Abstract
AbstractAddressing heterogeneity in depression is critically important to overcome replicability challenges and gain insights into neural etiology. We developed a novel hierarchical framework to systematically disentangle clinical and neurobiological sources of heterogeneity utilizing population data from the UK Biobank. Firstly, we defined patient subgroups who uniquely shared isolated clinical characteristics of depression (e.g., symptoms of anhedonia, depressed mood, and somatic disturbance; severity indices of lifetime chronicity and acute impairment; and late onset). Our results revealed distinct neurobiological features robustly associated with each clinically isolated subgroup, providing symptom-level insights into the neural etiology of depression, and supporting a one-to-one mapping between clinical and neurobiological sources of heterogeneity. Secondly, we investigated residual neurobiological heterogeneity within each subgroup using data-driven clustering. Our findings revealed stable neurobiological clusters that differed in cognitive ability within two clinical subgroups (chronicity and acute impairment), providing evidence that multiple neurobiological mechanisms may give rise to the same clinical presentation (many-to-one mapping).
Publisher
Cold Spring Harbor Laboratory
Cited by
3 articles.
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