| Title: | Contributions of polygenic risk and disease status to grey matter abnormalities in major depression |
| Journal: | Biological Psychiatry Cognitive Neuroscience and Neuroimaging |
| Published: | 23 Dec 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38142967/ |
| DOI: | https://doi.org/10.1016/j.bpsc.2023.12.001 |
Publication 9130
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Abstract
BACKGROUND: Gray matter (GM) abnormalities in depression are potentially attributable to some combination of trait, state, and illness history factors. Here, we sought to determine the contributions of polygenic risk for depression, depressive disease status, and the interaction of these factors to these GM abnormalities.</p>
METHODS: We conducted a cross-sectional comparison using a 2 × 3 factorial design examining effects of polygenic risk for depression (lower vs. upper quartile) and depression status (never depressed, currently depressed, or remitted depression) on regional GM concentration and GM volume. Participants were a subset of magnetic resonance imaging-scanned UK Biobank participants comprising 2682 people (876 men, 1806 women) algorithmically matched on 16 potential confounders.</p>
RESULTS: In women but not men, we observed that elevated polygenic risk for depression was associated with reduced cerebellar GM volume. This deficit occurred in salience and dorsal attention network regions of the cerebellum and was associated with poorer performance on tests of attention and executive function but not fluid intelligence. Moreover, in women with current depression compared to both women with remitted depression and women who never had depression, we observed GM reductions in ventral and medial prefrontal, insular, and medial temporal regions. These state-related abnormalities remained when accounting for antidepressant medication status.</p>
CONCLUSIONS: Neuroanatomical deficits attributed broadly to major depression are more likely due to an aggregation of independent factors. Polygenic risk for depression accounted for cerebellar structural abnormalities that themselves accounted for cognitive deficits observed in this disorder. Medial and ventral prefrontal, insular, and temporal cortex deficits constituted a much larger proportion of the aggregate deficit and were attributable to the depressed state.</p>
6 Authors
- Robin Kämpe
- Elisabeth R Paul
- Lars Östman
- Markus Heilig
- David M Howard
- J Paul Hamilton
1 Application
| Application ID | Title |
|---|---|
| 49037 | Reliable neural signatures in major depressive disorder: A machine-learning investigation of a large dataset. |
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