Metabolomics for clinical use and research in chronic kidney disease

• Published in: Nature reviews. Nephrology Vol. 13; no. 5; pp. 269 - 284
• Main Authors: Hocher, Berthold, Adamski, Jerzy
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.05.2017; Nature Publishing Group
• Subjects: 631/1647/320; 692/4022/1585/104; 692/53; Arginine - analogs & derivatives; Arginine - blood; Biomarkers; Biomedical Research; Biopsy; Care and treatment; Carnitine - analogs & derivatives; Carnitine - metabolism; Creatinine; Development and progression; Diabetes Mellitus - metabolism; Genetic aspects; Genomes; Humans; Hypothyroidism; Kidney diseases; Lipid Metabolism; Medical research; Medicine & Public Health; Metabolism; Metabolites; Metabolomics; Metabolomics - methods; Mortality; Nephrology; Oxidative Stress; Renal Insufficiency, Chronic - metabolism; review-article
• ISSN: 1759-5061; 1759-507X
• DOI: 10.1038/nrneph.2017.30

Key Points The human metabolome reflects genetic variability, intrinsic biochemical processes, environmental challenges and complex interactions of all these factors Metabolomics is instrumental in discovering specific biomarkers in diseases with systemic effects such as chronic kidney disease (CKD) Metabolomics analysis can detect CKD-relevant biomarkers in tissues, plasma, serum and urine samples Most metabolite biomarkers of CKD are markers of glomerular filtration, markers of tubular function or metabolites that reflect a decline in mitochondrial function, alterations in the urea cycle or amino acid metabolism As CKD stage increases, the metabolic biomarker signatures of different renal diseases tends to become more similar and less dependent on the underlying renal disease Metabolic biomarkers seen in the later stages of CKD reflect a loss of glomerular filtration, tubular function and a decline in kidney metabolism and endocrine function Metabolomics has been instrumental for the identification of new biomarkers of chronic kidney disease (CKD). Here, the authors discuss metabolomics technologies and their application in renal disease, including the specificity and functional relevance of CKD-associated metabolic biomarkers. Chronic kidney disease (CKD) has a high prevalence in the general population and is associated with high mortality; a need therefore exists for better biomarkers for diagnosis, monitoring of disease progression and therapy stratification. Moreover, very sensitive biomarkers are needed in drug development and clinical research to increase understanding of the efficacy and safety of potential and existing therapies. Metabolomics analyses can identify and quantify all metabolites present in a given sample, covering hundreds to thousands of metabolites. Sample preparation for metabolomics requires a very fast arrest of biochemical processes. Present key technologies for metabolomics are mass spectrometry and proton nuclear magnetic resonance spectroscopy, which require sophisticated biostatistic and bioinformatic data analyses. The use of metabolomics has been instrumental in identifying new biomarkers of CKD such as acylcarnitines, glycerolipids, dimethylarginines and metabolites of tryptophan, the citric acid cycle and the urea cycle. Biomarkers such as c-mannosyl tryptophan and pseudouridine have better performance in CKD stratification than does creatinine. Future challenges in metabolomics analyses are prospective studies and deconvolution of CKD biomarkers from those of other diseases such as metabolic syndrome, diabetes mellitus, inflammatory conditions, stress and cancer.