scholarly journals Comorbidities and Susceptibility to COVID-19: A Generalized Gene Set Meta-Analysis Approach

2020 ◽  
Author(s):  
Micaela F. Beckman ◽  
Chika K. Igba ◽  
Farah B. Mougeot ◽  
Jean-Luc Mougeot
Keyword(s):  
Protein Interactions ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Gene Expression Profiles ◽  
Gene Interaction ◽  
Snp Analysis ◽  
Nucleotide Polymorphisms ◽  
Protein Protein Interactions ◽  
Gene Expressions ◽  
Mrna Gene

Background The COVID-19 pandemic has led to over 820,000 deaths for almost 24 million confirmed cases worldwide, as of August 27th, 2020, per WHO report. Risk factors include pre-existing conditions such as cancer, cardiovascular disease, diabetes, obesity, and cancer. There are currently no effective treatments. Our objective was to complete a meta-analysis to identify comorbidity-associated single nucleotide polymorphisms (SNPs), potentially conferring increased susceptibility to SARS-CoV-2 infection using a computational approach. Results SNP datasets were downloaded from publicly available GWAS catalog for 141 of 258 candidate COVID-19 comorbidities. Gene-level SNP analysis was performed to identify significant pathways by using MAGMA program. SNP annotation program was used to analyze MAGMA-identified genes. COVID-19 comorbidities from six disease categories were found to have significant associated pathways, which were validated by Q-Q plots (p<0.05). The top 250 human mRNA gene expressions for SNP-affected pathways, extracted from publicly accessible gene expression profiles, were evaluated for significant pathways. Protein-protein interactions of identified differentially expressed genes, visualized with STRING program, were significant (p<0.05). Gene interaction networks were found to be relevant to SARS and influenza pathogenesis. Conclusion Pathways potentially affected by or affecting SARS-CoV-2 infection were identified in underlying medical conditions likely to confer susceptibility and/or severity to COVID-19. Our findings have implications in COVID-19 treatment development. Keywords: SARS-CoV-2, COVID-19, comorbidity, susceptibility, severity

scholarly journals Comorbidities and Susceptibility to COVID-19: A Generalized Gene Set Data Mining Approach

2021 ◽  
Vol 10 (8) ◽  
pp. 1666
Author(s):  
Micaela F. Beckman ◽  
Farah Bahrani Mougeot ◽  
Jean-Luc C. Mougeot
Keyword(s):  
Protein Interactions ◽  
Association Studies ◽  
Meta Analysis ◽  
Holistic Approach ◽  
Gene Interaction ◽  
Snp Analysis ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Protein Protein Interactions ◽  
Data Mining Approach

The COVID-19 pandemic has led to over 2.26 million deaths for almost 104 million confirmed cases worldwide, as of 4 February 2021 (WHO). Risk factors include pre-existing conditions such as cancer, cardiovascular disease, diabetes, and obesity. Although several vaccines have been deployed, there are few alternative anti-viral treatments available in the case of reduced or non-existent vaccine protection. Adopting a long-term holistic approach to cope with the COVID-19 pandemic appears critical with the emergence of novel and more infectious SARS-CoV-2 variants. Our objective was to identify comorbidity-associated single nucleotide polymorphisms (SNPs), potentially conferring increased susceptibility to SARS-CoV-2 infection using a computational meta-analysis approach. SNP datasets were downloaded from a publicly available genome-wide association studies (GWAS) catalog for 141 of 258 candidate COVID-19 comorbidities. Gene-level SNP analysis was performed to identify significant pathways by using the program MAGMA. An SNP annotation program was used to analyze MAGMA-identified genes. Differential gene expression was determined for significant genes across 30 general tissue types using the Functional and Annotation Mapping of GWAS online tool GENE2FUNC. COVID-19 comorbidities (n = 22) from six disease categories were found to have significant associated pathways, validated by Q–Q plots (p < 0.05). Protein–protein interactions of significant (p < 0.05) differentially expressed genes were visualized with the STRING program. Gene interaction networks were found to be relevant to SARS and influenza pathogenesis. In conclusion, we were able to identify the pathways potentially affected by or affecting SARS-CoV-2 infection in underlying medical conditions likely to confer susceptibility and/or the severity of COVID-19. Our findings have implications in future COVID-19 experimental research and treatment development.

