Identification of novel candidate genes involved in the progression of emphysema by bioinformatic methods

CircRNA-associated ceRNA networks (circCeNETs) in chronic obstructive pulmonary disease (COPD)

Chronic obstructive pulmonary disease (COPD), a chronic airway disorder, which is mostly brought on by cigarette smoke extract (CSE), is a leading cause of death which has a high frequency. In COPD patients, smoking cigarette could also trigger the epithelial-mesenchymal transition (EMT) of airway remodeling. One of the most significant elements of environmental contaminants that is linked to pulmonary damage is fine particulate matter (PM2.5). However, the basic processes of lung injury brought on by environmental contaminants and cigarette smoke are poorly understood, particularly the molecular pathways involved in inflammation. For the clinical management of COPD, investigating the molecular process and identifying workable biomarkers will be important. According to newly available research, circular RNAs (circRNAs) are aberrantly produced and serve as important regulators in the pathological processes of COPD. This class of non-coding RNAs (ncRNAs) functions as microRNA (miRNA) sponges to control the levels of gene expression, changing cellular phenotypes and advancing disease. These findings led us to concentrate our attention in this review on new studies about the regulatory mechanism and potential roles of circRNA-associated ceRNA networks (circCeNETs) in COPD.

Peripheral Blood Mononuclear Cell Gene Expression Associated with Pulmonary Microvascular Perfusion: The Multi-Ethnic Study of Atherosclerosis Chronic Obstructive Pulmonary Disease

Rationale: Chronic obstructive pulmonary disease (COPD) and emphysema are associated with endothelial damage and altered pulmonary microvascular perfusion. The molecular mechanisms underlying these changes are poorly understood in patients, in part because of the inaccessibility of the pulmonary vasculature. Peripheral blood mononuclear cells (PBMCs) interact with the pulmonary endothelium. Objectives: To test the association between gene expression in PBMCs and pulmonary microvascular perfusion in COPD. Methods: The Multi-Ethnic Study of Atherosclerosis (MESA) COPD Study recruited two independent samples of COPD cases and controls with ⩾10 pack-years of smoking history. In both samples, pulmonary microvascular blood flow, pulmonary microvascular blood volume, and mean transit time were assessed on contrast-enhanced magnetic resonance imaging, and PBMC gene expression was assessed by microarray. Additional replication was performed in a third sample with pulmonary microvascular blood volume measures on contrast-enhanced dual-energy computed tomography. Differential expression analyses were adjusted for age, gender, race/ethnicity, educational attainment, height, weight, smoking status, and pack-years of smoking. Results: The 79 participants in the discovery sample had a mean age of 69 ± 6 years, 44% were female, 25% were non-White, 34% were current smokers, and 66% had COPD. There were large PBMC gene expression signatures associated with pulmonary microvascular perfusion traits, with several replicated in the replication sets with magnetic resonance imaging (n = 47) or dual-energy contrast-enhanced computed tomography (n = 157) measures. Many of the identified genes are involved in inflammatory processes, including nuclear factor-κB and chemokine signaling pathways. Conclusions: PBMC gene expression in nuclear factor-κB, inflammatory, and chemokine signaling pathways was associated with pulmonary microvascular perfusion in COPD, potentially offering new targetable candidates for novel therapies.

Computational prognostic evaluation of Alzheimer's drugs from FDA-approved database through structural conformational dynamics and drug repositioning approaches

Drug designing is high-priced and time taking process with low success rate. To overcome this obligation, computational drug repositioning technique is being promptly used to predict the possible therapeutic effects of FDA approved drugs against multiple diseases. In this computational study, protein modeling, shape-based screening, molecular docking, pharmacogenomics, and molecular dynamic simulation approaches have been utilized to retrieve the FDA approved drugs against AD. The predicted MADD protein structure was designed by homology modeling and characterized through different computational resources. Donepezil and galantamine were implanted as standard drugs and drugs were screened out based on structural similarities. Furthermore, these drugs were evaluated and based on binding energy (Kcal/mol) profiles against MADD through PyRx tool. Moreover, pharmacogenomics analysis showed good possible associations with AD mediated genes and confirmed through detail literature survey. The best 6 drug (darifenacin, astemizole, tubocurarine, elacridar, sertindole and tariquidar) further docked and analyzed their interaction behavior through hydrogen binding. Finally, MD simulation study were carried out on these drugs and evaluated their stability behavior by generating root mean square deviation and fluctuations (RMSD/F), radius of gyration (Rg) and soluble accessible surface area (SASA) graphs. Taken together, darifenacin, astemizole, tubocurarine, elacridar, sertindole and tariquidar displayed good lead like profile as compared with standard and can be used as possible therapeutic agent in the treatment of AD after in-vitro and in-vivo assessment.

