LD score regression distinguishes confounding from polygenicity in genome-wide association studies

Brendan Bulik-Sullivan; Po Ru Loh; Hilary K. Finucane; Stephan Ripke; Jian Yang; Nick Patterson; Mark J. Daly; Alkes L. Price; Benjamin M. Neale; Aiden Corvin; James T.R. Walters; Kai How Farh; Peter A. Holmans; Phil Lee; David A. Collier; Hailiang Huang; Tune H. Pers; Ingrid Agartz; Esben Agerbo; Margot Albus; Madeline Alexander; Farooq Amin; Silviu A. Bacanu; Martin Begemann; Richard A. Belliveau; Judit Bene; Sarah E. Bergen; Elizabeth Bevilacqua; Tim B. Bigdeli; Donald W. Black; Richard Bruggeman; Nancy G. Buccola; Randy L. Buckner; William Byerley; Wiepke Cahn; Guiqing Cai; Murray J. Cairns; Dominique Campion; Rita M. Cantor; Vaughan J. Carr; Noa Carrera; Stanley V. Catts; Kimberly D. Chambert; Raymond C.K. Chan; Ronald Y.L. Chen; Eric Y.H. Chen; René S. Kahn; Kieran C. Murphy; Jim Van Os; Roel A. Ophoff

doi:10.1038/ng.3211

LD score regression distinguishes confounding from polygenicity in genome-wide association studies

Brendan Bulik-Sullivan, Po Ru Loh, Hilary K. Finucane, Stephan Ripke, Jian Yang, Nick Patterson, Mark J. Daly, Alkes L. Price, Benjamin M. Neale^*, Aiden Corvin, James T.R. Walters, Kai How Farh, Peter A. Holmans, Phil Lee, David A. Collier, Hailiang Huang, Tune H. Pers, Ingrid Agartz, Esben Agerbo, Margot AlbusMadeline Alexander, Farooq Amin, Silviu A. Bacanu, Martin Begemann, Richard A. Belliveau, Judit Bene, Sarah E. Bergen, Elizabeth Bevilacqua, Tim B. Bigdeli, Donald W. Black, Richard Bruggeman, Nancy G. Buccola, Randy L. Buckner, William Byerley, Wiepke Cahn, Guiqing Cai, Murray J. Cairns, Dominique Campion, Rita M. Cantor, Vaughan J. Carr, Noa Carrera, Stanley V. Catts, Kimberly D. Chambert, Raymond C.K. Chan, Ronald Y.L. Chen, Eric Y.H. Chen, René S. Kahn, Kieran C. Murphy, Jim Van Os, Roel A. Ophoff,

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

414 Citations (Scopus)

Abstract

Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from a true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size.

Original language	English
Pages (from-to)	291-295
Number of pages	5
Journal	Nature Genetics
Volume	47
Issue number	3
DOIs	https://doi.org/10.1038/ng.3211
Publication status	Published - 25 Feb 2015

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Bulik-Sullivan, B., Loh, P. R., Finucane, H. K., Ripke, S., Yang, J., Patterson, N., Daly, M. J., Price, A. L., Neale, B. M., Corvin, A., Walters, J. T. R., Farh, K. H., Holmans, P. A., Lee, P., Collier, D. A., Huang, H., Pers, T. H., Agartz, I., Agerbo, E. (2015). LD score regression distinguishes confounding from polygenicity in genome-wide association studies. Nature Genetics, 47(3), 291-295. https://doi.org/10.1038/ng.3211

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title = "LD score regression distinguishes confounding from polygenicity in genome-wide association studies",

abstract = "Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from a true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size.",

