血清氨基酸作为糖尿病周围神经病变诊断生物标志物的鉴定和验证。

IF 4.2 3区 医学 Q1 ENDOCRINOLOGY & METABOLISM
Wei-Sheng Xu, Huan Xing, Qing-Qing Wang, Hui Qi, Jian-Tao He, Tong Jin, Yan-Peng Kan, Shi-Yu Sun, Ji-Ying Wang, Fu-Qing Lin
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引用次数: 0

摘要

背景:糖尿病周围神经病变(DPN)是2型糖尿病(T2DM)最常见的并发症。由于缺乏特定的生物标志物,这种疾病的早期诊断是有限的。目的:鉴别并验证T2DM合并DPN与非DPN的血清氨基酸。方法:选取伴有DPN的T2DM患者、不伴有DPN的T2DM患者和健康对照者进行研究。参与者包括两个不重叠的队列:一个训练队列(DPN = 84人,T2DM = 82人,正常= 50人)和一个验证队列(DPN = 112人,T2DM = 93人,正常= 58人)。采用logistic回归模型建立血清氨基酸区分DPN与T2DM能力的预测模型,并采用曲线下面积(AUC)分析评价模型的诊断能力。同时对13例DPN患者在治疗前及治疗3个月后的血清氨基酸水平进行检测。结果:建立了一种基于三种血清氨基酸和糖尿病病程的生物标志物诊断DPN的临床方法。该诊断模型在训练组和验证组的AUC值分别为0.805 (95%CI: 0.739-0.871)和0.810 (95%CI: 0.750-0.870)。在鉴别T2DM患者和正常对照时,训练组和验证组的AUC值分别为0.891 (95%CI: 0.836-0.945)和0.883 (95%CI: 0.832-0.934)。精氨酸和酪氨酸水平在治疗后升高,而天冬氨酸水平在治疗后降低。结论:本研究成功鉴定并验证了精氨酸、酪氨酸和谷氨酸作为诊断DPN的潜在生物标志物的代谢组学意义。这些发现特别有价值,因为它们为开发DPN的第一个常规实验室测试奠定了基础。此外,本研究构建的诊断模型能够有效区分DPN患者与无神经病变的T2DM患者,有助于早期诊断和干预。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification and validation of serum amino acids as diagnostic biomarkers for diabetic peripheral neuropathy.

Background: Diabetic peripheral neuropathy (DPN) is the most prevalent complication of type 2 diabetes mellitus (T2DM). Due to a lack of specific biomarkers, the early diagnosis of this disorder is limited.

Aim: To identify and validate serum amino acids that could discriminate T2DM patients with DPN from those without DPN.

Methods: T2DM patients with DPN, T2DM patients without DPN, and healthy controls were recruited for this study. The participants comprised two nonoverlapping cohorts: A training cohort (DPN = 84 participants, T2DM = 82 participants, normal = 50 participants) and a validation cohort (DPN = 112 participants, T2DM = 93 participants, normal = 58 participants). A prediction model of the ability of serum amino acids to distinguish DPN from T2DM was established using a logistic regression model, and area under the curve (AUC) analysis was used to evaluate the diagnostic ability of the model. In addition, the serum amino acid levels of 13 DPN patients were also detected before treatment and after 3 months of treatment.

Results: A clinical detection method for the diagnosis of DPN based on a biomarker panel of three serum amino acids and diabetes duration was developed. The diagnostic model demonstrated AUC values of 0.805 (95%CI: 0.739-0.871) and 0.810 (95%CI: 0.750-0.870) in the training and verification cohorts, respectively. In the identification of T2DM patients and normal controls, the AUC values were 0.891 (95%CI: 0.836-0.945) and 0.883 (95%CI: 0.832-0.934) in the training and validation cohorts, respectively. Arginine and tyrosine levels were increased after treatment, whereas aspartic acid levels were decreased after treatment.

Conclusion: This study successfully identified and validated the metabolomic significance of arginine, tyrosine, and glutamic acid as potential biomarkers for diagnosing DPN. These findings are particularly valuable, as they establish a foundational step toward developing the first routine laboratory test for DPN. Moreover, the diagnostic model that was constructed in this study effectively distinguishes DPN patients from those with T2DM without neuropathy, thereby potentially facilitating early diagnosis and intervention.

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来源期刊
World Journal of Diabetes
World Journal of Diabetes ENDOCRINOLOGY & METABOLISM-
自引率
2.40%
发文量
909
期刊介绍: The WJD is a high-quality, peer reviewed, open-access journal. The primary task of WJD is to rapidly publish high-quality original articles, reviews, editorials, and case reports in the field of diabetes. In order to promote productive academic communication, the peer review process for the WJD is transparent; to this end, all published manuscripts are accompanied by the anonymized reviewers’ comments as well as the authors’ responses. The primary aims of the WJD are to improve diagnostic, therapeutic and preventive modalities and the skills of clinicians and to guide clinical practice in diabetes. Scope: Diabetes Complications, Experimental Diabetes Mellitus, Type 1 Diabetes Mellitus, Type 2 Diabetes Mellitus, Diabetes, Gestational, Diabetic Angiopathies, Diabetic Cardiomyopathies, Diabetic Coma, Diabetic Ketoacidosis, Diabetic Nephropathies, Diabetic Neuropathies, Donohue Syndrome, Fetal Macrosomia, and Prediabetic State.
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