# The Association Between Amino Acids and the Onset and Progression of Type 2 Diabetes Mellitus: A Comprehensive Analysis Based on UK Biobank Database

## TL;DR

This study explores how amino acid levels are linked to the development and progression of Type 2 diabetes, identifying potential biomarkers for predicting complications and treatment needs.

## Contribution

The study provides new evidence of causal relationships between specific amino acids and Type 2 diabetes, and develops a predictive model for complications.

## Key findings

- Alanine and valine are positively associated with T2DM, while glutamine and glycine are protective factors.
- A predictive model using amino acid profiles accurately predicts T2DM complications with high ROC area (>0.730).
- Specific amino acid profiles are linked to insulin resistance and treatment demands for T2DM.

## Abstract

Recent studies have demonstrated an association between amino acids (AAs) and the occurrence of Type 2 diabetes mellitus (T2DM). However, whether there is an underlying causal relationship between AAs and T2DM, as well as their potential links to T2DM progression, complications, and treatment selection, still lacks sufficient clinical evidence.

This study included 205,208 participants from the UKB database, with 14,066 diagnosed with T2DM. We used LASSO regression, supplemented by Mendelian randomization (MR), to explore the causal relationship between AA levels and T2DM. Additionally, restricted cubic splines, receiver operating characteristic (ROC) curves, and multivariable‐adjusted regression models were applied to analyze the association between AA levels, insulin resistance, secondary complications, and treatment options for T2DM.

Alanine and valine were positively associated with T2DM, while glutamine, glycine, and histidine were negatively associated with T2DM. In particular, the MR results indicated a causal relationship between T2DM and plasma glutamine and glycine, which were identified as protective factors. Other branched‐chain AAs, such as leucine and isoleucine, did not show significant positive associations in the regression analysis. Additionally, we integrated various AAs to develop a predictive model for secondary complications of T2DM. The model demonstrated high predictive accuracy for a range of T2DM‐related complications (all areas under the ROC curve > 0.730). In addition, specific AA profiles were related to insulin resistance and demand for insulin or oral hypoglycemic drug treatment.

Our study results demonstrate a close relationship between AA levels and the occurrence, development, and treatment demand for T2DM, offering potential biomarkers for predicting complications and guiding personalized treatment.