Your browser doesn't support javascript.
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 115
Filtrar
Mais filtros










Intervalo de ano de publicação
1.
Am J Psychiatry ; : appiajp201919030225, 2020 Mar 26.
Artigo em Inglês | MEDLINE | ID: mdl-32212855

RESUMO

OBJECTIVE: Schizophrenia has recently been associated with widespread white matter microstructural abnormalities, but the functional effects of these abnormalities remain unclear. Widespread heterogeneity of results from studies published to date preclude any definitive characterization of the relationship between white matter and cognitive performance in schizophrenia. Given the relevance of deficits in cognitive function to predicting social and functional outcomes in schizophrenia, the authors carried out a meta-analysis of available data through the ENIGMA Consortium, using a common analysis pipeline, to elucidate the relationship between white matter microstructure and a measure of general cognitive performance, IQ, in patients with schizophrenia and healthy participants. METHODS: The meta-analysis included 760 patients with schizophrenia and 957 healthy participants from 11 participating ENIGMA Consortium sites. For each site, principal component analysis was used to calculate both a global fractional anisotropy component (gFA) and a fractional anisotropy component for six long association tracts (LA-gFA) previously associated with cognition. RESULTS: Meta-analyses of regression results indicated that gFA accounted for a significant amount of variation in cognition in the full sample (effect size [Hedges' g]=0.27, CI=0.17-0.36), with similar effects sizes observed for both the patient (effect size=0.20, CI=0.05-0.35) and healthy participant groups (effect size=0.32, CI=0.18-0.45). Comparable patterns of association were also observed between LA-gFA and cognition for the full sample (effect size=0.28, CI=0.18-0.37), the patient group (effect size=0.23, CI=0.09-0.38), and the healthy participant group (effect size=0.31, CI=0.18-0.44). CONCLUSIONS: This study provides robust evidence that cognitive ability is associated with global structural connectivity, with higher fractional anisotropy associated with higher IQ. This association was independent of diagnosis; while schizophrenia patients tended to have lower fractional anisotropy and lower IQ than healthy participants, the comparable size of effect in each group suggested a more general, rather than disease-specific, pattern of association.

2.
Sci Rep ; 10(1): 4261, 2020 Mar 03.
Artigo em Inglês | MEDLINE | ID: mdl-32123264

RESUMO

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

3.
Sci Adv ; 6(6): eaav4520, 2020 02.
Artigo em Inglês | MEDLINE | ID: mdl-32076634

RESUMO

MRI has potential as a translational approach from rodents to humans. However, given that mouse functional MRI (fMRI) uses anesthetics for suppression of motion, it has been difficult to directly compare the result of fMRI in "unconsciousness" disease model mice with that in "consciousness" patients. We develop awake fMRI to investigate brain function in 15q dup mice, a copy number variation model of autism. Compared to wild-type mice, we find that 15q dup is associated with whole-brain functional hypoconnectivity and diminished fMRI responses to odors of stranger mice. Ex vivo diffusion MRI reveals widespread anomalies in white matter ultrastructure in 15q dup mice, suggesting a putative anatomical substrate for these functional hypoconnectivity. We show that d-cycloserine (DCS) treatment partially normalizes these anormalies in the frontal cortex of 15q dup mice and rescues some social behaviors. Our results demonstrate the utility of awake rodent fMRI and provide a rationale for further investigation of DCS therapy.

