{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T04:59:07Z","timestamp":1790657947257,"version":"4.1.0"},"reference-count":45,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T00:00:00Z","timestamp":1790640000000},"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. Immunol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Myasthenia gravis (MG) is mediated by abnormal antibody generation and is characterized by muscle weakness and pathological fatigue. However, the accuracy of anti-acetylcholine receptor (AChR) antibody testing for the diagnosis of MG needs improvement.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study was aimed to systematically characterize the plasma metabolome of patients with MG and identify novel biomarkers with significant diagnostic value.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A cohort of 130 subjects was enrolled and divided into discovery and validation sets, and their plasma metabolomic profiles were determined by liquid chromatography\u2013tandem mass spectrometry. Metabolomic variables were analyzed along with clinical information to identify relevant diagnostic biomarkers. The diagnostic efficacy of the screened metabolites and biomarker panel was assessed via receiver operating characteristic (ROC) curve analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      In positive and negative ion modes, plasma metabolomic profiling revealed 326 and 398 differentially abundant metabolites, respectively, in the discovery and validation sets. The metabolomic profile distinguished patients with MG from healthy controls across the two cohorts evaluated in this study. Furthermore, 890 metabolites were detected in both the discovery and validation sets. Metabolite set enrichment analysis of these 890 metabolites revealed that steroid hormone biosynthesis pathway was significantly enriched, implying that altered metabolism may serve as a potential pathological hallmark of MG. On the basis of the differences between groups, compound level, the value of the variable importance in projection, the area under the ROC curve (AUC) and precision\u2013recall curve analyses, 3 differentially abundant metabolites, namely, LysoPE(P-18:1\/0:0), PE(O-18:1\/0:0) and PE(P-16:0\/0:0), were selected as a biomarker panel to distinguish between patients with MG and healthy controls. ROC curve (AUC) analysis revealed that the biomarker panel and anti-AChR antibody testing had equivalent MG diagnostic ability (AUC: 0.883 vs. 0.825;\n                      <jats:italic>P<\/jats:italic>\n                      = 0.058 in the discovery set; AUC: 0.843 vs. 0.722;\n                      <jats:italic>P<\/jats:italic>\n                      = 0.121 in the validation set); moreover, the combination of the biomarker panel and anti-AChR antibody testing significantly improved the clinical diagnosis of MG in the discovery and validation sets compared with anti-AChR antibody testing alone.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Our screened biomarker panel discriminated patients with established MG from healthy healthy controls, however, further evaluation in independent cohorts including patients with suspected MG and other relevant autoimmune and neuromuscular junction disease healthy controls is warranted.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fimmu.2026.1906581","type":"journal-article","created":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T04:40:23Z","timestamp":1790656823000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Comprehensive metabolomic characterization of patients with myasthenia gravis"],"prefix":"10.3389","volume":"17","author":[{"given":"Hui","family":"Deng","sequence":"first","affiliation":[{"name":"Department of Neurology, Affiliated Hospital of Inner Mongolia Medical University","place":["Hohhot, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuexuan","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Pharmacy, Inner Mongolia Medical University","place":["Hohhot, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaowen","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Pharmacy, Affiliated Hospital of Inner Mongolia Medical University","place":["Hohhot, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Qin","sequence":"additional","affiliation":[{"name":"Department of Endocrinology, Affiliated Hospital of Inner Mongolia Medical University","place":["Hohhot, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Pharmacy, Affiliated Hospital of Inner Mongolia Medical University","place":["Hohhot, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tianlong","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Pharmacy, Affiliated Hospital of Inner Mongolia Medical University","place":["Hohhot, China"]},{"name":"Key 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