Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Victoria, Australia.
Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Victoria, Australia.
Neuroimage Clin. 2022;35:103064. doi: 10.1016/j.nicl.2022.103064. Epub 2022 May 28.
Brain structural alterations and cognitive dysfunction are independent predictors for poor clinical outcome in schizophrenia, and the associations between these domains remains unclear. We employed a novel, multiblock partial least squares correlation (MB-PLS-C) technique and investigated multivariate cortico-cognitive patterns in patients with treatment-resistant schizophrenia (TRS) and matched healthy controls (HC).
Forty-one TRS patients (age 38.5 ± 9.1, 30 males (M)), and 45 HC (age 40.2 ± 10.6, 29 M) underwent 3T structural MRI. Volumes of 68 brain regions and seven variables from CANTAB covering memory and executive domains were included. Univariate group differences were assessed, followed by the MB-PLS-C analyses to identify group-specific multivariate patterns of cortico-cognitive coupling. Supplementary three-group analyses, which included 23 non-affected first-degree relatives (NAR), were also conducted.
Univariate tests demonstrated that TRS patients showed impairments in all seven cognitive tasks and volume reductions in 12 cortical regions following Bonferroni correction. The MB-PLS-C analyses revealed two significant latent variables (LVs) explaining > 90% of the sum-of-squares variance. LV1 explained 78.86% of the sum-of-squares variance, describing a shared, widespread structure-cognitive pattern relevant to both TRS patients and HCs. In contrast, LV2 (13.47% of sum-of-squares variance explained) appeared specific to TRS and comprised a differential cortico-cognitive pattern including frontal and temporal lobes as well as paired associates learning (PAL) and intra-extra dimensional set shifting (IED). Three-group analyses also identified two significant LVs, with NARs more closely resembling healthy controls than TRS patients.
MB-PLS-C analyses identified multivariate brain structural-cognitive patterns in the latent space that may provide a TRS signature.
脑结构改变和认知功能障碍是精神分裂症患者临床预后不良的独立预测因素，而这两个领域之间的关系尚不清楚。我们采用了一种新的多块偏最小二乘相关（MB-PLS-C）技术，研究了难治性精神分裂症（TRS）患者和匹配的健康对照（HC）的皮质-认知多变量模式。
41 名 TRS 患者（年龄 38.5±9.1，30 名男性（M））和 45 名 HC（年龄 40.2±10.6，29 名 M）接受了 3T 结构 MRI 检查。纳入了 68 个脑区的体积和 CANTAB 涵盖记忆和执行域的 7 个变量。评估了单变量组差异，然后进行 MB-PLS-C 分析以确定皮质-认知耦合的特定组多变量模式。还进行了包括 23 名无影响一级亲属（NAR）的补充三分组分析。
单变量检验表明，TRS 患者在经过 Bonferroni 校正后，在所有七项认知任务中均表现出损伤，并且在 12 个皮质区域的体积减少。MB-PLS-C 分析显示，有两个显著的潜在变量（LV）解释了总和方差的>90%。LV1 解释了总和方差的 78.86%，描述了一个共享的、广泛的结构-认知模式，与 TRS 患者和 HC 均有关。相比之下，LV2（总和方差的 13.47%解释）似乎是 TRS 特有的，包括额叶和颞叶以及配对联想学习（PAL）和内外维度集转换（IED）的差异皮质-认知模式。三分组分析也确定了两个显著的 LV，NAR 比 TRS 患者更接近健康对照。
MB-PLS-C 分析在潜在空间中确定了多变量的大脑结构-认知模式，这可能为 TRS 提供一个特征。
