{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T11:08:23Z","timestamp":1771240103343,"version":"3.50.1"},"reference-count":39,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T00:00:00Z","timestamp":1771027200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001807","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo","doi-asserted-by":"publisher","award":["2022\/09354-9"],"award-info":[{"award-number":["2022\/09354-9"]}],"id":[{"id":"10.13039\/501100001807","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJMS"],"abstract":"<jats:p>Human T-cell lymphotropic virus type 1 (HTLV-1) can cause HTLV-1-associated myelopathy\/tropical spastic paraparesis (HAM\/TSP), a progressive neuroinflammatory disease that lacks noninvasive biomarkers. We used untargeted urine metabolomics with machine learning to profile 113 participants (39 with HAM, 17 with intermediate syndrome, 33 asymptomatic carriers, and 24 healthy controls). Gas chromatography\u2013mass spectrometry identified 175 metabolites, 86 of which showed significant differences (fold change &gt; 2, FDR p &lt; 0.05). Multivariate analyses revealed distinct but partially overlapping metabolic profiles: sPLS-DA captured a reproducible yet moderately discriminative signal, while nonlinear machine learning models (Random Forest and SVM) achieved robust group separation, with HAM displaying a distinct metabolic signature. Key discriminators included Unknown_151, Unknown_127, histidine, alanine, and 4-hydroxyphenylacetic acid, which showed marked reductions in HAM and yielded ROC AUCs of 0.855\u20130.871. Pathway and disease enrichment analyses highlighted disturbances in amino acid metabolism, particularly beta-alanine and aromatic amino acids, along with disease signatures related to inherited amino acid handling disorders such as hyperlysinemia. These results demonstrate that urinary metabolomics combined with machine learning can identify potential noninvasive biomarkers for HAM and provide novel insights into HTLV-1-associated pathophysiology.<\/jats:p>","DOI":"10.3390\/ijms27041827","type":"journal-article","created":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T10:14:32Z","timestamp":1771236872000},"page":"1827","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Urine Metabolomics and Machine Learning Identify Metabolic Features and Potential Biomarkers of HTLV-1-Associated Myelopathy (HAM)"],"prefix":"10.3390","volume":"27","author":[{"given":"Lorena Abreu","family":"Fernandes","sequence":"first","affiliation":[{"name":"Postgraduate Program in Translational Medicine, Department of Medicine, Federal University of S\u00e3o Paulo (UNIFESP), S\u00e3o Paulo 04023-062, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7774-4716","authenticated-orcid":false,"given":"Youko","family":"Nukui","sequence":"additional","affiliation":[{"name":"Department of Hematology, Faculty of Medicine, University of S\u00e3o Paulo, S\u00e3o Paulo 05403-000, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8396-0263","authenticated-orcid":false,"given":"Rosa Maria","family":"Marcusso","sequence":"additional","affiliation":[{"name":"Department of Neurology, Emilio Ribas Institute of Infectious Diseases, S\u00e3o Paulo 01246-900, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michel Elyas Jung","family":"Haziot","sequence":"additional","affiliation":[{"name":"Department of Neurology, Emilio Ribas Institute of Infectious Diseases, S\u00e3o Paulo 01246-900, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4084-7973","authenticated-orcid":false,"given":"Augusto C\u00e9sar Penalva","family":"de Oliveira","sequence":"additional","affiliation":[{"name":"Department of Neurology, Emilio Ribas Institute of Infectious Diseases, S\u00e3o Paulo 01246-900, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4553-2559","authenticated-orcid":false,"given":"Jorge","family":"Casseb","sequence":"additional","affiliation":[{"name":"Laboratory of Medical Investigation LIM-56, Department of Dermatology, University of S\u00e3o Paulo, S\u00e3o Paulo 05403-000, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Patricia Bianca","family":"Clissa","sequence":"additional","affiliation":[{"name":"Immunopathology Laboratory, Butantan Institute, S\u00e3o Paulo 05503-900, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6025-7500","authenticated-orcid":false,"given":"Ana","family":"Olivia de