Novel strategy for disease risk prediction incorporating predicted gene expression and DNA methylation data: a multi‐phased study of prostate cancer

Abstract

DNA methylation and gene expression are known to play important roles in the etiology of human diseases such as prostate cancer (PCa). However, it has not yet been possible to incorporate information of DNA methylation and gene expression into polygenic risk scores (PRSs). Here, we aimed to develop and validate an improved PRS for PCa risk by incorporating genetically predicted gene expression and DNA methylation, and other genomic information using an integrative method.

Document Details

Document Type
Pub Defense Publication
Publication Date
Sep 14, 2021
Source ID
10.1002/cac2.12205

Entities

People

  • Austin King
  • Chong Wu
  • Christopher A. Haiman
  • David V. Conti
  • Guimin Gao
  • Hong‐wen Deng
  • Jingjing Zhu
  • Jirong Long
  • Jong Y Park
  • Karen E. Knudsen
  • Lang Wu
  • Liang Wang
  • Qing Lu
  • Timothy R Rebbeck
  • Wei Pan
  • Wei Xing Zheng
  • Xiaoran Tong
  • Yaohua Yang

Organizations

  • Cancer Research UK
  • Dana–Farber Cancer Institute
  • Florida State University
  • H. Lee Moffitt Cancer Center & Research Institute
  • Harvard University
  • Michigan State University
  • National Institutes of Health
  • Thomas Jefferson University
  • Tulane University of Louisiana
  • University of Chicago
  • University of Florida
  • University of Hawaiʻi System
  • University of Minnesota
  • University of Southern California
  • Vanderbilt University

Tags

Fields of Study

  • Biology

Readers

  • Computational Modeling and Simulation
  • Molecular and genetic basis of cancer.

Technology Areas

  • Biotechnology