Linking psychotic-like experiences and brain white matter microstructure in young women
Poster No:
1596
Submission Type:
Abstract Submission
Authors:
Rikka Kjelkenes1, Sara Fernandez-Cabello1, Irene Voldsbekk2, Madelene Bukhari1, Andreas Dahl1, Ingvild Sandø Lofthus1, Henning Hoel Rise1, Ivan Maximov3, Lars Westlye4
Institutions:
1University of Oslo, Oslo, Oslo, 2Norwegian Centre for Mental Disorders Research, Oslo, Oslo, 3Western Norway University of Applied Sciences, Bergen, Bergen, 4Norwegian Centre for Mental Disorders Research (NORMENT), Oslo University Hospital, Oslo, Norway
First Author:
Co-Author(s):
Lars Westlye
Norwegian Centre for Mental Disorders Research (NORMENT), Oslo University Hospital
Oslo, Norway
Norwegian Centre for Mental Disorders Research (NORMENT), Oslo University Hospital
Oslo, Norway
Introduction:
Mental health issues in adolescence and young adulthood co-occurs with a complex interplay of psychosocial factors and neurobiological processes. Psychosis-like experiences have been viewed as a risk factor for psychosis, but it has also been suggested as a general severity marker for mental health. Sex differences in psychotic disorders have long been reported, yet little research has been carried out in female only samples. A better understanding of individual differences in vulnerability to psychotic-like experiences is highly relevant for identifying targets for prevention and intervention.
Methods:
We analyzed cross-sectional diffusion magnetic resonance imaging (dMRI) data and online questionnaires assessing mental health symptoms and social factors from 661 females aged 9-42 years. Self-administered questionnaires were used to measure Psychotic-like experiences as well as other domains of psychopathology. Linked independent component analysis (LICA) was used to decompose the voxel-wise data from 24 dMRI metrics from 4 different diffusion models, resulting in 10 spatially independent components and corresponding subject weights. Next, we examined the association between the components and age. Using Bayesian statistics, we tested for associations between the LICA subject weights and both total and subscales of psychotic-like experience.
Results:
The LICA analysis revealed that LICA component 6 appeared to capture protracted neurodevelopment. We found evidence for an association between LICA component 7 and Psychotic-like experiences. The evidence of this effect was the strongest for the subscale capturing persecutory ideations.
Conclusions:
These results show that LICA can be a valuable tool in fusing different modalities to decompose and sort out shared and unique variance across different advanced dMRI models to identify patterns of protracted white matter development, as well as patterns that can be linked to psychopathology.
Disorders of the Nervous System:
Neurodevelopmental/ Early Life (eg. ADHD, autism) 2
Psychiatric (eg. Depression, Anxiety, Schizophrenia)
Modeling and Analysis Methods:
Bayesian Modeling
Diffusion MRI Modeling and Analysis 1
Novel Imaging Acquisition Methods:
Diffusion MRI
Keywords:
Development
MRI
Psychiatric Disorders
Schizophrenia
Statistical Methods
White Matter
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
1|2Indicates the priority used for review