Person:

Das, Saumya

Patients with diabetes and heart failure (HF) have worse clinical outcomes compared to patients with HF without diabetes after cardiac resynchronization therapy (CRT). Patients with HF and diabetes represent a growing population at high risk for cardiovascular events and are increasingly treated with CRT. Although patients with diabetes and HF appear to benefit from CRT, their clinical outcomes are worse than those of patients without diabetes after CRT. The aim of this study was to identify clinical predictors that explain the differential hazard in patients with diabetes. We studied 442 patients (169 with diabetes) with systolic HF referred to the Massachusetts General Hospital CRT clinic from 2003 to 2010 to identify predictors of outcomes after CRT in patients with HF and diabetes. Patients with diabetes were more likely to have ischemic causes of HF than those without diabetes, but there was no difference in the left ventricular ejection fraction or HF classification at implantation. Patients with diabetes had poorer event-free survival (death or HF hospitalization) compared to those without diabetes (log-rank p = 0.04). The presence of diabetes was the most important independent predictor of differential outcomes in the entire population (hazard ratio 1.65, 95% confidence interval 1.10 to 2.51). Patients with diabetes receiving insulin therapy had poorer survival, whereas those not receiving insulin therapy had similar survival to patients without diabetes. Patients with peri-implantation glycosylated hemoglobin >7% had worse outcomes, whereas patients with glycosylated hemoglobin ≤7% had improved survival (hazard ratio 0.36, 95% confidence interval 0.15 to 0.86) equivalent to that of patients without diabetes. In conclusion, although the presence of diabetes, independent of other variables, increases the hazard of worse outcomes after CRT, there is additional risk conferred by insulin use and suboptimal peri-implantation glycemic control.

Background: Evolving interest in comprehensively profiling the full range of small RNAs present in small tissue biopsies and in circulating biofluids, and how the profile differs with disease, has launched small RNA sequencing (RNASeq) into more frequent use. However, known biases associated with small RNASeq, compounded by low RNA inputs, have been both a significant concern and a hurdle to widespread adoption. As RNASeq is becoming a viable choice for the discovery of small RNAs in low input samples and more labs are employing it, there should be benchmark datasets to test and evaluate the performance of new sequencing protocols and operators. In a recent publication from the National Institute of Standards and Technology, Pine et al., 2018, the investigators used a commercially available set of three tissues and tested performance across labs and platforms. Results: In this paper, we further tested the performance of low RNA input in three commonly used and commercially available RNASeq library preparation kits; NEB Next, NEXTFlex, and TruSeq small RNA library preparation. We evaluated the performance of the kits at two different sites, using three different tissues (brain, liver, and placenta) with high (1 μg) and low RNA (10 ng) input from tissue samples, or 5.0, 3.0, 2.0, 1.0, 0.5, and 0.2 ml starting volumes of plasma. As there has been a lack of robust validation platforms for differentially expressed miRNAs, we also compared low input RNASeq data with their expression profiles on three different platforms (Abcam Fireplex, HTG EdgeSeq, and Qiagen miRNome). Conclusions: The concordance of RNASeq results on these three platforms was dependent on the RNA expression level; the higher the expression, the better the reproducibility. The results provide an extensive analysis of small RNASeq kit performance using low RNA input, and replication of these data on three downstream technologies. Electronic supplementary material The online version of this article (10.1186/s12864-018-4726-6) contains supplementary material, which is available to authorized users.

OBJECTIVE Insulin resistance (IR) is a hallmark of obesity and metabolic disease. Circulating extracellular RNAs (ex-RNAs), stable RNA molecules in plasma, may play a role in IR, though most studies on ex-RNAs in IR are small. We sought to characterize the relationship between ex-RNAs and metabolic phenotypes in a large community-based human cohort. RESEARCH DESIGN AND METHODS We measured circulating plasma ex-RNAs in 2,317 participants without diabetes in the Framingham Heart Study (FHS) Offspring Cohort at cycle 8 and defined associations between ex-RNAs and IR (measured by circulating insulin level). We measured association between candidate ex-RNAs and markers of adiposity. Sensitivity analyses included individuals with diabetes. In a separate cohort of 90 overweight/obese youth, we measured selected ex-RNAs and metabolites. Biology of candidate microRNAs was investigated in silico. RESULTS The mean age of FHS participants was 65.8 years (56% female), with average BMI 27.7 kg/m2; participants in the youth cohort had a mean age of 15.5 years (60% female), with mean BMI 33.8 kg/m2. In age-, sex-, and BMI-adjusted models across 391 ex-RNAs in FHS, 18 ex-RNAs were associated with IR (of which 16 were microRNAs). miR-122 was associated with IR and regional adiposity in adults and IR in children (independent of metabolites). Pathway analysis revealed metabolic regulatory roles for miR-122, including regulation of IR pathways (AMPK, target of rapamycin signaling, and mitogen-activated protein kinase). CONCLUSIONS These results provide translational evidence in support of an important role of ex-RNAs as novel circulating factors implicated in IR.

Despite substantial declines in mortality following myocardial infarction (MI), subsequent left ventricular remodeling (LVRm) remains a significant long-term complication. Extracellular small non-coding RNAs (exRNAs) have been associated with cardiac inflammation and fibrosis and we hypothesized that they are associated with post-MI LVRm phenotypes. RNA sequencing of exRNAs was performed on plasma samples from patients with “beneficial” (decrease LVESVI ≥ 20%, n = 11) and “adverse” (increase LVESVI ≥ 15%, n = 11) LVRm. Selected differentially expressed exRNAs were validated by RT-qPCR (n = 331) and analyzed for their association with LVRm determined by cardiac MRI. Principal components of exRNAs were associated with LVRm phenotypes post-MI; specifically, LV mass, LV ejection fraction, LV end systolic volume index, and fibrosis. We then investigated the temporal regulation and cellular origin of exRNAs in murine and cell models and found that: 1) plasma and tissue miRNA expression was temporally regulated; 2) the majority of the miRNAs were increased acutely in tissue and at sub-acute or chronic time-points in plasma; 3) miRNA expression was cell-specific; and 4) cardiomyocytes release a subset of the identified miRNAs packaged in exosomes into culture media in response to hypoxia/reoxygenation. In conclusion, we find that plasma exRNAs are temporally regulated and are associated with measures of post-MI LVRm.