PTG
  • Home
  • Research
    • PTG Research
    • iBox technology
    • Publications
    • Collaborations
    • Granted Projects
    • Awards
    • Database access
  • Platforms
    • Technical & Analytical Platforms
  • Team
    • Current team
    • PTG alumni
  • News & Media
    • Latest news
    • Photo and Video Gallery
    • PTG in the media
  • Job offers
  • About

Value of Donor-Specific Anti-HLA Antibody Monitoring and Characterization for Risk Stratification of Kidney Allograft Loss

1/31/2017

 
Picture
Denis Viglietti et al.
J Am Soc Nephrol. 2017 Feb;28(2):702-715.
PMID: 27493255

Abstract
The diagnosis system for allograft loss lacks accurate individual risk stratification on the basis of donor-specific anti-HLA antibody (anti-HLA DSA) characterization. We investigated whether systematic monitoring of DSA with extensive characterization increases performance in predicting kidney allograft loss. This prospective study included 851 kidney recipients transplanted between 2008 and 2010 who were systematically screened for DSA at transplant, 1 and 2 years post-transplant, and the time of post-transplant clinical events. We assessed DSA characteristics and performed systematic allograft biopsies at the time of post-transplant serum evaluation. At transplant, 110 (12.9%) patients had DSAs; post-transplant screening identified 186 (21.9%) DSA-positive patients. Post-transplant DSA monitoring improved the prediction of allograft loss when added to a model that included traditional determinants of allograft loss (increase in c statistic from 0.67; 95% confidence interval [95% CI], 0.62 to 0.73 to 0.72; 95% CI, 0.67 to 0.77). Addition of DSA IgG3 positivity or C1q binding capacity increased discrimination performance of the traditional model at transplant and post-transplant. Compared with DSA mean fluorescence intensity, DSA IgG3 positivity and C1q binding capacity adequately reclassified patients at lower or higher risk for allograft loss at transplant (category-free net reclassification index, 1.30; 95% CI, 0.94 to 1.67; P<0.001 and 0.93; 95% CI, 0.49 to 1.36; P<0.001, respectively) and post-transplant (category-free net reclassification index, 1.33; 95% CI, 1.03 to 1.62; P<0.001 and 0.95; 95% CI, 0.62 to 1.28; P<0.001, respectively). Thus, pre- and post-transplant DSA monitoring and characterization may improve individual risk stratification for kidney allograft loss.
Picture

From Humoral Theory to Performant Risk Stratification in Kidney Transplantation

1/2/2017

 
Picture
Carmen Lefaucheur et al.
J Immunol Res. 2017;2017:5201098.
PMID: 28133619
Abstract
The purpose of the present review is to describe how we improve the model for risk stratification of transplant outcomes in kidney transplantation by incorporating the novel insights of donor-specific anti-HLA antibody (DSA) characteristics. The detection of anti-HLA DSA is widely used for the assessment of pre- and posttransplant risks of rejection and allograft loss; however, not all anti-HLA DSA carry the same risk for transplant outcomes. These antibodies have been shown to cause a wide spectrum of effects on allografts, ranging from the absence of injury to indolent or full-blown acute antibody-mediated rejection. Consequently, the presence of circulating anti-HLA DSA does not provide a sufficient level of accuracy for the risk stratification of allograft outcomes. Enhancing the predictive performance of anti-HLA DSA is currently one of the most pressing unmet needs for facilitating individualized treatment choices that may improve outcomes. Recent advancements in the assessment of anti-HLA DSA properties, including their strength, complement-binding capacity, and IgG subclass composition, significantly improved the risk stratification model to predict allograft injury and failure. Although risk stratification based on anti-HLA DSA properties appears promising, further specific studies that address immunological risk stratification in large and unselected populations are required to define the benefits and cost-effectiveness of such comprehensive assessment prior to clinical implementation.
Picture

Gene Expression Profiling for the Identification and Classification of Antibody-Mediated Heart Rejection

