Metabolomic Quantitative Trait Loci (mQTL) Mapping Implicates the Ubiquitin Proteasome System in Cardiovascular Disease Pathogenesis

Abstract

Levels of certain circulating short-chain dicarboxylacylcarnitine (SCDA), long-chain dicarboxylacylcarnitine (LCDA) and medium chain acylcarnitine (MCA) metabolites are heritable and predict cardiovascular disease (CVD) events. Little is known about the biological pathways that influence levels of most of these metabolites. Here, we analyzed genetics, epigenetics, and transcriptomics with metabolomics in samples from a large CVD cohort to identify novel genetic markers for CVD and to better understand the role of metabolites in CVD pathogenesis. Using genomewide association in the CATHGEN cohort (N = 1490), we observed associations of several metabolites with genetic loci. Our strongest findings were for SCDA metabolite levels with variants in genes that regulate components of endoplasmic reticulum (ER) stress (USP3, HERC1, STIM1, SEL1L, FBXO25, SUGT1) These findings were validated in a second cohort of CATHGEN subjects (N = 2022, combined p = 8.4x10-6–2.3x10-10). Importantly, variants in these genes independently predicted CVD events. Association of genomewide methylation profiles with SCDA metabolites identified two ER stress genes as differentially methylated (BRSK2 and HOOK2). Expression quantitative trait loci (eQTL) pathway analyses driven by gene variants and SCDA metabolites corroborated perturbations in ER stress and highlighted the ubiquitin proteasome system (UPS) arm. Moreover, culture of human kidney cells in the presence of levels of fatty acids found in individuals with cardiometabolic disease, induced accumulation of SCDA metabolites in parallel with increases in the ER stress marker BiP. Thus, our integrative strategy implicates the UPS arm of the ER stress pathway in CVD pathogenesis, and identifies novel genetic loci associated with CVD event risk.

Metabolomics and Metabolic Diseases: Where Do We Stand?

“…Those SNPs in turn are independently associated with CVD events in time-to-event analysis. Transcriptomic and epigenetic profiling in the same subjects also identified associations between ER stress genes and the DC-AC cluster (Kraus et al, 2015). …”

“…In addition, studies of 478 CATHGEN subjects who underwent coronary artery bypass grafting (CABG) revealed that the same short-chain DC-AC principal component was associated with adverse outcome in univariate analysis (P=0.002), and remained independently predictive of adverse outcomes in multivariable time-to-event analysis (P<0.001) (Shah et al, 2012c). In a follow-up study, integrated omics analysis including metabolomics, GWAS, transcriptomics and epigenetics in the CATHGEN cohort found that the DC-AC diagnostic signature maps with high significance to several SNPs associated with genes involved in ER stress and the protein unfolding response (Kraus et al, 2015). Those SNPs in turn are independently associated with CVD events in time-to-event analysis.…”

UBE2D3 gene overexpression increases radiosensitivity of EC109 esophageal cancer cells in vitro and in vivo

“…Ubiquitin-dependent proteolysis by the 26S proteasome plays a pivotal role in tumorigenesis [12]. In this pathway, E2, which is including UBE2D3, together with ubiquitin ligase (E3), transfers ubiquitin to the specific substrate protein(s) [9]; Polyubiquitinated proteins are recognized by the 26S proteasome and rapidly degraded [13].…”

A complete tool set for molecular QTL discovery and analysis

“…T o increase the explanatory power of genome-wide association studies (GWAS), many genetic studies now routinely combine genetic information with one or multiple molecular phenotypes such as gene expression [1][2][3] , protein abundance 4 , metabolomics 5 , methylation 6 and chromatin activity 7 . This makes the discovery of molecular Quantitative Trait Loci (molQTL) possible; a key step towards better understanding the effects of genetic variants on the cellular machinery and eventually on organismal phenotypes.…”