{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T14:26:13Z","timestamp":1790778373463,"version":"4.1.0"},"reference-count":51,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2020,12,8]],"date-time":"2020-12-08T00:00:00Z","timestamp":1607385600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Metabolites"],"abstract":"<jats:p>Autoimmune diseases (ADs) are chronic disorders characterized by the loss of self-tolerance, and although being heterogeneous, they share common pathogenic mechanisms. Self-antigens and inflammation markers are established diagnostic tools; however, the metabolic imbalances that underlie ADs are poorly described. The study aimed to employ metabolomics for the detection of disease-related changes in autoimmune diseases that could have predictive value. Quantitative analysis of 28 urine organic acids was performed using Gas Chromatography-Mass Spectrometry in a group of 392 participants. Autoimmune thyroiditis, inflammatory bowel disease, psoriasis and rheumatoid arthritis were the most prevalent autoimmune diseases of the study. Statistically significant differences were observed in the tricarboxylate cycle metabolites, succinate, methylcitrate and malate, the pyroglutamate and 2-hydroxybutyrate from the glutathione cycle and the metabolites methylmalonate, 4-hydroxyphenylpyruvate, 2-hydroxyglutarate and 2-hydroxyisobutyrate between the AD group and the control. Artificial neural networks and Binary logistic regression resulted in the highest predictive accuracy scores (66.7% and 74.9%, respectively), while Methylmalonate, 2-Hydroxyglutarate and 2-hydroxybutyrate were proposed as potential biomarkers for autoimmune diseases. Urine organic acid levels related to the mechanisms of energy production and detoxification were associated with the presence of autoimmune diseases and could be an adjunct tool for early diagnosis and prediction.<\/jats:p>","DOI":"10.3390\/metabo10120502","type":"journal-article","created":{"date-parts":[[2020,12,10]],"date-time":"2020-12-10T20:18:22Z","timestamp":1607631502000},"page":"502","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":45,"title":["Prediction of Autoimmune Diseases by Targeted Metabolomic Assay of Urinary Organic Acids"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6885-6209","authenticated-orcid":false,"given":"Dimitris","family":"Tsoukalas","sequence":"first","affiliation":[{"name":"Department of Clinical Pharmacy, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania"},{"name":"Metabolomic Medicine, Health Clinic for Autoimmune and Chronic Diseases, 10674 Athens, Greece"},{"name":"European Institute of Nutritional Medicine (E.I.Nu.M.), 00198 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vassileios","family":"Fragoulakis","sequence":"additional","affiliation":[{"name":"The Golden Helix Foundation, London WC2N 5AP, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Evangelos","family":"Papakonstantinou","sequence":"additional","affiliation":[{"name":"Metabolomic Medicine, Health Clinic for Autoimmune and Chronic Diseases, 10674 Athens, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maria","family":"Antonaki","sequence":"additional","affiliation":[{"name":"Laboratory of Health Economics &amp; Management, Economics Department, University of Piraeus, 18534 Piraeus, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8342-3839","authenticated-orcid":false,"given":"Athanassios","family":"Vozikis","sequence":"additional","affiliation":[{"name":"Laboratory of Health Economics &amp; Management, Economics Department, University of Piraeus, 18534 Piraeus, Greece"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3824-2462","authenticated-orcid":false,"given":"Aristidis","family":"Tsatsakis","sequence":"additional","affiliation":[{"name":"Laboratory of Toxicology and Forensic Sciences, Medical School, University of Crete, 71003 Heraklion, Greece"},{"name":"Department of Analytical and Forensic Medical Toxicology, Sechenov University, 119991 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0082-6956","authenticated-orcid":false,"given":"Ana Maria","family":"Buga","sequence":"additional","affiliation":[{"name":"Department of Biochemistry, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mihaela","family":"Mitroi","sequence":"additional","affiliation":[{"name":"ENT Department, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1523-9116","authenticated-orcid":false,"given":"Daniela","family":"Calina","sequence":"additional","affiliation":[{"name":"Department of Clinical Pharmacy, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,12,8]]},"reference":[{"key":"ref_1","first-page":"369","article-title":"Human autoimmune diseases: A comprehensive update","volume":"278","author":"Wang","year":"2015","journal-title":"J. Internet Med."