Saito Yoshito, Pantelis Christos, Cropley Vanessa, Laskaris Liliana, Wannan Cassandra M J, Syeda Warda T
Department of Psychiatry, The University of Melbourne, Carlton, VIC, Australia.
Department of Psychiatry, The University of Melbourne, Carlton, VIC, Australia; Western Centre for Health Research & Education, University of Melbourne & Western Health, Sunshine Hospital, St Albans, VIC, Australia; Monash Institute of Pharmaceutical Sciences (MIPS), Monash University, Clayton, VIC, Australia.
Neuroimage Clin. 2025 Jun 10;47:103824. doi: 10.1016/j.nicl.2025.103824.
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.
近期起病的精神病（ROP）患者存在广泛的灰质（GM）减少和白质（WM）异常。虽然先前的研究采用单变量方法，但了解多个GM区域与WM束之间的关系很重要，因为精神病涉及网络水平的脑功能障碍。了解特征性的GM-WM模式也可能阐明认知障碍的基础，认知障碍可能与精神病中的网络功能障碍有关。我们使用多变量分析研究了ROP患者全脑GM-WM关系及其与认知能力的关联。我们使用了71名非情感性ROP患者（年龄22.09±3.08）和71名匹配对照（年龄22.05±3.21）的T1和扩散加权图像。我们进行了多块偏最小二乘相关分析（MB-PLS-C），以基于GM厚度或表面积以及WM分数各向异性（FA）识别GM-WM模式，并检查它们与认知能力的关联。MB-PLS-C识别出一种代表组间差异的“GM厚度”-“WM FA”模式，解释了12.38%的方差，与额叶和颞叶GM区域以及皮质下结构周围的七条WM束相关。MB-PLS-C还识别出一种显示组间差异的“GM表面积”-“WM FA”模式，解释了18.92%的方差，与扣带回、额叶、颞叶和顶叶GM区域以及15条WM束相关，包括小脑下脚和放射冠。描述组间差异的“GM厚度”-“WM FA”模式与ROP患者的处理速度显著相关。MB-PLS-C识别出全脑不同的GM-WM关系，表明ROP患者脑改变的潜在特征。我们关于处理速度与GM厚度的GM-WM模式之间关系的发现，对我们理解精神病中的脑-行为关系具有启示意义。