4.
Neuroimage ; 212: 116654, 2020 Feb 15.
Artigo em Inglês | MEDLINE | ID: mdl-32068163

RESUMO

We propose a new framework to map structural connectomes using deep learning and diffusion MRI. We show that our framework not only enables connectome mapping with a convolutional neural network (CNN), but can also be straightforwardly incorporated into conventional connectome mapping pipelines to enhance accuracy. Our framework involves decomposing the entire brain volume into overlapping blocks. Blocks are sufficiently small to ensure that a CNN can be efficiently trained to predict each block's internal connectivity architecture. We develop a block stitching algorithm to rebuild the full brain volume from these blocks and thereby map end-to-end connectivity matrices. To evaluate our block decomposition and stitching (BDS) framework independent of CNN performance, we first map each block's internal connectivity using conventional streamline tractography. Performance is evaluated using simulated diffusion MRI data generated from numerical connectome phantoms with known ground truth connectivity. Due to the redundancy achieved by allowing blocks to overlap, we find that our block decomposition and stitching steps per se can enhance the accuracy of probabilistic and deterministic tractography algorithms by up to 20-30%. Moreover, we demonstrate that our framework can improve the strength of structure-function coupling between in vivo diffusion and functional MRI data. We find that structural brain networks mapped with deep learning correlate more strongly with functional brain networks (r â€‹= â€‹0.45) than those mapped with conventional tractography (r â€‹= â€‹0.36). In conclusion, our BDS framework not only enables connectome mapping with deep learning, but its two constituent steps can be straightforwardly incorporated as part of conventional connectome mapping pipelines to enhance accuracy.

5.
Schizophr Bull ; 46(1): 140-153, 2020 Jan 04.
Artigo em Inglês | MEDLINE | ID: mdl-31050754

RESUMO

Childhood adversity, such as physical, sexual, and verbal abuse, as well as neglect and family conflict, is a risk factor for schizophrenia. Such adversity can lead to disruptions of cognitive function during development, undermining intellectual capabilities and academic achievement. Schizophrenia is a neurodevelopmental disorder that is associated with cognitive impairments that may become evident during childhood. The Australian Schizophrenia Research Bank database comprises a large community cohort (N = 1169) in which we previously identified 3 distinct cognitive groups among people with schizophrenia: (1) Compromised, current, and estimated premorbid cognitive impairment; (2) Deteriorated, substantial decline from estimated premorbid function; and (3) Preserved, performing in the normal cognitive range without decline. The compromised group displayed the worst functional and symptom outcomes. Here, we extend our previous work by assessing the relationship among these categories of cognitive abilities and reported childhood adversity in 836 patients and healthy controls. Exploratory factor analysis of the Childhood Adversity Questionnaire revealed 3 factors (lack of parental involvement; overt abuse; family breakdown and hardship). People with schizophrenia reported significantly more childhood adversity than healthy controls on all items and factors. People with schizophrenia in the compromised group reported significantly more lack of parental involvement and family breakdown and hardship and lower socioeconomic status than those in the deteriorated group. The cognitive groups were not related to family history of psychosis. These findings identify specific social and family factors that impact cognition, highlighting the important role of these factors in the development of cognitive and functional abilities in schizophrenia.

7.
iScience ; 22: 380-391, 2019 Dec 20.
Artigo em Inglês | MEDLINE | ID: mdl-31812808

RESUMO

Microbial organisms of the human gut microbiome do not exist in isolation but form complex and diverse interactions to maintain health and reduce risk of disease development. The organization of the gut microbiome is assumed to be a singular assortative network, where interactions between operational taxonomic units (OTUs) can readily be clustered into segregated and distinct communities. Here, we leverage recent methodological advances in network modeling to assess whether communities in the human microbiome exhibit a single network structure or whether co-existing mesoscale network architectures are present. We found evidence for core-periphery structures in the microbiome, supported by strong, assortative community interactions. This complex architecture, coupled with previously reported functional roles of OTUs, provides a nuanced understanding of how the microbiome simultaneously promotes high microbial diversity and maintains functional redundancy.