scholarly journals Distinct p53 acetylation cassettes differentially influence gene-expression patterns and cell fate

2006 ◽  
Vol 173 (4) ◽  
pp. 533-544 ◽  
Author(s):  
Chad D. Knights ◽  
Jason Catania ◽  
Simone Di Giovanni ◽  
Selen Muratoglu ◽  
Ricardo Perez ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Fate ◽  
Protein Interactions ◽  
Posttranslational Modifications ◽  
Biological Activities ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
P53 Gene ◽  
Protein Protein Interactions

The activity of the p53 gene product is regulated by a plethora of posttranslational modifications. An open question is whether such posttranslational changes act redundantly or dependently upon one another. We show that a functional interference between specific acetylated and phosphorylated residues of p53 influences cell fate. Acetylation of lysine 320 (K320) prevents phosphorylation of crucial serines in the NH2-terminal region of p53; only allows activation of genes containing high-affinity p53 binding sites, such as p21/WAF; and promotes cell survival after DNA damage. In contrast, acetylation of K373 leads to hyperphosphorylation of p53 NH2-terminal residues and enhances the interaction with promoters for which p53 possesses low DNA binding affinity, such as those contained in proapoptotic genes, leading to cell death. Further, acetylation of each of these two lysine clusters differentially regulates the interaction of p53 with coactivators and corepressors and produces distinct gene-expression profiles. By analogy with the “histone code” hypothesis, we propose that the multiple biological activities of p53 are orchestrated and deciphered by different “p53 cassettes,” each containing combination patterns of posttranslational modifications and protein–protein interactions.

scholarly journals Molecular Characterization and Elucidation of Pathways to Identify Novel Therapeutic Targets in Pulmonary Arterial Hypertension

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiaoting Yao ◽  
Tian Jing ◽  
Tianxing Wang ◽  
Chenxin Gu ◽  
Xi Chen ◽  
...  
Keyword(s):  
Pulmonary Arterial Hypertension ◽  
Arterial Hypertension ◽  
Lung Tissue ◽  
Protein Interactions ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Molecular Signatures ◽  
Protein Protein Interactions ◽  
Pulmonary Arterial ◽  
Microarray Datasets

Background: Pulmonary arterial hypertension (PAH) is a life-threatening chronic cardiopulmonary disease. However, there are limited studies reflecting the available biomarkers from separate gene expression profiles in PAH. This study explored two microarray datasets by an integrative analysis to estimate the molecular signatures in PAH.Methods: Two microarray datasets (GSE53408 and GSE113439) were exploited to compare lung tissue transcriptomes of patients and controls with PAH and to estimate differentially expressed genes (DEGs). According to common DEGs of datasets, gene and protein overrepresentation analyses, protein–protein interactions (PPIs), DEG–transcription factor (TF) interactions, DEG–microRNA (miRNA) interactions, drug–target protein interactions, and protein subcellular localizations were conducted in this study.Results: We obtained 38 common DEGs for these two datasets. Integration of the genome transcriptome datasets with biomolecular interactions revealed hub genes (HSP90AA1, ANGPT2, HSPD1, HSPH1, TTN, SPP1, SMC4, EEA1, and DKC1), TFs (FOXC1, FOXL1, GATA2, YY1, and SRF), and miRNAs (hsa-mir-17-5p, hsa-mir-26b-5p, hsa-mir-122-5p, hsa-mir-20a-5p, and hsa-mir-106b-5p). Protein–drug interactions indicated that two compounds, namely, nedocromil and SNX-5422, affect the identification of PAH candidate biomolecules. Moreover, the molecular signatures were mostly localized in the extracellular and nuclear areas.Conclusions: In conclusion, several lung tissue-derived molecular signatures, highlighted in this study, might serve as novel evidence for elucidating the essential mechanisms of PAH. The potential drugs associated with these molecules could thus contribute to the development of diagnostic and therapeutic strategies to ameliorate PAH.

scholarly journals Intra- and intergenerational changes in the cortical DNA methylome in response to therapeutic intermittent hypoxia in mice

