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1.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 1742-1745, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018334

RESUMO

Convolutional Neural Network (CNN) has been successfully applied on classification of both natural images and medical images but limited studies applied it to differentiate patients with schizophrenia from healthy controls. Given the subtle, mixed, and sparsely distributed brain atrophy patterns of schizophrenia, the capability of automatic feature learning makes CNN a powerful tool for classifying schizophrenia from controls as it removes the subjectivity in selecting relevant spatial features. To examine the feasibility of applying CNN to classification of schizophrenia and controls based on structural Magnetic Resonance Imaging (MRI), we built 3D CNN models with different architectures and compared their performance with a handcrafted feature-based machine learning approach. Support vector machine (SVM) was used as classifier and Voxel-based Morphometry (VBM) was used as feature for handcrafted feature-based machine learning. 3D CNN models with sequential architecture, inception module and residual module were trained from scratch. CNN models achieved higher cross-validation accuracy than handcrafted feature-based machine learning. Moreover, testing on an independent dataset, 3D CNN models greatly outperformed handcrafted feature-based machine learning. This study underscored the potential of CNN for identifying patients with schizophrenia using 3D brain MR images and paved the way for imaging-based individual-level diagnosis and prognosis in psychiatric disorders.


Assuntos
Imagem por Ressonância Magnética , Esquizofrenia , Encéfalo/diagnóstico por imagem , Humanos , Redes Neurais de Computação , Esquizofrenia/diagnóstico por imagem , Máquina de Vetores de Suporte
2.
Nat Commun ; 11(1): 5272, 2020 10 19.
Artigo em Inglês | MEDLINE | ID: mdl-33077750

RESUMO

16p11.2 and 22q11.2 Copy Number Variants (CNVs) confer high risk for Autism Spectrum Disorder (ASD), schizophrenia (SZ), and Attention-Deficit-Hyperactivity-Disorder (ADHD), but their impact on functional connectivity (FC) remains unclear. Here we report an analysis of resting-state FC using magnetic resonance imaging data from 101 CNV carriers, 755 individuals with idiopathic ASD, SZ, or ADHD and 1,072 controls. We characterize CNV FC-signatures and use them to identify dimensions contributing to complex idiopathic conditions. CNVs have large mirror effects on FC at the global and regional level. Thalamus, somatomotor, and posterior insula regions play a critical role in dysconnectivity shared across deletions, duplications, idiopathic ASD, SZ but not ADHD. Individuals with higher similarity to deletion FC-signatures exhibit worse cognitive and behavioral symptoms. Deletion similarities identified at the connectivity level could be related to the redundant associations observed genome-wide between gene expression spatial patterns and FC-signatures. Results may explain why many CNVs affect a similar range of neuropsychiatric symptoms.


Assuntos
Transtorno do Deficit de Atenção com Hiperatividade/genética , Transtorno do Espectro Autista/genética , Encéfalo/fisiopatologia , Esquizofrenia/genética , Adolescente , Adulto , Transtorno do Deficit de Atenção com Hiperatividade/diagnóstico por imagem , Transtorno do Deficit de Atenção com Hiperatividade/fisiopatologia , Transtorno do Deficit de Atenção com Hiperatividade/psicologia , Transtorno do Espectro Autista/diagnóstico por imagem , Transtorno do Espectro Autista/fisiopatologia , Transtorno do Espectro Autista/psicologia , Encéfalo/diagnóstico por imagem , Criança , Pré-Escolar , Cognição , Estudos de Coortes , Variações do Número de Cópias de DNA , Feminino , Deleção de Genes , Duplicação Gênica , Humanos , Imagem por Ressonância Magnética , Masculino , Mutação , Esquizofrenia/diagnóstico por imagem , Esquizofrenia/fisiopatologia , Adulto Jovem
3.
Psiquiatr. biol. (Internet) ; 27(2): 78-81, mayo-ago. 2020. ilus, tab
Artigo em Espanhol | IBECS | ID: ibc-193252

