Dataset Information

Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals.

ABSTRACT: Fronto-limbic white matter (WM) abnormalities are assumed to lie at the heart of the pathophysiology of bipolar disorder (BD); however, diffusion tensor imaging (DTI) studies have reported heterogeneous results and it is not clear how the clinical heterogeneity is related to the observed differences. This study aimed to identify WM abnormalities that differentiate patients with BD from healthy controls (HC) in the largest DTI dataset of patients with BD to date, collected via the ENIGMA network. We gathered individual tensor-derived regional metrics from 26 cohorts leading to a sample size of N?=?3033 (1482 BD and 1551 HC). Mean fractional anisotropy (FA) from 43 regions of interest (ROI) and average whole-brain FA were entered into univariate mega- and meta-analyses to differentiate patients with BD from HC. Mega-analysis revealed significantly lower FA in patients with BD compared with HC in 29 regions, with the highest effect sizes observed within the corpus callosum (R²?=?0.041, P_corr?2?=?0.041, left: R²?=?0.040, P_corr?

SUBMITTER: Favre P

PROVIDER: S-EPMC6898371 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals.

Favre Pauline P Pauling Melissa M Stout Jacques J Hozer Franz F Sarrazin Samuel S Abé Christoph C Alda Martin M Alloza Clara C Alonso-Lana Silvia S Andreassen Ole A OA Baune Bernhard T BT Benedetti Francesco F Busatto Geraldo F GF Canales-Rodríguez Erick J EJ Caseras Xavier X Chaim-Avancini Tiffany Moukbel TM Ching Christopher R K CRK Dannlowski Udo U Deppe Michael M Eyler Lisa T LT Fatjo-Vilas Mar M Foley Sonya F SF Grotegerd Dominik D Hajek Tomas T Haukvik Unn K UK Howells Fleur M FM Jahanshad Neda N Kugel Harald H Lagerberg Trine V TV Lawrie Stephen M SM Linke Julia O JO McIntosh Andrew A Melloni Elisa M T EMT Mitchell Philip B PB Polosan Mircea M Pomarol-Clotet Edith E Repple Jonathan J Roberts Gloria G Roos Annerine A Rosa Pedro G P PGP Salvador Raymond R Sarró Salvador S Schofield Peter R PR Serpa Mauricio H MH Sim Kang K Stein Dan J DJ Sussmann Jess E JE Temmingh Henk S HS Thompson Paul M PM Verdolini Norma N Vieta Eduard E Wessa Michele M Whalley Heather C HC Zanetti Marcus V MV Leboyer Marion M Mangin Jean-François JF Henry Chantal C Duchesnay Edouard E Houenou Josselin J

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology 20190821 13

Fronto-limbic white matter (WM) abnormalities are assumed to lie at the heart of the pathophysiology of bipolar disorder (BD); however, diffusion tensor imaging (DTI) studies have reported heterogeneous results and it is not clear how the clinical heterogeneity is related to the observed differences. This study aimed to identify WM abnormalities that differentiate patients with BD from healthy controls (HC) in the largest DTI dataset of patients with BD to date, collected via the ENIGMA network. ...[more]

PMID: 31434102

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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

Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals.

Publications

Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals.

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