Combining Circulating MicroRNA and NT-proBNP to Detect and Categorize Heart Failure Subtypes.

BACKGROUND: Clinicians need improved tools to better identify nonacute heart failure with preserved ejection fraction (HFpEF). OBJECTIVES: The purpose of this study was to derive and validate circulating microRNA signatures for nonacute heart failure (HF). METHODS: Discovery and validation cohorts (N = 1,710), comprised 903 HF and 807 non-HF patients from Singapore and New Zealand (NZ). MicroRNA biomarker panel discovery in a Singapore cohort (n = 546) was independently validated in a second Singapore cohort (Validation 1; n = 448) and a NZ cohort (Validation 2; n = 716). RESULTS: In discovery, an 8-microRNA panel identified HF with an area under the curve (AUC) 0.96, specificity 0.88, and accuracy 0.89. Corresponding metrics were 0.88, 0.66, and 0.77 in Validation 1, and 0.87, 0.58, and 0.74 in Validation 2. Combining microRNA panels with N-terminal pro-B-type natriuretic peptide (NT-proBNP) clearly improved specificity and accuracy from AUC 0.96, specificity 0.91, and accuracy 0.90 for NT-proBNP alone to corresponding metrics of 0.99, 0.99, and 0.93 in the discovery and 0.97, 0.96, and 0.93 in Validation 1. The 8-microRNA discovery panel distinguished HFpEF from HF with reduced ejection fraction with AUC 0.81, specificity 0.66, and accuracy 0.72. Corresponding metrics were 0.65, 0.41, and 0.56 in Validation 1 and 0.65, 0.41, and 0.62 in Validation 2. For phenotype categorization, combined markers achieved AUC 0.87, specificity 0.75, and accuracy 0.77 in the discovery with corresponding metrics of 0.74, 0.59, and 0.67 in Validation 1 and 0.72, 0.52, and 0.68 in Validation 2, as compared with NT-proBNP alone of AUC 0.71, specificity 0.46, and accuracy 0.62 in the discovery; with corresponding metrics of 0.72, 0.44, and 0.57 in Validation 1 and 0.69, 0.48, and 0.66 in Validation 2. Accordingly, false negative (FN) (81% Singapore and all NZ FN cases were HFpEF) as classified by a guideline-endorsed NT-proBNP ruleout threshold, were correctly reclassified by the 8-microRNA panel in the majority (72% and 88% of FN in Singapore and NZ, respectively) of cases. CONCLUSIONS: Multi-microRNA panels in combination with NT-proBNP are highly discriminatory and improved specificity and accuracy in identifying nonacute HF. These findings suggest potential utility in the identification of nonacute HF, where clinical assessment, imaging, and NT-proBNP may not be definitive, especially in HFpEF.

Racial Differences in Electrocardiographic Characteristics and Prognostic Significance in Whites Versus Asians.

BACKGROUND: Racial differences in electrocardiographic (ECG) characteristics and prognostic significance among Whites and Asians are not well described. METHODS AND RESULTS: We studied 2677 White Framingham Heart Study participants (57% women) and 2972 Asian (64% women) Singapore Longitudinal Aging Study participants (mean age 66 years in both) free of myocardial infarction or heart failure. Racial differences in ECG characteristics and effect on mortality were assessed. In linear regression models, PR interval was longer in Asians compared with Whites (multivariable-adjusted ß±SE 5.0±1.4 ms in men and 6.6±0.9 ms in women, both P<0.0006). QT interval was shorter in Asian men (ß±SE -6.2±1.2 ms, P<0.0001) and longer in Asian women (ß±SE 3.6±0.9 ms, P=0.02) compared to White men and women, respectively. Asians had greater odds of having ECG left ventricular hypertrophy (LVH) compared with Whites (odds ratio [OR] 3.56, 95% confidence interval [CI] 1.36-9.35 for men, OR 1.93, 95% CI 1.35-2.76 for women, both P<0.02). Over a mean follow-up of 11±3 years in Framingham and 8±3 years in Singapore, mortality rates were 24.5 and 13.4 per 1000 person-years among Whites and Asians, respectively. In Cox models, the presence of LVH had a greater effect on all-cause mortality in Asians compared with Whites (hazard ratio [HR] 2.66, 95% CI 1.83-3.88 vs HR 1.30, 95% CI 0.90-1.89, P for interaction=0.02). CONCLUSION: Our findings from two large community-based cohorts show prominent race differences in ECG characteristics between Whites and Asians, and also suggest a differential association with mortality. These differences may carry implications for race-specific ECG reference ranges and cardiovascular risk.

Circulating microRNAs in heart failure with reduced and preserved left ventricular ejection fraction.

