RT Journal Article
SR Electronic
T1 GWAS results for educational attainment aid in identifying genetic heterogeneity of schizophrenia
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 114405
DO 10.1101/114405
A1 Vikas Bansal
A1 Marina Mitjans
A1 Casper A.P. Burik
A1 Richard Karlsson Linnér
A1 Aysu Okbay
A1 Cornelius A. Rietveld
A1 Martin Begemann
A1 Stefan Bonn
A1 Stephan Ripke
A1 Ronald de Vlaming
A1 Michel G. Nivard
A1 Hannelore Ehrenreich
A1 Philipp D. Koellinger
YR 2017
UL http://biorxiv.org/content/early/2017/08/02/114405.abstract
AB Higher educational attainment (EA) is known to have a protective effect on the severity of schizophrenia (SZ). However, recent studies have found a small positive genetic correlation between EA and SZ. We investigated possible causes of this counterintuitive finding using genome-wide association (GWAS) results for EA and SZ (N = 443,581) and a replication cohort (1,169 controls and 1,067 cases) with high-quality SZ phenotypes. We found strong genetic dependence between EA and SZ that cannot be explained by chance, linkage disequilibrium, or assortative mating. Instead, several genes seem to have pleiotropic effects on EA and SZ, but without a clear pattern of sign concordance. Genetic heterogeneity in both phenotypes is the most likely explanation of this finding. This insight can be exploited by using a combination of EA and SZ GWAS results to improve the polygenic prediction of clinical symptoms and disease severity of SZ. In particular, although a polygenic score for SZ is robustly associated with case-control status, it does not predict any of the SZ symptoms or disease severity. In contrast, co-dependent polygenic scores that split the SZ score into two parts based on the sign concordance of SNPs for SZ and EA predict symptoms and disease severity in patients to some extent. Furthermore, using EA as a proxy-phenotype for SZ, we isolate FOXO6 and SLITRK1 as additional statistically plausible candidate genes for SZ.