Cortisol Sine Score is a novel model-free scalar metric expressing cortisol daily exposure and rhythmicity (morning vs evening exposure)<\/jats:p>\n                    <\/jats:list-item>\n                    <jats:list-item>\n                      <jats:p>Cortisol Sine Score was validated using 3006 salivary samples from clinical data and golden standards in circadian analyses such as Cosinor and JTK_CYCLE<\/jats:p>\n                    <\/jats:list-item>\n                    <jats:list-item>\n                      <jats:p>Cortisol Sine Score was the top performer in our benchmarking approach predicting association with social disadvantage and gut microbiome composition<\/jats:p>\n                    <\/jats:list-item>\n                    <jats:list-item>\n                      <jats:p>Reliable with 3-4 daily samples, reducing participant burden<\/jats:p>\n                    <\/jats:list-item>\n                    <jats:list-item>\n                      <jats:p>Open-source R package CortSineScore democratizes cortisol cycle analysis<\/jats:p>\n                    <\/jats:list-item>\n                  <\/jats:list>\n                <\/jats:sec>","DOI":"10.64898\/2026.02.23.26346831","type":"posted-content","created":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T03:55:14Z","timestamp":1771991714000},"source":"Crossref","is-referenced-by-count":0,"title":["Simplifying Daily Cortisol Cycle Analysis: Validation and Benchmarking of the Cortisol Sine Score Against Cosinor and JTK_CYCLE models"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9498-6621","authenticated-orcid":false,"given":"Simone","family":"Anz\u00e0","sequence":"first","affiliation":[{"name":"Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, St. Louis, MO, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bruce A.","family":"Rosa","sequence":"additional","affiliation":[{"name":"Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, St. Louis, MO, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Max P.","family":"Herzberg","sequence":"additional","affiliation":[{"name":"Department of Psychology, University of Georgia, Athens, GA, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giljae","family":"Lee","sequence":"additional","affiliation":[{"name":"Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, St. Louis, MO, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erik D.","family":"Herzog","sequence":"additional","affiliation":[{"name":"Department of Biology, Washington University in St. Louis, St. Louis, MO, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peinan","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Obstetrics & Gynecology, Washington University School of Medicine in St. Louis, St. Louis, MO, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6820-446X","authenticated-orcid":false,"given":"Sarah K.","family":"England","sequence":"additional","affiliation":[{"name":"Department of Obstetrics & Gynecology, Washington University School of Medicine in St. Louis, St. Louis, MO, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"I. Malick","family":"Ndao","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Washington University School of Medicine in St. Louis, St. Louis, MO, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John","family":"Martin","sequence":"additional","affiliation":[{"name":"Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, St. Louis, MO, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christopher D.","family":"Smyser","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Washington University School of Medicine in St. Louis, St. Louis, MO, United States"},{"name":"Department of Neurology, Washington University School of Medicine in St. Louis, MO 63110"},{"name":"Department of Radiology, Washington University School of Medicine in St. Louis, MO 63110"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cynthia E.","family":"Rogers","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Washington University School of Medicine in St. Louis, St. Louis, MO, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Deanna M.","family":"Barch","sequence":"additional","affiliation":[{"name":"Department of Radiology, Washington University School of Medicine in St. Louis, MO 63110"},{"name":"Department of Psychological and Brain Sciences, Washington University in St. Louis, MO 63110"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Caroline","family":"Hoyniak","sequence":"additional","affiliation":[{"name":"Department of Psychology, University of Georgia, Athens, GA, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ronald","family":"McCarthy","sequence":"additional","affiliation":[{"name":"Department of Obstetrics & Gynecology, Washington University School of Medicine in St. Louis, St. Louis, MO, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joan","family":"Luby","sequence":"additional","affiliation":[{"name":"Department of Psychology, University of Georgia, Athens, GA, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Barbara B.","family":"Warner","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Washington University School of Medicine in St. Louis, St. Louis, MO, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Makedonka","family":"Mitreva","sequence":"additional","affiliation":[{"name":"Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, St. Louis, MO, United States"},{"name":"McDonnell Genome Institute, Washington University School of Medicine in St. Louis, MO, United States"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"54368","reference":[{"key":"2026022610151456000_2026.02.23.26346831v1.1","doi-asserted-by":"publisher","DOI":"10.1016\/j.physbeh.2006.08.025"},{"key":"2026022610151456000_2026.02.23.26346831v1.2","doi-asserted-by":"publisher","DOI":"10.1210\/clinem\/dgae202"},{"key":"2026022610151456000_2026.02.23.26346831v1.3","doi-asserted-by":"publisher","DOI":"10.1017\/S0954579419001779"},{"key":"2026022610151456000_2026.02.23.26346831v1.4","doi-asserted-by":"publisher","DOI":"10.1016\/S0306-4530(02)00108-7"},{"key":"2026022610151456000_2026.02.23.26346831v1.5","doi-asserted-by":"publisher","DOI":"10.1186\/1742-4682-11-16"},{"key":"2026022610151456000_2026.02.23.26346831v1.6","unstructured":"[6] JTK_CYCLE: An Efficient Nonparametric Algorithm for Detecting Rhythmic Components in Genome-Scale Data Sets - Michael E. 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