Meta-Data Analysis to Explore the Interaction of the Hub-Genes interlinking SARS-CoV-2 and Cardiovascular Diseases

Abstract

Introduction

The impact of the pandemic of SARS-CoV-2 infections in the population has caused many diseases onset, post the recovery. The most common is Cardiac injury, which causes further complications that lead to cardiovascular diseases (CVD). This study aimed to analyse the hub genes with a high correlation between SARS-CoV-2 and cardiovascular diseases.

Materials and Methods

The datasets were obtained from the already available GSE196822, GSE196656, and GSE169241 data sets. DESec 2 in R was used for differentially expressed genes, and enriched pathway analysis was performed. Further, Cytoscape used the protein-protein interactions by STRING and hub genes for the common DEGs.

Results

The transcriptome analysis of GSE196822 revealed that 7,376 upregulated and 3,673 downregulated genes were the differentially expressed genes (DEGs) among the three selected datasets. Combining the overlap of these data sets for the common genes involved in COVID-19 and CVD, 169 upregulated and 123 downregulated DEGs were observed. These DEGs are further examined with GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes). The KEGG pathway revealed 21 upregulated and 11 downregulated pathways, where the highest count was recorded in transcriptional misregulations in cancer and metabolic pathways, respectively. The top 10 hub genes analysis and PPI network analysis revealed their interlinings for upregulation and downregulations, respectively. The top three upregulated genes (TIMP1, MPO, NFKBIA) and downregulated genes (ACSS1, OXCT1, ADHFE1) identified by differential expression analysis were validated by qRT-PCR, confirming their significant and consistent expression changes under the experimental conditions.

Conclusion

The 9 out of 10 hub genes with elevated co-expressibility of linked genes between COVID-19 and CVD showed complications consistent with previous reports. Our findings further suggest that these hub genes may serve dual purposes: as indicators of early viral infection, including COVID-19 and related viral illnesses, and as potential predictors of cardiovascular disease (CVD) onset following COVID-19 infection. This work strongly urges health policymakers to implement screening for COVID-19 complications, especially CVDs, in the general public.

Zusammenfassung

Einleitung

Die SARS-CoV-2-Pandemie hat weitreichende gesundheitliche Folgen für die Bevölkerung nach überstandener Infektion gezeigt. Besonders häufig treten kardiale Schädigungen auf, die weitere Komplikationen nach sich ziehen und zur Entstehung kardiovaskulärer Erkrankungen (CVD) beitragen können. Ziel dieser Studie war es, Schlüsselgene, sog. „Hub-Gene“ zu identifizieren, die eine hohe Korrelation zwischen SARS-CoV-2-Infektionen und kardiovaskulären Erkrankungen aufweisen.

Material und Methoden

Die Analyse basierte auf öffentlich verfügbaren Datensätzen: GSE196822, GSE196656 und GSE169241. Zur Identifikation differentiell exprimierter Gene (DEGs) wurde das R-Paket DESeq2 verwendet. Anschließend erfolgte eine Anreicherungspfadanalyse. Für die Analyse von Protein-Protein-Interaktionen (PPI) und die Identifikation zentraler Gene (Hub-Gene) wurde Cytoscape unter Einbindung der STRING-Datenbank genutzt.

Ergebnisse

Die Transkriptomanalyse des Datensatzes GSE196822 ergab 7.376 hochregulierte und 3.673 herunterregulierte Gene. Durch Überlappung der drei Datensätze konnten 169 hochregulierte und 123 herunterregulierte gemeinsame DEGs identifiziert werden, die sowohl mit COVID-19 als auch mit CVD in Verbindung stehen. Diese Gene wurden mittels Gene Ontology (GO) und Kyoto Encyclopedia of Genes and Genomes (KEGG) weiter untersucht. Die KEGG-Analyse zeigte 21 hochregulierte und 11 herunterregulierte Signalwege, wobei die meisten Gene mit Transkriptionsfehlregulationen bei Krebs sowie mit metabolischen Signalwegen assoziiert waren. Die Analyse der zehn wichtigsten Hub-Gene und des PPI-Netzwerks verdeutlichte deren funktionelle Vernetzung. Die drei am stärksten hochregulierten Gene (TIMP1, MPO, NFKBIA) sowie die drei am stärksten herunterregulierten Gene (ACSS1, OXCT1, ADHFE1) wurden mittels quantitativer Real-Time-PCR (qRT-PCR) validiert, was ihre signifikanten und konsistenten Expressionsveränderungen unter experimentellen Bedingungen bestätigte.

Fazit

Neun der zehn identifizierten Hub-Gene zeigten eine erhöhte Ko-Expression mit Genen, die sowohl mit COVID-19 als auch mit kardiovaskulären Erkrankungen in Zusammenhang stehen. Diese Ergebnisse stimmen mit früheren Studien überein. Die identifizierten Gene könnten sowohl als Marker für eine frühe virale Infektion – einschließlich COVID-19 und verwandter viraler Erkrankungen – als auch als potenzielle Prädiktoren für das Auftreten kardiovaskulärer Erkrankungen nach einer COVID-19-Infektion dienen. Die Studie unterstreicht die Notwendigkeit, gesundheitspolitische Maßnahmen zur Früherkennung von COVID-19-bedingten Komplikationen, insbesondere kardiovaskulärer Erkrankungen, in der Allgemeinbevölkerung zu etablieren.

Keywords

COVID-19 - CVD - meta-analysis - differentially expressed genes - hub genes

Schlüsselwörter

COVID-19 - kardiovaskuläre Erkrankungen - Metaanalyse - Schlüsselgene - Hub-Gene

Publikationsverlauf

Eingereicht: 15. Juni 2025

Angenommen nach Revision: 03. September 2025

Artikel online veröffentlicht:
23. September 2025

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