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Article

Deciphering the genetic landscape of obesity: a data-driven approach to identifying plausible causal genes and therapeutic targets.

Journal of human genetics - 1 Dec 2023

Ang Mia Yang, Takeuchi Fumihiko, Kato Norihiro

Abstract excerpt

OBJECTIVES: Genome-wide association studies (GWAS) have successfully revealed numerous susceptibility loci for obesity. However, identifying the causal genes, pathways, and tissues/cell types responsible for these associations remains a challenge, and standardized analysis workflows are lacking. Additionally, due to limited treatment options for obesity, there is a need for the development of new pharmacological...

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Share to Adipokines, Inflammation, and Metabolic Diseases
Share to Gene Expression Profiling

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genetic Associations and Epidemiology

Share to Genetic Predisposition to Disease

Share to Genome-Wide Association Study

Share to Obesity

Share to Polymorphism, Single Nucleotide

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Source

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Identifiers

PMID: 37620670
DOI: 10.1038/s10038-023-01189-3
PMCID: PMC10678330

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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