RESUMO

Las anomalías físicas menores (minor physical anomalies [MPA]) son desviaciones anatómicas sutiles en la apariencia de una persona que pueden sugerir una embriogénesis alterada. Se ha observado que pacientes con esquizofrenia de inicio temprano (early onset schizophrenia [EOS]) presentan un mayor número de MPA, las cuales podrían servir como biomarcadores para predecir el inicio o pronóstico de esta enfermedad. Estas pueden ser numerosas, sin embargo, las más relevantes incluyen las ubicadas en cabeza y boca. Existe poca información respecto a la relación entre estudios de neuroimagen funcional y las MPA en pacientes con esquizofrenia, por lo que presentamos el siguiente caso de un adolescente varón de 16 años. Encontramos que la Escala de Waldrop para anomalías físicas menores se puntuó en 6. En la tomografía por emisión de fotón único cerebral (SPECTc) se evidenció una hiperperfusión en las siguientes áreas: lóbulo frontal, corteza orbitofrontal bilateral y núcleos caudados


Minor physical anomalies (MPA) are subtle anatomical deviations in a person's appearance, which may suggest an altered embryogenesis. It has been observed that patients with early onset schizophrenia (EOS) have a higher number of MPA, which could serve as biomarkers to predict the onset or prognosis of this disease. Although these can be numerous, the most relevant include those located in the head and mouth. There is little information regarding the relationship between functional neuroimaging studies and MPA in patients with schizophrenia, and for this reason the following case of a 16-year-old male adolescent is presented. The Waldrop Scale for minor physical anomalies gave a score of 6. The single photon emission tomography (SPECT) scan showed hyper-perfusion in the following areas: frontal lobe, bilateral orbital-frontal cortex, and caudate nuclei


Assuntos
Humanos , Masculino , Adolescente , Esquizofrenia/diagnóstico por imagem , Tomografia Computadorizada de Emissão de Fóton Único
4.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi ; 37(4): 661-669, 2020 Aug 25.
Artigo em Chinês | MEDLINE | ID: mdl-32840083

RESUMO

How to extract high discriminative features that help classification from complex resting-state fMRI (rs-fMRI) data is the key to improving the accuracy of brain disease recognition such as schizophrenia. In this work, we use a weighted sparse model for brain network construction, and utilize the Kendall correlation coefficient (KCC) to extract the discriminative connectivity features for schizophrenia classification, which is conducted with the linear support vector machine. Experimental results based on the rs-fMRI of 57 schizophrenia patients and 64 healthy controls show that our proposed method is more effective ( i.e., achieving a significantly higher classification accuracy, 81.82%) than other competing methods. Specifically, compared with the traditional network construction methods (Pearson's correlation and sparse representation) and the commonly used feature selection methods (two-sample t-test and Least absolute shrinkage and selection operator (Lasso)), the algorithm proposed in this paper can more effectively extract the discriminative connectivity features between the schizophrenia patients and the healthy controls, and further improve the classification accuracy. At the same time, the discriminative connectivity features extracted in the work could be used as the potential clinical biomarkers to assist the identification of schizophrenia.


Assuntos
Esquizofrenia , Algoritmos , Encéfalo , Mapeamento Encefálico , Humanos , Imagem por Ressonância Magnética , Esquizofrenia/diagnóstico por imagem
5.
Am J Psychiatry ; 177(6): 491-496, 2020 06 01.
Artigo em Inglês | MEDLINE | ID: mdl-32475142

RESUMO

Six articles in the June 2020 issue of the American Journal of Psychiatry address the overall construct of cognition. These articles have a broad connection to cognition, which is itself a broad concept. From the experimental psychology perspective, cognition is the set of processes associated with attending, learning, knowing, and remembering. From the clinical perspective, a number of neuropsychiatric conditions are defined by the presence of cognitive impairment, with onset ranging from childhood, such as attention deficit hyperactivity disorder and intellectual disability, to later life, such as dementia. Other conditions have notable cognitive impairments even if specific cognitive impairments are not an explicit part of their formal diagnostic criteria, including autism spectrum disorder and schizophrenia. Thus, the array of articles in this issue are related to each other and also may make important points about the role of cognition in everyday functioning and the connections between cognitive impairments in neuropsychiatric conditions and in the human population in general. Further, these articles address the neurobiological substrates that have an impact on cognition, with important implications in other domains, such as genomics. Finally, through sophisticated research methods, they clarify the results of previous studies that were affected by a variety of methodological challenges.


