Genetic overlap between multiple sclerosis and several cardiovascular disease risk factors
Year: 2016
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Epidemiological findings suggest a relationship between multiple sclerosis (MS) and cardiovascular disease (CVD) risk factors, although the nature of this relationship is not well understood. OBJECTIVE: We used genome-wide association study (GWAS) data to identify shared genetic factors (pleiotropy) between MS and CVD risk factors. METHODS: Using summary statistics from a large, recent GWAS (total n > 250,000 individuals), we investigated overlap in single nucleotide polymorphisms (SNPs) associated with MS and a number of CVD risk factors including triglycerides (TG), low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, body mass index, waist-to-hip ratio, type 2 diabetes, systolic blood pressure, and C-reactive protein level. RESULTS AND CONCLUSION: Using conditional enrichment plots, we found 30-fold enrichment of MS SNPs for different levels of association with LDL and TG SNPs, with a corresponding reduction in conditional false discovery rate (FDR). We identified 133 pleiotropic loci outside the extended major histocompatibility complex with conditional FDR < 0.01, of which 65 are novel. These pleiotropic loci were located on 21 different chromosomes. Our findings point to overlapping pathobiology between clinically diagnosed MS and cardiovascular risk factors and identify novel common variants associated with increased MS risk.
Source: Multiple Sclerosis Journal
Language: English
Subfield: Pathology and Forensic Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: green
Awards: Structural & Metabolic Neuroimaging Biomarkers in Early Alzheimer's Disease, Creating a Pediatric Imaging-Genomics Data Resource, Polygenicity, Pleiotrophy and Power: Novel Statistical Methods for Gene Discovery, Spatiotemporal Brain Imaging: Microscopic and System Level, Training Clinical Scientists in Radiological Imaging
OpenAlex ID: W2336848872
