Integrating genetic and transcriptomic data to identify genes underlying obesity risk loci

Area of Science:

• Genetics
• Genomics
• Molecular Biology

Background:

• Genome-wide association studies (GWAS) have identified numerous genetic loci associated with body mass index (BMI).
• The biological mechanisms connecting these risk loci to BMI remain largely unknown.
• Integrating omics data offers a pathway to a more comprehensive understanding of BMI-related biological pathways.

Purpose of the Study:

• To identify genes and biological mechanisms that link genetic variations at BMI risk loci to actual BMI.
• To translate findings from GWAS into functional insights by integrating genotype and gene expression data.

Main Methods:

• Analyzed genotype and blood gene expression data from the Framingham Heart Study (FHS) (up to 5619 samples).
• Performed association analyses between single-nucleotide polymorphisms (SNPs) at BMI loci, transcripts, and BMI.
• Utilized a correlated meta-analysis and prioritized transcripts based on Bonferroni-corrected significance and association strength.

Main Results:

• Identified seven genes (NT5C2, GSTM3, SNAPC3, SPNS1, TMEM245, YPEL3, and ZNF646) in five association regions.
• Validated SNAPC3 and YPEL3 in a Hispanic ancestry sample.
• Confirmed associations in various tissues including nucleus accumbens, visceral adipose tissue (VAT), and liver.

Conclusions:

• The identified genes provide a link between genetic variations at obesity risk loci and biological mechanisms.
• These findings contribute to translating GWAS discoveries into functional understanding of obesity.
• This research enhances our knowledge of the molecular underpinnings of BMI regulation.