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      International Journal of COPD (submit here)

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      The Distribution of Alpha-1 Antitrypsin Genotypes Between Patients with COPD/Emphysema, Asthma and Bronchiectasis

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          Abstract

          Purpose

          Alpha-1-antitrypsin deficiency (AATD) is a rare hereditary condition characterized by low circulating levels of alpha-1antitrypsin (AAT). While the association between AATD and COPD/emphysema is undisputed, the association between AATD and asthma or bronchiectasis is still a matter of debate.

          Aims and Objectives

          Our study aimed to investigate the distribution of AAT genotypes between patients with COPD/emphysema, asthma and bronchiectasis. To back up the diagnostic labels, we described symptoms associated with the diagnosis.

          Methods

          Between September 2003 and March 2020, 29,465 testing kits (AlphaKit®) were analyzed in the AAT laboratory, University of Marburg, Germany. The diagnosis of AATD has been made based on the measurements of AAT serum levels, followed by genotyping, phenotyping or whole gene sequencing depending on the availability and/or the need for more detailed interpretation of the results. The respiratory symptoms were recorded as well.

          Results

          Regarding the distribution of the wild type allele M and the most frequent mutations S (E264V) and Z (E342K), no significant differences could be found between COPD/emphysema [Pi*MM (58.24%); Pi*SZ (2.49%); Pi*ZZ (9.12%)] and bronchiectasis [Pi*MM (59.30%) Pi*SZ (2.81%); Pi*ZZ (7.02%)]. When COPD/emphysema and bronchiectasis were recorded in the same patient, the rate of Pi* ZZ (14.78%) mutations was even higher. Asthma patients exhibited significantly less deficient genotypes [Pi*MM (54.81%); Pi*SZ (2%); Pi*ZZ (2.77%)] than two other groups. Associated respiratory symptoms confirmed the diagnosis.

          Conclusion

          COPD/emphysema and bronchiectasis, but not asthma patients, exhibit higher frequency of AATD genotypes. Our data suggest that AATD testing should be offered to patients with COPD/emphysema and bronchiectasis.

          Most cited references36

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          Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Lung Disease 2017 Report. GOLD Executive Summary

          American Journal of Respiratory and Critical Care Medicine, 195(5), 557-582
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            Immunology of asthma and chronic obstructive pulmonary disease.

            Asthma and chronic obstructive pulmonary disease (COPD) are both obstructive airway diseases that involve chronic inflammation of the respiratory tract, but the type of inflammation is markedly different between these diseases, with different patterns of inflammatory cells and mediators being involved. As described in this Review, these inflammatory profiles are largely determined by the involvement of different immune cells, which orchestrate the recruitment and activation of inflammatory cells that drive the distinct patterns of structural changes in these diseases. However, it is now becoming clear that the distinction between these diseases becomes blurred in patients with severe asthma, in asthmatic subjects who smoke and during acute exacerbations. This has important implications for the development of new therapies.
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              BioVenn – a web application for the comparison and visualization of biological lists using area-proportional Venn diagrams

              Background In many genomics projects, numerous lists containing biological identifiers are produced. Often it is useful to see the overlap between different lists, enabling researchers to quickly observe similarities and differences between the data sets they are analyzing. One of the most popular methods to visualize the overlap and differences between data sets is the Venn diagram: a diagram consisting of two or more circles in which each circle corresponds to a data set, and the overlap between the circles corresponds to the overlap between the data sets. Venn diagrams are especially useful when they are 'area-proportional' i.e. the sizes of the circles and the overlaps correspond to the sizes of the data sets. Currently there are no programs available that can create area-proportional Venn diagrams connected to a wide range of biological databases. Results We designed a web application named BioVenn to summarize the overlap between two or three lists of identifiers, using area-proportional Venn diagrams. The user only needs to input these lists of identifiers in the textboxes and push the submit button. Parameters like colors and text size can be adjusted easily through the web interface. The position of the text can be adjusted by 'drag-and-drop' principle. The output Venn diagram can be shown as an SVG or PNG image embedded in the web application, or as a standalone SVG or PNG image. The latter option is useful for batch queries. Besides the Venn diagram, BioVenn outputs lists of identifiers for each of the resulting subsets. If an identifier is recognized as belonging to one of the supported biological databases, the output is linked to that database. Finally, BioVenn can map Affymetrix and EntrezGene identifiers to Ensembl genes. Conclusion BioVenn is an easy-to-use web application to generate area-proportional Venn diagrams from lists of biological identifiers. It supports a wide range of identifiers from the most used biological databases currently available. Its implementation on the World Wide Web makes it available for use on any computer with internet connection, independent of operating system and without the need to install programs locally. BioVenn is freely accessible at .
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                Author and article information

                Journal
                Int J Chron Obstruct Pulmon Dis
                Int J Chron Obstruct Pulmon Dis
                copd
                copd
                International Journal of Chronic Obstructive Pulmonary Disease
                Dove
                1176-9106
                1178-2005
                06 November 2020
                2020
                : 15
                : 2827-2836
                Affiliations
                [1 ]Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Member of the German Center for Lung Research , Marburg, Germany
                [2 ]Clinic for Pneumology, German Center for Lung Research (DZL), Medical University Hannover , Hannover, Germany
                [3 ]Department of Internal Medicine V, Pulmonology, Allergology, Respiratory and Intensive Care Medicine, Saarland Hospital , Homburg/Saar, Germany
                [4 ]Institute for Pulmonary Rehabilitation Research, Schoen Klinik Berchtesgadener Land, Teaching Hospital of Philipps-University of Marburg , Marburg, Germany
                Author notes
                Correspondence: Martina Veith Department of Medicine, Pulmonary and Critical Care Medicine, University Medical Center Giessen and Marburg, Member of the German Center for Lung Research , Marburg, GermanyTel +4964215864723Fax +496421586370 Email veithm@staff.uni-marburg.de
                Author information
                http://orcid.org/0000-0001-8160-0056
                http://orcid.org/0000-0003-3228-8021
                http://orcid.org/0000-0002-5884-3006
                Article
                271810
                10.2147/COPD.S271810
                7654539
                33192056
                e838371e-ee1c-44a9-b5ab-0840dede2389
                © 2020 Veith et al.

                This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

                History
                : 11 July 2020
                : 14 October 2020
                Page count
                Figures: 5, Tables: 4, References: 36, Pages: 10
                Categories
                Original Research

                Respiratory medicine
                serpina1,alpha-1-antitrypsin deficiency,bronchiectasis,asthma,diagnosis
                Respiratory medicine
                serpina1, alpha-1-antitrypsin deficiency, bronchiectasis, asthma, diagnosis

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