# N-phenethylacetamide, diaminopimelic acid, and Gly-Val as high-performance serum biomarkers for diagnosing untreated Graves’ disease: an LC-MS-based metabolomics study

**Authors:** Lihua Fang, Qing Ning, Chaowen Wu, Dan Liu, Jie Ning

PMC · DOI: 10.3389/fendo.2025.1707049 · Frontiers in Endocrinology · 2025-11-11

## TL;DR

This study identifies three metabolites that could serve as effective biomarkers for diagnosing untreated Graves' disease, a thyroid disorder, using serum metabolomics.

## Contribution

The study discovers N-phenethylacetamide, diaminopimelic acid, and Gly-Val as high-performance serum biomarkers for diagnosing untreated Graves' disease.

## Key findings

- 334 significantly dysregulated metabolites were identified in untreated Graves' disease patients.
- N-phenethylacetamide, diaminopimelic acid, and Gly-Val showed high diagnostic accuracy (AUCs of 0.94, 0.93, and 0.91 respectively).
- Lipid and organic acid metabolic pathways were prominently altered in Graves' disease.

## Abstract

Graves' disease (GD), a common autoimmune thyroid disorder, is typified by hyperthyroidism and pervasive metabolic perturbations. Metabolomics, a burgeoning field instrumental in biomarker identification and elucidating systemic biological mechanisms, has recently shed light on the intricate pathophysiology of GD. The present study endeavors to delineate the metabolic aberrations in untreated GD patients from Shenzhen, China, leveraging LC-MS-based serum metabolomics.

A cohort comprising 30 newly diagnosed, untreated GD patients and 32 healthy controls was assembled. Serum metabolite profiling was conducted via LC-MS, with subsequent identification and quantification of metabolites. Multivariate statistical analyses, encompassing principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), were employed to discern significant metabolic discrepancies. Pathway enrichment analysis and receiver operating characteristic (ROC) curve analysis were utilized to assess the diagnostic efficacy of the identified metabolites.

A total of 334 significantly dysregulated metabolites were uncovered, with a pronounced involvement of lipid and organic acid metabolic pathways. Notably, N-phenethylacetamide (AUC = 0.94), diaminopimelic acid (AUC = 0.93), and the dipeptide Gly-Val (AUC = 0.91) exhibited substantial diagnostic potential. Pathway enrichment analysis unveiled significant alterations in linoleic acid, alpha-linolenic acid, and arachidonic acid metabolism, underscoring the pivotal role of inflammatory lipid pathways and amino acid metabolism in GD.

This study offers a granular metabolic profile of untreated Graves' disease, unmasking profound dysregulation within lipid and organic acid metabolism. The identified metabolites, particularly N-phenethylacetamide, diaminopimelic acid, and Gly-Val, emerge as promising high-performance serum biomarkers for GD diagnosis. These findings not only augment our comprehension of the metabolic reprogramming inherent to GD but also proffer potential targets for subsequent therapeutic endeavors. Subsequent investigations are imperative to elucidate the mechanistic roles of these metabolites in GD pathogenesis and their viability as clinical biomarkers.

## Linked entities

- **Chemicals:** N-phenethylacetamide (PubChem CID 70143), diaminopimelic acid (PubChem CID 865), Gly-Val (PubChem CID 97417), linoleic acid (PubChem CID 5280450), alpha-linolenic acid (PubChem CID 5280934), arachidonic acid (PubChem CID 444899)
- **Diseases:** Graves' disease (MONDO:0005364)

## Full-text entities

- **Diseases:** autoimmune thyroid disorder (MESH:D013967), hyperthyroidism (MESH:D006980), GD (MESH:D006111), inflammatory lipid (MESH:D011017)
- **Chemicals:** lipid (MESH:D008055), arachidonic acid (MESH:D016718), N-phenethylacetamide (MESH:C054480), alpha-linolenic acid (MESH:D017962), linoleic acid (MESH:D019787), amino (-), Gly-Val (MESH:C035810), diaminopimelic acid (MESH:D003960)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

7 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12643872/full.md

## References

35 references — full list in the complete paper: https://tomesphere.com/paper/PMC12643872/full.md

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Source: https://tomesphere.com/paper/PMC12643872