8.
Neuroimage Clin ; : 102030, 2019 Oct 21.
Artigo em Inglês | MEDLINE | ID: mdl-31711956

RESUMO

OBJECTIVE: Sleep problems is the most common side effect of methylphenidate (MPH) treatment in ADHD youth and carry potential to negatively impact long-term self-regulatory functioning. This study aimed to examine whether applying machine learning approaches to pre-treatment demographic, clinical questionnaire, environmental, neuropsychological, genetic, and neuroimaging features can predict sleep side effects following MPH administration. METHOD: The present study included 83 ADHD subjects as a training dataset. The participants were enrolled in an 8-week, open-label trial of MPH. The Barkley Stimulant Side Effects Rating Scale was used to determine the presence/absence of sleep problems at the 2nd week of treatment. Prediction of sleep side effects were performed with step-wise addition of variables measured at baseline: demographics (age, gender, IQ, height/weight) and clinical variables (ADHD Rating Scale-IV (ADHD-RS) and Disruptive Behavior Disorder rating scale) at stage 1, neuropsychological test (continuous performance test (CPT), Stroop color word test) and genetic/environmental variables (dopamine and norepinephrine receptor gene (DAT1, DRD4, ADRA2A, and SLC6A2) polymorphisms, blood lead, and urine cotinine level) at stage 2, and structural connectivities of frontostriatal circuits at stage 3. Three different machine learning algorithms ((Logistic Ridge Regression (LR), support vector machine (SVM), J48) were used for data analysis. Robustness of classifier model was validated in the independent dataset of 36 ADHD subjects. RESULTS: Classification accuracy of LR was 95.5% (area under receiver operating characteristic curve (AUC) 0.99), followed by SVM (91.0%, AUC 0.85) and J48 (90.0%, AUC 0.87) at stage 3 for predicting sleep problems. The inattention symptoms of ADHD-RS, CPT response time variability, the DAT1, ADRA2A DraI, and SLC6A2 A-3081T polymorphisms, and the structural connectivities between frontal and striatal brain regions were identified as the most differentiating subset of features. Validation analysis achieved accuracy of 86.1% (AUC 0.92) at stage 3 with J48. CONCLUSIONS: Our results provide preliminary support to the combination of multimodal classifier, in particular, neuroimaging features, as an informative method that can assist in predicting MPH side effects in ADHD.

9.
Ann Clin Transl Neurol ; 6(12): 2544-2554, 2019 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-31755665

RESUMO

OBJECTIVE: To determine whether anatomical and functional brain features relate to key persistent post-concussion symptoms (PPCS) in children recovering from mild traumatic brain injuries (mTBI), and whether such brain indices can predict individual recovery from PPCS. METHODS: One hundred and ten children with mixed recovery following mTBI were seen at the concussion clinic at Neurology department Alberta Children's Hospital. The primary outcome was the Post-Concussion Symptom Inventory (PCSI, parent proxy). Sleep disturbance scores (PCSI subdomain) and the Neurocognition Index (CNS Vital Signs) were also measured longitudinally. PPCS was assessed at 4 weeks postinjury and 8-10 weeks postinjury. Gray matter volumes were assessed using magnetic resonance imaging (MRI) and voxel-based morphometry at 4 weeks postinjury. Functional connectivity was estimated at the same timepoint using resting-state MRI. Two complementary machine learning methods were used to assess if the combination of gray matter and functional connectivity indices carried meaningful prognostic information. RESULTS: Higher scores on a composite index of sleep disturbance, including fatigue, were associated with converging decreases in gray matter volume and local functional connectivity in two key nodes of the default mode network: the posterior cingulate cortex and the medial prefrontal cortex. Sleep-related disturbances also significantly correlated with reductions in functional connectivity between these brain regions. The combination of structural and functional brain indices associated to individual variations in the default mode network accurately predicted clinical outcomes at follow-up (area under the curve = 0.86). INTERPRETATION: These results highlight that the function-structure profile of core default mode regions underpins sleep-related problems following mTBI and carries meaningful prognostic information for pediatric concussion recovery.

