Bioinformatics Approach Predicts Candidate Targets for SARS‐CoV‐2 Infections to COPD Patients

Che, Li; Chen, Guangshu; Cai, Xingdong; Xie, Zhefan; Xia, Tingting; Zhang, Wei; Liu, Shengming

doi:10.1155/2022/1806427

Cited by 3 publications

(1 citation statement)

References 69 publications

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“…According to ACE2 , it is recognized as the main receptor for SARS-CoV-2 and it is a requirement for COVID-19 virus entry combined with TMPRSS2 . High expressions patterns of ACE2 and Dipeptidyl Peptidase 4 (DPP4) can be detected in blood and alveolar lavage fluid in patients with chronic obstructive pulmonary disease and asthma [ 21 , 23 ]. We selected its main SNP (rs2285666), but no significant values were reported.…”

Section: Discussionmentioning

confidence: 99%

Analyzing the role of ACE2, AR, MX1 and TMPRSS2 genetic markers for COVID-19 severity

Martinez-Diz,

Morales-Álvarez,

Garcia-Iglesias

et al. 2023

Hum Genomics

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Background The use of molecular biomarkers for COVID-19 remains unconclusive. The application of a molecular biomarker in combination with clinical ones that could help classifying aggressive patients in first steps of the disease could help clinician and sanitary system a better management of the disease. Here we characterize the role of ACE2, AR, MX1, ERG, ETV5 and TMPRSS2 for trying a better classification of COVID-19 through knowledge of the disease mechanisms. Methods A total of 329 blood samples were genotyped in ACE2, MX1 and TMPRSS2. RNA analyses were also performed from 258 available samples using quantitative polymerase chain reaction for genes: ERG, ETV5, AR, MX1, ACE2, and TMPRSS2. Moreover, in silico analysis variant effect predictor, ClinVar, IPA, DAVID, GTEx, STRING and miRDB database was also performed. Clinical and demographic data were recruited from all participants following WHO classification criteria. Results We confirm the use of ferritin (p < 0.001), D-dimer (p < 0.010), CRP (p < 0.001) and LDH (p < 0.001) as markers for distinguishing mild and severe cohorts. Expression studies showed that MX1 and AR are significantly higher expressed in mild vs severe patients (p < 0.05). ACE2 and TMPRSS2 are involved in the same molecular process of membrane fusion (p = 4.4 × 10–3), acting as proteases (p = 0.047). Conclusions In addition to the key role of TMPSRSS2, we reported for the first time that higher expression levels of AR are related with a decreased risk of severe COVID-19 disease in females. Moreover, functional analysis demonstrates that ACE2, MX1 and TMPRSS2 are relevant markers in this disease. Graphical abstract

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Section: Discussionmentioning

confidence: 99%

Analyzing the role of ACE2, AR, MX1 and TMPRSS2 genetic markers for COVID-19 severity

Martinez-Diz,

Morales-Álvarez,

Garcia-Iglesias

et al. 2023

Hum Genomics

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Network biology and bioinformatics-based framework to identify the impacts of SARS-CoV-2 infections on lung cancer and tuberculosis

Waaje,

Sarkar,

Islam

2024

Preprint

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The severe acute respiratory syndrome coronavirus 2 (SARSCoV 2) is a coronavirus variation responsible for COVID19, the respiratory disease that triggered the COVID19 pandemic. The primary aim of our study is to elucidate the complex network of interactions between SARS CoV 2, tuberculosis, and lung cancer employing a bioinformatics and network biology approach. Lung cancer is the leading cause of significant illness and death connected to cancer worldwide. Tuberculosis (TB) is a prevalent medical condition induced by the Mycobacterium bacteria. It mostly affects the lungs but may also have an influence on other areas of the body. Coronavirus disease (COVID19) causes a risk of respiratory complications between lung cancer and tuberculosis. SARSCoV 2 impacts the lower respiratory system and causes severe pneumonia, which can significantly increase the mortality risk in individuals with lung cancer. We conducted transcriptome analysis to determine molecular biomarkers and common pathways in lung cancer, TB, and COVID19, which provide understanding into the association of SARSCoV 2 to lung cancer and tuberculosis. Based on the compatible RNA-seq data, our research employed GREIN and NCBI's Gene Expression Omnibus (GEO) to perform differential gene expression analysis. Our study exploited three RNAseq datasets from the Gene Expression Omnibus (GEO) GSE171110, GSE89403, and GSE81089 to identify distinct relationships between differentially expressed genes (DEGs) in SARSCoV 2, tuberculosis, and lung cancer. We identified 30 common genes among SARSCoV 2, tuberculosis, and lung cancer (25 upregulated genes and 5 downregulated genes). We analyzed the following five databases: WikiPathway, KEGG, Bio Carta, Elsevier Pathway and Reactome. Using Cytohubba's MCC and Degree methods, We determined the top 15 hub genes resulting from the PPI interaction. These hub genes can serve as potential biomarkers, leading to novel treatment strategies for disorders under investigation. Transcription factors (TFs) and microRNAs (miRNAs) were identified as the molecules that control the differentially expressed genes (DEGs) of interest, either during transcription or after transcription. We identified 35 prospective therapeutic compounds that form significant differentially expressed genes (DEGs) in SARSCoV 2, lung cancer, and tuberculosis, which could potentially serve as medications. We hypothesized that the potential medications that emerged from this investigation may have therapeutic benefits.

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The role of autophagy in odontogenesis, dental implant surgery, periapical and periodontal diseases

İnan,

Barış

2024

J Cellular Molecular Medi

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Autophagy is a cellular process that is evolutionarily conserved, involving the sequestration of damaged organelles and proteins into autophagic vesicles, which subsequently fuse with lysosomes for degradation. Autophagy controls the development of many diseases by influencing apoptosis, inflammation, the immune response and different cellular processes. Autophagy plays a significant role in the aetiology of disorders associated with dentistry. Autophagy controls odontogenesis. Furthermore, it is implicated in the pathophysiology of pulpitis and periapical disorders. It enhances the survival, penetration and colonization of periodontal pathogenic bacteria into the host periodontal tissues and facilitates their escape from host defences. Autophagy plays a crucial role in mitigating exaggerated inflammatory reactions within the host's system during instances of infection and inflammation. Autophagy also plays a role in the relationship between periodontal disease and systemic diseases. Autophagy promotes wound healing and may enhance implant osseointegration. This study reviews autophagy's dento‐alveolar effects, focusing on its role in odontogenesis, periapical diseases, periodontal diseases and dental implant surgery, providing valuable insights for dentists on tooth development and dental applications. A thorough examination of autophagy has the potential to discover novel and efficacious treatment targets within the field of dentistry.

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Bioinformatics Approach Predicts Candidate Targets for SARS‐CoV‐2 Infections to COPD Patients

Cited by 3 publications

References 69 publications

Analyzing the role of ACE2, AR, MX1 and TMPRSS2 genetic markers for COVID-19 severity

Analyzing the role of ACE2, AR, MX1 and TMPRSS2 genetic markers for COVID-19 severity

Network biology and bioinformatics-based framework to identify the impacts of SARS-CoV-2 infections on lung cancer and tuberculosis

The role of autophagy in odontogenesis, dental implant surgery, periapical and periodontal diseases

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