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  • Frontiers Media SA  (2)
  • Chen, Hui  (2)
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  • Frontiers Media SA  (2)
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  • 1
    Online Resource
    Online Resource
    datasheet2.xlsx
    Frontiers Media SA ; 2021
    In:  Frontiers in Molecular Biosciences Vol. 8 ( 2021-4-14)
    Details
    In: Frontiers in Molecular Biosciences, Frontiers Media SA, Vol. 8 ( 2021-4-14)
    Abstract: Background: Coronary stenosis severity determines ischemic symptoms and adverse outcomes. The metabolomic analysis of human fluids can provide an insight into the pathogenesis of complex disease. Thus, this study aims to investigate the metabolomic and lipidomic biomarkers of coronary artery disease (CAD) severity and to develop diagnostic models for distinguishing individuals at an increased risk of atherosclerotic burden and plaque instability. Methods: Widely targeted metabolomic and lipidomic analyses of plasma in 1,435 CAD patients from three independent centers were performed. These patients were classified as stable coronary artery disease (SCAD), unstable angina (UA), and myocardial infarction (MI). Associations between CAD stages and metabolic conditions were assessed by multivariable-adjusted logistic regression. Furthermore, the least absolute shrinkage and selection operator logistic-based classifiers were used to identify biomarkers and to develop prediagnostic models for discriminating the diverse CAD stages. Results: On the basis of weighted correlation network analysis, 10 co-clustering metabolite modules significantly ( p & lt; 0.05) changed at different CAD stages and showed apparent correlation with CAD severity indicators. Moreover, cross-comparisons within CAD patients characterized that a total of 72 and 88 metabolites/lipid species significantly associated with UA (vs. SCAD) and MI (vs. UA), respectively. The disturbed pathways included glycerophospholipid metabolism, and cysteine and methionine metabolism. Furthermore, models incorporating metabolic and lipidomic profiles with traditional risk factors were constructed. The combined model that incorporated 11 metabolites/lipid species and four traditional risk factors represented better discrimination of UA and MI (C-statistic = 0.823, 95% CI, 0.783–0.863) compared with the model involving risk factors alone (C-statistic = 0.758, 95% CI, 0.712–0.810). The combined model was successfully used in discriminating UA and MI patients ( p & lt; 0.001) in a three-center validation cohort. Conclusion: Differences in metabolic profiles of diverse CAD subtypes provided a new approach for the risk stratification of unstable plaque and the pathogenesis decipherment of CAD progression.
    Type of Medium: Online Resource
    ISSN: 2296-889X
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fmolb.2021.632950
    DOI: 10.3389/fmolb.2021.632950.s001
    DOI: 10.3389/fmolb.2021.632950.s002
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2814330-9
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  • 2
    Online Resource
    Online Resource
    Data_Sheet_1.docx
    Frontiers Media SA ; 2021
    In:  Frontiers in Genetics Vol. 12 ( 2021-3-25)
    Details
    In: Frontiers in Genetics, Frontiers Media SA, Vol. 12 ( 2021-3-25)
    Abstract: Plasma lipids have been at the center stage of the prediction and prevention strategies for cardiovascular diseases (CVDs), and novel lipidomic traits have been recognized as reliable biomarkers for CVD risk prediction. The mitochondria serve as energy supply sites for cells and can synthesize a variety of lipids autonomously. Therefore, investigating the relationships between mitochondrial single nucleotide polymorphism (SNPs) and plasma lipidomic traits is meaningful. Here, we enrolled a total of 1,409 Han Chinese patients with coronary artery disease from three centers and performed linear regression analyses on the SNPs of mitochondrial DNA (mtDNA) and lipidomic traits in two independent groups. Sex, age, aspartate aminotransferase, estimated glomerular filtration rate, antihypertensive drugs, hypertension, and diabetes were adjusted. We identified three associations, namely, D-loop m .16089 T & gt; C with TG(50:4) NL-16:0, D-loop m .16145 G & gt; A with TG(54:5) NL-18:0, and D-loop m .16089 T & gt; C with PC(16:0_16:1) at the statistically significant threshold of FDR & lt; 0.05. Then, we explored the relationships between mitochondrial genetic variants and traditional lipids, including triglyceride, total cholesterol (TC), low-density lipoprotein cholesterol (LDLC), and high-density lipoprotein cholesterol. Two significant associations were found, namely MT-ND6 m .14178 T & gt; C with TC and D-loop m .215 A & gt; G with LDLC. Furthermore, we performed linear regression analysis to determine on the SNPs of mtDNA and left ventricular ejection fraction (LVEF) and found that the SNP D-loop m .16145 G & gt; A was nominally significantly associated with LVEF ( P = 0.047). Our findings provide insights into the lipidomic context of mtDNA variations and highlight the importance of studying mitochondrial genetic variants related to lipid species.
    Type of Medium: Online Resource
    ISSN: 1664-8021
    URL: Article
    URL: Article
    DOI: 10.3389/fgene.2021.630359
    DOI: 10.3389/fgene.2021.630359.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2021
    detail.hit.zdb_id: 2606823-0
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