Adversity as the key feature: neuroimaging profiles of subtypes from multiple depression risk factors

Depression arises from diverse environmental and psychosocial risk factors, yet how these factors co-occur within individuals remains unclear. This study identifies profiles of multiple depression risk factors and examines their clinical and neuroimaging correlates.

Among 157,317 UK Biobank participants completing the mental health questionnaire, 24 psychological, environmental, and lifestyle factors were assessed using latent class analysis. Logistic regression evaluated associations between profiles and depression outcomes; linear models examined neuroimaging differences. Imaging transcriptomics and gene-set enrichment analyses contextualized neural findings.

Three latent profiles emerged: low risk profile (81.09%), childhood adversity-related profile (CA; 10.95%), and adulthood adversity-related profile (AA; 7.97%). Both the CA profile and AA profile show significantly higher depression risk than the low risk profile. Compared with the low risk profile, the AA profile shows a 2.7-fold increase in depression risk (OR = 3.701, 95%CI: 3.532~3.881), with appetite change and psychomotor symptoms being more prominent. The CA profile shows a 2.5-fold increase in depression risk (OR = 3.507, 95%CI: 3.353~3.607), with worthlessness, sleep problems, and suicidal ideation being more prominent. Both adversity profiles showed lower white-matter FA in cerebellar-thalamic and associative pathways. The CA profile additionally showed reduced FA in occipital tracts, whereas the AA profile showed greater reductions in prefrontal pathways and lower GMV in insula, amygdala, and cerebellar lobules VIIIb/IX, alongside higher occipital pole GMV. The most pronounced nominally significant difference between CA and AA centered on the right amygdala. Genes overlapping subcortical GMV differences were enriched for psychiatric disorders.

Life-course adversity may be a key feature associated with distinct clinical and neural signatures, helping identify subgroups with co-occurring vulnerabilities. These patterns warrant further investigation in future studies.