Large‐scale plasma proteomics can reveal distinct endotypes in chronic obstructive pulmonary disease and severe asthma
Background Chronic airway diseases including chronic obstructive pulmonary disease (COPD) and asthma are heterogenous in nature and endotypes within are underpinned by complex biology. This study aimed to investigate the utility of proteomic profiling of plasma combined with bioinformatic mining, an...
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Published in | Clinical and translational allergy Vol. 11; no. 10; pp. e12091 - n/a |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
John Wiley & Sons, Inc
01.12.2021
John Wiley and Sons Inc Wiley |
Subjects | |
Online Access | Get full text |
ISSN | 2045-7022 2045-7022 |
DOI | 10.1002/clt2.12091 |
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Abstract | Background
Chronic airway diseases including chronic obstructive pulmonary disease (COPD) and asthma are heterogenous in nature and endotypes within are underpinned by complex biology. This study aimed to investigate the utility of proteomic profiling of plasma combined with bioinformatic mining, and to define molecular endotypes and expand our knowledge of the underlying biology in chronic respiratory diseases.
Methods
The plasma proteome was evaluated using an aptamer‐based affinity proteomics platform (SOMAscan®), representing 1238 proteins in 34 subjects with stable COPD and 51 subjects with stable but severe asthma. For each disease, we evaluated a range of clinical/demographic characteristics including bronchodilator reversibility, blood eosinophilia levels, and smoking history. We applied modified bioinformatic approaches used in the evaluation of RNA transcriptomics.
Results
Subjects with COPD and severe asthma were distinguished from each other by 365 different protein abundancies, with differential pathway networks and upstream modulators. Furthermore, molecular endotypes within each disease could be defined. The protein groups that defined these endotypes had both known and novel biology including groups significantly enriched in exosomal markers derived from immune/inflammatory cells. Finally, we observed associations to clinical characteristics that previously have been under‐explored.
Conclusion
This investigational study evaluating the plasma proteome in clinically‐phenotyped subjects with chronic airway diseases provides support that such a method can be used to define molecular endotypes and pathobiological mechanisms that underpins these endotypes. It provided new concepts about the complexity of molecular pathways that define these diseases. In the longer term, such information will help to refine treatment options for defined groups. |
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AbstractList | Chronic airway diseases including chronic obstructive pulmonary disease (COPD) and asthma are heterogenous in nature and endotypes within are underpinned by complex biology. This study aimed to investigate the utility of proteomic profiling of plasma combined with bioinformatic mining, and to define molecular endotypes and expand our knowledge of the underlying biology in chronic respiratory diseases.BACKGROUNDChronic airway diseases including chronic obstructive pulmonary disease (COPD) and asthma are heterogenous in nature and endotypes within are underpinned by complex biology. This study aimed to investigate the utility of proteomic profiling of plasma combined with bioinformatic mining, and to define molecular endotypes and expand our knowledge of the underlying biology in chronic respiratory diseases.The plasma proteome was evaluated using an aptamer-based affinity proteomics platform (SOMAscan®), representing 1238 proteins in 34 subjects with stable COPD and 51 subjects with stable but severe asthma. For each disease, we evaluated a range of clinical/demographic characteristics including bronchodilator reversibility, blood eosinophilia levels, and smoking history. We applied modified bioinformatic approaches used in the evaluation of RNA transcriptomics.METHODSThe plasma proteome was evaluated using an aptamer-based affinity proteomics platform (SOMAscan®), representing 1238 proteins in 34 subjects with stable COPD and 51 subjects with stable but severe asthma. For each disease, we evaluated a range of clinical/demographic characteristics including bronchodilator reversibility, blood eosinophilia levels, and smoking history. We applied modified bioinformatic approaches used in the evaluation of RNA transcriptomics.Subjects with COPD and severe asthma were distinguished from each other by 365 different protein abundancies, with differential pathway networks and upstream modulators. Furthermore, molecular endotypes within each disease could be defined. The protein groups that defined these endotypes had both known and