Assuntos
Antidepressivos/uso terapêutico , Transtorno do Deficit de Atenção com Hiperatividade/genética , Transtorno Autístico/epidemiologia , Benzodiazepinas/uso terapêutico , Cognição , Demência/epidemiologia , Sono , Feminino , Humanos , Gravidez , Efeitos Tardios da Exposição Pré-Natal/epidemiologia , Fatores de Proteção , Fatores de Risco , Esquizofrenia/diagnóstico por imagem , Substância Branca/diagnóstico por imagem
6.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi ; 37(3): 405-411, 2020 Jun 25.
Artigo em Chinês | MEDLINE | ID: mdl-32597081

RESUMO

Neuroimaging technologies have been applied to the diagnosis of schizophrenia. In order to improve the performance of the single-modal neuroimaging-based computer-aided diagnosis (CAD) for schizophrenia, an ensemble learning algorithm based on learning using privileged information (LUPI) was proposed in this work. Specifically, the extreme learning machine based auto-encoder (ELM-AE) was first adopted to learn new feature representation for the single-modal neuroimaging data. Random project algorithm was then performed on the learned high-dimensional features to generate several new feature subspaces. After that, multiple feature pairs were built among these subspaces to work as source domain and target domain, respectively, which were used to train multiple support vector machine plus (SVM+) classifier. Finally, a strong classifier is learned by combining these SVM+ classifiers for classification. The proposed algorithm was evaluated on a public schizophrenia neuroimaging dataset, including the data of structural magnetic resonance imaging (sMRI) and functional MRI (fMRI). The results showed that the proposed algorithm achieved the best diagnosis performance. In particular, the classification accuracy, sensitivity and specificity of the proposed algorithm were 72.12% ± 8.20%, 73.50% ± 15.44% and 70.93% ± 12.93%, respectively, on the sMRI data, and it also achieved the classification accuracy of 72.33% ± 8.95%, sensitivity of 68.50% ± 16.58% and specificity of 75.73% ± 16.10% on the fMRI data. The proposed algorithm overcomes the problem that the traditional LUPI methods need the additional privileged information modality as source domain. It can be directly applied to the single-modal data for classification, and also can improve the classification performance. Therefore, it suggests that the proposed algorithm will have wider applications.


Assuntos
Neuroimagem , Esquizofrenia , Diagnóstico por Computador , Humanos , Imagem por Ressonância Magnética , Esquizofrenia/diagnóstico por imagem , Máquina de Vetores de Suporte
7.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi ; 37(3): 480-486, 2020 Jun 25.
Artigo em Chinês | MEDLINE | ID: mdl-32597090

RESUMO

The study aims to investigate whether there is difference in pre-treatment white matter parameters in treatment-resistant and treatment-responsive schizophrenia. Diffusion tensor imaging (DTI) was acquired from 60 first-episode drug-naïve schizophrenia (39 treatment-responsive and 21 treatment-resistant schizophrenia patients) and 69 age- and gender-matched healthy controls. Imaging data was preprocessed via FSL software, then diffusion parameters including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) were extracted. Besides, structural network matrix was constructed based on deterministic fiber tracking. The differences of diffusion parameters and topology attributes between three groups were analyzed using analysis of variance (ANOVA). Compared with healthy controls, treatment-responsive schizophrenia showed altered white matter mainly in anterior thalamus radiation, splenium of corpus callosum, cingulum bundle as well as superior longitudinal fasciculus. While treatment-resistant schizophrenia patients showed white matter abnormalities in anterior thalamus radiation, cingulum bundle, fornix and pontine crossing tract relative to healthy controls. Treatment-resistant schizophrenia showed more severe white matter abnormalities in anterior thalamus radiation compared with treatment-responsive patients. There was no significant difference in white matter network topological attributes among the three groups. The performance of support vector machine (SVM) showed accuracy of 63.37% in separating the two patient subgroups ( P = 0.04). In this study, we showed different patterns of white matter alterations in treatment-responsive and treatment-resistant schizophrenia compared with healthy controls before treatment, which may help guiding patient identification, targeted treatment and prognosis improvement at baseline drug-naïve state.


Assuntos
Esquizofrenia , Substância Branca , Anisotropia , Encéfalo/diagnóstico por imagem , Imagem de Tensor de Difusão , Humanos , Esquizofrenia/diagnóstico por imagem
8.
Psychiatry Res Neuroimaging ; 300: 111084, 2020 06 30.
Artigo em Inglês | MEDLINE | ID: mdl-32388386

RESUMO

In this study, we explored the relationship between baseline hippocampal subfield volumes and change in body mass over 12 months of treatment in 90 first-episode schizophrenia spectrum disorder patients (66 males, 24 females; mean age= 24.7 ± 6.8 years). Body mass index was assessed in patients at baseline, and at months 3, 6, 9 and 12. Hippocampal subfields of interest were assessed at baseline using a segmentation algorithm included in the FreeSurfer 6.0 software program. Linear regression revealed a significant interactive effect between sex and anterior hippocampus size as predictors of change in body mass over 12 months, adjusting for age, substance use, and treatment duration. In an exploratory post-hoc sub-analysis, partial correlations showed a significant association between weight gain and smaller CA1, CA3 and subiculum volumes in females, but not males, adjusting for age and substance use, with similar trends evident for the CA4 and presubiculum subfields. In conclusion, our findings suggest that smaller anterior hippocampal subfields at baseline are associated with the development of weight gain over the course of treatment in first-episode schizophrenia spectrum disorders in a sex-specific fashion. This may be related to the greater increase in body mass evident for female patients in our study.


Assuntos
Antipsicóticos/uso terapêutico , Índice de Massa Corporal , Hipocampo/patologia , Esquizofrenia/patologia , Adulto , Feminino , Hipocampo/diagnóstico por imagem , Humanos , Modelos Lineares , Imagem por Ressonância Magnética , Masculino , Tamanho do Órgão/efeitos dos fármacos , Esquizofrenia/diagnóstico por imagem , Esquizofrenia/tratamento farmacológico , Resultado do Tratamento , Adulto Jovem
9.
J Clin Neurosci ; 78: 317-322, 2020 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-32448728

RESUMO

Cognitive control, the ability to use goal-directed information to guide behaviour, is impaired in schizophrenia, and mainly related to dysfunctions within the fronto-posterior brain network. However, cognitive control is a broad cognitive function encompassing distinct sub-processes that, until now, studies have failed to separate and relate to specific brain regions. The goal of this preliminary fMRI study is to investigate the functional specialization of posterior brain regions, and their functional interaction with lateral prefrontal cortex (LPFC) regions, in schizophrenia. Fourteen healthy participants and 15 matched schizophrenic patients participated in this fMRI study. We used a task paradigm that differentiates two cognitive control sub-processes according to the temporal framing of information, namely the control of immediate context (present cues) vs. temporal episode (past instructions). We found that areas activated during contextual and episodic controls were in dorsal posterior regions and that activations did not significantly differ between schizophrenic patients and healthy participants. However, while processing contextual signals, patients with schizophrenia failed to show decreased connectivity between caudal LPFC and areas located in ventral posterior regions. The absence of group difference in the functional specialization of posterior regions is difficult to interpret due to our small sample size. One interpretation for our connectivity results is that patients present an inefficient extinction of posterior regions involved in attention shifting by prefrontal areas involved in the top-down control of contextual signals. Further studies with larger sample sizes will be needed to ascertain those observations.


Assuntos
Cognição , Imagem por Ressonância Magnética/métodos , Esquizofrenia/fisiopatologia , Adulto , Atenção , Encéfalo/fisiopatologia , Mapeamento Encefálico/métodos , Estudos de Casos e Controles , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Córtex Pré-Frontal/fisiopatologia , Esquizofrenia/diagnóstico por imagem , Psicologia do Esquizofrênico
10.
PLoS One ; 15(4): e0231669, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32320431

RESUMO

Subtle abnormalities in sensory integration, motor coordination and sequencing of complex motor acts or neurological soft signs (NSS) are characteristic phenomena in patients with schizophrenia at any stage of the illness. Previous MRI studies in schizophrenia found NSS to be associated with cortical, thalamic and cerebellar changes. Since these studies mainly focused on first-episode or recent onset schizophrenia, the cerebral correlates of NSS in chronic schizophrenia remained rather unclear. 49 middle-aged patients with chronic schizophrenia with a mean duration of illness of 20.3 ± 14.0 years and 29 healthy subjects matched for age and sex were included. NSS were examined on the Heidelberg Scale and correlated to grey matter (GM) by using whole brain high resolution magnetic resonance imaging (3 Tesla) with SPM12/CAT12 analyses. As expected, NSS in patients were significantly (p≤0.001) elevated in contrast to healthy controls, a finding, which not only applied to NSS total score, but also to the respective subscales "motor coordination", "sensory integration", "complex motor tasks", "right/left and spatial orientation" and "hard signs". Within the patient group NSS total scores were significantly correlated to reduced GM in right lingual gyrus, left parahippocampal gyrus, left superior temporal gyrus, left thalamus (medial dorsal nucleus) and left posterior lobe of the cerebellum (declive). Respective negative associations could also be revealed for the subscales "motor coordination", "complex motor tasks" and "right/left and spatial orientation". These findings remained significant after FWE-correction for multiple comparisons and were confirmed when years of education, chlorpromazine-equivalents or variables indicating the severity of psychopathology were introduced as additional covariates. According to our results lingual, parahippocampal, superior temporal, inferior and middle frontal gyri, thalamus and cerebellum have to be considered as important sites of NSS in chronic schizophrenia. That these findings only applied for patients but not healthy controls may indicate a different pathogenesis of NSS.


Assuntos
Encéfalo/diagnóstico por imagem , Esquizofrenia/diagnóstico por imagem , Adulto , Estudos de Casos e Controles , Feminino , Humanos , Imagem por Ressonância Magnética , Masculino , Pessoa de Meia-Idade , Destreza Motora , Percepção , Esquizofrenia/patologia
12.
Psychiatry Res Neuroimaging ; 300: 111079, 2020 06 30.
Artigo em Inglês | MEDLINE | ID: mdl-32283474

RESUMO

Heart rate variability (HRV), a measurement of autonomic nervous system (ANS) activity, has been found reduced in schizophrenia. The anterior cingulate cortex (ACC), which is important in regulating the ANS, is structurally and functionally affected in schizophrenia. We investigate the relationship between HRV and functional and structural connectivity of the ACC in patients with schizophrenia and healthy controls. Ten patients with a diagnosis of schizophrenia and ten healthy controls were recruited. Heart rate was monitored in a naturalistic out-of-clinic setting. Magnetic resonance imaging (MRI) was performed, including resting-state functional MRI and diffusion tensor imaging. Patients with schizophrenia had significantly lower HRV compared to controls. A positive correlation between ACC connectivity with the bilateral cerebellum and HRV was found in the patients. HRV was also positively correlated with amplitude of low frequency fluctuations (ALFF) in the cerebellum, and with axial diffusivity in the middle cerebellar peduncle, in the patients. There was a significant negative relationship between antipsychotic medication dosage, HRV and all neuroimaging measures related to HRV. We conclude that ACC connectivity seems to be affected in schizophrenia, both structurally and functionally, and that the ACC-cerebellum connectivity, as well as cerebellar function, is associated with ANS regulation in patients with schizophrenia.


Assuntos
Sistema Nervoso Autônomo/fisiopatologia , Frequência Cardíaca/fisiologia , Rede Nervosa/fisiopatologia , Esquizofrenia/fisiopatologia , Adulto , Antipsicóticos/uso terapêutico , Sistema Nervoso Autônomo/diagnóstico por imagem , Estudos de Casos e Controles , Cerebelo/diagnóstico por imagem , Cerebelo/fisiopatologia , Imagem de Tensor de Difusão , Feminino , Giro do Cíngulo/diagnóstico por imagem , Giro do Cíngulo/fisiopatologia , Humanos , Imagem por Ressonância Magnética/métodos , Masculino , Pessoa de Meia-Idade , Rede Nervosa/diagnóstico por imagem , Esquizofrenia/diagnóstico por imagem , Esquizofrenia/tratamento farmacológico
13.
Psychiatry Res ; 288: 112957, 2020 06.
Artigo em Inglês | MEDLINE | ID: mdl-32325384

RESUMO

Visual perceptual and processing deficits are common in schizophrenia and possibly point towards visual pathway alterations. However, no studies have examined visual cortical morphology in first-episode psychosis (FEP). In an antipsychotic-naïve FEP population, we investigated primary visual (V1), association area (V2), and motion perception (V5/MT) morphology compared to controls. We found reductions in the V1 and V2 areas, greater MT area and lower MT thickness in the FEP-schizophrenia group when compared to controls. Also, lower MT thickness was associated with worse negative symptoms. Our results shed light on this poorly studied area of visual cortex morphology in FEP.


