HIMA2: high-dimensional mediation analysis and its application in epigenome-wide DNA methylation data

Chamila Perera; Haixiang Zhang; Yinan Zheng; Lifang Hou; Annie Qu; Cheng Zheng; Ke Xie; Lei Liu

doi:10.1186/s12859-022-04748-1

HIMA2: high-dimensional mediation analysis and its application in epigenome-wide DNA methylation data

Chamila Perera, Haixiang Zhang, Yinan Zheng, Lifang Hou, Annie Qu, Cheng Zheng, Ke Xie, Lei Liu^*

^*Corresponding author for this work

Preventive Medicine

Research output: Contribution to journal › Article › peer-review

15 Scopus citations

Abstract

Mediation analysis plays a major role in identifying significant mediators in the pathway between environmental exposures and health outcomes. With advanced data collection technology for large-scale studies, there has been growing research interest in developing methodology for high-dimensional mediation analysis. In this paper we present HIMA2, an extension of the HIMA method (Zhang in Bioinformatics 32:3150–3154, 2016). First, the proposed HIMA2 reduces the dimension of mediators to a manageable level based on the sure independence screening (SIS) method (Fan in J R Stat Soc Ser B 70:849–911, 2008). Second, a de-biased Lasso procedure is implemented for estimating regression parameters. Third, we use a multiple-testing procedure to accurately control the false discovery rate (FDR) when testing high-dimensional mediation hypotheses. We demonstrate its practical performance using Monte Carlo simulation studies and apply our method to identify DNA methylation markers which mediate the pathway from smoking to reduced lung function in the Coronary Artery Risk Development in Young Adults (CARDIA) Study.

Original language	English (US)
Article number	296
Journal	BMC bioinformatics
Volume	23
Issue number	1
DOIs	https://doi.org/10.1186/s12859-022-04748-1
State	Published - Dec 2022

Funding

This research was partly supported by NIH/NIA R21 AG 063370, R21 AG068955, and NIH/NCATS UL1 TR002345. The Coronary Artery Risk Development in Young Adults Study (CARDIA) is supported by contracts HHSN268201800003I, HHSN268201800004I, HHSN268201800005I, HHSN268201800006I, and HHSN268201800007I from the National Heart, Lung, and Blood Institute (NHLBI). This manuscript has been reviewed by CARDIA for scientific content. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Keywords

Causality
Epigenetics
Joint significant test
Variable selection

ASJC Scopus subject areas

Structural Biology
Biochemistry
Molecular Biology
Computer Science Applications
Applied Mathematics

Access to Document

10.1186/s12859-022-04748-1

Cite this

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title = "HIMA2: high-dimensional mediation analysis and its application in epigenome-wide DNA methylation data",

abstract = "Mediation analysis plays a major role in identifying significant mediators in the pathway between environmental exposures and health outcomes. With advanced data collection technology for large-scale studies, there has been growing research interest in developing methodology for high-dimensional mediation analysis. In this paper we present HIMA2, an extension of the HIMA method (Zhang in Bioinformatics 32:3150–3154, 2016). First, the proposed HIMA2 reduces the dimension of mediators to a manageable level based on the sure independence screening (SIS) method (Fan in J R Stat Soc Ser B 70:849–911, 2008). Second, a de-biased Lasso procedure is implemented for estimating regression parameters. Third, we use a multiple-testing procedure to accurately control the false discovery rate (FDR) when testing high-dimensional mediation hypotheses. We demonstrate its practical performance using Monte Carlo simulation studies and apply our method to identify DNA methylation markers which mediate the pathway from smoking to reduced lung function in the Coronary Artery Risk Development in Young Adults (CARDIA) Study.",

keywords = "Causality, Epigenetics, Joint significant test, Variable selection",

author = "Chamila Perera and Haixiang Zhang and Yinan Zheng and Lifang Hou and Annie Qu and Cheng Zheng and Ke Xie and Lei Liu",

note = "Funding Information: This research was partly supported by NIH/NIA R21 AG 063370, R21 AG068955, and NIH/NCATS UL1 TR002345. The Coronary Artery Risk Development in Young Adults Study (CARDIA) is supported by contracts HHSN268201800003I, HHSN268201800004I, HHSN268201800005I, HHSN268201800006I, and HHSN268201800007I from the National Heart, Lung, and Blood Institute (NHLBI). This manuscript has been reviewed by CARDIA for scientific content. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Publisher Copyright: {\textcopyright} 2022, The Author(s).",

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doi = "10.1186/s12859-022-04748-1",

language = "English (US)",

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AU - Hou, Lifang

AU - Qu, Annie

AU - Zheng, Cheng

AU - Xie, Ke

AU - Liu, Lei

N1 - Funding Information: This research was partly supported by NIH/NIA R21 AG 063370, R21 AG068955, and NIH/NCATS UL1 TR002345. The Coronary Artery Risk Development in Young Adults Study (CARDIA) is supported by contracts HHSN268201800003I, HHSN268201800004I, HHSN268201800005I, HHSN268201800006I, and HHSN268201800007I from the National Heart, Lung, and Blood Institute (NHLBI). This manuscript has been reviewed by CARDIA for scientific content. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Publisher Copyright: © 2022, The Author(s).

PY - 2022/12

Y1 - 2022/12

N2 - Mediation analysis plays a major role in identifying significant mediators in the pathway between environmental exposures and health outcomes. With advanced data collection technology for large-scale studies, there has been growing research interest in developing methodology for high-dimensional mediation analysis. In this paper we present HIMA2, an extension of the HIMA method (Zhang in Bioinformatics 32:3150–3154, 2016). First, the proposed HIMA2 reduces the dimension of mediators to a manageable level based on the sure independence screening (SIS) method (Fan in J R Stat Soc Ser B 70:849–911, 2008). Second, a de-biased Lasso procedure is implemented for estimating regression parameters. Third, we use a multiple-testing procedure to accurately control the false discovery rate (FDR) when testing high-dimensional mediation hypotheses. We demonstrate its practical performance using Monte Carlo simulation studies and apply our method to identify DNA methylation markers which mediate the pathway from smoking to reduced lung function in the Coronary Artery Risk Development in Young Adults (CARDIA) Study.

AB - Mediation analysis plays a major role in identifying significant mediators in the pathway between environmental exposures and health outcomes. With advanced data collection technology for large-scale studies, there has been growing research interest in developing methodology for high-dimensional mediation analysis. In this paper we present HIMA2, an extension of the HIMA method (Zhang in Bioinformatics 32:3150–3154, 2016). First, the proposed HIMA2 reduces the dimension of mediators to a manageable level based on the sure independence screening (SIS) method (Fan in J R Stat Soc Ser B 70:849–911, 2008). Second, a de-biased Lasso procedure is implemented for estimating regression parameters. Third, we use a multiple-testing procedure to accurately control the false discovery rate (FDR) when testing high-dimensional mediation hypotheses. We demonstrate its practical performance using Monte Carlo simulation studies and apply our method to identify DNA methylation markers which mediate the pathway from smoking to reduced lung function in the Coronary Artery Risk Development in Young Adults (CARDIA) Study.

KW - Causality

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HIMA2: high-dimensional mediation analysis and its application in epigenome-wide DNA methylation data

Abstract

Funding

Keywords

ASJC Scopus subject areas

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