Metabolomics profile and 10-year atherosclerotic cardiovascular disease (ASCVD) risk score.

Background: The intermediate metabolites associated with the development of atherosclerotic cardiovascular disease (ASCVD) remain largely unknown. Thus, we conducted a large panel of metabolomics profiling to identify the new candidate metabolites that were associated with 10-year ASCVD risk. Methods: Thirty acylcarnitines and twenty amino acids were measured in the fasting plasma of 1,102 randomly selected individuals using a targeted FIA-MS/MS approach. The 10-year ASCVD risk score was calculated based on 2013 ACC/AHA guidelines. Accordingly, the subjects were stratified into four groups: low-risk (n = 620), borderline-risk (n = 110), intermediate-risk (n = 225), and high-risk (n = 147). 10 factors comprising collinear metabolites were extracted from principal component analysis. Results: C4DC, C8:1, C16OH, citrulline, histidine, alanine, threonine, glycine, glutamine, tryptophan, phenylalanine, glutamic acid, arginine, and aspartic acid were significantly associated with the 10-year ASCVD risk score (p-values ≤ 0.044). The high-risk group had higher odds of factor 1 (12 long-chain acylcarnitines, OR = 1.103), factor 2 (5 medium-chain acylcarnitines, OR = 1.063), factor 3 (methionine, leucine, valine, tryptophan, tyrosine, phenylalanine, OR = 1.074), factor 5 (6 short-chain acylcarnitines, OR = 1.205), factor 6 (5 short-chain acylcarnitines, OR = 1.229), factor 7 (alanine, proline, OR = 1.343), factor 8 (C18:2OH, glutamic acid, aspartic acid, OR = 1.188), and factor 10 (ornithine, citrulline, OR = 1.570) compared to the low-risk ones; the odds of factor 9 (glycine, serine, threonine, OR = 0.741), however, were lower in the high-risk group. "D-glutamine and D-glutamate metabolism", "phenylalanine, tyrosine, and tryptophan biosynthesis", and "valine, leucine, and isoleucine biosynthesis" were metabolic pathways having the highest association with borderline/intermediate/high ASCVD events, respectively. Conclusions: Abundant metabolites were found to be associated with ASCVD events in this study. Utilization of this metabolic panel could be a promising strategy for early detection and prevention of ASCVD events.

The role of CDH2 and MCP-1 mRNAs of blood extracellular vesicles in predicting early-stage diabetic nephropathy.

BACKGROUND: Extracellular vesicles (EVs), including exosomes and microvesicles, are involved in intercellular communication by transferring biomolecules such as mRNA, which has been shown to be as essential biomarkers for many physiological and pathological conditions such as diabetic nephropathy (DN). This study aimed to investigate the expression of CDH1, CDH2, MCP-1, and PAI-1 mRNAs in blood EVs of DN patients and to determine their accuracy in predicting early-stage DN. METHODS: We recruited 196 participants, including 35 overt DN patients, 53 incipient DN patients, 62 diabetic patients (DM), and 46 healthy individuals. Quantification of the mRNA profile of blood EVs was performed using the qRT-PCR method. The diagnostic performance of mRNA was evaluated using receiver operating characteristic analysis. RESULTS: The mRNA expression of CDH2 and MCP-1 was downregulated in overt DN group (0.22-fold change and 0.15-fold change, respectively) and incipient DN group (0.60-fold change and 0.43-fold change, respectively) compared to DM group (1.72-fold change and 2.77-fold change, respectively), while PAI-1 mRNA expression decreased in incipient DN group (0.70-fold change) and DM group (0.58-fold change) compared to control. However, the expression level of CDH1 mRNA was not significantly different among the four groups (p = 0.408). Moreover, CDH2 and MCP-1 mRNAs inversely correlated with creatinine (r = -0.370 and r = -0.361, p<0.001) and Alb/Cr ratio (r = -0.355 and r = -0.297, p<0.001). 1/CDH2 mRNA also predicted overt DN with an accuracy of 0.75 (95%CI: 0.65-0.85) and incipient DN with an accuracy of 0.61 (95%CI: 0.50-0.71) while 1/MCP-1 mRNA had an accuracy of 0.66 (95%CI: 0.55-0.77) for overt DN prediction and an accuracy of 0.61 (95%CI: 0.51-0.71) for incipient DN prediction. CONCLUSION: CDH2 and MCP-1 mRNAs expression in blood EVs was decreased with the development of DN, suggesting the renoprotective effect of these mRNAs in diabetic individuals. Moreover, their quantifications could serve as diagnostic biomarkers for early-stage DN.

WT1 and ACE mRNAs of blood extracellular vesicle as biomarkers of diabetic nephropathy.

BACKGROUND: Diabetic nephropathy (DN) has an increasing global prevalence with excessive health expenditure and burden. Exosomal mRNAs regulate intercellular communications and participate in the pathogenesis of various disorders like DN. This study aimed to assess the expression levels of ACE, ELMO1, and WT1 mRNAs in the blood extracellular vesicles (EVs) of DN patients and diabetic patients without nephropathy (DM group) in comparison to healthy controls and investigate their correlations with the severity of DN. METHODS: The performed investigation is a cross-sectional study of 256 participants including 103 DN patients, 100 DM patients, and 53 healthy controls. The quantification of WT1, ACE, and ELMO1 mRNAs in the blood EVs were executed using qRT-PCR. The ROC analysis was performed to determine the diagnostic accuracy of mRNAs. RESULTS: DN patients had significantly higher expressed WT1 mRNA (1.70-fold change) and lower expressed ACE mRNA (0.55-fold change) in the blood EVs compared to DM patients and controls. ELMO1 mRNA was not expressed in EVs of any groups. A positive correlation between WT1 mRNA level and urine Alb/Cr ratio (r = 0.602, p < 0.001) and a negative correlation between ACE mRNA expression and urine Alb/Cr ratio within DN patients (r = - 0.474, p < 0.001) was identified. The accuracy of WT1 mRNA and 1/ACE mRNA for predicting incipient DN was 0.63 (95% CI 0.55, 0.72) and 0.62 (95% CI 0.54, 0.71), and for predicting overt DN was 0.83 (95% CI 0.74, 0.92) and 0.75 (95% CI 0.66, 0.83), respectively. CONCLUSIONS: WT1 and ACE mRNAs level in blood EVs were predictors for early diagnosis of DN therefore their quantifications might be used to determine the severity of albuminuria and glomerular injuries.