Digital biomarkers shed light on seasonality of mood disorders

Wrist-based activity sensors worn by people with depression and those without for two weeks provided evidence of a relationship between daily sun exposure and physical activity, according to a study published September 25, 2024 in the open-access journal PLOS Mental Health by Oleg Kovtun and Sandra Rosenthal of Vanderbilt University, USA

Mood disorders are the leading cause of “disability” worldwide. Up to 30% of people with major depressive disorder and bipolar disorder have seasonal symptoms. This phenomenon is now recognized in official diagnostic manuals. Yet, very little is known about the influence of day length (i.e., photoperiod) and sunlight intensity (i.e., sunshine) on seasonal patterns of major depressive disorder and bipolar disorder.

In their study, Kovtun and Rosenthal used a quantitative approach to examine the relationship between measures of sunlight and objectively measured movement activity patterns to begin to understand the environmental factors behind the seasonality of major depressive disorder and bipolar disorder.

They used motor activity recordings collected by accelerometers (which measure the rate of change in an object’s speed over time) from 23 people with unipolar or bipolar depression and 32 people without depression. Participants were recruited from the University of Bergen, Norway.

Results revealed relationships between daytime physical activity, depressive state, photoperiod, and solar insolation. In particular, more depressive states were associated with lower daytime activity, while daytime activity increased with photoperiod and solar insolation. Additional findings suggest that the impact of solar insolation on physical activity may differ between depressed and non-depressed individuals.

This finding may indicate that depressed individuals have an altered physiological link between energy intake (i.e., sunlight) and physical activity. On the other hand, it is also possible that increased sedentary behavior leads to reduced time spent outdoors and does not allow depressed individuals to take advantage of the benefits of sunlight exposure.

According to the authors, the study presents a generalizable strategy for understanding the complex interplay between sunlight, physical activity, and depressive state using open-source digital tools. The ability to identify mood disorders, particularly in seasonally sensitive individuals, using passive digital biomarker data holds promise for informing next-generation predictive and personalized diagnostics in mental health.

Specifically, a digital biomarker, such as motor activity patterns derived from an accelerometer, could form the basis of an early warning system that alerts a clinician to initiate rapid intervention.

Integrating objectively measured markers of sun exposure (i.e., solar insolation data collected by NASA or accelerometer-measured light exposure) could further improve the predictive power of these tools and lay the foundation for personalized models for individuals susceptible to mood disorders related to seasonal patterns.

Rosenthal and Kovtun add: “People with seasonal mood disorder may not yet recognize the pattern of their illness. One goal of our study is to motivate the development of digital tools to support clinicians and help people self-manage their symptoms.”