novel biology including groups significantly enriched in exosomal markers derived from immune/inflammatory cells. Finally, we observed associations to clinical characteristics that previously have been under-explored.RESULTSSubjects with COPD and severe asthma were distinguished from each other by 365 different protein abundancies, with differential pathway networks and upstream modulators. Furthermore, molecular endotypes within each disease could be defined. The protein groups that defined these endotypes had both known and novel biology including groups significantly enriched in exosomal markers derived from immune/inflammatory cells. Finally, we observed associations to clinical characteristics that previously have been under-explored.This investigational study evaluating the plasma proteome in clinically-phenotyped subjects with chronic airway diseases provides support that such a method can be used to define molecular endotypes and pathobiological mechanisms that underpins these endotypes. It provided new concepts about the complexity of molecular pathways that define these diseases. In the longer term, such information will help to refine treatment options for defined groups.CONCLUSIONThis investigational study evaluating the plasma proteome in clinically-phenotyped subjects with chronic airway diseases provides support that such a method can be used to define molecular endotypes and pathobiological mechanisms that underpins these endotypes. It provided new concepts about the complexity of molecular pathways that define these diseases. In the longer term, such information will help to refine treatment options for defined groups. BackgroundChronic airway diseases including chronic obstructive pulmonary disease (COPD) and asthma are heterogenous in nature and endotypes within are underpinned by complex biology. This study aimed to investigate the utility of proteomic profiling of plasma combined with bioinformatic mining, and to define molecular endotypes and expand our knowledge of the underlying biology in chronic respiratory diseases.MethodsThe plasma proteome was evaluated using an aptamer‐based affinity proteomics platform (SOMAscan®), representing 1238 proteins in 34 subjects with stable COPD and 51 subjects with stable but severe asthma. For each disease, we evaluated a range of clinical/demographic characteristics including bronchodilator reversibility, blood eosinophilia levels, and smoking history. We applied modified bioinformatic approaches used in the evaluation of RNA transcriptomics.ResultsSubjects with COPD and severe asthma were distinguished from each other by 365 different protein abundancies, with differential pathway networks and upstream modulators. Furthermore, molecular endotypes within each disease could be defined. The protein groups that defined these endotypes had both known and novel biology including groups significantly enriched in exosomal markers derived from immune/inflammatory cells. Finally, we observed associations to clinical characteristics that previously have been under‐explored.ConclusionThis investigational study evaluating the plasma proteome in clinically‐phenotyped subjects with chronic airway diseases provides support that such a method can be used to define molecular endotypes and pathobiological mechanisms that underpins these endotypes. It provided new concepts about the complexity of molecular pathways that define these diseases. In the longer term, such information will help to refine treatment options for defined groups. Background Chronic airway diseases including chronic obstructive pulmonary disease (COPD) and asthma are heterogenous in nature and endotypes within are underpinned by complex biology. This study aimed to investigate the utility of proteomic profiling of plasma combined with bioinformatic mining, and to define molecular endotypes and expand our knowledge of the underlying biology in chronic respiratory diseases. Methods The plasma proteome was evaluated using an aptamer‐based affinity proteomics platform (SOMAscan®), representing 1238 proteins in 34 subjects with stable COPD and 51 subjects with stable but severe asthma. For each disease, we evaluated a range of clinical/demographic characteristics including bronchodilator reversibility, blood eosinophilia levels, and smoking history. We applied modified bioinformatic approaches used in the evaluation of RNA transcriptomics. Results Subjects with COPD and severe asthma were distinguished from each other by 365 different protein abundancies, with differential pathway networks and upstream modulators. Furthermore, molecular endotypes within each disease could be defined. The protein groups that defined these endotypes had both known and novel biology including groups significantly enriched in exosomal markers derived from immune/inflammatory cells. Finally, we