Donor Derived Cell-free DNA and Rejection of Kidney Allografts
Conditions: Kidney Rejection Transplant
Sponsor: Paris Translational Research Center for Organ Transplantation

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MINIMAL RISKS AND CONSTRAINTS HUMAN RESEARCH STUDY 
 
 
Version N°1.1 of 01/03/2020 
Protocol code number: 
ddcfDNA_study001 
 
 
 
Coordinating Investigator: 
Professor Alexandre Loupy 
Department of Kidney Transplantation 
Necker Hospital 
149 rue de Sèvres 
75015 Paris, France 
Phone: +33 1 53 98 80 00 
Fax: +33 1 53 98 79 54 
E-mail: alexandre.loupy@aphp.fr 
 
 
Scientific Director: 
Doctor Olivier Aubert 
Department of Nephrology 
Necker Hospital 
149 rue de Sèvres 
75015 Paris, France 
Phone: +33 1 44 49 54 38 
Fax: +33 1 44 49 42 30 
E-mail: olivier.aubert@aphp.fr 
 
 
Sponsor: OrganX Foundation 
Baarerstrasse 6300 Zug, Switzerland 
 
Donor derived cell-free DNA and rejection of kidney allografts 

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PROTOCOL SIGNATURE PAGE 
 
MINIMAL RISKS AND CONSTRAINTS HUMAN RESEARCH STUDY 
Protocol code number: ddcfDNA_study001 
Title: " Donor derived cell-free DNA and rejection of kidney allografts " 
Version N°1.1 of: 01/03/2020 
 
 
The research is carried out in accordance with the current version of the protocol, with GCP and 
with all statutory and regulatory requirements. 
 
Coordinating Investigator: 
Pr Alexandre Loupy 
Department of Kidney Transplantation 
Necker Hospital 
Paris, France 
 
Date: ……………/………/……….. 
Signature: 
 
Scientific Director: 
Dr Olivier Aubert 
Department of Kidney 
Transplantation Necker 
Hospital 
Paris, France
 
Date: ……………/………/……….. 
Signature: 
 
Sponsor  
OrganX Foundation 
Baarerstrasse 6300 Zug,Switzerland 
 
 
 
Date: ……………/………/……….. 
Signature:

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1 
SUMMARY 
 
Full title 
Donor derived cell-free DNA and rejection of kidney allografts 
Coordinating Investigator 
Pr Alexandre Loupy 
Scientific Director (if 
applicable) 
Dr Olivier Aubert 
Sponsor 
Organ X Foundation  
Scientific justification 
Allograft rejection is a major problem worldwide and results in the 
loss of thousands of transplants every year, with devastating 
consequences for patients in terms of mortality, morbidity and 
quality of life. With a prevalence of approximately 20% in the first-
year after kidney transplantation, allograft rejection also represents 
a considerable economic burden for health care systems with the 
associated downstream cost related to graft failure and return to 
dialysis. The standard strategy to monitor rejection is based on 
surveillance of nonspecific functional markers such as serum 
creatinine level, estimated glomerular filtration rate, proteinuria and 
circulating donor-specific anti-HLA antibodies (DSA), which lack 
sensitivity and specificity. The current gold standard for diagnosing 
allograft rejection is the biopsy which is a potentially harmful, costly 
and often unnecessary procedure. 
Recently, one promising non-invasive biomarkers has emerged in 
various fields such as oncology or gynecology for the monitoring of 
the patients: the cell-free DNA. In transplantation, donor-derived 
cell-free DNA (dd-cfDNA) detected in the blood of transplant 
recipients has been proposed as a noninvasive biomarker for the 
detection of rejection. However, dd-cfDNA has not been assessed 
in an unselected and deeply phenotyped population, with the 
comparison to the conventional parameters including functional, 
clinical or immunological factors to monitor patients and detect 
rejection.  
Main objective and primary 
endpoint 
Main objectives 
To assess the association of dd-cfDNA with the presence, activity 
and severity of allograft rejection, and determine whether dd-cfDNA 
adds value to standard of care monitoring parameters in detecting 
kidney allograft rejection 

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 Primary endpoint 
 Kidney allograft rejection (all causes) 
 Time Frame: Up to 10 years after kidney transplantation 
Design of the study 
Type of study: Multicenter international study  
Time Perspective: prospective 
Population of study 
participants 
Derivation cohort: Prospective cohort of kidney transplant recipients 
recruited in 2 French centers  
 
Validation cohort: kidney transplant recipients in 11 North-American 
centers and 1 Belgian center with clinical, biological, histological and 
immunological data, and dd-cfDNA assessment. 
 
Inclusion criteria 
• 
Recipients transplanted from a deceased or living donor, who 
undergone a kidney allograft biopsy with clinical, biological, 
histological and immunological data. Written informed consent 
at the time of transplantation for the center database. 
Exclusion criteria 
• 
Combined organ transplantation 
• 
Pregnant women 
• 
Bone marrow transplant 
Interventions or product under 
investigation 
This study involves minimal risk and constraints. The intervention 
consists in the evaluation of the risk of allograft rejection based on 
parameters measured as part of the standard of care and dd-cfDNA. 
No medicinal product is under investigation in this protocol. 
Other interventions added by 
the study 
Gene expression measurement in allograft biopsies 
Expected benefits for the 
participants and for society 
There will be no immediate individual benefit for the patient to 
participate in the study. 
This study will be the first that evaluates the independent 
association of dd-cfDNA with rejection and its added value in 
addition to conventional features to predict kidney allograft 
rejection.  
This first integrative system will improve the patient monitoring and 
will help physicians in decision-making process. 

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Minimal risks and constraints 
added by the study 
The intervention added by the study represents minimal risk and 
constraints for the patient as it will be embedded within the 
standard of care. 
No additional puncture is performed; only one additional blood 
tube is taken for the measurement of dd-cfDNA. 
Scope of the study 
Kidney transplantation; non-invasive diagnosis of rejection for 
improving patient monitoring 
Anticipated number of 
participants 
Number of participants with post-transplant risk evaluation: 
Derivation prospective cohort: 1000 patients 
External validation cohort: 1500 patients 
Number of sites 
Multicenter international study involving 14 sites.  
 
Derivation cohort: 
• 
Saint-Louis Hospital, Paris, France 
• 
Necker Hospital, Paris, France 
 
Validation cohort: 
• 
Leuven Hospital, Leuven, Belgium 
• 
Cedars-Sinai, Los Angeles, USA  
• 
UCLA, Los Angeles, USA 
• 
Emory University, Atlanta, USA 
• 
Intermountain Medical Center Transplant Services, Murray, 
USA 
• 
Weill-Cornell Medical School, New York, USA 
• 
New York Hospital Medical Center, New York, USA 
• 
Virginia Commonwealth University, Richmond, USA 
• 
Washington University School of Medicine in St. Louis, St. 
Louis, pediatric department 
• 
Washington University School of Medicine in St. Louis, St. 
Louis, adult department 
• 
Transplant Institute, Tampa General Hospital, Tampa, USA 
• 
University of Wisconsin, Madison, USA 
Schedule for the study 
Inclusion period 2011- 2022;  
Participation period (follow-up): Derivation and validation cohorts: 
up to August 2022 
 

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Expected number of 
enrolments per site 
Derivation cohort (n=1000) 
 
External validation cohorts (n=1500) 
Statistical analysis 
Continuous variables will be described using means and standard 
deviations (SDs) or median and the interquartile range. We will 
compare means and proportions between groups using Student’s t-
test, analysis of variance (ANOVA) (Mann-Whitney test for donor 
specific antibodies (DSA) mean fluorescent intensity) or the chi-
square test (or Fisher’s exact test if appropriate).  
We will evaluate the association between the dd-cfDNA levels and 
each allograft diagnosis (ABMR, TCMR, Mixed rejection, 
glomerulitis without rejection, polyomavirus nephritis, fibrosis, 
borderline changes, no specific lesions). Then, to investigate the 
association of dd-cfDNA with rejection severity, we will compare the 
mean dd-cfDNA level according to each active and chronic Banff 
lesion score (ranked from 0 to 3). 
 
Evaluation of the association between dd-cfDNA and rejection 
The associations between allograft rejection and clinical, functional, 
and immunologic factors will be first computed using logistic 
regression analyses. The factors identified in these analyses will be 
thereafter included in a final multivariable analysis if the p-value of 
the Wald test is < 0.1. Multivariable logistic regression analysis will 
be performed using a stepwise backward elimination until each 
predictor is associated with allograft rejection with a p-value below 
0.05. The internal validity of the final model will be confirmed using 
a bootstrap procedure, which involves generating 1,000 datasets 
derived from resampling the original dataset and permitting the 
estimation of the biased corrected 95% CI and the accelerated 
bootstrap OR.  
 
Assessment of the added value of dd-cfDNA 
To evaluate the added value of dd-cfDNA, we will assess the 
performances of the reference model (including independent 
standard of care predictors of the final multivariable model) with and 
without dd-cfDNA to evaluate to risk of rejection. The performances 
of the models to predict rejection will be evaluated with the use of 
the accuracy of the model, which will be assessed based on its 
discrimination ability and calibration performance. For each model, 
the discrimination ability (i.e., the ability to separate patients with 
different prognoses) of the final model will be evaluated using Area 
under the curve (AUC). Calibration (the ability to provide unbiased 
rejection predictions in groups of similar patients) will be assessed 
based on a visual examination of the calibration plots. 

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We will follow the TRIPOD (Transparent Reporting of a Multivariable 
Prediction Model for Individual Prognosis or Diagnosis) statement 
for reporting multivariable prediction model development and 
validation.  
 
 
Sensitivity analyses: 
We will investigate the independent association of dd-cfDNA with 
rejection and its added value in predicting rejection in different 
clinical scenarios (biopsies performed during the first year or after 
one-year post-transplantation, according to the subtypes of 
rejection, protocol biopsies or biopsies performed for clinical 
indication) and according to the patient ethnicity.  
 
 
We will use R (version 4.1.2, R Foundation for Statistical 
Computing) and STATA (v17) for the descriptive and prediction 
analyses. Values of p<0.05 will be considered significant, and all 
tests will be 2-tailed. 
 
Sources of monetary support 
The study is funded by the OrganX Foundation