Assuntos
Antipsicóticos , Transtornos Psicóticos/diagnóstico por imagem , Córtex Visual/diagnóstico por imagem , Vias Visuais/diagnóstico por imagem , Adolescente , Adulto , Antipsicóticos/uso terapêutico , Criança , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Percepção de Movimento/fisiologia , Transtornos Psicóticos/psicologia , Esquizofrenia/diagnóstico por imagem , Esquizofrenia/tratamento farmacológico , Adulto Jovem
14.
Am J Psychiatry ; 177(6): 537-547, 2020 06 01.
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.


Assuntos
Cognição/fisiologia , Inteligência , Esquizofrenia/diagnóstico por imagem , Psicologia do Esquizofrênico , Substância Branca/diagnóstico por imagem , Adulto , Anisotropia , Encéfalo/diagnóstico por imagem , Estudos de Casos e Controles , Imagem de Tensor de Difusão , Análise Fatorial , Feminino , Voluntários Saudáveis , Humanos , Masculino , Pessoa de Meia-Idade , Vias Neurais/diagnóstico por imagem , Análise de Componente Principal , Esquizofrenia/fisiopatologia , Escalas de Wechsler
15.
Int J Geriatr Psychiatry ; 35(7): 728-736, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-32128879

RESUMO

Obesity, aging, and pathophysiology of schizophrenia (SCZ) may collectively contribute to the gray matter loss in brain regions of SCZ. We attempted to examine the association between volumes of specific brain regions, body mass index (BMI), inflammatory markers, and clinical features in older SCZ patients. METHOD: Clinically stable outpatients with schizophrenia (DSM-IV) aged ≥50 years were recruited to undergo whole-brain magnetic resonance imaging. We measured patients' plasma levels of soluble tumor necrosis factor receptor-1, soluble interleukin (IL)-2 receptor (sIL-2R), IL-1ß, and IL-1 receptor antagonist (IL-1Ra). Clinical data were obtained from medical records and interviewing patients along with their reliable others. RESULTS: There were 32 patients with mean age 58.8 years in this study. Multivariate regression analysis found only higher BMI significantly associated with lower volume of total gray matter, bilateral orbitofrontal and prefrontal cortexes, and the right hippocampal and frontal cortexes. Increased intensity of residual symptoms (higher Positive and Negative Syndrome Scale scores) was related to lower volumes of frontal lobe, prefrontal cortex, insula, hippocampus, left hemisphere amygdala, and total white matter. The lower volume of left anterior cingulum was associated with older age and higher sIL-2R plasma level; and higher IL-1Ra level was associated with greater right anterior cingulate volume. Older age at illness onset was significantly associated with the smaller right insula volume. CONCLUSIONS: Higher BMI, more residual symptoms, and inflammatory activity in IL-2 and IL-1 systems may play a role in gray matter loss in various brain regions of schizophrenia across the life span.


Assuntos
Esquizofrenia , Idoso , Índice de Massa Corporal , Encéfalo/diagnóstico por imagem , Humanos , Inflamação , Imagem por Ressonância Magnética , Esquizofrenia/diagnóstico por imagem
16.
BMC Psychiatry ; 20(1): 128, 2020 03 17.
Artigo em Inglês | MEDLINE | ID: mdl-32183776

RESUMO

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disorder featuring the behavioral and psychological symptoms of dementia. Patients with early-onset AD that exhibits first as psychotic symptoms usually lack obvious cognitive impairment, so they may be misdiagnosed with late-onset schizophrenia. CASE PRESENTATION: We report a patient who had prominent psychotic symptoms at the age of 60 and was initially diagnosed with very-late-onset-schizophrenia-like psychosis. Psychotic symptoms disappeared rapidly after treatment with olanzapine, and the patient later showed extrapyramidal symptoms and decline in cognitive function. Brain magnetic resonance imaging (MRI) showed frontotemporal atrophy, and positron emission tomography (PET) showed extensive areas of hypometabolism in the frontal cortex and head of the caudate nucleus. The patient's SORL1 gene was found to carry a heterozygrous mutation (c.296A > G). The patient was eventually diagnosed with early-onset AD. CONCLUSIONS: Our case suggests that clinicians should consider the possibility of early-onset AD in middle-aged or elderly patients whose first symptoms are the behavioral and psychological symptoms of dementia. To distinguish early-onset AD from late-onset schizophrenia, clinicians should evaluate cognitive function, perform MRI and PET, and search for SORL1 mutations.


