<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>11</volume><submitter>Lin X</submitter><pubmed_abstract>Osteoarthritis (OA) is the most common joint disease in the world, characterized by pain and loss of joint function, which has led to a serious reduction in the quality of patients' lives. In this work, ultrahigh performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-QToF/MS) in conjunction with multivariate pattern recognition methods and an univariate statistical analysis scheme were applied to explore the serum metabolic signatures within OA group (&lt;i>n&lt;/i&gt; = 31), HC (healthy controls) group (&lt;i>n&lt;/i> = 57) and non-OA group (&lt;i>n&lt;/i> = 19) for early diagnosis and differential diagnosis of OA. Based on logistic regression analysis and receiver operating characteristic (ROC) curve analysis, seven metabolites, including phosphatidylcholine (</pubmed_abstract><journal>PeerJ</journal><pagination>e14563</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC9841907</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Diagnostic biomarker panels of osteoarthritis: UPLC-QToF/MS-based serum metabolic profiling.</pubmed_title><pmcid>PMC9841907</pmcid><pubmed_authors>He S</pubmed_authors><pubmed_authors>Zhang T</pubmed_authors><pubmed_authors>Gong S</pubmed_authors><pubmed_authors>Wu S</pubmed_authors><pubmed_authors>Gao Y</pubmed_authors><pubmed_authors>Lin X</pubmed_authors><pubmed_authors>Minjie T</pubmed_authors></additional><is_claimable>false</is_claimable><name>Diagnostic biomarker panels of osteoarthritis: UPLC-QToF/MS-based serum metabolic profiling.</name><description>Osteoarthritis (OA) is the most common joint disease in the world, characterized by pain and loss of joint function, which has led to a serious reduction in the quality of patients' lives. In this work, ultrahigh performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-QToF/MS) in conjunction with multivariate pattern recognition methods and an univariate statistical analysis scheme were applied to explore the serum metabolic signatures within OA group (&lt;i>n&lt;/i&gt; = 31), HC (healthy controls) group (&lt;i>n&lt;/i> = 57) and non-OA group (&lt;i>n&lt;/i> = 19) for early diagnosis and differential diagnosis of OA. Based on logistic regression analysis and receiver operating characteristic (ROC) curve analysis, seven metabolites, including phosphatidylcholine (</description><dates><release>2023-01-01T00:00:00Z</release><publication>2023</publication><modification>2025-04-04T14:28:26.226Z</modification><creation>2025-04-04T14:28:26.226Z</creation></dates><accession>S-EPMC9841907</accession><cross_references><pubmed>36655043</pubmed><doi>10.7717/peerj.14563</doi></cross_references></HashMap>