Mobile Technology to Identify Behavioral Mechanisms Linking Genetic Variation and Depression

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Project Summary/Abstract Large scale genome-wide association studies have identified genetic variation definitively associated with major depression. To translate this advancement into improved diagnosis, monitoring, and treatment, a critical next step is to elucidate the behavioral mechanisms linking the implicated genetic variation with depression. Unfortunately, the large-scale studies that have identified associated variants have typically employed single time point and limited phenotypic assessments that are not suited to study mechanisms linking genes and depression, a chronic multi-modal disease. Our long-term goal is to elucidate the pathophysiological architecture underlying depression to facilitate the development of improved treatments. Our objective in the parent R01 application is to understand how genetic variants associated with the development of depression exert their effect. Medical internship, the first year of professional physician training, presents a unique situation in which we can prospectively predict the onset of a uniform, chronic stressor and follow the development of depressive symptoms. We have found that rates of depression increase dramatically, from 4% prior to internship to 26% during internship year. Our intern cohort is an ideal population to closely monitor the development of depression with recent mobile health technology as a tool to follow these individuals in real- time, with objective measures. For the current grant period, we proposed the following three specific aims: 1) Identify data driven features, derived from mobile data elements, that predict short-term risk for mood changes and depressive episodes. 2) Identify genetic variants associated with depression under stress. 3) Identify relationship between depression-associated genetic variation and objective depression-associated mobile features. The grant period has been highly productive to date, with data collected from the study as primary data source for papers published in New England Journal of Medicine, BMJ, Annals of Internal Medicine, Nature Human Behavior, American Journal of Psychiatry, Biological Psychiatry, NPJ Digital Medicine among other journals. Unfortunately, the COVID-19 pandemic disrupted this study in multiple ways and has delayed completion of the Aims. With university shutdowns and loss of childcare, the availability and bandwidth for our clinical recruitment and analysis staff were substantially reduced. Similarly, with the burden COVID-19 placed on our recruitment population of training physicians, our recruitment rate was also compromised. Further, the genotyping proposed as part of the current R01 through was delayed by 9 months because of COVID-19 related delays at the Michigan Sequencing Core. This supplement seeks to provide funding for personnel to avoid hardship and allow completion of the study aims.