{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T20:52:39Z","timestamp":1775595159356,"version":"3.50.1"},"reference-count":52,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T00:00:00Z","timestamp":1732665600000},"content-version":"vor","delay-in-days":5,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"Dalian Institute of Chemical Physics Innovation Project","award":["202207I"],"award-info":[{"award-number":["202207I"]}]},{"name":"Project from Liaoning Provincial Department of Science and Technology","award":["2021 JH2\/10200004"],"award-info":[{"award-number":["2021 JH2\/10200004"]}]},{"name":"Natural Science Foundation of Liaoning Province, China","award":["2024-MS-175"],"award-info":[{"award-number":["2024-MS-175"]}]},{"name":"Dalian Scientific and Technological Talents Innovation Support Plan","award":["2022RG17"],"award-info":[{"award-number":["2022RG17"]}]},{"name":"2023 Basic Scientific Research Project of Liaoning Provincial Department of Education","award":["JYTZD2023050"],"award-info":[{"award-number":["JYTZD2023050"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,11,22]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Major depressive disorder (MDD) is a severe psychiatric disorder that currently lacks any objective diagnostic markers. Here, we develop a deep learning approach to discover the mass spectrometric features that can discriminate MDD patients from health controls. Using plasma peptides, the neural network, termed as CMS-Net, can perform diagnosis and prediction with an accuracy of 0.9441. The sensitivity and specificity reached 0.9352 and 0.9517 respectively, and the area under the curve was enhanced to 0.9634. Using the gradient-based feature importance method to interpret crucial features, we identify 28 differential peptide sequences from 14 precursor proteins (e.g. hemoglobin, immunoglobulin, albumin, etc.). This work highlights the possibility of molecular diagnosis of MDD with the aid of chemical and computer science.<\/jats:p>","DOI":"10.1093\/bib\/bbae554","type":"journal-article","created":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T01:16:16Z","timestamp":1732670176000},"source":"Crossref","is-referenced-by-count":3,"title":["Toward molecular diagnosis of major depressive disorder by plasma peptides using a deep learning approach"],"prefix":"10.1093","volume":"26","author":[{"given":"Jiaqi","family":"Wang","sequence":"first","affiliation":[{"name":"School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University , 103 Wenhua Road, Shenhe District, Shenyang 110016,","place":["China"]},{"name":"CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences , 457 Zhongshan Road, Dalian 116023, Liaoning,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ronggang","family":"Xi","sequence":"additional","affiliation":[{"name":"The 967th Hospital of the Joint Logistics Support Force of PLA , 80 Shengli Road, Xigang District, Dalian 116021, Liaoning,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Wang","sequence":"additional","affiliation":[{"name":"Dalian Institute of Chemical Physics, Chinese Academy of Sciences CAS Key Laboratory of Separation Science for Analytical Chemistry, , 457 Zhongshan Road, Dalian 116023,","place":["Liaoning, China"]},{"name":"University of Chinese Academy of Sciences , Beijing,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huiyuan","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University , 103 Wenhua Road, Shenhe District, Shenyang 110016,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ming","family":"Gao","sequence":"additional","affiliation":[{"name":"Dongbei University of Finance and Economics School of Management Science and Engineering, Key Laboratory of Big Data Management Optimization and Decision of Liaoning Province, , No. 217 Jianshan Street, Shahekou District, Dalian 116025, Liaoning,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1494-278X","authenticated-orcid":false,"given":"Xiaozhe","family":"Zhang","sequence":"additional","affiliation":[{"name":"CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences , 457 Zhongshan Road, Dalian 