Discovering common pathogenetic processes between COVID-19 and tuberculosis by bioinformatics and system biology approach

Huang, Tengda; He, Jinyi; Zhou, Xinyi; Pan, Hongyuan; He, Fang; Du, Ao; Yu, Bingxuan; Jiang, Nan; Li, Xiaoquan; Yuan, Kefei; Wang, Zhen

doi:10.3389/fcimb.2023.1280223

Cited by 4 publications

(1 citation statement)

References 97 publications

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“…Coronavirus disease 2019 (COVID-19) has already caused a global pandemic in just a few years after its appearance, posing a significant health challenge worldwide, with the pandemic having killed more than 6 million people[1]. As the pandemic progresses, new variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have emerged.…”

Section: Introductionmentioning

confidence: 99%

Exploration of the link between COVID-19 and gastric cancer from the perspective of bioinformatics and systems biology

Ma,

Huang,

et al. 2024

Preprint

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Background: Coronavirus disease 2019 (COVID-19), an infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has caused a global pandemic. Gastric cancer (GC) poses a great threat to people's health, which is a high-risk factor for COVID-19. Previous studies have found some associations between GC and COVID-19, whereas the underlying molecular mechanisms are not well understood. Methods: We used a bioinformatics and systems biology approach to investigate the relationship between GC and COVID-19. The gene expression profiles of COVID-19 (GSE196822) and GC (GSE179252) were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the shared differentially expressed genes (DEGs) for GC and COVID-19, functional annotation, protein-protein interaction (PPI) network, hub genes, transcriptional regulatory networks and candidate drugs were analyzed. Results: A total of 209 shared DEGs were identified to explore the linkages between COVID-19 and GC. Functional analyses showed that Immune-related pathway collectively participated in the development and progression of COVID-19 and GC. In addition, there are selected 10 hub genes including CDK1, KIF20A, TPX2, UBE2C, HJURP, CENPA, PLK1, MKI67, IFI6, and IFIT2. The transcription factor/gene and miRNA/gene interaction networks identified 38 transcription factors (TFs) and 234 miRNAs. More importantly, we identified ten potential therapeutic agents, including ciclopirox, resveratrol, etoposide, methotrexate, trifluridine, enterolactone, troglitazone, calcitriol, dasatinib and deferoxamine, some of which have been reported to improve and treat GC and COVID-19. This study also provides insight into the diseases most associated with mutual DEGs, which may provide new ideas for research on the treatment of COVID-19. Conclusions: This research has the possibility to be contributed to effective therapeutic in COVID-19 and GC.

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Section: Introductionmentioning

confidence: 99%

Exploration of the link between COVID-19 and gastric cancer from the perspective of bioinformatics and systems biology

Ma,

Huang,

et al. 2024

Preprint

Self Cite

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Discovering common pathogenetic processes between periodontitis and Alzheimer’s disease by bioinformatics and system biology approach

Ge,

Zhao,

Zheng

et al. 2024

BMC Oral Health

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Background There is increasing evidence that inflammation plays a key role in the pathophysiology of periodontitis (PT) and Alzheimer’s disease (AD), but the roles of inflammation in linking PT and AD are not clear. Our aim is to analyze the potential molecular mechanisms between these two diseases using bioinformatics and systems biology approaches. Methods To elucidate the link between PT and AD, we selected shared genes (SGs) with gene-disease-association scores of ≥ 0.1 from the Disease Gene Network (DisGeNET) database, followed by extracting the hub genes. Based on these genes, we constructed gene ontology (GO) enrichment analysis, pathway enrichment analysis, protein-protein interaction (PPI) networks, transcription factors (TFs)-gene networks, microRNAs (miRNAs)-gene regulatory networks, and gene-disease association analyses. Finally, the Drug Signatures database (DSigDB) was utilized to predict candidate molecular drugs related to hub genes. Results A total of 21 common SGs between PT and AD were obtained. Cell cytokine activity, inflammatory response, and extracellular membrane were the most important enriched items in GO analysis. Interleukin-10 Signaling, LTF Danger Signal Response Pathway, and RAGE Pathway were identified as important shared pathways. IL6 , IL10 , IL1B , TNF , IFNG , CXCL8 , CCL2 , MMP9 , TLR4 were identified as hub genes. Both shared pathways and hub genes are closely related to endoplasmic reticulum (ER) stress and mitochondrial dysfunction. Importantly, glutathione, simvastatin, and dexamethasone were identified as important candidate drugs for the treatment of PT and AD. Conclusions There is a close link between PT and AD pathogenesis, which may involve in the inflammation, ER and mitochondrial function. Supplementary Information The online version contains supplementary material available at 10.1186/s12903-024-04775-9.

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Exploration of the link between COVID-19 and gastric cancer from the perspective of bioinformatics and systems biology

Ma,

Huang,

et al. 2024

Front. Med.

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BackgroundCoronavirus disease 2019 (COVID-19), an infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has caused a global pandemic. Gastric cancer (GC) poses a great threat to people’s health, which is a high-risk factor for COVID-19. Previous studies have found some associations between GC and COVID-19, whereas the underlying molecular mechanisms are not well understood.MethodsWe employed bioinformatics and systems biology to explore these links between GC and COVID-19. Gene expression profiles of COVID-19 (GSE196822) and GC (GSE179252) were obtained from the Gene Expression Omnibus (GEO) database. After identifying the shared differentially expressed genes (DEGs) for GC and COVID-19, functional annotation, protein-protein interaction (PPI) network, hub genes, transcriptional regulatory networks and candidate drugs were analyzed.ResultsWe identified 209 shared DEGs between COVID-19 and GC. Functional analyses highlighted immune-related pathways as key players in both diseases. Ten hub genes (CDK1, KIF20A, TPX2, UBE2C, HJURP, CENPA, PLK1, MKI67, IFI6, IFIT2) were identified. The transcription factor/gene and miRNA/gene interaction networks identified 38 transcription factors (TFs) and 234 miRNAs. More importantly, we identified ten potential therapeutic agents, including ciclopirox, resveratrol, etoposide, methotrexate, trifluridine, enterolactone, troglitazone, calcitriol, dasatinib and deferoxamine, some of which have been reported to improve and treat GC and COVID-19.ConclusionThis research offer valuable insights into the molecular interplay between COVID-19 and GC, potentially guiding future therapeutic strategies.

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Discovering common pathogenetic processes between COVID-19 and tuberculosis by bioinformatics and system biology approach

Cited by 4 publications

References 97 publications

Exploration of the link between COVID-19 and gastric cancer from the perspective of bioinformatics and systems biology

Exploration of the link between COVID-19 and gastric cancer from the perspective of bioinformatics and systems biology

Discovering common pathogenetic processes between periodontitis and Alzheimer’s disease by bioinformatics and system biology approach

Exploration of the link between COVID-19 and gastric cancer from the perspective of bioinformatics and systems biology

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