Molecular Microscope Strategy to Improve Risk Stratification in Early Antibody-Mediated Kidney Allograft Rejection

Affiliation auteurs!!!! Error affiliation !!!!
TitreMolecular Microscope Strategy to Improve Risk Stratification in Early Antibody-Mediated Kidney Allograft Rejection
Type de publicationJournal Article
Year of Publication2014
AuteursLoupy A, Lefaucheur C, Vernerey D, Chang J, Hidalgo LG, Beuscart T, Verine J, Aubert O, Dubleurnortier S, van Huyen J-PDuong, Jouven X, Glotz D, Legendre C, Halloran PF
JournalJOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY
Volume25
Pagination2267-2277
Date PublishedOCT
Type of ArticleArticle
ISSN1046-6673
Résumé

Antibody-mediated rejection (ABMR) is the leading cause of kidney allograft loss. We investigated whether the addition of gene expression measurements to conventional methods could serve as a molecular microscope to identify kidneys with ABMR that are at high risk for failure. We studied 939 consecutive kidney recipients at Necker Hospital (2004-2010; principal cohort) and 321 kidney recipients at Saint Louis Hospital (2006-2010; validation cohort) and assessed patients with ABM R in the first 1 year post-transplant. In addition to conventional features, we assessed microarray-based gene expression in transplant biopsy specimens using relevant molecular measurements: the ABMR Molecular Score and endothelial donor-specific antibody-selective transcript set. The main outcomes were kidney transplant loss and progression to chronic transplant injury. We identified 74 patients with ABMR in the principal cohort and 54 patients with ABMR in the validation cohort. Conventional features independently associated with failure were donor age and humoral histologic score (g+ptc+v+cg+C4d). Adjusting for conventional features, ABMR Molecular Score (hazard ratio [H RI, 2.22; 95% confidence interval [95% CI] 1.37 to 3.58; P=0.001) and endothelial donor-specific antibody-selective transcripts (HR, 3.02; 95% CI, 1.00 to 9.16; P<0.05) independently associated with an increased risk of graft loss. The results were replicated in the independent validation group. Adding a gene expression assessment to a traditional risk model improved the stratification of patients at risk for graft failure (continuous net reclassification improvement, 1.01; 95% Cl, 0.57 to 1.46; P<0.001; integrated discrimination improvement, 0.16; P<0.001). Compared with conventional assessment, the addition of gene expression measurement in kidney transplants with ABMR improves stratification of patients at high risk for graft loss.

DOI10.1681/ASN.2013111149