Skip to main content
padlock icon - secure page this page is secure

Free Content Exploring the Major Sources and Extent of Heterogeneity in a Genome‐Wide Association Meta‐Analysis

Download Article:

You have access to the full text article on a website external to Ingenta Connect.

Please click here to view this article on Wiley Online Library.

You may be required to register and activate access on Wiley Online Library before you can obtain the full text. If you have any queries please visit Wiley Online Library

Genome‐wide association (GWA) meta‐analysis has become a popular approach for discovering genetic variants responsible for complex diseases. The between‐study heterogeneity effect is a severe issue that may complicate the interpretation of results. Aiming to improve the interpretation of meta‐analysis results, we empirically explored the extent and source of heterogeneity effect. We analyzed a previously reported GWA meta‐analysis of obesity, in which over 21,000 subjects from seven individual samples were meta‐analyzed. We first evaluated the extent and distribution of heterogeneity across the entire genome. We then studied the effects of several potentially confounding factors, including age, ethnicity, gender composition, study type, and genotype imputation on heterogeneity with a random‐effects meta‐regression model. Of the total 4,325,550 SNPs being tested, heterogeneity was moderate to very large for 25.4% of the total SNPs. Heterogeneity was more severe in SNPs with stronger association signals. Ethnicity, average age, and genotype imputation accuracy had significant effects on the heterogeneity. Exploring the effects of ethnicity can provide clues to the potential ethnic‐specific effects for two loci known to affect obesity, MC4R, and MTCH2. Our analysis can help to clarify understanding of the obesity mechanism and may provide guidance for an effective design of future GWA meta‐analysis.
No References
No Citations
No Supplementary Data
No Article Media
No Metrics

Keywords: Genome‐wide association study; heterogeneity; meta‐analysis; meta‐regression; obesity

Document Type: Research Article

Publication date: March 1, 2016

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more