Genetic interactions and pleiotropy in metabolic diseases: Insights from a comprehensive GWAS analysis.

ABSTRACT: This study offers insights into the genetic and biological connections between nine common metabolic diseases using data from genome-wide association studies. Our goal is to unravel the genetic interactions and biological pathways of these complex diseases, enhancing our understanding of their genetic architecture. We employed a range of advanced analytical techniques to explore the genetic correlations and shared genetic variants of these diseases. These methods include Linked Disequilibrium Score Regression, High-Definition Likelihood (HDL), genetic analysis combining multiplicity and annotation (GPA), two-sample Mendelian randomization analyses, analysis under the multiplicity-complex null hypothesis (PLACO), and Functional mapping and annotation of genetic associations (FUMA). Addition

SUBMITTER: Shen J 

PROVIDER: S-EPMC11377178 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature