Longitudinal Associations Between White Matter Microstructure and Psychiatric Symptoms in Youth - 28/11/23
Abstract |
Objective |
Associations between psychiatric problems and white matter (WM) microstructure have been reported in youth. Yet, a deeper understanding of this relation has been hampered by a dearth of well-powered longitudinal studies and a lack of explicit examination of the bidirectional associations between brain and behavior. We investigated the temporal directionality of WM microstructure and psychiatric symptom associations in youth.
Method |
In this observational study, we leveraged the world’s largest single- and multi-site cohorts of neurodevelopment: the Generation R (GenR) and Adolescent Brain Cognitive Development Studies (ABCD) (total n scans = 11,400; total N = 5,700). We assessed psychiatric symptoms with the Child Behavioral Checklist as broad-band internalizing and externalizing scales, and as syndrome scales (eg, Anxious/Depressed). We quantified WM with diffusion tensor imaging (DTI), globally and at a tract level. We used cross-lagged panel models to test bidirectional associations of global and specific measures of psychopathology and WM microstructure, meta-analyzed results across cohorts, and used linear mixed-effects models for validation.
Results |
We did not identify any longitudinal associations of global WM microstructure with internalizing or externalizing problems across cohorts (confirmatory analyses) before, and after multiple testing corrections. We observed similar findings for longitudinal associations between tract-based microstructure with internalizing and externalizing symptoms, and for global WM microstructure with specific syndromes (exploratory analyses). Some cross-sectional associations surpassed multiple testing corrections in ABCD, but not in GenR.
Conclusion |
Uni- or bi-directionality of longitudinal associations between WM and psychiatric symptoms were not robustly identified. We have proposed several explanations for these findings, including interindividual differences, the use of longitudinal approaches, and smaller effects than expected.
Study registration information |
Bidirectionality Brain Function and Psychiatric Symptoms; PNY92
Le texte complet de cet article est disponible en PDF.Key words : DTI, brain connectivity, mental health problems, bidirectional, adolescence
Plan
| Data used in the preparation of this article were obtained from the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study (abcdstudy.org/), held in the NIMH Data Archive (NDA). This is a multisite, longitudinal study designed to recruit more than 10,000 children age 9-10 and follow them over 10 years into early adulthood. The ABCD Study® is supported by the National Institutes of Health and additional federal partners under award numbers U01DA041048, U01DA050989, U01DA051016, U01DA041022, U01DA051018, U01DA051037, U01DA050987, U01DA041174, U01DA041106, U01DA041117, U01DA041028, U01DA041134, U01DA050988, U01DA051039, U01DA041156, U01DA041025, U01DA041120, U01DA051038, U01DA041148, U01DA041093, U01DA041089, U24DA041123, U24DA041147. A full list of supporters is available at federal-partners.html. A listing of participating sites and a complete listing of the study investigators can be found at consortium_members/. ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in the analysis or writing of this report. This manuscript reflects the views of the authors and may not reflect the opinions or views of the NIH or ABCD consortium investigators. The Generation R Study is supported by Erasmus MC, Erasmus University Rotterdam, the Rotterdam Homecare Foundation, the Municipal Health Service Rotterdam area, the Stichting Trombosedienst & Artsenlaboratorium Rijnmond, the Netherlands Organization for Health Research and Development (ZonMw), and the Ministry of Health, Welfare and Sport. Neuroimaging informatics and image analysis was supported by the Sophia Foundation (S18-20), Netherlands Organization for Scientific Research (Exacte Wetenschappen) and SURFsara (Cartesius Compute Cluster, www.surfsara.nl/) supported the Supercomputing resources. Authors were supported by an NWO-VICI grant (NWO-ZonMW: 016.VICI.170.200), the Sophia Foundation S18-20, and Erasmus MC Fellowship. |
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| Consent has been provided for descriptions of specific patient information. |
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| This work has been previously posted on a preprint server: 2022.08.27.22279298. |
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| This work has been prospectively registered: bg5wt. |
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| Jan van der Ende, PhD, of Erasmus MC, served as the statistical expert for this research. |
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| Author Contributions Conceptualization: Muetzel, Tiemeier, Dall’Aglio, Xu Data curation: Dall’Aglio, Muetzel Formal analysis: Dall’Aglio Funding acquisition: Tiemeier, Muetzel Investigation: Dall’Aglio Methodology: Dall’Aglio, Tiemeier, Muetzel Project administration: Muetzel, Tiemeier, Dall’Aglio Resources: Muetzel Software: Dall’Aglio, Xu Supervision: Muetzel, Tiemeier Validation: Xu Visualization: Dall’Aglio Writing – original draft: Dall’Aglio Writing – review and editing: Dall’Aglio, Muetzel, Tiemeier, Xu |
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| Disclosure: Prof. Tiemeier, Dr. Muetzel, and Mss. Dall’Aglio and Xu have reported no biomedical financial interests or potential conflicts of interest. |
Vol 62 - N° 12
P. 1326-1339 - décembre 2023 Retour au numéro
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