The CKD plasma lipidome varies with disease severity and outcome.

BACKGROUND: Various alterations in lipid metabolism have been observed in patients with chronic kidney disease (CKD). OBJECTIVES: To determine the levels of lipid species in plasma from CKD and hemodialysis (HD) patients and test their association with CKD severity and patient outcome. METHODS: Seventy-seven patients with CKD stage 2 to HD were grouped into classes of CKD severity at baseline and followed-up for 3.5 years for the occurrence of transition to HD or death (combined outcome). Plasma levels of phosphatidylcholines (PCs), lysophosphatidylcholines (LPCs), sphingomyelins (SMs), and fatty acids were analyzed by flow-injection analysis coupled to tandem mass spectrometry or gas chromatography coupled with mass spectrometry. Kruskal Wallis rank tests and Cox regressions were used to analyze the association of lipids with CKD severity and the risk of combined outcome, respectively. RESULTS: The plasma level of PCs, LPCs, and SMs was decreased in HD patients compared with nondialyzed CKD patients (all P < .05), whereas esterified and/or nonesterified fatty acids level did not change. Thirty-four lipids displayed significantly lower abundance in plasma of HD patients, whereas elaidic acid (C18:1ω9t) level was increased (P < .001). The total amount of LPCs and individual LPCs were associated with better outcome (P < .05). In particular, LPC 18:2 and LPC 20:3 were statistically associated with outcome in adjusted models (P < .05). DISCUSSION: In HD patients, a reduction in plasma lipids is observed. Some of the alterations, namely reduced LPCs, were associated with the risk of adverse outcome. These changes could be related to metabolic dysfunctions.

Assessment of metabolomic and proteomic biomarkers in detection and prognosis of progression of renal function in chronic kidney disease.

Chronic kidney disease (CKD) is part of a number of systemic and renal diseases and may reach epidemic proportions over the next decade. Efforts have been made to improve diagnosis and management of CKD. We hypothesised that combining metabolomic and proteomic approaches could generate a more systemic and complete view of the disease mechanisms. To test this approach, we examined samples from a cohort of 49 patients representing different stages of CKD. Urine samples were analysed for proteomic changes using capillary electrophoresis-mass spectrometry and urine and plasma samples for metabolomic changes using different mass spectrometry-based techniques. The training set included 20 CKD patients selected according to their estimated glomerular filtration rate (eGFR) at mild (59.9±16.5 mL/min/1.73 m2; n = 10) or advanced (8.9±4.5 mL/min/1.73 m2; n = 10) CKD and the remaining 29 patients left for the test set. We identified a panel of 76 statistically significant metabolites and peptides that correlated with CKD in the training set. We combined these biomarkers in different classifiers and then performed correlation analyses with eGFR at baseline and follow-up after 2.8±0.8 years in the test set. A solely plasma metabolite biomarker-based classifier significantly correlated with the loss of kidney function in the test set at baseline and follow-up (ρ = -0.8031; p<0.0001 and ρ = -0.6009; p = 0.0019, respectively). Similarly, a urinary metabolite biomarker-based classifier did reveal significant association to kidney function (ρ = -0.6557; p = 0.0001 and ρ = -0.6574; p = 0.0005). A classifier utilising 46 identified urinary peptide biomarkers performed statistically equivalent to the urinary and plasma metabolite classifier (ρ = -0.7752; p<0.0001 and ρ = -0.8400; p<0.0001). The combination of both urinary proteomic and urinary and plasma metabolic biomarkers did not improve the correlation with eGFR. In conclusion, we found excellent association of plasma and urinary metabolites and urinary peptides with kidney function, and disease progression, but no added value in combining the different biomarkers data.

Plasma and urinary amino acid metabolomic profiling in patients with different levels of kidney function.

BACKGROUND AND OBJECTIVES: Patients with CKD display altered plasma amino acid profiles. This study estimated the association between the estimated GFR and urinary and plasma amino acid profiles in CKD patients. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Urine and plasma samples were taken from 52 patients with different stages of CKD, and plasma samples only were taken from 25 patients on maintenance hemodialysis. Metabolic profiling was performed by liquid chromatography coupled with tandem mass spectrometry after phenylisothiocyanate derivatization. RESULTS: Most plasma amino acid concentrations were decreased in hemodialysis patients, whereas proline, citrulline, asparagine, asymmetric dimethylarginine, and hydroxykynurenine levels were increased (P<0.05). Both plasma levels and urinary excretion of citrulline were higher in the group of patients with advanced CKD (CKD stages 2 and 3 versus CKD stages 4 and 5; in plasma: 35.9±16.3 versus 61.8±23.6 µmol/L, P<0.01; in urine: 1.0±1.2 versus 7.1±14.3 µmol/mol creatinine, P<0.001). Plasma asymmetric dimethylarginine levels were higher in advanced CKD (CKD stages 2 and 3, 0.57±0.29; CKD stages 4 and 5, 1.02±0.48, P<0.001), whereas urinary excretion was lower (2.37±0.93 versus 1.51±1.43, P<0.001). Multivariate analyses adjusting on estimated GFR, serum albumin, proteinuria, and other covariates revealed associations between diabetes and plasma citrulline (P=0.02) and between serum sodium and plasma asymmetric dimethylarginine (P=0.03). Plasma tyrosine to phenylalanine and valine to glycine ratios were lower in advanced CKD stages (P<0.01). CONCLUSION: CKD patients have altered plasma and urinary amino acid profiles that are not corrected by dialysis. Depending on solutes, elevated plasma levels were associated with increased or decreased urinary excretion, depicting situations of uremic retention (asymmetric dimethylarginine) or systemic overproduction (citrulline). These results give some insight in the CKD-associated modifications of amino acid metabolism, which may help improve their handling.

CKD273, a new proteomics classifier assessing CKD and its prognosis.

National Kidney Foundation CKD staging has allowed uniformity in studies on CKD. However, early diagnosis and predicting progression to end stage renal disease are yet to be improved. Seventy six patients with different levels of CKD, including outpatients and dialysed patients were studied for transcriptome, metabolome and proteome description. High resolution urinary proteome analysis was blindly performed in the 53 non-anuric out of the 76 CKD patients. In addition to routine clinical parameters, CKD273, a urinary proteomics-based classifier and its peptides were quantified. The baseline values were analyzed with regard to the clinical parameters and the occurrence of death or renal death during follow-up (3.6 years) as the main outcome measurements. None of the patients with CKD273<0.55 required dialysis or died while all fifteen patients that reached an endpoint had a CKD273 score >0.55. Unsupervised clustering analysis of the CKD273 peptides separated the patients into two main groups differing in CKD associated parameters. Among the 273 biomarkers, peptides derived from serum proteins were relatively increased in patients with lower glomerular filtration rate, while collagen-derived peptides were relatively decreased (p<0.05; Spearman). CKD273 was different in the groups with different renal function (p<0.003). The CKD273 classifier separated CKD patients according to their renal function and informed on the likelihood of experiencing adverse outcome. Recently defined in a large population, CKD273 is the first proteomic-based classifier successfully tested for prognosis of CKD progression in an independent cohort.