BACKGROUND: Significant progress has been made in cardiac transplantation over the past 30 years; however, the means for detection of acute cardiac allograft rejection remains in need of improvement. At present, the endomyocardial biopsy, an invasive and inconvenient procedure for patients, is required for the surveillance and diagnosis of acute cardiac allograft rejection. In the Biomarkers in Transplantation initiative, we investigated gene expression profiles in peripheral blood of cardiac transplant subjects as potential biomarkers for diagnosis of allograft rejection. METHODS: Whole blood samples were obtained from 28 cardiac transplant subjects who consented to the study. Serial samples were collected from pre-transplant through 3 years post-transplant according to the standard protocol. Temporally correspondent biopsies were also collected, reviewed in a blinded manner, and graded according to current ISHLT guidelines. Blood samples were analyzed using Affymetrix microarrays. Genomic profiles were compared in subjects with acute rejection (AR; ISHLT Grade > or =2R) and no rejection (NR; Grade 0R). Biomarker panel genes were identified using linear discriminant analysis. RESULTS: We found 1,295 differentially expressed probe-sets between AR and NR samples and developed a 12-gene biomarker panel that classifies our internal validation samples with 83% sensitivity and 100% specificity. CONCLUSIONS: Based on our current results, we believe whole blood genomic biomarkers hold great potential in the diagnosis of acute cardiac allograft rejection. A prospective, Canada-wide trial will be conducted shortly to further evaluate the classifier panel in diverse patients and a range of clinical programs.
BACKGROUND: Significant progress has been made in cardiac transplantation over the past 30 years; however, the means for detection of acute cardiac allograft rejection remains in need of improvement. At present, the endomyocardial biopsy, an invasive and inconvenient procedure for patients, is required for the surveillance and diagnosis of acute cardiac allograft rejection. In the Biomarkers in Transplantation initiative, we investigated gene expression profiles in peripheral blood of cardiac transplant subjects as potential biomarkers for diagnosis of allograft rejection. METHODS: Whole blood samples were obtained from 28 cardiac transplant subjects who consented to the study. Serial samples were collected from pre-transplant through 3 years post-transplant according to the standard protocol. Temporally correspondent biopsies were also collected, reviewed in a blinded manner, and graded according to current ISHLT guidelines. Blood samples were analyzed using Affymetrix microarrays. Genomic profiles were compared in subjects with acute rejection (AR; ISHLT Grade > or =2R) and no rejection (NR; Grade 0R). Biomarker panel genes were identified using linear discriminant analysis. RESULTS: We found 1,295 differentially expressed probe-sets between AR and NR samples and developed a 12-gene biomarker panel that classifies our internal validation samples with 83% sensitivity and 100% specificity. CONCLUSIONS: Based on our current results, we believe whole blood genomic biomarkers hold great potential in the diagnosis of acute cardiac allograft rejection. A prospective, Canada-wide trial will be conducted shortly to further evaluate the classifier panel in diverse patients and a range of clinical programs.
Authors: R C Starling; J Stehlik; D A Baran; B Armstrong; J R Stone; D Ikle; Y Morrison; N D Bridges; P Putheti; T B Strom; M Bhasin; I Guleria; A Chandraker; M Sayegh; K P Daly; D M Briscoe; P S Heeger Journal: Am J Transplant Date: 2015-08-10 Impact factor: 8.086
Authors: Mary E Winn; Marian Shaw; Craig April; Brandy Klotzle; Jian-Bing Fan; Sarah S Murray; Nicholas J Schork Journal: BMC Genomics Date: 2011-08-15 Impact factor: 3.969
Authors: Casey P Shannon; Zsuzsanna Hollander; Janet Wilson-McManus; Robert Balshaw; Raymond T Ng; Robert McMaster; Bruce M McManus; Paul A Keown; Scott J Tebbutt Journal: Bioinform Biol Insights Date: 2012-04-10
Authors: Gabriela V Cohen Freue; Anna Meredith; Derek Smith; Axel Bergman; Mayu Sasaki; Karen K Y Lam; Zsuzsanna Hollander; Nina Opushneva; Mandeep Takhar; David Lin; Janet Wilson-McManus; Robert Balshaw; Paul A Keown; Christoph H Borchers; Bruce McManus; Raymond T Ng; W Robert McMaster Journal: PLoS Comput Biol Date: 2013-04-04 Impact factor: 4.475
Authors: Oliver P Günther; Virginia Chen; Gabriela Cohen Freue; Robert F Balshaw; Scott J Tebbutt; Zsuzsanna Hollander; Mandeep Takhar; W Robert McMaster; Bruce M McManus; Paul A Keown; Raymond T Ng Journal: BMC Bioinformatics Date: 2012-12-08 Impact factor: 3.169