Souza","sequence":"additional","affiliation":[{"name":"Development and Innovation Laboratory, Instituto Butantan, Avenida Vital Brasil, 1500, S\u00e3o Paulo 05503-900, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0148-5882","authenticated-orcid":false,"given":"Silas G.","family":"Villas-Boas","sequence":"additional","affiliation":[{"name":"Luxembourg Institute of Science and Technology, 5, Avenue des Hauts-Fourneaux, L-4362 Esch-sur-Alzette, Luxembourg"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8876-8262","authenticated-orcid":false,"given":"Sabri Saeed","family":"Sanabani","sequence":"additional","affiliation":[{"name":"Laboratory of Medical Investigation LIM-56, Department of Dermatology, University of S\u00e3o Paulo, S\u00e3o Paulo 05403-000, Brazil"},{"name":"Laboratory of Medical Investigation LIM-03, Department of Pathology, University of S\u00e3o Paulo, S\u00e3o Paulo 05403-000, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"6476","DOI":"10.1073\/pnas.78.10.6476","article-title":"Adult T-cell leukemia: Antigen in an ATL cell line and detection of antibodies to the antigen in human sera","volume":"78","author":"Hinuma","year":"1981","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1016\/S0140-6736(85)92734-5","article-title":"Antibodies to human T-lymphotropic virus type-I in patients with tropical spastic paraparesis","volume":"2","author":"Gessain","year":"1985","journal-title":"Lancet"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"686","DOI":"10.1590\/S0004-282X2012000900007","article-title":"Difficulties in HAM\/TSP diagnosis","volume":"70","author":"Slater","year":"2012","journal-title":"Arq. Neuropsiquiatr."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2230015","DOI":"10.1080\/21505594.2023.2230015","article-title":"Identification of miRnas with possible prognostic roles for HAM\/TSP","volume":"14","author":"Pessoa","year":"2023","journal-title":"Virulence"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Souza, F.D.S., Freitas, N.L., Gomes, Y.C.P., Torres, R.C., Echevarria-Lima, J., da Silva-Filho, I.L., Leite, A., de Lima, M., da Silva, M.T.T., and Araujo, A.Q.C. (2021). Following the Clues: Usefulness of Biomarkers of Neuroinflammation and Neurodegeneration in the Investigation of HTLV-1-Associated Myelopathy Progression. Front. Immunol., 12.","DOI":"10.3389\/fimmu.2021.737941"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Sato, T., Yagishita, N., Tamaki, K., Inoue, E., Hasegawa, D., Nagasaka, M., Suzuki, H., Araya, N., Coler-Reilly, A., and Hasegawa, Y. (2018). Proposal of Classification Criteria for HTLV-1-Associated Myelopathy\/Tropical Spastic Paraparesis Disease Activity. Front. Microbiol., 9.","DOI":"10.3389\/fmicb.2018.01651"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Gomez-Archila, L.G., Palomino-Schatzlein, M., Zapata-Builes, W., Rugeles, M.T., and Galeano, E. (2023). Plasma metabolomics by nuclear magnetic resonance reveals biomarkers and metabolic pathways associated with the control of HIV-1 infection\/progression. Front. Mol. Biosci., 10.","DOI":"10.3389\/fmolb.2023.1204273"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1038\/s41392-023-01399-3","article-title":"Small molecule metabolites: Discovery of biomarkers and therapeutic targets","volume":"8","author":"Qiu","year":"2023","journal-title":"Signal Transduct. Target. Ther."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"659","DOI":"10.1021\/acs.jproteome.5b01111","article-title":"A Urinary Metabolic Signature for Multiple Sclerosis and Neuromyelitis Optica","volume":"15","author":"Gebregiworgis","year":"2016","journal-title":"J. Proteome Res."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Donatti, A., Canto, A.M., Godoi, A.B., da Rosa, D.C., and Lopes-Cendes, I. (2020). Circulating Metabolites as Potential Biomarkers for Neurological Disorders-Metabolites in Neurological Disorders. Metabolites, 10.","DOI":"10.3390\/metabo10100389"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.jpba.2014.12.017","article-title":"Metabolomics for laboratory diagnostics","volume":"113","author":"Bujak","year":"2015","journal-title":"J. Pharm. Biomed. Anal."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"370","DOI":"10.1074\/mcp.M111.016006","article-title":"Urine metabolomics analysis for biomarker discovery and detection of jaundice syndrome in patients with liver disease","volume":"11","author":"Wang","year":"2012","journal-title":"Mol. Cell Proteomics"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1007\/s11481-018-9815-4","article-title":"Urinary and Plasma Metabolomics Identify the Distinct Metabolic Profile of Disease State in Chronic Mouse Model of Multiple Sclerosis","volume":"14","author":"Singh","year":"2019","journal-title":"J. Neuroimmune Pharmacol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1377","DOI":"10.1038\/s41592-021-01303-3","article-title":"Metabolite discovery through global annotation of untargeted metabolomics data","volume":"18","author":"Chen","year":"2021","journal-title":"Nat. Methods"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"e23146","DOI":"10.1590\/s2175-97902023e23146","article-title":"Advancements in artificial intelligence and machine learning in revolutionising biomarker discovery","volume":"59","author":"Raikar","year":"2023","journal-title":"Braz. J. Pharm. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1657","DOI":"10.1038\/s41467-024-46043-y","article-title":"Metabolomic machine learning predictor for diagnosis and prognosis of gastric cancer","volume":"15","author":"Chen","year":"2024","journal-title":"Nat. Commun."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"15139","DOI":"10.1038\/s41598-023-42338-0","article-title":"Machine learning approaches for biomarker discovery to predict large-artery atherosclerosis","volume":"13","author":"Sun","year":"2023","journal-title":"Sci. Rep."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"4327","DOI":"10.1016\/j.apsb.2025.07.030","article-title":"Artificial intelligence-driven multi-omics approaches in Alzheimer\u2019s disease: Progress, challenges, and future directions","volume":"15","author":"Ren","year":"2025","journal-title":"Acta Pharm. Sin. B"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"102954","DOI":"10.1016\/j.arr.2025.102954","article-title":"Next-generation biosensor technologies for Alzheimer\u2019s disease: Innovations in diagnosis, monitoring, and treatment","volume":"114","author":"Yin","year":"2026","journal-title":"Ageing Res. Rev."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"e17110","DOI":"10.2196\/17110","article-title":"Predicting Metabolic Syndrome with Machine Learning Models Using a Decision Tree Algorithm: Retrospective Cohort Study","volume":"8","author":"Yu","year":"2020","journal-title":"JMIR Med. Inform."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Galal, A., Talal, M., and Moustafa, A. (2022). Applications of machine learning in metabolomics: Disease modeling and classification. Front. Genet., 13.","DOI":"10.3389\/fgene.2022.1017340"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"c26","DOI":"10.1159\/000106509","article-title":"Antiglycation and antioxidant effect of carnosine against glucose degradation products in peritoneal mesothelial cells","volume":"107","author":"Alhamdani","year":"2007","journal-title":"Nephron Clin. Pract."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"3839","DOI":"10.1007\/s12035-023-03303-0","article-title":"Th17\/IL-17 Axis in HTLV-1-Associated Myelopathy Tropical Spastic Paraparesis and Multiple Sclerosis: Novel Insights into the Immunity During HAMTSP","volume":"60","author":"Shafiei","year":"2023","journal-title":"Mol. Neurobiol."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Nozuma, S., and Jacobson, S. (2019). Neuroimmunology of Human T-Lymphotropic Virus Type 1-Associated Myelopathy\/Tropical Spastic Paraparesis. Front. Microbiol., 10.","DOI":"10.3389\/fmicb.2019.00885"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Martynova, E., Khaibullin, T., Salafutdinov, I., Markelova, M., Laikov, A., Lopukhov, L., Liu, R., Sahay, K., Goyal, M., and Baranwal, M. (2023). Seasonal Changes in Serum Metabolites in Multiple Sclerosis Relapse. Int. J. Mol. Sci., 24.","DOI":"10.3390\/ijms24043542"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Ye, Z., Wang, S., Zhang, C., and Zhao, Y. (2020). Coordinated Modulation of Energy Metabolism and Inflammation by Branched-Chain Amino Acids and Fatty Acids. Front. Endocrinol., 11.","DOI":"10.3389\/fendo.2020.00617"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"12171","DOI":"10.1038\/s41598-020-68739-z","article-title":"Divergence in the metabolome between natural aging and Alzheimer\u2019s disease","volume":"10","author":"Hunsberger","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Li, Q., and Hoppe, T. (2023). Role of amino acid metabolism in mitochondrial homeostasis. Front. Cell Dev. Biol., 11.","DOI":"10.3389\/fcell.2023.1127618"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1016\/S1097-2765(03)00105-9","article-title":"An integrated stress response regulates amino acid metabolism and resistance to oxidative stress","volume":"11","author":"Harding","year":"2003","journal-title":"Mol. Cell"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Solis, M.Y., Cooper, S., Hobson, R.M., Artioli, G.G., Otaduy, M.C., Roschel, H., Robertson, J., Martin, D., Painelli, V.S., and Harris, R.C. (2015). Effects of beta-alanine supplementation on brain homocarnosine\/carnosine signal and cognitive function: An exploratory study. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0123857"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"P7.253","DOI":"10.1212\/WNL.82.10_supplement.P7.253","article-title":"A Double-Blind Placebo Controlled Study of the Effect of Beta-Alanine, a Nonessential Amino-Acid, on Neurologic, Motor Function, Quality of Life, and Fatigue in Patients Diagnosed with Multiple Sclerosis (P7.253)","volume":"82","author":"Kanter","year":"2014","journal-title":"Neurology"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1007\/s11306-024-02161-8","article-title":"Characterising the urinary acylcarnitine and amino acid profiles of HIV\/TB co-infection, using LC-MS metabolomics","volume":"20","author":"Pretorius","year":"2024","journal-title":"Metabolomics"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"3181","DOI":"10.1007\/s00018-020-03733-2","article-title":"An emerging potential of metabolomics in multiple sclerosis: A comprehensive overview","volume":"78","author":"Zahoor","year":"2021","journal-title":"Cell. Mol. Life Sci."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Haziot, M.E., Gascon, M.R., Assone, T., Fonseca, L.A.M., Luiz, O.D.C., Smid, J., Paiva, A.M., Marcusso, R., de Oliveira, A.C.P., and Casseb, J. (2019). Detection of clinical and neurological signs in apparently asymptomatic HTLV-1 infected carriers: Association with high proviral load. PLoS Negl. Trop. Dis., 13.","DOI":"10.1371\/journal.pntd.0006967"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Marcusso, R., Assone, T., Haziot, M.E., Smid, J., Folgosi, V.A., Rosadas, C., Casseb, J., de Oliveira, A.C.P., and The Htlv-Clinical Definition Working Group (2024). HTLV-1-Associated Myelopathy (HAM) Incidence in Asymptomatic Carriers and Intermediate Syndrome (IS) Patients. Pathogens, 13.","DOI":"10.3390\/pathogens13050403"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"544","DOI":"10.1016\/j.foodres.2018.11.004","article-title":"Human urine metabolomic signature after ingestion of polyphenol-rich juice of purple grumixama (Eugenia brasiliensis Lam.)","volume":"120","author":"Teixeira","year":"2019","journal-title":"Food Res. Int."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1709","DOI":"10.1038\/nprot.2010.108","article-title":"Analytical platform for metabolome analysis of microbial cells using methyl chloroformate derivatization followed by gas chromatography-mass spectrometry","volume":"5","author":"Smart","year":"2010","journal-title":"Nat. Protoc."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"W398","DOI":"10.1093\/nar\/gkae253","article-title":"MetaboAnalyst 6.0: Towards a unified platform for metabolomics data processing, analysis and interpretation","volume":"52","author":"Pang","year":"2024","journal-title":"Nucleic Acids Res."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"D587","DOI":"10.1093\/nar\/gkac963","article-title":"KEGG for taxonomy-based analysis of pathways and genomes","volume":"51","author":"Kanehisa","year":"2023","journal-title":"Nucleic Acids Res."}],"container-title":["International Journal of Molecular Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1422-0067\/27\/4\/1827\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T10:17:18Z","timestamp":1771237038000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1422-0067\/27\/4\/1827"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,14]]},"references-count":39,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2026,2]]}},"alternative-id":["ijms27041827"],"URL":"https:\/\/doi.org\/10.3390\/ijms27041827","relation":{},"ISSN":["1422-0067"],"issn-type":[{"value":"1422-0067","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,14]]}}}