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Activity Number: 561 - Fine-Scale Inference from Aggregate-Level Genomic Data
Type: Invited
Date/Time: Thursday, August 6, 2020 : 3:00 PM to 4:50 PM
Sponsor: Section on Statistics in Genomics and Genetics
Abstract #308071
Title: Testing Cell-Type-Specific Mediation Effects in Genome-Wide Epigenetic Studies
Author(s): Zhonghua Liu * and Xiangyu Luo and Joel Schwartz and Andrea Baccarelli
Companies: University of Hong Kong and Renmin University of China and Harvard University and Columbia University
Keywords: mediation; epigenetics; deconvolution

Current epigenome-wide mediation analysis can only identify DNA methylation CpG sites that mediate a causal effect at bulk level. The measured methylation values are mixed from a heterogeneous population of cells, it is crucial to get fine-grained results by detecting mediation CpG sites in a cell-type-specific way. We propose a novel method MICS (Methylation In a Cell-type-Specific fashion) to identify cell-type-specific mediation effects in genome-wide epigenetic studies. MICS first estimates the cellular compositions via a reference methylation matrix, then uses the estimated cell proportions to obtain the cell-type-specific p-values with respect to the exposure effects on the CpG sites as well as the methylation effects on the outcome, and finally combines the two p-value matrices using a joint-significance-followed by-squaring procedure. We conduct simulation studies to demonstrate that our method has correct type I error control and is powerful and robust under practical settings. We also apply our method to the Normative Aging Study and identify three CpG sites in the monocytes that might mediate the effects of smoking on lung function.

Authors who are presenting talks have a * after their name.

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