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.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117 J+Am+Soc+Nephrol
2014 ; 25
(10
): 2267-77
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Molecular microscope strategy to improve risk stratification in early
antibody-mediated kidney allograft rejection
#MMPMID24700874
Loupy A
; Lefaucheur C
; Vernerey D
; Chang J
; Hidalgo LG
; Beuscart T
; Verine J
; Aubert O
; Dubleumortier S
; Duong van Huyen JP
; Jouven X
; Glotz D
; Legendre C
; Halloran PF
J Am Soc Nephrol
2014[Oct]; 25
(10
): 2267-77
PMID24700874
show ga
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 ABMR 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 [HR], 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% CI, 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.