{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T19:51:11Z","timestamp":1790020271853,"version":"4.0.1"},"reference-count":107,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T00:00:00Z","timestamp":1770940800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100021856","name":"Ministero dell\u2019Universit\u00e0 e della Ricerca","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100021856","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Psychiatry"],"abstract":"<jats:p>Mental disorders remain diagnosed primarily through symptom-based classification systems that overlook biological heterogeneity, preventing the identification of mechanistically distinct patient subgroups and precluding pathophysiology-guided treatment selection. Metabolomics offers a promising pathway towards precision psychiatry by capturing dynamic biochemical readouts at the functional endpoint of the omics cascade, integrating genetic, environmental, and pharmacological influences on cellular metabolism. Over the past 15 years, untargeted and targeted metabolomics studies using nuclear magnetic resonance spectroscopy and mass spectrometry have identified consistent patterns of metabolic dysregulation across psychiatric disorders, particularly involving amino acid metabolism, lipid signaling, energy homeostasis, and oxidative stress pathways. Schizophrenia presents disruptions in arginine and proline metabolism, glutathione metabolism, and energy-related processes. Bipolar disorder shows perturbations in branched-chain and aromatic amino acids, kynurenine pathway, and tricarboxylic acid cycle dysfunction with phase-specific metabolic signatures. Major depressive disorder exhibits widespread alterations in amino acid turnover, bioenergetic processes, membrane lipid homeostasis, and glutamate-GABA cycling, with treatment-responsive metabolic changes. Despite these advances, substantial challenges remain: heterogeneous findings with disorder overlap, limited replication cohorts, predominance of cross-sectional designs, confounding by medication and lifestyle factors, pre-analytical variability, and high-dimensional data complexity. Future research requires harmonized multi-site protocols, longitudinal validation studies, multi-platform analytical approaches, integration with genomics, proteomics, and digital phenotyping, and implementation of artificial intelligence frameworks to enhance phenotype discrimination and predictive accuracy. In this mini-review, we provide an overview of current methodologies, major findings, strengths, challenges, and emerging directions in psychiatric metabolomics, with the goal of facilitating the translation of metabolomic insights into clinically applicable, personalized psychiatric treatment.<\/jats:p>","DOI":"10.3389\/fpsyt.2026.1736206","type":"journal-article","created":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T06:38:33Z","timestamp":1770964713000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Metabolomics biomarkers for precision psychiatry"],"prefix":"10.3389","volume":"17","author":[{"given":"Daniele","family":"Cavaleri","sequence":"first","affiliation":[{"name":"School of Medicine and Surgery, University of Milano-Bicocca","place":["Monza, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carlo","family":"Bassetti","sequence":"additional","affiliation":[{"name":"School of Medicine and Surgery, University of Milano-Bicocca","place":["Monza, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giorgio","family":"Cucchi","sequence":"additional","affiliation":[{"name":"School of Medicine and Surgery, University of Milano-Bicocca","place":["Monza, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pasquale","family":"De Fazio","sequence":"additional","affiliation":[{"name":"Department of Health Sciences, University \u201cMagna Graecia\u201d of Catanzaro","place":["Catanzaro, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Renato","family":"de Filippis","sequence":"additional","affiliation":[{"name":"Department of Health Sciences, University \u201cMagna Graecia\u201d of Catanzaro","place":["Catanzaro, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Umberto","family":"Albert","sequence":"additional","affiliation":[{"name":"Department of Medicine, Surgery and Health Sciences, University of Trieste","place":["Trieste, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luca","family":"Pellegrini","sequence":"additional","affiliation":[{"name":"Department of Medicine, Surgery and Health Sciences, University of Trieste","place":["Trieste, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giuseppe","family":"Carr\u00e0","sequence":"additional","affiliation":[{"name":"School of Medicine and Surgery, University of Milano-Bicocca","place":["Monza, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesco","family":"Bartoli","sequence":"additional","affiliation":[{"name":"School of Medicine and Surgery, University of Milano-Bicocca","place":["Monza, Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,2,13]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1002\/wps.20436","article-title":"Etiology in psychiatry: embracing the reality of poly-gene-environmental causation of mental illness","volume":"16","author":"Uher","year":"2017","journal-title":"World Psychiatry"},{"key":"B2","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1002\/wps.20998","article-title":"Psychiatric diagnosis and treatment in the 21st century: paradigm shifts versus incremental integration","volume":"21","author":"Stein","year":"2022","journal-title":"World Psychiatry"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2020.00432","article-title":"Biomarkers in psychiatry: concept, definition, types and relevance to the clinical reality","volume":"11","author":"Garc\u00eda-Guti\u00e9rrez","year":"2020","journal-title":"Front Psychiatry"},{"key":"B4","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/j.psychres.2019.07.005","article-title":"Heterogeneity in psychiatric diagnostic classification","volume":"279","author":"Allsopp","year":"2019","journal-title":"Psychiatry Res"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1038\/s41380-025-03070-5","article-title":"Precision psychiatry roadmap: towards a biology-informed framework for mental disorders","volume":"30","author":"Kas","year":"2025","journal-title":"Mol Psychiatry"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1038\/nrm.2016.25","article-title":"Metabolomics: beyond biomarkers and towards mechanisms","volume":"17","author":"Johnson","year":"2016","journal-title":"Nat Rev Mol Cell Biol"},{"key":"B7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-21735-8_10","article-title":"Metabolomics biomarkers for precision psychiatry","volume":"1161","author":"Shih","year":"2019","journal-title":"Adv Exp Med Biol"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1038\/nrm3314","article-title":"Metabolomics: the apogee of the omics trilogy","volume":"13","author":"Patti","year":"2012","journal-title":"Nat Rev Mol Cell Biol"},{"key":"B9","doi-asserted-by":"publisher","first-page":"254","DOI":"10.1186\/s10020-025-01258-7","article-title":"Validated metabolomic biomarkers in psychiatric disorders: a narrative review","volume":"31","author":"Konjevod","year":"2025","journal-title":"Mol Med"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.1016\/j.pnpbp.2019.03.010","article-title":"Advances and challenges in development of precision psychiatry through clinical metabolomics on mood and psychotic disorders","volume":"93","author":"Pedrini","year":"2019","journal-title":"Prog Neuropsychopharmacol Biol Psychiatry"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.1074\/mcp.M112.021816","article-title":"Identification and validation of urinary metabolite biomarkers for major depressive disorder","volume":"12","author":"Zheng","year":"2013","journal-title":"Mol Cell Proteomics"},{"key":"B12","doi-asserted-by":"publisher","first-page":"e149","DOI":"10.1038\/tp.2012.76","article-title":"Schizophrenia shows a unique metabolomics signature in plasma","volume":"2","author":"He","year":"2012","journal-title":"Transl Psychiatry"},{"key":"B13","doi-asserted-by":"publisher","first-page":"e327","DOI":"10.1371\/journal.pmed.0030327","article-title":"Metabolic profiling of CSF: evidence that early intervention may impact on disease progression and outcome in schizophrenia","volume":"3","author":"Holmes","year":"2006","journal-title":"PloS Med"},{"key":"B14","doi-asserted-by":"publisher","first-page":"16310","DOI":"10.1038\/s41598-020-72914-7","article-title":"Short-term variability of the human serum metabolome depending on nutritional and metabolic health status","volume":"10","author":"Agueusop","year":"2020","journal-title":"Sci Rep"},{"key":"B15","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.3584","article-title":"Real-time metabolome profiling of the