title: GPA-MDS: A Visualization Approach to Investigate Genetic Architecture among Phenotypes Using GWAS Results.
abstract: Genome-wide association studies (GWAS) have identified tens of thousands of genetic variants associated with hundreds of phenotypes and diseases, which have provided clinical and medical benefits to patients with novel biomarkers and therapeutic targets. Recently, there has been accumulating evidence suggesting that different complex traits share a common risk basis, namely, pleiotropy. Previously, a statistical method, namely, GPA (Genetic analysis incorporating Pleiotropy and Annotation), was developed to improve identification of risk variants and to investigate pleiotropic structure through a joint analysis of multiple GWAS datasets. While GPA provides a statistically rigorous framework to evaluate pleiotropy between phenotypes, it is still not trivial to investigate genetic relationships among a large number of phenotypes using the GPA framework. In order to address this challenge, in this paper, we propose a novel approach, GPA-MDS, to visualize genetic relationships among phenotypes using the GPA algorithm and multidimensional scaling (MDS). This tool will help researchers to investigate common etiology among diseases, which can potentially lead to development of common treatments across diseases. We evaluate the proposed GPA-MDS framework using a simulation study and apply it to jointly analyze GWAS datasets examining 18 unique phenotypes, which helps reveal the shared genetic architecture of these phenotypes.
authors.affiliation: Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
authors.forename: Wei
authors.initials: W
authors.lastname: Wei
authors.affiliation: Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA; Department of Medicine, Medical University of South Carolina, Charleston, SC, USA.
authors.forename: Paula S
authors.identifier: 0000-0002-9433-6634
authors.initials: PS
authors.lastname: Ramos
authors.affiliation: Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA; Ralph H. Johnson VA Medical Center, Charleston, SC, USA.
authors.forename: Kelly J
authors.initials: KJ
authors.lastname: Hunt
authors.affiliation: Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
authors.forename: Bethany J
authors.initials: BJ
authors.lastname: Wolf
authors.affiliation: Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA; Department of Medicine, Medical University of South Carolina, Charleston, SC, USA; Center for Genomic Medicine, Medical University of South Carolina, Charleston, SC, USA.
authors.forename: Gary
authors.initials: G
authors.lastname: Hardiman
authors.affiliation: Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
authors.forename: Dongjun
authors.identifier: 0000-0002-8072-5671
authors.initials: D
authors.lastname: Chung