Urinary Metabolomic Markers of Protein Glycation, Oxidation, and Nitration in Early-Stage Decline in Metabolic, Vascular, and Renal Health

Author:

Masania Jinit1,Faustmann Gernot23,Anwar Attia1,Hafner-Giessauf Hildegard2,Rajpoot Nasir4,Grabher Johanna2,Rajpoot Kashif5,Tiran Beate6,Obermayer-Pietsch Barbara7,Winklhofer-Roob Brigitte M.3,Roob Johannes M.2,Rabbani Naila1,Thornalley Paul J.18ORCID

Affiliation:

1. Warwick Medical School, Clinical Sciences Research Laboratories, University of Warwick, University Hospital, Coventry CV2 2DX, UK

2. Clinical Division of Nephrology, Department of Internal Medicine, Medical University of Graz, 8036 Graz, Austria

3. Human Nutrition & Metabolism Research and Training Center (HNMRC), Institute of Molecular Biosciences, Karl Franzens University of Graz, Universitätsplatz 2, 8010 Graz, Austria

4. Department of Computer Sciences, University of Warwick, Coventry CV4 7AL, UK

5. School of Computer Science, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK

6. Clinical Institute of Medical and Clinical Laboratory Diagnostics, Medical University of Graz, 8036 Graz, Austria

7. Clinical Division of Endocrinology, Department of Internal Medicine, Medical University of Graz, 8036 Graz, Austria

8. Diabetes Research Center, Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Qatar Foundation, P.O. Box 34110, Doha, Qatar

Abstract

Glycation, oxidation, nitration, and crosslinking of proteins are implicated in the pathogenic mechanisms of type 2 diabetes, cardiovascular disease, and chronic kidney disease. Related modified amino acids formed by proteolysis are excreted in urine. We quantified urinary levels of these metabolites and branched-chain amino acids (BCAAs) in healthy subjects and assessed changes in early-stage decline in metabolic, vascular, and renal health and explored their diagnostic utility for a noninvasive health screen. We recruited 200 human subjects with early-stage health decline and healthy controls. Urinary amino acid metabolites were determined by stable isotopic dilution analysis liquid chromatography-tandem mass spectrometry. Machine learning was applied to optimise and validate algorithms to discriminate between study groups for potential diagnostic utility. Urinary analyte changes were as follows: impaired metabolic health—increased Nε-carboxymethyl-lysine, glucosepane, glutamic semialdehyde, and pyrraline; impaired vascular health—increased glucosepane; and impaired renal health—increased BCAAs and decreased Nε-(γ-glutamyl)lysine. Algorithms combining subject age, BMI, and BCAAs discriminated between healthy controls and impaired metabolic, vascular, and renal health study groups with accuracy of 84%, 72%, and 90%, respectively. In 2-step analysis, algorithms combining subject age, BMI, and urinary Nε-fructosyl-lysine and valine discriminated between healthy controls and impaired health (any type), accuracy of 78%, and then between types of health impairment with accuracy of 69%-78% (cf. random selection 33%). From likelihood ratios, this provided small, moderate, and conclusive evidence of early-stage cardiovascular, metabolic, and renal disease with diagnostic odds ratios of 6 – 7, 26 – 28, and 34 – 79, respectively. We conclude that measurement of urinary glycated, oxidized, crosslinked, and branched-chain amino acids provides the basis for a noninvasive health screen for early-stage health decline in metabolic, vascular, and renal health.

Funder

Bundesministerium für Wissenschaft, Forschung und Wirtschaft

Publisher

Hindawi Limited

Subject

Cell Biology,Aging,General Medicine,Biochemistry

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