A subset-based approach improves power and interpretation for the combined analysis of genetic association studies of heterogeneous traits

Samsiddhi Bhattacharjee, Preetha Rajaraman, Kevin B. Jacobs, William A. Wheeler, Beatrice S. Melin, Patricia Hartge, Meredith Yeager, Charles C. Chung, Stephen J. Chanock, Nilanjan Chatterjee

Research output: Contribution to journalArticle

Abstract

Pooling genome-wide association studies (GWASs) increases power but also poses methodological challenges because studies are often heterogeneous. For example, combining GWASs of related but distinct traits can provide promising directions for the discovery of loci with small but common pleiotropic effects. Classical approaches for meta-analysis or pooled analysis, however, might not be suitable for such analysis because individual variants are likely to be associated with only a subset of the traits or might demonstrate effects in different directions. We propose a method that exhaustively explores subsets of studies for the presence of true association signals that are in either the same direction or possibly opposite directions. An efficient approximation is used for rapid evaluation of p values. We present two illustrative applications, one for a meta-analysis of separate case-control studies of six distinct cancers and another for pooled analysis of a case-control study of glioma, a class of brain tumors that contains heterogeneous subtypes. Both the applications and additional simulation studies demonstrate that the proposed methods offer improved power and more interpretable results when compared to traditional methods for the analysis of heterogeneous traits. The proposed framework has applications beyond genetic association studies.

Original languageEnglish (US)
Pages (from-to)821-835
Number of pages15
JournalAmerican Journal of Human Genetics
Volume90
Issue number5
DOIs
StatePublished - May 4 2012
Externally publishedYes

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Genetic Association Studies
Genome-Wide Association Study
Meta-Analysis
Case-Control Studies
Brain Neoplasms
Glioma
Direction compound
Neoplasms

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

Cite this

A subset-based approach improves power and interpretation for the combined analysis of genetic association studies of heterogeneous traits. / Bhattacharjee, Samsiddhi; Rajaraman, Preetha; Jacobs, Kevin B.; Wheeler, William A.; Melin, Beatrice S.; Hartge, Patricia; Yeager, Meredith; Chung, Charles C.; Chanock, Stephen J.; Chatterjee, Nilanjan.

In: American Journal of Human Genetics, Vol. 90, No. 5, 04.05.2012, p. 821-835.

Research output: Contribution to journalArticle

Bhattacharjee, S, Rajaraman, P, Jacobs, KB, Wheeler, WA, Melin, BS, Hartge, P, Yeager, M, Chung, CC, Chanock, SJ & Chatterjee, N 2012, 'A subset-based approach improves power and interpretation for the combined analysis of genetic association studies of heterogeneous traits', American Journal of Human Genetics, vol. 90, no. 5, pp. 821-835. https://doi.org/10.1016/j.ajhg.2012.03.015
Bhattacharjee, Samsiddhi ; Rajaraman, Preetha ; Jacobs, Kevin B. ; Wheeler, William A. ; Melin, Beatrice S. ; Hartge, Patricia ; Yeager, Meredith ; Chung, Charles C. ; Chanock, Stephen J. ; Chatterjee, Nilanjan. / A subset-based approach improves power and interpretation for the combined analysis of genetic association studies of heterogeneous traits. In: American Journal of Human Genetics. 2012 ; Vol. 90, No. 5. pp. 821-835.
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