Identifying BMI-associated genes via a genome-wide multi-omics integrative approach using summary data.

ABSTRACT:

Objective

This study aims to identify BMI-associated genes by integrating aggregated summary information from different omics data.

Methods

We conducted a meta-analysis to leverage information from a genome-wide association study (n = 339 224), a transcriptome-wide association study (n = 5619), and an epigenome-wide association study (n = 3743). We prioritized the significant genes with a machine learning-based method, netWAS, which borrows information from adipose tissue-specific interaction networks. We also used the brain-specific network in netWAS to investigate genes potentially involved in brain-adipose interaction.

Results

We identified 195 genes that were significantly associated with BMI through meta-analysis. The netWAS analysis narrowed down the list to 21

SUBMITTER: Tang J 

PROVIDER: S-EPMC11000658 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature