Estimating and testing high-dimensional mediation effects in epigenetic studies
High-dimensional DNA methylation markers may mediate pathways linking environmental exposures with health outcomes. However, there is a lack of analytical methods to identify significant mediators for high-dimensional mediation analysis. Based on sure independent screening and minimax concave penalt...
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| Veröffentlicht in: | Bioinformatics (Oxford, England) England), 2016-10, Vol.32 (20), p.3150-3154 |
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| creator | Zhang, Haixiang Zheng, Yinan Zhang, Zhou Gao, Tao Joyce, Brian Yoon, Grace Zhang, Wei Schwartz, Joel Just, Allan Colicino, Elena Vokonas, Pantel Zhao, Lihui Lv, Jinchi Baccarelli, Andrea Hou, Lifang Liu, Lei |
| description | High-dimensional DNA methylation markers may mediate pathways linking environmental exposures with health outcomes. However, there is a lack of analytical methods to identify significant mediators for high-dimensional mediation analysis.
Based on sure independent screening and minimax concave penalty techniques, we use a joint significance test for mediation effect. We demonstrate its practical performance using Monte Carlo simulation studies and apply this method to investigate the extent to which DNA methylation markers mediate the causal pathway from smoking to reduced lung function in the Normative Aging Study. We identify 2 CpGs with significant mediation effects.
R package, source code, and simulation study are available at https://github.com/YinanZheng/HIMA CONTACT: lei.liu@northwestern.edu. |
| doi_str_mv | 10.1093/bioinformatics/btw351 |
| format | Article |
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Based on sure independent screening and minimax concave penalty techniques, we use a joint significance test for mediation effect. We demonstrate its practical performance using Monte Carlo simulation studies and apply this method to investigate the extent to which DNA methylation markers mediate the causal pathway from smoking to reduced lung function in the Normative Aging Study. We identify 2 CpGs with significant mediation effects.
R package, source code, and simulation study are available at https://github.com/YinanZheng/HIMA CONTACT: lei.liu@northwestern.edu.</description><identifier>ISSN: 1367-4803</identifier><identifier>ISSN: 1460-2059</identifier><identifier>EISSN: 1367-4811</identifier><identifier>DOI: 10.1093/bioinformatics/btw351</identifier><identifier>PMID: 27357171</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Aging ; analytical methods ; bioinformatics ; computer software ; DNA Methylation ; environmental exposure ; epigenetics ; Epigenomics ; Humans ; lung function ; Monte Carlo Method ; Original Paper ; screening ; Smoking</subject><ispartof>Bioinformatics (Oxford, England), 2016-10, Vol.32 (20), p.3150-3154</ispartof><rights>The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.</rights><rights>The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c440t-66a3750d76c4b92f1c87381f5d725b594bed04dd325b130d994141f7d9d7d4ee3</citedby><cites>FETCH-LOGICAL-c440t-66a3750d76c4b92f1c87381f5d725b594bed04dd325b130d994141f7d9d7d4ee3</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/PMC5048064/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5048064/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,724,777,781,882,27905,27906,53772,53774</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27357171$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhang, Haixiang</creatorcontrib><creatorcontrib>Zheng, Yinan</creatorcontrib><creatorcontrib>Zhang, Zhou</creatorcontrib><creatorcontrib>Gao, Tao</creatorcontrib><creatorcontrib>Joyce, Brian</creatorcontrib><creatorcontrib>Yoon, Grace</creatorcontrib><creatorcontrib>Zhang, Wei</creatorcontrib><creatorcontrib>Schwartz, Joel</creatorcontrib><creatorcontrib>Just, Allan</creatorcontrib><creatorcontrib>Colicino, Elena</creatorcontrib><creatorcontrib>Vokonas, Pantel</creatorcontrib><creatorcontrib>Zhao, Lihui</creatorcontrib><creatorcontrib>Lv, Jinchi</creatorcontrib><creatorcontrib>Baccarelli, Andrea</creatorcontrib><creatorcontrib>Hou, Lifang</creatorcontrib><creatorcontrib>Liu, Lei</creatorcontrib><title>Estimating and testing high-dimensional mediation effects in epigenetic studies</title><title>Bioinformatics (Oxford, England)</title><addtitle>Bioinformatics</addtitle><description>High-dimensional DNA methylation markers may mediate pathways linking environmental exposures with health outcomes. However, there is a lack of analytical methods to identify significant mediators for high-dimensional mediation analysis.
Based on sure independent screening and minimax concave penalty techniques, we use a joint significance test for mediation effect. We demonstrate its practical performance using Monte Carlo simulation studies and apply this method to investigate the extent to which DNA methylation markers mediate the causal pathway from smoking to reduced lung function in the Normative Aging Study. We identify 2 CpGs with significant mediation effects.
R package, source code, and simulation study are available at https://github.com/YinanZheng/HIMA CONTACT: lei.liu@northwestern.edu.</description><subject>Aging</subject><subject>analytical methods</subject><subject>bioinformatics</subject><subject>computer software</subject><subject>DNA Methylation</subject><subject>environmental exposure</subject><subject>epigenetics</subject><subject>Epigenomics</subject><subject>Humans</subject><subject>lung function</subject><subject>Monte Carlo Method</subject><subject>Original Paper</subject><subject>screening</subject><subject>Smoking</subject><issn>1367-4803</issn><issn>1460-2059</issn><issn>1367-4811</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFUclOwzAUtBCIlsIngHLkEmrHW3JBQlVZpEq9wNlyvKRGiV3iFMTf41Ko6ImTx_K8eTMeAC4RvEGwwtPaBedt6Ds5OBWn9fCBKToCY4QZz0mJ0PEeQzwCZzG-QggppOwUjAqOKUccjcFyHge31fBNJr3OBhO_8co1q1y7zvjogpdt1hntEi34zFhr1BAzl-DaNcab5CCLw0Y7E8_BiZVtNBc_5wS83M-fZ4_5YvnwNLtb5IoQOOSMScwp1JwpUleFRarkuESWal7QmlakNhoSrXG6IQx1VRFEkOW60lwTY_AE3O5015s6WVPGD71sxbpPYfpPEaQThy_erUQT3gWF6UMYSQLXPwJ9eNuk1KJzUZm2ld6ETRRFQdNyzjn7l4rKgnFYlWRLpTuq6kOMvbF7RwiKbW_isDex6y3NXf2Ns5_6LQp_AfE-m4Q</recordid><startdate>20161015</startdate><enddate>20161015</enddate><creator>Zhang, Haixiang</creator><creator>Zheng, Yinan</creator><creator>Zhang, Zhou</creator><creator>Gao, Tao</creator><creator>Joyce, Brian</creator><creator>Yoon, Grace</creator><creator>Zhang, Wei</creator><creator>Schwartz, Joel</creator><creator>Just, Allan</creator><creator>Colicino, Elena</creator><creator>Vokonas, Pantel</creator><creator>Zhao, Lihui</creator><creator>Lv, Jinchi</creator><creator>Baccarelli, Andrea</creator><creator>Hou, Lifang</creator><creator>Liu, Lei</creator><general>Oxford University Press</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7S9</scope><scope>L.6</scope><scope>5PM</scope></search><sort><creationdate>20161015</creationdate><title>Estimating and testing high-dimensional mediation effects in epigenetic studies</title><author>Zhang, Haixiang ; Zheng, Yinan ; Zhang, Zhou ; Gao, Tao ; Joyce, Brian ; Yoon, Grace ; Zhang, Wei ; Schwartz, Joel ; Just, Allan ; Colicino, Elena ; Vokonas, Pantel ; Zhao, Lihui ; Lv, Jinchi ; Baccarelli, Andrea ; Hou, Lifang ; Liu, Lei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c440t-66a3750d76c4b92f1c87381f5d725b594bed04dd325b130d994141f7d9d7d4ee3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Aging</topic><topic>analytical methods</topic><topic>bioinformatics</topic><topic>computer software</topic><topic>DNA Methylation</topic><topic>environmental exposure</topic><topic>epigenetics</topic><topic>Epigenomics</topic><topic>Humans</topic><topic>lung function</topic><topic>Monte Carlo Method</topic><topic>Original Paper</topic><topic>screening</topic><topic>Smoking</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Haixiang</creatorcontrib><creatorcontrib>Zheng, Yinan</creatorcontrib><creatorcontrib>Zhang, Zhou</creatorcontrib><creatorcontrib>Gao, Tao</creatorcontrib><creatorcontrib>Joyce, Brian</creatorcontrib><creatorcontrib>Yoon, Grace</creatorcontrib><creatorcontrib>Zhang, Wei</creatorcontrib><creatorcontrib>Schwartz, Joel</creatorcontrib><creatorcontrib>Just, Allan</creatorcontrib><creatorcontrib>Colicino, Elena</creatorcontrib><creatorcontrib>Vokonas, Pantel</creatorcontrib><creatorcontrib>Zhao, Lihui</creatorcontrib><creatorcontrib>Lv, Jinchi</creatorcontrib><creatorcontrib>Baccarelli, Andrea</creatorcontrib><creatorcontrib>Hou, Lifang</creatorcontrib><creatorcontrib>Liu, Lei</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Bioinformatics (Oxford, England)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Haixiang</au><au>Zheng, Yinan</au><au>Zhang, Zhou</au><au>Gao, Tao</au><au>Joyce, Brian</au><au>Yoon, Grace</au><au>Zhang, Wei</au><au>Schwartz, Joel</au><au>Just, Allan</au><au>Colicino, Elena</au><au>Vokonas, Pantel</au><au>Zhao, Lihui</au><au>Lv, Jinchi</au><au>Baccarelli, Andrea</au><au>Hou, Lifang</au><au>Liu, Lei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Estimating and testing high-dimensional mediation effects in epigenetic studies</atitle><jtitle>Bioinformatics (Oxford, England)</jtitle><addtitle>Bioinformatics</addtitle><date>2016-10-15</date><risdate>2016</risdate><volume>32</volume><issue>20</issue><spage>3150</spage><epage>3154</epage><pages>3150-3154</pages><issn>1367-4803</issn><issn>1460-2059</issn><eissn>1367-4811</eissn><abstract>High-dimensional DNA methylation markers may mediate pathways linking environmental exposures with health outcomes. However, there is a lack of analytical methods to identify significant mediators for high-dimensional mediation analysis.
Based on sure independent screening and minimax concave penalty techniques, we use a joint significance test for mediation effect. We demonstrate its practical performance using Monte Carlo simulation studies and apply this method to investigate the extent to which DNA methylation markers mediate the causal pathway from smoking to reduced lung function in the Normative Aging Study. We identify 2 CpGs with significant mediation effects.
R package, source code, and simulation study are available at https://github.com/YinanZheng/HIMA CONTACT: lei.liu@northwestern.edu.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>27357171</pmid><doi>10.1093/bioinformatics/btw351</doi><tpages>5</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Aging analytical methods bioinformatics computer software DNA Methylation environmental exposure epigenetics Epigenomics Humans lung function Monte Carlo Method Original Paper screening Smoking |
| title | Estimating and testing high-dimensional mediation effects in epigenetic studies |
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