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

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. Methods 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. Results 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. Conclusions 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.

Bioinformatics and systems biology approaches to identify molecular targeting mechanism influenced by COVID-19 on heart failure

“…The TFs associated with all hub genes were FOXC1, FOS, YY1, GATA2, HNF4A, STAT3, RELA, USF2, JUN, PRDM1, and RUNX2. Based on previous studies, most of these 11 TF, especially FOXC1 and STAT3 are involved in the progression of COVID-19 and heart-related diseases ( 100 ). Eleven miRNAs were associated with all hub genes, some of which have been associated with liver cancer ( 101 – 103 ) (e.g., hsa-mir-27a-3p, hsa-mir-26a-5p, hsa-mir-182-5p, and hsa-mir-212-3p) and some have been closely related to lung cancer ( 104 – 107 ) (e.g., hsa-mir-335-5p, hsa mir-182-5p, hsa-mir-212-3p, and hsa-mir-29c-3p).…”

Differential expression profiles of plasma exosomal microRNAs in dilated cardiomyopathy with chronic heart failure

“…Based on miRBase 22.0 (http://www.mirbase.org/)), the unique sequences with the length of 18 ~ 26 nt were mapped to miRNA sequences, to recognize confirmed miRNAs and pre‐miRNAs (including novel 3p‐ and 5p‐derived miRNAs). Also, after the procedure, data normalization was applied based on the method described previously 22–24 . The remaining unmapped sequences were further screened against Homo sapiens genomic sequences to identify potential novel miRNAs.…”

A year in heart failure: updates of clinical and preclinical findings

“…Authors identified 10–12 genes from a protein–protein interaction study and as a shared transcriptional signature. Interestingly, the importance of the unhealthy microbiota status and a gut–heart axis were emphasized as bridging pathogenic mechanisms between HF and COVID‐19 57 …”

“…Interestingly, the importance of the unhealthy microbiota status and a gutheart axis were emphasized as bridging pathogenic mechanisms between HF and COVID-19. 57 Dubé et al conducted a pharmacogenomic study of HF and the angiotensin-II receptor blocker, candesartan response from the CHARM programme where their objective was to identify genetic predictors of HF progression and of the efficacy and safety of treatment with candesartan. In short, in their genome-wide association studies, including 2727 patients, they have identified a candidate genetic variant potentially predictive of the progression of HF in patients with preserved ejection fraction.…”