Quantitative analysis of d-amino acids in renal samples using derivatization

d-Amino acids are the enantiomers of l-amino acids that occur in minimal concentrations within organisms and exert significant effects on physiological regulation and pathological progression. Abnormal d-amino acid levels are closely associated with neurological disorders and metabolic disturbances. The present research is dedicated to establishing a highly sensitive and reliable quantitative detection approach for evaluating metabolic changes in d-amino acids linked to kidney disease, aiming to assist clinical diagnosis. Samples were processed by precipitating proteins, drying them with nitrogen, and resolubilizing them in water. Finally, l-FDLA (N^α-(5-fluoro-2,4-dinitrophenyl)-l-leucinamide) functioned as a reagent for derivatizing samples of plasma, urine, and cyst fluid. For the calibration curve, activated carbon treatment was used to prepare a blank matrix, which was then tested for separation and detection using reverse-phase chromatography and tandem mass spectrometry. The analysis of biological fluid samples obtained from patients with chronic kidney disease (CKD) and autosomal dominant polycystic kidney disease (ADPKD) was carried out following method validation. A progressive increase in plasma d-serine levels, accompanied by a marked reduction in urinary d-serine, was observed during the course of kidney disease, indicating that D-serine may represent a potential metabolic biomarker of kidney dysfunction. Furthermore, higher levels of d-serine were found in the cyst fluid of an ADPKD patient. Based on the quantitative method used in this study, it was found that it exhibits high sensitivity and selectivity and that it was effective in identifying the metabolic characteristic changes that occur in d-amino acids during kidney disease. Overall, patterns of d-amino acid distribution and their dynamic alterations were strongly associated with the initiation and progression of the disease. The detection of these markers holds promise for providing novel biochemical indicators applicable to the early diagnosis and assessment of kidney disease progression. In terms of methodology, this study extended the use of l-FDLA derivatization to other biological matrices besides human blood, and applied the matrix stripping method for the method validation, thus improving the accuracy of endogenous amino acid quantification. In terms of method application, a focus on amino acid trends in various biofluids of ADPKD patients is offered, within the larger group of kidney dysfunction patients.