Association between single-nucleotide polymorphism of cytokines genes and chronic obstructive pulmonary disease: A systematic review and meta-analysis.

Chronic obstructive pulmonary disease (COPD) is a common chronic inflammatory disease with high morbidity and mortality rates worldwide. Cytokines, which are the main regulators of immune responses, play crucial roles in inflammatory diseases such as COPD. Moreover, certain genetic variations can alter cytokine expression, and changes in cytokine level or function can affect disease susceptibility. Therefore, investigating the association between genetic variations and disease progression can be useful for prevention and treatment. Several studies have explored the association between common genetic variations in cytokine genes and COPD susceptibility. In this study, we summarized the reported studies and, where possible, conducted a systematic review and meta-analysis to evaluate the genetic association between various cytokines and COPD pathogenesis. We extracted relevant articles from PubMed and Google Scholar databases using a standard systematic search strategy. We included a total of 183 studies from 78 separate articles that evaluated 50 polymorphisms in 12 cytokine genes in this study. Our analysis showed that among all reported cytokine polymorphisms (including TNF-α, TGF-ß, IL1, IL1RN, IL4, IL4R, IL6, IL10, IL12, IL13, IL17, IL18, IL27, and IL33), only four variants, including TNF-α-rs1800629, TGF-ß1-rs6957, IL13-rs1800925, and IL6-rs1800796, were associated with the risk of COPD development. This updated meta-analysis strongly supports the association of TNF-α-rs1800629, TGF-ß1-rs6957, IL13-rs1800925, and IL6-rs1800796 variants with a high risk of COPD.

PI3K signalling in chronic obstructive pulmonary disease and opportunities for therapy.

Chronic obstructive pulmonary disease (COPD) is a chronic lung disease characterised by airway inflammation and progressive obstruction of the lung airflow. Current pharmacological treatments include bronchodilators, alone or in combination with steroids, or other anti-inflammatory agents, which have only partially contributed to the inhibition of disease progression and mortality. Therefore, further research unravelling the underlying mechanisms is necessary to develop new anti-COPD drugs with both lower toxicity and higher efficacy. Extrinsic signalling pathways play crucial roles in COPD development and exacerbations. In particular, phosphoinositide 3-kinase (PI3K) signalling has recently been shown to be a major driver of the COPD phenotype. Therefore, several small-molecule inhibitors have been identified to block the hyperactivation of this signalling pathway in COPD patients, many of them showing promising outcomes in both preclinical animal models of COPD and human clinical trials. In this review, we discuss the critically important roles played by hyperactivated PI3K signalling in the pathogenesis of COPD. We also critically review current therapeutics based on PI3K inhibition, and provide suggestions focusing on PI3K signalling for the further improvement of the COPD phenotype. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Atopic dermatitis: molecular, cellular, and clinical aspects.

Atopic dermatitis (AD) is a complicated, inflammatory skin disease, which numerous genetic and environmental factors play roles in its development. AD is categorized into different phenotypes and stages, although they are mostly similar in their pathophysiological aspects. Immune response alterations and structural distortions of the skin-barrier layer are evident in AD patients. Genetic makeup, lifestyle, and environment are also significantly involved in contextual factors. Genes involved in AD-susceptibility, including filaggrin and natural moisturizing, cause considerable structural modifications in the skin's lipid bilayer and cornified envelope. Additionally, the skin's decreased integrity and altered structure are accompanied by biochemical changes in the normal skin microflora's dysbiosis. The dynamic immunological responses, genetic susceptibilities, and structural modifications associated with AD's pathophysiology will be extensively discussed in this review, each according to the latest achievements and findings.

Causal Path of COPD Progression-Associated Genes in Different Biological Samples.

Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory disease with pulmonary and extra-pulmonary complications. Due to the disease's systemic nature, many investigations investigated the genetic alterations in various biological samples. We aimed to infer causal genes in COPD's pathogenesis in different biological samples using elastic-net logistic regression and the Structural Equation Model. Samples of small airway epithelial cells, bronchoalveolar lavage macrophages, lung tissue biopsy, sputum, and blood samples were selected (135, 70, 235, 143, and 226 samples, respectively). Elastic-net Logistic Regression analysis was implemented to identify the most important genes involved in COPD progression. Thirty-three candidate genes were identified as essential factors in the pathogenesis of COPD and regulation of lung function. Recognized candidate genes in small airway epithelial (SAE) cells have the highest area under the ROC curve (AUC = 97%, SD = 3.9%). Our analysis indicates that macrophages and epithelial cells are more influential in COPD progression at the transcriptome level.

