基于机器学习识别和验证氨基酸代谢相关基因作为慢性肾脏病的新型生物标志物

Machine learning-based identification and validation of amino acid metabolism related genes as novel biomarkers in chronic kidney disease.

作者信息

Zhang Guoqing, Luo Hongyan, Lu Xiaohua, Liu Yonghua, Wang Mei, Li Bo, Lu Haixia, Zheng Yali

机构信息

Department of Nephrology, Ningxia Medical University Affiliated People's Hospital of Autonomous Region, Yinchuan, China.

The Third Clinical Medical College, Ningxia Medical University, Yinchuan, China.

出版信息

Heliyon. 2025 Jan 10;11(2):e41872. doi: 10.1016/j.heliyon.2025.e41872. eCollection 2025 Jan 30.

DOI:10.1016/j.heliyon.2025.e41872

PMID:39897884

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11786826/

Abstract

OBJECTIVES

Chronic kidney disease (CKD) is a progressive illness with a high rate of morbidity and mortality with no proven therapy. Alterations of amino acid(AA) metabolism are associated with the incidence and progression of CKD. To characterize the potential value of AA metabolism related genes in the diagnosis and progression of CKD.

METHODS

We filtered the key genes associated with AA metabolism based on the least absolute shrinkage and selection operator (LASSO) and SVM algorithm. Then, we constructed logistic regression models and evaluated the accuracy and specificity by nomogram analysis and DCA. Also, we mapped the ROC curves.Meanwhile, in order to determine the underlying mechanism and relevant biological features of CKD, we conducted differential analysis between high and low risk subgroups in CKD. Moreover,we employed ssGSEA algorithm to evaluate the infiltration abundance of immune cells and calculated the correlation among the immune cells with the key genes. Finally,we validated the expression and clinical relevance of amino acid metabolism key genes via cultured cells and clinical data. A total of six key genes related to amino acid metabolism were identified, including ALDH18A1, CENPF, CSAD, CTH, CYP27B1, HBB.

RESULTS

All six genes exhibited promising diagnostic capabilities (AUC:0.7 to 0.9). Immune cells such as Activated CD4 T cells, Regulatory T cells, Immature B cells and MDSC,etc.infiltrated differentially in the high and low risk groups of CKD. There were correlations between immune cells abundance and the expression of key genes. All key genes correlated significantly with markers of kidney injury, such as eGFR and serum creatinine. The expression of ALDH18A1, CENPF were increased while CSAD, CTH and CYP27B1 were decreased in HK-2 cells cultured with indole sulfate.

CONCLUSIONS

Our study identified key genes involved in amino acid metabolism associated with immune cells infiltration and renal function in CKD, which may be potential biomarkers for the diagnosis and prognosis of CKD.

摘要

目的

慢性肾脏病（CKD）是一种发病率和死亡率较高的进行性疾病，尚无经证实的治疗方法。氨基酸（AA）代谢改变与CKD的发生和进展相关。旨在阐明AA代谢相关基因在CKD诊断和进展中的潜在价值。

方法

基于最小绝对收缩和选择算子（LASSO）和支持向量机（SVM）算法筛选与AA代谢相关的关键基因。然后，构建逻辑回归模型，并通过列线图分析和决策曲线分析（DCA）评估其准确性和特异性。同时，绘制ROC曲线。此外，为了确定CKD的潜在机制和相关生物学特征，我们对CKD的高风险和低风险亚组进行了差异分析。而且，我们采用单样本基因集富集分析（ssGSEA）算法评估免疫细胞的浸润丰度，并计算免疫细胞与关键基因之间的相关性。最后，我们通过培养细胞和临床数据验证了氨基酸代谢关键基因的表达及其临床相关性。共鉴定出6个与氨基酸代谢相关的关键基因，包括醛脱氢酶18A1（ALDH18A1）、着丝粒蛋白F（CENPF）、胱硫醚γ-裂解酶（CSAD）、半胱氨酸双加氧酶（CTH）、细胞色素P450 27B1（CYP27B1）、血红蛋白β（HBB）。

结果

所有6个基因均表现出良好的诊断能力（曲线下面积：0.7至0.9）。活化的CD4 T细胞、调节性T细胞、未成熟B细胞和骨髓来源的抑制性细胞（MDSC）等免疫细胞在CKD的高风险和低风险组中存在差异浸润。免疫细胞丰度与关键基因的表达之间存在相关性。所有关键基因均与肾损伤标志物如估算肾小球滤过率（eGFR）和血清肌酐显著相关。在用硫酸吲哚培养的人近端肾小管上皮细胞（HK-2）中，ALDH18A1、CENPF的表达增加，而CSAD、CTH和CYP27B1的表达降低。