},{"key":"ref_2","unstructured":"(2020, November 29). American Autoimmune Related Disease Association Autoimmune Diseases Statistics. Available online: https:\/\/www.aarda.org\/news-information\/statistics\/#1488234345468-3bf2d325-1052."},{"key":"ref_3","unstructured":"(2017). ENVI European Parliament Autoimmune Diseases-Modern Diseases, Directorate for Internal Policies (Workshop). Available online: https:\/\/www.europarl.europa.eu\/committees\/en\/autoimmune-diseases-modern-diseases\/product-details\/20170822WKS00741."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1462","DOI":"10.1136\/annrheumdis-2013-204680","article-title":"The global burden of other musculoskeletal disorders: Estimates from the Global Burden of Disease 2010 study","volume":"73","author":"Smith","year":"2014","journal-title":"Ann. Rheum. Dis."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2481","DOI":"10.1007\/s12325-017-0627-3","article-title":"Prevalence of Co-existing Autoimmune Disease in Rheumatoid Arthritis: A Cross-Sectional Study","volume":"34","author":"Simon","year":"2017","journal-title":"Adv. Ther."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"183.e1","DOI":"10.1016\/j.amjmed.2009.06.030","article-title":"Prevalence and Relative Risk of Other Autoimmune Diseases in Subjects with Autoimmune Thyroid Disease","volume":"123","author":"Boelaert","year":"2010","journal-title":"Am. J. Med."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"7683","DOI":"10.1038\/s41598-020-64732-8","article-title":"Prevalence and pattern of comorbidities in chronic rheumatic and musculoskeletal diseases: The COMORD study","volume":"10","author":"Ziade","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1038\/ncprheum0895","article-title":"Nature and functions of autoantibodies","volume":"4","author":"Elkon","year":"2008","journal-title":"Nat. Clin. Pr. Rheumatol."},{"key":"ref_9","first-page":"605","article-title":"Autoimmune disorders due to double antiviral therapy with peginterferon and ribavirin in patients with hepatitis C virus infection","volume":"64","author":"Docea","year":"2016","journal-title":"Farmacia"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1080\/0891693031000089427","article-title":"Evidence for Cytokine Dysregulation in Multiple Sclerosis: Peripheral Blood Mononuclear Cell Production of Pro-inflammatory and Anti-inflammatory Cytokines During Relapse and Remission","volume":"36","author":"Hollifield","year":"2003","journal-title":"Autoimmunity"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Mititelu, R.R., P\u0103dureanu, R., B\u0103c\u0103noiu, M., P\u0103dureanu, V., Docea, A.O., Calina, D., Barbulescu, A.L., and Buga, A.M. (2020). Inflammatory and Oxidative Stress Markers\u2014Mirror Tools in Rheumatoid Arthritis. Biomedicines, 8.","DOI":"10.3390\/biomedicines8050125"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Tsoukalas, D., Sarandi, E., Thanasoula, M., Docea, A.O., Tsilimidos, G., Calina, D., and Tsatsakis, A. (2019). Metabolic Fingerprint of Chronic Obstructive Lung Diseases: A New Diagnostic Perspective. Metabolites, 9.","DOI":"10.3390\/metabo9120290"},{"key":"ref_13","first-page":"294","article-title":"Metabolomics for the masses: The future of metabolomics in a personalized world","volume":"3","author":"Trivedi","year":"2017","journal-title":"New Horiz. Transl. Med."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1038\/s41467-019-13668-3","article-title":"Mitochondrial TCA cycle metabolites control physiology and disease","volume":"11","author":"Chandel","year":"2020","journal-title":"Nat. Commun."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"112","DOI":"10.3892\/ijmm.2017.2983","article-title":"Application of metabolomics: Focus on the quantification of organic acids in healthy adults","volume":"40","author":"Tsoukalas","year":"2017","journal-title":"Int. J. Mol. Med."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Sarandi, E., Thanasoula, M., Anamaterou, C., Papakonstantinou, E., Geraci, F., Papamichael, M.M., Itsiopoulos, C., and Tsoukalas, D. (2020). Metabolic Profiling of Organic and Fatty Acids in Chronic and Autoimmune Diseases, Elsevier Inc.. [1st ed.].","DOI":"10.1016\/bs.acc.2020.06.003"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1691","DOI":"10.1289\/ehp.7199","article-title":"Epidemiologic evaluation of measurement data in the presence of detection limits","volume":"112","author":"Lubin","year":"2004","journal-title":"Environ. Health Perspect."