Recognizing the pivotal role of circadian rhythm in the human aging process and its scalability through wearables, we introduce CosinorAge, a novel digital biomarker of aging developed from wearable-derived circadian rhythmicity from 80,000 midlife and older adults in the UK and US. A one-year increase in CosinorAge corresponded to 8-12% higher all-cause and cause-specific mortality risks and 3-14% increased prospective incidences of age-related diseases. CosinorAge also captured a non-linear decline in resilience and physical functioning, evidenced by an 8-33% reduction in self-rated health and a 3-23% decline in health-related quality of life score, adjusting for covariates and multiple testing. The associations were robust in sensitivity analyses and external validation using an independent cohort from a disparate geographical region using a different wearable device. Moreover, we illustrated a heterogeneous impact of circadian parameters associated with biological aging, with young (<45 years) and fast agers experiencing a substantially delayed acrophase with a 25-minute difference in peak timing compared to slow agers, diminishing to a 7-minute difference in older adults (>65 years). Our findings underscore CosinorAge’s potential as a scalable, economic, and digital solution for promoting healthy longevity, elucidating the critical and multifaceted circadian rhythmicity in aging processes. Consequently, our research contributes to advancing preventive measures in digital medicine.

Prolonged systemic inflammation is recognized as a major contributor to the development of various chronic inflammatory diseases. Daily measurements of inflammatory biomarkers can significantly improve disease monitoring of systemic inflammation, thus contributing to reducing the burden on patients and the entire healthcare system. There exists, however, no scalable, cost-efficient, and non-invasive biomarker for remote assessment of systemic inflammation. To this end, we propose a novel multi-modal, non-invasive approach for measuring inflammatory biomarkers. We aim to evaluate the relationship between the levels of inflammatory biomarkers in serum (gold standard) and those measured non-invasively in urine, sweat, saliva, exhaled breath, stool, and core body temperature in patients with systemic inflammation. This study is a single-center, cross-sectional study and includes a total of 20 participants (10 systemic inflammation patients and 10 control patients). Eligible participants provide serum, urine, sweat, saliva, exhaled breath, and stool samples for biomarker analyses. Core body temperature is measured using a sensor. The primary endpoint is the level of C-reactive protein. The secondary endpoints are interleukin (IL)-1β, IL-6, IL-8, IL-10, and tumor necrosis factor-α levels. The tertiary endpoints are fractional exhaled nitric oxide, calprotectin, and core body temperature. Shapiro-Wilk test will be used to evaluate the normality of the distribution in each variable. We will perform the two-tailed t-test (or Wilcoxon rank-sum test, if non-normal) to compare the levels of inflammatory biomarkers between patients with systemic inflammations and controls. Pearson and Spearman correlation coefficients will assess the relationship between non-invasive methods and the serum. A total of 20 participants participated in the study measurements between February and September 2023. Participants were on average 52.8 (range 24-82, SD 14.4) years of age, and 70% (n=14) of them were women. The analysis results reporting findings are expected to be published in the fall of 2024. This is a proof-of-concept study evaluating the feasibility of non-invasive, multi-modal inflammatory biomarker discovery. Promising results could lead to the creation of non-invasive and digital biomarkers for systemic inflammation, which could be implemented for a larger, prospective, longitudinal cohort study.

We introduce the Bitemporal Lens Model, a comprehensive methodology for chronic disease prevention using digital biomarkers. The Bitemporal Lens Model integrates the change-point model, focusing on critical disease-specific parameters, and the recurrent-pattern model, emphasizing lifestyle and behavioral patterns, for early risk identification. Results-By incorporating both the change-point and recurrent-pattern models, the Bitemporal Lens Model offers a comprehensive approach to preventive healthcare, enabling a more nuanced understanding of individual health trajectories, demonstrated through its application in cardiovascular disease prevention. We explore the benefits of the Bitemporal Lens Model, highlighting its capacity for personalized risk assessment through the integration of two distinct lenses. We also acknowledge challenges associated with handling intricate data across dual temporal dimensions, maintaining data integrity, and addressing ethical concerns pertaining to privacy and data protection. The Bitemporal Lens Model presents a novel approach to enhancing preventive healthcare effectiveness.

Repeated disruptions in circadian rhythms are associated with implications for health outcomes and longevity. The utilization of wearable devices in quantifying circadian rhythm to elucidate its connection to longevity, through continuously collected data remains largely unstudied. In this work, we investigate a data-driven segmentation of the 24-h accelerometer activity profiles from wearables as a novel digital biomarker for longevity in 7,297 U.S. adults from the 2011–2014 National Health and Nutrition Examination Survey. Using hierarchical clustering, we identified five clusters and described them as follows - “High activity”, “Low activity”, “Mild circadian rhythm (CR) disruption”, “Severe CR disruption”, and “Very low activity”. Young adults with extreme CR disturbance are seemingly healthy with few comorbid conditions, but in fact associated with higher white blood cell, neutrophils, and lymphocyte counts (0.05–0.07 log-unit, all p < 0.05) and accelerated biological aging (1.42 years, p < 0.001). Older adults with CR disruption are significantly associated with increased systemic inflammation indexes (0.09–0.12 log-unit, all p < 0.05), biological aging advance (1.28 years, p = 0.021), and all-cause mortality risk (HR = 1.58, p = 0.042). Our findings highlight the importance of circadian alignment on longevity across all ages and suggest that data from wearable accelerometers can help in identifying at-risk populations and personalize treatments for healthier aging.