Exploration of glycosyltransferases mutation status in cervical cancer reveals PARP14 as a potential prognostic marker

This study investigates the potential role of Glycosyltransferases (GTs) in the glycosylation process and their association with malignant tumors. Specifically, the study focuses on PARP14, a member of GTs, and its potential as a target for tumors in the diagnosis and treatment of cervical cancer. To gather data, the study used somatic mutation data, gene expression data and clinical information from TCGA-CESE dataset as well as tissue samples from cervical cancer patients. Further verification was conducted through RT-qPCR and immunohistochemistry staining on cervical cancer tissues to confirm the expression of PARP14. The study utilized Kaplan-Meier for survival analysis of cervical cancer patient and found significant mutational abnormalities in GTs. The high frequency mutated gene was identified as PARP14. RT-qPCR revealed significantly higher mRNA expression of PARP14 compared to precancerous tissue. Using IHC combined with Kaplan-Meier,patients in the PARP14 high expression group had a better prognosis than the low expression group. The study identified PARP14 as a frequently mutated gene in cervical cancer and proposed its potential role in diagnosis and treatment.

Bioinformatics analysis of PLA2G7 as an immune-related biomarker in COPD by promoting expansion and suppressive functions of MDSCs

BACKGROUND

Immune mechanism is involved in the pathogenesis of chronic obstructive pulmonary disease (COPD). However, the exact immune pathogenesis still remains unclear. This study aimed to identify the immune-related biomarkers in COPD through bioinformatics analysis and its potential molecular mechanism.

METHODS

GSE76925 was downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened, and enrichment analysis was performed. Single sample gene enrichment analysis (ssGSEA) was conducted to score the infiltration levels of immune cells. Weighted gene co-expression network analysis (WGCNA) was applied to identify trait-related modules and to further determine the key module-related DEGs. Moreover, the correlations between the key genes and clinical parameters and infiltration levels of immune cells were analyzed. Furthermore, expression of the selected one key gene, PLA2G7, the frequency of MDSCs, and the expression of MDSCs-related immunosuppressive mediators were determined among healthy, smokers and COPD patients. Finally, effects of PLA2G7 abnormal expression on the frequency of MDSCs and the expression of MDSCs-related immunosuppressive mediators were examined.

RESULTS

A total of 352 DEGs were observed. These DEGs were mainly related to RNA metabolism and positive regulation of organelle organization. In addition, the black module was the most correlated with COPD. Six key genes (ADAMDEC1, CCL19, CHIT1, MMP9, PLA2G7, and TM4SF19) were identified between the black module and DEGs. Serum Lp-PLA2 and mRNA levels of PLA2G7, MDSCs, and MDSCs-related immunosuppressive mediators were found to be upregulated in COPD patients compared to the controls. The expression of PLA2G7 represented positive impact on the frequency of MDSCs and the expression of MDSCs-related immunosuppressive mediators.

CONCLUSION

PLA2G7 may serve as a potential immune-related biomarker contributing to the progression of COPD by promoting expansion and suppressive functions of MDSCs.

Dynamic analysis of gene signatures in the progression of COPD

Aims

Oxidative stress is an important amplifying mechanism in COPD; however, it is unclear how oxidative stress changes and what its exact amplification mechanism is in the pathological process. We aimed to dynamically analyse the progression of COPD and further elucidate the characteristics of each developmental stage and unveil the underlying mechanisms.

Methods

We performed a holistic analysis by integrating Gene Expression Omnibus microarray datasets related to smoking, emphysema and Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification based on the concept of gene, environment and time (GET). Gene ontology (GO), protein-protein interaction (PPI) networks and gene set enrichment analysis (GSEA) were used to explore the changing characteristics and potential mechanisms. Lentivirus was used to promote HIF3A overexpression.