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3389\/fmolb.2019.00120","article-title":"Targeted Metabolomic Analysis of Serum Fatty Acids for the Prediction of Autoimmune Diseases","volume":"6","author":"Tsoukalas","year":"2019","journal-title":"Front. Mol. Biosci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"e12706","DOI":"10.14814\/phy2.12706","article-title":"Long-term patterns of urinary pyroglutamic acid in healthy humans","volume":"4","author":"Lord","year":"2016","journal-title":"Physiol. Rep."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1016\/j.jchromb.2018.09.004","article-title":"Fasting serum \u03b1-hydroxybutyrate and pyroglutamic acid as important metabolites for detecting isolated post-challenge diabetes based on organic acid profiles","volume":"1100\u20131101","author":"Chou","year":"2018","journal-title":"J. Chromatogr. B"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"995","DOI":"10.1017\/S0007114511001279","article-title":"Anti-diabetic effect of pyroglutamic acid in type 2 diabetic Goto-Kakizaki rats and KK-A y mice","volume":"106","author":"Yoshinari","year":"2011","journal-title":"Br. J. Nutr."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"27","DOI":"10.3389\/fmolb.2016.00027","article-title":"Biomarkers and Algorithms for the Diagnosis of Vitamin B 12 Deficiency","volume":"3","author":"Hannibal","year":"2016","journal-title":"Front. Mol. Biosci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"624","DOI":"10.1038\/nm.2682","article-title":"2-hydroxyglutarate detection by magnetic resonance spectroscopy in IDH-mutated patients with gliomas","volume":"18","author":"Choi","year":"2012","journal-title":"Nat. Med."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"666","DOI":"10.1001\/archneur.62.4.666","article-title":"L-2-Hydroxyglutaric Aciduria: Clinical, Neuroimaging, and Neuropathological Findings","volume":"62","author":"Navarro","year":"2005","journal-title":"Arch. Neurol."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Wang, H., Zhang, H., Deng, P., Liu, C., Li, D., Jie, H., Zhang, H., Zhou, Z., and Zhao, Y.-L. (2016). Tissue metabolic profiling of human gastric cancer assessed by 1H NMR. BMC Cancer, 16.","DOI":"10.1186\/s12885-016-2356-4"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Mutsaers, H.A.M., Engelke, U.F.H., Wilmer, M.J.G., Wetzels, J.F.M., Wevers, R.A., van den Heuvel, L.P., Hoenderop, J.G., and Masereeuw, R. (2013). Optimized Metabolomic Approach to Identify Uremic Solutes in Plasma of Stage 3\u20134 Chronic Kidney Disease Patients. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0071199"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"5775","DOI":"10.1038\/s41598-018-24128-1","article-title":"GC-MS-based urinary organic acid profiling reveals multiple dysregulated metabolic pathways following experimental acute alcohol consumption","volume":"8","author":"Irwin","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"828","DOI":"10.1161\/01.HYP.0000163475.04421.e4","article-title":"Mechanisms of insulin resistance in humans and possible links with inflammation","volume":"45","author":"Savage","year":"2005","journal-title":"Hypertension"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"902","DOI":"10.1002\/acn3.486","article-title":"4-Hydroxybenzoic acid restores CoQ10 biosynthesis in human COQ2 deficiency","volume":"4","author":"Herebian","year":"2017","journal-title":"Ann. Clin. Transl. Neurol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"7446","DOI":"10.1021\/ja00728a032","article-title":"Mechanism of enzymic formation of homogentisate from p-hydroxyphenylpyruvate","volume":"92","author":"Lindblad","year":"1970","journal-title":"J. Am. Chem. Soc."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1855","DOI":"10.1007\/s00125-015-3636-2","article-title":"A systems view of type 2 diabetes-associated metabolic perturbations in saliva, blood and urine at different timescales of glycaemic control","volume":"58","author":"Yousri","year":"2015","journal-title":"Diabetologia"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1007\/s11306-019-1625-z","article-title":"Metabolomic profile overlap in prototypical autoimmune humoral disease: A comparison of myasthenia gravis and rheumatoid arthritis","volume":"16","author":"Blackmore","year":"2020","journal-title":"Metabolomics"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"694","DOI":"10.3389\/fphys.2020.00694","article-title":"Lifestyle, Oxidative Stress, and Antioxidants: Back and Forth in the Pathophysiology of Chronic Diseases","volume":"11","author":"Zucca","year":"2020","journal-title":"Front. Physiol."