In a recent study published within the journal Nature Genetics, researchers carried out a genome-wide association study (GWAS) of triglyceride (TG):high-density lipoprotein-cholesterol (HDL-C) ratios amongst 402,398 European people in the UK Biobank (UKBB).
Study: Comprehensive genetic study of the insulin resistance marker TG:HDL-C within the UK Biobank. Image Credit: Victor Moussa / Shutterstock
Background on Insulin Resistance and Genetic Markers
Insulin resistance (IR), a big risk factor for metabolic disease, is measured by the reference standard strategy of glucose clamping. Easy techniques just like the insulin sensitivity index (ISI) and the homeostatic model assessment for IR (HOMA-IR) have identified 130 loci related to insulin resistance related to genes involved in glycogen metabolism, insulin receptor pathways, and adipogenesis. Nonetheless, the genetic analyses have a limited scale in comparison with those from groups just like the UKBB or the Genetic Investigation of Anthropometric Traits (GIANT) Consortium, which collected data on non-fasting lipids.
Methodology of the Genome-Wide Association Study
In the current study, researchers performed a genetic study of TG: HDL-C levels, which indicate insulin resistance. The study focused on high-confidence insulin resistance-associated single-nucleotide polymorphisms (SNPs), attaining statistical significance values in external analyses of insulin resistance. The high-confidence-type loci were explored relative to insulin biology, analyzed for priorly undocumented associations with insulin resistance, and assessed for his or her contributions to illness within the external datasets.
The team obtained serological HDL-C and TG levels for the participants at enrolment. They calculated TG:HDL-C values and performed genome-wide association research by linear mixed modeling using the Scalable and Accurate Implementation of GEneralized mixed model (SAIGE). They applied conditional and joint multiple-SNP evaluation (COJO) to extract independent SNPs. The study approach included data-based expression prioritization integration for complex traits (DEPICT) prioritization, proximity, tissue expression, and the expression quantitative trait loci (eQTLs) to pick out the most certainly causative gene.
To discover TG:HDL-C genetic loci with priorly undocumented relationships with IR, the researchers performed conditional analyses including 130 variations from IR-related traits, as documented by the Meta-Analyses of Glucose and Insulin-related Traits Consortium (MAGIC) study researchers. They investigated whether TG:HDL-C included the 130 IR-associated loci previously identified within the MAGIC study. In total, 114 of the 369 independent variations of TG:HDL-C showed P values below 0.05 in at the very least one in every of the IR characteristics. 72 of the 114 high-confidence loci haven’t any previous IR studies.
Subsequently, the researchers investigated the 114 SNPs with a Bonferroni-adjusted P value of <0.05 in other publicly available studies of metabolic characteristics. To find out the role of the high-confidence insulin resistance-associated SNPs in non-European ancestries, the team conducted a GWAS of TG:HDL-C values for South Asian, African, and Chinese individuals.
Results: Identifying Genetic Loci Related to Insulin Resistance
The team identified 369 independent single-nucleotide polymorphisms, with 114 having p-values below 0.050 in other genome-level insulin resistance studies. These 114 genetic loci clustered into five groups on phenome-wide evaluation and were enriched for candidate genes crucial to insulin signaling, protein metabolism, and adipocyte physiology. The team developed polygenic-risk scores using the high-confidence insulin resistance-related loci. They identified associations with hyperglyceridemia, diabetes, hypertension, ischemic heart disease, and non-alcoholic fatty liver disease.
GWAS identified 369 independent genetic loci for the TG:HDL-C biomarker, and 32,573 variants attained genome-wide statistical significance for the TG:HDL-C biomarker after excluding insertions and deletions, ambiguous or multiallelic single-nucleotide polymorphisms, and people unavailable within the Michigan Genomics Initiative (MGI). Of 369 independent SNPs, 318 had no prior reports for IR. In total, 322 of the 369 SNPs remained genome-wide significant. Of the 369 independent SNPs, 114 were high-confidence insulin resistance-associated loci.
Of 130 genetic loci, the team detected 127 within the UKBB. Of 127 priorly documented variants, 92 (72%) showed P values below 0.050 in summary statistical data of the study, and 57 (45%) out of 127 genetic variants attained genome-wide statistical significance. The phenome-wide association study identified distinct effects inside metabolic traits. The team found that the subgroups had distinct impacts on insulin-related parameters similar to the waist-hip ratio (WHR), body mass index (BMI), serum lipids, non-alcoholic fatty liver disease (NAFLD, evaluated as proton density fat fraction), and estimated glomerular filtration rate (eGFR).
All subgroups were related to increased TGs and lowered HDL, the first phenotype. High-confidence insulin resistance loci were enriched for insulin-related biology, with 114 loci showing robust enrichment in fatty tissues. Thirty-one high-confidence loci showed sex-specific effects. The study identified 24 SNPs with higher sex-specific effects in females, enriched for loci showing significant associations with weight gain (WHR) adjusted for body mass index. Further evaluation of those sex-specific, high-confidence insulin resistance-related loci may help explain observed differences in metabolic phenotypes between men and ladies.
Conclusions and Implications for Understanding Insulin Resistance
The study findings showed that 369 SNPs are central to insulin resistance (IR) pathology, explaining 3.2% of TG: HDL-C levels and referring to IR-related traits. These loci are related to adipocyte biology, the endocrine system, growth and cancer pathways, hepatic genes, and people involved in the feminine reproductive system. These high-confidence insulin resistance-associated loci represent liver-related genes, including primary metabolic enzymes. Mutations in TM6SF2, a lipoprotein excretion regulator, may result in fat retention and increased IR.