表征代谢失调早期慢性肾脏疾病的诊断见解。

IF 2.4 4区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY
Molecular omics Pub Date : 2025-05-29 DOI:10.1039/d5mo00018a
Upasna Gupta, Amrita Sahu, Dharmendra Singh Bhadauria, Bikash Baishya, Neeraj Sinha
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引用次数: 0

摘要

慢性肾脏疾病(CKD)是一种进行性疾病,在早期用常规的诊断方法(如血清肌酐和白蛋白评估)诊断通常是具有挑战性的。早期CKD (G1-G3期)的定义是GFR≥30 mL min-1/1.73 m2,表明肾功能正常至中度下降,伴有或不伴有肾功能受损症状。确定可能的早期检测和个性化治疗的生物标志物,以及与早期ckd相关的生理变化——这一领域以前尚未得到充分研究——是该研究的目标,以解决这一差距。我们使用1H NMR对115人血清样本(24名健康对照和91名早期CKD患者)进行了代谢组学分析。使用MetaboAnalyst 6.0进行数据预处理和统计分析(PCA、PLS-DA、OPLS-DA、ANOVA和Wilcoxon Mann-Whitney检验)。CKD阶段之间的强烈区分是通过随机森林模型实现的。采用KEGG数据库进行途径富集,采用ROC分析评估重要代谢物的诊断价值。在不同的CKD阶段,10种不同的代谢物有显著变化:肌醇、甘油、丙酮酸、肉碱、苯丙氨酸、酪氨酸、组氨酸、氧化三甲胺、2-羟基异丁酸和3-羟基异丁酸(p < 0.05, VIP bbb1)。ROC曲线的AUC值为>.7,显示其诊断潜力。通路分析显示,肌醇磷酸、酪氨酸、组氨酸和丙酮酸的代谢以及苯丙氨酸、色氨酸和酪氨酸的生物合成存在明显的失调。这项全面的代谢组学研究除了发现显著的代谢异常外,还发现了潜在的早期CKD生物标志物。这些发现有助于为早期CKD治疗提供个性化护理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Characterizing metabolic dysregulation in early-stage chronic kidney disease for diagnostic insights.

The progressive illness known as chronic kidney disease (CKD) can often be challenging to diagnose in its early stages with conventional diagnostic approaches such as serum creatinine and albumin assessment. Early-stage CKD (stages G1-G3) is defined by a GFR of ≥30 mL min-1/1.73 m2, which indicates normal to moderately reduced kidney function with or without symptoms of impaired kidney function. Identifying possible biomarkers for early detection and personalised treatment, as well as physiological changes linked to early CKD-an area that has not been fully investigated before-is the goal of the study to address this gap. We performed a metabolomic analysis using 1H NMR on 115 human serum samples (24 healthy controls and 91 patients with early-stage CKD). MetaboAnalyst 6.0 was used for data pre-processing and statistical analyses (PCA, PLS-DA, OPLS-DA, ANOVA, and Wilcoxon Mann-Whitney test). Strong differentiation between CKD stages was achieved by random forest modelling. The KEGG database was used to perform pathway enrichment, and ROC analysis was used to evaluate the diagnostic value of important metabolites. Across CKD stages, significant changes were observed in ten different metabolites: myo-Inositol, glycerol, pyruvate, carnitine, phenylalanine, tyrosine, histidine, TMAO, 2-hydroxyisobutyrate, and 3-hydroxyisobutyrate (p < 0.05, VIP > 1). AUC values > 0.7 from ROC curves demonstrated its potential for diagnosis. Pathway analysis revealed significant dysregulation in the metabolism of inositol phosphate, tyrosine, histidine, and pyruvate, and biosynthesis of phenylalanine, tryptophan and tyrosine. This comprehensive metabolomics investigation identified potential early-stage CKD biomarkers in addition to significant metabolic abnormalities. These findings could help provide individualized care for early CKD management.

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来源期刊
Molecular omics
Molecular omics Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
5.40
自引率
3.40%
发文量
91
期刊介绍: Molecular Omics publishes high-quality research from across the -omics sciences. Topics include, but are not limited to: -omics studies to gain mechanistic insight into biological processes – for example, determining the mode of action of a drug or the basis of a particular phenotype, such as drought tolerance -omics studies for clinical applications with validation, such as finding biomarkers for diagnostics or potential new drug targets -omics studies looking at the sub-cellular make-up of cells – for example, the subcellular localisation of certain proteins or post-translational modifications or new imaging techniques -studies presenting new methods and tools to support omics studies, including new spectroscopic/chromatographic techniques, chip-based/array technologies and new classification/data analysis techniques. New methods should be proven and demonstrate an advance in the field. Molecular Omics only accepts articles of high importance and interest that provide significant new insight into important chemical or biological problems. This could be fundamental research that significantly increases understanding or research that demonstrates clear functional benefits. Papers reporting new results that could be routinely predicted, do not show a significant improvement over known research, or are of interest only to the specialist in the area are not suitable for publication in Molecular Omics.
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