Comparisons of Voxel-Based Morphometric Brain Volumes of Individuals with Methamphetamine-Induced Psychotic Disorder and Schizophrenia Spectrum Disorder and Healthy Controls

Exploring Schizophrenia Classification Through Multimodal MRI and Deep Graph Neural Networks: Unveiling Brain Region-Specific Weight Discrepancies and Their Association With Cell-Type Specific Transcriptomic Features

BACKGROUND AND HYPOTHESIS

Schizophrenia (SZ) is a prevalent mental disorder that imposes significant health burdens. Diagnostic accuracy remains challenging due to clinical subjectivity. To address this issue, we explore magnetic resonance imaging (MRI) as a tool to enhance SZ diagnosis and provide objective references and biomarkers. Using deep learning with graph convolution, we represent MRI data as graphs, aligning with brain structure, and improving feature extraction, and classification. Integration of multiple modalities is expected to enhance classification.

STUDY DESIGN

Our study enrolled 683 SZ patients and 606 healthy controls from 7 hospitals, collecting structural MRI and functional MRI data. Both data types were represented as graphs, processed by 2 graph attention networks, and fused for classification. Grad-CAM with graph convolution ensured interpretability, and partial least squares analyzed gene expression in brain regions.

STUDY RESULTS

Our method excelled in the classification task, achieving 83.32% accuracy, 83.41% sensitivity, and 83.20% specificity in 10-fold cross-validation, surpassing traditional methods. And our multimodal approach outperformed unimodal methods. Grad-CAM identified potential brain biomarkers consistent with gene analysis and prior research.

CONCLUSIONS

Our study demonstrates the effectiveness of deep learning with graph attention networks, surpassing previous SZ diagnostic methods. Multimodal MRI's superiority over unimodal MRI confirms our initial hypothesis. Identifying potential brain biomarkers alongside gene biomarkers holds promise for advancing objective SZ diagnosis and research in SZ.

Consistent brain structural abnormalities and multisite individualised classification of schizophrenia using deep neural networks

BACKGROUND

Previous analyses of grey and white matter volumes have reported that schizophrenia is associated with structural changes. Deep learning is a data-driven approach that can capture highly compact hierarchical non-linear relationships among high-dimensional features, and therefore can facilitate the development of clinical tools for making a more accurate and earlier diagnosis of schizophrenia.

AIMS

To identify consistent grey matter abnormalities in patients with schizophrenia, 662 people with schizophrenia and 613 healthy controls were recruited from eight centres across China, and the data from these independent sites were used to validate deep-learning classifiers.

METHOD

We used a prospective image-based meta-analysis of whole-brain voxel-based morphometry. We also automatically differentiated patients with schizophrenia from healthy controls using combined grey matter, white matter and cerebrospinal fluid volumetric features, incorporated a deep neural network approach on an individual basis, and tested the generalisability of the classification models using independent validation sites.

RESULTS

We found that statistically reliable schizophrenia-related grey matter abnormalities primarily occurred in regions that included the superior temporal gyrus extending to the temporal pole, insular cortex, orbital and middle frontal cortices, middle cingulum and thalamus. Evaluated using leave-one-site-out cross-validation, the performance of the classification of schizophrenia achieved by our findings from eight independent research sites were: accuracy, 77.19-85.74%; sensitivity, 75.31-89.29% and area under the receiver operating characteristic curve, 0.797-0.909.

CONCLUSIONS

These results suggest that, by using deep-learning techniques, multidimensional neuroanatomical changes in schizophrenia are capable of robustly discriminating patients with schizophrenia from healthy controls, findings which could facilitate clinical diagnosis and treatment in schizophrenia.

Common gray matter loss in the frontal cortex in patients with methamphetamine-associated psychosis and schizophrenia

BACKGROUND AND HYPOTHESIS

Methamphetamine (MA)-associated psychosis has become a public concern. However, its mechanism is not clear. Investigating similarities and differences between MA-associated psychosis and schizophrenia in brain alterations would be informative for neuropathology.

STUDY DESIGN

This study compared gray matter volumes of the brain across four participant groups: healthy controls (HC, n = 53), MA users without psychosis (MA, n = 22), patients with MA-associated psychosis (MAP, n = 34) and patients with schizophrenia (SCZ, n = 33). Clinical predictors of brain alterations, as well as association of brain alterations with psychotic symptoms and attention impairment were further investigated.

