{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,13]],"date-time":"2026-08-13T19:18:08Z","timestamp":1786648688516,"version":"build-2736575974"},"reference-count":35,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,11,11]],"date-time":"2025-11-11T00:00:00Z","timestamp":1762819200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fendo.2025.1707049","type":"journal-article","created":{"date-parts":[[2025,11,11]],"date-time":"2025-11-11T05:11:13Z","timestamp":1762837873000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["N-phenethylacetamide, diaminopimelic acid, and Gly-Val as high-performance serum biomarkers for diagnosing untreated Graves\u2019 disease: an LC-MS-based metabolomics 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