Aptamer Proteomics for Biomarker Discovery in Heart Failure With Preserved Ejection Fraction: The PARAGON-HF Proteomic Substudy.

BACKGROUND: Prognostic markers and biological pathways linked to detrimental clinical outcomes in heart failure with preserved ejection fraction (HFpEF) remain incompletely defined. METHODS AND RESULTS: We measured serum levels of 4123 unique proteins in 1117 patients with HFpEF enrolled in the PARAGON-HF (Efficacy and Safety of LCZ696 Compared to Valsartan, on Morbidity and Mortality in Heart Failure Patients With Preserved Ejection Fraction) trial using a modified aptamer proteomic assay. Baseline circulating protein concentrations significantly associated with the primary end point and the timing and occurrence of total heart failure hospitalization and cardiovascular death were identified by recurrent events regression, accounting for multiple testing, adjusted for age, sex, treatment, and anticoagulant use, and compared with published analyses in 2515 patients with heart failure with reduced ejection fraction from the PARADIGM-HF (Prospective Comparison of ARNI With ACEI to Determine Impact on Global Mortality and Morbidity in Heart Failure) and ATMOSPHERE (Efficacy and Safety of Aliskiren and Aliskiren/Enalapril Combination on Morbidity-Mortality in Patients With Chronic Heart Failure) clinical trials. We identified 288 proteins that were robustly associated with the risk of heart failure hospitalization and cardiovascular death in patients with HFpEF. The baseline proteins most strongly related to outcomes included B2M (ß-2 microglobulin), TIMP1 (tissue inhibitor of matrix metalloproteinase 1), SERPINA4 (serpin family A member 4), and SVEP1 (sushi, von Willebrand factor type A, EGF, and pentraxin domain containing 1). Overall, the protein-outcome associations in patients with HFpEF did not markedly differ as compared with patients with heart failure with reduced ejection fraction. A proteomic risk score derived in patients with HFpEF was not superior to a previous proteomic score derived in heart failure with reduced ejection fraction nor to clinical risk factors, NT-proBNP (N-terminal pro-B-type natriuretic peptide), or high-sensitivity cardiac troponin. CONCLUSIONS: Numerous serum proteins linked to metabolic, coagulation, and extracellular matrix regulatory pathways were associated with worse HFpEF prognosis in the PARAGON-HF proteomic substudy. Our results demonstrate substantial similarities among serum proteomic risk markers for heart failure hospitalization and cardiovascular death when comparing clinical trial participants with heart failure across the ejection fraction spectrum. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique Identifiers: NCT01920711, NCT01035255, NCT00853658.

A Multi-Omics Interpretable Machine Learning Model Reveals Modes of Action of Small Molecules.

High-throughput screening and gene signature analyses frequently identify lead therapeutic compounds with unknown modes of action (MoAs), and the resulting uncertainties can lead to the failure of clinical trials. We developed an approach for uncovering MoAs through an interpretable machine learning model of transcriptomics, epigenomics, metabolomics, and proteomics. Examining compounds with beneficial effects in models of Huntington's Disease, we found common MoAs for compounds with unrelated structures, connectivity scores, and binding targets. The approach also predicted highly divergent MoAs for two FDA-approved antihistamines. We experimentally validated these effects, demonstrating that one antihistamine activates autophagy, while the other targets bioenergetics. The use of multiple omics was essential, as some MoAs were virtually undetectable in specific assays. Our approach does not require reference compounds or large databases of experimental data in related systems and thus can be applied to the study of agents with uncharacterized MoAs and to rare or understudied diseases.

Cell freezing protocol suitable for ATAC-Seq on motor neurons derived from human induced pluripotent stem cells.

In recent years, the assay for transposase-accessible chromatin using sequencing (ATAC-Seq) has become a fundamental tool of epigenomic research. However, it is difficult to perform this technique on frozen samples because freezing cells before extracting nuclei can impair nuclear integrity and alter chromatin structure, especially in fragile cells such as neurons. Our aim was to develop a protocol for freezing neuronal cells that is compatible with ATAC-Seq; we focused on a disease-relevant cell type, namely motor neurons differentiated from induced pluripotent stem cells (iMNs) from a patient affected by spinal muscular atrophy. We found that while flash-frozen iMNs are not suitable for ATAC-Seq, the assay is successful with slow-cooled cryopreserved cells. Using this method, we were able to isolate high quality, intact nuclei, and we verified that epigenetic results from fresh and cryopreserved iMNs quantitatively agree.