2020 ◽  
Vol 52 (1) ◽  
pp. 20-34 ◽  
Author(s):  
Krystal Courtney D. Belmonte ◽  
Jarrod C. Harman ◽  
Nicholas A. Lanson ◽  
Jeffrey M. Gidday
Keyword(s):  
Gene Expression ◽  
Prefrontal Cortex ◽  
Protein Interactions ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Protein Protein Interactions ◽  
Dna Methylome ◽  
Methylated Dna ◽  
Modified Dna ◽  
F1 Generation

Recent evidence from our laboratory documents functional resilience to retinal ischemic injury in untreated mice derived from parents exposed to repetitive hypoxic conditioning (RHC) before breeding. To begin to understand the epigenetic basis of this intergenerational protection, we used methylated DNA immunoprecipitation and sequencing to identify genes with differentially methylated promoters (DMGPs) in the prefrontal cortex of mice treated directly with the same RHC stimulus (F0-RHC) and in the prefrontal cortex of their untreated F1-generation offspring (F1-*RHC). Subsequent bioinformatic analyses provided key mechanistic insights into how changes in gene expression secondary to promoter hypo- and hypermethylation might afford such protection within and across generations. We found extensive changes in DNA methylation in both generations consistent with the expression of many survival-promoting genes, with twice the number of DMGPs in the cortex of F1*RHC mice relative to their F0 parents that were directly exposed to RHC. In contrast to our hypothesis that similar epigenetic modifications would be realized in the cortices of both F0-RHC and F1-*RHC mice, we instead found relatively few DMGPs common to both generations; in fact, each generation manifested expected injury resilience via distinctly unique gene expression profiles. Whereas in the cortex of F0-RHC mice, predicted protein-protein interactions reflected activation of an anti-ischemic phenotype, networks activated in F1-*RHC cortex comprised networks indicative of a much broader cytoprotective phenotype. Altogether, our results suggest that the intergenerational transfer of an acquired phenotype to offspring does not necessarily require the faithful recapitulation of the conditioning-modified DNA methylome of the parent.

scholarly journals Identification of Disease-Related Genes That Are Common between Alzheimer’s and Cardiovascular Disease Using Blood Genome-Wide Transcriptome Analysis

Biomedicines ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1525
Author(s):  
Taesic Lee ◽  
Hyunju Lee ◽  
Keyword(s):  
Cardiovascular Disease ◽  
Protein Interactions ◽  
Regulatory Networks ◽  
Nucleotide Polymorphisms ◽  
Protein Protein Interactions ◽  
Gene Expressions ◽  
Genome Wide ◽  
Cell Gene Expression ◽  
Cell Gene ◽  
Disease Related Gene

Accumulating evidence has suggested a shared pathophysiology between Alzheimer’s disease (AD) and cardiovascular disease (CVD). Based on genome-wide transcriptomes, specifically those of blood samples, we identify the shared disease-related signatures between AD and CVD. In addition to gene expressions in blood, the following prior knowledge were utilized to identify several candidate disease-related gene (DRG) sets: protein–protein interactions, transcription factors, disease–gene relationship databases, and single nucleotide polymorphisms. We selected the respective DRG sets for AD and CVD that show a high accuracy for disease prediction in bulk and single-cell gene expression datasets. Then, gene regulatory networks (GRNs) were constructed from each of the AD and CVD DRG sets to identify the upstream regulating genes. Using the GRNs, we identified two common upstream genes (GPBP1 and SETDB2) between the AD and CVD GRNs. In summary, this study has identified the potential AD- and CVD-related genes and common hub genes between these sets, which may help to elucidate the shared mechanisms between these two diseases.

Gene Expression Profiles as Predictors of Poor Outcomes in Stage II Colorectal Cancer: A Systematic Review and Meta-analysis

2009 ◽  
Vol 8 (4) ◽  
pp. 207-214 ◽  
Author(s):  
An-Ting T. Lu ◽  
Shelley R. Salpeter ◽  
Anthony E. Reeve ◽  
Steven Eschrich ◽  
Patrick G. Johnston ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Systematic Review ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Gene Expression Profiles ◽  
Stage Ii ◽  
Stage Ii Colorectal Cancer ◽  
Poor Outcomes
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