Maes MH, Stoyanov D. False dogmas in mood disorders research: Towards a nomothetic network approach. World J Psychiatry 2022; 12(5): 651-667 [PMID: 35663296 DOI: 10.5498/wjp.v12.i5.651]
Corresponding Author of This Article
Michael HJ Maes, PhD, Professor, Department of Psychiatry, Chulalongkorn University, Rama IV, Bangkok 10330, Thailand. dr.michaelmaes@hotmail.com
Research Domain of This Article
Neurosciences
Article-Type of This Article
Opinion Review
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Psychiatry. May 19, 2022; 12(5): 651-667 Published online May 19, 2022. doi: 10.5498/wjp.v12.i5.651
False dogmas in mood disorders research: Towards a nomothetic network approach
Michael HJ Maes, Drozdstoy Stoyanov
Michael HJ Maes, Department of Psychiatry, Chulalongkorn University, Bangkok 10330, Thailand
Drozdstoy Stoyanov, Department of Psychiatry, Medical University Plovdiv, Plovdiv 4000, Bulgaria
Author contributions: All the contributing authors have participated in the manuscript’s conception, design and preparation, and approved the final version submitted for publication.
Supported bythe Ratchadapiseksompotch Funds, Faculty of Medicine, Chulalongkorn University, RA61/050.
Conflict-of-interest statement: The authors have no conflict of interest with any commercial or other association in connection with the submitted article.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Michael HJ Maes, PhD, Professor, Department of Psychiatry, Chulalongkorn University, Rama IV, Bangkok 10330, Thailand. dr.michaelmaes@hotmail.com
Received: July 11, 2021 Peer-review started: July 11, 2021 First decision: October 4, 2021 Revised: October 7, 2021 Accepted: April 25, 2022 Article in press: April 25, 2022 Published online: May 19, 2022 Processing time: 310 Days and 23.5 Hours
Core Tip
Core Tip: We review the merits of machine learning-derived nomothetic network psychiatry (NNP) models of mood disorders. The NNP models of mood disorders show that major depressive disorder/bipolar disorder are not mind-brain or psycho-social but systemic medical disorders. The DSM/ICD taxonomies are counterproductive. A shared core, namely the reoccurrence of illness (ROI), underpins the intertwined recurrence of depressive and manic episodes and suicidal behaviors. Mood disorders should be ROI-defined. ROI mediates the effects of nitro-oxidative stress pathways and early lifetime trauma on the phenome of mood disorders. Severity of illness and treatment response should be delineated using NNP-derived causome, adverse outcome pathways, ROI and phenome scores.
