Abstract
BACKGROUND: Psychotic-like experiences (PLE) represent a risk factor for later psychotic disorders and a marker for general mental distress. The connectivity and microstructure of key brain white matter pathways, including fronto-temporal trajectories, have been implicated in psychosis and psychosis-risk. Although sex differences in PLE prevalence and characteristics have been reported, most neuroimaging studies of PLE have primarily included mixed-sex, samples and little research has been carried out in females only. This study examines the associations between PLE and white matter characteristics in young to middle-aged females. METHODS: We analyzed cross-sectional diffusion magnetic resonance imaging (dMRI) and self-reported data from 661 females aged 9-44 years using the 15-item version of The Community Assessment of Psychic Experiences (CAPE) questionnaire. Associations between CAPE subscales and other psychopathology measures were tested. Using linked independent component analysis (LICA), we decomposed the voxel-wise data from 24 dMRI metrics across five different diffusion models into 10 spatially independent components. We then examined the association between the LICA subject weights and age. Next, we tested for associations between the LICA subject weights and both CAPE total and subscales scores using Bayesian statistics. RESULTS: PLE were broadly associated with various domains of psychopathology and psychosocial factors. Moderate evidence emerged for an association between PLE and an LICA component reflecting a broad and complex pattern of diffusivity in major pathways, including the inferior fronto- occipital fasciculus, anterior thalamic radiation, and forceps minor. The persecutory ideations subscale showed the strongest evidence of an effect. CONCLUSION: PLE in young females are associated with a distinct multimodal white matter pattern reflecting microstructural characteristics in key commissural, association, and thalamocortical pathways in young females. The findings support that LICA is a valuable tool for fusing and decomposing advanced dMRI metrics to delineate white matter patterns that show sensitivity to PLE and mental distress.