The Relationship Between Family History of Depression and Brain Structure and Function: A Systematic Review of Large Cohorts. Review uri icon

Overview

abstract

  • Family history (FH) of major depression is a well-replicated risk factor for developing the disorder. Studying individuals who may be at high familial risk but are symptom free may allow us to better distinguish mechanisms predisposing individuals to depression from mechanisms that arise from having the disorder. Neuroimaging studies using such high-risk designs have suggested several cortical and subcortical regions that may contribute to depression susceptibility; however, specificity, timing of mechanisms, and long-term clinical implications remain unclear. As developing de novo cohorts to address these questions would be resource intensive, we sought to identify existing longitudinal cohorts that could be used to examine the effects of FH on brain imaging outcomes rigorously and cost-effectively, to determine the way FH was assessed in these cohorts, and to summarize their major findings published to date. A structured PubMed search identified 25 longitudinal cohorts (13 countries), each containing ≥1000 participants, direct- or informant-based FH, psychiatric measures, and ≥1 magnetic resonance imaging collection. Across publications from these cohorts, subcortical (particularly striatum, amygdala) and cortical (anterior cingulate, prefrontal) regions most frequently showed alterations in association with familial risk. However, current evidence for whether these regions predict psychopathology is limited, and the question should be examined in future studies as offspring in these cohorts age. This comprehensive review should also serve as a resource for further analyses of existing data from cohorts with FH and neuroimaging data in the context of depression and other disorders.

publication date

  • January 15, 2026

Identity

Scopus Document Identifier

  • 105031861126

Digital Object Identifier (DOI)

  • 10.1016/j.biopsych.2026.01.006

PubMed ID

  • 41547389