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LD Score Regression Distinguishes Confounding from Polygenicity in Genome-Wide Association Studies

View ORCID ProfileBrendan K. Bulik-Sullivan, Po-Ru Loh, Hilary Finucane, Stephan Ripke, Jian Yang, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Nick Patterson, Mark J. Daly, Alkes L. Price, Benjamin M. Neale
doi: https://doi.org/10.1101/002931
Brendan K. Bulik-Sullivan
1Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
2Analytical and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA
3Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA
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  • ORCID record for Brendan K. Bulik-Sullivan
Po-Ru Loh
4Department of Epidemiology, Harvard School of Public Health, Boston, MA
5Department of Biostatistics, Harvard School of Public Health, Boston, MA
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Hilary Finucane
6Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA
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Stephan Ripke
2Analytical and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA
3Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA
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Jian Yang
7Brain Institute, University of Queensland, Brisbane, Queensland, Australia
8University of Queensland Diamantina Institute, University of Queensland, Princess Alexandra Hospital, Brisbane, Queensland, Australia
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Nick Patterson
1Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
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Mark J. Daly
1Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
2Analytical and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA
3Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA
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Alkes L. Price
1Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
4Department of Epidemiology, Harvard School of Public Health, Boston, MA
5Department of Biostatistics, Harvard School of Public Health, Boston, MA
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Benjamin M. Neale
1Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA
2Analytical and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA
3Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA
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  • For correspondence: bneale@broadinstitute.org
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Abstract

Both polygenicity1,2 (i.e. many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification3, can yield inflated distributions of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from bias and true signal from polygenicity. We have developed an approach that quantifies the contributions of each by examining the relationship between test statistics and linkage disequilibrium (LD). We term this approach LD Score regression. LD Score regression provides an upper bound on the contribution of confounding bias to the observed inflation in test statistics and can be used to estimate a more powerful correction factor than genomic control4–14. We find strong evidence that polygenicity accounts for the majority of test statistic inflation in many GWAS of large sample size.

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Posted February 21, 2014.
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LD Score Regression Distinguishes Confounding from Polygenicity in Genome-Wide Association Studies
Brendan K. Bulik-Sullivan, Po-Ru Loh, Hilary Finucane, Stephan Ripke, Jian Yang, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Nick Patterson, Mark J. Daly, Alkes L. Price, Benjamin M. Neale
bioRxiv 002931; doi: https://doi.org/10.1101/002931
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LD Score Regression Distinguishes Confounding from Polygenicity in Genome-Wide Association Studies
Brendan K. Bulik-Sullivan, Po-Ru Loh, Hilary Finucane, Stephan Ripke, Jian Yang, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Nick Patterson, Mark J. Daly, Alkes L. Price, Benjamin M. Neale
bioRxiv 002931; doi: https://doi.org/10.1101/002931

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