AIM: The potential diagnostic utility of circulating microRNAs in heart failure (HF) or in distinguishing HF with reduced vs. preserved left ventricular ejection fraction (HFREF and HFPEF, respectively) is unclear. We sought to identify microRNAs suitable for diagnosis of HF and for distinguishing both HFREF and HFPEF from non-HF controls and HFREF from HFPEF. METHODS AND RESULTS: MicroRNA profiling performed on whole blood and corresponding plasma samples of 28 controls, 39 HFREF and 19 HFPEF identified 344 microRNAs to be dysregulated among the three groups. Further analysis using an independent cohort of 30 controls, 30 HFREF and 30 HFPEF, presented 12 microRNAs with diagnostic potential for one or both HF phenotypes. Of these, miR-1233, -183-3p, -190a, -193b-3p, -193b-5p, -211-5p, -494, and -671-5p distinguished HF from controls. Altered levels of miR-125a-5p, -183-3p, -193b-3p, -211-5p, -494, -638, and -671-5p were found in HFREF while levels of miR-1233, -183-3p, -190a, -193b-3p, -193b-5p, and -545-5p distinguished HFPEF from controls. Four microRNAs (miR-125a-5p, -190a, -550a-5p, and -638) distinguished HFREF from HFPEF. Selective microRNA panels showed stronger discriminative power than N-terminal pro-brain natriuretic peptide (NT-proBNP). In addition, individual or multiple microRNAs used in combination with NT-proBNP increased NT-proBNP's discriminative performance, achieving perfect intergroup distinction. Pathway analysis revealed that the altered microRNAs expression was associated with several mechanisms of potential significance in HF. CONCLUSIONS: We report specific microRNAs as potential biomarkers in distinguishing HF from non-HF controls and in differentiating between HFREF and HFPEF.

Influence of progressive renal dysfunction in chronic heart failure.

Chronic heart failure (CHF) is often associated with impaired renal function due to hypoperfusion. Such patients are very sensitive to changes in renal perfusion pressure, and may develop acute tubular necrosis if the pressure falls too far. The situation is complicated by the use of diuretics, ACE inhibitors and spironolactone, all of which may affect renal function and potassium balance. Chronic renal failure (CRF) may also be associated with fluid overload. Anaemia and hypertension in CRF contribute to the development of left ventricular hypertrophy (LVH), which carries a poor prognosis, so correction of these factors is important.

Growth differentiation factor 15, ST2, high-sensitivity troponin T, and N-terminal pro brain natriuretic peptide in heart failure with preserved vs. reduced ejection fraction.

AIMS: Growth differentiation factor 15 (GDF15), ST2, high-sensitivity troponin T (hsTnT), and N-terminal pro brain natriuretic peptide (NT-proBNP) are biomarkers of distinct mechanisms that may contribute to the pathophysiology of heart failure (HF) [inflammation (GDF15); ventricular remodelling (ST2); myonecrosis (hsTnT); and wall stress (NT-proBNP)]. METHODS AND RESULTS: We compared circulating levels of GDF15, ST2, hsTnT, and NT-proBNP, as well as their combinations, in compensated patients with clinical HF with reduced ejection fraction (HFREF) (n = 51), HF with preserved ejection fraction (HFPEF) (n= 50), and community-based controls (n = 50). Compared with controls, patients with HFPEF and HFREF had higher median levels of GDF15 (540 pg/mL vs. 2529 and 2672 pg/mL, respectively), hsTnT (3.7 pg/mL vs. 23.7 and 35.6 pg/mL), and NT-proBNP (69 pg/mL vs. 942 and 2562 pg/mL), but not ST2 (27.6 ng/mL vs. 31.5 and 35.3 ng/mL), adjusting for clinical covariates. In receiver operating characteristic curve analyses, NT-proBNP distinguished HFREF from controls with an area under the curve (AUC) of 0.987 (P < 0.001); GDF15 distinguished HFPEF from controls with an AUC of 0.936 (P < 0.001); and the combination of NT-proBNP and GDF15 distinguished HFPEF from controls with an AUC of 0.956 (P < 0.001). NT-proBNP and hsTnT levels were higher in HFREF than in HFPEF (adjusted P < 0.04). The NT-proBNP:GDF15 ratio distinguished between HFPEF and HFREF with the largest AUC (0.709; P < 0.001). CONCLUSIONS: Our study provides comparative data on physiologically distinct circulating biomarkers in HFPEF, HFREF, and controls from the same community. These data suggest a prominent role for myocardial injury (hsTnT) with increased wall stress (NT-proBNP) in HFREF, and systemic inflammation (GDF15) in HFPEF.