Discovery of functional variants regulating lipid metabolism in an East Asian population.

Multi-omic characterization of the Hispanic/Latino blood lipidome reveals an additional locus and attenuated genetic prediction.

A lipidome-wide GWAS of 830 lipid species in 2,287 Hispanic/Latino participants and predictive modeling across omics layers provided a genetic landscape of lipid metabolism in a highly burdened population and highlights the challenges in predicting lipid abundance.

Genome-Wide Association of Genetic Variants with Intestinal Cholesterol Absorption Markers in a European Population

Background: Interindividual variability in intestinal cholesterol absorption contributes to differences in serum lipid concentrations and cardiovascular risk. Total cholesterol (TC)-standardized campesterol and sitosterol levels are established markers of cholesterol absorption. However, genetic variants in Europeans associated with these markers remain incompletely characterized. Methods: A genome-wide association study (GWAS) was performed in 398 healthy individuals of European ancestry. Samples were genotyped using the Precision Medicine Research Array (PMRA). After quality control, 166,037 common genetic variants with a minor allele frequency (MAF) > 20% were analyzed. Associations between genetic variants and intestinal cholesterol absorption markers (campesterol/TC and sitosterol/TC) were evaluated using additive and recessive genetic models. Results: A total of 16 SNPs were identified. Eight SNPs overlapped with both campesterol/TC and sitosterol/TC, of which 2 reached genome-wide significance. Six overlapping SNPs were associated with higher concentrations of both markers: 3 SNPs in ABCG8 (rs4299376, rs6544713, and rs4245791), 1 SNP in ADAM12 (rs4962526), and 2 SNPs in non-coding regions (rs260769 and rs5011112). Additionally, two SNPs (rs2033254 and rs12708980) in CETP were associated with lower concentrations of these markers. Five of the identified SNPs have not previously been linked to markers of intestinal cholesterol absorption. Conclusions: This GWAS confirmed previously reported associations within ABCG8 and identified candidate loci in CETP and ADAM12 that may be involved in intestinal cholesterol absorption. These findings contribute to our understanding of genetic factors underlying intestinal cholesterol absorption and highlight candidate loci for future replication and functional studies.

Integrative genomic and transcriptomic analysis of hypertension in a Taiwanese population.

OBJECTIVES Hypertension is highly prevalent in Asian populations and represents a major cardiovascular risk factor. However, most genome-wide association studies (GWASs) and transcriptome-wide association studies (TWASs) have focused primarily on Caucasian cohorts. This study aimed to identify genetic loci and gene expression signatures associated with hypertension in an Asian population. METHODS We analyzed 10 739 hypertensive patients and 49 668 controls from the Taiwan Biobank, testing 4 512 191 genome-wide single nucleotide polymorphisms (SNPs). Integrated GWAS, TWAS, and expression quantitative trait locus (eQTL) analyses were conducted to characterize genetic risk. Additionally, a polygenic risk score (PRS) was constructed using a split-sample design to evaluate genetic risk stratification. RESULTS We identified 14 loci significantly associated with hypertension, including a novel locus at 5p13.1. eQTL analysis linked this locus to DAB2 expression in whole blood. TWAS detected 55 hypertension-associated genes, with 20 (36%) overlapping GWAS loci. Several novel genes outside GWAS loci, including FBXL15, KCNIP2, and CRIP3, were highly significant and implicated in vascular biology and hypertension mechanisms. PRS analysis effectively differentiated hypertension risk, with individuals in the top 10% showing a > 3.5-fold increased risk compared to the bottom 10%. CONCLUSIONS Our findings provide new insights into the genetic and transcriptomic landscape of hypertension in Asians. The identification of novel loci and genes advances understanding of disease biology and may guide precision medicine approaches for risk prediction and therapeutic development.

Using human proteomic and lipidomic to exploration drug target of bladder cancer

Cell-type-specific polygenic risk scores reveal adipocyte-related interactions with lipids in coronary artery disease

Background: Genome-wide polygenic risk scores (PRSs) for coronary artery disease (CAD) aggregate genetic effects across the genome and may obscure biologically distinct mechanisms. We aimed to develop cell-type-specific PRSs (csPRSs) using single-cell RNA sequencing (scRNA-seq) data and investigate their interactions with lipids on CAD risk. Methods: Using publicly available scRNA-seq data from human heart tissue, we identified cell-type-specific genes across 13 major cell types and 64 subpopulations and grouped them into 10 cell clusters. Variants from a CAD genome-wide association study (GWAS) were mapped to cluster-specific genes to construct csPRSs for European-ancestry participants from the UK Biobank (UKB). Interactions between csPRSs and lipid-related phenotypes were evaluated using Cox proportional hazards models and stratified analyses, with significant findings further assessed in an internal validation dataset. Results: Distinct interaction patterns with lipid phenotypes were observed across csPRSs. Low-density lipoprotein (LDL)-related lipid traits, including apolipoprotein B (ApoB), low-density lipoprotein cholesterol (LDL-C), and total cholesterol (cholesterol), primarily interacted with adipocytes (Adip), whereas high-density lipoprotein (HDL) traits interacted with endothelial-mesothelial (EC-Meso), fibroblast (FB), and immune-cell csPRSs. Notably, interactions for Adip csPRSs were replicated in internal validation analyses. Conclusions: Cell-type-specific decomposition of genome-wide PRSs for CAD identified biologically distinct lipid interactions that were not captured by the genome-wide PRS. Adipocyte genetic factors may influence how LDL lipids affect CAD risk. These findings highlight the potential of cell-type-informed PRSs to improve the biological interpretation of PRSs and provide insights into the heterogeneous mechanisms underlying CAD.

Genetic Variants Related to Coffee Consumption and Their Association with Obesity Risk: A Systematic Review

Coffee consumption has been associated with metabolic health and obesity risk, potentially through bioactive compounds that influence energy metabolism. Genetic variation may partly explain interindividual differences in these effects, yet the population-specific relevance of such variants remains unclear. However, the population-specific relevance of these genetic variants remains insufficiently explored. OBJECTIVES: This systematic review synthesizes genetic variants associated with coffee consumption and obesity susceptibility across ethnically diverse populations and validates their relevance in global populations using public genomic databases. METHODS: A comprehensive literature search was conducted in PubMed, Scopus, Web of Science, and Google Scholar to identify genome-wide association studies and candidate gene studies examining genetic variants related to coffee consumption, caffeine metabolism, and obesity-related traits. Identified variants were cross-referenced with dbSNP and the GWAS Catalog to assess allele frequency distributions and genomic support. Study quality was evaluated using the National Institutes of Health assessment tools for observational studies. RESULTS: The review identified genetic variants involved in caffeine metabolism (POR, ALDH2, GCKR), neuroregulation and appetite control (BDNF), taste perception (TAS2R38, CA6), adipokine regulation (KNG1), dietary fat response (APOA2), and obesity susceptibility (MC4R, ARL15).   Public genomic database analyses suggest that several variants are consistently observed across global populations, supporting their potential generalizability. CONCLUSION: This review highlights the broad population-genetic predispositions underlying the relationship between coffee consumption and obesity risk and supports the need for future research that integrates multi-omics approaches with in vivo and in vitro models to elucidate the biological mechanisms of coffee-related genetic variation.