Evidence map›Paper›PMID 25642630›Full record

ArticleNature genetics2015

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

Brendan K Bulik-Sullivan, Po-Ru Loh, Hilary K Finucane, Stephan Ripke, Jian Yang, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Nick Patterson, Mark J Daly, Alkes L Price, Benjamin M Neale

Abstract read
In one paragraph

Article in Nature genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3,651 papers, 19 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3,651citing papers in PubMed, 19 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3,651 citing papers in PubMed, 19 syntheses or guidelines pooled it.

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  6. Genome-wide meta-analysis with 1,590,596 individuals identifies 12 novel risk loci for systemic lupus erythematosus.Mammalian genome : official journal of the International Mammalian Genome Society · 2026
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3,591 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Brendan K Bulik-Sullivan1] Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA. [2] Analytical and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA. [3] Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
Po-Ru Loh1] Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA. [2] Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Hilary K Finucane1] Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA. [2] Department of Mathematics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
Stephan Ripke1] Analytical and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA. [2] Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
Jian YangQueensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia.ORCID 0000000320012474
Schizophrenia Working Group of the Psychiatric Genomics Consortium
Nick PattersonProgram in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
Mark J Daly1] Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA. [2] Analytical and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA. [3] Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.
Alkes L Price1] Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA. [2] Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA. [3] Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Benjamin M Neale1] Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA. [2] Analytical and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA. [3] Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.

Funding

HARVARD CLINICAL AND TRANSLATIONAL SCIENCE CENTER (UL1)UL1RR025758 · NCRR · HARVARD MEDICAL SCHOOL · PI NADLER, LEE MARSHALL · 2008 to 2011
$91.4M
Genomic Psychiatry CohortR01MH085548 · NIMH · UNIVERSITY OF SOUTHERN CALIFORNIA · PI PATO, CARLOS N, PATO, MICHELE T · 2008 to 2012
$16.3M
Statistical methods for studies of rare variantsR01MH101244 · NIMH · HARVARD MEDICAL SCHOOL · PI Benjamin Michael Neale, ALKES L PRICE · 2013 to 2026
$9.4M
Methods for Genome-wide Association Studies in Admixed PopulationsR01HG006399 · NHGRI · HARVARD UNIVERSITY D/B/A HARVARD SCHOOL OF PUBLIC HEALTH · PI PRICE, ALKES L · 2011 to 2024
$6.3M
2/4-Psychiatric GWAS Consortium: Genomic Follow-Up Next-Gen Sequencing & GenotypiU01MH094432 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI DALY, MARK JOSEPH · 2012 to 2015
$3.0M
1/4 Psychiatric GWAS Consortium: Genomic Follow-up Next-Gen Sequencing & GenotypiU01MH094421 · NIMH · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SULLIVAN, PATRICK F · 2012 to 2015
$1.9M
The genetic architecture of breast cancer risk factors and breast cancerR03CA173785 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI LINDSTROEM, SARA · 2013 to 2014
$174k
Fast and powerful extensions of mixed model methods for GWASF32HG007805 · NHGRI · HARVARD SCHOOL OF PUBLIC HEALTH · PI LOH, PO-RU · 2014 to 2017
$150k
Medical Research Council G0801418Medical Research Council MR/L010305/1Medical Research Council MR/L023784/1Medical Research Council MR/L023784/2NCI NIH HHS R03 CA173785NCRR NIH HHS UL1 RR025758NHGRI NIH HHS F32 HG007805NHGRI NIH HHS R01 HG006399NIMH NIH HHS R01 MH085548NIMH NIH HHS R01 MH094421NIMH NIH HHS R01 MH101244NIMH NIH HHS U01 MH094421NIMH NIH HHS U01 MH094432
6 · The paper itself

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.

Indexed as

Linkage DisequilibriumComputer SimulationGenome, HumanGenome-Wide Association StudyHumansPolymorphism, Single NucleotideRegression AnalysisSample Size

Identifiers

PMID25642630
PMCPMC4495769

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.