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Background: This study assessed the predictive performance of inflammatory, hepatic, coagulation, and cardiac biomarkers in patients with prediabetes and diabetes mellitus hospitalized for COVID-19 in Austria. Methods: This was an analysis of a multicenter cohort study of 747 patients with diabetes mellitus or prediabetes hospitalized for COVID-19 in 11 hospitals in Austria. The primary outcome of this study was in-hospital mortality. The predictor variables included demographic characteristics, clinical parameters, comorbidities, use of medication, disease severity, and laboratory measurements of biomarkers. The association between biomarkers and in-hospital mortality was assessed using simple and multiple logistic regression analyses. The predictive performance of biomarkers was assessed using discrimination and calibration. Results: In our analysis, 70.8% had type 2 diabetes mellitus, 5.8% had type 1 diabetes mellitus, 14.9% had prediabetes, and 8.6% had other types of diabetes mellitus. The mean age was 70.3 ± 13.3 years, and 69.3% of patients were men. A total of 19.0% of patients died in the hospital. In multiple logistic regression analysis, LDH, CRP, IL-6, PCT, AST-ALT ratio, NT-proBNP, and Troponin T were significantly associated with in-hospital mortality. The discrimination of NT-proBNP was 74%, and that of Troponin T was 81%. The calibration of NT-proBNP was adequate (p = 0.302), while it was inadequate for Troponin T (p = 0.010). Conclusion: Troponin T showed excellent predictive performance, while NT-proBNP showed good predictive performance for assessing in-hospital mortality in patients with diabetes mellitus hospitalized with COVID-19. Therefore, these cardiac biomarkers may be used for prognostication of COVID-19 patients. [ABSTRACT FROM AUTHOR]

Objectives: We studied apolipoprotein C‐III (apoC‐III) in relation to diabetic kidney disease (DKD), cardiovascular outcomes, and mortality in type 1 diabetes. Methods: The cohort comprised 3966 participants from the prospective observational Finnish Diabetic Nephropathy Study. Progression of DKD was determined from medical records. A major adverse cardiac event (MACE) was defined as acute myocardial infarction, coronary revascularization, stroke, or cardiovascular mortality through 2017. Cardiovascular and mortality data were retrieved from national registries. Results: ApoC‐III predicted DKD progression independent of sex, diabetes duration, blood pressure, HbA1c, smoking, LDL‐cholesterol, lipid‐lowering medication, DKD category, and remnant cholesterol (hazard ratio [HR] 1.43 [95% confidence interval 1.05–1.94], p = 0.02). ApoC‐III also predicted the MACE in a multivariable regression analysis; however, it was not independent of remnant cholesterol (HR 1.05 [0.81–1.36, p = 0.71] with remnant cholesterol; 1.30 [1.03–1.64, p = 0.03] without). DKD‐specific analyses revealed that the association was driven by individuals with albuminuria, as no link between apoC‐III and the outcome was observed in the normal albumin excretion or kidney failure categories. The same was observed for mortality: Individuals with albuminuria had an adjusted HR of 1.49 (1.03–2.16, p = 0.03) for premature death, while no association was found in the other groups. The highest apoC‐III quartile displayed a markedly higher risk of MACE and death than the lower quartiles; however, this nonlinear relationship flattened after adjustment. Conclusions: The impact of apoC‐III on MACE risk and mortality is restricted to those with albuminuria among individuals with type 1 diabetes. This study also revealed that apoC‐III predicts DKD progression, independent of the initial DKD category. [ABSTRACT FROM AUTHOR]

Background: Although diabetic kidney disease demonstrates both familial clustering and single nucleotide polymorphism heritability, the specific genetic factors influencing risk remain largely unknown., Methods: To identify genetic variants predisposing to diabetic kidney disease, we performed genome-wide association study (GWAS) analyses. Through collaboration with the Diabetes Nephropathy Collaborative Research Initiative, we assembled a large collection of type 1 diabetes cohorts with harmonized diabetic kidney disease phenotypes. We used a spectrum of ten diabetic kidney disease definitions based on albuminuria and renal function., Results: Our GWAS meta-analysis included association results for up to 19,406 individuals of European descent with type 1 diabetes. We identified 16 genome-wide significant risk loci. The variant with the strongest association (rs55703767) is a common missense mutation in the collagen type IV alpha 3 chain ( COL4A3) gene, which encodes a major structural component of the glomerular basement membrane (GBM). Mutations in COL4A3 are implicated in heritable nephropathies, including the progressive inherited nephropathy Alport syndrome. The rs55703767 minor allele (Asp326Tyr) is protective against several definitions of diabetic kidney disease, including albuminuria and ESKD, and demonstrated a significant association with GBM width; protective allele carriers had thinner GBM before any signs of kidney disease, and its effect was dependent on glycemia. Three other loci are in or near genes with known or suggestive involvement in this condition ( BMP7) or renal biology ( COLEC11 and DDR1 )., Conclusions: The 16 diabetic kidney disease-associated loci may provide novel insights into the pathogenesis of this condition and help identify potential biologic targets for prevention and treatment., (Copyright © 2019 by the American Society of Nephrology.)

Objective: Elevated serum ferritin has been linked to type 2 diabetes (T2D) and adverse health outcomes in subjects with the Metabolic Syndrome (MetS). As the mechanisms underlying the negative impact of excess iron have so far remained elusive, we aimed to identify potential links between iron homeostasis and metabolic pathways., Methods: In a cross-sectional study, data were obtained from 163 patients, allocated to one of three groups: (1) lean, healthy controls (n = 53), (2) MetS without hyperferritinemia (n = 54) and (3) MetS with hyperferritinemia (n = 56). An additional phlebotomy study included 29 patients with biopsy-proven iron overload before and after iron removal. A detailed clinical and biochemical characterization was obtained and metabolomic profiling was performed via a targeted metabolomics approach., Results: Subjects with MetS and elevated ferritin had higher fasting glucose (p < 0.001), HbA1c (p = 0.035) and 1 h glucose in oral glucose tolerance test (p = 0.002) compared to MetS subjects without iron overload, whereas other clinical and biochemical features of the MetS were not different. The metabolomic study revealed significant differences between MetS with high and low ferritin in the serum concentrations of sarcosine, citrulline and particularly long-chain phosphatidylcholines. Methionine, glutamate, and long-chain phosphatidylcholines were significantly different before and after phlebotomy (p < 0.05 for all metabolites)., Conclusions: Our data suggest that high serum ferritin concentrations are linked to impaired glucose homeostasis in subjects with the MetS. Iron excess is associated to distinct changes in the serum concentrations of phosphatidylcholine subsets. A pathway involving sarcosine and citrulline also may be involved in iron-induced impairment of glucose metabolism.