Kidney Week

Abstract: SA-PO725

A Nuclear Magnetic Resonance-Based Biomarker Constellation for GFR Prediction Enables Metabolic Phenotyping

Session Information

• Pathology and Lab Medicine: Clinical
  November 09, 2019 | Location: Exhibit Hall, Walter E. Washington Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: Pathology and Lab Medicine

• 1602 Pathology and Lab Medicine: Clinical

Authors

• Ehrich, Jochen H.h., Hannover Medical School, Hannover, Bavaria, Germany

Jochen H.h. Ehrich,

• Dubourg, Laurence, Hospices Civils de Lyon - Université Claude Bernard Lyon 1-INSERM U 820, Lyon, France

Laurence Dubourg,

• Hansson, Sverker, Sahlgrenska University Hospital, Göteborg, Sweden

Sverker Hansson,

• Schäffler, Katharina, numares AG, Regensburg, Germany

Katharina Schäffler,

• Steinle, Tobias, numares AG, Regensburg, Germany

Tobias Steinle,

• Fruth, Jana, numares AG, Regensburg, Germany

Jana Fruth,

• Höckner, Sebastian, numares AG, Regensburg, Germany

Sebastian Höckner,

• Schiffer, Eric, numares AG, Regensburg, Germany

Eric Schiffer,

Background

Assessment of kidney function does either entail high burden for patients as part of clearance measurements (mGFR) or estimated GFR by moderately-performing equations (eGFR). Recently, we developed a novel method for accurate prediction of mGFR, based on a serum biomarker constellation of creatinine, myo-inositol, valine and dimethyl sulfone (DMS) analyzed by nuclear magnetic resonance (NMR) spectroscopy. This metabolomic constellation was tested and validated in three separate cohorts in a multi-center study.

Methods

In order to characterize the role of these biomarkers in renal dysfunction and pathogenesis of CKD and to test their value for metabolic phenotyping, biomarker profiling was applied to sets of three age-, sex-, and mGFR-matched male patients with CKD stage II during end-stage liver disease. To compare the obtained profiles, measured biomarker concentrations were transformed into z-scores and plotted into a radar chart with four axes, one each for creatinine (marker for filtration), dimethyl sulfone (marker of oxidative stress), myo-inositol (marker of uremia), and valine (marker of metabolic acidosis).

Results

Within these age-, sex-, and mGFR-matched sets, the metabolic profiles of clinically similar patients differed significantly concerning single markers reflecting filtration, uremic toxins, oxidative stress, and acidosis. An exemplary set of patients with an mGFR of 62 ml/min/1.73m² is depicted in the figure where every color indicates the distinct metabolic profile of one matched patient.

Conclusion

These observations suggest that the set of renal biomarkers enables molecular phenotyping of clinically highly selected age-, sex-, and mGFR-matched patients of homogenous clinical etiology providing further insights into their individual renal comorbidities based upon complex design thinking and a single diagnostic method using one serum sample.

z-score radar chart

Funding

• Commercial Support –