Assuntos
Doença de Alzheimer , Transtornos Psicóticos , Esquizofrenia , Idoso , Doença de Alzheimer/complicações , Doença de Alzheimer/diagnóstico por imagem , Doença de Alzheimer/genética , Humanos , Proteínas Relacionadas a Receptor de LDL/genética , Imagem por Ressonância Magnética , Proteínas de Membrana Transportadoras/genética , Pessoa de Meia-Idade , Mutação , Tomografia por Emissão de Pósitrons , Transtornos Psicóticos/diagnóstico , Transtornos Psicóticos/etiologia , Esquizofrenia/diagnóstico por imagem , Esquizofrenia/tratamento farmacológico
17.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi ; 37(1): 45-53, 2020 Feb 25.
Artigo em Chinês | MEDLINE | ID: mdl-32096376

RESUMO

Cognitive impairment is one of the three primary symptoms of schizophrenic patients and shows important value in early detection and warning for high-risk individuals. To study the specifics of electroencephalogram (EEG) in patients with schizophrenia under the cognitive load, we collected EEG signals from 17 schizophrenic patients and 19 healthy controls, extracted signals of each band based on wavelet transform, calculated the characteristics of nonlinear dynamic and functional brain networks, and automatically classified the two groups of people by using a machine learning algorithm. Experimental results indicated that the correlation dimension and sample entropy showed significant differences in α, ß, θ, and γ rhythm of the Fp1 and Fp2 electrodes between groups under the cognitive load. These results implied that the functional disruptions in the frontal lobe might be the important factors of cognitive impairments in schizophrenic patients. Further results of the automatic classification analysis indicated that the combination of nonlinear dynamics and functional brain network properties as the input characteristics of the classifier showed the best performance, with the accuracy of 76.77%, sensitivity of 72.09%, and specificity of 80.36%. The results of this study demonstrated that the combination of nonlinear dynamics and function brain network properties may be potential biomarkers for early screening and auxiliary diagnosis of schizophrenia.


Assuntos
Cognição , Eletroencefalografia , Esquizofrenia/diagnóstico por imagem , Processamento de Sinais Assistido por Computador , Humanos , Dinâmica não Linear
18.
Psychiatry Res ; 284: 112770, 2020 02.
Artigo em Inglês | MEDLINE | ID: mdl-32004893

RESUMO

Auditory hallucinations (AHs) are one of the most distressing symptoms of schizophrenia (SZ) and are often resistant to medication. Imaging studies of individuals with SZ show hyperactivation of the default mode network (DMN) and the superior temporal gyrus (STG). Studies in SZ show DMN hyperconnectivity and reduced anticorrelation between DMN and the central executive network (CEN). DMN hyperconnectivity has been associated with positive symptoms such as AHs while reduced DMN anticorrelations with cognitive impairment. Using real-time fMRI neurofeedback (rt-fMRI-NFB) we trained SZ patients to modulate DMN and CEN networks. Meditation is effective in reducing AHs in SZ and to modulate brain network integration and increase DMN anticorrelations. Consequently, patients were provided with meditation strategies to enhance their abilities to modulate DMN/CEN. Results show a reduction of DMN hyperconnectivity and increase in DMNCEN anticorrelation. Furthermore, the change in individual DMN connectivity significantly correlated with reductions in AHs. This is the first time that meditation enhanced through rt-fMRI-NFB is used to reduce AHs in SZ. Moreover, it provides the first empirical evidence for a direct causal relation between meditation enhanced rt-fMRI-NFB modulation of DMNCEN activity and post-intervention modulation of resting state networks ensuing in reductions in frequency and severity of AHs.


Assuntos
Encéfalo/diagnóstico por imagem , Alucinações/diagnóstico por imagem , Imagem por Ressonância Magnética/métodos , Rede Nervosa/diagnóstico por imagem , Neurorretroalimentação/métodos , Esquizofrenia/diagnóstico por imagem , Adulto , Mapeamento Encefálico/métodos , Feminino , Alucinações/terapia , Humanos , Masculino , Meditação/métodos , Meditação/psicologia , Pessoa de Meia-Idade , Estudo de Prova de Conceito , Descanso , Esquizofrenia/terapia
19.
Nat Commun ; 11(1): 246, 2020 01 14.
Artigo em Inglês | MEDLINE | ID: mdl-31937764