Results

In smokers versus nonsmokers, the GO term mainly enriched in "negative regulation of apoptotic process". In later transitions between stages, the main enriched terms were continuous progression of "oxidation-reduction process" and "cellular response to hydrogen peroxide". Logistic regression showed that these core differentially expressed genes (DEGs) had diagnostic accuracy in test (area under the curve (AUC)=0.828) and validation (AUC=0.750) sets. GSEA and PPI networks showed that one of the core DEGs, HIF3A, strongly interacted with the ubiquitin-mediated proteolysis pathway. Overexpression of HIF3A restored superoxide dismutase levels and alleviated the reactive oxygen species accumulation caused by cigarette smoke extract treatment.

Conclusion

Oxidative stress was continuously intensified from mild emphysema to GOLD 4; thus, special attention should be paid to the identification of emphysema. Furthermore, the downregulated HIF3A may play an important role in the intensified oxidative stress in COPD.

Newborn DNA methylation and asthma acquisition across adolescence and early adulthood

BACKGROUND

Little is known about the association of newborn DNA methylation (DNAm) with asthma acquisition across adolescence and early adult life.

OBJECTIVE

We aim to identify epigenetic biomarkers in newborns for asthma acquisition during adolescence or young adulthood.

METHODS

The Isle of Wight Birth Cohort (IOWBC) (n = 1456) data at ages 10, 18 and 26 years were assessed. To screen cytosine-phosphate-guanine site (CpGs) potentially associated with asthma acquisition, at the genome scale, we examined differentially methylated regions (DMR) using dmrff R package and individual CpG sites using linear regression on such associations. For CpGs that passed screening, we examined their enrichment in biological pathways using their mapping genes and tested their associations with asthma acquisitions using logistic regressions. Findings in IOWBC were tested in an independent cohort, the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort.

RESULTS

In total, 2636 unique CpGs passed screening, based on which we identified one biological pathway linked to asthma acquisition during adolescence in females (FDR adjusted p-value = .003 in IOWBC). Via logistic regressions, for females, four CpGs were shown to be associated with asthma acquisition during adolescence, and another four CpGs with asthma acquisition in young adulthood (FDR adjusted p-value < .05 in IOWBC) and these eight CpGs were replicated in ALSPAC (all p-values < .05). DNAm at all the identified CpGs was shown to be temporally consistent, and at six of the CpGs was associated with expressions of adjacent or mapping genes in females (all p-values < .05). For males, 622 CpGs were identified in IOWBC (FDR = 0.01), but these were not tested in ALSPAC due to small sample sizes.

CONCLUSION AND CLINICAL RELEVANCE

Eight CpGs on LHX5, IL22RA2, SOX11, CBX4, ACPT, CFAP46, MUC4, and ATP1B2 genes have the potential to serve as candidate epigenetic biomarkers in newborns for asthma acquisition in females during adolescence or young adulthood.

COPD is Associated with Epigenome-wide Differential Methylation in BAL Lung Cells

DNA methylation patterns in chronic pulmonary obstructive disease (COPD) might offer new insights into disease pathogenesis. To assess methylation profiles in the main COPD target organ, we performed an epigenome-wide association study on bronchoalveolar lavage (BAL) cells. Bronchoscopies were performed in 18 COPD subjects and 15 controls (ex- and current smokers). DNA methylation was measured with Illumina MethylationEPIC BeadChip covering >850,000 CpGs. Differentially methylated positions (DMPs) were examined for 1) enrichment in pathways and functional gene relationships using Kyoto Encyclopedia of Genes and Genomes and Gene Ontology; 2) accelerated aging using Horvath's epigenetic clock; 3) correlation with gene expression; and 4) co-localization with genetic variation. We found 1,155 Bonferroni significant (P < 6.74 × 10^-8) DMPs associated with COPD, many with large effect sizes. Functional analysis identified biologically plausible pathways and gene relationships, including enrichment for transcription factor activity. Strong correlation was found between COPD and chronological age, but not with accelerated epigenetic aging. For 79 unique DMPs, DNA methylation correlated significantly with gene expression in BAL cells. Thirty-nine percent of DMPs were co-localized with COPD-associated SNPs. To the best of our knowledge, this is the first EWAS of COPD on BAL cells, and our analyses revealed many differential methylation sites. Integration with mRNA data showed a strong functional readout for relevant genes, identifying sites where DNA methylation might directly impact expression. Almost half of DMPs were co-located with SNPs identified in previous GWAS of COPD, suggesting joint genetic and epigenetic pathways related to disease.

