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Meta-analysis of gene-level associations for rare variants based on single-variant statistics.

TitleMeta-analysis of gene-level associations for rare variants based on single-variant statistics.
Publication TypeJournal Article
Year of Publication2013
AuthorsHu Y-J, Berndt SI, Gustafsson S, Ganna A, Hirschhorn J, North KE, Ingelsson E
Secondary AuthorsLin D-Y
Corporate AuthorsGenetic Investigation of Anthropometric Traits(GIANT) Consortium
JournalAm J Hum Genet
Volume93
Issue2
Pagination236-48
Date Published2013 Aug 08
ISSN1537-6605
KeywordsComputer Simulation, Gene Frequency, Genetic Variation, Genome-Wide Association Study, Genotype, Humans, Models, Genetic, Phenotype, Polymorphism, Single Nucleotide, Receptors, LDL, Receptors, Odorant, Software
Abstract

Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available.

DOI10.1016/j.ajhg.2013.06.011
Alternate JournalAm J Hum Genet
PubMed ID23891470
PubMed Central IDPMC3738834
Grant ListR01 CA082659 / CA / NCI NIH HHS / United States
HHSN268201100012C / HL / NHLBI NIH HHS / United States
UL1RR025005 / RR / NCRR NIH HHS / United States
K05 AA017688 / AA / NIAAA NIH HHS / United States
R01HL59367 / HL / NHLBI NIH HHS / United States
HHSN268201100010C / HL / NHLBI NIH HHS / United States
UL1 RR025005 / RR / NCRR NIH HHS / United States
HHSN26820110009C / / PHS HHS / United States
R01 HL059367 / HL / NHLBI NIH HHS / United States
R01CA082659 / CA / NCI NIH HHS / United States
HHSN268201100011I / HL / NHLBI NIH HHS / United States
HHSN268201100011C / HL / NHLBI NIH HHS / United States
R01 HL086694 / HL / NHLBI NIH HHS / United States
G1000143 / / Medical Research Council / United Kingdom
U01HG004803 / HG / NHGRI NIH HHS / United States
HHSN268200625226C / / PHS HHS / United States
U01 HG004402 / HG / NHGRI NIH HHS / United States
R01 DK075787 / DK / NIDDK NIH HHS / United States
HHSN268201100010C / / PHS HHS / United States
U01HG004402 / HG / NHGRI NIH HHS / United States
HHSN26820110006C / / PHS HHS / United States
097117 / / Wellcome Trust / United Kingdom
/ / Intramural NIH HHS / United States
HHSN26820110007C / / PHS HHS / United States
14136 / / Cancer Research UK / United Kingdom
HHSN26820110008C / / PHS HHS / United States
HHSN268201100012C / / PHS HHS / United States
R01HL087641 / HL / NHLBI NIH HHS / United States
U01 HG004803 / HG / NHGRI NIH HHS / United States
G0401527 / / Medical Research Council / United Kingdom
HHSN26820110005C / / PHS HHS / United States
090532 / / Wellcome Trust / United Kingdom
MC_PC_U127561128 / / Medical Research Council / United Kingdom
MR/K013351/1 / / Medical Research Council / United Kingdom
HHSN268201100011C / / PHS HHS / United States
P01CA142538 / CA / NCI NIH HHS / United States
P01 CA142538 / CA / NCI NIH HHS / United States
R01 HL087641 / HL / NHLBI NIH HHS / United States
HHSN26800625226C / / PHS HHS / United States
R01HL086694 / HL / NHLBI NIH HHS / United States