BACKGROUND: Thousands of common single nucleotide polymorphisms (SNPs) are weakly associated with schizophrenia. It is likely that subsets of disease-associated SNPs are associated with distinct heritable disease-associated phenotypes. Therefore, we examined the shared genetic susceptibility modulating schizophrenia and brain volume. METHODS: Odds ratios for genome-wide SNP data were calculated in the sample collected by the Psychiatric Genome-wide Association Study Consortium (8690 schizophrenia patients and 11,831 control subjects, excluding subjects from the present study). These were used to calculate individual polygenic schizophrenia (risk) scores in an independent sample of 152 schizophrenia patients and 142 healthy control subjects with available structural magnetic resonance imaging scans. RESULTS: In the entire group, the polygenic schizophrenia score was significantly associated with total brain volume (R2 = .048, p = 1.6 × 10(-4)) and white matter volume (R2 = .051, p = 8.6 × 10(-5)) equally in patients and control subjects. The number of (independent) SNPs that substantially influenced both disease risk and white matter (n = 2020) was much smaller than the entire set of SNPs that modulated disease status (n = 14,751). From the set of 2020 SNPs, a group of 186 SNPs showed most evidence for association with white matter volume and an explorative functional analysis showed that these SNPs were located in genes with neuronal functions. CONCLUSIONS: These results indicate that a relatively small subset of schizophrenia genetic risk variants is related to the (normal) development of white matter. This, in turn, suggests that disruptions in white matter growth increase the susceptibility to develop schizophrenia.
BACKGROUND: Thousands of common single nucleotide polymorphisms (SNPs) are weakly associated with schizophrenia. It is likely that subsets of disease-associated SNPs are associated with distinct heritable disease-associated phenotypes. Therefore, we examined the shared genetic susceptibility modulating schizophrenia and brain volume. METHODS: Odds ratios for genome-wide SNP data were calculated in the sample collected by the Psychiatric Genome-wide Association Study Consortium (8690 schizophrenia patients and 11,831 control subjects, excluding subjects from the present study). These were used to calculate individual polygenic schizophrenia (risk) scores in an independent sample of 152 schizophrenia patients and 142 healthy control subjects with available structural magnetic resonance imaging scans. RESULTS: In the entire group, the polygenic schizophrenia score was significantly associated with total brain volume (R2 = .048, p = 1.6 × 10(-4)) and white matter volume (R2 = .051, p = 8.6 × 10(-5)) equally in patients and control subjects. The number of (independent) SNPs that substantially influenced both disease risk and white matter (n = 2020) was much smaller than the entire set of SNPs that modulated disease status (n = 14,751). From the set of 2020 SNPs, a group of 186 SNPs showed most evidence for association with white matter volume and an explorative functional analysis showed that these SNPs were located in genes with neuronal functions. CONCLUSIONS: These results indicate that a relatively small subset of schizophrenia genetic risk variants is related to the (normal) development of white matter. This, in turn, suggests that disruptions in white matter growth increase the susceptibility to develop schizophrenia.
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