Abstract #0115

Distinct longitudinal brain white matter microstructure changes and associated polygenic psychiatric and neurodegenerative disorder risk

Max Korbmacher^1,2,3, Dennis van der Meer^2,4, Dani Beck^2,5,6, Daniel Edvard Askeland-Gjerde², Eli Nina Eikefjord^1,3, Arvid Lundervold^1,3,7,8, Ole A. Andreassen^2,9, Lars T. Westlye^2,6,9, and Ivan I. Maximov^1,2

¹Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway, ²NORMENT Centre for Psychosis Research, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway, ³Mohn Medical Imaging and Visualization Centre (MMIV), Bergen, Norway, ⁴Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands, ⁵Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway, ⁶Department of Psychology, University of Oslo, Oslo, Norway, ⁷Department of Radiology, Haukeland University Hospital, Bergen, Norway, ⁸Department of Biomedicine, University of Bergen, Bergen, Norway, ⁹KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway

Synopsis

Motivation: White matter microstructural (WMM) changes are a crucial feature of ageing and disease development. There is yet no comprehensive mapping of such changes.

Goal(s): Providing an overview of WMM changes at different spatial scales, and relationship of these changes to polygenic risk scores (PGRS) of developing psychiatric disorders and Alzheimer's disease.

Approach: WMM metrics were estimated using multiple diffusion approaches, associated with age and PGRS, and ageing changes (inter-scan interval:2.44±0.73 years) assessed at different spatial scales.

Results: We find spatially distributed WMM-changes and PGRS-associations across the brain (most age-sensitive: central and cerebellar WMM). Brain longitudinal changes reflected disorder PGRS better than cross-sectional measures.

Impact: The manuscript details for the first time longitudinal WMM changes in a large longitudinal sample (UK Biobank, N=2,676), and provides the currently most comprehensive overview of PGRS associations with WMM change and WMM (using an additional cross-sectional validation sample, N=31,056).

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