Poster No:
566
Submission Type:
Abstract Submission
Authors:
Ming-Hsuan Lu1, Wen-Yih Tseng2, Chang-Le Chen3, Tzung-Jeng Hwang1,4, Chih-Min Liu1,4
Institutions:
1Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan, 2Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, Taipei, Taiwan, 3Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, 4Department of Psychiatry, College of Medicine, National Taiwan Univeristy, Taipei, Taiwan
First Author:
Ming-Hsuan Lu
Department of Psychiatry, National Taiwan University Hospital
Taipei, Taiwan
Co-Author(s):
Wen-Yih Tseng
Institute of Medical Device and Imaging, College of Medicine, National Taiwan University
Taipei, Taiwan
Chang-Le Chen
Department of Bioengineering, University of Pittsburgh
Pittsburgh, PA
Tzung-Jeng Hwang
Department of Psychiatry, National Taiwan University Hospital|Department of Psychiatry, College of Medicine, National Taiwan Univeristy
Taipei, Taiwan|Taipei, Taiwan
Chih-Min Liu
Department of Psychiatry, National Taiwan University Hospital|Department of Psychiatry, College of Medicine, National Taiwan Univeristy
Taipei, Taiwan|Taipei, Taiwan
Introduction:
Schizophrenia is a heterogeneous disorder characterized by highly individual structural changes involving the whole brain. White matter microstructural abnormality, as measured with diffusion MRI, is a robust endophenotype for schizophrenia at the group level. However, white matter microstructure is highly heritable and sensitive to multiple factors other than schizophrenia. Therefore, white matter changes relevant to schizophrenia are often obscured and indiscernible in individuals. We developed a multilevel analytic approach to extract the personalized disease-relevant features from diffusion MRI and to quantify the systems-level enrichment of disease features in five white matter systems, including two association systems (corticolimbic and corticocortical), two projection systems (frontostriatal and corticothalamic), and the commissural system.
Methods:
Using diffusion spectrum imaging, we characterized generalized fractional anisotropy (GFA) of 76 fibers in patients with schizophrenia (SCZ, n = 97) and their unaffected siblings (Sib, n = 90). Following normative modeling (reference group n = 482), we derived GFA z-scores of 45 fibers with high reliability. To extract disease-relevant features, we subtracted GFA z-scores of siblings from those of patients in sib-pairs. To quantify the systems-level enrichment of white matter changes, we derived normalized enrichment scores (NES) and false discovery rate (FDR), either from GFA z-scores from patients only or from disease-relevant features (SCZ subtracted by Sib), of the five systems. Cognitive functions were assessed with the Continuous Performance Test (CPT) and the Weschler's Adult Intelligence Test - III (WAIS-III). Symptoms were profiled using the Positive and Negative Syndrome Scale (PANSS). Association of systems-level white matter hypointegrity (NES) with cognitive functions (WAIS-III IQ and CPT d') and symptom severity (PANSS) were evaluated using linear regression, with age and gender as covariates. For symptom severity, IQ was also included as a covariate since it is associated with both symptom severity and white matter microstructure.
Results:
At the level of individual tracts, bilateral fornix, bilateral orbitofrontal-striatal fibers, and some commissural fibers showed significantly lower GFA in patients compared with unaffected siblings. Of the five systems, corticolimbic, frontostriatal, and commissural system had more systems-level hypointegrity in both disease-relevant NES and patient-only NES than in sibling-only NES (% subjects with NES > 2, corresponding approximately to FDR < 0.05: Corticolimbic SCZ-Sib = 21.8%, SCZ = 24%, Sib = 16.1%; Frontostriatal SCZ-Sib = 24.1%, SCZ = 19.5%, Sib = 11.0%; Commissural SCZ-Sib = 23.0%, SCZ = 23.0%, Sib = 20.7%; Corticocortical SCZ-Sib = 9.2%, SCZ = 16.1%, Sib = 11.5%; Corticothalamic SCZ-Sib = 9.2%, SCZ = 6.9%, Sib = 10.3% ). NES of these three systems were included for association tests with cognitive functions and symptom severity. Disease-relevant systems-level corticolimbic hypointegrity was associated with IQ (p = 0.0191, beta = 4.591) and perceptual sensitivity (CPT d' z-score, p = 0.0143, beta = 0.358), indicating that schizophrenic brains with white matter changes concentrated within the corticolimbic system may have cognitive functions preserved. In terms of symptom severity, disease-relevant systems-level corticolimbic hypointegrity was associated with excitement/hostility (p = 0.0087, beta = 0.210) and depression/anxiety (p = 0.0162, beta = 0.280), suggesting that corticolimbic-specific hypointegrity presents with aggression and mood symptoms in schizophrenia. The associations held for disease-relevant NES but not patient-only NES.
Conclusions:
At the systems level, corticolimbic-specific white matter hypointegrity is associated with preserved cognitive functions, aggression, and mood symptoms in schizophrenia. The personalized white matter system index may inform disease subtyping and patient stratification.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Modeling and Analysis Methods:
Diffusion MRI Modeling and Analysis 2
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
White Matter Anatomy, Fiber Pathways and Connectivity
Keywords:
Limbic Systems
Psychiatric
Schizophrenia
Systems
Tractography
White Matter
WHITE MATTER IMAGING - DTI, HARDI, DSI, ETC
Workflows
1|2Indicates the priority used for review
Provide references using author date format
Chen, C.L. et al. (2022), 'Detection of advanced brain aging in schizophrenia and its structural underpinning by using normative brain age metrics', NeuroImage: Clinical, vol. 34, no. 103003.
Chen, Y.J. et al. (2015), 'Automatic whole brain tract-based analysis using predefined tracts in a diffusion spectrum imaging template and an accurate registration strategy', Human Brain Mapping, vol. 36, no. 9, pp. 3441-3458.
Koshiyama, D. et al. (2020), 'White matter microstructural alterations across four major psychiatric disorders: mega-analysis study in 2937 individuals', Molecular Psychiatry, vol. 25, no. 4, pp. 883-895.
Lv, J. et al. (2021), 'Individual deviations from normative models of brain structure in a large cross-sectional schizophrenia cohort', Molecular Psychiatry, vol. 26, no. 7, pp. 3512-3523.
Tseng, I.W.Y. et al. (2021), 'Microstructural differences in white matter tracts across middle to late adulthood: a diffusion MRI study on 7167 UK Biobank participants', Neurobiolgy of Aging. vol. 98, pp. 160-172.