Widespread white matter microstructural abnormalities in bipolar disorder: Evidence from mega- and meta-analyses across 3,033 individuals

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, Pcorr < 0.001) and cingulum (right: R2 = 0.041, left: R2 = 0.040, Pcorr < 0.001). Lithium medication, later onset and short disease duration were related to higher FA along multiple ROIs. Results of the meta-analysis showed similar effects. We demonstrated widespread WM abnormalities in BD and highlighted that altered WM connectivity within the corpus callosum and the cingulum are strongly associated with BD. These brain abnormalities could represent a biomarker for use in the diagnosis of BD. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org

Diagnostic accuracy in adults with ADHD and bipolar disorder: high-dimensional MRI pattern classification

INTRODUÇÃO: O transtorno de déficit de atenção com hiperatividade (TDAH) persistente em adultos apresenta prevalência significativa na população geral. Nota-se também uma alta taxa de comorbidade com outros quadros psiquiátricos, especialmente o transtorno bipolar (TB). Entretanto, ainda hoje discutem-se as próprias definições do TDAH e os limites da comorbidade TDAH+TB, que poderia ser uma extensão dos sintomas do espectro bipolar, uma sobreposição dos dois transtornos ou uma entidade separada com substrato neurobiológico distinto. Impõe-se, assim, a pesquisa de biomarcadores válidos com potencial aplicação na prática clínica. O surgimento recente de técnicas de classificação de padrões morfológicos cerebrais complexos possibilita uma investigação mais direcionada de biomarcadores, buscando em cada indivíduo um conjunto de características que seja capaz de classificá-lo como pertencente a um determinado grupo. OBJETIVOS: Aplicar, de maneira inédita, a técnica de reconhecimento automatizado de padrão aos dados de neuroimagem de pacientes adultos sem tratamento prévio com diagnóstico de TDAH com início na infância, TB, TDAH+TB e controles saudáveis (CS), em busca de assinaturas neuroanatômicas associadas a estes transtornos. MÉTODOS: Três grupos de adultos nunca tratados compostos de 67 sujeitos com TDAH, 30 sujeitos com TB e 16 sujeitos preenchendo critérios diagnósticos para ambos os transtornos; e uma amostra de CS (n=66), foram submetidos ao exame de ressonância magnética (RM) estrutural e de imagem por tensor de difusão (diffusion tensor imaging; DTI). Através de um método automatizado, regiões de interesse foram posicionadas ao longo de todo o cérebro e através destas foram obtidas medidas cerebrais a partir das imagens multimodais. Tais medidas foram usadas como dados de entrada para um classificador não-linear baseado em support vector machine (SVM). Comparações entre todos os pacientes e CS foram feitas através de subgrupos pareados individualmente para gênero e idade e pareados entre os grupos para nível socioeconômico e escolaridade. As medidas de desempenho diagnóstico foram analisadas com o auxílio de curvas receiver operating characteristic (ROC). RESULTADOS: As análises de classificação entre todos os subgrupos apresentaram resultados expressivamente acima do acaso, com exceção da comparação entre os pacientes com TB e os CS (p=0,09). A comparação entre os subgrupos com TDAH e CS apresentou medidas de área sob a curva (AUC) e acurácia diagnóstica de até 0,71 e 66,2% (p=0,003). A comparação entre os subgrupos com TDAH e TB obteve AUC e acurácia diagnóstica de até 0,78 e 70,2% (p=0,01). As análises de classificação entre os pacientes TDAH+TB e todos os outros subgrupos resultaram em valores de até 0,89 e 80,5% (p=0,0009) de AUC e acurácia diagnóstica respectivamente. CONCLUSÃO: Os resultados fornecem endosso neurobiológico para a validade do diagnóstico clinico de TDAH em adultos. As características cerebrais mostraram-se suficientemente fortes para o diagnóstico diferencial entre o TDAH e o TB e também reforçam a hipótese de que a associação TDAH+TB deve ser compreendida como uma entidade neurobiológica distinta. Restam ainda relevantes dificuldades na busca de biomarcadores para a caracterização do TB. As assinaturas neuroanatômicas identificadas neste estudo podem fornecer informações objetivas adicionais e valiosas, servindo como base para estudos futuros que avaliem sua possível influência em decisões terapêuticas dos pacientes apresentando sintomas do espectro TDAH e da comorbidade TDAH+TBINTRODUCTION: Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent condition in the general adult population. Also important is its high rate of comorbidity with other psychiatric disorders, particularly bipolar disorder (BD). However, not only the definition of ADHD is still a matter of discussion but also the limits of the ADHD+BD comorbidity; such comorbidity may be interpreted as a continuum spectrum of BD, an overlap of symptoms, or a separate diagnostic entity with a distinct neurobiological substrate. Therefore, further search for valid biomarkers with potential application in clinical practice is still required. The recent development of high-dimensional pattern recognition techniques has allowed targeted investigations of biomarkers, searching for sets of characteristics that could be used to classify each patient in a particular group. OBECTIVES: To apply, for the first time in the literature, machine learning-based pattern recognition methods to neuroimaging data obtained in never-treated adults with childhood-onset ADHD, BD, ADHD+BD and healthy controls (HC), searching for different neuroanatomical signatures associated with each disorder. METHODS: Three groups of never treated adults as following: 67 ADHD patients, 30 BD patients, 16 patients fulfilling diagnostic criteria for both disorders; and a sample of HC (n=66) underwent structural magnetic resonance imaging (MRI) and diffusion magnetic resonance imaging (DTI) acquisitions. A support vector machine (SVM) classifier with non-linear kernel was applied on multi-modal image features extracted on regions-of-interest placed across the whole brain. Comparisons among all patients and controls were carried out through subgroups individually matched for gender and age, and group-matched for years of education and socio-economic status. Diagnostic performance measures were evaluated by computing receiver operating characteristic (ROC) curves. RESULTS: All results on classification analyses were clearly significant above chance level, except in the comparison analysis between BD patients and HC (p=0.09). The comparison between ADHD and HC subgroups afforded area under the curve (AUC) measures and diagnostic accuracy of up to 0.71 and 66.2% (p=0.003). Comparison between ADHD and BD subgroups achieved AUC and diagnostic accuracy of up to 0.78 and 70.2% (p=0.01). Classification analysis between ADHD+BD patients and the other subgroups yielded AUC and diagnostic accuracy values of up to 0.89 and 80.5% (p=0.0009). CONCLUSION: The present study provides neurobiological endorsement to the validity of the clinically-based diagnosis of ADHD in adults. Brain features were strong enough to the differential diagnosis between ADHD and BD, as well as to reinforce the hypothesis that ADHD+BD may represent a distinct neurobiological entity. However, relevant challenges persist regarding the search for biomarkers for BD. The neuroanatomical signatures identified herein may provide additional, objective information, paving the way for future studies assessing its influence in treatment decisions in adults with ADHD and ADHD+BD spectrum symptom

