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White matter microstructural alterations across four major psychiatric disorders: mega-analysis study in 2937 individuals.

ABSTRACT: Identifying both the commonalities and differences in brain structures among psychiatric disorders is important for understanding the pathophysiology. Recently, the ENIGMA-Schizophrenia DTI Working Group performed a large-scale meta-analysis and reported widespread white matter microstructural alterations in schizophrenia; however, no similar cross-disorder study has been carried out to date. Here, we conducted mega-analyses comparing white matter microstructural differences between healthy comparison subjects (HCS; N?=?1506) and patients with schizophrenia (N?=?696), bipolar disorder (N?=?211), autism spectrum disorder (N?=?126), or major depressive disorder (N?=?398; total N?=?2937 from 12 sites). In comparison with HCS, we found that schizophrenia, bipolar disorder, and autism spectrum disorder share similar white matter microstructural differences in the body of the corpus callosum; schizophrenia and bipolar disorder featured comparable changes in the limbic system, such as the fornix and cingulum. By comparison, alterations in tracts connecting neocortical areas, such as the uncinate fasciculus, were observed only in schizophrenia. No significant difference was found in major depressive disorder. In a direct comparison between schizophrenia and bipolar disorder, there were no significant differences. Significant differences between schizophrenia/bipolar disorder and major depressive disorder were found in the limbic system, which were similar to the differences in schizophrenia and bipolar disorder relative to HCS. While schizophrenia and bipolar disorder may have similar pathological characteristics, the biological characteristics of major depressive disorder may be close to those of HCS. Our findings provide insights into nosology and encourage further investigations of shared and unique pathophysiology of psychiatric disorders.

SUBMITTER: Koshiyama D

PROVIDER: S-EPMC7156346 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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White matter microstructural alterations across four major psychiatric disorders: mega-analysis study in 2937 individuals.

Koshiyama Daisuke D Fukunaga Masaki M Okada Naohiro N Morita Kentaro K Nemoto Kiyotaka K Usui Kaori K Yamamori Hidenaga H Yasuda Yuka Y Fujimoto Michiko M Kudo Noriko N Azechi Hirotsugu H Watanabe Yoshiyuki Y Hashimoto Naoki N Narita Hisashi H Kusumi Ichiro I Ohi Kazutaka K Shimada Takamitsu T Kataoka Yuzuru Y Yamamoto Maeri M Ozaki Norio N Okada Go G Okamoto Yasumasa Y Harada Kenichiro K Matsuo Koji K Yamasue Hidenori H Abe Osamu O Hashimoto Ryuichiro R Takahashi Tsutomu T Hori Tomoki T Nakataki Masahito M Onitsuka Toshiaki T Holleran Laurena L Jahanshad Neda N van Erp Theo G M TGM Turner Jessica J Donohoe Gary G Thompson Paul M PM Kasai Kiyoto K Hashimoto Ryota R

Molecular psychiatry 20191129 4

Identifying both the commonalities and differences in brain structures among psychiatric disorders is important for understanding the pathophysiology. Recently, the ENIGMA-Schizophrenia DTI Working Group performed a large-scale meta-analysis and reported widespread white matter microstructural alterations in schizophrenia; however, no similar cross-disorder study has been carried out to date. Here, we conducted mega-analyses comparing white matter microstructural differences between healthy comp ...[more]

PMID: 31780770

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Project description:BACKGROUND:Altered structural network-connectivity has been reported in psychotic disorder but whether these alterations are associated with genetic vulnerability, and/or with phenotypic variation, has been less well examined. This study examined i) whether differences in network-connectivity exist between patients with psychotic disorder, siblings of patients with psychotic disorder and controls, and ii) whether network-connectivity alterations vary with (subclinical) symptomatology. METHODS:Network-connectivity measures (global efficiency (GE), density, local efficiency (LE), clustering coefficient (CC)) were derived from diffusion weighted imaging (DWI) and were compared between 85 patients with psychotic disorder, 93 siblings without psychotic disorder and 80 healthy comparison subjects using multilevel regression models. In patients, associations between Positive and Negative Syndrome Scale (PANSS) symptoms and topological measures were examined. In addition, interactions between subclinical psychopathology and sibling/healthy comparison subject status were examined in models of topological measures. RESULTS:While there was no main effect of group with respect to GE, density, LE and CC, siblings had a significantly higher CC compared to patients (B = 0.0039, p = .002). In patients, none of the PANSS symptom domains were significantly associated with any of the four network-connectivity measures. The two-way interaction between group and SIR-r positive score in the model of LE was significant (χ2 = 6.24, p = .01, df = 1). In the model of CC, the interactions between group and respectively SIS-r positive (χ2 = 5.59, p = .02, df = 1) and negative symptom scores (χ2 = 4.71, p = .03, df = 1) were significant. Stratified analysis showed that, in siblings, decreased LE and CC was significantly associated with increased SIS-r positive scores (LE: B = -0.0049, p = .003, CC: B = -0.0066, p = .01) and that decreased CC was significantly associated with increased SIS-r negative scores (B = -0.012, p = .003). There were no significant interactions between group and SIS-r scores in the models of GE and density. CONCLUSION:The findings indicate absence of structural network-connectivity alterations in individuals with psychotic disorder and in individuals at higher than average genetic risk for psychotic disorder, in comparison with healthy subjects. The differential subclinical symptom-network connectivity associations in siblings with respect to controls may be a sign of psychosis vulnerability in the siblings.

Dataset Information

White matter microstructural alterations across four major psychiatric disorders: mega-analysis study in 2937 individuals.

Publications

White matter microstructural alterations across four major psychiatric disorders: mega-analysis study in 2937 individuals.

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