Major depression has been linked to alterations of the brain's white matter architecture. Major depression has also a considerable genetic component. It is, however, unclear if genetic liability for depression relates directly to the suggested alterations at the brain level. We re-evaluated white matter fiber tract alterations in major depression and aimed to relate polygenic risk for depression in unaffected individuals to these alterations. We conducted a population-based retrospective cohort study with N=17183 participants (n=287 currently depressed, n=5536 formerly depressed, n= 13360 healthy) aged 44 to 82 from the UK Biobank imaging cohort, collected between 2015 and 2020. Depression status was assessed based on questionnaire data. We derived 27 major white matter tracts from diffusion MRI and indexed their integrity according to mean fractional anisotropy. Genetic liability for depression was quantified by polygenic scores based on three recent case-control GWAS. White matter integrity was globally reduced in depression. The reduction was most pronounced on thalamic and intracortical fiber tracts, where the reduction was observed irrespective of current symptom status. Non-depressed individuals showed already a reduction in relevant fiber tracts with increasing polygenic risk, particularly in thalamic radiations. Subsequent in-silico simulations and non-parametric tests confirmed that the polygenic association was stronger than expected given the low-level statistical dependencies between target and discovery samples. White matter integrity on thalamic and association tracts is reduced in depression irrespective of current disease status and relates to the underlying genetic risk factors in unaffected individuals. The observed statistical links between genes, brain, and disorder adhere to the definition of an intermediate phenotype at the brain level.

The authors have declared no competing interest.

This study did not receive any funding

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North West Multi-centre Research Ethics Committee (MREC) gave ethical approval for this work.

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All data produced are available online at ukbiobank.ac.uk.