10.
Netw Neurosci ; 3(4): 1121-1140, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31637341

RESUMO

Stroke is characterized by delays in the resting-state hemodynamic response, resulting in synchronization lag in neural activity between brain regions. However, the structural basis of this lag remains unclear. In this study, we used resting-state functional MRI (rs-fMRI) to characterize synchronization lag profiles between homotopic regions in 15 individuals (14 males, 1 female) with brain lesions consequent to stroke as well as a group of healthy comparison individuals. We tested whether the network communication efficiency of each individual's structural brain network (connectome) could explain interindividual and interregional variation in synchronization lag profiles. To this end, connectomes were mapped using diffusion MRI data, and communication measures were evaluated under two schemes: shortest paths and navigation. We found that interindividual variation in synchronization lags was inversely associated with communication efficiency under both schemes. Interregional variation in lag was related to navigation efficiency and navigation distance, reflecting its dependence on both distance and structural constraints. Moreover, severity of motor deficits significantly correlated with average synchronization lag in stroke. Our results provide a structural basis for the delay of information transfer between homotopic regions inferred from rs-fMRI and provide insight into the clinical significance of structural-functional relationships in stroke individuals.

11.
Sci Rep ; 9(1): 13522, 2019 Sep 18.
Artigo em Inglês | MEDLINE | ID: mdl-31534143

RESUMO

Multiple sclerosis (MS) is a brain network disconnection syndrome. Although the brain network topology in MS has been evaluated using diffusion MRI tractography, the mechanism underlying disconnection in the disorder remains unclear. In this study, we evaluated the brain network topology in MS using connectomes with connectivity strengths based on the ratio of the inner to outer myelinated axon diameter (i.e., g-ratio), thereby providing enhanced sensitivity to demyelination compared with the conventional measures of connectivity. We mapped g-ratio-based connectomes in 14 patients with MS and compared them with those of 14 age- and sex-matched healthy controls. For comparison, probabilistic tractography was also used to map connectomes based on the number of streamlines (NOS). We found that g-ratio- and NOS-based connectomes comprised significant connectivity reductions in patients with MS, predominantly in the motor, somatosensory, visual, and limbic regions. However, only the g-ratio-based connectome enabled detection of significant increases in nodal strength in patients with MS. Finally, we found that the g-ratio-weighted nodal strength in motor, visual, and limbic regions significantly correlated with inter-individual variation in measures of disease severity. The g-ratio-based connectome can serve as a sensitive biomarker for diagnosing and monitoring disease progression.

12.
Nat Commun ; 10(1): 4289, 2019 09 19.
Artigo em Inglês | MEDLINE | ID: mdl-31537787

RESUMO

Neural information flow is inherently directional. To date, investigation of directional communication in the human structural connectome has been precluded by the inability of non-invasive neuroimaging methods to resolve axonal directionality. Here, we demonstrate that decentralized measures of network communication, applied to the undirected topology and geometry of brain networks, can infer putative directions of large-scale neural signalling. We propose the concept of send-receive communication asymmetry to characterize cortical regions as senders, receivers or neutral, based on differences between their incoming and outgoing communication efficiencies. Our results reveal a send-receive cortical hierarchy that recapitulates established organizational gradients differentiating sensory-motor and multimodal areas. We find that send-receive asymmetries are significantly associated with the directionality of effective connectivity derived from spectral dynamic causal modeling. Finally, using fruit fly, mouse and macaque connectomes, we provide further evidence suggesting that directionality of neural signalling is significantly encoded in the undirected architecture of nervous systems.


