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

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.

[1]  Geoffrey J McLachlan,et al.  Selection bias in gene extraction on the basis of microarray gene-expression data , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[2]  I. Helland.  ON THE STRUCTURE OF PARTIAL LEAST SQUARES REGRESSION , 1988 .

[3]  B. Efron.  The jackknife, the bootstrap, and other resampling plans , 1987 .

[4]  David L. Donoho,et al.  De-noising by soft-thresholding , 1995, IEEE Trans. Inf. Theory.

[5]  Jianqing Fan,et al.  Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties , 2001 .

[6]  V. Jeevanandam,et al.  Altered myocardial phenotype after mechanical support in human beings with advanced cardiomyopathy. , 1997, The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation.

[7]  Anders Berglund,et al.  A multivariate approach applied to microarray data for identification of genes with cell cycle-coupled transcription , 2003, Bioinform..

[8]  Danh V. Nguyen,et al.  Partial least squares proportional hazard regression for application to DNA microarray survival data , 2002, Bioinform..

[9]  H Harasaki,et al.  Implantable left ventricular assist device. Approaching an alternative for end-stage heart failure. Implantable LVAD Study Group. , 1994, Circulation.

[10]  M. Radmacher,et al.  Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification. , 2003, Journal of the National Cancer Institute.

[11]  P. Garthwaite.  An Interpretation of Partial Least Squares , 1994 .

[12]  H Harasaki,et al.  Structural and left ventricular histologic changes after implantable LVAD insertion. , 1995, The Annals of thoracic surgery.

[13]  Matthew West,et al.  Bayesian factor regression models in the''large p , 2003 .

[14]  Lu Tian,et al.  Linking gene expression data with patient survival times using partial least squares , 2002, ISMB.

[15]  M C Oz,et al.  Implantable left ventricular assist devices. , 1998, The New England journal of medicine.

[16]  M C Oz,et al.  Transient normalization of systolic and diastolic function after support with a left ventricular assist device in a patient with dilated cardiomyopathy. , 1996, The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation.

[17]  R. Tibshirani.  Regression Shrinkage and Selection via the Lasso , 1996 .

[18]  E. Antman,et al.  ACC/AHA PRACTICE GUIDELINES ACC/AHA Guidelines for the Evaluation and Management of Chronic Heart Failure in the Adult: Executive Summary , 2002 .

[19]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[20]  I. Johnstone,et al.  Ideal spatial adaptation by wavelet shrinkage , 1994 .

[21]  Danh V. Nguyen,et al.  Tumor classification by partial least squares using microarray gene expression data , 2002, Bioinform..

[22]  R. Tibshirani,et al.  Diagnosis of multiple cancer types by shrunken centroids of gene expression , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[23]  A. Höskuldsson.  PLS regression methods , 1988 .

[24]  S. Houser,et al.  Myocyte recovery after mechanical circulatory support in humans with end-stage heart failure. , 1998, Circulation.

[25]  William A. Smith,et al.  Mechanical Circulatory Support--a Long and Winding Road , 2002, Science.

[26]  Douglas M. Hawkins,et al.  Exploring Blood Spectra for Signs of Ovarian Cancer , 2003 .

[27]  Danh V. Nguyen,et al.  Multi-class cancer classification via partial least squares with gene expression profiles , 2002, Bioinform..

[28]  C. Fraser,et al.  Hemodynamic and physiologic changes during support with an implantable left ventricular assist device. , 1995, The Journal of thoracic and cardiovascular surgery.

[29]  Wei Pan,et al.  Linear regression and two-class classification with gene expression data , 2003, Bioinform..