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

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, Pcorr < 0.001) and cingulum (right: R2 = 0.041, left: R2 = 0.040, Pcorr < 0.001). Lithium medication, later onset and short disease duration were related to higher FA along multiple ROIs. Results of the meta-analysis showed similar effects. We demonstrated widespread WM abnormalities in BD and highlighted that altered WM connectivity within the corpus callosum and the cingulum are strongly associated with BD. These brain abnormalities could represent a biomarker for use in the diagnosis of BD. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org

Grey and white matter volumes either in treatment-naïve or hormone-treated transgender women: a voxel-based morphometry study

Abstract Many previous magnetic resonance imaging (MRI) studies have documented sex differences in brain morphology, but the patterns of sexual brain differences in transgender women – male sex assigned at birth – with a diagnosis of gender dysphoria (TW) have been rarely investigated to date. We acquired T1-weighted MRI data for the following four (n = 80) groups: treatment-naïve TW (TNTW), TW treated with cross-sex hormones for at least one year (TTW), cisgender men, and cisgender women (cisgender individuals as controls). Differences in whole-brain and regional white matter volume and grey matter volume (GMV) were assessed using voxel-based morphometry. We found lower global brain volumes and regional GMVs in a large portion of the posterior-superior frontal cortex in the cisgender women group than in the TTW and cisgender men groups. Additionally, both transgender groups exhibited lower bilateral insular GMVs than the cisgender women group. Our results highlight differences in the insula in both transgender groups; such differences may be characteristic of TW. Furthermore, these alterations in the insula could be related to the neural network of body perception and reflect the distress that accompanies gender dysphoria

Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA consortium

Hemispheric asymmetry is a cardinal feature of human brain organization. Altered brain asymmetry has also been linked to some cognitive and neuropsychiatric disorders. Here, the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium presents the largest-ever analysis of cerebral cortical asymmetry and its variability across individuals. Cortical thickness and surface area were assessed in MRI scans of 17,141 healthy individuals from 99 datasets worldwide. Results revealed widespread asymmetries at both hemispheric and regional levels, with a generally thicker cortex but smaller surface area in the left hemisphere relative to the right. Regionally, asymmetries of cortical thickness and/or surface area were found in the inferior frontal gyrus, transverse temporal gyrus, parahippocampal gyrus, and entorhinal cortex. These regions are involved in lateralized functions, including language and visuospatial processing. In addition to population-level asymmetries, variability in brain asymmetry was related to sex, age, and intracranial volume. Interestingly, we did not find significant associations between asymmetries and handedness. Finally, with two independent pedigree datasets (n = 1,443 and 1,113, respectively), we found several asymmetries showing significant, replicable heritability. The structural asymmetries identified and their variabilities and heritability provide a reference resource for future studies on the genetic basis of brain asymmetry and altered laterality in cognitive, neurological, and psychiatric disorders

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

An amendment to this paper has been published and can be accessed via a link at the top of the paper

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

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, Pcorr &lt; 0.001) and cingulum (right: R2 = 0.041, left: R2 = 0.040, Pcorr &lt; 0.001). Lithium medication, later onset and short disease duration were related to higher FA along multiple ROIs. Results of the meta-analysis showed similar effects. We demonstrated widespread WM abnormalities in BD and highlighted that altered WM connectivity within the corpus callosum and the cingulum are strongly associated with BD. These brain abnormalities could represent a biomarker for use in the diagnosis of BD. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org