Metabolomic Quantitative Trait Loci (mQTL) Mapping Implicates the Ubiquitin Proteasome System in Cardiovascular Disease Pathogenesis.
Journal Article (Journal Article)
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.
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Duke Authors
- Bain, James R.
- Gregory, Simon Gray
- Hauser, Elizabeth Rebecca
- Kraus, William Erle
- Muoio, Deborah Marie
- Newgard, Christopher Bang
- Shah, Svati Hasmukh
Cited Authors
- Kraus, WE; Muoio, DM; Stevens, R; Craig, D; Bain, JR; Grass, E; Haynes, C; Kwee, L; Qin, X; Slentz, DH; Krupp, D; Muehlbauer, M; Hauser, ER; Gregory, SG; Newgard, CB; Shah, SH
Published Date
- November 2015
Published In
Volume / Issue
- 11 / 11
Start / End Page
- e1005553 -
PubMed ID
- 26540294
Pubmed Central ID
- PMC4634848
Electronic International Standard Serial Number (EISSN)
- 1553-7404
Digital Object Identifier (DOI)
- 10.1371/journal.pgen.1005553
Language
- eng
Conference Location
- United States