Chronic kidney disease (CKD) has emerged as a major public health problem worldwide. It frequently progresses to end-stage renal disease, which is related to very high cost and mortality. Novel biomarkers can provide insight into the novel mechanism, facilitate early detection, and monitor progression of CKD and its response to therapeutic interventions. To identify potential biomarkers, we applied an UPLC-HDMS together with univariate and multivariate statistical analyses using plasma samples from patients with CKD of diverse etiologies (100 sera in discovery set and 120 sera in validation set) and two different rat models of CKD. Using comprehensive screening and validation workflow, we identified a panel of seven metabolites that were shared by all patients and animals regardless of the underlying cause of CKD. These included ricinoleic acid, stearic acid, cytosine, LPA(16:0), LPA(18:2), 3-methylhistidine, and argininic acid. The combination of these seven biomarkers enabled the discrimination of patients with CKD from healthy subjects with a sensitivity of 83.3% and a specificity of 96.7%. In addition, these biomarkers accurately reflected improvements in renal function in response to the therapeutic interventions. Our results indicated that the identified biomarkers may improve the diagnosis of CKD and provide a novel tool for monitoring of the progression of disease and response to treatment in CKD patients.

Early detection is critical in prevention and treatment of kidney disease. However currently clinical laboratory and histopathological tests do not provide region-specific and accurate biomarkers for early detection of kidney disease. The present study was conducted to identify sensitive biomarkers for early detection and progression of tubulo-interstitial nephropathy in aristolochic acid I-induced rats at weeks 4, 8 and 12. Biomarkers were validated using aristolochic acid nephropathy (AAN) rats at week 24, adenine-induced chronic kidney disease (CKD) rats and CKD patients. Compared with control rats, AAN rats showed anemia, increased serum urea and creatinine, progressive renal interstitial fibrosis, activation of nuclear factor-kappa B, and up-regulation of pro-inflammatory, pro-oxidant, and pro-fibrotic proteins at weeks 8 and 12. However, no significant difference was found at week 4. Metabolomics identified 12-ketodeoxycholic acid, taurochenodesoxycholic acid, LPC(15:0) and docosahexaenoic acid as biomarkers for early detection of tubulo-interstitial nephropathy. With prolonging aristolochic acid I exposure, LPE(20:2), cholic acid, chenodeoxycholic acid and LPC(17:0) were identified as biomarkers for progression from early to advanced AAN and lysoPE(22:5), indoxyl sulfate, uric acid and creatinine as biomarkers of advanced AAN. These biomarkers were reversed by treatment of irbesartan and ergone in AAN rats at week 24 and adenine-induced CKD rats. In addition, these biomarkers were also reversed by irbesartan treatment in CKD patients.

Background

Although dialysis ameliorates uremia and fluid and electrolytes disorders, annual mortality rate remains high in dialysis population reflecting its shortcoming in replacing renal function. Unlike the normal kidney, dialysis causes dramatic shifts in volume and composition of body fluids and indiscriminate removal of vital solutes. Present study was undertaken to determine the impact of hemodialysis on plasma metabolites in end-stage renal disease (ESRD) patients.

Methods

80 hemodialysis patients and 80 age/gender-matched healthy controls were enrolled in the study. Using ultra performance liquid chromatography-high-definition mass spectrometry, we measured plasma metabolites before, during, and after hemodialysis procedure and in blood entering and leaving the dialysis filter.

Results

Principal component analysis revealed significant difference in concentration of 214 metabolites between healthy control and ESRD patients' pre-dialysis plasma (126 increased and 88 reduced in ESRD group). Comparison of post-dialysis with pre-dialysis data revealed significant changes in the 362 metabolites. Among ESI⁺ metabolites 195 decreased and 55 increased and among ESI^- metabolites 82 decreased and 30 increased following hemodialysis. Single blood passage through the dialyzer caused significant changes in 323 metabolites. Comparison of ESRD patients' post-hemodialysis with healthy subjects' data revealed marked differences in metabolic profiles. We identified 55 of the 362 differential metabolites including well known uremic toxins, waste products and vital biological compounds.

Conclusion

In addition to uremic toxins and waste products hemodialysis removes large number of identified and as-yet un-identified metabolites. Depletion of vital biological compounds by dialysis may contribute to the high morbidity and annual mortality rate in this population.

Early diagnosis of CKD patients at risk for microalbuminuria or macroalbuminuria could facilitate clinical outcomes and long-term survival. Considering the few and limited efficacy of current biomarkers in early detection, we aim to discover plasma lipids that effectively predict the development of CKD paitents with microalbuminuria or macroalbuminuria. A total of 380 healthy controls and 1156 patients with CKD stages 3 to 5 were stratified by urine albumin-creatinine ratio as microalbuminuria (30-300 mg/g) and macroalbuminuria (>300 mg/g). Fasting plasma samples were determined by UPLC-HDMS based on lipidomics. Quantitative real-time polymerase chain reaction, Western blot and immunohistochemical analyses were used to validate the lipid metabolism-associated pathways. Pathway analysis demonstrated that these lipids were closely associated with PPARγ, inflammatory mediator regulation of TRP channels and RAS signaling, which were intimately involved in activated NF-κB and Nrf2 pathways. We further carried out pathway validation and demonstrated that NF-κB pathway was activated in patients with macroalbuminuria compared with CKD patients with microalbuminuria, while Nrf2-associated protein expression was downregulated, which was accompanied by the up-regulation of Wnt/β-catenin signaling pathway. Four lipids including DTA, 5,8-TDA, GGD3 and DHA that showed great potential in the discrimination of CKD patients with microalbuminuria and healthy controls were selected by logistic regression analysis. Additionally, six lipid species including CDCA, glucosylceramide, GGD2, TTA, DHA and EDA that contributed to the discrimination of CKD patients with microalbuminuria and macroalbuminuria were selected by logistic LASSO regression Gangliosides were first identified and might be promising therapeutic targets for CKD patients with the different degree of albuminuria. Collectively, this study first demonstrates the association of plasma inflammation, oxidative stress, Wnt/β-catenin and lipid metabolism in CKD patients with microalbuminuria and macroalbuminuria.

Early detection and accurate monitoring of chronic kidney disease (CKD) could improve care and retard progression to end-stage renal disease. Here, using untargeted metabolomics in 2155 participants including patients with stage 1-5 CKD and healthy controls, we identify five metabolites, including 5-methoxytryptophan (5-MTP), whose levels strongly correlate with clinical markers of kidney disease. 5-MTP levels decrease with progression of CKD, and in mouse kidneys after unilateral ureteral obstruction (UUO). Treatment with 5-MTP ameliorates renal interstitial fibrosis, inhibits IκB/NF-κB signaling, and enhances Keap1/Nrf2 signaling in mice with UUO or ischemia/reperfusion injury, as well as in cultured human kidney cells. Overexpression of tryptophan hydroxylase-1 (TPH-1), an enzyme involved in 5-MTP synthesis, reduces renal injury by attenuating renal inflammation and fibrosis, whereas TPH-1 deficiency exacerbates renal injury and fibrosis by activating NF-κB and inhibiting Nrf2 pathways. Together, our results suggest that TPH-1 may serve as a target in the treatment of CKD.