| Project outline
RENUM – Renal Function Assessment by Nuclear Magnetic Resonance based Metabolomics
Objective:
Development and validation of an NMR based metabolite constellation determining glomerular filtration rate (GFR) for innovative and non-invasive estimation of severity of chronic kidney diseases (CKD).
DCMT (London), Honorary Member of the European Society for Paediatric Nephrology
According to the KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease, the severity of CKD should be classified based on glomerular filtration rate (GFR), etiology and albuminuria. The gold standards to determine measured GFR are inulin and other exogenous substances [1, 2, 3]. These mGFR methods are expensive, invasive, time-consuming and very limited for routine use in out-patient settings. Therefore, GFR is mostly estimated by endogenous creatinine and/or cystatin C (eGFR) [4].
However, both substances have shown to be imprecise. Their results depend on chemical methods and on patient’s individual features like age and muscle mass. More than 50 eGFR equations were tested without great success to compensate for these inaccuracies, and recent recommendations proposed their parallel use with a new equation.
In conclusion, measuring eGFR is still regarded to be the weak link in the diagnostic chain of renal diseases [5]. Based on these facts, we concluded that there is a need for a test system that combines precision of mGFR with robustness of a new method, thus, allowing to compare the results between different laboratories and varying groups of patients.
Study design:
RENUM is a retrospective multi-center observational study
Material:
Biobanked serum samples of patients with broad spectrum of primary renal diseases and degrees of renal impairment
Reference standard:
mGFR
Approach:
The scientific literature indicates that there is a connection between increasing/ decreasing concentrations of endogenous blood metabolites and the GFR. To establish a combination of endogenous metabolites with creatinine to a metabolite constellation reflecting GFR, numares uses its precise, fast and flexible analytical AXINON® System, which allows simultaneous detection of metabolites in a highly reproducible single analytical step.
Phase 1:
The association of endogenous serum metabolites with GFR will be tested. Quantitative NMR signals of both, literature reported candidates and proprietary metabolic markers, will be correlated with mGFR reference data. Candidates significantly associated with GFR will be used to model renal clearance based mGFR.
Phase 2:
The diagnostic performance (trueness and precision) of the obtained model(s) will be tested in a further, independent sample set (not used for discovery or modelling).
Success:
Our efforts resulted in a novel, simple blood test for estimating GFR that is available for clinical routine since 2019: AXINON® GFR (NMR)*.
AXINON® GFR (NMR)* allows a deeper insight into kidney pathophysiology. It provides a metabolite panel with serum concentrations of eight metabolites that are associated with kidney function and also allows conclusions to be drawn on renal and extra-renal co-morbidities.
References:
1. Smith, H.W., The kidney: Structure and function in health and disease. Oxford University Press Inc, New York, 1951.
2. National Kidney, F., K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am J Kidney Dis, 2002. 39(2 Suppl 1): p. S1-266.
3. Stevens, L.A. and A.S. Levey, Measured GFR as a confirmatory test for estimated GFR. J Am Soc Nephrol, 2009. 20(11): p. 2305-13.
4. Kemperman, F.A., R.T. Krediet, and L. Arisz, Formula-derived prediction of the glomerular filtration rate from plasma creatinine concentration. Nephron, 2002. 91(4): p. 547-58.
5. Johnson, D. and I. Caring for Australians with Renal, The CARI guidelines. Evaluation of renal function. Nephrology (Carlton), 2005. 10 Suppl 4: p. S133-76.
*numares’ products are not yet available for sale within the United States; they have not yet been approved or cleared by the U.S. Food and Drug Administration.
| Events
November 1 - 6, 2022
Orlando, FL, U.S.
April 6 - 10, 2022
Boston, MA, U.S.
Publications
Banas, M., et al.
A Prospective Multicenter Trial to Evaluate Urinary Metabolomics for Non-invasive Detection of Renal Allograft Rejection (PARASOL): Study Protocol and Patient Recruitment.
Front. Med. (2022)
Ehrich, J., et al.
Serum myo-inositol, dimethyl sulfone, and valine in combination with creatinine allow accurate assessment of renal insufficiency.
Diagnostics (2021)
Stämmler, F., et al.
Estimating Glomerular Filtration Rate from Serum Myo-Inositol, Valine, Creatinine and Cystatin C.
Diagnostics (2021)
Atul K. Sharma Tom D. Blydt-Hansen
To accompany Banas et al., Time for a Paradigm Shift
EBioMedicine (2019)
M. Banas, S. Neuman, P. Pagel, F. J. Putz, G. Boehmig, J. Eiglsperger, et al.
A urinary metabolite constellation to detect acute rejection in kidney allografts
EBioMedicine (2019)
M. Banas, S. Neumann, J. Eiglsperger, E. Schiffer, F. J. Putz, S. Reichelt-Wurm, et al.
Identification of a urine metabolite constellation characteristic for kidney allograft rejection
Metabolomics Off J Metabolomic Soc, 14 (9) (2018), p. 116
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Quantitative evaluation of the diagnostic accuracy (AUC value, sensitivity, and specificity) of AXINON® renalTX-SCORE-U100® for the detection of acute renal allograft rejections
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