Diastolic Dysfunction in Individuals With Human Immunodeficiency Virus Infection: Literature Review, Rationale and Design of the Characterizing Heart Function on Antiretroviral Therapy (CHART) Study - Butler, Javed; Kalogeropoulos, Andreas P.; Anstrom, Kevin J.; Hsue, Priscilla Y.; Kim, Raymond J.; Scherzer, Rebecca; Shah, Sanjiv J.; Shah, Svati H.; Velazquez, Eric J.; Hernandez, Adrian F.; Desvigne-Nickens, Patrice; Braunwald, Eugene (Journal of cardiac failure, 2018)
Antiretroviral therapy (ART) has been associated with a shift in the epidemiology of human immunodeficiency virus (HIV)–associated cardiomyopathy from a phenotype of primarily left ventricular (LV) systolic dysfunction to LV diastolic dysfunction (DD). Patients with HIV receiving ART have higher rates of DD compared with age-matched control subjects and develop DD at a younger age. However, little is known about the natural history and pathogenesis of DD in virally suppressed HIV-infected patients. Current evidence suggests that immune processes modulate the risk for cardiac involvement in HIV-infected persons. Ongoing inflammation appears to have myocardial effects, and accelerated myocardial fibrosis appears to be a key mediator of HIV-induced DD. The Characterizing Heart Function on Antiretroviral Therapy (CHART) study aims to systematically investigate determinants, mechanisms, and consequences of DD in HIV-infected patients. We will compare ART-treated virally suppressed HIV-infected individuals with and without DD and HIV− individuals with DD regarding (1) systemic inflammation, myocardial stress, and subclinical myocardial necrosis as indicated by circulating biomarkers; (2) immune system activation as indicated by cell surface receptors; (3) myocardial fibrosis according to cardiac magnetic resonance examination; (4) markers of fibrosis and remodeling, oxidative stress, and hypercoagulability; (5) left atrial function according to echocardiographic examination; (6) myocardial stress and subclinical necrosis as indicated by circulating biomarkers; (7) proteomic and metabolic profiles; and (8) phenotype signatures derived from clinical, biomarker, and imaging data.