Improved detection of common variants associated with schizophrenia by leveraging pleiotropy with cardiovascular-disease risk factors - PubMed (original) (raw)

. 2013 Feb 7;92(2):197-209.

doi: 10.1016/j.ajhg.2013.01.001. Epub 2013 Jan 31.

Srdjan Djurovic, Wesley K Thompson, Andrew J Schork, Kenneth S Kendler, Michael C O'Donovan, Dan Rujescu, Thomas Werge, Martijn van de Bunt, Andrew P Morris, Mark I McCarthy; International Consortium for Blood Pressure GWAS; Diabetes Genetics Replication and Meta-analysis Consortium; Psychiatric Genomics Consortium Schizophrenia Working Group; J Cooper Roddey, Linda K McEvoy, Rahul S Desikan, Anders M Dale

Collaborators, Affiliations

Improved detection of common variants associated with schizophrenia by leveraging pleiotropy with cardiovascular-disease risk factors

Ole A Andreassen et al. Am J Hum Genet. 2013.

Abstract

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.

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

PubMed Disclaimer

Figures

Figure 1

Figure 1

Enrichment and Replication (A and B) Stratified Q-Q plot of nominal versus empirical –log10 p values (corrected for inflation) in SCZ below the standard GWAS threshold of p < 5 × 10−8 as a function of significance of association with (A) TGs and (B) WHR at the levels of –log10(p) > 0, –log10(p) > 1, –log10(p) > 2, and –log10(p) > 3, which correspond to p < 1, p < 0.1, p < 0.01, and p < 0.001, respectively. Dashed lines indicate the null hypothesis. (C and D) Stratified TDR plots illustrating the TDR increase associated with increased pleiotropic enrichment in (C) SCZ conditioned on TG (SCZ|TG) and (D) SCZ conditioned on WHR (SCZ|WHR). (E and F) Cumulative replication plot showing the average rate of replication (p < 0.05) within SCZ substudies for a given p value threshold demonstrates that pleiotropic enriched SNP categories replicate at a higher rate in independent SCZ samples for (E) SCZ conditioned on TG (SCZ|TG) and (F) SCZ conditioned on WHR (SCZ|WHR). The vertical intercept is the overall replication rate per category.

Figure 2

Figure 2

Conditional Manhattan Plot Conditional Manhattan plot of conditional –log10 (FDR) values for SCZ alone (black) and SCZ given the following CVD risk factors: TGs (SCZ|TG, red), LDL (SCZ|LDL, orange), HDL (SCZ|HDL, cyan), SBP (SCZ|SBP, green), BMI (SCZ|BMI, purple), WHR (SCZ|WHR, blue), and T2D (SCZ|T2D, chartreuse). SNPs with conditional –log10 FDR > 1.3 (i.e., FDR < 0.05) are shown with large points. A black line around the large points indicates the most significant SNP in each LD block, and this SNP was annotated with the closest gene, which is listed above the symbols in each locus (except for the HLA region on chromosome 6) and in Table S2. The figure shows the localization of 106 loci on a total of 21 chromosomes (1–19, 21, and 22). Details for the loci with –log10 FDR > 2 (i.e., FDR < 0.01) are shown in Table 1.

Similar articles

Cited by

References

    1. Glazier A.M., Nadeau J.H., Aitman T.J. Finding genes that underlie complex traits. Science. 2002;298:2345–2349. - PubMed
    1. Hirschhorn J.N., Daly M.J. Genome-wide association studies for common diseases and complex traits. Nat. Rev. Genet. 2005;6:95–108. - PubMed
    1. Hindorff L.A., Sethupathy P., Junkins H.A., Ramos E.M., Mehta J.P., Collins F.S., Manolio T.A. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl. Acad. Sci. USA. 2009;106:9362–9367. - PMC - PubMed
    1. Manolio T.A., Collins F.S., Cox N.J., Goldstein D.B., Hindorff L.A., Hunter D.J., McCarthy M.I., Ramos E.M., Cardon L.R., Chakravarti A. Finding the missing heritability of complex diseases. Nature. 2009;461:747–753. - PMC - PubMed
    1. Yang J., Benyamin B., McEvoy B.P., Gordon S., Henders A.K., Nyholt D.R., Madden P.A., Heath A.C., Martin N.G., Montgomery G.W. Common SNPs explain a large proportion of the heritability for human height. Nat. Genet. 2010;42:565–569. - PMC - PubMed

Publication types

MeSH terms

Grants and funding

LinkOut - more resources