Department of Nephrology, Kiang Wu Hospital, Macau, China.
Department of Nephrology, The Third Affiliated Hospital of Sun Yat-sen University, Guang Zhou, China.
BMC Nephrol. 2023 Apr 21;24(1):105. doi: 10.1186/s12882-023-03147-9.
Chronic kidney disease (CKD) is a global public health issue. The diagnosis of CKD would be considerably enhanced by discovering novel biomarkers used to determine the glomerular filtration rate (GFR). Small molecule metabolites related to kidney filtration function that might be utilized as biomarkers to measure GFR more accurately could be found via a metabolomics analysis of blood samples taken from individuals with varied glomerular filtration rates.
An untargeted metabolomics study of 145 plasma samples was performed using ultrahigh-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS). The 145 samples were divided into four groups based on the patient's measured glomerular filtration rates (mGFRs) determined by the iohexol plasma clearance rate. The data were analyzed using random forest analyses and six other unique statistical analyses. Principal component analysis (PCA) was conducted using R software.
A large number of metabolites involved in various metabolic pathways changed significantly between groups with different GFRs. These included metabolites involved in tryptophan or pyrimidine metabolism. The top 30 metabolites that best distinguished between the four groups in a random forest plot analysis included 13 amino acids, 9 nucleotides, and 3 carbohydrates. A panel of metabolites (including hydroxyaparagine, pseudouridine, C-glycosyltryptophan, erythronate, N-acetylalanine, and 7-methylguanidine) for estimating GFR was selected for future testing in targeted analyses by combining the candidate lists with the six other statistical analyses. Both hydroxyasparagine and N,N-dimethyl-proline-proline are unique biomarkers shown to be inversely associated with kidney function that have not been reported previously. In contrast, 1,5-anhydroglucitol (1,5-AG) decreases with impaired renal function.
This global untargeted metabolomics study of plasma samples from patients with different degrees of renal function identified potential metabolite biomarkers related to kidney filtration. These novel potential metabolites provide more insight into the underlying pathophysiologic processes that may contribute to the progression of CKD, lead to improvements in the estimation of GFR and provide potential therapeutic targets to improve kidney function.
慢性肾脏病（CKD）是一个全球性的公共卫生问题。通过发现用于确定肾小球滤过率（GFR）的新型生物标志物，将极大地提高 CKD 的诊断水平。通过对来自不同肾小球滤过率患者的血液样本进行代谢组学分析，可能会发现与肾脏滤过功能相关的小分子代谢物，这些代谢物可能被用作更准确测量 GFR 的生物标志物。
对 145 份血浆样本进行了非靶向代谢组学研究，使用超高效液相色谱串联质谱法（UPLC-MS/MS）。根据患者的 iohexol 血浆清除率测定的肾小球滤过率（mGFR），将 145 个样本分为四组。使用随机森林分析和其他六种独特的统计分析对数据进行分析。使用 R 软件进行主成分分析（PCA）。
在不同 GFR 组之间，大量涉及各种代谢途径的代谢物发生了显著变化。这些代谢物包括色氨酸或嘧啶代谢物。在随机森林图分析中，将四个组最佳区分的前 30 个代谢物包括 13 种氨基酸、9 种核苷酸和 3 种碳水化合物。一组代谢物（包括羟基天冬酰胺、假尿嘧啶、C-糖基色氨酸、赤藓糖、N-乙酰丙氨酸和 7-甲基胍）被选中用于进一步的靶向分析，通过将候选列表与其他六种统计分析相结合，用于估计 GFR。羟基天冬酰胺和 N，N-二甲基脯氨酸-脯氨酸这两种与肾功能呈负相关的独特生物标志物，以前没有报道过。相反，1,5-脱水葡萄糖醇（1,5-AG）随着肾功能受损而减少。
这项针对不同肾功能患者血浆样本的全球非靶向代谢组学研究，确定了与肾脏滤过相关的潜在代谢物生物标志物。这些新的潜在代谢物为深入了解可能导致 CKD 进展的潜在病理生理过程提供了更多的认识，提高了 GFR 的估计水平，并提供了改善肾脏功能的潜在治疗靶点。
