Dataset Information

Large-scale Metabolomic Analysis Reveals Potential Biomarkers for Early Stage Coronary Atherosclerosis.

ABSTRACT: Coronary atherosclerosis (CAS) is the pathogenesis of coronary heart disease, which is a prevalent and chronic life-threatening disease. Initially, this disease is not always detected until a patient presents with seriously vascular occlusion. Therefore, new biomarkers for appropriate and timely diagnosis of early CAS is needed for screening to initiate therapy on time. In this study, we used an untargeted metabolomics approach to identify potential biomarkers that could enable highly sensitive and specific CAS detection. Score plots from partial least-squares discriminant analysis clearly separated early-stage CAS patients from controls. Meanwhile, the levels of 24 metabolites increased greatly and those of 18 metabolites decreased markedly in early CAS patients compared with the controls, which suggested significant metabolic dysfunction in phospholipid, sphingolipid, and fatty acid metabolism in the patients. Furthermore, binary logistic regression showed that nine metabolites could be used as a combinatorial biomarker to distinguish early-stage CAS patients from controls. The panel of nine metabolites was then tested with an independent cohort of samples, which also yielded satisfactory diagnostic accuracy (AUC?=?0.890). In conclusion, our findings provide insight into the pathological mechanism of early-stage CAS and also supply a combinatorial biomarker to aid clinical diagnosis of early-stage CAS.

SUBMITTER: Gao X

PROVIDER: S-EPMC5603568 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Large-scale Metabolomic Analysis Reveals Potential Biomarkers for Early Stage Coronary Atherosclerosis.

Gao Xueqin X Ke Chaofu C Liu Haixia H Liu Wei W Li Kang K Yu Bo B Sun Meng M

Scientific reports 20170918 1

Coronary atherosclerosis (CAS) is the pathogenesis of coronary heart disease, which is a prevalent and chronic life-threatening disease. Initially, this disease is not always detected until a patient presents with seriously vascular occlusion. Therefore, new biomarkers for appropriate and timely diagnosis of early CAS is needed for screening to initiate therapy on time. In this study, we used an untargeted metabolomics approach to identify potential biomarkers that could enable highly sensitive ...[more]

PMID: 28924163

Similar Datasets

Project description:BackgroundVascular calcification is associated with poor cardiovascular outcome. Histochemical analysis of calcification and the expression of proteins involved in mineralization are usually based on whole section analysis, thereby often ignoring regional differences in atherosclerotic lesions. At present, limited information is available about factors involved in the initiation and progression of atherosclerosis.Aim of this studyThis study investigates the intra-section association of micro-calcifications with markers for atherosclerosis in randomly chosen section areas of human coronary arteries. Moreover, the possible causal relationship between calcifying vascular smooth muscle cells and inflammation was explored in vitro.Technical approachTo gain insights into the pathogenesis of atherosclerosis, we performed analysis of the distribution of micro-calcifications using a 3-MeV proton microbeam. Additionally, we performed systematic analyses of 30 to 40 regions of 12 coronary sections obtained from 6 patients including histology and immuno-histochemistry. Section areas were classified according to CD68 positivity. In vitro experiments using human vascular smooth muscle cells (hVSMCs) were performed to evaluate causal relationships between calcification and inflammation.ResultsFrom each section multiple areas were randomly chosen and subsequently analyzed. Depositions of calcium crystals at the micrometer scale were already observed in areas with early pre-atheroma type I lesions. Micro-calcifications were initiated at the elastica interna concomitantly with upregulation of the uncarboxylated form of matrix Gla-protein (ucMGP). Both the amount of calcium crystals and ucMGP staining increased from type I to IV atherosclerotic lesions. Osteochondrogenic markers BMP-2 and osteocalcin were only significantly increased in type IV atheroma lesions, and at this stage correlated with the degree of calcification. From atheroma area type III onwards a considerable number of CD68 positive cells were observed in combination with calcification, suggesting a pro-inflammatory effect of micro-calcifications. In vitro, invasion assays revealed chemoattractant properties of cell-culture medium of calcifying vascular smooth muscle cells towards THP-1 cells, which implies pro-inflammatory effect of calcium deposits. Additionally, calcifying hVSMCs revealed a pro-inflammatory profile as compared to non-calcifying hVSMCs.ConclusionOur data indicate that calcification of VSMCs is one of the earliest events in the genesis of atherosclerosis, which strongly correlates with ucMGP staining. Our findings suggest that loss of calcification inhibitors and/or failure of inhibitory capacity is causative for the early precipitation of calcium, with concomitant increased inflammation followed by osteochondrogenic transdifferentiation of VSMCs.

