There is increasing evidence that HFpEF is a heterogeneous clinical entity and distinct molecular pathways may contribute to pathophysiology. Leveraging unbiased proteomics to identify novel biomarkers, this study seeks to understand the underlying molecular mechanisms of HFpEF. The discovery cohort consisted of HFpEF cases and non-HF controls from the CATHGEN study (N = 176); the validation cohort consisted of participants from the TECOS trial of patients with diabetes (N = 109). Proteins associated with HFpEF were included in a LASSO model to create a discriminative multi-protein model and assessed in the validation cohort. Survival models and meta-analysis were used to test the association of proteins with incident clinical outcomes, including HF hospitalization, mortality and HFpEF hospitalization in CATHGEN, TECOS and the Jackson Heart Study. In the derivation set, 190 proteins were associated with HFpEF in univariate analysis, of which 65 remained significant in the multivariate model. Twenty (30.8%) of these proteins validated in TECOS, including LCN2, U-PAR, IL-1ra, KIM1, CSTB and Gal-9 (OR 1.93–2.77, p < 0.01). LASSO regression yielded a 13-protein model which, when added to a clinical model inclusive of NT-proBNP, improved the AUC from 0.82 to 0.92 (p = 1.5 × 10–4). Five proteins were associated with incident HF hospitalization, four with HFpEF hospitalization and eleven with mortality (p < 0.05). We identified and validated multiple circulating biomarkers associated with HFpEF as well as HF outcomes. These biomarkers added incremental discriminative capabilities beyond clinical factors and NT-proBNP.
Sunitinib and docetaxel/prednisone followed by salvage RT resulted in excess pre-specified DLTs. Although nearly half of the men experienced durable disease control, efficacy was not greater than expected with radiation alone. The use of the intermediate end point of PFS in this salvage setting permitted an early decision on further development of this combination.
Introduction: Metabolic substrate utilization is central to metabolic disease. Metabolic pathways linking type 2 diabetes (T2D) to major adverse cardiac events (MACE) and heart failure (HF) remain poorly understood and T2D drug effects on metabolite biomarkers could improve biological understanding and support precision medicine approaches. Hypothesis: Circulating metabolites characterizing mitochondrial dysfunction are predictors for MACE and hospitalization for HF (hHF), and are improved with exenatide. Methods: We performed targeted mass-spectrometry profiling of 60 metabolites on baseline and 12-month plasma samples from 978 participants from EXSCEL, a randomized trial of the GLP-1 receptor agonist, exenatide. Principal components analysis (PCA) was used; resultant metabolite factors were analyzed with univariate and multivariable logistic regression (adjusted for history of HF, coronary artery disease, BMI, HbA 1c , eGFR, blood pressure) for association with MACE (CV death, non-fatal MI or stroke) and hHF. Results were validated in participants from TECOS, a randomized trial of the DPP-4 inhibitor sitagliptin. Metabolite changes by treatment arm were tested. Results: Of 12 PCA metabolite factors, two nominally associated with MACE in both univariate and multivariable models and two associated with hHF in univariate, but not multivariable models ( Table ). Individual metabolites remained associated with MACE in multivariable models and with hHF in univariate models. Similar results were seen in the TECOS validation cohort. Individual metabolites decreased to a greater extent in exenatide randomized individuals compared with placebo. Conclusions: Metabolites reporting on dysregulated mitochondrial fatty acid oxidation are increased in individuals with T2D who experience MACE. These biomarkers may improve CV risk prediction models, appear to be beneficially modified by exenatide, and highlight emerging risk mechanisms.
Metabolic mechanisms underlying the heterogeneity of major adverse cardiovascular (CV) event (MACE) risk in individuals with type 2 diabetes mellitus (T2D) remain unclear. We hypothesized that circulating metabolites reflecting mitochondrial dysfunction predict incident MACE in T2D. Targeted mass-spectrometry profiling of 60 metabolites was performed on baseline plasma samples from the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS; discovery cohort) and Exenatide Study of Cardiovascular Event Lowering (EXSCEL; validation cohort) biomarker substudy cohorts. A principal components analysis metabolite factor comprising medium-chain acylcarnitines (MCACs) was associated with MACE in TECOS and validated in EXSCEL, with higher levels associated with higher MACE risk. Meta-analysis showed that long-chain acylcarnitines (LCACs) and dicarboxylacylcarnitines were also associated with MACE. Metabolites remained associated with MACE in multivariate models and favorably changed with exenatide therapy. A third cohort (Cardiac Catheterization Genetics [CATHGEN]) with T2D was assessed to determine whether these metabolites improved discriminative capability of multivariate models for MACE. Nine metabolites (MCACs and LCACs and 1 dicarboxylacylcarnitine) were associated with time to MACE in the CATHGEN cohort. Addition of these metabolites to clinical models minimally improved the discriminative capability for MACE but did significantly down reclassify risk. Thus, metabolites reporting on dysregulated mitochondrial fatty acid oxidation are present in higher levels in individuals with T2D who experience subsequent MACE. These biomarkers may improve CV risk prediction models, be therapy responsive, and highlight emerging risk mechanisms.
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