Title: Translation of disease associated gene signatures across tissues

Authors: Adetayo Kasim; Ziv Shkedy; Dan Lin; Suzy Van Sanden; Josè Cortiñas Abrahantes; Hinrich W.H. Göhlmann; Luc Bijnens; Dani Yekutieli; Michael Camilleri; Jeroen Aerssens; Willem Talloen

Addresses: Wolfson Research Institute for Health and Wellbeing, Durham University Queen's Campus, Stockton-on-Tees, TS17 6BH, UK ' Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Diepenbeek, Belgium ' Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Diepenbeek, Belgium ' Janssen Pharmaceutica NV, Beerse, Belgium ' European Food Safety Authority, Parma, Italy ' Janssen Pharmaceutica NV, Beerse, Belgium ' Janssen Pharmaceutica NV, Beerse, Belgium ' Department of Statistics and Operational Research, Tel Aviv University, Tel Aviv, Israel ' Mayo Clinic College of Medicine, Rochester, MN, USA ' Janssen Pharmaceutica NV, Beerse, Belgium ' Janssen Pharmaceutica NV, Beerse, Belgium

Abstract: It has recently been shown that disease associated gene signatures can be identified by profiling tissue other than the disease related tissue. In this paper, we investigate gene signatures for Irritable Bowel Syndrome (IBS) using gene expression profiling of both disease related tissue (colon) and surrogate tissue (rectum). Gene specific joint ANOVA models were used to investigate differentially expressed genes between the IBS patients and the healthy controls taken into account both intra and inter tissue dependencies among expression levels of the same gene. Classification algorithms in combination with feature selection methods were used to investigate the predictive power of gene expression levels from the surrogate and the target tissues. We conclude based on the analyses that expression profiles of the colon and the rectum tissue could result in better predictive accuracy if the disease associated genes are known.

Keywords: gene expression; joint modelling; surrogate markers; biomarkers; target tissues; surrogate tissue; feature selection; classification; class prediction; irritable bowel syndrome; IBS; disease associated gene signatures; ANOVA; colon tissue; rectum tissue; bioinformatics.

DOI: 10.1504/IJDMB.2015.067321

International Journal of Data Mining and Bioinformatics, 2015 Vol.11 No.3, pp.301 - 313

Available online: 05 Feb 2015

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