The composition of lung microbiome in lung cancer: a systematic review and meta-analysis.

BACKGROUND: Although recent studies have indicated that imbalance in the respiratory microbiome composition is linked to several chronic respiratory diseases, the association between the lung microbiome and lung cancer has not been extensively studied. Conflicting reports of individual studies on respiratory microbiome alterations in lung cancer complicate the matter for specifying how the lung microbiome is linked to lung cancer. Consequently, as the first meta-analysis on this topic, we integrate publicly available 16S rRNA gene sequence data on lung tissue samples of lung cancer patients to identify bacterial taxa which differ consistently between case and control groups. RESULTS: The findings of the current study suggest that the relative abundance of several bacterial taxa including Actinobacteria phylum, Corynebacteriaceae and Halomonadaceae families, and Corynebacterium, Lachnoanaerobaculum, and Halomonas genera is significantly decreased (p < 0.05) in lung tumor tissues of lung cancer patients in comparison with tumor-adjacent normal tissues. CONCLUSIONS: Despite the underlying need for scrutinizing the findings further, the present study lays the groundwork for future research and adds to our limited understanding of the key role of the lung microbiome and its complex interaction with lung cancer. More data on demographic factors and tumor tissue types would help establish a greater degree of accuracy in characterizing the lung microbial community which accords with subtypes and stages of the disease and fully capturing the changes of the lung microbiome in lung cancer.

A multimodal deep learning-based drug repurposing approach for treatment of COVID-19.

Recently, various computational methods have been proposed to find new therapeutic applications of the existing drugs. The Multimodal Restricted Boltzmann Machine approach (MM-RBM), which has the capability to connect the information about the multiple modalities, can be applied to the problem of drug repurposing. The present study utilized MM-RBM to combine two types of data, including the chemical structures data of small molecules and differentially expressed genes as well as small molecules perturbations. In the proposed method, two separate RBMs were applied to find out the features and the specific probability distribution of each datum (modality). Besides, RBM was used to integrate the discovered features, resulting in the identification of the probability distribution of the combined data. The results demonstrated the significance of the clusters acquired by our model. These clusters were used to discover the medicines which were remarkably similar to the proposed medications to treat COVID-19. Moreover, the chemical structures of some small molecules as well as dysregulated genes' effect led us to suggest using these molecules to treat COVID-19. The results also showed that the proposed method might prove useful in detecting the highly promising remedies for COVID-19 with minimum side effects. All the source codes are accessible using https://github.com/LBBSoft/Multimodal-Drug-Repurposing.git.

Laboratory methods to decipher epigenetic signatures: a comparative review.

Epigenetics refers to nucleotide sequence-independent events, and heritable changes, including DNA methylation and histone modification (as the two main processes), contributing to the phenotypic features of the cell. Both genetics and epigenetics contribute to determining the outcome of regulatory gene expression systems. Indeed, the flexibility of epigenetic effects and stability of genetic coding lead to gene regulation complexity in response signals. Since some epigenetic changes are significant in abnormalities such as cancers and neurodegenerative diseases, the initial changes, dynamic and reversible properties, and diagnostic potential of epigenomic phenomena are subject to epigenome-wide association studies (EWAS) for therapeutic aims. Based on recent studies, methodological developments are necessary to improve epigenetic research. As a result, several methods have been developed to explore epigenetic alterations at low, medium, and high scales, focusing on DNA methylation and histone modification detection. In this research field, bisulfite-, enzyme sensitivity- and antibody specificity-based techniques are used for DNA methylation, whereas histone modifications are gained based on antibody recognition. This review provides a mechanism-based understanding and comparative overview of the most common techniques for detecting the status of epigenetic effects, including DNA methylation and histone modifications, for applicable approaches from low- to high-throughput scales.

An efficient hybrid feature selection method to identify potential biomarkers in common chronic lung inflammatory diseases.

Asthma, chronic obstructive pulmonary disease (COPD), and idiopathic pulmonary fibrosis (IPF) are three serious lung inflammatory diseases. The understanding of the pathogenesis mechanism and the identification of potential prognostic biomarkers of these diseases can provide the patients with more efficient treatments. In this study, an efficient hybrid feature selection method was introduced in order to extract informative genes. We implemented an ontology-based ranking approach on differentially expressed genes following a wrapper method. The examination of the different gene ontologies and their combinations motivated us to propose a biological functional-based method to improve the performance of further wrapper methods. The results identified: TOM1L1, SRSF1, and GIT2 in asthma; CHCHD4, PAIP2, CRLF3, UBQLN4, TRAK1, PRELID1, VAMP4, CCM2, and APBB1IP in COPD; and TUFT1, GAB2, B4GALNT1, TNFRSF17, PRDM8, and SETDB2 in IPF as the potential biomarkers. The proposed method can be used to identify hub genes in other high-throughput datasets.

Identification of biomarkers in common chronic lung diseases by co-expression networks and drug-target interactions analysis.

BACKGROUND: asthma, chronic obstructive pulmonary disease (COPD), and idiopathic pulmonary fibrosis (IPF) are three serious pulmonary diseases that contain common and unique characteristics. Therefore, the identification of biomarkers that differentiate these diseases is of importance for preventing misdiagnosis. In this regard, the present study aimed to identify the disorders at the early stages, based on lung transcriptomics data and drug-target interactions. METHODS: To this end, the differentially expressed genes were found in each disease. Then, WGCNA was utilized to find specific and consensus gene modules among the three diseases. Finally, the disease-disease similarity was analyzed, followed by determining candidate drug-target interactions. RESULTS: The results confirmed that the asthma lung transcriptome was more similar to COPD than IPF. In addition, the biomarkers were found in each disease and thus were proposed for further clinical validations. These genes included RBM42, STX5, and TRIM41 in asthma, CYP27A1, GM2A, LGALS9, SPI1, and NLRC4 in COPD, ATF3, PPP1R15A, ZFP36, SOCS3, NAMPT, and GADD45B in IPF, LRRC48 and CETN2 in asthma-COPD, COL15A1, GIMAP6, and JAM2 in asthma-IPF and LMO7, TSPAN13, LAMA3, and ANXA3 in COPD-IPF. Finally, analyzing drug-target networks suggested anti-inflammatory candidate drugs for treating the above mentioned diseases. CONCLUSION: In general, the results revealed the unique and common biomarkers among three chronic lung diseases. Eventually, some drugs were suggested for treatment purposes.

Bacterial infections in acute exacerbation of chronic obstructive pulmonary disease: a systematic review and meta-analysis.

OBJECTIVE: Due to the importance of Chronic obstructive pulmonary disease (COPD) as the fourth cause of mortality worldwide and the lack of studies evaluating the prevalence of bacterial infections in disease exacerbation, this systematic review and meta-analysis was performed to determine the prevalence rate of bacterial infections in COPD patients. METHODS: PubMed, ISI Web of Science, and Scopus databases were systematically searched for population-based prevalence studies (1980-2018). MeSH terms for "Bacterial infections" and "AECOPD" were used as search keywords. The selected studies were filtered according to the inclusion and exclusion criteria. Fixed and random-effects models were used for estimation of summary effect sizes. Between-study heterogeneity, as well as publication bias, were calculated. RESULTS: Finally, 118 out of 31,440 studies were selected. The overall estimation of the prevalence of bacterial infection was 49.59% [95% confidence interval (CI) 0.4418-0.55]. The heterogeneity in estimating the pooled prevalence of bacterial infections was shown in the studies (Cochran Q test: 6615, P < 0.0001, I2 = 98.23%). In addition, S. pneumoniae, H. influenzae, M. catarrhalis, A. baumannii, P. aeruginosa, and S. aureus were the most prevalent reported bacteria. CONCLUSIONS: Our results as the first meta-analysis for the issue demonstrated that bacterial infections are an important risk factor for AECOPD. Further studies must be performed for understanding the exact role of bacterial agents in AECOPD and help physicians for more applicable preventive and therapeutic measurements.

Association between chronic obstructive pulmonary disease and interleukins gene variants: A systematic review and meta-analysis.

Interleukins are cytokines involved in systemic inflammation and immune system regulation. Many studies have investigated the association between common genetic variations in interleukin-coding genes and COPD susceptibility. In this study, a systematic review and meta-analysis was performed to evaluate the association between interleukin gene variations and COPD pathogenesis. Association studies were retrieved from PubMed and Google Scholar databases using the standard systematic search strategy. A total of 26 different studies evaluating eight polymorphisms in four interleukin genes were included in this study. In overall comparisons, IL1ß-rs16944, -rs1143627, -rs1143634, IL13-rs20541 polymorphisms were found not to be associated with the increased risk for developing COPD. However, IL1RN-rs2234663 and IL13-rs1800925 showed a strong association with COPD. We showed that the CC genotype carriers of the IL6-rs1800795 are at significantly higher risk of developing COPD (OR = 1.31, 95% CI: 1.04-1.64, P = 0.01) compared to GG carriers. In case of IL6-rs1800796, individuals with CC and CG genotypes showed a lower risk to develop COPD (OR = 0.46, 95%CI: 0.32-0.66, P > 0.00). This updated meta-analysis strongly supports the association of IL1RN-rs2234663, IL6-rs1800795, -rs1800795 and IL13-rs1800925 variants with COPD.

TNF-α -308 G/A variant and susceptibility to chronic obstructive pulmonary disease: A systematic review and meta-analysis.

BACKGROUND AND OBJECTIVE: TNF-α -308 G/A variant is recognized to play an important role in the pathogenesis of chronic obstructive pulmonary disease (COPD). Although many studies have investigated the association of TNF-α-308 and COPD risk, a deep understanding of this association is lacking due to small subjects sizes and insufficiently study designs among different investigations. In this study, a systematic review and meta-analysis was performed based on published reports on the association of TNF-α and COPD. METHOD: The published studies concerned the association between TNF-α and COPD were identified using a systematic research in Scopus, Google Scholar, and PubMed up to April 2018. A total of 46 different papers studying the rs1800629 variant in TNF-α gene were included. Then, human studies were selected to further analysis regardless of papers language. RESULTS: Based on the results, the major outcome of this meta-analysis can be represented as follows: individuals with GG and GA genotypes possess less risk of developing COPD (OR = 0.58, 95%CI: (0.44-0.79), P < 0.00) compared to AA genotype carriers. In contrast, the AA genotype carriers of the TNF-α rs1800629 has a significantly higher risk of developing COPD (OR = 1.83, 95%CI: (1.34-2.51), P < 0.00) compared to GG carrier. Despite the previous meta-analysis results which reported significantly decreasing of heterogeneity with ethnicity, we found that the source of controls has a significant contribution to observed heterogeneity. CONCLUSIONS: Thanks to the global burden of COPD studies, proving TNF-α 308 gene variant as an independent factor in its pathogenesis opens new insights to diagnosis and management of COPD.

Human endogenous retrovirus env genes: Potential blood biomarkers in lung cancer.

Lung cancer, the leading cause of cancer mortality, needs urgent development of newly qualified diagnostic and therapeutic biomarkers. Recently, Human Endogenous Retroviruses (HERVs) have been introduced for cancer diagnosis. In this case-control study, we have collected blood samples from 60 lung cancer patients and 20 healthy controls. Quantitative gene expression analysis of various HERV env genes, including HERV-R, HERV-H, HERV-K, and HERV-P was performed by real-time PCR. Results indicate that expression of all four HERV env mRNAs is significantly increased in the blood of lung cancer patients than healthy controls (P-values<0.01). Furthermore, we have observed a positive and significant pairwise correlation between the expressions of four HERV env genes. The level of HERV env transcript in the blood of adenocarcinoma patients was generally much higher than squamous cell carcinoma (SCC) and small-cell lung cancer (SCLC) patients. Also, the expression of three HERV P, HERV H, and HERV K in the blood of lung cancer patients could significantly differentiate between adenocarcinoma and other types of lung cancer. In conclusion, these four HERV families could be considered as promising non-invasive blood-based biomarkers for prognosis, early detection, and monitoring of lung cancer.

Worldwide prevalence of viral infection in AECOPD patients: A meta-analysis.

BACKGROUND AND OBJECTIVE: Chronic obstructive pulmonary disease (COPD) is a chronic progressive lung disease. On the other hand, viral infections of the airway are associated with the acute exacerbations of COPD. A systematic review and meta-analysis were performed to determine the prevalence rate of viral infections in acute exacerbations of COPD patients. METHODS: PubMed database was systematically searched for population-based prevalence studies (1930-2017). Fixed and random effects models were used for estimation of summary effect-sizes. Between-study heterogeneity and publication bias were also calculated. "Viral infections" and "COPD patients with exacerbations" were the two critical inclusion criteria. RESULTS: Twenty-eight studies were selected out of 26078 articles for the present review. The overall estimation of the prevalence of viral infection was 0.374 (95% C.I: 0.359-0.388). Also, the evident heterogeneity of viral infection was observed among the studies (Cochran Q test, p value < 0.001 and I-squared = 97.5%). The highest and lowest prevalence rate was related to rhinovirus and echovirus, respectively. Also, the results of this study showed that the prevalence of viral infection in exacerbated COPD patients has fluctuation during the years with a slight increase and decrease. CONCLUSIONS: The results of this systematic review demonstrated that respiratory viral infections have an important role in the acute exacerbation of COPD (AECOPD). In addition, determining the exact geographic epidemiology of these viruses is very important to manage the treatment of these infections.

Cellular and molecular mechanisms of acute exposure to sulfur mustard: a systematic review.

CONTEXT: Mustard gas (e.g. sulfur mustard (SM)) has been used as a chemical agent in several battles and is still a potential worldwide menace. Besides local absorption, particularly in the skin, eyes and lungs, systemic spread of the agent also has detrimental effects on gonads, bone marrow and nervous system. Moreover, chronic exposure of SM to respiratory system causes death. Inducing oxidative stress, and disturbing DNA and tissue repair systems, inflammation and cell death signaling pathways have been introduced as molecular mechanisms of the injury. METHODS: In this systematic review, more than 1200 (2000-2014) articles focusing on gross or molecular pathological reports in the acute phase of the respiratory injury after SM exposure were reviewed, followed by two different layers of gross and molecular pathological data (clinic and laboratory) integrated together in a spatio-temporal order. Role of epithelial, neutrophil and macrophage cells and three signaling pathways of inflammation, oxidative stress and cell death are covered in details. RESULTS AND CONCLUSION: Our results propose a critical role of interleukin-17 producing cells in acute and chronic inflammatory responses.

Signaling network of lipids as a comprehensive scaffold for omics data integration in sputum of COPD patients.

Chronic obstructive pulmonary disease (COPD) is a heterogeneous and progressive inflammatory condition that has been linked to the dysregulation of many metabolic pathways including lipid biosynthesis. How lipid metabolism could affect disease progression in smokers with COPD remains unclear. We cross-examined the transcriptomics, proteomics, metabolomics, and phenomics data available on the public domain to elucidate the mechanisms by which lipid metabolism is perturbed in COPD. We reconstructed a sputum lipid COPD (SpLiCO) signaling network utilizing active/inactive, and functional/dysfunctional lipid-mediated signaling pathways to explore how lipid-metabolism could promote COPD pathogenesis in smokers. SpLiCO was further utilized to investigate signal amplifiers, distributers, propagators, feed-forward and/or -back loops that link COPD disease severity and hypoxia to disruption in the metabolism of sphingolipids, fatty acids and energy. Also, hypergraph analysis and calculations for dependency of molecules identified several important nodes in the network with modular regulatory and signal distribution activities. Our systems-based analyses indicate that arachidonic acid is a critical and early signal distributer that is upregulated by the sphingolipid signaling pathway in COPD, while hypoxia plays a critical role in the elevated dependency to glucose as a major energy source. Integration of SpLiCo and clinical data shows a strong association between hypoxia and the upregulation of sphingolipids in smokers with emphysema, vascular disease, hypertension and those with increased risk of lung cancer.

Human RNAi pathway: crosstalk with organelles and cells.

Understanding gene regulation mechanisms has been a serious challenge in biology. As a novel mechanism, small non-coding RNAs are an alternative means of gene regulation in a specific and efficient manner. There are growing reports on regulatory roles of these RNAs including transcriptional gene silencing/activation and post-transcriptional gene silencing events. Also, there are several known small non-coding RNAs which all work through RNA interference pathway. Interestingly, these small RNAs are secreted from cells toward targeted cells presenting new communication approach in cell-cell or cell-organ signal transduction. In fact, understanding cellular and molecular basis of these pathways will strongly improve developing targeted therapies and potent and specific regulatory tools. This study will review some of the most recent findings in this subject and will introduce a super-pathway RNA interference-based small RNA silencing network.

HomoTarget: a new algorithm for prediction of microRNA targets in Homo sapiens.

MiRNAs play an essential role in the networks of gene regulation by inhibiting the translation of target mRNAs. Several computational approaches have been proposed for the prediction of miRNA target-genes. Reports reveal a large fraction of under-predicted or falsely predicted target genes. Thus, there is an imperative need to develop a computational method by which the target mRNAs of existing miRNAs can be correctly identified. In this study, combined pattern recognition neural network (PRNN) and principle component analysis (PCA) architecture has been proposed in order to model the complicated relationship between miRNAs and their target mRNAs in humans. The results of several types of intelligent classifiers and our proposed model were compared, showing that our algorithm outperformed them with higher sensitivity and specificity. Using the recent release of the mirBase database to find potential targets of miRNAs, this model incorporated twelve structural, thermodynamic and positional features of miRNA:mRNA binding sites to select target candidates.

Atopic dermatitis-associated protein interaction network lead to new insights in chronic sulfur mustard skin lesion mechanisms.

Chronic sulfur mustard skin lesions (CSMSLs) are the most common complications of sulfur mustard exposure; however, its mechanism is not completely understood.According to clinical signs, there are similarities between CSMSL and atopic dermatitis (AD). In this study, proteomic results of AD were reviewed and the AD-associated protein-protein interaction network (PIN) was analyzed. According to centrality measurements, 16 proteins were designated as pivotal elements in AD mechanisms. Interestingly, most of these proteins had been reported in some sulfur mustard-related studies in late and acute phases separately. Based on the gene enrichment analysis, aging, cell response to stress, cancer, Toll- and NOD-like receptor and apoptosis signaling pathways have the greatest impact on the disease. By the analysis of directed protein interaction networks, it is concluded that TNF, IL-6, AKT1, NOS3 and CDKN1A are the most important proteins. It is possible that these proteins play role in the shared complications of AD and CSMSL including xerosis and itching.

cAMP-PDE signaling in COPD: Review of cellular, molecular and clinical features.

Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death among non-contagious diseases in the world. PDE inhibitors are among current medicines prescribed for COPD treatment of which, PDE-4 family is the predominant PDE isoform involved in hydrolyzing cyclic adenosine monophosphate (cAMP) that regulates the inflammatory responses in neutrophils, lymphocytes, macrophages and epithelial cells The aim of this study is to investigate the cellular and molecular mechanisms of cAMP-PDE signaling, as an important pathway in the treatment management of patients with COPD. In this review, a comprehensive literature review was performed about the effect of PDEs in COPD. Generally, PDEs are overexpressed in COPD patients, resulting in cAMP inactivation and decreased cAMP hydrolysis from AMP. At normal amounts, cAMP is one of the essential agents in regulating metabolism and suppressing inflammatory responses. Low amount of cAMP lead to activation of downstream inflammatory signaling pathways. PDE4 and PDE7 mRNA transcript levels were not altered in polymorphonuclear leukocytes and CD8 lymphocytes originating from the peripheral venous blood of stable COPD subjects compared to healthy controls. Therefore, cAMP-PDE signaling pathway is one of the most important signaling pathways involved in COPD. By examining the effects of different drugs in this signaling pathway critical steps can be taken in the treatment of this disease.