Host Factor Interaction Networks Identified by Integrative Bioinformatics Analysis Reveals Therapeutic Implications in COPD Patients With COVID-19

Background: The COVID-19 pandemic poses an imminent threat to humanity, especially for those who have comorbidities. Evidence of COVID-19 and COPD comorbidities is accumulating. However, data revealing the molecular mechanism of COVID-19 and COPD comorbid diseases is limited. Methods: We got COVID-19/COPD -related genes from different databases by restricted screening conditions (top500), respectively, and then supplemented with COVID-19/COPD-associated genes (FDR<0.05, |LogFC|≥1) from clinical sample data sets. By taking the intersection, 42 co-morbid host factors for COVID-19 and COPD were finally obtained. On the basis of shared host factors, we conducted a series of bioinformatics analysis, including protein-protein interaction analysis, gene ontology and pathway enrichment analysis, transcription factor-gene interaction network analysis, gene-microRNA co-regulatory network analysis, tissue-specific enrichment analysis and candidate drug prediction. Results: We revealed the comorbidity mechanism of COVID-19 and COPD from the perspective of host factor interaction, obtained the top ten gene and 3 modules with different biological functions. Furthermore, we have obtained the signaling pathways and concluded that dexamethasone, estradiol, progesterone, and nitric oxide shows effective interventions. Conclusion: This study revealed host factor interaction networks for COVID-19 and COPD, which could confirm the potential drugs for treating the comorbidity, ultimately, enhancing the management of the respiratory disease.

Aberrant Methylation of Aging-Related Genes in Asthma

Background: Asthma is a complex pulmonary inflammatory disease which is common among older adults. Aging-related alterations have also been found in structural cells and immune cells of asthma patients. Nonetheless, the underlying mechanism by which differenced aging-related gene contributes to asthma pathology remains unclear. Of note, DNA methylation (DNAm) has been proven to play a critical mechanism for age-related gene expression changes. However, the methylation changes of aging-related genes in asthma patients are still obscure.

Methods: First, changes in DNAm and gene expression were detected with multiple targeted bisulfite enrichment sequencing (MethTarget) and qPCR in peripheral blood of 51 healthy controls (HCs) and 55 asthmatic patients. Second, the correlation between the DNAm levels of specific altered CpG sites and the pulmonary function indicators of asthma patients was evaluated. Last, the receiver operator characteristic (ROC) curve and principal component analysis (PCA) were used to identify the feasibility of the candidate CpG sites as biomarkers for asthma.

Results: Compared with HCs, there was a differential mRNA expression for nine aging-related genes in peripheral blood of asthma patients. Besides, the methylation levels of the nine aging-related genes were also altered in asthma patients, and a total of 68 CpG sites were associated with the severity of asthma. Notably, 9 of the 68 CpG sites were significantly associated with pulmonary function parameters. Moreover, ROC curve and PCA analysis showed that the candidate differential methylation sites (DMSs) can be used as potential biomarkers for asthma.

Conclusions: In summary, this study confirmed the differentially expressed mRNA and aberrant DNAm level of aging-related genes in asthma patients. DMSs are associated with the clinical evaluation indicators of asthma, which indicate the involvement of aging-related genes in the pathogenesis of asthma and provide some new possible biomarkers for asthma.

Identification of Inflammation-Related Biomarker Lp-PLA2 for Patients With COPD by Comprehensive Analysis

Purpose

Chronic obstructive pulmonary disease (COPD) is a complex and persistent lung disease and lack of biomarkers. The aim of this study is to screen and verify effective biomarkers for medical practice.

Methods

Differential expressed genes analysis and weighted co-expression network analysis were used to explore potential biomarker. Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene set enrichment analysis (GSEA) analysis were used to explore potential mechanism. CIBERSORTx website was used to evaluate tissue-infiltrating immune cells. Enzyme-linked immunosorbent assay (ELISA) was used to assess the concentrations of the Lp-PLA2 in serum.

Results

Ten genes were selected via combined DEGs and WGCNA. Furthermore, PLA2G7 was choose based on validation from independent datasets. Immune infiltrate and enrichment analysis suggest PLA2G7 may regulate immune pathway via macrophages. Next, Lp-PLA2(coded by PLA2G7 gene) level was upregulated in COPD patients, increased along with The Global Average of COPD (GOLD) stage. In additional, Lp-PLA2 level was significant correlate with FEV1/FVC, BMI, FFMI, CAT score, mMRC score and 6MWD of COPD patients. Finally, the predictive efficiency of Lp-PLA2 level (AUC:0.796) and derived nomogram model (AUC:0.884) in exercise tolerance was notably superior to that of the sit-to-stand test and traditional clinical features.