116023, Liaoning,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2543-1547","authenticated-orcid":false,"given":"Lihua","family":"Zhang","sequence":"additional","affiliation":[{"name":"CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences , 457 Zhongshan Road, Dalian 116023, Liaoning,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yukui","family":"Zhang","sequence":"additional","affiliation":[{"name":"CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences , 457 Zhongshan Road, Dalian 116023, Liaoning,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2024,11,25]]},"reference":[{"key":"2024122001564462400_ref1","doi-asserted-by":"publisher","DOI":"10.3390\/ijms24010578","article-title":"Selected biomarkers of depression: what are the effects of cytokines and inflammation?","volume":"24","author":"Harsanyi","year":"2022","journal-title":"Int J Mol Sci"},{"key":"2024122001564462400_ref2","doi-asserted-by":"publisher","DOI":"10.3390\/diagnostics13010002","article-title":"Challenges for artificial intelligence in recognizing mental disorders","volume":"13","author":"Yan","year":"2022","journal-title":"Diagnostics (Basel)"},{"key":"2024122001564462400_ref3","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1007\/978-1-4939-2377-9_13","article-title":"The strengths and weaknesses of NMR spectroscopy and mass spectrometry with particular focus on metabolomics research","volume":"1277","author":"Emwas","year":"2015","journal-title":"Methods Mol Biol"},{"key":"2024122001564462400_ref4","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1016\/j.jmsacl.2023.02.003","article-title":"Small molecule biomarker discovery: proposed workflow for LC-MS-based clinical research projects","volume":"28","author":"Rischke","year":"2023","journal-title":"J Mass Spectrom Adv Clin Lab"},{"key":"2024122001564462400_ref5","doi-asserted-by":"publisher","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":"2024122001564462400_ref6","doi-asserted-by":"publisher","first-page":"e18909","DOI":"10.1016\/j.heliyon.2023.e18909","article-title":"A review of new insights into existing major depressive disorder biomarkers","volume":"9","author":"Rimti","year":"2023","journal-title":"Heliyon"},{"key":"2024122001564462400_ref7","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1038\/s41398-017-0056-8","article-title":"Beta-defensin 1, aryl hydrocarbon receptor and plasma kynurenine in major depressive disorder: metabolomics-informed genomics","volume":"8","author":"Liu","year":"2018","journal-title":"Transl Psychiatry"},{"key":"2024122001564462400_ref8","doi-asserted-by":"publisher","first-page":"179","DOI":"10.1038\/s41598-017-17500-0","article-title":"Blood plasma\/IgG N-glycome biosignatures associated with major depressive disorder symptom severity and the antidepressant response","volume":"8","author":"Park","year":"2018","journal-title":"Sci Rep"},{"key":"2024122001564462400_ref9","doi-asserted-by":"publisher","first-page":"1406","DOI":"10.1038\/s41598-020-80873-2","article-title":"Vasoactive intestinal polypeptide plasma levels associated with affective symptoms and brain structure and function in healthy females","volume":"11","author":"Simon","year":"2021","journal-title":"Sci Rep"},{"key":"2024122001564462400_ref10","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1016\/j.bbi.2023.08.025","article-title":"Associations of potential plasma biomarkers with suicide attempt history, current suicidal ideation and subsequent suicidal events in patients with depression: a discovery study","volume":"114","author":"Aiste","year":"2023","journal-title":"Brain Behav Immun"},{"key":"2024122001564462400_ref11","doi-asserted-by":"publisher","first-page":"28877","DOI":"10.1021\/acsomega.0c04568","article-title":"Comprehensive analysis of low molecular weight serum proteome enrichment for mass spectrometric studies","volume":"5","author":"Das","year":"2020","journal-title":"ACS Omega"},{"key":"2024122001564462400_ref12","doi-asserted-by":"publisher","first-page":"e2000058","DOI":"10.1002\/prca.202000058","article-title":"Plasma nontargeted peptidomics discovers potential biomarkers for major depressive disorder","volume":"15","author":"Wang","year":"2021","journal-title":"Proteomics Clin