Transition From Depression to Mental Health: Toward an Operationalization of Plasticity | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Transition From Depression to Mental Health: Toward an Operationalization of Plasticity Igor Branchi, Claudia Delli Colli, Flavia Chiarotti, Patrizia Campolongo, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2741248/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Jan, 2024 Read the published version in Nature Mental Health → Version 1 posted You are reading this latest preprint version Abstract Plasticity is the ability to modify brain and behavior and allows the transition from psychopathology to mental wellbeing. High plasticity has been associated to high susceptibility to contextual factors, e.g., living conditions, which ultimately drive plasticity outcome. Here, we exploited network analysis to show that plasticity – i.e., the susceptibility to modify depression score – can be assessed by measuring the symptom network connectivity: the weaker the connectivity, the higher the plasticity, resulting in a greater modification in mood symptoms. We analyzed the STAR*D dataset and proved that connectivity strength at baseline is weaker in responder compared to non-responder patients. Moreover, connectivity strength at baseline was inversely correlated with improvement in depression score (Pearson's r=-0.87) and susceptibility to change mood according to context (Pearson's r=-0.77). This operationalization of plasticity provides a mathematical tool to investigate and predict resilience, vulnerability and recovery, and to develop novel approaches for the prevention and treatment of depression. Health sciences/Diseases/Psychiatric disorders/Depression Health sciences/Biomarkers/Predictive markers Figures Figure 1 Figure 2 Figure 3 Figure 4 Full Text Additional Declarations There is NO Competing Interest. Table 1 is available in the Supplementary Files section. Supplementary Files DelliCollietaleditorialpolicychecklist.pdf Checklist DelliCollietalSupplementaryInformation.pdf Supplementary Information DelliCollietalTab.1.pdf Table 1. Baseline demographic and clinical characteristics of the sample considered in the network analysis. MDE, major depressive episode. Cite Share Download PDF Status: Published Journal Publication published 15 Jan, 2024 Read the published version in Nature Mental Health → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2741248","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":189419494,"identity":"73a172da-7de9-4a9e-816c-69121ae049ae","order_by":0,"name":"Igor Branchi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYBACNhDB2AAieRgOfDAA0sykaDk4A6yFkB5kLcw8YC4BLXz8i499YNxxT96c/ezBwzYFdfYM7PwH8DtM4lnyDMYzxYY7e/ISDucYHE5sIOQwNokzxgyMbQmMG27wGAC1HEgg6BeYFnuwFgsDoMMIauHvAWtJBGthMGBmJMJhbMkMiWcSkjecyTE42AP0SxszswFeLfL9hw8zfNyRYLvh+BnjDz/+1Nnz8x98gN8aiQQGhgQUe/GrBwICkTAKRsEoGAWjgIEBAE3VPkeD9KPKAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-4484-3598","institution":"Istituto Superiore di Sanit\u0026#x00E0","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Igor","middleName":"","lastName":"Branchi","suffix":""},{"id":189419495,"identity":"2d39feb9-16ff-4af5-b92f-7fb24560805f","order_by":1,"name":"Claudia Delli Colli","email":"","orcid":"","institution":"Sapienza University of Rome, Rome, Italy","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Claudia","middleName":"Delli","lastName":"Colli","suffix":""},{"id":189419496,"identity":"b0a21100-0f90-484d-8429-b8a7374e448d","order_by":2,"name":"Flavia Chiarotti","email":"","orcid":"","institution":"Istituto Superiore di Sanità","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Flavia","middleName":"","lastName":"Chiarotti","suffix":""},{"id":189419497,"identity":"540a7d54-9eff-4b86-8126-38f3e419d7f4","order_by":3,"name":"Patrizia Campolongo","email":"","orcid":"","institution":"Sapienza University of Rome, Rome, Italy","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Patrizia","middleName":"","lastName":"Campolongo","suffix":""},{"id":189419498,"identity":"4586faa9-cb65-4c39-9848-6c412818d026","order_by":4,"name":"Alessandro Giuliani","email":"","orcid":"","institution":"Istituto Superiore di Sanità","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Alessandro","middleName":"","lastName":"Giuliani","suffix":""}],"badges":[],"createdAt":"2023-03-27 09:47:00","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2741248/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2741248/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s44220-023-00192-z","type":"published","date":"2024-01-15T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":35398435,"identity":"44531ad6-6841-4737-b92e-907e5956ed3d","added_by":"auto","created_at":"2023-04-06 14:52:51","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":822003,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagrams of the samples included in the analyses.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2741248/v1/b0421b05d68dcd9a82878dca.jpg"},{"id":35398436,"identity":"a4e519f8-9388-4159-8fd1-3a83b6deb4c5","added_by":"auto","created_at":"2023-04-06 14:52:51","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":838909,"visible":true,"origin":"","legend":"\u003cp\u003eConnectivity strength of the symptom network is weaker in responders than in non-responders. Network structures of non-responders (n = 1,907) and responders (n = 637) at baseline. Blue connections represent positive associations, whereas red connections represent negative associations. 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Correlation between connectivity strength and the Δ\u003csub\u003eQIDS\u003c/sub\u003e (i.e., |QIDS-C\u003csub\u003e16\u003c/sub\u003e score at week 4 - QIDS-C\u003csub\u003e16\u003c/sub\u003e score at week 0|). ***p-value of Pearson’s correlation \u0026lt; 0.001. Sample sizes are described in Supplementary Table 1.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-2741248/v1/1dcec78e164bc95d1008403f.jpg"},{"id":35398441,"identity":"80fc7f75-c730-4489-9732-495311b55d45","added_by":"auto","created_at":"2023-04-06 14:52:51","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":507087,"visible":true,"origin":"","legend":"\u003cp\u003eConnectivity strength of the symptom network is strongly and inversely correlated to the susceptibility to change mood according to context. Correlation between connectivity strength and the match between subjective appraisal and improvement (i.e., Z-score QLES-Q-SF – Z-score of Δ\u003csub\u003eQIDS\u003c/sub\u003e). *p-value of Pearson’s correlation\u0026lt; 0.05. 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