Uncovering the genetic links of SARS-CoV-2 infections on heart failure co-morbidity by a systems biology approach.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35727093", "kind": "science-record", "revision": 4, "content_hash": "sha256:9c8c6985ba57007fe931f4797c7e7d78f486fa287e43248e06d38e7bcacfdfec", "created_at": "2026-11-01T18:14:44Z", "updated_at": "2026-11-01T22:06:50Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Uncovering the genetic links of SARS-CoV-2 infections on heart failure co-morbidity by a systems biology approach.", "doi": "10.1002/ehf2.14003", "pmid": "35727093", "authors": ["Ge Zhang", "Xiaolin Cui", "Li Zhang", "Gangqiong Liu", "Xiaodan Zhu", "Jiahong Shangguan", "Wenjing Zhang", "Yingying Zheng", "Hui Zhang", "Junnan Tang", "Jinying Zhang"], "journal": "ESC heart failure", "year": 2022, "abstract": "AIMS: The co-morbidities contribute to the inferior prognosis of COVID-19 patients. Recent reports suggested that the higher co-morbidity rate between COVID-19 and heart failure (HF) leads to increased mortality. However, the common pathogenic mechanism between them remained elusive. Here, we aimed to reveal underlying molecule mechanisms and genetic correlation between COVID-19 and HF, providing a new perspective on current clinical management for patients with co-morbidity.\nMETHODS: The gene expression profiles of HF (GSE26887) and COVID-19 (GSE147507) were retrieved from the GEO database. After identifying the common differentially expressed genes (|log2FC| > 1 and adjusted P < 0.05), integrated analyses were performed, namely, enrichment analyses, protein-protein interaction network, module construction, critical gene identification, and functional co-expression analysis. The performance of critical genes was validation combining hierarchical clustering, correlation, and principal component analysis in external datasets (GSE164805 and GSE9128). Potential transcription factors and miRNAs were obtained from the JASPER and RegNetwork repository used to construct co-regulatory networks. The candidate drug compounds in potential genetic link targets were further identified using the DSigDB database.\nRESULTS: The alteration of 12 genes was identified as a shared transcriptional signature, with the role of immune inflammatory pathway, especially Toll-like receptor, NF-kappa B, chemokine, and interleukin-related pathways that primarily emphasized in response to SARS-CoV-2 complicated with HF. Top 10 critical genes (TLR4, TLR2, CXCL8, IL10, STAT3, IL1B, TLR1, TP53, CCL20, and CXCL10) were identified from protein-protein interaction with topological algorithms. The unhealthy microbiota status and gut-heart axis in co-morbidity were identified as potential disease roads in bridging pathogenic mechanism, and lipopolysaccharide acts as a potential marker for monitoring HF during COVID-19. For transcriptional and post-transcriptional levels, regulation networks tightly coupling with both disorders were constructed, and significant regulator signatures with high interaction degree, especially FOXC1, STAT3, NF-κB1, miR-181, and miR-520, were detected to regulate common differentially expressed genes. According to genetic links targets, glutathione-based antioxidant strategy combined with muramyl dipeptide-based microbe-derived immunostimulatory therapies was identified as promising anti-COVID-19 and anti-HF therapeutics.\nCONCLUSIONS: This study identified shared transcriptomic and corresponding regulatory signatures as emerging therapeutic targets and detected a set of pharmacologic agents targeting genetic links. Our findings provided new insights for underlying pathogenic mechanisms between COVID-19 and HF.", "claims": [{"id": "claim-method", "statement": "Differentially expressed genes (DEGs) were extracted from both datasets using absolute log2FC cut‐off 1 and adjusted P‐value cut‐off 0.05.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35727093", "locator": "sections[4] \"Identification of shared transcriptomic signature between HF and COVID‐19\" paragraph 2", "quote": "Differentially expressed genes (DEGs) were extracted from both datasets using absolute log2FC cut‐off 1 and adjusted P‐value cut‐off 0.05."}], "state": "complete"}, {"id": "claim-data-access", "statement": "As shown in the flow chart (Figure 1 A ), all data from two independent datasets (GSE147507: COVID‐19 and GSE26887: HF) were obtained from the GEO database.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35727093", "locator": "sections[4] \"Identification of shared transcriptomic signature between HF and COVID‐19\" paragraph 2", "quote": "As shown in the flow chart (Figure 1 A ), all data from two independent datasets (GSE147507: COVID‐19 and GSE26887: HF) were obtained from the GEO database."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The alteration of 12 genes was identified as a shared transcriptional signature, with the role of immune inflammatory pathway, especially Toll‐like receptor, NF‐kappa B, chemokine, and interleukin‐related pathways that primarily emphasized in response to SARS‐CoV‐2 complicated with HF.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35727093", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The alteration of 12 genes was identified as a shared transcriptional signature, with the role of immune inflammatory pathway, especially Toll‐like receptor, NF‐kappa B, chemokine, and interleukin‐related pathways that primarily emphasized in response to SARS‐CoV‐2 complicated with HF."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The alteration of 12 genes was identified as a shared transcriptional signature, with the role of immune inflammatory pathway, especially Toll‐like receptor, NF‐kappa B, chemokine, and interleukin‐related pathways that primarily emphasized in response to SARS‐CoV‐2 complicated with HF.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:35727093"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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