Estimating Glomerular Filtration Rate from Serum Myo-Inositol, Valine, Creatinine and Cystatin C

Frank Stämmler; Marcello Grassi; Jeffrey W Meeusen; John C Lieske; Surendra Dasari; Laurence Dubourg; Sandrine Lemoine; Jochen Ehrich; Eric Schiffer

doi:10.3390/diagnostics11122291

Estimating Glomerular Filtration Rate from Serum Myo-Inositol, Valine, Creatinine and Cystatin C

Diagnostics (Basel). 2021 Dec 7;11(12):2291. doi: 10.3390/diagnostics11122291.

Authors

Frank Stämmler¹, Marcello Grassi¹, Jeffrey W Meeusen², John C Lieske^{2

3}, Surendra Dasari⁴, Laurence Dubourg⁵, Sandrine Lemoine⁵, Jochen Ehrich⁶, Eric Schiffer¹

Affiliations

¹ Department of Research and Development, numares AG, 93053 Regensburg, Germany.
² Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA.
³ Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN 55905, USA.
⁴ Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN 55905, USA.
⁵ Service d'Explorations Fonctionnelles Rénales et Métaboliques, Hôpital Edouard Herriot, 69437 Lyon, France.
⁶ Children's Hospital, Hannover Medical School, 30625 Hannover, Germany.

Abstract

Assessment of renal function relies on the estimation of the glomerular filtration rate (eGFR). Existing eGFR equations, usually based on serum levels of creatinine and/or cystatin C, are not uniformly accurate across patient populations. In the present study, we expanded a recent proof-of-concept approach to optimize an eGFR equation targeting the adult population with and without chronic kidney disease (CKD), based on a nuclear magnetic resonance spectroscopy (NMR) derived 'metabolite constellation' (GFR_NMR). A total of 1855 serum samples were partitioned into development, internal validation and external validation datasets. The new GFR_NMR equation used serum myo-inositol, valine, creatinine and cystatin C plus age and sex. GFR_NMR had a lower bias to tracer measured GFR (mGFR) than existing eGFR equations, with a median bias (95% confidence interval [CI]) of 0.0 (-1.0; 1.0) mL/min/1.73 m² for GFR_NMR vs. -6.0 (-7.0; -5.0) mL/min/1.73 m² for the Chronic Kidney Disease Epidemiology Collaboration equation that combines creatinine and cystatin C (CKD-EPI₂₀₁₂) (p < 0.0001). Accuracy (95% CI) within 15% of mGFR (1-P15) was 38.8% (34.3; 42.5) for GFR_NMR vs. 47.3% (43.2; 51.5) for CKD-EPI₂₀₁₂ (p < 0.010). Thus, GFR_NMR holds promise as an alternative way to assess eGFR with superior accuracy in adult patients with and without CKD.

Keywords: CKD; NMR; chronic kidney disease; cystatin C; eGFR; eGFR equation; filtration markers; glomerular filtration rate; metabolite; serum creatinine.