Project description:BackgroundThe etiology of colorectal cancer is not fully understood.MethodsUsing genetic variants and metabolomics data including 217 metabolites from the Framingham Heart Study (n = 1,357), we built genetic prediction models for circulating metabolites. Models with prediction R2 > 0.01 (Nmetabolite = 58) were applied to predict levels of metabolites in two large consortia with a combined sample size of approximately 46,300 cases and 59,200 controls of European and approximately 21,700 cases and 47,400 controls of East Asian (EA) descent. Genetically predicted levels of metabolites were evaluated for their associations with colorectal cancer risk in logistic regressions within each racial group, after which the results were combined by meta-analysis.ResultsOf the 58 metabolites tested, 24 metabolites were significantly associated with colorectal cancer risk [Benjamini-Hochberg FDR (BH-FDR) < 0.05] in the European population (ORs ranged from 0.91 to 1.06; P values ranged from 0.02 to 6.4 × 10-8). Twenty one of the 24 associations were replicated in the EA population (ORs ranged from 0.26 to 1.69, BH-FDR < 0.05). In addition, the genetically predicted levels of C16:0 cholesteryl ester was significantly associated with colorectal cancer risk in the EA population only (OREA: 1.94, 95% CI, 1.60-2.36, P = 2.6 × 10-11; OREUR: 1.01, 95% CI, 0.99-1.04, P = 0.3). Nineteen of the 25 metabolites were glycerophospholipids and triacylglycerols (TAG). Eighteen associations exhibited significant heterogeneity between the two racial groups (PEUR-EA-Het < 0.005), which were more strongly associated in the EA population. This integrative study suggested a potential role of lipids, especially certain glycerophospholipids and TAGs, in the etiology of colorectal cancer.ConclusionsThis study identified potential novel risk biomarkers for colorectal cancer by integrating genetics and circulating metabolomics data.ImpactThe identified metabolites could be developed into new tools for risk assessment of colorectal cancer in both European and EA populations.

Project description:BackgroundVenous thromboembolism (VTE) is a leading cause of cardiovascular mortality. The diagnosis of acute VTE is based on complex imaging exams due to the lack of biomarkers. Recent multi-omics based research has contributed to the development of novel biomarkers in cardiovascular diseases. Our aim was to determine whether patients with acute VTE have differences in the metabolomic profile compared to non-acute VTE.MethodsThis observational trial included 62 patients with clinical suspicion of acute deep vein thrombosis or pulmonary embolism, admitted to the emergency room. There were 50 patients diagnosed with acute VTE and 12 with non-acute VTE conditions and no significant differences were found between the two groups for clinical and demographic characteristics. Metabolomics assays identified and quantified a final number of 91 metabolites in plasma and 55 metabolites in red blood cells (RBCs). Plasma from acute VTE patients expressed tendency to a specific metabolomic signature, with univariate analyses revealing 23 significantly different molecules between acute VTE patients and controls (p < 0.05). The most relevant metabolic pathway with the strongest impact on the acute VTE phenotype was D-glutamine and D-glutamate (p = 0.001, false discovery rate = 0.06). RBCs revealed a specific metabolomic signature in patients with a confirmed diagnosis of DVT or PE that distinguished them from other acutely diseased patients, represented by 20 significantly higher metabolites and four lower metabolites. Three of those metabolites revealed high performant ROC curves, including adenosine 3',5'-diphosphate (AUC 0.983), glutathione (AUC 0.923), and adenine (AUC 0.91). Overall, the metabolic pathway most impacting to the differences observed in the RBCs was the purine metabolism (p = 0.000354, false discovery rate = 0.68).ConclusionsOur findings show that metabolite differences exist between acute VTE and nonacute VTE patients admitted to the ER in the early phases. Three potential biomarkers obtained from RBCs showed high performance for acute VTE diagnosis. Further studies should investigate accessible laboratory methods for the future daily practice usefulness of these metabolites for the early diagnosis of acute VTE in the ER.

Dataset Information

Large-scale Metabolomic Analysis Reveals Potential Biomarkers for Early Stage Coronary Atherosclerosis.

Publications

Large-scale Metabolomic Analysis Reveals Potential Biomarkers for Early Stage Coronary Atherosclerosis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets