RESUMO
BACKGROUND: Effective evaluation or prediction of therapy response could be helpful for treatment of chronic kidney disease (CKD), which may rely on accurate biomarkers. Acylcarnitines are involved with lipid metabolism and mitochondrial function. The relation of acylcarnitines with treatment response in patients with CKD is unknown. The purpose of this study is to investigate the association of plasma acylcarnitines with renal function and its alteration by intervention in patients with IgA nephropathy (IgAN). METHODS: A retrospective study was performed in 81 IgAN patients with treatment by traditional Chinese medicine (TCM). Multivariate linear regression analyses were performed to identify the association of acylcarnitines with baseline estimated glomerular filtration rate (eGFR) and eGFR changes after treatment. RESULTS: Twenty-seven acylcarnitines were measured at baseline and after 1-year TCM intervention. Certain short-chain and median-chain acylcarnitines were independently associated with baseline eGFR and eGFR alterations after 1 year treatment. Particularly, patients with high C5:1(ß = - 0.42), C8:1(ß = - 0.49), C3DC(ß = - 0.5), C10:1(ß = - 0.36) and C5DC(ß = - 0.64)at baseline would have worse prognosis and treatment response. Moreover, certain acylcarnitines could be changed along with the eGFR alteration after 1-year TCM treatment. CONCLUSIONS: The findings indicate a significant association between plasma acylcarnitines with prognosis and treatment responses in patients with IgAN, which suggest its role as a potential penal of biomarker for IgAN.
RESUMO
The patient's response to drug treatment is usually systems-wide based on multi-spots through either direct or indirect targets. Thus, the evaluation of the treatment cannot rely on single targeted biomarker, especially for complex diseases such as chronic kidney disease. In the present study, we performed a systems-wide analysis using proteomic approach to quantify changes in the proteomic profiles of the plasma from IgA nephropathy (IgAN) patients before and after treatment. In particular, the patient-to-health distances based on global proteome quantification before and after treatment were calculated and considered as quantitative readouts to measure patient divergences from the healthy condition. We found that the patient-to-health distance nicely correlated with the patient's response to drug treatment and long-term prognosis, which created a self-tracking platform for personalized evaluation. In addition, the steroid treatment plays a role in immunosuppression, while the Chinese Traditional Medicine (TCM) can modulate whole-body systems. Our results indicated that STC therapy normalized the proteomic profile more significantly than SA therapy. This work provides an omics-based and systematic platform for personalized evaluation of disease treatment. This strategy could help us to evaluate treatment outcomes and predict prognosis in patients with IgAN and other complex diseases.