Meta-analysis of Gene-Level Associations for Rare Variants Based on Single-Variant Statistics
2013 (English)In: American Journal of Human Genetics, ISSN 0002-9297, E-ISSN 1537-6605, Vol. 93, no 2, 236-248 p.Article in journal (Refereed) Published
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.
Place, publisher, year, edition, pages
2013. Vol. 93, no 2, 236-248 p.
Medical and Health Sciences
IdentifiersURN: urn:nbn:se:uu:diva-206973DOI: 10.1016/j.ajhg.2013.06.011ISI: 000323186200004OAI: oai:DiVA.org:uu-206973DiVA: diva2:646580