👤 Stefan Coassin

Our understanding of the genetic regulation of lipoprotein(a) [Lp(a)] is hindered by the complex structure of the LPA gene, limited non-European datasets and its elusive cellular receptor(s). This review summarizes recent efforts and advances providing new insights on its genetic architecture, variability across ancestries and regulators beyond the LPA gene. Impressive advances in DNA sequencing and bioinformatics now resolve LPA variants and kringle IV-type 2 copy number at scale. This provides new reference datasets and enables tools that unlock hidden variation also from already available sequencing datasets. In parallel, genetic studies broaden our understanding of the regulation of Lp(a) across ancestries and improve genetic risk scores. Finally, while recent studies implicate new mechanisms for Lp(a) uptake, upcoming genome-wide gene knockout screens allow comprehensive, agnostic scans for regulators and receptors. Puzzlingly, this still converges on the LDL receptor, whose exact role in Lp(a) uptake remains enigmatic. Technological advances establish a foundation for more accurate genetic risk assessment across ancestries. These advances are enhancing our understanding of Lp(a) regulation and build a framework for future integrative genetic studies, which may shed new light on the evolution of the Lp(a) trait, adding important context for its physiological and clinical relevance. Show less

HDL-mediated cholesterol efflux capacity (CEC) may protect from cardiovascular disease. Thus, we aimed to identify its genetic and non-genetic determinants. We measured CEC to 2% apolipoprotein B-depleted serum using BODIPY-cholesterol and cAMP-stimulated J774A.1 macrophages using serum samples from 4,981 participants in the German Chronic Kidney Disease (GCKD) study. Variance of CEC explained by clinical and biochemical parameters in a multivariable linear regression model was calculated by proportional marginal variance decomposition. A genome-wide association study with 7,746,917 variants was performed based on an additive genetic model. The main model was adjusted for age, sex and principal components 1-10. Further models were selected for sensitivity analysis and to reduce residual variance by known CEC pathways. Variables that explained 1% and more of the variance of CEC were concentrations of triglycerides (12.9%), HDL-cholesterol (11.8%), LDL-cholesterol (3.0%), apolipoprotein A-IV (2.8%), PCSK9 (1.0%), and eGFR (1.0%). The KLKB1 (chr4) and APOE/C1 (chr19) loci were genome-wide significantly (p < 5x10 We identified HDL-cholesterol and triglycerides as the main determinants of CEC. Furthermore, we newly found a significant association of CEC with the KLKB1 and the CLSTN2 locus and confirmed the association with the APOE/C1 locus, likely mediated by triglycerides. Show less

Apolipoprotein A-IV (apoA-IV) has been observed to be associated with lipids, kidney function, adiposity- and diabetes-related parameters. To assess the causal relationship of apoA-IV with these phenotypes, we conducted bidirectional Mendelian randomization (MR) analyses using publicly available summary-level datasets from GWAS consortia on apoA-IV concentrations (n = 13,813), kidney function (estimated glomerular filtration rate (eGFR), n = 133,413), lipid traits (HDL cholesterol, LDL cholesterol, triglycerides, n = 188,577), adiposity-related traits (body-mass-index (n = 322,206), waist-hip-ratio (n = 210,088)) and fasting glucose (n = 133,010). Main analyses consisted in inverse-variance weighted and multivariable MR, whereas MR-Egger regression and weighted median estimation were used as sensitivity analyses. We found that eGFR is likely to be causal on apoA-IV concentrations (53 SNPs; causal effect estimate per 1-SD increase in eGFR = -0.39; 95% CI = [-0.54, -0.24]; p-value = 2.4e-07). Triglyceride concentrations were also causally associated with apoA-IV concentrations (40 SNPs; causal effect estimate per 1-SD increase in triglycerides = -0.06; 95% CI = [-0.08, -0.04]; p-value = 4.8e-07), independently of HDL-C and LDL-C concentrations (causal effect estimate from multivariable MR = -0.06; 95% CI = [-0.10, -0.02]; p-value = 0.0014). Evaluating the inverse direction of causality revealed a possible causal association of apoA-IV on HDL-cholesterol (2 SNPs; causal effect estimate per one percent increase in apoA-IV = -0.40; 95% CI = [-0.60, -0.21]; p-value = 5.5e-05). Show less

Apolipoprotein A-IV (apoA-IV) is a major component of HDL and chylomicron particles and is involved in reverse cholesterol transport. It is an early marker of impaired renal function. We aimed to identify genetic loci associated with apoA-IV concentrations and to investigate relationships with known susceptibility loci for kidney function and lipids. A genome-wide association meta-analysis on apoA-IV concentrations was conducted in five population-based cohorts (n = 13,813) followed by two additional replication studies (n = 2,267) including approximately 10 M SNPs. Three independent SNPs from two genomic regions were significantly associated with apoA-IV concentrations: rs1729407 near APOA4 (P = 6.77 × 10 Show less