Appl"},{"key":"2024122001564462400_ref13","doi-asserted-by":"publisher","first-page":"6332","DOI":"10.1038\/s41598-023-33359-w","article-title":"Predictive biosignature of major depressive disorder derived from physiological measurements of outpatients using machine learning","volume":"13","author":"Ricka","year":"2023","journal-title":"Sci Rep"},{"key":"2024122001564462400_ref14","doi-asserted-by":"publisher","first-page":"i245","DOI":"10.1093\/bioinformatics\/btab311","article-title":"On the feasibility of deep learning applications using raw mass spectrometry data","volume":"37","author":"Cadow","year":"2021","journal-title":"Bioinformatics"},{"key":"2024122001564462400_ref15","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":"2024122001564462400_ref16","doi-asserted-by":"publisher","first-page":"759","DOI":"10.1016\/j.cels.2021.06.006","article-title":"Artificial intelligence for proteomics and biomarker discovery","volume":"12","author":"Mann","year":"2021","journal-title":"Cell Syst"},{"key":"2024122001564462400_ref17","doi-asserted-by":"publisher","first-page":"457","DOI":"10.1109\/JBHI.2022.3217015","article-title":"Aligning small datasets using domain adversarial learning: applications in automated in vivo oral cancer diagnosis","volume":"27","author":"Caughlin","year":"2023","journal-title":"IEEE J Biomed Health Inform"},{"key":"2024122001564462400_ref18","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1038\/s41386-020-0767-z","article-title":"Deep learning for small and big data in psychiatry","volume":"46","author":"Koppe","year":"2021","journal-title":"Neuropsychopharmacology"},{"key":"2024122001564462400_ref19","doi-asserted-by":"publisher","first-page":"e1900344","DOI":"10.1002\/pmic.201900344","article-title":"A deep learning-based tumor classifier directly using MS raw data","volume":"20","author":"Dong","year":"2020","journal-title":"Proteomics"},{"key":"2024122001564462400_ref20","doi-asserted-by":"publisher","DOI":"10.1038\/s41421-022-00442-x","article-title":"Artificial intelligence defines protein-based classification of thyroid nodules","volume":"8","year":"2022","journal-title":"Cell Discov"},{"key":"2024122001564462400_ref21","doi-asserted-by":"publisher","first-page":"2002021","DOI":"10.1002\/advs.202002021","article-title":"Rapid computer-aided diagnosis of stroke by serum metabolic fingerprint based multi-modal recognition","volume":"7","author":"Xu","year":"2020","journal-title":"Adv Sci (Weinh)"},{"key":"2024122001564462400_ref22","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1093\/bioinformatics\/btad422","article-title":"Chromothripsis detection with multiple myeloma patients based on deep graph learning","volume":"39","author":"Yu","year":"2023","journal-title":"Bioinformatics"},{"key":"2024122001564462400_ref23","doi-asserted-by":"publisher","first-page":"e10240","DOI":"10.15252\/msb.202110240","article-title":"Diagnostics and correction of batch effects in large-scale proteomic studies: a tutorial","volume":"17","author":"Cuklina","year":"2021","journal-title":"Mol Syst Biol"},{"key":"2024122001564462400_ref24","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1038\/s41398-023-02321-9","article-title":"Latent class analysis of psychotic-affective disorders with data-driven plasma proteomics","volume":"13","author":"Rhee","year":"2023","journal-title":"Transl Psychiatry"},{"key":"2024122001564462400_ref25","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1186\/s12911-019-1004-8","article-title":"Comparing different supervised machine learning algorithms for disease prediction","volume":"19","author":"Uddin","year":"2019","journal-title":"BMC Med Inform Decis Mak"},{"key":"2024122001564462400_ref26","doi-asserted-by":"publisher","first-page":"106864","DOI":"10.1016\/j.compbiomed.2023.106864","article-title":"A web server for predicting and scanning of IL-5 inducing peptides using alignment-free and alignment-based method","volume":"158","author":"Naorem","year":"2023","journal-title":"Comput Biol Med"},{"key":"2024122001564462400_ref27","doi-asserted-by":"publisher","first-page":"675","DOI":"10.1016\/j.beth.2020.05.002","article-title":"Supervised machine learning: a brief primer","volume":"51","author":"Jiang","year":"2020","journal-title":"Behav Ther"},{"key":"2024122001564462400_ref28","doi-asserted-by":"publisher","first-page":"603","DOI":"10.1111\/joim.12822","article-title":"eDoctor: machine learning and the future of medicine","volume":"284","author":"Handelman","year":"2018","journal-title":"J Intern Med"},{"key":"2024122001564462400_ref29","doi-asserted-by":"publisher","first-page":"407","DOI":"10.4103\/aca.ACA_94_19","article-title":"Application of student\u2019s t-test, analysis of variance, and covariance","volume":"22","author":"Mishra","year":"2019","journal-title":"Ann Card Anaesth"},{"key":"2024122001564462400_ref30","doi-asserted-by":"publisher","first-page":"102009","DOI":"10.1016\/j.mex.2023.102009","article-title":"Generating post-hoc explanation from deep neural networks for multi-modal medical image analysis tasks","volume":"10","author":"Jin","year":"2023","journal-title":"MethodsX"},{"key":"2024122001564462400_ref31","doi-asserted-by":"publisher","first-page":"ooad086","DOI":"10.1093\/jamiaopen\/ooad086","article-title":"Sequential autoencoders for feature engineering and pretraining in major depressive disorder risk prediction","volume":"6","author":"Jones","year":"2023","journal-title":"JAMIA Open"},{"key":"2024122001564462400_ref32","doi-asserted-by":"publisher","first-page":"816","DOI":"10.1186\/s12888-022-04439-4","article-title":"A hybrid machine learning model of depression estimation in home-based older adults: a 7-year follow-up study","volume":"22","author":"Lin","year":"2022","journal-title":"BMC Psychiatry"},{"key":"2024122001564462400_ref33","doi-asserted-by":"publisher","first-page":"524","DOI":"10.1038\/s41467-023-43095-4","article-title":"Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma","volume":"15","author":"Chanda","year":"2024","journal-title":"Nat Commun"},{"key":"2024122001564462400_ref34","doi-asserted-by":"publisher","first-page":"e41205","DOI":"10.2196\/41205","article-title":"Enabling early health care intervention by detecting depression in users of web-based forums using language models: longitudinal analysis and evaluation","volume":"2","author":"Owen","year":"2023","journal-title":"JMIR AI"},{"key":"2024122001564462400_ref35","doi-asserted-by":"publisher","first-page":"6263","DOI":"10.1038\/s41598-023-33525-0","article-title":"Detection of the chronic kidney disease using XGBoost classifier and explaining the influence of the attributes on the model using SHAP","volume":"13","author":"Raihan","year":"2023","journal-title":"Sci Rep"},{"key":"2024122001564462400_ref36","doi-asserted-by":"publisher","first-page":"e1009736","DOI":"10.1371\/journal.pcbi.1009736","article-title":"Positional SHAP (PoSHAP) for interpretation of machine learning models trained from biological sequences","volume":"18","author":"Dickinson","year":"2022","journal-title":"PLoS Comput Biol"},{"key":"2024122001564462400_ref37","doi-asserted-by":"publisher","first-page":"478","DOI":"10.1186\/s13054-020-03179-9","article-title":"Prediction of the development of acute kidney injury following cardiac surgery by machine learning","volume":"24","author":"Tseng","year":"2020","journal-title":"Crit Care"},{"key":"2024122001564462400_ref38","doi-asserted-by":"publisher","first-page":"3008","DOI":"10.1038\/s41467-021-22756-2","article-title":"Permutation-based identification of important biomarkers for complex diseases via machine learning models","volume":"12","author":"Mi","year":"2021","journal-title":"Nat Commun"},{"key":"2024122001564462400_ref39","doi-asserted-by":"publisher","first-page":"1340","DOI":"10.1093\/bioinformatics\/btq134","article-title":"Permutation importance: a corrected feature importance measure","volume":"26","author":"Altmann","year":"2010","journal-title":"Bioinformatics"},{"key":"2024122001564462400_ref40","doi-asserted-by":"publisher","first-page":"22132","DOI":"10.3390\/ijms141122132","article-title":"AlPOs synthetic factor analysis based on maximum weight and minimum redundancy feature selection","volume":"14","author":"Guo","year":"2013","journal-title":"Int J Mol Sci"},{"key":"2024122001564462400_ref41","doi-asserted-by":"publisher","DOI":"10.3390\/e25020325","article-title":"Kernel partial least squares feature selection based on maximum weight minimum redundancy","volume":"25","author":"Liu","year":"2023","journal-title":"Entropy (Basel)"},{"key":"2024122001564462400_ref42","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1016\/j.jpsychires.2012.09.017","article-title":"Diagnostic accuracy of serum brain derived neurotrophic factor concentration in antidepressant naive patients with first major depression episode","volume":"47","author":"Karlovic","year":"2013","journal-title":"J Psychiatr Res"},{"key":"2024122001564462400_ref43","doi-asserted-by":"publisher","first-page":"152363","DOI":"10.1016\/j.comppsych.2022.152363","article-title":"The diagnostic utility of miRNA and elucidation of pathological mechanisms in major depressive disorder","volume":"121","author":"Ho","year":"2023","journal-title":"Compr Psychiatry"},{"key":"2024122001564462400_ref44","doi-asserted-by":"publisher","first-page":"110151","DOI":"10.1016\/j.pnpbp.2020.110151","article-title":"Brain-derived neurotrophic factor (BDNF) and inflammatory markers: perspectives for the management of depression","volume":"108","author":"Carniel","year":"2021","journal-title":"Prog Neuropsychopharmacol Biol Psychiatry"},{"key":"2024122001564462400_ref45","first-page":"18","article-title":"A review on deep learning interpretability in medical image processing","volume":"48","author":"Zb","year":"2021","journal-title":"J ZheJiang Univ Sci"},{"key":"2024122001564462400_ref46","doi-asserted-by":"publisher","first-page":"2596","DOI":"10.1007\/s10618-023-00924-w","article-title":"The grammar of interactive explanatory model analysis","volume":"38","author":"Baniecki","year":"2023","journal-title":"Data Min Knowl Discov"},{"key":"2024122001564462400_ref47","doi-asserted-by":"publisher","first-page":"490","DOI":"10.1002\/da.22881","article-title":"Differentiating PTSD from anxiety and depression: lessons from the ICD-11 PTSD diagnostic criteria","volume":"36","author":"Barbano","year":"2019","journal-title":"Depress Anxiety"},{"key":"2024122001564462400_ref48","doi-asserted-by":"publisher","first-page":"7467","DOI":"10.1038\/s41598-023-34298-2","article-title":"Comparing resting state and task-based EEG using machine learning to predict vulnerability to depression in a non-clinical population","volume":"13","author":"Kaushik","year":"2023","journal-title":"Sci Rep"},{"key":"2024122001564462400_ref49","doi-asserted-by":"publisher","first-page":"1224","DOI":"10.1038\/s41386-019-0369-9","article-title":"Superolateral medial forebrain bundle deep brain stimulation in major depression: a gateway trial","volume":"44","author":"Coenen","year":"2019","journal-title":"Neuropsychopharmacology"},{"key":"2024122001564462400_ref50","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1016\/j.jad.2022.08.123","article-title":"Comparison of three machine learning models to predict suicidal ideation and depression among Chinese adolescents: a cross-sectional study","volume":"319","author":"Huang","year":"2022","journal-title":"J Affect Disord"},{"key":"2024122001564462400_ref51","article-title":"Individualized depression nursing strategy based on deep learning emotion classification models","volume":"35","year":"2020","journal-title":"J Nurs Sci"},{"key":"2024122001564462400_ref52","first-page":"5\u201310","article-title":"An auxiliary diagnosis method for major depression disorder based on convolutional neural network","volume":"48","author":"Yin","year":"2022","journal-title":"J Lanzhou Univ Med Sci"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/26\/1\/bbae554\/60811437\/bbae554.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/26\/1\/bbae554\/60811437\/bbae554.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,20]],"date-time":"2024-12-20T01:57:15Z","timestamp":1734659835000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbae554\/7908432"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,22]]},"references-count":52,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2024,11,22]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbae554","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2025,1]]},"published":{"date-parts":[[2024,11,22]]},"article-number":"bbae554"}}