Back to Search Start Over

An integrative framework to prioritize genes in more than 500 loci associated with body mass index.

Authors :
Hemerich, Daiane
Svenstrup, Victor
Obrero, Virginia Diez
Preuss, Michael
Moscati, Arden
Hirschhorn, Joel N.
Loos, Ruth J.F.
Source :
American Journal of Human Genetics. Jun2024, Vol. 111 Issue 6, p1035-1046. 12p.
Publication Year :
2024

Abstract

Obesity is a major risk factor for a myriad of diseases, affecting >600 million people worldwide. Genome-wide association studies (GWASs) have identified hundreds of genetic variants that influence body mass index (BMI), a commonly used metric to assess obesity risk. Most variants are non-coding and likely act through regulating genes nearby. Here, we apply multiple computational methods to prioritize the likely causal gene(s) within each of the 536 previously reported GWAS-identified BMI-associated loci. We performed summary-data-based Mendelian randomization (SMR), FINEMAP, DEPICT, MAGMA, transcriptome-wide association studies (TWASs), mutation significance cutoff (MSC), polygenic priority score (PoPS), and the nearest gene strategy. Results of each method were weighted based on their success in identifying genes known to be implicated in obesity, ranking all prioritized genes according to a confidence score (minimum: 0; max: 28). We identified 292 high-scoring genes (≥11) in 264 loci, including genes known to play a role in body weight regulation (e.g., DGKI , ANKRD26 , MC4R , LEPR , BDNF , GIPR , AKT3 , KAT8 , MTOR) and genes related to comorbidities (e.g., FGFR1 , ISL1 , TFAP2B , PARK2 , TCF7L2 , GSK3B). For most of the high-scoring genes, however, we found limited or no evidence for a role in obesity, including the top-scoring gene BPTF. Many of the top-scoring genes seem to act through a neuronal regulation of body weight, whereas others affect peripheral pathways, including circadian rhythm, insulin secretion, and glucose and carbohydrate homeostasis. The characterization of these likely causal genes can increase our understanding of the underlying biology and offer avenues to develop therapeutics for weight loss. [Display omitted] Hemerich et al. apply multiple computational methods to prioritize the likely causal gene(s) within more than 500 previously reported GWAS-identified BMI-associated loci. They identified 292 high-scoring genes, most of which have not previously been implicated in obesity. Characterization of these likely causal genes can provide insights into obesity biology. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00029297
Volume :
111
Issue :
6
Database :
Academic Search Index
Journal :
American Journal of Human Genetics
Publication Type :
Academic Journal
Accession number :
177601875
Full Text :
https://doi.org/10.1016/j.ajhg.2024.04.016