Voxel-wise multivariate analysis of brain-psychosocial associations in adolescents reveals six latent dimensions of cognition and psychopathology

Rick A Adams; Cemre Zor; Agoston Mihalik; Konstantinos Tsirlis; Mikael Brudfors; James Chapman; John Ashburner; Martin P Paulus; Janaina Mourão-Miranda

doi:10.1016/j.bpsc.2024.03.006

Voxel-wise multivariate analysis of brain-psychosocial associations in adolescents reveals six latent dimensions of cognition and psychopathology

Biol Psychiatry Cogn Neurosci Neuroimaging. 2024 Apr 6:S2451-9022(24)00085-5. doi: 10.1016/j.bpsc.2024.03.006. Online ahead of print.

Authors

Rick A Adams¹, Cemre Zor², Agoston Mihalik³, Konstantinos Tsirlis⁴, Mikael Brudfors⁵, James Chapman⁴, John Ashburner⁶, Martin P Paulus⁷, Janaina Mourão-Miranda⁴

Affiliations

¹ Centre for Medical Image Computing, Department of Computer Science, University College London, WC1V 6LJ, UK; Max Planck Centre for Computational Psychiatry and Ageing Research, University College London, WC1B 5EH, UK. Electronic address: rick.adams@ucl.ac.uk.
² Centre for Medical Image Computing, Department of Computer Science, University College London, WC1V 6LJ, UK.
³ Centre for Medical Image Computing, Department of Computer Science, University College London, WC1V 6LJ, UK; Max Planck Centre for Computational Psychiatry and Ageing Research, University College London, WC1B 5EH, UK; Department of Psychiatry, University of Cambridge, CB2 0SZ, UK.
⁴ Centre for Medical Image Computing, Department of Computer Science, University College London, WC1V 6LJ, UK; Max Planck Centre for Computational Psychiatry and Ageing Research, University College London, WC1B 5EH, UK.
⁵ Wellcome Centre for Human Neuroimaging, University College London, WC1N 3BG, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, SE1 7EH, UK.
⁶ Wellcome Centre for Human Neuroimaging, University College London, WC1N 3BG, UK.
⁷ Laureate Institute for Brain Research, Tulsa, Oklahoma, USA.

PMID: 38588854
DOI: 10.1016/j.bpsc.2024.03.006

Abstract

Background: Adolescence heralds the onset of much psychopathology, which may be conceptualized as an emergence of altered covariation between symptoms and brain measures. Multivariate methods can detect such modes of covariation or latent dimensions, but none specifically relating to psychopathology have yet been found using population-level structural brain data. Using voxel-wise (instead of parcellated) brain data may strengthen latent dimensions' brain-psychosocial relationships, but this creates computational challenges.

Methods: We obtained voxel-wise grey matter density and psychosocial variables from the baseline (aged 9-10 years) Adolescent Brain and Cognitive Development cohort (n=11288), and employed a state-of-the-art segmentation method, sparse partial least squares, and a rigorous machine learning framework to prevent overfitting.

Results: We found six latent dimensions, four pertaining specifically to mental health. The mental health dimensions related to overeating, anorexia/internalizing, oppositional symptoms (all p<0.002) and ADHD symptoms (p=0.03). ADHD related to increased and internalizing related to decreased grey matter density in dopaminergic and serotonergic midbrain areas, whereas oppositional symptoms related to increased grey matter in a noradrenergic nucleus. Internalizing related to increased and oppositional symptoms to reduced grey matter density in insula, cingulate and auditory cortices. Striatal regions featured strongly, with reduced caudate nucleus grey matter in ADHD, and reduced putamen grey matter in oppositional/conduct problems. Voxel-wise grey matter density generated stronger brain-psychosocial correlations than brain parcellations.

Conclusions: Voxel-wise brain data strengthen latent dimensions of brain-psychosocial covariation and sparse multivariate methods increase their psychopathological specificity. Internalizing and externalizing are associated with opposite grey matter changes in similar cortical and subcortical areas.

Keywords: brain-behaviour associations; machine learning; neurodevelopment; partial least squares; psychopathology; structural MRI.