# Characterising grey-white matter relationships in recent-onset psychosis and its association with cognitive function

## TL;DR

This study examines how grey and white matter in the brain are related in people with recent-onset psychosis and how these relationships affect cognitive abilities like processing speed.

## Contribution

The study introduces a multivariate method to identify whole-brain grey-white matter patterns linked to cognitive function in recent-onset psychosis.

## Key findings

- A grey matter thickness-white matter pattern was associated with group differences and processing speed in psychosis.
- Two distinct GM-WM patterns were identified, each explaining a significant portion of the variance in brain structure differences.
- The GM surface area-WM pattern involved multiple brain regions and tracts, suggesting network-level dysfunction in psychosis.

## Abstract

•Grey and white matter relationships compared in recent-onset psychosis and controls.•Multiblock partial least squares correlation technique was applied.•Both developmentally driven and disease-related GM-WM patterns were observed.•The GM thickness-WM pattern showing group differences was linked to processing speed.

Grey and white matter relationships compared in recent-onset psychosis and controls.

Multiblock partial least squares correlation technique was applied.

Both developmentally driven and disease-related GM-WM patterns were observed.

The GM thickness-WM pattern showing group differences was linked to processing speed.

Individuals with recent-onset psychosis (ROP) present widespread grey matter (GM) reductions and white matter (WM) abnormalities. While prior studies used univariate approaches, understanding how multiple GM regions relate to WM tracts is important, as psychosis involves network-level brain dysfunction. Understanding characteristic GM-WM patterns may also clarify the basis of cognitive impairments, which are potentially linked to network dysfunction in psychosis. Using multivariate analysis, we examined whole-brain GM-WM relationships and their association with cognitive abilities in ROP.

We used T1 and diffusion-weighted images from 71 non-affective ROP individuals (age 22.09 ± 3.08) and 71 matched controls (age 22.05 ± 3.21). We performed multiblock partial least squares correlation (MB-PLS-C) to identify GM-WM patterns based on GM thickness or surface area and WM fractional anisotropy (FA), and examined their associations with cognitive abilities.

MB-PLS-C identified a ‘GM thickness’–‘WM FA’ pattern representing group differences, explaining 12.38 % of the variance and associated with frontal and temporal GM regions and seven WM tracts around subcortical structures. MB-PLS-C also identified a ‘GM surface area’–‘WM FA’ pattern showing group differences, explaining 18.92 % and related with cingulate, frontal, temporal, and parietal GM regions and 15 WM tracts, including the inferior cerebellar peduncle and corona radiata. The ‘GM thickness’–‘WM FA’ pattern describing group differences was significantly correlated with processing speed in ROP.

MB-PLS-C identified differential whole-brain GM-WM relationships, indicating a potential signature of brain alterations in ROP. Our findings of a relationship between processing speed and GM-WM patterns for GM thickness have implications for our understanding of brain-behaviour relationships in psychosis.