A plasma N-acetyl amino acid panel for type 2 diabetes discrimination built by targeted LC–MS/MS: A case–control study

By
Shusi Ding
Zhanxiong Xie
Daqiu Chen
Xiaomai Huang
Qiutong Wu
Lemin Zheng
Shanghua Xu
Shunxiang Luo
June 3, 2026
0 min

Frontiers In Medicine

Overview

This study characterizes the plasma N-acetyl amino acid (NAcAA) profile in type 2 diabetes (T2D) and evaluates its potential as a diagnostic tool. A targeted LC–MS/MS assay identified significant metabolic differences between T2D patients and non-diabetic controls, leading to the development of an 8-metabolite panel for T2D discrimination.

Background

Type 2 diabetes (T2D) is associated with various metabolic disturbances, necessitating the identification of actionable biomarkers beyond traditional glycemic indices. N-acetyl amino acids (NAcAAs) have emerged as metabolites linked to amino acid metabolism, yet their diagnostic relevance in T2D remains underexplored. Understanding these metabolites could enhance early detection and risk stratification in T2D.

Data Highlights

Metabolite	Association with T2D	Odds Ratio (OR)	95% Confidence Interval (CI)
N-acetyltryptophan	Positive	9.452	4.421–20.211
N-acetylproline	Inverse	0.041	0.015–0.111
N-acetyllysine	Inverse	0.088	0.038–0.203

Key Findings

The plasma NAcAA profile significantly differs between T2D patients and non-diabetic controls.
Increased levels of N-acetyltryptophan are positively associated with T2D.
N-acetylproline and N-acetyllysine show inverse associations with T2D.
An 8-metabolite panel derived from NAcAAs achieved an AUC of 0.963 for T2D discrimination.
NAcAAs correlate with glycemic traits such as fasting glucose and HbA1c.

Clinical Implications

The findings suggest that NAcAAs could serve as potential biomarkers for T2D, providing insights into metabolic disturbances associated with the disease. The developed metabolite panel may aid in the early identification and risk stratification of T2D patients.

Conclusion

The study highlights the distinct metabolic signature of NAcAAs in T2D and the potential of a metabolite-based panel for improved diagnostic capabilities.