Schizophrenia risk variants modulate white matter volume across the psychosis spectrum: evidence from two independent cohorts.

Viola Oertel-Knöchel,Kiran Mantripragada,Michael J Owen,David E.J Linden,Christian Knöchel,Thomas M Lancaster,Helena Storchak,Alina Jurcoane,Britta Reinke,Michael C O’Donovan,Katherine E Tansey,Michael Stäblein,Jonathan Kniep,David Prvulovic

doi:10.1016/j.nicl.2015.03.005

Abstract

Polygenic 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.

Highlights

Neurobiological models of schizophrenia (SZ) and bipolar disorder (BD) implicate altered interregional connectivity and suggest that some of the changes in white matter structure may be heritable (Kaymaz and van Os, 2009; McDonald et al, 2004; McIntosh et al, 2006)
Considering that disrupted white matter has been repeatedly observed in relatives of patients with schizophrenia and patients with bipolar disorder (Emsell and McDonald, 2009; Francis et al, 2013; Hasler et al, 2006; Matsuo et al, 2012; McDonald et al, 2004; McIntosh et al, 2006; Oertel-Knochel et al, 2012; van Haren et al, 2012), we suggest that common genetic risk factors should contribute to the neurobiological mechanisms that underlie volumetric white matter disturbances
We aim to explore the association between additive effects of these seven schizophrenia risk SNPs (7-SNP SZ-RPS) with white matter volume

Summary

Introduction

Neurobiological models of schizophrenia (SZ) and bipolar disorder (BD) implicate altered interregional connectivity and suggest that some of the changes in white matter structure may be heritable (Kaymaz and van Os, 2009; McDonald et al, 2004; McIntosh et al, 2006). Considering that disrupted white matter has been repeatedly observed in relatives of patients with schizophrenia and patients with bipolar disorder (Emsell and McDonald, 2009; Francis et al, 2013; Hasler et al, 2006; Matsuo et al, 2012; McDonald et al, 2004; McIntosh et al, 2006; Oertel-Knochel et al, 2012; van Haren et al, 2012), we suggest that common genetic risk factors should contribute to the neurobiological mechanisms that underlie volumetric white matter disturbances At present, it is not known which molecular pathways are responsible for modulating white matter at the genetic level, and in the present study, we employ an RPS model calculated only using robust, genome-wide significant SNPs for schizophrenia (GWAS Consortium, 2011). We hypothesise that larger risk profile scores are associated with reduced white matter volume across the psychosis spectrum

Objectives

Methods

Results

Conclusion