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Sharifi-Rad, J., Rodrigues, C.F., Sharopov, F., Docea, A.O., Karaca, A.C., Sharifi-Rad, M., Karincaoglu, D.K., G\u00fclseren, G., \u015eenol, E., and Demircan, E. (2020). Diet, lifestyle and cardiovascular diseases: Linking pathophysiology to cardioprotective effects of natural bioactive compounds. Int. J. Environ. Res. Public Health, 17.","DOI":"10.3390\/ijerph17072326"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Arnald, A., Juli\u00e0, A., Vinaixa, M., Dom\u00e8nech, E., Fern\u00e1ndez-Nebro, A., Ca\u00f1ete, J.D., Ferr\u00e1ndiz, C., Tornero, J., Gisbert, J.P., and Nos, P. (2016). Urine metabolome profiling of immune-mediated inflammatory diseases. BMC Med., 14.","DOI":"10.1186\/s12916-016-0681-8"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Nyamundanda, G., Gormley, I.C., Fan, Y., Gallagher, W.M., and Brennan, L. (2013). MetSizeR: Selecting the optimal sample size for metabolomic studies using an analysis based approach. BMC Bioinform., 14.","DOI":"10.1186\/1471-2105-14-338"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1016\/S0140-6736(02)07605-5","article-title":"Case-control studies: Research in reverse","volume":"359","author":"Schulz","year":"2002","journal-title":"Lancet"},{"key":"ref_38","first-page":"5","article-title":"ACR\/EULAR 2010 rheumatoid arthritis classification criteria","volume":"51","author":"Kay","year":"2012","journal-title":"Rheumatology (UK)"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Mamula, P., and Grossman, A.B. (2017). Classification of inflammatory bowel disease in children. Pediatric Inflammatory Bowel Disease, Springer. [3rd ed.].","DOI":"10.1007\/978-3-319-49215-5"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"292","DOI":"10.1002\/ana.22366","article-title":"Diagnostic criteria for multiple sclerosis: 2010 Revisions to the McDonald criteria","volume":"69","author":"Polman","year":"2011","journal-title":"Ann. Neurol."},{"key":"ref_41","unstructured":"(2020, November 29). IBM SPSS Software. Available online: https:\/\/www.ibm.com\/analytics\/spss-statistics-software."},{"key":"ref_42","unstructured":"Foundation, T.R. (2020, November 29). The R Project for Statistical Computing. Available online: https:\/\/www.r-project.org\/."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1136\/bmj.323.7309.391","article-title":"Mann-Whitney test is not just a test of medians: Differences in spread can be important","volume":"323","author":"Hart","year":"2001","journal-title":"BMJ"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"775","DOI":"10.3390\/metabo2040775","article-title":"A guideline to univariate statistical analysis for LC\/MS-based untargeted metabolomics-derived data","volume":"2","author":"Vinaixa","year":"2012","journal-title":"Metabolites"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1002\/bimj.201700067","article-title":"Variable selection\u2014A review and recommendations for the practicing statistician","volume":"60","author":"Heinze","year":"2018","journal-title":"Biom. J."},{"key":"ref_46","unstructured":"Sordo, M. (2002). Introduction to neural networks in healthcare. Open Clin., Available online: https:\/\/www.academia.edu\/20719514\/Introduction_to_neural_networks_in_healthcare."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"719","DOI":"10.1038\/s41551-018-0305-z","article-title":"Artificial intelligence in healthcare","volume":"2","author":"Yu","year":"2018","journal-title":"Nat. Biomed. Eng."},{"key":"ref_48","first-page":"627","article-title":"Receiver Operating Characteristic (ROC) Curve Analysis for Medical Diagnostic Test Evaluation","volume":"4","year":"2013","journal-title":"Casp. J. Internet Med."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Rose, S., and van der Laan, M.J. (2009). Why Match? Investigating Matched Case-Control Study Designs with Causal Effect Estimation. Int. J. Biostat., 5.","DOI":"10.2202\/1557-4679.1127"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"325","DOI":"10.3390\/ijerph7010325","article-title":"To match or not to match in epidemiological studies\u2014Same outcome but less power","volume":"7","year":"2010","journal-title":"Int. J. Environ. Res. Public Health"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"e86","DOI":"10.1002\/cpbi.86","article-title":"Using MetaboAnalyst 4.0 for Comprehensive and Integrative Metabolomics Data Analysis","volume":"68","author":"Chong","year":"2019","journal-title":"Curr. Protoc. Bioinf."}],"container-title":["Metabolites"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2218-1989\/10\/12\/502\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:42:28Z","timestamp":1760179348000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2218-1989\/10\/12\/502"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12,8]]},"references-count":51,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2020,12]]}},"alternative-id":["metabo10120502"],"URL":"https:\/\/doi.org\/10.3390\/metabo10120502","relation":{},"ISSN":["2218-1989"],"issn-type":[{"value":"2218-1989","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,12,8]]}}}