• Viola Oertel-Knöchel, Thomas M Lancaster, Christian Knöchel, Michael Stäblein, Helena Storchak, Britta Reinke, Alina Jurcoane, Jonathan Kniep, David Prvulovic, Kiran Mantripragada, Katherine E Tansey, Michael C O'Donovan, Michael J Owen, and David E J Linden.
• Dept. of Psychiatry, Psychosomatic Medicine and Psychotherapy, Laboratory for Neuroimaging, Goethe Univ., Frankfurt a. M, Germany.
• Neuroimage Clin. 2015 Jan 1; 7: 764-70.

AbstractPolygenic risk scores, based on risk variants identified in genome-wide-association-studies (GWAS), explain a considerable portion of the heritability for schizophrenia (SZ) and bipolar disorder (BD). However, little is known about the combined effects of these variants, although polygenic neuroimaging has developed into a powerful tool of translational neuroscience. In this study, we used genome wide significant SZ risk variants to test the predictive capacity of the polygenic model and explored potential associations with white matter volume, a key candidate in imaging phenotype for psychotic disorders. By calculating the combined additive schizophrenia risk of seven SNPs (significant hits from a recent schizophrenia GWAS study), we show that increased additive genetic risk for SZ was associated with reduced white matter volume in a group of participants (n = 94) consisting of healthy individuals, SZ first-degree relatives, SZ patients and BD patients. This effect was also seen in a second independent sample of healthy individuals (n = 89). We suggest that a moderate portion of variance (~4%) of white matter volume can be explained by the seven hits from the recent schizophrenia GWAS. These results provide evidence for associations between cumulative genetic risk for schizophrenia and intermediate neuroimaging phenotypes in models of psychosis. Our work contributes to a growing body of literature suggesting that polygenic risk may help to explain white matter alterations associated with familial risk for psychosis.

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