author = "Brendan Bulik-Sullivan and Loh, {Po Ru} and Finucane, {Hilary K.} and Stephan Ripke and Jian Yang and Nick Patterson and Daly, {Mark J.} and Price, {Alkes L.} and Neale, {Benjamin M.} and Aiden Corvin and Walters, {James T.R.} and Farh, {Kai How} and Holmans, {Peter A.} and Phil Lee and Collier, {David A.} and Hailiang Huang and Pers, {Tune H.} and Ingrid Agartz and Esben Agerbo and Margot Albus and Madeline Alexander and Farooq Amin and Bacanu, {Silviu A.} and Martin Begemann and Belliveau, {Richard A.} and Judit Bene and Bergen, {Sarah E.} and Elizabeth Bevilacqua and Bigdeli, {Tim B.} and Black, {Donald W.} and Richard Bruggeman and Buccola, {Nancy G.} and Buckner, {Randy L.} and William Byerley and Wiepke Cahn and Guiqing Cai and Cairns, {Murray J.} and Dominique Campion and Cantor, {Rita M.} and Carr, {Vaughan J.} and Noa Carrera and Catts, {Stanley V.} and Chambert, {Kimberly D.} and Chan, {Raymond C.K.} and Chen, {Ronald Y.L.} and Chen, {Eric Y.H.} and Kahn, {Ren{\'e} S.} and Murphy, {Kieran C.} and {Van Os}, Jim and Ophoff, {Roel A.}",

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doi = "10.1038/ng.3211",

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Bulik-Sullivan, B, Loh, PR, Finucane, HK, Ripke, S, Yang, J, Patterson, N, Daly, MJ, Price, AL, Neale, BM, Corvin, A, Walters, JTR, Farh, KH, Holmans, PA, Lee, P, Collier, DA, Huang, H, Pers, TH, Agartz, I, Agerbo, E, Albus, M, Alexander, M, Amin, F, Bacanu, SA, Begemann, M, Belliveau, RA, Bene, J, Bergen, SE, Bevilacqua, E, Bigdeli, TB, Black, DW, Bruggeman, R, Buccola, NG, Buckner, RL, Byerley, W, Cahn, W, Cai, G, Cairns, MJ, Campion, D, Cantor, RM, Carr, VJ, Carrera, N, Catts, SV, Chambert, KD, Chan, RCK, Chen, RYL, Chen, EYH, Kahn, RS, Murphy, KC, Van Os, J, Ophoff, RA 2015, 'LD score regression distinguishes confounding from polygenicity in genome-wide association studies', Nature Genetics, vol. 47, no. 3, pp. 291-295. https://doi.org/10.1038/ng.3211

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T1 - LD score regression distinguishes confounding from polygenicity in genome-wide association studies

AU - Bulik-Sullivan, Brendan

AU - Loh, Po Ru

AU - Finucane, Hilary K.

AU - Ripke, Stephan

AU - Yang, Jian

AU - Patterson, Nick

AU - Daly, Mark J.

AU - Price, Alkes L.

AU - Neale, Benjamin M.

AU - Corvin, Aiden

AU - Walters, James T.R.

AU - Farh, Kai How

AU - Holmans, Peter A.

AU - Lee, Phil

AU - Collier, David A.

AU - Huang, Hailiang

AU - Pers, Tune H.

AU - Agartz, Ingrid

AU - Agerbo, Esben

AU - Albus, Margot

AU - Alexander, Madeline

AU - Amin, Farooq

AU - Bacanu, Silviu A.

AU - Begemann, Martin

AU - Belliveau, Richard A.

AU - Bene, Judit

AU - Bergen, Sarah E.

AU - Bevilacqua, Elizabeth

AU - Bigdeli, Tim B.

AU - Black, Donald W.

AU - Bruggeman, Richard

AU - Buccola, Nancy G.

AU - Buckner, Randy L.

AU - Byerley, William

AU - Cahn, Wiepke

AU - Cai, Guiqing

AU - Cairns, Murray J.

AU - Campion, Dominique

AU - Cantor, Rita M.

AU - Carr, Vaughan J.

AU - Carrera, Noa

AU - Catts, Stanley V.

AU - Chambert, Kimberly D.

AU - Chan, Raymond C.K.

AU - Chen, Ronald Y.L.

AU - Chen, Eric Y.H.

AU - Kahn, René S.

AU - Murphy, Kieran C.

AU - Van Os, Jim

AU - Ophoff, Roel A.

PY - 2015/2/25

Y1 - 2015/2/25

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AB - Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from a true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size.

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U2 - 10.1038/ng.3211

DO - 10.1038/ng.3211

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SN - 1061-4036

VL - 47

SP - 291

EP - 295

JO - Nature Genetics

JF - Nature Genetics

IS - 3

ER -

LD score regression distinguishes confounding from polygenicity in genome-wide association studies

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