Integrating genome-wide association and eQTLs studies identifies the genes associated with age at menarche and age at natural menopause.

• Main Authors: Gang Wang, Jian Lv, Xiaoxin Qiu, Yujun An
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2019-01-01
• Series: PLoS ONE
• Online Access: https://doi.org/10.1371/journal.pone.0213953

<h4>Objective</h4>An early onset of menarche and, later, menopause are well-established risk factors for the development of breast cancer and endometrial cancer. Although the largest GWASs have identified 389 independent signals for age at menarche (AAM) and 44 regions for age at menopause (ANM), GWAS can only identify the associations between variants and traits. The aim of this study was to identify genes whose expression levels were associated with AAM or ANM due to pleiotropy or causality by integrating GWAS data with genome-wide expression quantitative trait loci (eQTLs) data. We also aimed to identify the pleiotropic genes that influenced both phenotypes.<h4>Method</h4>We employed GWAS data of AAM and ANM and genome-wide eQTL data from whole blood. The summary data-based Mendelian randomization method was used to prioritize the associated genes for further study. The colocalization analysis was used to identify the pleiotropic genes associated with both phenotypes.<h4>Results</h4>We identified 31 genes whose expression was associated with AAM and 24 genes whose expression was associated with ANM due to pleiotropy or causality. Two pleiotropic genes were identified to be associated with both phenotypes.<h4>Conclusion</h4>The results point out the most possible genes which were responsible for the association. Our study prioritizes the associated genes for further functional mechanistic study of AAM and ANM and illustrates the benefit of integrating different omics data into the study of complex traits.