observed associations to clinical characteristics that previously have been under‐explored. Conclusion This investigational study evaluating the plasma proteome in clinically‐phenotyped subjects with chronic airway diseases provides support that such a method can be used to define molecular endotypes and pathobiological mechanisms that underpins these endotypes. It provided new concepts about the complexity of molecular pathways that define these diseases. In the longer term, such information will help to refine treatment options for defined groups. Abstract Background Chronic airway diseases including chronic obstructive pulmonary disease (COPD) and asthma are heterogenous in nature and endotypes within are underpinned by complex biology. This study aimed to investigate the utility of proteomic profiling of plasma combined with bioinformatic mining, and to define molecular endotypes and expand our knowledge of the underlying biology in chronic respiratory diseases. Methods The plasma proteome was evaluated using an aptamer‐based affinity proteomics platform (SOMAscan®), representing 1238 proteins in 34 subjects with stable COPD and 51 subjects with stable but severe asthma. For each disease, we evaluated a range of clinical/demographic characteristics including bronchodilator reversibility, blood eosinophilia levels, and smoking history. We applied modified bioinformatic approaches used in the evaluation of RNA transcriptomics. Results Subjects with COPD and severe asthma were distinguished from each other by 365 different protein abundancies, with differential pathway networks and upstream modulators. Furthermore, molecular endotypes within each disease could be defined. The protein groups that defined these endotypes had both known and novel biology including groups significantly enriched in exosomal markers derived from immune/inflammatory cells. Finally, we observed associations to clinical characteristics that previously have been under‐explored. Conclusion This investigational study evaluating the plasma proteome in clinically‐phenotyped subjects with chronic airway diseases provides support that such a method can be used to define molecular endotypes and pathobiological mechanisms that underpins these endotypes. It provided new concepts about the complexity of molecular pathways that define these diseases. In the longer term, such information will help to refine treatment options for defined groups. Chronic airway diseases including chronic obstructive pulmonary disease (COPD) and asthma are heterogenous in nature and endotypes within are underpinned by complex biology. This study aimed to investigate the utility of proteomic profiling of plasma combined with bioinformatic mining, and to define molecular endotypes and expand our knowledge of the underlying biology in chronic respiratory diseases. The plasma proteome was evaluated using an aptamer-based affinity proteomics platform (SOMAscan®), representing 1238 proteins in 34 subjects with stable COPD and 51 subjects with stable but severe asthma. For each disease, we evaluated a range of clinical/demographic characteristics including bronchodilator reversibility, blood eosinophilia levels, and smoking history. We applied modified bioinformatic approaches used in the evaluation of RNA transcriptomics. Subjects with COPD and severe asthma were distinguished from each other by 365 different protein abundancies, with differential pathway networks and upstream modulators. Furthermore, molecular endotypes within each disease could be defined. The protein groups that defined these endotypes had both known and novel biology including groups significantly enriched in exosomal markers derived from immune/inflammatory cells. Finally, we observed associations to clinical characteristics that previously have been under-explored. This investigational study evaluating the plasma proteome in clinically-phenotyped subjects with chronic airway diseases provides support that such a method can be used to define molecular endotypes and pathobiological mechanisms that underpins these endotypes. It provided new concepts about the complexity of molecular pathways that define these diseases. In the longer term, such information will help to refine treatment options for defined groups. |
Author | Cole, John J. Maciewicz, Rose A. Konno, Satoshi Suzuki, Masaru Kimura, Hiroki Nishimura, Masaharu Makita, Hironi |
AuthorAffiliation | 3 Hokkaido Medical Research Institute for Respiratory Diseases Sapporo Japan 1 Department of Respiratory Medicine, Faculty of Medicine and Graduate School of Medicine Hokkaido University Sapporo Japan 4 Respiratory, Inflammation and Autoimmunity, Innovative Medicines and Early Development Biotech Unit AstraZeneca Gothenburg Sweden 2 GLAZgo Discovery Centre University of Glasgow Glasgow UK |
