Large-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci

Area of Science:

• Genetics
• Cardiovascular Disease Research
• Metabolic Disorders

Background:

• Genome-wide association studies (GWASs) have identified numerous single nucleotide polymorphisms (SNPs) linked to plasma lipid variations.
• However, a comprehensive understanding of the genetic architecture of lipid levels, including high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), remains incomplete.

Purpose of the Study:

• To investigate whether a dense gene-centric genotyping approach can identify additional genetic loci associated with plasma lipid phenotypes.
• To discover novel SNPs and genes contributing to variations in HDL-C, LDL-C, TC, and TGs.

Main Methods:

• A large-scale meta-analysis involving 32 studies and 66,240 individuals of European ancestry was conducted.
• A custom genotyping array (ITMAT-Broad-CARe) with approximately 50,000 SNPs across ~2,000 candidate genes was utilized.
• Associations were validated through replication in an independent cohort (24,736 samples) and the Global Lipid Genetic Consortium.

Main Results:

• The study identified multiple unreported SNPs within established lipid genes for HDL-C, LDL-C, TC, and TGs.
• Several novel lipid-related SNPs were discovered in previously unreported genes, including DGAT2, HCAR2, GPIHBP1, PPARG, FTO, SOCS3, APOH, SPTY2D1, BRCA2, VLDLR, UGT1A1, UBE3B, FCGR2A, CHUK, INSIG2, SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2.
• The proportion of explained phenotypic variance was comparable to traditional GWAS meta-analyses, with values ranging from 8.0% for TGs to 10.3% for TC.

Conclusions:

• A dense gene-centric approach effectively identified novel SNPs and previously unknown loci associated with plasma lipid levels.
• This focused genotyping strategy offers a powerful complement to GWAS, enhancing the understanding of plasma lipid heritability.
• The findings contribute to a more complete genetic map of lipid metabolism and cardiovascular risk.