Large-scale candidate gene analysis of HDL particle features

Area of Science:

• Genetics
• Cardiovascular Disease
• Metabolomics

Background:

• High-density lipoprotein cholesterol (HDL-C) is a key cardiovascular risk marker with strong genetic influence.
• HDL particles are heterogeneous, and detailed phenotyping can enhance understanding of HDL metabolism.
• Previous studies focused on HDL-C, potentially missing genetic associations due to HDL particle diversity.

Purpose of the Study:

• To investigate the genetic underpinnings of HDL metabolism using advanced HDL phenotyping.
• To compare the power of HDL particle size and number versus HDL-C in identifying associated genes.
• To conduct a large-scale candidate gene association analysis for HDL traits.

Main Methods:

• Nuclear Magnetic Resonance (NMR) spectroscopy was used to measure HDL particle size and number in 2024 British Caucasian individuals.
• Genotyping involved over 49,000 single nucleotide polymorphisms (SNPs) across >2,100 cardiometabolic candidate genes.
• Statistical analyses included False Discovery Rate (FDR) correction for multiple testing.

Main Results:

• Standard HDL-C analysis identified significant associations with CETP and SGCD.
• HDL particle size analysis revealed additional associations with LIPC, PLTP, and FBLN5.
• Replication analyses for SGCD and FBLN5 with HDL particle size were unsuccessful in independent cohorts.

Conclusions:

• Advanced HDL phenotyping via NMR spectroscopy is more effective at detecting genes involved in HDL metabolism than traditional HDL-C analysis.
• This study highlights the importance of particle-level analysis for a comprehensive understanding of HDL regulation.
• Further research is needed to validate novel associations and understand their clinical relevance.