The cardiopulmonary effects of ambient air pollution and mechanistic pathways: a comparative hierarchical pathway analysis
Previous studies have investigated the associations between exposure to ambient air pollution and biomarkers of physiological pathways, yet little has been done on the comparison across biomarkers of different pathways to establish the temporal pattern of biological response. In the current study, w...
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| Veröffentlicht in: | PloS one 2014-12, Vol.9 (12), p.e114913 |
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| creator | Roy, Ananya Gong, Jicheng Thomas, Duncan C Zhang, Junfeng Kipen, Howard M Rich, David Q Zhu, Tong Huang, Wei Hu, Min Wang, Guangfa Wang, Yuedan Zhu, Ping Lu, Shou-En Ohman-Strickland, Pamela Diehl, Scott R Eckel, Sandrah P |
| description | Previous studies have investigated the associations between exposure to ambient air pollution and biomarkers of physiological pathways, yet little has been done on the comparison across biomarkers of different pathways to establish the temporal pattern of biological response. In the current study, we aim to compare the relative temporal patterns in responses of candidate pathways to different pollutants. Four biomarkers of pulmonary inflammation and oxidative stress, five biomarkers of systemic inflammation and oxidative stress, ten parameters of autonomic function, and three biomarkers of hemostasis were repeatedly measured in 125 young adults, along with daily concentrations of ambient CO, PM2.5, NO2, SO2, EC, OC, and sulfate, before, during, and after the Beijing Olympics. We used a two-stage modeling approach, including Stage I models to estimate the association between each biomarker and pollutant over each of 7 lags, and Stage II mixed-effect models to describe temporal patterns in the associations when grouping the biomarkers into the four physiological pathways. Our results show that candidate pathway groupings of biomarkers explained a significant amount of variation in the associations for each pollutant, and the temporal patterns of the biomarker-pollutant-lag associations varied across candidate pathways (p |
| doi_str_mv | 10.1371/journal.pone.0114913 |
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In the current study, we aim to compare the relative temporal patterns in responses of candidate pathways to different pollutants. Four biomarkers of pulmonary inflammation and oxidative stress, five biomarkers of systemic inflammation and oxidative stress, ten parameters of autonomic function, and three biomarkers of hemostasis were repeatedly measured in 125 young adults, along with daily concentrations of ambient CO, PM2.5, NO2, SO2, EC, OC, and sulfate, before, during, and after the Beijing Olympics. We used a two-stage modeling approach, including Stage I models to estimate the association between each biomarker and pollutant over each of 7 lags, and Stage II mixed-effect models to describe temporal patterns in the associations when grouping the biomarkers into the four physiological pathways. Our results show that candidate pathway groupings of biomarkers explained a significant amount of variation in the associations for each pollutant, and the temporal patterns of the biomarker-pollutant-lag associations varied across candidate pathways (p<0.0001) and were not linear (from lag 0 to lag 3: p = 0.0629, from lag 3 to lag 6: p = 0.0005). These findings suggest that, among this healthy young adult population, the pulmonary inflammation and oxidative stress pathway is the first to respond to ambient air pollution exposure (within 24 hours) and the hemostasis pathway responds gradually over a 2-3 day period. The initial pulmonary response may contribute to the more gradual systemic changes that likely ultimately involve the cardiovascular system.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0114913</identifier><identifier>PMID: 25502951</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Air Pollutants - adverse effects ; Air Pollutants - analysis ; Air pollution ; Atmospheric pollution ; Autonomic Agents - metabolism ; Biomarkers ; Biomarkers - metabolism ; China - epidemiology ; Comparative analysis ; Engineering and Technology ; Hemostasis - physiology ; Humans ; Inflammation ; Inflammation - chemically induced ; Inflammation - metabolism ; Medicine and Health Sciences ; Models, Biological ; Nitrogen dioxide ; Oxidative stress ; Oxidative Stress - physiology ; Particulate matter ; Physical Sciences ; Physiological aspects ; Pneumonia - chemically induced ; Pneumonia - epidemiology ; Pneumonia - metabolism ; Pollutants ; Research and Analysis Methods ; Roy, Ananya ; Sulfates ; Time Factors ; Young Adult</subject><ispartof>PloS one, 2014-12, Vol.9 (12), p.e114913</ispartof><rights>COPYRIGHT 2014 Public Library of Science</rights><rights>2014 Roy et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2014 Roy et al 2014 Roy et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-f173a8ba1fdcdd9850b4ef8ed89458dd8939a94d1a1ee9eed7c8304e0ca2ccf3</citedby><cites>FETCH-LOGICAL-c692t-f173a8ba1fdcdd9850b4ef8ed89458dd8939a94d1a1ee9eed7c8304e0ca2ccf3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4264846/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4264846/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79342,79343</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25502951$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Roy, Ananya</creatorcontrib><creatorcontrib>Gong, Jicheng</creatorcontrib><creatorcontrib>Thomas, Duncan C</creatorcontrib><creatorcontrib>Zhang, Junfeng</creatorcontrib><creatorcontrib>Kipen, Howard M</creatorcontrib><creatorcontrib>Rich, David Q</creatorcontrib><creatorcontrib>Zhu, Tong</creatorcontrib><creatorcontrib>Huang, Wei</creatorcontrib><creatorcontrib>Hu, Min</creatorcontrib><creatorcontrib>Wang, Guangfa</creatorcontrib><creatorcontrib>Wang, Yuedan</creatorcontrib><creatorcontrib>Zhu, Ping</creatorcontrib><creatorcontrib>Lu, Shou-En</creatorcontrib><creatorcontrib>Ohman-Strickland, Pamela</creatorcontrib><creatorcontrib>Diehl, Scott R</creatorcontrib><creatorcontrib>Eckel, Sandrah P</creatorcontrib><title>The cardiopulmonary effects of ambient air pollution and mechanistic pathways: a comparative hierarchical pathway analysis</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Previous studies have investigated the associations between exposure to ambient air pollution and biomarkers of physiological pathways, yet little has been done on the comparison across biomarkers of different pathways to establish the temporal pattern of biological response. In the current study, we aim to compare the relative temporal patterns in responses of candidate pathways to different pollutants. Four biomarkers of pulmonary inflammation and oxidative stress, five biomarkers of systemic inflammation and oxidative stress, ten parameters of autonomic function, and three biomarkers of hemostasis were repeatedly measured in 125 young adults, along with daily concentrations of ambient CO, PM2.5, NO2, SO2, EC, OC, and sulfate, before, during, and after the Beijing Olympics. We used a two-stage modeling approach, including Stage I models to estimate the association between each biomarker and pollutant over each of 7 lags, and Stage II mixed-effect models to describe temporal patterns in the associations when grouping the biomarkers into the four physiological pathways. Our results show that candidate pathway groupings of biomarkers explained a significant amount of variation in the associations for each pollutant, and the temporal patterns of the biomarker-pollutant-lag associations varied across candidate pathways (p<0.0001) and were not linear (from lag 0 to lag 3: p = 0.0629, from lag 3 to lag 6: p = 0.0005). These findings suggest that, among this healthy young adult population, the pulmonary inflammation and oxidative stress pathway is the first to respond to ambient air pollution exposure (within 24 hours) and the hemostasis pathway responds gradually over a 2-3 day period. The initial pulmonary response may contribute to the more gradual systemic changes that likely ultimately involve the cardiovascular system.</description><subject>Air Pollutants - adverse effects</subject><subject>Air Pollutants - analysis</subject><subject>Air pollution</subject><subject>Atmospheric pollution</subject><subject>Autonomic Agents - metabolism</subject><subject>Biomarkers</subject><subject>Biomarkers - metabolism</subject><subject>China - epidemiology</subject><subject>Comparative analysis</subject><subject>Engineering and Technology</subject><subject>Hemostasis - physiology</subject><subject>Humans</subject><subject>Inflammation</subject><subject>Inflammation - chemically induced</subject><subject>Inflammation - metabolism</subject><subject>Medicine and Health Sciences</subject><subject>Models, Biological</subject><subject>Nitrogen dioxide</subject><subject>Oxidative stress</subject><subject>Oxidative Stress - physiology</subject><subject>Particulate 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One</addtitle><date>2014-12-12</date><risdate>2014</risdate><volume>9</volume><issue>12</issue><spage>e114913</spage><pages>e114913-</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Previous studies have investigated the associations between exposure to ambient air pollution and biomarkers of physiological pathways, yet little has been done on the comparison across biomarkers of different pathways to establish the temporal pattern of biological response. In the current study, we aim to compare the relative temporal patterns in responses of candidate pathways to different pollutants. Four biomarkers of pulmonary inflammation and oxidative stress, five biomarkers of systemic inflammation and oxidative stress, ten parameters of autonomic function, and three biomarkers of hemostasis were repeatedly measured in 125 young adults, along with daily concentrations of ambient CO, PM2.5, NO2, SO2, EC, OC, and sulfate, before, during, and after the Beijing Olympics. We used a two-stage modeling approach, including Stage I models to estimate the association between each biomarker and pollutant over each of 7 lags, and Stage II mixed-effect models to describe temporal patterns in the associations when grouping the biomarkers into the four physiological pathways. Our results show that candidate pathway groupings of biomarkers explained a significant amount of variation in the associations for each pollutant, and the temporal patterns of the biomarker-pollutant-lag associations varied across candidate pathways (p<0.0001) and were not linear (from lag 0 to lag 3: p = 0.0629, from lag 3 to lag 6: p = 0.0005). These findings suggest that, among this healthy young adult population, the pulmonary inflammation and oxidative stress pathway is the first to respond to ambient air pollution exposure (within 24 hours) and the hemostasis pathway responds gradually over a 2-3 day period. The initial pulmonary response may contribute to the more gradual systemic changes that likely ultimately involve the cardiovascular system.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>25502951</pmid><doi>10.1371/journal.pone.0114913</doi><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2014-12, Vol.9 (12), p.e114913 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_1635439893 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
| subjects | Air Pollutants - adverse effects Air Pollutants - analysis Air pollution Atmospheric pollution Autonomic Agents - metabolism Biomarkers Biomarkers - metabolism China - epidemiology Comparative analysis Engineering and Technology Hemostasis - physiology Humans Inflammation Inflammation - chemically induced Inflammation - metabolism Medicine and Health Sciences Models, Biological Nitrogen dioxide Oxidative stress Oxidative Stress - physiology Particulate matter Physical Sciences Physiological aspects Pneumonia - chemically induced Pneumonia - epidemiology Pneumonia - metabolism Pollutants Research and Analysis Methods Roy, Ananya Sulfates Time Factors Young Adult |
| title | The cardiopulmonary effects of ambient air pollution and mechanistic pathways: a comparative hierarchical pathway analysis |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-05T05%3A06%3A00IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=The%20cardiopulmonary%20effects%20of%20ambient%20air%20pollution%20and%20mechanistic%20pathways:%20a%20comparative%20hierarchical%20pathway%20analysis&rft.jtitle=PloS%20one&rft.au=Roy,%20Ananya&rft.date=2014-12-12&rft.volume=9&rft.issue=12&rft.spage=e114913&rft.pages=e114913-&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0114913&rft_dat=%3Cgale_plos_%3EA418634902%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1635439893&rft_id=info:pmid/25502951&rft_galeid=A418634902&rft_doaj_id=oai_doaj_org_article_163ae414127c41cd8a3b7aed0abf9d7e&rfr_iscdi=true |