Molecular Prediction of Development, Progression or Complications of Kidney, Immune or Transplantation-related Diseases

Condition(s) studied

Investigational drug(s) / intervention(s)

Biological samples collection: SOT patients: samples will be collected at the time of the protocol follow-up visit (registration on the transplant list, on the day of the transplantation, and then at day 15, month 1-3-6-9-12 and then annually, as well as if complications or therapeutic modifications). Dialysis patients: at the start of the dialysis and then at M3, M12, and if complications or modification of the dialysis protocol. Non-dialysis or cancer patients: the sampling frequency will be individualized according to the pathology studied (acute or chronic) and the purpose of the sampling (diagnostic, mechanistic, prediction, evaluation of the therapeutic response). Samples for diagnostic and mechanistic purposes will be taken only once. Samples for prognostic purposes will be taken at regular intervals, adapted to the natural history of the disease while respecting the maximum volume of blood samples defined by the French law. Samples will be collected during a sampling performed as part of routine care.

Study summary

Managing patients with renal failure requires an understanding of the molecular mechanisms that lead to its occurrence (i.e. upstream of the disease), its worsening and its persistence (i.e. downstream), while also specifying the risk of worsening renal failure (risk stratification, intolerance to the treatment or complications (infectious, metabolic, cardiovascular, cancer…). Nephrogene 2.0 aims to study these different components of kidney, immune and solid organ transplantation (SOT)-related diseases.

Eligibility

Primary outcome measure(s)

• Identification of the molecular mechanisms underlying kidney, immune and solid organ transplantation-related diseases. — yearly and up to 10 years after inclusion in the study
  To identify the molecular mechanisms underlying kidney, immune and solid organ transplantation-related diseases. An unbiased multi-omic approach (including peptidomics, metabolomics, genome sequencing, and flow cytometry and transcriptomic of circulating immune cells) will be performed at the inclusion in the study and correlated to specific end-points (acute kidney injury, kidney failure progression, end-stage kidney disease, infection, cancer according to the underlying condition). Multiple measurements will be studied individually to identify genes variations, gene expression changes, urinary or plasma peptides abundance, immune cells relative abundance in the blood that correlate with the end-point. In a second step, an attempt to combine them in a single predictive signature using artificial intelligence approach.

Trial sites (1)

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