Digital phenotyping from wearables using AI characterizes psychiatric disorders and identifies genetic associations.

ABSTRACT: Psychiatric disorders are influenced by genetic and environmental factors. However, their study is hindered by limitations on precisely characterizing human behavior. New technologies such as wearable sensors show promise in surmounting these limitations in that they measure heterogeneous behavior in a quantitative and unbiased fashion. Here, we analyze wearable and genetic data from the Adolescent Brain Cognitive Development (ABCD) study. Leveraging >250 wearable-derived features as digital phenotypes, we show that an interpretable AI framework can objectively classify adolescents with psychiatric disorders more accurately than previously possible. To relate digital phenotypes to the underlying genetics, we show how they can be employed in univariate and multivariate genome-wide associati

SUBMITTER: Liu JJ 

PROVIDER: S-EPMC12278733 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature