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Article: Testing cell-type-specific mediation effects in genome-wide epigenetic studies

TitleTesting cell-type-specific mediation effects in genome-wide epigenetic studies
Authors
KeywordsDNA methylation
mediation analysis
cell-type specific
multiple testing
inverse regression
Issue Date2021
PublisherOxford University Press. The Journal's web site is located at http://bib.oxfordjournals.org/
Citation
Briefings in Bioinformatics, 2021, v. 22 n. 3, article no. bbaa131 How to Cite?
AbstractEpigenome-wide mediation analysis aims to identify DNA methylation CpG sites that mediate the causal effects of genetic/environmental exposures on health outcomes. However, DNA methylations in the peripheral blood tissues are usually measured at the bulk level based on a heterogeneous population of white blood cells. Using the bulk level DNA methylation data in mediation analysis might cause confounding bias and reduce study power. Therefore, it is crucial to get fine-grained results by detecting mediation CpG sites in a cell-type-specific way. However, there is a lack of methods and software to achieve this goal. We propose a novel method (Mediation In a Cell-type-Specific fashion, MICS) to identify cell-type-specific mediation effects in genome-wide epigenetic studies using only the bulk-level DNA methylation data. MICS follows the standard mediation analysis paradigm and consists of three key steps. In step1, we assess the exposure-mediator association for each cell type; in step 2, we assess the mediator-outcome association for each cell type; in step 3, we combine the cell-type-specific exposure-mediator and mediator-outcome associations using a multiple testing procedure named MultiMed [Sampson JN, Boca SM, Moore SC, et al. FWER and FDR control when testing multiple mediators. Bioinformatics 2018;34:2418–24] to identify significant CpGs with cell-type-specific mediation effects. We conduct simulation studies to demonstrate that our method has correct FDR control. We also apply the MICS procedure to the Normative Aging Study and identify nine DNA methylation CpG sites in the lymphocytes that might mediate the effect of cigarette smoking on the lung function.
Persistent Identifierhttp://hdl.handle.net/10722/284609
ISSN
2023 Impact Factor: 6.8
2023 SCImago Journal Rankings: 2.143
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLuo, X-
dc.contributor.authorSchwartz, J-
dc.contributor.authorBaccarelli, A-
dc.contributor.authorLiu, Z-
dc.date.accessioned2020-08-07T09:00:06Z-
dc.date.available2020-08-07T09:00:06Z-
dc.date.issued2021-
dc.identifier.citationBriefings in Bioinformatics, 2021, v. 22 n. 3, article no. bbaa131-
dc.identifier.issn1467-5463-
dc.identifier.urihttp://hdl.handle.net/10722/284609-
dc.description.abstractEpigenome-wide mediation analysis aims to identify DNA methylation CpG sites that mediate the causal effects of genetic/environmental exposures on health outcomes. However, DNA methylations in the peripheral blood tissues are usually measured at the bulk level based on a heterogeneous population of white blood cells. Using the bulk level DNA methylation data in mediation analysis might cause confounding bias and reduce study power. Therefore, it is crucial to get fine-grained results by detecting mediation CpG sites in a cell-type-specific way. However, there is a lack of methods and software to achieve this goal. We propose a novel method (Mediation In a Cell-type-Specific fashion, MICS) to identify cell-type-specific mediation effects in genome-wide epigenetic studies using only the bulk-level DNA methylation data. MICS follows the standard mediation analysis paradigm and consists of three key steps. In step1, we assess the exposure-mediator association for each cell type; in step 2, we assess the mediator-outcome association for each cell type; in step 3, we combine the cell-type-specific exposure-mediator and mediator-outcome associations using a multiple testing procedure named MultiMed [Sampson JN, Boca SM, Moore SC, et al. FWER and FDR control when testing multiple mediators. Bioinformatics 2018;34:2418–24] to identify significant CpGs with cell-type-specific mediation effects. We conduct simulation studies to demonstrate that our method has correct FDR control. We also apply the MICS procedure to the Normative Aging Study and identify nine DNA methylation CpG sites in the lymphocytes that might mediate the effect of cigarette smoking on the lung function.-
dc.languageeng-
dc.publisherOxford University Press. The Journal's web site is located at http://bib.oxfordjournals.org/-
dc.relation.ispartofBriefings in Bioinformatics-
dc.rightsThis is a pre-copy-editing, author-produced PDF of an article accepted for publication in Briefings in Bioinformatics following peer review. The definitive publisher-authenticated version Briefings in Bioinformatics, 2021, v. 22 n. 3, article no. bbaa131 is available online at: https://academic.oup.com/bib/article-abstract/22/3/bbaa131/5868071?redirectedFrom=fulltext-
dc.subjectDNA methylation-
dc.subjectmediation analysis-
dc.subjectcell-type specific-
dc.subjectmultiple testing-
dc.subjectinverse regression-
dc.titleTesting cell-type-specific mediation effects in genome-wide epigenetic studies-
dc.typeArticle-
dc.identifier.emailLiu, Z: zhhliu@hku.hk-
dc.identifier.authorityLiu, Z=rp02429-
dc.description.naturepostprint-
dc.identifier.doi10.1093/bib/bbaa131-
dc.identifier.pmid32632436-
dc.identifier.scopuseid_2-s2.0-85107087728-
dc.identifier.hkuros312169-
dc.identifier.volume22-
dc.identifier.issue3-
dc.identifier.spagearticle no. bbaa131-
dc.identifier.epagearticle no. bbaa131-
dc.identifier.isiWOS:000709461300074-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl1467-5463-

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