ArticleJournal of inflammation research2023
Integration of RNA-Seq and Machine Learning Identifies Hub Genes for Empagliflozin Benefitable Heart Failure with Reduced Ejection Fraction.
Article in Journal of inflammation research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed, 0 citations in OpenAlex.
- The impact of SGLT2 inhibitors on uric acid levels in patients with heart failure with preserved ejection fraction: integration of mechanisms and clinical evidence.Frontiers in cardiovascular medicine · 2026Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: This study aimed to analyze the hub genes of heart failure with reduced ejection fraction (HFrEF) treated with Empagliflozin using RNA sequencing (RNA-seq) and bioinformatics methods, including machine learning. Methods: From February 2021 to February 2023, nine patients with HFrEF were enrolled from our hospital's cardiovascular department. In addition to routine drug treatment, these patients received 10 mg of Empagliflozin once daily for two months. Efficacy was assessed and RNA-seq was performed on peripheral blood before and after treatment with empagliflozin. HFrEF-related hub genes were identified through bioinformatics analyses including differential gene expression analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, immune infiltration analysis, machine learning, immune cell correlation analysis and clinical indicator correlation analysis. Results: The nine patients included in this study completed a two-month treatment regimen, with an average age of 62.11 ± 6.36 years. By performing bioinformatics analysis on the transcriptome from the treatment groups, 42 differentially expressed genes were identified, with six being up-regulated and 36 being down-regulated (|log2FC|>1 and adj.pvalue<0.05). Immune infiltration analysis of these genes demonstrated a significant difference in the proportion of plasma between the pre-treatment and post-treatment groups ( Conclusion: Through RNA-seq and bioinformatics analysis, this study identified GTF2IP14 and MTLN as the hub genes of HFrEF, and their mechanisms may be related to immune inflammatory responses and various immune cells.
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