Dietary intake, a major contributor to the global obesity epidemic 1-5 , is a complex phenotype partially affected by innate physiological processes. [6][7][8][9][10][11] However, previous genome-wide association studies (GWAS) have only implicated a few loci in variability of dietary composition. 12-14 Here, we present a multi-trait genome-wide association meta-analysis of inter-individual variation in dietary intake in 283,119 European-ancestry participants from UK Biobank and CHARGE consortium, and identify 96 genome-wide significant loci. Dietary intake signals map to different brain tissues and are enriched for genes expressed in b1tanycytes and serotonergic and GABAergic neurons. We also find enrichment of biological pathways related to neurogenesis. Integration of cell-line and brainspecific epigenomic annotations identify 15 additional loci. Clustering of genomewide significant variants yields three main genetic clusters with distinct associations with obesity and type 2 diabetes (T2D). Overall, these results enhance biological understanding of dietary composition, highlight neural mechanisms, and support functional follow-up experiments.As dietary components are strongly correlated, we conducted a multi-trait genomewide association meta-analysis of overall variation in dietary intake among 283,119European-ancestry participants from the UK Biobank 15 and the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium 14 (Methods; Supplementary Table 1). First, we conducted single-trait GWAS for the proportion of total energy intake from carbohydrate, fat, and protein in UK Biobank (n=192,005).Next, single-trait GWAS from the UK Biobank and CHARGE Consortium (n=91,114) were meta-analyzed and combined into a multi-trait genome-wide association metaanalysis (Methods). An analysis overview is presented in Supplementary Fig. 1.We evaluated dietary intake using 24-hour web-based diet recall in the UK Biobank 16,17 and validated food frequency questionnaires, diet history and diet records in the CHARGE Consortium. 14 We observed strong genome-wide genetic correlations for nutrient estimates between the UK Biobank and CHARGE datasets (r g >0.6 for all; P <0.001; Supplementary Table 2). The quantile-quantile plots of single-trait and multi-trait meta-analyses showed moderate inflation (l GC ranging from 1.12 to 1.17) with a linkage disequilibrium (LD) score intercept 18 of ~1 (standard error (s.e.) = 0.01), indicating that most inflation could be explained by polygenic signal ( Supplementary Fig. 2, Supplementary Table 3). In single-trait meta-analyses, genome-wide SNP-based heritability 19 was estimated at 3.9% (s.e.=0.01), 2.8% (s.e.=0.01), and 3.0% (s.e.=0.01) for carbohydrate, fat, and protein, respectively ( Supplementary Table 3), in line with previous GWAS findings 12,14 and other behavioral phenotypes such as tobacco or alcohol use. 20
Background: Obstructive sleep apnea (OSA) and its features, such as chronic intermittent hypoxia (IH), may differentially affect specific molecular pathways and processes in the pathogenesis of coronary artery disease (CAD) and influence the subsequent risk and severity of CAD events. In particular, competing adverse (e.g. inflammatory) and protective (e.g. increased coronary collateral blood flow) mechanisms may operate, but remain poorly understood. We hypothesize that common genetic variation in selected molecular pathways influences the likelihood of CAD events differently in individuals with and without OSA, in a pathway-dependent manner. Methods: We selected a cross-sectional sample of 471,877 participants from the UK Biobank, among whom we ascertained 4,974 to have OSA, 25,988 to have CAD, and 711 to have both. We calculated pathway-specific polygenic risk scores (PS-PRS) for CAD, based on 6.6 million common variants evaluated in the CARDIoGRAMplusC4D genome-wide association study (GWAS), annotated to specific genes and pathways using functional genomics databases. Based on evidence of involvement with IH and CAD, we tested PS-PRS for the HIF-1, VEGF, NFkB and TNF signaling pathways. Results: In a multivariable-adjusted logistic generalized additive model, elevated PS-PRSs for the KEGG VEGF pathway (39 genes) associated with protection for CAD in OSA (interaction odds ratio 0.86, p = 6E-04). By contrast, the genome-wide CAD PRS did not show evidence of statistical interaction with OSA. Conclusions: We find evidence that pathway-specific genetic risk of CAD differs between individuals with and without OSA in a qualitatively pathway-dependent manner, consistent with the previously studied phenomena whereby features of OSA may have both positive and negative effects on CAD. These results provide evidence that gene-by-environment interaction influences CAD risk in certain pathways among people with OSA, an effect that is not well-captured by the genome-wide PRS. These results can be followed up to study how OSA interacts with genetic risk at the molecular level, and potentially to personalize OSA treatment and reduce CAD risk according to individual pathway-specific genetic risk profiles.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.