Heart failure with preserved ejection fraction (HFpEF) is a complex clinical syndrome with high morbidity and mortality, commonly seen in the elderly population. The mechanisms underlying the pathophysiology of HFpEF are currently unclear; consequently, understanding these mechanisms is essential to identify biomarkers and develop targeted therapies.

A recent study published in the Genes & Diseases journal by researchers affiliated with Chongqing Medical University and Chongqing University applies an integrated bioinformatics and machine learning approach to understand the molecular mechanisms behind HFpEF and identify the associated prognostic & diagnostic markers.

As an initial step, the authors successfully established an HFpEF model in mice by combining a high-fat diet (HFD) with L-NG-nitroarginine methyl ester (L-NAME), an endothelial nitric oxide synthase inhibitor, and performed bulk RNA sequencing on the heart tissues. Using different GSE datasets and multiple bioinformatics analysis, the authors identified 15 ageing-related differentially expressed genes (ARDEGs), which were primarily associated with metabolic and immune functions and might play an important role in the immune response in HFpEF.

The ARDEGs were then subjected to different machine learning analyses, through which five, namely AGTR1a, CCAR1, Il10RA, NR3C1 and PRKAB1, were identified as potential diagnostic biomarkers. The receiver operating characteristic curve analysis validated three ARDEGs, Agtr1, Nr3c1, and Prkab1, as potential diagnostic markers for HFpEF, while the A-scores showed CENPF, C1QA, and HSP90AB1 as possessing high diagnostic potential for HFpEF subtypes.

Furthermore, HFpEF was classified into high and low A-score groups, which displayed significant differences in the proportion of 24 immune cell types. Importantly, the key DEGs were found to positively correlate with the immune infiltration content, suggesting their critical role in immune regulation in HFpEF. “Although, the precise mechanism of the key DEGs in immune infiltration regulation remains unexplored, targeting them may provide a promising approach for treating HFpEF.”

In conclusion, this study provides key insights in the potential role of ARDEGs as promising prognostic and predictive biomarkers for HFpEF and highlights the pivotal role of immune regulation in HFpEF, which may aid in the identification of novel therapeutic targets.

Reference

Title of the original paper: Identification of ageing-associated gene signatures in heart failure with preserved ejection fraction by integrated bioinformatics analysis and machine learning

Journal: Genes & Diseases
Genes & Diseases is a journal for molecular and translational medicine. The journal primarily focuses on publishing investigations on the molecular bases and experimental therapeutics of human diseases. Publication formats include full length research article, review article, short communication, correspondence, perspectives, commentary, views on news, and research watch.

DOI: https://doi.org/10.1016/j.gendis.2024.101478

Funding Information:
National Natural Science Foundation of China (No. 82070238)
Natural Science Foundation of Chongqing, China (No. CSTB2022NSCQ-MSX0913, CSTB2023NSCQ-MSX0219, CSTC2020JCYJ-MSXMX0290)
Chongqing Education Committee of China (No. KJQN202300480)
Program for Youth Innovation in Future Medicine, Chongqing Medical University (No. W0168).

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Genes & Diseases publishes rigorously peer-reviewed and high quality original articles and authoritative reviews that focus on the molecular bases of human diseases. Emphasis is placed on hypothesis-driven, mechanistic studies relevant to pathogenesis and/or experimental therapeutics of human diseases. The journal has worldwide authorship, and a broad scope in basic and translational biomedical research of molecular biology, molecular genetics, and cell biology, including but not limited to cell proliferation and apoptosis, signal transduction, stem cell biology, developmental biology, gene regulation and epigenetics, cancer biology, immunity and infection, neuroscience, disease-specific animal models, gene and cell-based therapies, and regenerative medicine.

Scopus CiteScore: 7.3 | Impact Factor: 6.9

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