Assuntos
Encéfalo/fisiologia , Comunicação Celular/fisiologia , Rede Nervosa/fisiologia , Vias Neurais/fisiologia , Adulto , Animais , Conectoma , Drosophila/fisiologia , Feminino , Humanos , Macaca/fisiologia , Masculino , Camundongos , Modelos Neurológicos , Transdução de Sinais/fisiologia , Adulto Jovem
13.
Cells ; 8(8)2019 08 05.
Artigo em Inglês | MEDLINE | ID: mdl-31387313

RESUMO

This study aimed to discriminate between neuroinflammation and neuronal degeneration in the white matter (WM) and gray matter (GM) of patients with Parkinson's disease (PD) using free-water (FW) imaging. Analysis using tract-based spatial statistics (TBSS) of 20 patients with PD and 20 healthy individuals revealed changes in FW imaging indices (i.e., reduced FW-corrected fractional anisotropy (FAT), increased FW-corrected mean, axial, and radial diffusivities (MDT, ADT, and RDT, respectively) and fractional volume of FW (FW) in somewhat more specific WM areas compared with the changes of DTI indices. The region-of-interest (ROI) analysis further supported these findings, whereby those with PD showed significantly lower FAT and higher MDT, ADT, and RDT (indices of neuronal degeneration) in anterior WM areas as well as higher FW (index of neuroinflammation) in posterior WM areas compared with the controls. Results of GM-based spatial statistics (GBSS) analysis revealed that patients with PD had significantly higher MDT, ADT, and FW than the controls, whereas ROI analysis showed significantly increased MDT and FW and a trend toward increased ADT in GM areas, corresponding to Braak stage IV. These findings support the hypothesis that neuroinflammation precedes neuronal degeneration in PD, whereas WM microstructural alterations precede changes in GM.

15.
Psychol Med ; : 1-15, 2019 Jul 05.
Artigo em Inglês | MEDLINE | ID: mdl-31274065

RESUMO

BACKGROUND: In schizophrenia, relative stability in the magnitude of cognitive deficits across age and illness duration is inconsistent with the evidence of accelerated deterioration in brain regions known to support these functions. These discrepant brain-cognition outcomes may be explained by variability in cognitive reserve (CR), which in neurological disorders has been shown to buffer against brain pathology and minimize its impact on cognitive or clinical indicators of illness. METHODS: Age-related change in fluid reasoning, working memory and frontal brain volume, area and thickness were mapped using regression analysis in 214 individuals with schizophrenia or schizoaffective disorder and 168 healthy controls. In patients, these changes were modelled as a function of CR. RESULTS: Patients showed exaggerated age-related decline in brain structure, but not fluid reasoning compared to controls. In the patient group, no moderation of age-related brain structural change by CR was evident. However, age-related cognitive change was moderated by CR, such that only patients with low CR showed evidence of exaggerated fluid reasoning decline that paralleled the exaggerated age-related deterioration of underpinning brain structures seen in all patients. CONCLUSIONS: In schizophrenia-spectrum illness, CR may negate ageing effects on fluid reasoning by buffering against pathologically exaggerated structural brain deterioration through some form of compensation. CR may represent an important modifier that could explain inconsistencies in brain structure - cognition outcomes in the extant literature.

16.
Hum Brain Mapp ; 40(16): 4618-4629, 2019 11 01.
Artigo em Inglês | MEDLINE | ID: mdl-31332903

RESUMO

The neurobiology of major depressive disorder (MDD) remains incompletely understood, and many individuals fail to respond to standard treatments. Repetitive transcranial magnetic stimulation (rTMS) of the dorsolateral prefrontal cortex (DLPFC) has emerged as a promising antidepressant therapy. However, the heterogeneity of response underscores a pressing need for biomarkers of treatment outcome. We acquired resting state functional magnetic resonance imaging (rsfMRI) data in 47 MDD individuals prior to 5-8 weeks of rTMS treatment targeted using the F3 beam approach and in 29 healthy comparison subjects. The caudate, prefrontal cortex, and thalamus showed significantly lower blood oxygenation level-dependent (BOLD) signal power in MDD individuals at baseline. Critically, individuals who responded best to treatment were associated with lower pre-treatment BOLD power in these regions. Additionally, functional connectivity (FC) in the default mode and affective networks was associated with treatment response. We leveraged these findings to train support vector machines (SVMs) to predict individual treatment responses, based on learned patterns of baseline FC, BOLD signal power and clinical features. Treatment response (responder vs. nonresponder) was predicted with 85-95% accuracy. Reduction in symptoms was predicted to within a mean error of ±16% (r = .68, p < .001). These preliminary findings suggest that therapeutic outcome to DLPFC-rTMS could be predicted at a clinically meaningful level using only a small number of core neurobiological features of MDD, warranting prospective testing to ascertain generalizability. This provides a novel, transparent and physiologically plausible multivariate approach for classification of individual response to what has become the most commonly employed rTMS treatment worldwide. This study utilizes data from a larger clinical study (Australian New Zealand Clinical Trials Registry: Investigating Predictors of Response to Transcranial Magnetic Stimulation for the Treatment of Depression; ACTRN12610001071011; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=336262).

