A cross-omics integrative study of metabolic signatures of chronic obstructive pulmonary disease
Background Chronic obstructive pulmonary disease (COPD) is a common lung disorder characterized by persistent and progressive airflow limitation as well as systemic changes. Metabolic changes in blood may help detect COPD in an earlier stage and predict prognosis. Methods We conducted a comprehensiv...
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Veröffentlicht in: | BMC pulmonary medicine 2020-07, Vol.20 (1), p.193-193, Article 193 |
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creator | Prokic, Ivana Lahousse, Lies de Vries, Maaike Liu, Jun Kalaoja, Marita Vonk, Judith M. van der Plaat, Diana A. van Diemen, Cleo C. van der Spek, Ashley Zhernakova, Alexandra Fu, Jingyuan Ghanbari, Mohsen Ala-Korpela, Mika Kettunen, Johannes Havulinna, Aki S. Perola, Markus Salomaa, Veikko Lind, Lars Arnlov, Johan Stricker, Bruno H. C. Brusselle, Guy G. Boezen, H. Marike van Duijn, Cornelia M. Amin, Najaf |
description | Background Chronic obstructive pulmonary disease (COPD) is a common lung disorder characterized by persistent and progressive airflow limitation as well as systemic changes. Metabolic changes in blood may help detect COPD in an earlier stage and predict prognosis. Methods We conducted a comprehensive study of circulating metabolites, measured by proton Nuclear Magnetic Resonance Spectroscopy, in relation with COPD and lung function. The discovery sample consisted of 5557 individuals from two large population-based studies in the Netherlands, the Rotterdam Study and the Erasmus Rucphen Family study. Significant findings were replicated in 12,205 individuals from the Lifelines-DEEP study, FINRISK and the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) studies. For replicated metabolites further investigation of causality was performed, utilizing genetics in the Mendelian randomization approach. Results There were 602 cases of COPD and 4955 controls used in the discovery meta-analysis. Our logistic regression results showed that higher levels of plasma Glycoprotein acetyls (GlycA) are significantly associated with COPD (OR = 1.16,P = 5.6 x 10(- 4)in the discovery and OR = 1.30,P = 1.8 x 10(- 6)in the replication sample). A bi-directional two-sample Mendelian randomization analysis suggested that circulating blood GlycA is not causally related to COPD, but that COPD causally increases GlycA levels. Using the prospective data of the same sample of Rotterdam Study in Cox-regression, we show that the circulating GlycA level is a predictive biomarker of COPD incidence (HR = 1.99, 95%CI 1.52-2.60, comparing those in the highest and lowest quartile of GlycA) but is not significantly associated with mortality in COPD patients (HR = 1.07, 95%CI 0.94-1.20). Conclusions Our study shows that circulating blood GlycA is a biomarker of early COPD pathology. |
doi_str_mv | 10.1186/s12890-020-01222-7 |
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C. ; Brusselle, Guy G. ; Boezen, H. Marike ; van Duijn, Cornelia M. ; Amin, Najaf</creator><creatorcontrib>Prokic, Ivana ; Lahousse, Lies ; de Vries, Maaike ; Liu, Jun ; Kalaoja, Marita ; Vonk, Judith M. ; van der Plaat, Diana A. ; van Diemen, Cleo C. ; van der Spek, Ashley ; Zhernakova, Alexandra ; Fu, Jingyuan ; Ghanbari, Mohsen ; Ala-Korpela, Mika ; Kettunen, Johannes ; Havulinna, Aki S. ; Perola, Markus ; Salomaa, Veikko ; Lind, Lars ; Arnlov, Johan ; Stricker, Bruno H. C. ; Brusselle, Guy G. ; Boezen, H. Marike ; van Duijn, Cornelia M. ; Amin, Najaf</creatorcontrib><description>Background Chronic obstructive pulmonary disease (COPD) is a common lung disorder characterized by persistent and progressive airflow limitation as well as systemic changes. Metabolic changes in blood may help detect COPD in an earlier stage and predict prognosis. Methods We conducted a comprehensive study of circulating metabolites, measured by proton Nuclear Magnetic Resonance Spectroscopy, in relation with COPD and lung function. The discovery sample consisted of 5557 individuals