Meta-GWAS Accuracy and Power (MetaGAP) Calculator Shows that Hiding Heritability Is Partially Due to Imperfect Genetic Correlations across Studies

Ronald de Vlaming, Aysu Okbay, Cornelius A Rietveld, Magnus Johannesson, Patrik K E Magnusson, André G Uitterlinden, Frank J A van Rooij, Albert Hofman, Patrick J F Groenen, A Roy Thurik, Philipp D Koellinger

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Large-scale genome-wide association results are typically obtained from a fixed-effects meta-analysis of GWAS summary statistics from multiple studies spanning different regions and/or time periods. This approach averages the estimated effects of genetic variants across studies. In case genetic effects are heterogeneous across studies, the statistical power of a GWAS and the predictive accuracy of polygenic scores are attenuated, contributing to the so-called 'missing heritability'. Here, we describe the online Meta-GWAS Accuracy and Power (MetaGAP) calculator (available at www.devlaming.eu) which quantifies this attenuation based on a novel multi-study framework. By means of simulation studies, we show that under a wide range of genetic architectures, the statistical power and predictive accuracy provided by this calculator are accurate. We compare the predictions from the MetaGAP calculator with actual results obtained in the GWAS literature. Specifically, we use genomic-relatedness-matrix restricted maximum likelihood to estimate the SNP heritability and cross-study genetic correlation of height, BMI, years of education, and self-rated health in three large samples. These estimates are used as input parameters for the MetaGAP calculator. Results from the calculator suggest that cross-study heterogeneity has led to attenuation of statistical power and predictive accuracy in recent large-scale GWAS efforts on these traits (e.g., for years of education, we estimate a relative loss of 51-62% in the number of genome-wide significant loci and a relative loss in polygenic score R2 of 36-38%). Hence, cross-study heterogeneity contributes to the missing heritability.

Original languageEnglish
Article numbere1006495
JournalPLoS Genetics
Volume13
Issue number1
DOIs
Publication statusPublished - 17 Jan 2017

Funding

HRS (Health and Retirement Study) The HRS (Health and Retirement Study) is sponsored by the National Institute on Aging (grant number NIA U01AG009740) and is conducted by the University of Michigan. The genotyping was funded separately by the National Institute on Aging (RC2 AG036495, RC4 AG039029). Our genotyping was conducted by the NIH Center for Inherited Disease Research (CIDR) at Johns Hopkins University. Genotyping quality control and final preparation of the data were performed by the Genetics Coordinating Center at the University of Washington. STR (Swedish Twin Registry) The Jan Wallander and Tom Hedelius Foundation (P2012-0002:1), the Ragnar Söderberg Foundation (E9/11), The Swedish Research Council (421-2013-1061), the Ministry for Higher Education, The Swedish Research Council (M-2205-1112), GenomEUtwin (EU/QLRT-2001-01254; QLG2-CT-2002-01254), NIH DK U01-066134, The Swedish Foundation for Strategic Research (SSF). RS (Rotterdam Study) The generation and management of GWAS genotype data for the Rotterdam Study is supported by the Netherlands Organisation of Scientific Research NWO Investments (nr. 175.010.2005.011, 911-03-012). This study is funded by the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), the Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO) project nr. 050-060-810. We thank Pascal Arp, Mila Jhamai, Marijn Verkerk, Lizbeth Herrera and Marjolein Peters for their help in creating the GWAS database, and Karol Estrada and Maksim V. Struchalin for their support in creation and analysis of imputed data. The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. The authors are grateful to the study participants, the staff from the Rotterdam Study and the participating general practitioners and pharmacists. RAND HRS RAND HRS Data, Version N. Produced by the RAND Center for the Study of Aging, with funding from the National Institute on Aging and the Social Security Administration. Santa Monica, CA (September 2014).

FundersFunder number
Ministry for Higher EducationM-2205-1112, QLG2-CT-2002-01254, EU/QLRT-2001-01254
Netherlands Genomics Initiative
Netherlands Organisation of Scientific Research NWO175.010.2005.011, 911-03-012
Netherlands Organization for the Health Research and Development
RAND Center for the Study of Aging
RIDE2
Ragnar Söderberg FoundationE9/11
Research Institute for Diseases in the Elderly014-93-015
National Institutes of HealthDK U01-066134
National Institute on AgingU01AG009740
U.S. Social Security Administration
University of MichiganRC4 AG039029, RC2 AG036495
Jan Wallanders och Tom Hedelius Stiftelse samt Tore Browaldhs StiftelseP2012-0002:1
European Commission
Stiftelsen för Strategisk Forskning
ZonMw
Erasmus Universiteit Rotterdam
Ministerie van Volksgezondheid, Welzijn en Sport
Erasmus Medisch Centrum
Ministerie van Onderwijs, Cultuur en Wetenschap
Nederlandse Organisatie voor Wetenschappelijk Onderzoek050-060-810
Vetenskapsrådet421-2013-1061

    Keywords

    • Data Accuracy
    • Genome-Wide Association Study
    • Humans
    • Journal Article
    • Meta-Analysis as Topic
    • Software

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