17.
Neurosurgery ; 2019 Jul 17.
Artigo em Inglês | MEDLINE | ID: mdl-31313803

RESUMO

BACKGROUND AND IMPORTANCE: Obsessive-compulsive disorder (OCD) is a disabling psychiatric disorder, mainly treated with psychotherapy and pharmacotherapy. Surgical intervention may be appropriate for patients with treatment-refractory OCD. Deep brain stimulation (DBS) is an alternative for previously common ablative surgical procedures. Tractography has been proposed as a method for individualizing DBS treatment and may have the potential to improve efficacy. CLINICAL PRESENTATION: We present a patient with treatment-refractory OCD previously treated with bilateral leucotomies, who underwent DBS surgery with targeting informed by tractography. Preoperative tractography to identify suitable DBS targets was undertaken. Structural images were also utilized for standard stereotactic surgical planning. The anteromedial globus pallidus internus (amGPi) was chosen as the target bilaterally after consideration of white matter projections to frontal cortical regions and neurosurgical approach. Bilateral amGPi DBS surgery was undertaken without adverse events. At 16-mo follow-up, there was a 48.5% reduction in OCD symptom severity as measured by the Yale-Brown Obsessive Compulsive Scale. CONCLUSION: The amGPi can be a successful DBS target for OCD. This is the first known case to report on DBS surgery postleucotomies for OCD and highlights the utility of tractography for surgical planning in OCD.

18.
Int J Obes (Lond) ; 43(11): 2309-2321, 2019 11.
Artigo em Inglês | MEDLINE | ID: mdl-31350442

RESUMO

BACKGROUND: Previous studies suggest that obesity (OB) is associated with disrupted brain network organization; however, it remains unclear whether these differences already exist during childhood. Moreover, it should be investigated whether deviant network organization may be susceptible to treatment. METHODS: Here, we compared the structural connectomes of children with OB with age-matched healthy weight (HW) controls (aged 7-11 years). In addition, we examined the effect of a multidisciplinary treatment program, consisting of diet restriction, cognitive behavioral therapy, and physical activity for children with OB on brain network organization. After stringent quality assessment criteria, 40 (18 OB, 22 HW) data sets of the total sample of 51 participants (25 OB, 26 HW) were included in further analyses. For all participants, anthropometric measurements were administered twice, with a 5-month interval between pre- and post tests. Pre- and post T1- and diffusion-weighted imaging scans were also acquired and analyzed using a graph-theoretical approach and network-based statistics. RESULTS: Global network analyses revealed a significantly increased normalized clustering coefficient and small-worldness in children with OB compared with HW controls. In addition, regional analyses revealed increased betweenness centrality, reduced clustering coefficient, and increased structural network strength in children with OB, mainly in the motor cortex and reward network. Importantly, children with OB lost a considerable amount of their body mass after the treatment; however, no changes were observed in the organization of their brain networks. CONCLUSION: This is the first study showing disrupted structural connectomes of children with OB, especially in the motor and reward network. These results provide new insights into the pathophysiology underlying childhood obesity. The treatment did result in a significant weight loss, which was however not associated with alterations in the brain networks. These findings call for larger samples to examine the impact of short-term and long-term weight loss (treatment) on children's brain network organization.

