Identification and validation of serum amino acids as diagnostic biomarkers for diabetic peripheral neuropathy

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

doi:10.4239/wjd.v16.i6.105592

Identification and validation of serum amino acids as diagnostic biomarkers for diabetic peripheral neuropathy

World J Diabetes. 2025 Jun 15;16(6):105592. doi: 10.4239/wjd.v16.i6.105592.

Authors

Affiliations

¹ Department of Pain Medicine, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai 200072, China.
² Department of Anesthesiology, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai 200072, China.
³ Department of Pain Medicine, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai 200072, China. fuqinglin@tongji.edu.cn.

Abstract

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.

Keywords: Arginine; Diabetic peripheral neuropathy; Glutamic acid; Type 2 diabetes mellitus; Tyrosine.