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- Bauer, S, et al.
(author)
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Identification of the Transcription Factor ATF3 as a Direct and Indirect Regulator of the LDLR
- 2022
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In: Metabolites. - : MDPI AG. - 2218-1989. ; 12:9
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Journal article (peer-reviewed)abstract
- Coronary artery disease (CAD) is a complex, multifactorial disease caused, in particular, by inflammation and cholesterol metabolism. At the molecular level, the role of tissue-specific signaling pathways leading to CAD is still largely unexplored. This study relied on two main resources: (1) genes with impact on atherosclerosis/CAD, and (2) liver-specific transcriptome analyses from human and mouse studies. The transcription factor activating transcription factor 3 (ATF3) was identified as a key regulator of a liver network relevant to atherosclerosis and linked to inflammation and cholesterol metabolism. ATF3 was predicted to be a direct and indirect (via MAF BZIP Transcription Factor F (MAFF)) regulator of low-density lipoprotein receptor (LDLR). Chromatin immunoprecipitation DNA sequencing (ChIP-seq) data from human liver cells revealed an ATF3 binding motif in the promoter regions of MAFF and LDLR. siRNA knockdown of ATF3 in human Hep3B liver cells significantly upregulated LDLR expression (p < 0.01). Inflammation induced by lipopolysaccharide (LPS) stimulation resulted in significant upregulation of ATF3 (p < 0.01) and subsequent downregulation of LDLR (p < 0.001). Liver-specific expression data from human CAD patients undergoing coronary artery bypass grafting (CABG) surgery (STARNET) and mouse models (HMDP) confirmed the regulatory role of ATF3 in the homeostasis of cholesterol metabolism. This study suggests that ATF3 might be a promising treatment candidate for lowering LDL cholesterol and reducing cardiovascular risk.
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- Bjorkegren, JLM, et al.
(author)
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Atherosclerosis: Recent developments
- 2022
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In: Cell. - : Elsevier BV. - 1097-4172 .- 0092-8674. ; 185:10, s. 1630-1645
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Journal article (peer-reviewed)
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- Cohain, AT, et al.
(author)
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An integrative multiomic network model links lipid metabolism to glucose regulation in coronary artery disease
- 2021
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In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 12:1, s. 547-
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Journal article (peer-reviewed)abstract
- Elevated plasma cholesterol and type 2 diabetes (T2D) are associated with coronary artery disease (CAD). Individuals treated with cholesterol-lowering statins have increased T2D risk, while individuals with hypercholesterolemia have reduced T2D risk. We explore the relationship between lipid and glucose control by constructing network models from the STARNET study with sequencing data from seven cardiometabolic tissues obtained from CAD patients during coronary artery by-pass grafting surgery. By integrating gene expression, genotype, metabolomic, and clinical data, we identify a glucose and lipid determining (GLD) regulatory network showing inverse relationships with lipid and glucose traits. Master regulators of the GLD network also impact lipid and glucose levels in inverse directions. Experimental inhibition of one of the GLD network master regulators, lanosterol synthase (LSS), in mice confirms the inverse relationships to glucose and lipid levels as predicted by our model and provides mechanistic insights.
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- Li, L, et al.
(author)
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Transcriptome-wide association study of coronary artery disease identifies novel susceptibility genes
- 2022
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In: Basic research in cardiology. - : Springer Science and Business Media LLC. - 1435-1803 .- 0300-8428. ; 117:1, s. 6-
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Journal article (peer-reviewed)abstract
- The majority of risk loci identified by genome-wide association studies (GWAS) are in non-coding regions, hampering their functional interpretation. Instead, transcriptome-wide association studies (TWAS) identify gene-trait associations, which can be used to prioritize candidate genes in disease-relevant tissue(s). Here, we aimed to systematically identify susceptibility genes for coronary artery disease (CAD) by TWAS. We trained prediction models of nine CAD-relevant tissues using EpiXcan based on two genetics-of-gene-expression panels, the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) and the Genotype-Tissue Expression (GTEx). Based on these prediction models, we imputed gene expression of respective tissues from individual-level genotype data on 37,997 CAD cases and 42,854 controls for the subsequent gene-trait association analysis. Transcriptome-wide significant association (i.e. P < 3.85e−6) was observed for 114 genes. Of these, 96 resided within previously identified GWAS risk loci and 18 were novel. Stepwise analyses were performed to study their plausibility, biological function, and pathogenicity in CAD, including analyses for colocalization, damaging mutations, pathway enrichment, phenome-wide associations with human data and expression-traits correlations using mouse data. Finally, CRISPR/Cas9-based gene knockdown of two newly identified TWAS genes, RGS19 and KPTN, in a human hepatocyte cell line resulted in reduced secretion of APOB100 and lipids in the cell culture medium. Our CAD TWAS work (i) prioritized candidate causal genes at known GWAS loci, (ii) identified 18 novel genes to be associated with CAD, and iii) suggested potential tissues and pathways of action for these TWAS CAD genes.
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