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Identification of metabolic biomarkers in patients with type 2 diabetic coronary heart diseases based on metabolomic approach.

ABSTRACT: Type 2 diabetic coronary heart disease (T2DM-CHD) is a kind of serious and complex disease. Great attention has been paid to exploring its mechanism; however, the detailed understanding of T2DM-CHD is still limited. Plasma samples from 15 healthy controls, 13 coronary heart disease (CHD) patients, 15 type 2 diabetes mellitus (T2DM) patients and 28 T2DM-CHD patients were analyzed in this research. The potential biomarkers of CHD and T2DM were detected and screened out by (1)H NMR-based plasma metabolic profiling and multivariate data analysis. About 11 and 12 representative metabolites of CHD and T2DM were identified respectively, mainly including alanine, arginine, proline, glutamine, creatinine and acetate. Then the diagnostic model was further constructed based on the previous metabolites of CHD and T2DM to detect T2DM-CHD with satisfying sensitivity of 92.9%, specificity of 93.3% and accuracy of 93.2%, validating the robustness of (1)H NMR-based plasma metabolic profiling to diagnostic strategy. The results demonstrated that the NMR-based metabolomics approach processed good performance to identify diagnostic plasma biomarkers and most identified metabolites related to T2DM and CHD could be considered as predictors of T2DM-CHD as well as the therapeutic targets for prevention, which provided new insight into diagnosing and forecasting of complex diseases.

SUBMITTER: Liu X

PROVIDER: S-EPMC4965763 | biostudies-other | 2016

REPOSITORIES: biostudies-other

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Identification of metabolic biomarkers in patients with type 2 diabetic coronary heart diseases based on metabolomic approach.

Liu Xinfeng X Gao Jian J Chen Jianxin J Wang Zhiyong Z Shi Qi Q Man Hongxue H Guo Shuzhen S Wang Yingfeng Y Li Zhongfeng Z Wang Wei W

Scientific reports 20160729

Type 2 diabetic coronary heart disease (T2DM-CHD) is a kind of serious and complex disease. Great attention has been paid to exploring its mechanism; however, the detailed understanding of T2DM-CHD is still limited. Plasma samples from 15 healthy controls, 13 coronary heart disease (CHD) patients, 15 type 2 diabetes mellitus (T2DM) patients and 28 T2DM-CHD patients were analyzed in this research. The potential biomarkers of CHD and T2DM were detected and screened out by (1)H NMR-based plasma met ...[more]

PMID: 27470195

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Project description:BackgroundComorbidities of coronavirus disease 2019 (COVID-19)/coronary heart disease (CHD) pose great threats to disease outcomes, yet little is known about their shared pathology. The study aimed to examine whether comorbidities of COVID-19/CHD involved shared genetic pathology, as well as to clarify the shared genetic variants predisposing risks common to COVID-19 severity and CHD risks.MethodsBy leveraging publicly available summary statistics, we assessed the genetically determined causality between COVID-19 and CHD with bidirectional Mendelian randomization. To further quantify the causality contributed by shared genetic variants, we interrogated their genetic correlation with the linkage disequilibrium score regression method. Bayesian colocalization analysis coupled with conditional/conjunctional false discovery rate analysis was applied to decipher the shared causal single nucleotide polymorphisms (SNPs).FindingsBriefly, we observed that the incident CHD risks post COVID-19 infection were partially determined by shared genetic variants. The shared genetic variants contributed to the causality at a proportion of 0.18 (95% CI 0.18-0.19) to 0.23 (95% CI 0.23-0.24). The SNP (rs10490770) located near LZTFL1 suggested direct causality (SNPs → COVID-19 → CHD), and SNPs in ABO (rs579459, rs495828), ILRUN(rs2744961), and CACFD1(rs4962153, rs3094379) may simultaneously influence COVID-19 severity and CHD risks.InterpretationFive SNPs located near LZTFL1 (rs10490770), ABO (rs579459, rs495828), ILRUN (rs2744961), and CACFD1 (rs4962153, rs3094379) may simultaneously influence their risks. The current study suggested that there may be shared mechanisms predisposing to both COVID-19 severity and CHD risks. Genetic predisposition to COVID-19 is a causal risk factor for CHD, supporting that reducing the COVID-19 infection risk or alleviating COVID-19 severity among those with specific genotypes might reduce their subsequent CHD adverse outcomes. Meanwhile, the shared genetic variants identified may be of clinical implications for identifying the target population who are more vulnerable to adverse CHD outcomes post COVID-19 and may also advance treatments of 'Long COVID-19.'

Project description:BackgroundA better understanding of the pathophysiology involving coronary artery calcification (CAC) in patients on hemodialysis (HD) will help to develop new therapies. We sought to identify the differences in metabolomics profiles between patients on HD with and without CAC.MethodsIn this case-control study, nested within a cohort of 568 incident patients on HD, the cases were patients without diabetes with a CAC score >100 (n=51), and controls were patients without diabetes with a CAC score of zero (n=48). We measured 452 serum metabolites in each participant. Metabolites and pathway scores were compared using Mann-Whitney U tests, partial least squares-discriminant analyses, and pathway enrichment analyses.ResultsCompared with controls, cases were older (64±13 versus 42±12 years) and were less likely to be Black (51% versus 94%). We identified three metabolites in bile-acid synthesis (chenodeoxycholic, deoxycholic, and glycolithocholic acids) and one pathway (arginine/proline metabolism). After adjusting for demographics, higher levels of chenodeoxycholic, deoxycholic, and glycolithocholic acids were associated with higher odds of having CAC; comparing the third with the first tertile of each bile acid, the OR was 6.34 (95% CI, 1.12 to 36.06), 6.73 (95% CI, 1.20 to 37.82), and 8.53 (95% CI, 1.50 to 48.49), respectively. These associations were no longer significant after further adjustment for coronary artery disease and medication use. Per 1 unit higher in the first principal component score, arginine/proline metabolism was associated with CAC after adjusting for demographics (OR, 1.83; 95% CI, 1.06 to 3.15), and the association remained significant with additional adjustments for statin use (OR, 1.84; 95% CI, 1.04 to 3.27).ConclusionsAmong patients on HD without diabetes mellitus, chenodeoxycholic, deoxycholic, and glycolithocholic acids may be potential biomarkers for CAC, and arginine/proline metabolism is a plausible mechanism to study for CAC. These findings need to be confirmed in future studies.

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Identification of metabolic biomarkers in patients with type 2 diabetic coronary heart diseases based on metabolomic approach.

Publications

Identification of metabolic biomarkers in patients with type 2 diabetic coronary heart diseases based on metabolomic approach.

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