19.
Nat Commun ; 10(1): 2619, 2019 06 13.
Artigo em Inglês | MEDLINE | ID: mdl-31197175

RESUMO

Sleep architecture carries vital information about brain health across the lifespan. In particular, the ability to express distinct vigilance states is a key physiological marker of neurological wellbeing in the newborn infant although systems-level mechanisms remain elusive. Here, we demonstrate that the transition from quiet to active sleep in newborn infants is marked by a substantial reorganization of large-scale cortical activity and functional brain networks. This reorganization is attenuated in preterm infants and predicts visual performance at two years. We find a striking match between these empirical effects and a computational model of large-scale brain states which uncovers fundamental biophysical mechanisms not evident from inspection of the data. Active sleep is defined by reduced energy in a uniform mode of neural activity and increased energy in two more complex anteroposterior modes. Preterm-born infants show a deficit in this sleep-related reorganization of modal energy that carries novel prognostic information.


Assuntos
Encéfalo/fisiologia , Recém-Nascido Prematuro/fisiologia , Modelos Biológicos , Transtornos do Neurodesenvolvimento/diagnóstico , Sono/fisiologia , Eletroencefalografia , Feminino , Seguimentos , Humanos , Lactente , Recém-Nascido , Masculino , Prognóstico , Análise Espaço-Temporal
20.
Am J Psychiatry ; 176(7): 552-563, 2019 07 01.
Artigo em Inglês | MEDLINE | ID: mdl-31164006

RESUMO

OBJECTIVE: Cortical thickness reductions in schizophrenia are irregularly distributed across multiple loci. The authors hypothesized that cortical connectivity networks would explain the distribution of cortical thickness reductions across the cortex, and, specifically, that cortico-cortical connectivity between loci with these reductions would be exceptionally strong and form an interconnected network. This hypothesis was tested in three cross-sectional schizophrenia cohorts: first-episode psychosis, chronic schizophrenia, and treatment-resistant schizophrenia. METHODS: Structural brain images were acquired for 70 patients with first-episode psychosis, 153 patients with chronic schizophrenia, and 47 patients with treatment-resistant schizophrenia and in matching healthy control groups (N=57, N=168, and N=54, respectively). Cortical thickness was compared between the patient and respective control groups at 148 regions spanning the cortex. Structural connectivity strength between pairs of cortical regions was quantified with structural covariance analysis. Connectivity strength between regions with cortical thickness reductions was compared with connectivity strength between 5,000 sets of randomly chosen regions to establish whether regions with reductions were interconnected more strongly than would be expected by chance. RESULTS: Significant (false discovery rate corrected) and widespread cortical thickness reductions were found in the chronic schizophrenia (79 regions) and treatment-resistant schizophrenia (106 regions) groups, with more circumscribed reductions in the first-episode psychosis group (34 regions). Cortical thickness reductions with the largest effect sizes were found in frontal, temporal, cingulate, and insular regions. In all cohorts, both the patient and healthy control groups showed significantly increased structural covariance between regions with cortical thickness reductions compared with randomly selected regions. CONCLUSIONS: Brain network architecture can explain the irregular topographic distribution of cortical thickness reductions in schizophrenia. This finding, replicated in three distinct schizophrenia cohorts, suggests that the effect is robust and independent of illness stage.


Assuntos
Córtex Cerebral/patologia , Rede Nervosa/patologia , Esquizofrenia/patologia , Adulto , Estudos de Casos e Controles , Córtex Cerebral/diagnóstico por imagem , Estudos Transversais , Feminino , Humanos , Imagem por Ressonância Magnética , Masculino , Neuroimagem , Esquizofrenia/diagnóstico por imagem , Adulto Jovem
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA