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      Chronic Obstructive Pulmonary Disease Molecular Subtyping and Pathway Deviation-Based Candidate Gene Identification

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          Abstract

          Objective

          The aim of this study was to identify the molecular subtypes of chronic obstructive pulmonary disease (COPD) and to prioritize COPD candidate genes using bioinformatics methods.

          Materials and Methods

          In this bioinformatics study, the gene expression dataset GSE76705 (including 229 COPD samples) and known COPD-related genes (candidate genes) were downloaded from the Gene Expression Omnibus (GEO) and the Online Mendelian Inheritance in Man (OMIM) databases respectively. Based on the expression values of the candidate genes, COPD samples were divided into molecular subtypes through hierarchical clustering analysis. Candidate genes were accordingly allocated into the defined molecular subtypes and functional enrichment analysis was undertaken. Pathway deviation scores were then analyzed, followed by the analysis of clinical indicators (FEV1, FEV1/FVC, age and gender) of COPD patients in each subtype, and prediction models were constructed. Furthermore, the gene expression dataset GSE71220 was used to bioinformatically validate our results.

          Results

          A total of 213 COPD-related genes were identified, which divided samples into three subtypes based on the gene expression values. After intersection analysis, 160 common genes including transforming growth factor β1 (TGFB1), epidermal growth factor receptor ( EGFR) and interleukin 13 (IL13) were obtained. Functional enrichment analysis identified 22 pathways such as ‘hsa04060: cytokine-cytokine receptor interaction pathways, ‘hsa04110: cell cycle’ and ‘hsa05222: small cell lung cancer’. Pathways in subtype 2 had higher deviation scores. Furthermore, three receiver operating characteristic (ROC) curves (accuracies >80%) were constructed. The three subtypes in COPD samples were also identified in the validation dataset GSE71220.

          Conclusion

          COPD may be further subdivided into several molecular subtypes, which may be useful in improving COPD therapy based on the molecular subtype of a patient.

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          Most cited references31

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          The natural history of chronic airflow obstruction.

          A prospective epidemiological study of the early stages of the development of chronic obstructive pulmonary disease was performed on London working men. The findings showed that forced expiratory volume in one second (FEV1) falls gradually over a lifetime, but in most non-smokers and many smokers clinically significant airflow obstruction never develops. In susceptible people, however, smoking causes irreversible obstructive changes. If a susceptible smoker stops smoking he will not recover his lung function, but the average further rates of loss of FEV1 will revert to normal. Therefore, severe or fatal obstructive lung disease could be prevented by screening smokers' lung function in early middle age if those with reduced function could be induced to stop smoking. Infective processes and chronic mucus hypersecretion do not cause chronic airflow obstruction to progress more rapidly. There are thus two largely unrelated disease processes, chronic airflow obstruction and the hypersecretory disorder (including infective processes).
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            The cytokine network in asthma and chronic obstructive pulmonary disease.

            Asthma and chronic obstructive pulmonary disease (COPD) are very common inflammatory diseases of the airways. They both cause airway narrowing and are increasing in incidence throughout the world, imposing enormous burdens on health care. Cytokines play a key role in orchestrating the chronic inflammation and structural changes of the respiratory tract in both asthma and COPD and have become important targets for the development of new therapeutic strategies in these diseases.
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              Reference spirometric values using techniques and equipment that meet ATS recommendations.

              Forced expiratory volumes and flows were measured in 251 healthy nonsmoking men and women using techniques and equipment that meet American Thoracic Society (ATS) recommendations. Linear regression equations using height and age alone predict spirometric parameters as well as more complex equations using additional variables. Single values for 95% confidence intervals are acceptable and should replace the commonly used method of subtracting 20% to determine the lower limit of normal for a predicted value. Our study produced predicted values for forced vital capacity and forced expiratory volume in one second that were almost identical to those predicted by Morris and associates (1) when the data from their study were modified to be compatible with the back extrapolation technique recommended by the ATS. The study of Morris and colleagues was performed at sea level in rural subjects, whereas ours was performed at an altitude of 1,400 m in urban subjects. Either the present study or the study of Morris and co-workers, modified to back extrapolation, could be recommended for predicting normal values.
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                Author and article information

                Journal
                Cell J
                Cell J
                Royan Institute
                Cell Journal (Yakhteh)
                Royan Institute
                2228-5806
                2228-5814
                Autumn 2018
                28 May 2018
                : 20
                : 3
                : 326-332
                Affiliations
                [1 ]Department of Respiratory Medicine, The Affiliated Hospital of Qingdao University, Qingdao, China
                [2 ]Department of Respiratory Medicine, People’s Hospital of RizhaoLanshan, Rizhao, China
                [3 ]Department of Pharmacy, Qilu Hospital of Shandong University (Qingdao), Qingdao, China
                [4 ]Department of President’s Office, The Affiliated Hospital of Qingdao University, Qingdao, China
                Author notes
                [*Corresponding Address: ]Department of President’s OfficeThe Affiliated Hospital of Qingdao University No. 16 Jiangsu RoadQingdao266003P.R. China Email: gaoyufang201508@ 123456hotmail.com
                Article
                Cell-J-20-326
                10.22074/cellj.2018.5412
                6004990
                29845785
                53b3ee43-cd3c-4320-acaa-288ab9b80faa
                Any use, distribution, reproduction or abstract of this publication in any medium, with the exception of commercial purposes, is permitted provided the original work is properly cited

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 21 July 2017
                : 27 September 2017
                Categories
                Original Article
                Genetics
                Respiratory Medicine
                Custom metadata
                Zhao J, Cheng W, He X, Liu Y, Li J, Sun J, Li J, Wang F, Gao Y. Chronic obstructive pulmonary disease molecular subtyping and pathway deviation-based candidate gene identification. Cell J. 2018; 20(3): 326-332. doi: 10.22074/cellj.2018.5412.

                chronic obstructive pulmonary disease,pathway,subtype

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