AuthorAffiliation_xml | – name: 3 Hokkaido Medical Research Institute for Respiratory Diseases Sapporo Japan – name: 4 Respiratory, Inflammation and Autoimmunity, Innovative Medicines and Early Development Biotech Unit AstraZeneca Gothenburg Sweden – name: 1 Department of Respiratory Medicine, Faculty of Medicine and Graduate School of Medicine Hokkaido University Sapporo Japan – name: 2 GLAZgo Discovery Centre University of Glasgow Glasgow UK |
Author_xml | – sequence: 1 givenname: Masaru orcidid: 0000-0002-2124-6793 surname: Suzuki fullname: Suzuki, Masaru organization: Hokkaido University – sequence: 2 givenname: John J. surname: Cole fullname: Cole, John J. organization: University of Glasgow – sequence: 3 givenname: Satoshi surname: Konno fullname: Konno, Satoshi organization: Hokkaido University – sequence: 4 givenname: Hironi surname: Makita fullname: Makita, Hironi organization: Hokkaido Medical Research Institute for Respiratory Diseases – sequence: 5 givenname: Hiroki surname: Kimura fullname: Kimura, Hiroki organization: Hokkaido University – sequence: 6 givenname: Masaharu surname: Nishimura fullname: Nishimura, Masaharu organization: Hokkaido Medical Research Institute for Respiratory Diseases – sequence: 7 givenname: Rose A. orcidid: 0000-0002-5371-7828 surname: Maciewicz fullname: Maciewicz, Rose A. email: rosemac1955@outlook.com organization: AstraZeneca |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/34962717$$D View this record in MEDLINE/PubMed |
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Keywords | プロテオミクス proteomics BPCO endotipos protéomique asthme sévère proteomic エンドタイプ exosomen asma severa endotypes エクソソーム exosomas proteómica endotypen exosomes schweres Asthma severe asthma 重症喘息 exosome COPD EPOC |
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Notes | Masaru Suzuki and John J. Cole contributed equally and are co‐first authors. ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
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References | 2017; 7 2021; 22 2013; 66 2017; 47 2016; 428 2013; 23 2013; 61 2008; 39 2016; 32 2006; 174 2003; 58 2015; 308 2020; 58 2012; 18 2017; 195 2020; 11 2011; 17 2012; 13 2018; 48 2017; 72 2006; 63 2019; 20 2015; 135 2005; 102 2015; 136 2006; 27 2019; 25 2016; 311 2012; 29 2007; 62 2010; 5 2012; 337 2016; 194 2004; 101 2012; 185 2015; 16 2001; 164 2019; 5 2006; 7 2011; 37 2017; 132 2018; 23 2018; 24 2016; 7 2012; 90 2018; 2018 2015; 192 2017; 14 2020; 30 2017; 11 2004; 350 2017; 13 2017; 12 2017; 56 2015; 2015 2016; 134 2018; 15 e_1_2_8_28_1 e_1_2_8_24_1 e_1_2_8_47_1 e_1_2_8_26_1 e_1_2_8_49_1 e_1_2_8_3_1 e_1_2_8_5_1 e_1_2_8_7_1 e_1_2_8_9_1 e_1_2_8_20_1 e_1_2_8_43_1 e_1_2_8_22_1 e_1_2_8_45_1 e_1_2_8_62_1 e_1_2_8_41_1 e_1_2_8_60_1 e_1_2_8_17_1 e_1_2_8_19_1 e_1_2_8_13_1 e_1_2_8_36_1 e_1_2_8_59_1 e_1_2_8_38_1 e_1_2_8_57_1 Gold L (e_1_2_8_15_1) 2012; 29 e_1_2_8_32_1 e_1_2_8_55_1 e_1_2_8_11_1 e_1_2_8_34_1 e_1_2_8_53_1 e_1_2_8_51_1 e_1_2_8_30_1 e_1_2_8_29_1 e_1_2_8_25_1 e_1_2_8_46_1 e_1_2_8_27_1 e_1_2_8_48_1 Global Initiative for Chronic Obstructive Lung Disease (GOLD) (e_1_2_8_2_1) e_1_2_8_4_1 e_1_2_8_6_1 e_1_2_8_8_1 e_1_2_8_21_1 e_1_2_8_42_1 e_1_2_8_23_1 e_1_2_8_44_1 e_1_2_8_63_1 e_1_2_8_40_1 e_1_2_8_61_1 e_1_2_8_18_1 e_1_2_8_39_1 e_1_2_8_14_1 e_1_2_8_35_1 e_1_2_8_16_1 e_1_2_8_37_1 e_1_2_8_58_1 e_1_2_8_10_1 e_1_2_8_31_1 e_1_2_8_56_1 e_1_2_8_12_1 e_1_2_8_33_1 e_1_2_8_54_1 e_1_2_8_52_1 e_1_2_8_50_1 |
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Snippet | Background
Chronic airway diseases including chronic obstructive pulmonary disease (COPD) and asthma are heterogenous in nature and endotypes within are... Chronic airway diseases including chronic obstructive pulmonary disease (COPD) and asthma are heterogenous in nature and endotypes within are underpinned by... BackgroundChronic airway diseases including chronic obstructive pulmonary disease (COPD) and asthma are heterogenous in nature and endotypes within are... Abstract Background Chronic airway diseases including chronic obstructive pulmonary disease (COPD) and asthma are heterogenous in nature and endotypes within... |
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SubjectTerms | asma severa Asthma asthme sévère Biology Body mass index BPCO Bronchodilators Cardiovascular disease Chronic illnesses Chronic obstructive pulmonary disease COPD Datasets endotipos endotypen endotypes EPOC exosomas exosome exosomen exosomes Gene expression Hay fever Hospitals Original Patients Plasma Proteins proteomic Proteomics proteómica protéomique Respiratory diseases Rhinitis schweres Asthma severe asthma エクソソーム エンドタイプ プロテオミクス 重症喘息 |
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Title | Large‐scale plasma proteomics can reveal distinct endotypes in chronic obstructive pulmonary disease and severe asthma |
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