metabolic switch between starvation and growth","volume":"12","author":"Link","year":"2015","journal-title":"Nat Methods"},{"key":"B16","doi-asserted-by":"publisher","DOI":"10.1007\/s00439-023-02560-2","article-title":"The omics era: a nexus of untapped potential for Mendelian chromatinopathies","volume":"143","author":"Nava","year":"2024","journal-title":"Hum Genet"},{"key":"B17","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1038\/s41398-024-02886-z","article-title":"Identifying plasma metabolic characteristics of major depressive disorder, bipolar disorder, and schizophrenia in adolescents","volume":"14","author":"Yin","year":"2024","journal-title":"Transl Psychiatry"},{"key":"B18","doi-asserted-by":"publisher","DOI":"10.3390\/metabo10020047","article-title":"Salivary metabolomics: from diagnostic biomarker discovery to investigating biological function","volume":"10","author":"Gardner","year":"2020","journal-title":"Metabolites"},{"key":"B19","doi-asserted-by":"publisher","first-page":"30964","DOI":"10.1038\/s41598-024-82041-2","article-title":"Evaluation of metabolite stability in dried blood spot stored at different temperatures and times","volume":"14","author":"Cui","year":"2024","journal-title":"Sci Rep"},{"key":"B20","doi-asserted-by":"publisher","DOI":"10.3390\/metabo9080156","article-title":"Pre-analytical factors that affect metabolite stability in human urine, plasma, and serum: A review","volume":"9","author":"Stevens","year":"2019","journal-title":"Metabolites"},{"key":"B21","doi-asserted-by":"publisher","DOI":"10.3390\/metabo12080678","article-title":"NMR and metabolomics\u2013A roadmap for the future","volume":"12","author":"Wishart","year":"2022","journal-title":"Metabolites"},{"key":"B22","doi-asserted-by":"publisher","first-page":"e0218549","DOI":"10.1371\/journal.pone.0218549","article-title":"Assessment of reproducibility and biological variability of fasting and postprandial plasma metabolite concentrations using 1H NMR spectroscopy","volume":"14","author":"Li-Gao","year":"2019","journal-title":"PloS One"},{"key":"B23","doi-asserted-by":"publisher","DOI":"10.3390\/metabo9070123","article-title":"NMR spectroscopy for metabolomics research","volume":"9","author":"Emwas","year":"2019","journal-title":"Metabolites"},{"key":"B24","doi-asserted-by":"publisher","DOI":"10.1186\/s12953-025-00241-8","article-title":"Mass-spectrometry based metabolomics: an overview of workflows, strategies, data analysis and applications","volume":"23","author":"Hajnajafi","year":"2025","journal-title":"Proteome Sci"},{"key":"B25","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1038\/s43586-022-00175-x","article-title":"Liquid chromatography-tandem mass spectrometry for clinical diagnostics","volume":"2","author":"Thomas","year":"2022","journal-title":"Nat Rev Methods Primers"},{"key":"B26","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jproteome.8b00567","article-title":"Combining mass spectrometry and NMR improves metabolite detection and annotation","volume":"17","author":"Bhinderwala","year":"2018","journal-title":"J Proteome Res"},{"key":"B27","doi-asserted-by":"publisher","DOI":"10.1016\/j.redox.2017.09.002","article-title":"Short overview on metabolomic approach and redox changes in psychiatric disorders","volume":"14","author":"Nedic Erjavec","year":"2018","journal-title":"Redox Biol"},{"key":"B28","doi-asserted-by":"publisher","first-page":"e0207082","DOI":"10.1371\/journal.pone.0207082","article-title":"Development, characterization and comparisons of targeted and non-targeted metabolomics methods","volume":"13","author":"Ribbenstedt","year":"2018","journal-title":"PloS One"},{"key":"B29","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymgme.2023.108115","article-title":"An evaluation of untargeted metabolomics methods to characterize inborn errors of metabolism","volume":"141","author":"Wurth","year":"2024","journal-title":"Mol Genet Metab"},{"key":"B30","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1007\/978-1-4939-9236-2_3","article-title":"High-throughput metabolomics based on direct mass spectrometry analysis in biomedical research","volume":"1978","author":"Gonz\u00e1lez-Dom\u00ednguez","year":"2019","journal-title":"Methods Mol Biol"},{"key":"B31","doi-asserted-by":"publisher","first-page":"10918","DOI":"10.1038\/s41598-020-67939-x","article-title":"Inter-laboratory reproducibility of an untargeted metabolomics GC-MS assay for