1/1/2017

 
Picture
Alexandre Loupy et al.
​Circulation. 2017 Mar 7;135(10):917-935.
PMID: 28148598
Abstract
Antibody-mediated rejection (AMR) contributes to heart allograft loss. However, an important knowledge gap remains in terms of the pathophysiology of AMR and how detection of immune activity, injury degree, and stage could be improved by intragraft gene expression profiling.
We prospectively monitored 617 heart transplant recipients referred from 4 French transplant centers (January 1, 2006-January 1, 2011) for AMR. We compared patients with AMR (n=55) with a matched control group of 55 patients without AMR. We characterized all patients using histopathology (ISHLT [International Society for Heart and Lung Transplantation] 2013 grades), immunostaining, and circulating anti-HLA donor-specific antibodies at the time of biopsy, together with systematic gene expression assessments of the allograft tissue, using microarrays. Effector cells were evaluated with in vitro human cell cultures. We studied a validation cohort of 98 heart recipients transplanted in Edmonton, AB, Canada, including 27 cases of AMR and 71 controls.
A total of 240 heart transplant endomyocardial biopsies were assessed. AMR showed a distinct pattern of injury characterized by endothelial activation with microcirculatory inflammation by monocytes/macrophages and natural killer (NK) cells. We also observed selective changes in endothelial/angiogenesis and NK cell transcripts, including CD16A signaling and interferon-γ-inducible genes. The AMR-selective gene sets accurately discriminated patients with AMR from those without and included NK transcripts (area under the curve=0.87), endothelial activation transcripts (area under the curve=0.80), macrophage transcripts (area under the curve=0.86), and interferon-γ transcripts (area under the curve=0.84; P<0.0001 for all comparisons). These 4 gene sets showed increased expression with increasing pathological AMR (pAMR) International Society for Heart and Lung Transplantation grade (P<0.001) and association with donor-specific antibody levels. The unsupervised principal components analysis demonstrated a high proportion of molecularly inactive pAMR1(I+), and there was significant molecular overlap between pAMR1(H+) and full-blown pAMR2/3 cases. Endothelial activation transcripts, interferon-γ, and NK transcripts showed association with chronic allograft vasculopathy. The molecular architecture and selective AMR transcripts, together with gene set discrimination capacity for AMR identified in the discovery set, were reproduced in the validation cohort.

​
Tissue-based measurements of specific pathogenesis-based transcripts reflecting NK burden, endothelial activation, macrophage burden, and interferon-γ effects accurately classify AMR and correlate with degree of injury and disease activity. This study illustrates the clinical potential of a tissue-based analysis of gene transcripts to refine diagnosis of heart transplant rejection.
Picture

    Paris Transplant Group

    Our global aim is to accelerate the translation of immunological and gene expression discoveries into the clinical field by filling the gap between basic science and applied biomedical researches.

    CATEGORIES

    Awards
    Events
    Job offers
    Press Releases
    Publications

    See also

    Press coverage
    Video and ​Picture gallery

    ALl

    All
    Alexandre Loupy
    Antoine Bouquegneau
    Antoine Durrbach
    Antoine Roux
    Awards
    Blaise Robin
    Carmen Lefaucheur
    Charlotte Debiais
    Charlotte Loheac
    Christophe Legendre
    Daniel Yoo
    Dany Anglicheau
    Denis Glotz
    Denis Viglietti
    Dina Zielinski
    Elodie Bailly
    Events
    Gillian Divard
    Guillaume Bonnet
    Guillaume Coutance
    Huanxi Zhang
    Jean Luc Taupin
    Jean Paul Duong Van Huyen
    Jean Philippe Empana
    Jessy Dagobert
    Job
    Juliette Gueguen
    Kevin Louis
    Marc Raynaud
    Marie-Cécile Bories
    Marion Rabant
    Maud Racape
    Michel Delahousse
    Olivier Aubert
    Pascal Leprince
    Patrick Bruneval
    Peter Reese
    Press Releases
    Publications
    Shaida Varnous
    Valentin Goutaudier
    Xavier Jouven
    Yassine Bouatou
    Zeynep Demir

    Archives

    October 2021
    September 2021
    August 2021
    July 2021
    February 2021
    January 2021
    December 2020
    November 2020
    October 2020
    September 2020
    August 2020
    July 2020
    May 2020
    March 2020
    January 2020
    December 2019
    October 2019
    September 2019
    August 2019
    June 2019
    May 2019
    March 2019
    February 2019
    December 2018
    September 2018
    May 2018
    February 2018
    January 2018
    December 2017
    November 2017
    October 2017
    September 2017
    June 2017
    May 2017
    April 2017
    March 2017
    February 2017
    January 2017
    December 2016
    November 2016
    June 2016
    April 2016
    October 2015
    June 2015
    August 2014
    January 2014
    September 2013
    January 2013
    June 2011
    August 2010
    May 2009

    RSS Feed

Paris Transplant Group

About PTG
PTG Team
​​Careers at PTG
​Latest News
​
Awards
Video and Picture Gallery

PTG in the Press
​Contact us

Research

iBox technology
PTG Research
PTG Publications
Covid-related research 🔓

Platforms

Technical platforms

Partnerships

Research collaborations
​Database access
​

Search

LEGAL NOTICE AND PRIVACY POLICY
© COPYRIGHT 2022. ALL RIGHTS RESERVED.

 LABS EXPLORER for the PARIS TRANSPLANT GROUP.
  • Home
  • Research
    • PTG Research
    • iBox technology
    • Publications
    • Collaborations
    • Granted Projects
    • Awards
    • Database access
  • Platforms
    • Technical & Analytical Platforms
  • Team
    • Current team
    • PTG alumni
  • News & Media
    • Latest news
    • Photo and Video Gallery
    • PTG in the media
  • Job offers
  • About