RESUMO

Synaptic dysfunction is hypothesised to play a key role in schizophrenia pathogenesis, but this has not been tested directly in vivo.  Here, we investigated synaptic vesicle glycoprotein 2A (SV2A) levels and their relationship to symptoms and structural brain measures using [11C]UCB-J positron emission tomography in 18 patients with schizophrenia and 18 controls. We found significant group and group-by-region interaction effects on volume of distribution (VT). [11C]UCB-J VT was significantly lower in the frontal and anterior cingulate cortices in schizophrenia with large effect sizes (Cohen's d = 0.8-0.9), but there was no significant difference in the hippocampus. We also investigated the effects of antipsychotic drug administration on SV2A levels in Sprague-Dawley rats using western blotting, [3H]UCB-J autoradiography and immunostaining with confocal microscopy, finding no significant effects on any measure. These findings indicate that there are lower synaptic terminal protein levels in schizophrenia in vivo and that antipsychotic drug exposure is unlikely to account for them.


Assuntos
Antipsicóticos/uso terapêutico , Encéfalo/metabolismo , Glicoproteínas de Membrana/metabolismo , Proteínas do Tecido Nervoso/metabolismo , Esquizofrenia/tratamento farmacológico , Esquizofrenia/metabolismo , Animais , Encéfalo/anatomia & histologia , Encéfalo/diagnóstico por imagem , Feminino , Lobo Frontal/diagnóstico por imagem , Lobo Frontal/metabolismo , Giro do Cíngulo/diagnóstico por imagem , Giro do Cíngulo/metabolismo , Humanos , Masculino , Especificidade de Órgãos , Tomografia por Emissão de Pósitrons , Piridinas/metabolismo , Pirrolidinonas/metabolismo , Ratos , Ratos Sprague-Dawley , Esquizofrenia/diagnóstico por imagem
20.
J Neurosci ; 40(6): 1265-1275, 2020 02 05.
Artigo em Inglês | MEDLINE | ID: mdl-31896669

RESUMO

Adolescence is a time of extensive neural restructuring, leaving one susceptible to atypical development. Although neural maturation in humans can be measured using functional and structural MRI, the subtle patterns associated with the initial stages of abnormal change may be difficult to identify, particularly at an individual level. Brain age prediction models may have utility in assessing brain development in an individualized manner, as deviations between chronological age and predicted brain age could reflect one's divergence from typical development. Here, we built a support vector regression model to summarize high-dimensional neuroimaging as an index of brain age in both sexes. Using structural and functional MRI data from two large pediatric datasets and a third clinical dataset, we produced and validated a two-dimensional neural maturation index (NMI) that characterizes typical brain maturation patterns and identifies those who deviate from this trajectory. Examination of brain signatures associated with NMI scores revealed that elevated scores were related to significantly lower gray matter volume and significantly higher white matter volume, particularly in high-order regions such as the prefrontal cortex. Additionally, those with higher NMI scores exhibited enhanced connectivity in several functional brain networks, including the default mode network. Analysis of data from a sample of male and female patients with schizophrenia revealed an association between advanced NMI scores and schizophrenia diagnosis in participants aged 16-22, confirming the NMI's utility as a marker of atypicality. Altogether, our findings support the NMI as an individualized, interpretable measure by which neural development in adolescence may be assessed.SIGNIFICANCE STATEMENT The substantial neural restructuring that occurs during adolescence increases one's vulnerability to aberration. A brain index that is capable of capturing one's conformance with typical development will allow for individualized assessment and enhance our understanding of typical and atypical development. In this analysis, we produce a neural maturation index (NMI) using support vector regression and a large pediatric sample. This index generalizes across multiple cohorts and shows potential in the identification of clinical groups. We also implement a novel method for examining the developmental trajectory through data-driven analysis. The signatures identified by the NMI reflect key stages of the extensive neural development that occurs during adolescence and support its utility as a metric of typical brain development.


Assuntos
Encéfalo/diagnóstico por imagem , Encéfalo/crescimento & desenvolvimento , Processamento de Imagem Assistida por Computador/métodos , Neuroimagem/métodos , Esquizofrenia/diagnóstico por imagem , Máquina de Vetores de Suporte , Adolescente , Criança , Feminino , Humanos , Imagem por Ressonância Magnética/métodos , Masculino , Adulto Jovem
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