analysis of human plasma","volume":"10","author":"Lin","year":"2020","journal-title":"Sci Rep"},{"key":"B32","doi-asserted-by":"publisher","DOI":"10.1002\/1878-0261.13791","article-title":"Targeted metabolomics reveals novel diagnostic biomarkers for colorectal cancer","volume":"19","author":"Hu","year":"2025","journal-title":"Mol Oncol"},{"key":"B33","doi-asserted-by":"publisher","DOI":"10.1021\/acs.analchem.6b02930","article-title":"Interlaboratory reproducibility of a targeted metabolomics platform for analysis of human serum and plasma","volume":"89","author":"Siskos","year":"2017","journal-title":"Anal Chem"},{"key":"B34","doi-asserted-by":"publisher","first-page":"e2400007","DOI":"10.1002\/ansa.202400007","article-title":"Challenges and recent advances in quantitative mass spectrometry-based metabolomics","volume":"5","author":"Ghafari","year":"2024","journal-title":"Anal Sci Adv"},{"key":"B35","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-97-4402-2_18","article-title":"Precision medicine in depression: the role of proteomics and metabolomics in personalized treatment approaches","volume":"1456","author":"Jaber","year":"2024","journal-title":"Adv Exp Med Biol"},{"key":"B36","doi-asserted-by":"publisher","DOI":"10.3390\/cells13171436","article-title":"Gut-brain axis: role of microbiome, metabolomics, hormones, and stress in mental health disorders","volume":"13","author":"Verma","year":"2024","journal-title":"Cells"},{"key":"B37","doi-asserted-by":"publisher","DOI":"10.47626\/1516-4446-2022-2973","article-title":"The kynurenine pathway in major depressive disorder, bipolar disorder, and schizophrenia: a systematic review and meta-analysis of cerebrospinal fluid studies","volume":"45","author":"Inam","year":"2023","journal-title":"Braz J Psychiatry"},{"key":"B38","doi-asserted-by":"publisher","first-page":"e23009","DOI":"10.7759\/cureus.23009","article-title":"Metabolomics of major depressive disorder: A systematic review of clinical studies","volume":"14","author":"Guerreiro Costa","year":"2022","journal-title":"Cureus"},{"key":"B39","doi-asserted-by":"publisher","DOI":"10.1080\/15622975.2023.2271965","article-title":"The relationship between alterations in plasma metabolites and treatment responses in antipsychotic-na\u00efve female patients with schizophrenia","volume":"25","author":"Wang","year":"2024","journal-title":"World J Biol Psychiatry"},{"key":"B40","doi-asserted-by":"publisher","DOI":"10.1111\/pcn.13194","article-title":"Alteration of lipids and amino acids in plasma distinguish schizophrenia patients from controls: a targeted metabolomics study","volume":"75","author":"Liu","year":"2021","journal-title":"Psychiatry Clin Neurosci"},{"key":"B41","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2021.763547","article-title":"A metabolomics study of serum in hospitalized patients with chronic schizophrenia","volume":"12","author":"Okamoto","year":"2021","journal-title":"Front Psychiatry"},{"key":"B42","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jproteome.1c00504","article-title":"Salivary metabolomics reveals that metabolic alterations precede the onset of schizophrenia","volume":"20","author":"Cui","year":"2021","journal-title":"J Proteome Res"},{"key":"B43","doi-asserted-by":"publisher","first-page":"e379","DOI":"10.1038\/tp.2014.19","article-title":"A snapshot of plasma metabolites in first-episode schizophrenia: a capillary electrophoresis time-of-flight mass spectrometry study","volume":"4","author":"Koike","year":"2014","journal-title":"Transl Psychiatry"},{"key":"B44","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2025.1540260","article-title":"Discovery of biological markers for schizophrenia based on metabolomics: a systematic review","volume":"16","author":"Yao","year":"2025","journal-title":"Front Psychiatry"},{"key":"B45","doi-asserted-by":"publisher","DOI":"10.25011\/cim.v45i2.38096","article-title":"Metabolomics and cytokine analysis for identification of schizophrenia with auditory hallucination","volume":"45","author":"Li","year":"2022","journal-title":"Clin Invest Med"},{"key":"B46","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2022.1013698","article-title":"Association between lipid metabolism and cognitive function in patients with schizophrenia","volume":"13","author":"Liu","year":"2022","journal-title":"Front Psychiatry"},{"key":"B47","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2022.950602","article-title":"Plasma metabolomics of schizophrenia with cognitive impairment: a pilot study","volume":"13","author":"Jiang","year":"2022","journal-title":"Front Psychiatry"},{"key":"B48","doi-asserted-by":"publisher","DOI":"10.1021\/pr2006796","article-title":"Metabolomic profiling to identify potential serum biomarkers for schizophrenia and risperidone action","volume":"10","author":"Xuan","year":"2011","journal-title":"J Proteome Res"},{"key":"B49","doi-asserted-by":"publisher","DOI":"10.1016\/j.psychres.2023.115070","article-title":"Potential plasma biomarker panels identification for the diagnosis of first-episode schizophrenia and monitoring antipsychotic monotherapy with the use of metabolomics analyses","volume":"321","author":"Song","year":"2023","journal-title":"Psychiatry Res"},{"key":"B50","doi-asserted-by":"publisher","DOI":"10.1038\/srep05855","article-title":"Combined application of NMR- and GC-MS-based metabonomics yields a superior urinary biomarker panel for bipolar disorder","volume":"4","author":"Chen","year":"2014","journal-title":"Sci Rep"},{"key":"B51","doi-asserted-by":"publisher","first-page":"492","DOI":"10.1016\/j.jad.2024.01.033","article-title":"Biomarkers of bipolar disorder based on metabolomics: A systematic review","volume":"350","author":"Chen","year":"2024","journal-title":"J Affect Disord"},{"key":"B52","doi-asserted-by":"publisher","first-page":"e82","DOI":"10.1192\/j.eurpsy.2022.2340","article-title":"The association of kynurenine pathway metabolites with symptom severity and clinical features of bipolar disorder: An overview","volume":"65","author":"Bartoli","year":"2022","journal-title":"Eur Psychiatry"},{"key":"B53","doi-asserted-by":"publisher","DOI":"10.2147\/NDT.S508021","article-title":"Alterations of blood plasma metabolites, including kynurenine and tryptophan, in bipolar disorder","volume":"21","author":"Nakayama","year":"2025","journal-title":"Neuropsychiatr Dis Treat"},{"key":"B54","doi-asserted-by":"publisher","DOI":"10.1001\/jamapsychiatry.2023.4096","article-title":"Metabolomic biomarker signatures for bipolar and unipolar depression","volume":"81","author":"Tomasik","year":"2024","journal-title":"JAMA Psychiatry"},{"key":"B55","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1038\/s41398-025-03367-7","article-title":"Bioenergetic biomarkers as predictive indicators and their relationship with cognitive function in newly diagnosed, drug-na\u00efve patients with bipolar disorder","volume":"15","author":"Cao","year":"2025","journal-title":"Transl Psychiatry"},{"key":"B56","doi-asserted-by":"publisher","DOI":"10.1016\/j.nsa.2022.100108","article-title":"Metabolomics analysis of cerebrospinal fluid suggests citric acid cycle aberrations in bipolar disorder","volume":"1","author":"Smedler","year":"2022","journal-title":"Neurosci Appl"},{"key":"B57","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2023.1319870","article-title":"Comparing the metabolic pathways of different clinical phases of bipolar disorder through metabolomics studies","volume":"14","author":"Guo","year":"2024","journal-title":"Front Psychiatry"},{"key":"B58","doi-asserted-by":"publisher","DOI":"10.1111\/cts.12324","article-title":"An untargeted metabolomics analysis of antipsychotic use in bipolar disorder","volume":"8","author":"Burghardt","year":"2015","journal-title":"Clin Transl Sci"},{"key":"B59","doi-asserted-by":"publisher","DOI":"10.1016\/j.jad.2024.01.053","article-title":"Metabolomics on depression: A comparison of clinical and animal research","volume":"349","author":"Wang","year":"2024","journal-title":"J Affect Disord"},{"key":"B60","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2024.1391535","article-title":"Assessing the associations of 1,400 blood metabolites with major depressive disorder: A Mendelian randomization study","volume":"15","author":"Dong","year":"2024","journal-title":"Front Psychiatry"},{"key":"B61","doi-asserted-by":"publisher","first-page":"15608","DOI":"10.1038\/s41598-021-95221-1","article-title":"Metabolomics-based discrimination of patients with remitted depression from healthy controls using 1H-NMR spectroscopy","volume":"11","author":"Hung","year":"2021","journal-title":"Sci Rep"},{"key":"B62","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1007\/s00429-008-0189-x","article-title":"Brain structural and functional abnormalities in mood disorders: implications for neurocircuitry models of depression","volume":"213","author":"Drevets","year":"2008","journal-title":"Brain Struct Funct"},{"key":"B63","doi-asserted-by":"publisher","DOI":"10.3390\/molecules28217430","article-title":"Recent progress in mass spectrometry-based metabolomics in major depressive disorder research","volume":"28","author":"Liu","year":"2023","journal-title":"Molecules"},{"key":"B64","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyt.2021.810302","article-title":"Non-targeted metabolomics profiling of plasma samples from patients with major depressive disorder","volume":"12","author":"Wu","year":"2022","journal-title":"Front Psychiatry"},{"key":"B65","doi-asserted-by":"publisher","DOI":"10.1176\/appi.ajp.2014.14010067","article-title":"Glutamate metabolism in major depressive disorder","volume":"171","author":"Abdallah","year":"2014","journal-title":"Am J Psychiatry"},{"key":"B66","doi-asserted-by":"publisher","DOI":"10.1016\/j.schres.2021.04.008","article-title":"The kynurenine pathway in schizophrenia and other mental disorders: Insight from meta-analyses on the peripheral blood levels of tryptophan and related metabolites","volume":"232","author":"Bartoli","year":"2021","journal-title":"Schizophr Res"},{"key":"B67","doi-asserted-by":"publisher","first-page":"e70197","DOI":"10.1002\/bmc.70197","article-title":"Biomarker for diagnosis and monitoring of treatment response in major depressive disorder: changes in serum L-glutamine levels","volume":"39","author":"Lee","year":"2025","journal-title":"BioMed Chromatogr"},{"key":"B68","doi-asserted-by":"publisher","first-page":"107086","DOI":"10.1016\/j.psyneuen.2024","article-title":"Metabolic features of adolescent major depressive disorder: A comparative study between treatment-resistant depression and first-episode drug-na\u00efve depression","volume":"167","author":"Gan","year":"2024","journal-title":"Psychoneuroendocrinology"},{"key":"B69","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1038\/s41398-023-02696-9","article-title":"Metabolic features of treatment-refractory major depressive disorder with suicidal ideation","volume":"13","author":"Pan","year":"2023","journal-title":"Transl Psychiatry"},{"key":"B70","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1038\/s41398-022-01947-5","article-title":"Effects of pharmacological treatment on metabolomic alterations in animal models of depression","volume":"12","author":"Pu","year":"2022","journal-title":"Transl Psychiatry"},{"key":"B71","doi-asserted-by":"publisher","first-page":"397","DOI":"10.1016\/j.jad.2025.01.064","article-title":"Metabolomics signatures of serotonin reuptake inhibitor (escitalopram), serotonin norepinephrine reuptake inhibitor (duloxetine) and cognitive-behavioral therapy on key neurotransmitter pathways in major depressive disorder","volume":"375","author":"Bhattacharyya","year":"2025","journal-title":"J Affect Disord"},{"key":"B72","doi-asserted-by":"publisher","DOI":"10.1016\/j.neulet.2024.137791","article-title":"Evidence from preclinical and clinical metabolomics studies on the antidepressant effects of ketamine and esketamine","volume":"831","author":"Cavaleri","year":"2024","journal-title":"Neurosci Lett"},{"key":"B73","doi-asserted-by":"publisher","DOI":"10.3390\/ijms21134784","article-title":"Metabolomic biomarkers in anxiety disorders","volume":"21","author":"Humer","year":"2020","journal-title":"Int J Mol Sci"},{"key":"B74","doi-asserted-by":"publisher","DOI":"10.1016\/j.cca.2022.06.022","article-title":"Serum metabolomics study of anxiety disorder patients based on LC-MS","volume":"533","author":"Kui","year":"2022","journal-title":"Clin Chim Acta"},{"key":"B75","doi-asserted-by":"publisher","DOI":"10.1111\/acps.13310","article-title":"Metabolomic profiles discriminating anxiety from depression","volume":"144","author":"de Kluiver","year":"2021","journal-title":"Acta Psychiatr Scand"},{"key":"B76","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1038\/s41398-022-01940-y","article-title":"Metabolomics analysis of post-traumatic stress disorder symptoms in World Trade Center responders","volume":"12","author":"Kuan","year":"2022","journal-title":"Transl Psychiatry"},{"key":"B77","doi-asserted-by":"publisher","first-page":"e0213839","DOI":"10.1371\/journal.pone.0213839","article-title":"Metabolomic analysis of male combat veterans with post traumatic stress disorder","volume":"14","author":"Mellon","year":"2019","journal-title":"PloS One"},{"key":"B78","doi-asserted-by":"publisher","DOI":"10.1016\/j.bbi.2023.07.015","article-title":"Integrated analysis of proteomics, epigenomics and metabolomics data revealed divergent pathway activation patterns in the recent versus chronic post-traumatic stress disorder","volume":"113","author":"Muhie","year":"2023","journal-title":"Brain Behav Immun"},{"key":"B79","doi-asserted-by":"publisher","DOI":"10.1016\/j.jad.2024.12.029","article-title":"Human blood metabolites and risk of post-traumatic stress disorder: A Mendelian randomization study","volume":"372","author":"Wei","year":"2025","journal-title":"J Affect Disord"},{"key":"B80","doi-asserted-by":"publisher","DOI":"10.1016\/j.bbi.2025.01.013","article-title":"Serum metabolites and inflammation predict brain functional connectivity changes in Obsessive-Compulsive disorder","volume":"126","author":"Chen","year":"2025","journal-title":"Brain Behav Immun"},{"key":"B81","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2023.1148971","article-title":"Untargeted metabolomics analysis in drug-na\u00efve patients with severe obsessive-compulsive disorder","volume":"17","author":"Li","year":"2023","journal-title":"Front Neurosci"},{"key":"B82","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jproteome.1c00857","article-title":"NMR-based metabolomics and fatty acid profiles to unravel biomarkers in preclinical animal models of compulsive behavior","volume":"21","author":"Abreu","year":"2022","journal-title":"J Proteome Res"},{"key":"B83","doi-asserted-by":"publisher","first-page":"3284","DOI":"10.1038\/s41467-023-39030-2","article-title":"The monoaminergic system is a bilaterian innovation","volume":"14","author":"Goulty","year":"2023","journal-title":"Nat Commun"},{"key":"B84","doi-asserted-by":"publisher","DOI":"10.1007\/s11064-016-2057-z","article-title":"Interactions in the metabolism of glutamate and the branched-chain amino acids and ketoacids in the CNS","volume":"42","author":"Yudkoff","year":"2017","journal-title":"Neurochem Res"},{"key":"B85","doi-asserted-by":"publisher","DOI":"10.1016\/j.tics.2017.06.006","article-title":"Mapping the consequences of impaired synaptic plasticity in schizophrenia through development: an integrative model for diverse clinical features","volume":"21","author":"Forsyth","year":"2017","journal-title":"Trends Cognit Sci"},{"key":"B86","doi-asserted-by":"publisher","DOI":"10.1038\/nm.4050","article-title":"Synaptic plasticity and depression: new insights from stress and rapid-acting antidepressants","volume":"22","author":"Duman","year":"2016","journal-title":"Nat Med"},{"key":"B87","doi-asserted-by":"publisher","DOI":"10.3389\/fnagi.2023.1322419","article-title":"Exploring the complexities of 1C metabolism: implications in aging and neurodegenerative diseases","volume":"15","author":"Bou Ghanem","year":"2024","journal-title":"Front Aging Neurosci"},{"key":"B88","doi-asserted-by":"publisher","DOI":"10.1007\/s00726-013-1493-1","article-title":"Glycine metabolism in animals and humans: implications for nutrition and health","volume":"45","author":"Wang","year":"2013","journal-title":"Amino Acids"},{"key":"B89","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuron.2012.08.019","article-title":"Synaptic energy use and supply","volume":"75","author":"Harris","year":"2012","journal-title":"Neuron"},{"key":"B90","doi-asserted-by":"publisher","DOI":"10.1152\/ajpcell.00222.2006","article-title":"Mitochondria and neuronal activity","volume":"292","author":"Kann","year":"2007","journal-title":"Am J Physiol Cell Physiol"},{"key":"B91","doi-asserted-by":"publisher","DOI":"10.1124\/pharmrev.121.000408","article-title":"Acylcarnitines: nomenclature, biomarkers, therapeutic potential, drug targets, and clinical trials","volume":"74","author":"Dambrova","year":"2022","journal-title":"Pharmacol Rev"},{"key":"B92","doi-asserted-by":"publisher","DOI":"10.1021\/cr2002917","article-title":"Sphingolipid and glycosphingolipid metabolic pathways in the era of sphingolipidomics","volume":"111","author":"Merrill","year":"2011","journal-title":"Chem Rev"},{"key":"B93","doi-asserted-by":"publisher","DOI":"10.1038\/s41380-019-0414-4","article-title":"The kynurenine pathway: a finger in every pie","volume":"25","author":"Savitz","year":"2020","journal-title":"Mol Psychiatry"},{"key":"B94","doi-asserted-by":"publisher","DOI":"10.3390\/metabo10060224","article-title":"Current status of metabolomic biomarker discovery: impact of study design and demographic characteristics","volume":"10","author":"Tolstikov","year":"2020","journal-title":"Metabolites"},{"key":"B95","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1007\/s11306-014-0707-1","article-title":"Molecular phenotyping of a UK population: defining the human serum metabolome","volume":"11","author":"Dunn","year":"2015","journal-title":"Metabolomics"},{"key":"B96","doi-asserted-by":"publisher","first-page":"903","DOI":"10.1038\/s42003-021-02421-6","article-title":"Metabolomic signatures associated with depression and predictors of antidepressant response in humans: A CAN-BIND-1 report","volume":"4","author":"Caspani","year":"2021","journal-title":"Commun Biol"},{"key":"B97","doi-asserted-by":"publisher","DOI":"10.3390\/metabo14090474","article-title":"An overview of pre-analytical factors impacting metabolomics analyses of blood samples","volume":"14","author":"Thachil","year":"2024","journal-title":"Metabolites"},{"key":"B98","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2022.104082","article-title":"Topological data analysis in biomedicine: A review","volume":"130","author":"Skaf","year":"2022","journal-title":"J BioMed Inform"},{"key":"B99","doi-asserted-by":"publisher","DOI":"10.1038\/s41587-021-00895-7","article-title":"Computational principles and challenges in single-cell data integration","volume":"39","author":"Argelaguet","year":"2021","journal-title":"Nat Biotechnol"},{"key":"B100","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1038\/s41398-021-01632-z","article-title":"Multi-omics driven predictions of response to acute phase combination antidepressant therapy: a machine learning approach with cross-trial replication","volume":"11","author":"Joyce","year":"2021","journal-title":"Transl Psychiatry"},{"key":"B101","doi-asserted-by":"publisher","DOI":"10.3389\/fmolb.2022.967205","article-title":"Computational approaches for network-based integrative multi-omics analysis","volume":"9","author":"Agamah","year":"2022","journal-title":"Front Mol Biosci"},{"key":"B102","doi-asserted-by":"publisher","DOI":"10.3389\/fgene.2022.1017340","article-title":"Applications of machine learning in metabolomics: Disease modeling and classification","volume":"13","author":"Galal","year":"2022","journal-title":"Front Genet"},{"key":"B103","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkad1045","article-title":"MetaboLights: open data repository for metabolomics","volume":"52","author":"Yurekten","year":"2024","journal-title":"Nucleic Acids Res"},{"key":"B104","doi-asserted-by":"publisher","DOI":"10.14348\/molcells.2021.0042","article-title":"Integrative multi-omics approaches in cancer research: from biological networks to clinical subtypes","volume":"44","author":"Heo","year":"2021","journal-title":"Mol Cells"},{"key":"B105","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1038\/s41746-024-01236-z","article-title":"Integrating digital gait data with metabolomics and clinical data to predict outcomes in Parkinson\u2019s disease","volume":"7","author":"Brzenczek","year":"2024","journal-title":"NPJ Digit Med"},{"key":"B106","doi-asserted-by":"publisher","first-page":"e44502","DOI":"10.2196\/44502","article-title":"Digital phenotyping: data-driven psychiatry to redefine mental health","volume":"25","author":"Oudin","year":"2023","journal-title":"J Med Internet Res"},{"key":"B107","doi-asserted-by":"publisher","DOI":"10.5152\/alphapsychiatry.2024.241549","article-title":"The resistant depression response to esketamine assessing metabolomics (ReDREAM) project\u2013untargeted metabolomics to identify biomarkers of treatment response to intranasal esketamine in individuals with treatment-resistant depression: A study protocol","volume":"25","author":"Bartoli","year":"2024","journal-title":"Alpha Psychiatry"}],"container-title":["Frontiers in Psychiatry"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fpsyt.2026.1736206\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T06:38:34Z","timestamp":1770964714000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fpsyt.2026.1736206\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,13]]},"references-count":107,"alternative-id":["10.3389\/fpsyt.2026.1736206"],"URL":"https:\/\/doi.org\/10.3389\/fpsyt.2026.1736206","relation":{},"ISSN":["1664-0640"],"issn-type":[{"value":"1664-0640","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,13]]},"article-number":"1736206"}}