Genetic schizophrenia risk variants jointly modulate total brain and white matter volume

Abstract

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.

Figure 1. The variance explained of different phenotypes by PSS for different P_cutoff-SZ SNP sets

SZ= schizophrenia, TB= total brain volume, WM= white matter volume, GM= gray matter volume, IC= intracranial volume. y-axis = explained variance by the PSS of this phenotype. For dichotomous traits Nagelkerke’s pseudo R² was compared between a model with only covariates and a model including covariates and the PSS. For continuous traits the difference in R² was used. Intracranial volume and sex were included as negative controls. For more information see supplementary table 1.

Figure 2. Schematic representation of the SNPs involved in different phenotypes

The large green circle represents all 117,924 SNPs included after quality control and removing SNPs in LD. The yellow circle represents the 14,751 SNPs having the largest effect on schizophrenia in the target sample. The small white area stands for the subset of these SNPs (n=2,020) that do also explain variance in white matter volume. There could be more SNPs influencing white matter volume (represented by the translucent white circle), but these were not investigated. The small blue circle represents the 186 SNPs who are likely to contribute most to both schizophrenia and white matter volume. The size of the circles represents the number of SNPs in that group.