Comparing personalized brain-based and genetic risk scores for major depressive disorder in large population samples of adults and adolescents

Gladi Thng, Xueyi Shen, Aleks Stolicyn, Mathew A. Harris, Mark J. Adams, Miruna C. Barbu, Alex S.F. Kwong, Sophia Frangou, Stephen M. Lawrie, Andrew M. McIntosh, Liana Romaniuk, Heather C. Whalley

Research output: Contribution to journalArticlepeer-review


Background Major depressive disorder (MDD) is a polygenic disorder associated with brain alterations but until recently, there have been no brain-based metrics to quantify individual-level variation in brain morphology. Here, we evaluated and compared the performance of a new brain-based 'Regional Vulnerability Index' (RVI) with polygenic risk scores (PRS), in the context of MDD. We assessed associations with syndromal MDD in an adult sample (N = 702, age = 59 ± 10) and with subclinical depressive symptoms in a longitudinal adolescent sample (baseline N = 3,825, age = 10 ± 1; 2-year follow-up N = 2,081, age = 12 ± 1). Methods MDD-RVIs quantify the correlation of the individual's corresponding brain metric with the expected pattern for MDD derived in an independent sample. Using the same methodology across samples, subject-specific MDD-PRS and six MDD-RVIs based on different brain modalities (subcortical volume, cortical thickness, cortical surface area, mean diffusivity, fractional anisotropy, and multimodal) were computed. Results In adults, MDD-RVIs (based on white matter and multimodal measures) were more strongly associated with MDD (β = 0.099-0.281, PFDR = 0.001-0.043) than MDD-PRS (β = 0.056-0.152, PFDR = 0.140-0.140). In adolescents, depressive symptoms were associated with MDD-PRS at baseline and follow-up (β = 0.084-0.086, p = 1.38 × 10-4-4.77 × 10-4) but not with any MDD-RVIs (β < 0.05, p > 0.05). Conclusions Our results potentially indicate the ability of brain-based risk scores to capture a broader range of risk exposures than genetic risk scores in adults and are also useful in helping us to understand the temporal origins of depression-related brain features. Longitudinal data, specific to the developmental period and on white matter measures, will be useful in informing risk for subsequent psychiatric illness.

Original languageEnglish
Article numbere44
JournalEuropean Psychiatry
Issue number1
StatePublished - 28 Jul 2022


  • Adolescents
  • genetics
  • imaging
  • major depressive disorder


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