{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T01:27:09Z","timestamp":1793237229192,"version":"4.5.0"},"reference-count":18,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T00:00:00Z","timestamp":1788912000000},"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>Background<\/jats:title>\n                    <jats:p>Pituitary apoplexy is a clinical emergency resulting from hemorrhage or infarction of a pituitary adenoma, which leads to a sudden increase in tumor volume, acute neuroendocrine dysfunction, and local compressive symptoms. In severe cases, it may be life-threatening. The diagnosis of this condition remains challenging, especially in patients without a prior history of pituitary disease, and reliable serum biomarkers are currently lacking. Metabolomics enables the systematic identification of metabolic alterations under physiological and pathological conditions, thereby providing a powerful tool for elucidating disease mechanisms and discovering diagnostic biomarkers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      In this study, untargeted metabolomics analysis using UPLC-MS\/MS was performed on serum samples collected from 39 patients with nonapoplectic pituitary adenoma and 11 patients with pituitary apoplexy. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were applied to assess differences in metabolic profiles between the two groups. Differential metabolites were identified based on variable importance in projection (VIP &amp;gt; 1) and an independent-samples\n                      <jats:italic>t<\/jats:italic>\n                      -test (\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0&amp;lt;\u00a00.05). The diagnostic potential of these metabolites was further evaluated using receiver operating characteristic (ROC) curves.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Compared with the nonapoplectic pituitary adenoma group, the pituitary apoplexy group showed distinct serum metabolic profiles, with 92 metabolites upregulated and 310 metabolites downregulated. Further analysis revealed two key differential metabolites\u2014glycerol-3-phosphate (G-3-P) and\n                      <jats:italic>N<\/jats:italic>\n                      -acetyl-\n                      <jats:sc>d<\/jats:sc>\n                      -galactosamine (GalNAc)\u2014as potential diagnostic biomarkers for pituitary apoplexy.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study reveals distinct serum metabolic profiles between the pituitary apoplexy group and the nonapoplectic pituitary adenoma group, offering novel metabolic insights into the pathogenesis of pituitary apoplexy.<\/jats:p>\n                  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