ArticleBriefings in bioinformatics2025
High-dimensional mediation analysis for longitudinal mediators and survival outcomes.
Lili Liu, Haixiang Zhang, Yinan Zheng, Tao Gao, Cheng Zheng, Kai Zhang, Lifang Hou, Lei Liu
Abstract read
In one paragraphArticle in Briefings in bioinformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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2 · The registryThe trial behind it
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4 · The recordCorrections and comments
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5 · Who and what moneyAuthors and funding
8 authors.
Lili LiuCenter for Biostatistics and Data Science, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO 63110, United States.
Haixiang ZhangCenter for Applied Mathematics, Tianjin University, No. 92 Weijin Road, Nankai District, Tianjin 300072, China.
Yinan ZhengDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 N. Lake Shore Drive, Chicago, IL 60611, United States.ORCID 0000-0002-2006-7320 Tao GaoDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 N. Lake Shore Drive, Chicago, IL 60611, United States.
Cheng ZhengDepartment of Biostatistics, University of Nebraska Medical Center, 42nd and Emile Streets, Omaha, NE 68198, United States.ORCID 0000-0002-6562-870X Kai ZhangDepartment of Population and Community Health, College of Public Health, The University of North Texas Health Science Center at Fort Worth, 3500 Camp Bowie Blvd, Fort Worth, TX 76107, United States.
Lifang HouDepartment of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 N. Lake Shore Drive, Chicago, IL 60611, United States.
Lei LiuCenter for Biostatistics and Data Science, Washington University in St. Louis, 660 S. Euclid Ave, St. Louis, MO 63110, United States.ORCID 0000-0003-1844-338X Funding
WU INSTITUTE OF CLINICAL AND TRANSLATIONAL SCIENCESUL1TR002345 · NCATS · WASHINGTON UNIVERSITY · PI William G. Powderly · 2017 to 2026
$97.8MStudies of Rare Genetic Variation in the Isolated Population of SardiniaR01HL117626 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ABECASIS, GONCALO · 2013 to 2016
$10.5MRare variants and NHLBI traits in deeply phenotyped cohortsR01HL120393 · NHLBI · UNIVERSITY OF WASHINGTON · PI PSATY, BRUCE M, RICE, KENNETH M. · 2014 to 2016
$8.9MRare variants and NHLBI traits in deeply phenotyped cohortsU01HL120393 · NHLBI · UNIVERSITY OF WASHINGTON · PI PSATY, BRUCE M, RICE, KENNETH M. · 2017 to 2018
$5.6MBlood mitochondrial DNA biomarkers of midlife cognitive decline and adverse brain imaging changes - A longitudinal investigation in the CARDIA population‐based cohort studyR01AG069120 · NIA · NORTHWESTERN UNIVERSITY AT CHICAGO · PI HOU, LIFANG, YAFFE, KRISTINE · 2020 to 2024
$4.0MEpigenomic landscape of individual- and neighborhood-level social disadvantages and cardiovascular health disparityR01AG081244 · NIA · NORTHWESTERN UNIVERSITY AT CHICAGO · PI HOU, LIFANG, LIU, LEI · 2022 to 2025
$2.2MInnovative Analytical Methods for DNA Methylation AgeR21AG068955 · NIA · WASHINGTON UNIVERSITY · PI LIU, LEI, ZHENG, YINAN · 2021 to 2022
$448kHigh Dimensional Mediation Analysis for DNA Methylation Markers Mediating Cardiovascular Health Metrics and Cardiovascular DiseasesR21AG063370 · NIA · WASHINGTON UNIVERSITY · PI HOU, LIFANG, LIU, LEI · 2019 to 2020
$447kKeck School of Medicine of the University of Southern California HHSN268201600038IMolecular Genomics CoreNational Heart, Lung and Blood InstituteNCATS NIH HHS UL1 TR002345NHLBI NIH HHS HHSN268201600038CNHLBI NIH HHS HHSN268201800001CNHLBI NIH HHS R01 HL117626NHLBI NIH HHS R01 HL120393NHLBI NIH HHS U01 HL120393NIA NIH HHS R01 AG069120NIA NIH HHS R01 AG081244NIA NIH HHS R21 AG063370NIA NIH HHS R21 AG068955NIH HHS R21 AG063370TOPMed Data Coordinating Center R01HL-120393TOPMed Informatics Research Center 3R01HL-117626-02S1Trans-Omics in Precision Medicine
6 · The paper itselfAbstract
Mediation analysis with high-dimensional mediators is crucial for identifying epigenetic pathways linking environmental exposures to health outcomes. However, high-dimensional mediation analysis methods for longitudinal mediators and a survival outcome remain underdeveloped. This study fills that gap by introducing a method that captures mediation effects over time using multivariate, longitudinally measured time-varying mediators. Our approach uses a longitudinal mixed effects model to examine the relationship between the exposure and the mediating process. We connect the mediating process to the survival outcome using a Cox proportional hazards model with time-varying mediators. To handle high-dimensional data, we first employ a mediation-based sure independence screening method for dimension reduction. A Lasso inference procedure is further utilized to identify significant time-varying mediators. We adopt a joint significance test to accurately control the family wise error rate in testing high-dimensional mediation hypotheses. Simulation studies and an analysis of the Coronary Artery Risk Development in Young Adults Study demonstrate the utility and validity of our method.
Indexed as
Mediation AnalysisComputer SimulationFemaleHumansLongitudinal StudiesMaleProportional Hazards ModelsSurvival Analysishigh-dimensional mediation analysislongitudinal datasurvival outcomevariable selection
Identifiers
PMID40350699
PMCPMC12066418
What OpenQuestion holds
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LicenceCC BY-NC
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