from two large population-based studies in the Netherlands, the Rotterdam Study and the Erasmus Rucphen Family study. Significant findings were replicated in 12,205 individuals from the Lifelines-DEEP study, FINRISK and the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) studies. For replicated metabolites further investigation of causality was performed, utilizing genetics in the Mendelian randomization approach. Results There were 602 cases of COPD and 4955 controls used in the discovery meta-analysis. Our logistic regression results showed that higher levels of plasma Glycoprotein acetyls (GlycA) are significantly associated with COPD (OR = 1.16,P = 5.6 x 10(- 4)in the discovery and OR = 1.30,P = 1.8 x 10(- 6)in the replication sample). A bi-directional two-sample Mendelian randomization analysis suggested that circulating blood GlycA is not causally related to COPD, but that COPD causally increases GlycA levels. Using the prospective data of the same sample of Rotterdam Study in Cox-regression, we show that the circulating GlycA level is a predictive biomarker of COPD incidence (HR = 1.99, 95%CI 1.52-2.60, comparing those in the highest and lowest quartile of GlycA) but is not significantly associated with mortality in COPD patients (HR = 1.07, 95%CI 0.94-1.20). Conclusions Our study shows that circulating blood GlycA is a biomarker of early COPD pathology.</description><identifier>ISSN: 1471-2466</identifier><identifier>EISSN: 1471-2466</identifier><identifier>DOI: 10.1186/s12890-020-01222-7</identifier><identifier>PMID: 32677943</identifier><language>eng</language><publisher>LONDON: Springer Nature</publisher><subject>Aged ; Aged, 80 and over ; Biological markers ; Biomarkers ; Biomarkers - blood ; Blood ; Chronic illnesses ; Chronic obstructive lung disease ; Chronic obstructive pulmonary disease ; Cohort Studies ; COPD ; Development and progression ; Diagnosis ; Female ; Glycoprotein acetyls ; Glycoproteins ; Glycoproteins - blood ; Glycoproteins - chemistry ; Health and Welfare ; Health aspects ; Humans ; Hälsa och välfärd ; Life Sciences & Biomedicine ; Logistic Models ; Lung - metabolism ; Lung diseases ; Magnetic resonance spectroscopy ; Male ; Medicin och hälsovetenskap ; Mendelian randomization ; Mendelian Randomization Analysis ; Metabolites ; Metabolomics ; Metabolomics - methods ; Middle Aged ; Netherlands - epidemiology ; NMR ; Nuclear magnetic resonance ; Obstructive lung disease ; Physiological aspects ; Population studies ; Prognosis ; Pulmonary Disease, Chronic Obstructive - blood ; Pulmonary Disease, Chronic Obstructive - metabolism ; Pulmonary Disease, Chronic Obstructive - mortality ; Pulmonology ; Respiratory function ; Respiratory System ; Risk Factors ; Science & Technology ; Studies ; Survival Rate</subject><ispartof>BMC pulmonary medicine, 2020-07, Vol.20 (1), p.193-193, Article 193</ispartof><rights>COPYRIGHT 2020 BioMed Central Ltd.</rights><rights>2020. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>The Author(s) 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>true</woscitedreferencessubscribed><woscitedreferencescount>13</woscitedreferencescount><woscitedreferencesoriginalsourcerecordid>wos000552384400001</woscitedreferencesoriginalsourcerecordid><citedby>FETCH-LOGICAL-c724t-1ed184cfcdadca3d785173ed1387860226ab6295011790d0e02100542c22d46c3</citedby><cites>FETCH-LOGICAL-c724t-1ed184cfcdadca3d785173ed1387860226ab6295011790d0e02100542c22d46c3</cites><orcidid>0000-0001-7531-4547 ; 0000-0002-0755-7296 ; 0000-0002-0361-357X ; 0000-0001-5288-3042 ; 0000-0002-8944-1771 ; 0000-0002-3345-491X ; 0000-0001-7210-8174 ; 0000-0001-5578-1236 ; 0000-0002-9476-7143 ; 0000-0001-5905-1206 ; 0000-0002-3494-4363 ; 0000-0002-0370-1473</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7364599/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7364599/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,315,554,729,782,786,866,887,2104,2116,27931,27932,28255,53798,53800</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32677943$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://urn.kb.se/resolve?urn=urn:nbn:se:du-34649$$DView record from Swedish Publication Index$$Hfree_for_read</backlink><backlink>$$Uhttps://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-419785$$DView record from Swedish Publication Index$$Hfree_for_read</backlink><backlink>$$Uhttp://kipublications.ki.se/Default.aspx?queryparsed=id:144235314$$DView record from Swedish Publication Index$$Hfree_for_read</backlink></links><search><creatorcontrib>Prokic, Ivana</creatorcontrib><creatorcontrib>Lahousse, Lies</creatorcontrib><creatorcontrib>de Vries, Maaike</creatorcontrib><creatorcontrib>Liu, Jun</creatorcontrib><creatorcontrib>Kalaoja, Marita</creatorcontrib><creatorcontrib>Vonk, Judith M.</creatorcontrib><creatorcontrib>van der Plaat, Diana A.</creatorcontrib><creatorcontrib>van Diemen, Cleo C.</creatorcontrib><creatorcontrib>van der Spek, Ashley</creatorcontrib><creatorcontrib>Zhernakova, Alexandra</creatorcontrib><creatorcontrib>Fu, Jingyuan</creatorcontrib><creatorcontrib>Ghanbari, Mohsen</creatorcontrib><creatorcontrib>Ala-Korpela, Mika</creatorcontrib><creatorcontrib>Kettunen, Johannes</creatorcontrib><creatorcontrib>Havulinna, Aki S.</creatorcontrib><creatorcontrib>Perola, Markus</creatorcontrib><creatorcontrib>Salomaa, Veikko</creatorcontrib><creatorcontrib>Lind, Lars</creatorcontrib><creatorcontrib>Arnlov, Johan</creatorcontrib><creatorcontrib>Stricker, Bruno H. C.</creatorcontrib><creatorcontrib>Brusselle, Guy G.</creatorcontrib><creatorcontrib>Boezen, H. Marike</creatorcontrib><creatorcontrib>van Duijn, Cornelia M.</creatorcontrib><creatorcontrib>Amin, Najaf</creatorcontrib><title>A cross-omics integrative study of metabolic signatures of chronic obstructive pulmonary disease</title><title>BMC pulmonary medicine</title><addtitle>BMC PULM MED</addtitle><addtitle>BMC Pulm Med</addtitle><description>Background Chronic obstructive pulmonary disease (COPD) is a common lung disorder characterized by persistent and progressive airflow limitation as well as systemic changes. Metabolic changes in blood may help detect COPD in an earlier stage and predict prognosis. Methods We conducted a comprehensive study of circulating metabolites, measured by proton Nuclear Magnetic Resonance Spectroscopy, in relation with COPD and lung function. The discovery sample consisted of 5557 individuals from two large population-based studies in the Netherlands, the Rotterdam Study and the Erasmus Rucphen Family study. Significant findings were replicated in 12,205 individuals from the Lifelines-DEEP study, FINRISK and the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) studies. For replicated metabolites further investigation of causality was performed, utilizing genetics in the Mendelian randomization approach. Results There were 602 cases of COPD and 4955 controls used in the discovery meta-analysis. Our logistic regression results showed that higher levels of plasma Glycoprotein acetyls (GlycA) are significantly associated with COPD (OR = 1.16,P = 5.6 x 10(- 4)in the discovery and OR = 1.30,P = 1.8 x 10(- 6)in the replication sample). A bi-directional two-sample Mendelian randomization analysis suggested that circulating blood GlycA is not causally related to COPD, but that COPD causally increases GlycA levels. Using the prospective data of the same sample of Rotterdam Study in Cox-regression, we show that the circulating GlycA level is a predictive biomarker of COPD incidence (HR = 1.99, 95%CI 1.52-2.60, comparing those in the highest and lowest quartile of GlycA) but is not significantly associated with mortality in COPD patients (HR = 1.07, 95%CI 0.94-1.20). Conclusions Our study shows that circulating blood GlycA is a biomarker of early COPD pathology.</description><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Biological markers</subject><subject>Biomarkers</subject><subject>Biomarkers - blood</subject><subject>Blood</subject><subject>Chronic illnesses</subject><subject>Chronic obstructive lung disease</subject><subject>Chronic obstructive pulmonary disease</subject><subject>Cohort Studies</subject><subject>COPD</subject><subject>Development and progression</subject><subject>Diagnosis</subject><subject>Female</subject><subject>Glycoprotein acetyls</subject><subject>Glycoproteins</subject><subject>Glycoproteins - blood</subject><subject>Glycoproteins - chemistry</subject><subject>Health and Welfare</subject><subject>Health aspects</subject><subject>Humans</subject><subject>Hälsa och välfärd</subject><subject>Life Sciences & Biomedicine</subject><subject>Logistic Models</subject><subject>Lung - metabolism</subject><subject>Lung diseases</subject><subject>Magnetic resonance spectroscopy</subject><subject>Male</subject><subject>Medicin och hälsovetenskap</subject><subject>Mendelian randomization</subject><subject>Mendelian Randomization Analysis</subject><subject>Metabolites</subject><subject>Metabolomics</subject><subject>Metabolomics - methods</subject><subject>Middle Aged</subject><subject>Netherlands - epidemiology</subject><subject>NMR</subject><subject>Nuclear magnetic resonance</subject><subject>Obstructive lung disease</subject><subject>Physiological aspects</subject><subject>Population studies</subject><subject>Prognosis</subject><subject>Pulmonary Disease, Chronic Obstructive - blood</subject><subject>Pulmonary Disease, Chronic Obstructive - metabolism</subject><subject>Pulmonary Disease, Chronic Obstructive - mortality</subject><subject>Pulmonology</subject><subject>Respiratory function</subject><subject>Respiratory System</subject><subject>Risk Factors</subject><subject>Science & Technology</subject><subject>Studies</subject><subject>Survival Rate</subject><issn>1471-2466</issn><issn>1471-2466</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>AOWDO</sourceid><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>D8T</sourceid><sourceid>DOA</sourceid><recordid>eNqNU01v1DAQjRCIloU_wAFF4oIEKf6KY1-QVstXpUpcgKtx7MnWS9Ze7KRV_z3ObrvtIipQFGU0ee95PDOvKJ5jdIKx4G8TJkKiCpH8YkJI1TwojjFrcEUY5w_vxEfFk5RWCOFG1PRxcUQJbxrJ6HHxY16aGFKqwtqZVDo_wDLqwV1AmYbRXpWhK9cw6Db0zpTJLb0exghpypvzGHzOhjYNcTRb0mbs18HreFVal0AneFo86nSf4Nn1d1Z8-_jh6-Jzdfbl0-liflaZhrChwmCxYKYzVlujqc2F4obmJBWN4IgQrltOZI0wbiSyCBDBCNWMGEIs44bOitOdrg16pTbRrXMRKmintokQl0rHwZkeVNNgaoHYjgJnGLCsjSAEmKataDvGsla100qXsBnbA7Xr1M8cgWJc8iw2K-S9-E0M9pZ0Q8SMEVpTPJ315l7ue_d9vq18HBXDchrerHj9b7gdFWWcyYx-t0Nn6BqsAT9E3R_Wd_DHu3O1DBeqoZzVchJ4dS0Qw68R0qDWLhnoe-0hjEkRRpiUDUc8Q1_-AV2FMfo88y1KIFGTO6ilzpNwvgv5XDOJqjmnWMia0qmhJ39B5cdCXtPgoXM5f0AgO8J2mSN0-ztipCazqJ1ZVDaL2polX3FWvLjbnT3lxh23zb6ENnTJOPAG9jCU968mVDCWIzTVIP4fvXBDdlnwizD6gf4GtagxHw</recordid><startdate>20200716</startdate><enddate>20200716</enddate><creator>Prokic, Ivana</creator><creator>Lahousse, Lies</creator><creator>de Vries, Maaike</creator><creator>Liu, Jun</creator><creator>Kalaoja, Marita</creator><creator>Vonk, Judith M.</creator><creator>van der Plaat, Diana A.</creator><creator>van Diemen, Cleo C.</creator><creator>van der Spek, Ashley</creator><creator>Zhernakova, Alexandra</creator><creator>Fu, Jingyuan</creator><creator>Ghanbari, Mohsen</creator><creator>Ala-Korpela, Mika</creator><creator>Kettunen, Johannes</creator><creator>Havulinna, Aki S.</creator><creator>Perola, Markus</creator><creator>Salomaa, Veikko</creator><creator>Lind, Lars</creator><creator>Arnlov, Johan</creator><creator>Stricker, Bruno H. 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C. ; Brusselle, Guy G. ; Boezen, H. Marike ; van Duijn, Cornelia M. ; Amin, Najaf</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c724t-1ed184cfcdadca3d785173ed1387860226ab6295011790d0e02100542c22d46c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Biological markers</topic><topic>Biomarkers</topic><topic>Biomarkers - blood</topic><topic>Blood</topic><topic>Chronic illnesses</topic><topic>Chronic obstructive lung disease</topic><topic>Chronic obstructive pulmonary disease</topic><topic>Cohort Studies</topic><topic>COPD</topic><topic>Development and progression</topic><topic>Diagnosis</topic><topic>Female</topic><topic>Glycoprotein acetyls</topic><topic>Glycoproteins</topic><topic>Glycoproteins - blood</topic><topic>Glycoproteins - chemistry</topic><topic>Health and Welfare</topic><topic>Health aspects</topic><topic>Humans</topic><topic>Hälsa och välfärd</topic><topic>Life Sciences & Biomedicine</topic><topic>Logistic Models</topic><topic>Lung - metabolism</topic><topic>Lung diseases</topic><topic>Magnetic resonance spectroscopy</topic><topic>Male</topic><topic>Medicin och hälsovetenskap</topic><topic>Mendelian randomization</topic><topic>Mendelian Randomization Analysis</topic><topic>Metabolites</topic><topic>Metabolomics</topic><topic>Metabolomics - methods</topic><topic>Middle Aged</topic><topic>Netherlands - epidemiology</topic><topic>NMR</topic><topic>Nuclear magnetic resonance</topic><topic>Obstructive lung disease</topic><topic>Physiological aspects</topic><topic>Population studies</topic><topic>Prognosis</topic><topic>Pulmonary Disease, Chronic Obstructive - blood</topic><topic>Pulmonary Disease, Chronic Obstructive - metabolism</topic><topic>Pulmonary Disease, Chronic Obstructive - mortality</topic><topic>Pulmonology</topic><topic>Respiratory function</topic><topic>Respiratory System</topic><topic>Risk Factors</topic><topic>Science & Technology</topic><topic>Studies</topic><topic>Survival Rate</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Prokic, Ivana</creatorcontrib><creatorcontrib>Lahousse, Lies</creatorcontrib><creatorcontrib>de Vries, Maaike</creatorcontrib><creatorcontrib>Liu, Jun</creatorcontrib><creatorcontrib>Kalaoja, Marita</creatorcontrib><creatorcontrib>Vonk, Judith M.</creatorcontrib><creatorcontrib>van der Plaat, Diana A.</creatorcontrib><creatorcontrib>van Diemen, Cleo C.</creatorcontrib><creatorcontrib>van der Spek, Ashley</creatorcontrib><creatorcontrib>Zhernakova, Alexandra</creatorcontrib><creatorcontrib>Fu, Jingyuan</creatorcontrib><creatorcontrib>Ghanbari, Mohsen</creatorcontrib><creatorcontrib>Ala-Korpela, Mika</creatorcontrib><creatorcontrib>Kettunen, Johannes</creatorcontrib><creatorcontrib>Havulinna, Aki S.</creatorcontrib><creatorcontrib>Perola, Markus</creatorcontrib><creatorcontrib>Salomaa, Veikko</creatorcontrib><creatorcontrib>Lind, Lars</creatorcontrib><creatorcontrib>Arnlov, Johan</creatorcontrib><creatorcontrib>Stricker, Bruno H. C.</creatorcontrib><creatorcontrib>Brusselle, Guy G.</creatorcontrib><creatorcontrib>Boezen, H. Marike</creatorcontrib><creatorcontrib>van Duijn, Cornelia M.</creatorcontrib><creatorcontrib>Amin, Najaf</creatorcontrib><collection>Web of Science - Science Citation Index Expanded - 2020</collection><collection>Web of Science Core Collection</collection><collection>Science Citation Index Expanded</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Oncogenes and Growth Factors Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Access via ProQuest (Open Access)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>SwePub</collection><collection>SwePub Articles</collection><collection>SWEPUB Freely available online</collection><collection>SwePub Articles full text</collection><collection>SWEPUB Uppsala universitet full text</collection><collection>SWEPUB Uppsala universitet</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>BMC pulmonary medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Prokic, Ivana</au><au>Lahousse, Lies</au><au>de Vries, Maaike</au><au>Liu, Jun</au><au>Kalaoja, Marita</au><au>Vonk, Judith M.</au><au>van der Plaat, Diana A.</au><au>van Diemen, Cleo C.</au><au>van der Spek, Ashley</au><au>Zhernakova, Alexandra</au><au>Fu, Jingyuan</au><au>Ghanbari, Mohsen</au><au>Ala-Korpela, Mika</au><au>Kettunen, Johannes</au><au>Havulinna, Aki S.</au><au>Perola, Markus</au><au>Salomaa, Veikko</au><au>Lind, Lars</au><au>Arnlov, Johan</au><au>Stricker, Bruno H. C.</au><au>Brusselle, Guy G.</au><au>Boezen, H. Marike</au><au>van Duijn, Cornelia M.</au><au>Amin, Najaf</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A cross-omics integrative study of metabolic signatures of chronic obstructive pulmonary disease</atitle><jtitle>BMC pulmonary medicine</jtitle><stitle>BMC PULM MED</stitle><addtitle>BMC Pulm Med</addtitle><date>2020-07-16</date><risdate>2020</risdate><volume>20</volume><issue>1</issue><spage>193</spage><epage>193</epage><pages>193-193</pages><artnum>193</artnum><issn>1471-2466</issn><eissn>1471-2466</eissn><abstract>Background Chronic obstructive pulmonary disease (COPD) is a common lung disorder characterized by persistent and progressive airflow limitation as well as systemic changes. Metabolic changes in blood may help detect COPD in an earlier stage and predict prognosis. Methods We conducted a comprehensive study of circulating metabolites, measured by proton Nuclear Magnetic Resonance Spectroscopy, in relation with COPD and lung function. The discovery sample consisted of 5557 individuals from two large population-based studies in the Netherlands, the Rotterdam Study and the Erasmus Rucphen Family study. Significant findings were replicated in 12,205 individuals from the Lifelines-DEEP study, FINRISK and the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) studies. For replicated metabolites further investigation of causality was performed, utilizing genetics in the Mendelian randomization approach. Results There were 602 cases of COPD and 4955 controls used in the discovery meta-analysis. Our logistic regression results showed that higher levels of plasma Glycoprotein acetyls (GlycA) are significantly associated with COPD (OR = 1.16,P = 5.6 x 10(- 4)in the discovery and OR = 1.30,P = 1.8 x 10(- 6)in the replication sample). A bi-directional two-sample Mendelian randomization analysis suggested that circulating blood GlycA is not causally related to COPD, but that COPD causally increases GlycA levels. Using the prospective data of the same sample of Rotterdam Study in Cox-regression, we show that the circulating GlycA level is a predictive biomarker of COPD incidence (HR = 1.99, 95%CI 1.52-2.60, comparing those in the highest and lowest quartile of GlycA) but is not significantly associated with mortality in COPD patients (HR = 1.07, 95%CI 0.94-1.20). Conclusions Our study shows that circulating blood GlycA is a biomarker of early COPD pathology.</abstract><cop>LONDON</cop><pub>Springer Nature</pub><pmid>32677943</pmid><doi>10.1186/s12890-020-01222-7</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0001-7531-4547</orcidid><orcidid>https://orcid.org/0000-0002-0755-7296</orcidid><orcidid>https://orcid.org/0000-0002-0361-357X</orcidid><orcidid>https://orcid.org/0000-0001-5288-3042</orcidid><orcidid>https://orcid.org/0000-0002-8944-1771</orcidid><orcidid>https://orcid.org/0000-0002-3345-491X</orcidid><orcidid>https://orcid.org/0000-0001-7210-8174</orcidid><orcidid>https://orcid.org/0000-0001-5578-1236</orcidid><orcidid>https://orcid.org/0000-0002-9476-7143</orcidid><orcidid>https://orcid.org/0000-0001-5905-1206</orcidid><orcidid>https://orcid.org/0000-0002-3494-4363</orcidid><orcidid>https://orcid.org/0000-0002-0370-1473</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Aged Aged, 80 and over Biological markers Biomarkers Biomarkers - blood Blood Chronic illnesses Chronic obstructive lung disease Chronic obstructive pulmonary disease Cohort Studies COPD Development and progression Diagnosis Female Glycoprotein acetyls Glycoproteins Glycoproteins - blood Glycoproteins - chemistry Health and Welfare Health aspects Humans Hälsa och välfärd Life Sciences & Biomedicine Logistic Models Lung - metabolism Lung diseases Magnetic resonance spectroscopy Male Medicin och hälsovetenskap Mendelian randomization Mendelian Randomization Analysis Metabolites Metabolomics Metabolomics - methods Middle Aged Netherlands - epidemiology NMR Nuclear magnetic resonance Obstructive lung disease Physiological aspects Population studies Prognosis Pulmonary Disease, Chronic Obstructive - blood Pulmonary Disease, Chronic Obstructive - metabolism Pulmonary Disease, Chronic Obstructive - mortality Pulmonology Respiratory function Respiratory System Risk Factors Science & Technology Studies Survival Rate |
title | A cross-omics integrative study of metabolic signatures of chronic obstructive pulmonary disease |
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