Digital biomarkers shed light on seasonality in mood disorders

According to a study published in the open access journal Nature on September 25, 2024, wrist-worn activity sensors worn by people with and without depression for two weeks provided evidence of a relationship between daily sunlight exposure and physical activity. PLOS Mental Health Oleg Kovtun and Sandra Rosenthal (Vanderbilt University, USA)

Mood disorders are a leading cause of disability worldwide. Up to 30% of patients with major depressive disorder and bipolar disorder exhibit seasonal symptom patterns; this phenomenon is now recognized in official diagnostic manuals. However, little is known about the effects of day length (i.e., photoperiod) and daylight intensity (i.e., solar radiation) on the seasonal pattern of major depressive disorder and bipolar disorder.

In their study, Kovtun and Rosenthal used a quantitative approach to examine the relationship between measurements of daylight and objectively measured patterns of motor activity to begin to understand the environmental factors that drive seasonality in major depressive disorder and bipolar disorder.

The researchers used motor activity records collected with an accelerometer (which measures the rate of change of an object’s velocity over time) from 23 patients with unipolar or bipolar depression and 32 non-depressed participants. The subjects were recruited at the University of Bergen in Norway.

Findings revealed relationships between daytime physical activity, depression, day length, and solar exposure. In particular, greater depression was associated with less daytime activity, and daytime activity increased with increasing day length and solar exposure. Additional findings suggest that the effects of solar exposure on physical activity may differ between depressed and non-depressed individuals.

This finding may indicate that depressed individuals have an altered physiological association between energy intake (i.e., solar exposure) and physical activity, whereas increased sedentary behaviour may reduce time spent outdoors, preventing depressed individuals from reaping the benefits of sun exposure.

According to the authors, this study presents a generalizable strategy to understand the complex interplay between sunlight, physical activity, and depression using open-source digital tools. The ability to identify mood disorders using passive digital biomarker data, especially in seasonally vulnerable individuals, is expected to inform the next generation of predictive and personalized diagnostics in mental health.

Specifically, digital biomarkers such as motor activity patterns derived from accelerometers could be the basis of early warning systems that alert clinicians to initiate timely interventions.

Incorporating objectively measured sun exposure markers (such as solar radiation data collected by NASA or light exposure measured by accelerometers) could further enhance the predictive power of these tools and lay the foundation for personalized models targeted at individuals who are more susceptible to seasonal patterns of mood disturbance.

Rosenthal and Kovtun further note, “Patients with seasonal mood disorder may not yet recognize patterns in their illness. One goal of our research is to facilitate the development of digital tools to assist clinicians and empower patients to self-manage their symptoms.”