Association of Biomarker Clusters With Cardiac Phenotypes and Mortality in Patients With HIV Infection

Abstract

Background: Although individual cardiac biomarkers are associated with heart failure risk and all-cause mortality in HIV-infected individuals, their combined use for prediction has not been well studied.

Methods and results: Unsupervised k-means cluster analysis was performed blinded to the study outcomes in 332 HIV-infected participants on 8 biomarkers: ST2, NT-proBNP (N-terminal pro-B-type natriuretic peptide), hsCRP (high-sensitivity C-reactive protein), GDF-15 (growth differentiation factor 15), cystatin C, IL-6 (interleukin-6), D-dimer, and troponin. We evaluated cross-sectional associations of each cluster with diastolic dysfunction, pulmonary hypertension (defined as echocardiographic pulmonary artery systolic pressure ≥35 mm Hg), and longitudinal associations with all-cause mortality. The biomarker-derived clusters partitioned subjects into 3 groups. Cluster 3 (n=103) had higher levels of CRP, IL-6, and D-dimer (inflammatory phenotype). Cluster 2 (n=86) displayed elevated levels of ST2, NT-proBNP, and GDF-15 (cardiac phenotype). Cluster 1 (n=143) had lower levels of both phenotype-associated biomarkers. After multivariable adjustment for traditional and HIV-related risk factors, cluster 3 was associated with a 51% increased risk of diastolic dysfunction (95% confidence interval, 1.12-2.02), and cluster 2 was associated with a 67% increased risk of pulmonary hypertension (95% confidence interval, 1.04-2.68), relative to cluster 1. Over a median 6.9-year follow-up, 48 deaths occurred. Cluster 3 was independently associated with a 3.3-fold higher risk of mortality relative to cluster 1 (95% confidence interval, 1.3-8.1), and cluster 2 had a 3.1-fold increased risk (95% confidence interval, 1.1-8.4), even after controlling for diastolic dysfunction, pulmonary hypertension, left ventricular mass, and ejection fraction.

Conclusions: Serum biomarkers can be used to classify HIV-infected individuals into separate clusters for differentiating cardiopulmonary structural and functional abnormalities and can predict mortality independent of these structural and functional measures.

Keywords: HIV infection; biomarkers; cluster analysis; heart failure; mortality.

Figure 1.

Correlations of biomarkers among HIV-infected participants. Spearman correlation coefficients are shown for intracorrelations of biomarkers. Heat map with overlaid dendrogram depicts separation of cardiac and inflammatory biomarkers. CysC indicates Cystatin C; GDF-15, growth differentiation factor-15; IL-6, interleukin-6; and NT-proBNP, N-terminal pro-B-type natriuretic peptide.

Figure 2.

Association of integrated biomarker scores with cluster membership.Scatterplot shows separation of clusters by integrated biomarker scores. Standardized canonical coefficients were used to calculate integrated biomarker scores as follows: Score I=−0.08×ST2–0.40×BNP−0.27×GDF-15+0.81×CRP+0.61×IL-6+0.71×D-dimer. Score C=+0.53×ST2+0.59×BNP+0.80×GDF-15+0.05×CRP+0.03×IL-6+0.12×D-dimer. Each biomarker is log-transformed and standardized to a mean of 0 and SD of 1. BNP indicates N-terminal pro-B-type natriuretic peptide; CRP, C-reactive protein; GDF-15, growth differentiation factor-15; and IL-6, interleukin-6.

Figure 3.

Cumulative mortality by biomarker-derived phenotype. The following is a list of biomarkers used to derive phenotypes: ST2, NT-proBNP (N-terminal pro-B-type natriuretic peptide), GDF-15 (growth differentiation factor 15), hsCRP (high sensitivity C-reactive protein), IL-6 (interleukin-6), and D-dimer.