Electrical and Electronic Engineering - Research Publications

Permanent URI for this collection

http://hdl.handle.net/11343/362

Filters

2022 1
Reset filters

Settings
Statistics
Citations
Author: Everall, Ian × Type: Journal Article × Start date: 2020 × End date: 2022 ×

Search Results

Now showing 1 - 1 of 1
  • Item
    Thumbnail Image
    Cortico-cognition coupling in treatment resistant schizophrenia
    Syeda, WT ; Wannan, CMJ ; Merritt, AH ; Raghava, JM ; Jayaram, M ; Velakoulis, D ; Kristensen, TD ; Soldatos, RF ; Tonissen, S ; Thomas, N ; Ambrosen, KS ; Sorensen, ME ; Fagerlund, B ; Rostrup, E ; Glenthoj, BY ; Skafidas, E ; Bousman, CA ; Johnston, LA ; Everall, I ; Ebdrup, BH ; Pantelis, C (ELSEVIER SCI LTD, 2022)
    BACKGROUND: 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). METHOD: 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. RESULTS: 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. CONCLUSIONS: MB-PLS-C analyses identified multivariate brain structural-cognitive patterns in the latent space that may provide a TRS signature.