Conclusion

Lp-PLA2 is a promising biomarker for COPD patients and is suitable for assessing exercise tolerance in clinical practice.

Recent developments in PARP14 research

This review aims to reflect upon the major developments in PARP14 research from late 2017 to early 2020. In doing so, this report will focus on the continual elucidation of PARP14's function including an emerging role in viral replication. This is in addition to other functional developments in cancer and inflammation, along with reflecting upon the leads in inhibitor design, including the increased attention toward the macrodomain. This report will also include a brief recap on contemporary poly(ADP-ribose) polymerase inhibitors and reflect upon the development surrounding the other poly(ADP-ribose) polymerases to overall give a succinct update to assist the development of selective PARP14 inhibitors.

STRING data mining of GWAS data in canine hereditary pigment-associated deafness

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Genome-wide association studies may fail to identify significant associations between a disorder and causative genes in complex hereditary disorders.

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STRING software is a bioinformatics data mining tool that identifies known and predicted physical and functional relationship networks among the proteins of candidate genes.

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STRING analysis provides a mechanism to identify gene-gene interactions that might not otherwise have been recognized.

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Relationships identified from STRING analysis can uncover function-based gene-gene relationships that may not be easily extracted from literature, thereby providing genes for pursuit as a cause of a complex hereditary disorder.

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In this study STRING analysis was applied to identification of candidate genes to pursue as the cause of pigment-associated hereditary deafness in dogs.

Most canine deafness is linked to white pigmentation caused by the piebald locus, shown to be the gene MITF (melanocyte inducing transcription factor), but studies have failed to identify a deafness cause. The coding regions of MITF have not been shown to be mutated in deaf dogs, leading us to pursue genes acting on or controlled by MITF. We have genotyped DNA from 502 deaf and hearing Australian cattle dogs, Dalmatians, and English setters, breeds with a high deafness prevalence. Genome-wide significance was not attained in any of our analyses, but we did identify several suggestive associations. Genome-wide association studies (GWAS) in complex hereditary disorders frequently fail to identify causative gene variants, so advanced bioinformatics data mining techniques are needed to extract information to guide future studies.

STRING diagrams are graphical representations of known and predicted networks of protein-protein interactions, identifying documented relationships between gene proteins based on the scientific literature, to identify functional gene groupings to pursue for further scrutiny. The STRING program predicts associations at a preset confidence level and suggests biological functions based on the identified genes.

Starting with (1) genes within 500 kb of GWAS-suggested SNPs, (2) known pigmentation genes, (3) known human deafness genes, and (4) genes identified from proteomic analysis of the cochlea, we generated STRING diagrams that included these genes. We then reduced the number of genes by excluding genes with no relationship to auditory function, pigmentation, or relevant structures, and identified clusters of genes that warrant further investigation.

Identification of differentially expressed genes and enriched pathways in lung cancer using bioinformatics analysis

Lung cancer is the leading cause of cancer‑associated mortality worldwide. The aim of the present study was to identify the differentially expressed genes (DEGs) and enriched pathways in lung cancer by bioinformatics analysis, and to provide potential targets for diagnosis and treatment. Valid microarray data of 31 pairs of lung cancer tissues and matched normal samples (GSE19804) were obtained from the Gene Expression Omnibus database. Significance analysis of the gene expression profile was used to identify DEGs between cancer tissues and normal tissues, and a total of 1,970 DEGs, which were significantly enriched in biological processes, were screened. Through the Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, 77 KEGG pathways associated with lung cancer were identified, among which the Toll‑like receptor pathway was observed to be important. Protein‑protein interaction network analysis extracted 1,770 nodes and 10,667 edges, and identified 10 genes with key roles in lung cancer with highest degrees, hub centrality and betweenness. Additionally, the module analysis of protein‑protein interactions revealed that 'chemokine signaling pathway', 'cell cycle' and 'pathways in cancer' had a close association with lung cancer. In conclusion, the identified DEGs, particularly the hub genes, strengthen the understanding of the development and progression of lung cancer, and certain genes (including advanced glycosylation end‑product specific receptor and epidermal growth factor receptor) may be used as candidate target molecules to diagnose, monitor and treat lung cancer.