For decades, sleep science has categorized individuals into two broad chronotypes: “night owls” who prefer late hours and “early birds” who rise with the dawn. However, a groundbreaking new study led by McGill University challenges this binary framework, revealing a far more intricate mosaic of human biological clocks. Published in Nature Communications, the research uncovers five distinct chronotype subtypes, each embodying unique behavioral and health profiles that extend well beyond the simplistic night owl-early bird divide.
Chronotype, a term used to describe a person’s natural inclination toward timing of sleep and wakefulness within a 24-hour period, has long fascinated neuroscientists and health researchers. While earlier studies linked late chronotypes with various adverse health outcomes, these findings were often inconsistent and lacked nuance. The new McGill study offers deeper clarity by demonstrating that broad labels mask a diversity rooted in complex interactions between genetics, environment, and lifestyle, moving the discourse toward more personalized understanding of human circadian biology.
Utilizing cutting-edge artificial intelligence algorithms, the researchers integrated functional brain imaging data with detailed lifestyle questionnaires and comprehensive medical records from over 27,000 participants in the U.K. Biobank—a vast repository of genetic, health, and brain data. This multidisciplinary approach enabled the identification of three distinct subtypes of night owls and two early bird subtypes. Notably, these groups diverge not only in their sleep-wake timing but also in cognitive abilities, emotional regulation, risk-taking behaviors, and susceptibility to various health conditions.
Among the early birds, one subtype demonstrated minimal health complications, underscoring the potential protective aspects of certain circadian profiles. Conversely, the other early bird subtype exhibited strong associations with depressive symptoms, illustrating that early rising does not unequivocally signify mental wellness. Such differentiation within a traditionally monolithic category challenges prevailing assumptions and calls for refinement in both clinical practice and behavioral research paradigms.
The night owl subtypes display even greater heterogeneity. One group excelled in cognitive testing, suggesting enhanced executive functioning and memory performance, yet paradoxically struggled with emotional regulation, highlighting a complex neuropsychological profile. Another subgroup trended towards risk-taking behaviors and presented increased markers of cardiovascular vulnerability, aligning with epidemiological evidence linking late sleep timing to heart disease. The final night owl subtype was characterized by elevated rates of depression, higher tobacco use, and amplified cardiovascular risk, indicating a convergence of lifestyle and biological risk factors.
Danilo Bzdok, senior author and Associate Professor in McGill’s Department of Biomedical Engineering, emphasizes that these multifaceted chronotype classifications emerge from dynamic, intertwined influences rather than simple behavioral choices. “Our findings underscore that chronotypes are not solely about preferred sleep hours but involve brain functional differences shaped by genetic predisposition and environmental exposures,” Bzdok notes. This revelation paves the way for reconceptualizing chronotype beyond mere lifestyle categorization to incorporate neural and systemic physiological dimensions.
These insights bear significant implications for public health and medicine. The heterogeneity in health outcomes among chronotype subgroups signals the inadequacy of uniform sleep hygiene recommendations or work schedule policies. Personalized medicine approaches that account for an individual’s nuanced chronotype subtype could optimize treatment efficacy and improve overall well-being, particularly in domains such as mental health, cardiovascular disease prevention, and cognitive performance enhancement.
Furthermore, the study’s use of AI-enabled integrative methodologies sets a new standard in chronobiology research. By synthesizing multidimensional data, including neuroimaging and health records, the investigation transcended traditional observational designs, exemplifying how machine learning can unravel subtle brain-behavior relationships embedded within population-scale datasets. This paradigm shift illustrates the transformative potential of computational tools in deciphering complex biological phenomena.
The ramifications extend to societal and occupational structures as well. In a post-pandemic landscape marked by remote work and flexible hours, sleep patterns have become increasingly heterogeneous. Understanding the biological diversity underlying chronotypes could inform tailored work schedules that align with individual circadian propensities, potentially boosting productivity and mental health. Consequently, this personalized framework may challenge entrenched norms such as the “9-to-5” workday, promoting healthier, chronobiologically attuned environments.
Looking ahead, the research team aims to explore the genetic foundations of these chronotype subtypes. Investigating whether these profiles originate from innate biological determinants present from birth could clarify causality and facilitate early interventions. Such pursuits promise to deepen the neuroscientific comprehension of circadian regulation and its lifelong impact on health trajectories.
In light of these findings, the longstanding narrative of sleep typologies must evolve. The simplistic dichotomy of night owls versus early birds inadequately reflects the rich and intricate variability inherent in human biological clocks. Recognizing and harnessing this diversity holds profound promise for advancing personalized healthcare, optimizing behavioral interventions, and ultimately enriching quality of life through tailored circadian management.
Subject of Research: Human chronotypes, circadian biology, brain imaging, behavioral and health profiles
Article Title: Latent brain subtypes of chronotype reveal unique behavioral and health profiles across population cohorts
News Publication Date: 22-Dec-2025
Web References:
https://www.nature.com/articles/s41467-025-66784-8
References:
Zhou, L., Bzdok, D., et al. (2025). Latent brain subtypes of chronotype reveal unique behavioral and health profiles across population cohorts. Nature Communications.
Keywords:
Sleep, chronotypes, circadian rhythms, neuroscience, brain imaging, artificial intelligence, mental health, cardiovascular risk, behavioral science
