Prognostic Significance of Amino Acid and Biogenic Amines Profiling in Chronic Kidney Disease

Author:

Gervasini Guillermo123ORCID,Verde Zoraida456ORCID,González Luz M.1,Chicharro Celia67,González-Rodríguez Laura13,Fernández-Araque Ana58ORCID,Mota-Zamorano Sonia1,Cancho Bárbara9,Pérez-Hernández Alberto10,García-López Virginio1ORCID,Bandrés Fernando67,Robles Nicolás R.39ORCID

Affiliation:

1. Department of Medical and Surgical Therapeutics, Medical School, University of Extremadura, 06006 Badajoz, Spain

2. Institute of Molecular Pathology Biomarkers, University of Extremadura, 06006 Badajoz, Spain

3. RICORS2040 Renal Research Network, 28029 Madrid, Spain

4. Department of Biochemistry, Molecular Biology and Physiology, Universidad de Valladolid, 42005 Soria, Spain

5. GIR—Pharmacogenetics, Cancer Genetics, Genetic Polymorphisms and Pharmacoepidemiology, University of Valladolid, 47005 Valladolid, Spain

6. Research Group Centro de Estudios Gregorio Marañón, Fundación Ortega-Marañón, 28010 Madrid, Spain

7. Biopathology-Toxicology Laboratory, Department of Legal Medicine, Psychiatry and Pathology, Faculty of Medicine, University Complutense of Madrid, 28040 Madrid, Spain

8. Department of Nursery, University of Valladolid, 42005 Soria, Spain

9. Service of Nephrology, Badajoz University Hospital, 06006 Badajoz, Spain

10. Department of Clinical Biochemistry, Hospital Santa Bárbara, 42005 Soria, Spain

Abstract

There is a pressing need for more precise biomarkers of chronic kidney disease (CKD). Plasma samples from 820 subjects [231 with CKD, 325 with end-stage kidney disease (ESKD) and 264 controls] were analyzed by liquid chromatography with tandem mass spectrometry (LC-MS/MS) to determine a metabolic profile of 28 amino acids (AAs) and biogenic amines to test their value as markers of CKD risk and progression. The kynurenine/tryptophan ratio showed the strongest correlation with estimated glomerular filtration rate values (coefficient = −0.731, p < 0.0001). Models created with orthogonal partial least squares-discriminant analysis (OPLS-DA) containing the metabolic signature showed a high goodness of fit and predictability for controls/CKD (R2X:0.73:R2Y:0.92:Q2:0.92, p < 0.0001) and lower values for CKD/ESKD (R2X:0.56:R2Y:0.59:Q2:0.55, p < 0.0001). Based on generated VIP scores, the most relevant markers for segregating samples into control/CKD and CKD/ESKD groups were citrulline (1.63) and tryptophan (1.47), respectively. ROC analysis showed that the addition of the metabolic profile to a model including CKD classic risk factors improved the AUC from 86.7% (83.6–89.9) to 100% (100–100) for CKD risk (p < 0.0001) and from 63.0% (58.2–67.8) to 96.5% (95.3–97.8) for the risk of progression from CKD to ESKD (p < 0.0001). Plasma concentrations of AAs and related amines may be useful as diagnostic biomarkers of kidney disease, both for CKD risk and for progression of CKD patients to ESKD.

Funder

Instituto de Salud Carlos III, Madrid (Spain), financed by the European Union-NextGeneration UE, Recovery and Resilience Mechanism

Instituto de Salud Carlos III (ISCIII) and co-funded by the European Union

Junta de Extremadura, Mérida (Spain) and Fondo Europeo de Desarrollo Regional (FEDER) “Una manera de hacer Europa”

Publisher

MDPI AG

Subject

General Biochemistry, Genetics and Molecular Biology,Medicine (miscellaneous)

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