Multi-Scale Analysis of Phenotypes in Heart Failure (MAP-HEART)

Heart Failure

Heart Failure, Proteolytic, Metabolomics, Social determinant of health

Background: More than 6.5 million people in the United States live with heart failure (HF), and more than a million new cases are diagnosed each year. Treatments have improved in recent years, but researchers want to understand more about how HF develops. To do this, they need to compare blood and other samples from many people with HF. Objective: To collect blood and other samples from people with HF. These samples will be used to identify and study proteins and other factors that may lead to decreased heart function over time. Eligibility: People aged 18 years and older with heart failure. Design: Participants will be asked to join the study based on a review of their medical records. They will have 1 study visit. They will provide a blood sample: About 3 tablespoons will be collected from a needle inserted into a vein. Other tests are optional: Participants may provide urine and stool samples. They may have a cotton swab rubbed on the inside of the mouth to collect DNA. Participants may also take 3 questionnaires. They will answer questions about dietary, social, and other factors that affect their health. Participants will receive compensation. Researchers will follow the participants health by monitoring their medical records for up to 5 years.

Study Description: Our general hypothesis is that clinical and molecular data will generate new mechanistic knowledge and transform our understanding of the heterogeneous forms of heart failure (HF) syndrome. To do so, we will create a data-rich ecosystem by building a population-based registry. By grounding our work in the community within the District of Columbia / Maryland/Virginia metropolitan region (DMV), we will optimize inference and facilitate community translation. We will prospectively recruit a community cohort of 2000 participants with clinical HF from the DMV area and collect blood samples to measure multi-omics (specifically proteomics, metabolomics)signatures. We will integrate the results of the multi-omics assays to electronic medical records (EMR)-driven phenotypic representation (e.g., symptoms at clinical presentation, comorbid conditions, frailty, imaging data, ejection fraction, and laboratory values) collected during clinical care. Patients' records will be followed for up to 10 years after recruitment to monitor key characteristics and events, including death. Objectives: Primary Objective: -To study the association between multi-omics signatures with all-cause mortality Secondary Objectives: * To study the association between multi-omics signatures with cardiovascular mortality * To study the cross-sectional association between multi-omics signatures with clinical sub-phenotypes of heart failure Exploratory Objectives: * To study the association between multi-omics signatures with HF-related hospitalizations. * To study the cross-sectional association between multi-omics signatures and HF sub-phenotypes based on clinical biomarkers across the spectrum of heart failure. * To explore both germline (i.e., inherited) and somatic (i.e., de novo or acquired) genetic variants contributing to HF sub phenotypes. * To explore epigenetic and gene expression alterations contributing to HF sub phenotypes. Endpoints: Primary Endpoint will be all-cause mortality. Secondary Endpoints will be: * Cardiovascular mortality * Clinical sub-phenotypes of heart failure are defined by the following: * Ejection Fraction, by echocardiogram (\>=50% vs. \< 50%) * Severity measured by New York Heart Association class (3-4 vs. 1-2) * HF duration (\>=18 months vs. \< 18 months) * Etiology (Ischemic vs. Non-Ischemic) * Comorbidity - diabetes, hypertension, chronic obstructive pulmonary disease, atrial fibrillation, cerebrovascular disease, body mass index (\>=30 vs. \< 30), age (median cut) Exploratory Endpoints will be: * HF-related hospitalization * Biomarkers related to HF including N-terminal pro-brain natriuretic peptide (NT-proBNP), Cystatin C, Neutrophil gelatinase-associated lipocalin (NGAL), Galectin-3, soluble interleukin 1 1 (ST2), Troponin T, I, or C, Vascular cell adhesion protein 1 (VCAM-one), ICAM, E-selectin, CRP, TNF- alpha, interleukins, cortisol, and/or adiponectin * Genomic analyses including whole exome or whole genome sequencing (WGS) to determine pathways, genes, genetic variants, and structural changes to DNA that may be related to HF syndrome. * Epigenetic analyses including DNA methylation measurements to characterize differentially methylated sites that may be related to HF syndrome. * Transcriptomic analyses to characterize alterations to gene expression that may be related to HF syndrome.

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