Modeling the relationship between LVAD support time and gene expression changes in the human heart by penalized partial least squares

Xiaohong Huang, Wei Pan, Soon Park, Xinqiang Han, Leslie W. Miller, Jennifer Hall

Research output: Contribution to journalArticle

34 Scopus citations

Abstract

Motivation: Heart failure affects more than 20 million people in the world. Heart transplantation is the most effective therapy, but the number of eligible patients far outweighs the number of available donor hearts. The left mechanical ventricular assist device (LVAD) has been developed as a successful substitution therapy that aids the failing ventricle while a patient is waiting for the donor heart. We obtained genomics data from paired human heart samples harvested at the time of LVAD implant and explant. The heart failure patients in our study were supported by the LVAD for various periods of time. The goal of this study is to model the relationship between the time of LVAD support and gene expression changes. Results: To serve the purpose, we propose a novel penalized partial least squares (PPLS) method to build a regression model. Compared with partial least squares and Breiman's random forest method, PPLS gives the best prediction results for the LVAD data.

Original languageEnglish (US)
Pages (from-to)888-894
Number of pages7
JournalBioinformatics
Volume20
Issue number6
DOIs
StatePublished - Apr 12 2004

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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