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General Framework for Meta-Analysis of Haplotype Association Tests.

Wednesday,2016-08-17 16:49 America/Los_Angeles — zdrager
TitleGeneral Framework for Meta-Analysis of Haplotype Association Tests.
Publication TypeJournal Article
Year of Publication2016
AuthorsWang, S, Zhao, JH, An, P, Guo, X, Jensen, RA, Marten, J, Huffman, JE, Meidtner, K, Boeing, H, Campbell, A, Rice, KM, Scott, RA, Yao, J, Schulze, MB, Wareham, NJ, Borecki, IB, Province, MA, Rotter, JI, Hayward, C, Goodarzi, MO, Meigs, JB, Dupuis, J
JournalGenet Epidemiol
Volume40
Issue3
Pagination244-52
Date Published2016 Apr
ISSN1098-2272
Abstract<p>For complex traits, most associated single nucleotide variants (SNV) discovered to date have a small effect, and detection of association is only possible with large sample sizes. Because of patient confidentiality concerns, it is often not possible to pool genetic data from multiple cohorts, and meta-analysis has emerged as the method of choice to combine results from multiple studies. Many meta-analysis methods are available for single SNV analyses. As new approaches allow the capture of low frequency and rare genetic variation, it is of interest to jointly consider multiple variants to improve power. However, for the analysis of haplotypes formed by multiple SNVs, meta-analysis remains a challenge, because different haplotypes may be observed across studies. We propose a two-stage meta-analysis approach to combine haplotype analysis results. In the first stage, each cohort estimate haplotype effect sizes in a regression framework, accounting for relatedness among observations if appropriate. For the second stage, we use a multivariate generalized least square meta-analysis approach to combine haplotype effect estimates from multiple cohorts. Haplotype-specific association tests and a global test of independence between haplotypes and traits are obtained within our framework. We demonstrate through simulation studies that we control the type-I error rate, and our approach is more powerful than inverse variance weighted meta-analysis of single SNV analysis when haplotype effects are present. We replicate a published haplotype association between fasting glucose-associated locus (G6PC2) and fasting glucose in seven studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium and we provide more precise haplotype effect estimates.</p>
DOI10.1002/gepi.21959
Alternate JournalGenet. Epidemiol.
PubMed ID27027517
PubMed Central IDPMC4869684
Grant ListAG023629 / AG / NIA NIH HHS / United States
CZD/16/6 / / Chief Scientist Office / United Kingdom
DK063491 / DK / NIDDK NIH HHS / United States
HHSN268200800007C / HL / NHLBI NIH HHS / United States
HHSN268200800007C / / PHS HHS / United States
HHSN268201200036C / HL / NHLBI NIH HHS / United States
HHSN268201200036C / / PHS HHS / United States
HL068986 / HL / NHLBI NIH HHS / United States
HL080295 / HL / NHLBI NIH HHS / United States
HL087652 / HL / NHLBI NIH HHS / United States
HL103612 / HL / NHLBI NIH HHS / United States
K24 DK080140 / DK / NIDDK NIH HHS / United States
K24 DK080140 / DK / NIDDK NIH HHS / United States
MC_U106179471 / / Medical Research Council / United Kingdom
N01-HC-95159 / HC / NHLBI NIH HHS / United States
N01-HC-95160 / HC / NHLBI NIH HHS / United States
N01-HC-95161 / HC / NHLBI NIH HHS / United States
N01-HC-95162 / HC / NHLBI NIH HHS / United States
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R01 AG023629 / AG / NIA NIH HHS / United States
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