TY - JOUR

T1 - Improved Detection of Common Variants Associated with Schizophrenia by Leveraging Pleiotropy with Cardiovascular-Disease Risk Factors

AU - Andreassen, Ole A

AU - Djurovic, Srdjan

AU - Thompson, Wesley K

AU - Schork, Andrew J

AU - Kendler, Kenneth S

AU - O'Donovan, Michael C

AU - Rujescu, Dan

AU - Werge, Thomas

AU - van de Bunt, Martijn

AU - Morris, Andrew P

AU - McCarthy, Mark I

AU - Roddey, J Cooper

AU - McEvoy, Linda K

AU - Desikan, Rahul S

AU - Dale, Anders M

AU - International Consortium for Blood Pressure GWAS

N1 - Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

PY - 2013/2

Y1 - 2013/2

N2 - Several lines of evidence suggest that genome-wide association studies (GWASs) have the potential to explain more of the "missing heritability" of common complex phenotypes. However, reliable methods for identifying a larger proportion of SNPs are currently lacking. Here, we present a genetic-pleiotropy-informed method for improving gene discovery with the use of GWAS summary-statistics data. We applied this methodology to identify additional loci associated with schizophrenia (SCZ), a highly heritable disorder with significant missing heritability. Epidemiological and clinical studies suggest comorbidity between SCZ and cardiovascular-disease (CVD) risk factors, including systolic blood pressure, triglycerides, low- and high-density lipoprotein, body mass index, waist-to-hip ratio, and type 2 diabetes. Using stratified quantile-quantile plots, we show enrichment of SNPs associated with SCZ as a function of the association with several CVD risk factors and a corresponding reduction in false discovery rate (FDR). We validate this "pleiotropic enrichment" by demonstrating increased replication rate across independent SCZ substudies. Applying the stratified FDR method, we identified 25 loci associated with SCZ at a conditional FDR level of 0.01. Of these, ten loci are associated with both SCZ and CVD risk factors, mainly triglycerides and low- and high-density lipoproteins but also waist-to-hip ratio, systolic blood pressure, and body mass index. Together, these findings suggest the feasibility of using genetic-pleiotropy-informed methods for improving gene discovery in SCZ and identifying potential mechanistic relationships with various CVD risk factors.

AB - Several lines of evidence suggest that genome-wide association studies (GWASs) have the potential to explain more of the "missing heritability" of common complex phenotypes. However, reliable methods for identifying a larger proportion of SNPs are currently lacking. Here, we present a genetic-pleiotropy-informed method for improving gene discovery with the use of GWAS summary-statistics data. We applied this methodology to identify additional loci associated with schizophrenia (SCZ), a highly heritable disorder with significant missing heritability. Epidemiological and clinical studies suggest comorbidity between SCZ and cardiovascular-disease (CVD) risk factors, including systolic blood pressure, triglycerides, low- and high-density lipoprotein, body mass index, waist-to-hip ratio, and type 2 diabetes. Using stratified quantile-quantile plots, we show enrichment of SNPs associated with SCZ as a function of the association with several CVD risk factors and a corresponding reduction in false discovery rate (FDR). We validate this "pleiotropic enrichment" by demonstrating increased replication rate across independent SCZ substudies. Applying the stratified FDR method, we identified 25 loci associated with SCZ at a conditional FDR level of 0.01. Of these, ten loci are associated with both SCZ and CVD risk factors, mainly triglycerides and low- and high-density lipoproteins but also waist-to-hip ratio, systolic blood pressure, and body mass index. Together, these findings suggest the feasibility of using genetic-pleiotropy-informed methods for improving gene discovery in SCZ and identifying potential mechanistic relationships with various CVD risk factors.

U2 - 10.1016/j.ajhg.2013.01.001

DO - 10.1016/j.ajhg.2013.01.001

M3 - Journal article

C2 - 23375658

VL - 92

SP - 197

EP - 209

JO - American Journal of Human Genetics

JF - American Journal of Human Genetics

SN - 0002-9297

IS - 2

ER -