STUDY RESULTS

Compared with the HC, the MAP and the SCZ showed similar gray matter reductions in the frontal cortex, particularly in prefrontal areas. Moreover, a stepwise extension of gray matter reductions was exhibited across the MA - MAP - SCZ. Duration of abstinence was associated with regional volumetric recovery in the MAP, while this amendment in brain morphometry was not accompanied with symptom's remission. Illness duration of psychosis was among the predictive factors of regional gray matter reductions in both psychotic groups. Volume reductions were found to be associated with attention impairment in the SCZ, while this association was reversed in the MAP in frontal cortex.

CONCLUSIONS

This study suggested MA-associated psychosis and schizophrenia had common neuropathology in cognitive-related frontal cortices. A continuum of neuropathology between MA use and schizophrenia was tentatively implicated. Illness progressions and glial repairments could both play roles in neuropathological changes in MA-associated psychosis.

Prevention of relapse to methamphetamine self-administration by environmental enrichment: involvement of glucocorticoid receptors

RATIONALE

In rodents, environmental enrichment (EE) produces both preventive and curative effects on drug addiction, and this effect is believed to depend at least in part on EE's actions on the stress system.

OBJECTIVES

This study investigated whether exposure to EE during abstinence reduces methamphetamine seeking after extended self-administration. In addition, we investigated whether these effects are associated with alterations in the levels of glucocorticoid receptors (GR) in the brain and whether administration of GR antagonists blocks methamphetamine relapse.

METHODS

We allowed rats to self-administer methamphetamine for twenty 14-h sessions. After 3 weeks of abstinence either in standard (SE) or EE conditions, we measured methamphetamine seeking in a single 3-h session. Then, we used western blot techniques to measure GR levels in several brain areas. Finally, in an independent group of rats, after methamphetamine self-administration and abstinence in SE, we administered the GR antagonist mifepristone, and we investigated methamphetamine seeking.

RESULTS

Exposure to EE reduced methamphetamine seeking and reversed methamphetamine-induced increases in GR levels in the ventral and dorsal hippocampus. In addition, EE decreased GR levels in the amygdala in drug-naive animals, but this effect was prevented by previous exposure to methamphetamine. Administration of mifepristone significantly decreased methamphetamine seeking.

CONCLUSIONS

The anti-craving effects of EE are paralleled by restoration of methamphetamine-induced dysregulation of GR in the hippocampus. These results provide support for the hypothesis that the effect of EE on methamphetamine relapse is at least in part mediated by EE's action on the brain stress system.

Long non-coding RNA-associated competing endogenous RNA axes in the olfactory epithelium in schizophrenia: a bioinformatics analysis

The etiology of schizophrenia (SCZ), as a serious mental illness, is unknown. The significance of genetics in SCZ pathophysiology is yet unknown, and newly identified mechanisms involved in the regulation of gene transcription may be helpful in determining how these changes affect SCZ development and progression. In the current work, we used a bioinformatics approach to describe the role of long non-coding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs) in the olfactory epithelium (OE) samples in order to better understand the molecular regulatory processes implicated in SCZ disorders in living individuals. The Gene Expression Omnibus database was used to obtain the OE microarray dataset (GSE73129) from SCZ sufferers and control subjects, which contained information about both lncRNAs and mRNAs. The limma package of R software was used to identify the differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs). RNA interaction pairs were discovered using the Human MicroRNA Disease Database, DIANA-LncBase, and miRTarBase databases. In this study, the Pearson correlation coefficient was utilized to find positive correlations between DEmRNAs and DElncRNAs in the ceRNA network. Eventually, lncRNA-associated ceRNA axes were developed based on co-expression relations and DElncRNA-miRNA-DEmRNA interactions. This work found six potential DElncRNA-miRNA-DEmRNA loops in SCZ pathogenesis, including, SNTG2-AS1/hsa-miR-7-5p/SLC7A5, FLG-AS1/hsa-miR-34a-5p/FOSL1, LINC00960/hsa-miR-34a-5p/FOSL1, AQP4-AS1/hsa-miR-335-5p/FMN2, SOX2-OT/hsa-miR-24-3p/NOS3, and CASC2/hsa-miR-24-3p/NOS3. According to the findings, ceRNAs in OE might be promising research targets for studying SCZ molecular mechanisms. This could be a great opportunity to examine different aspects of neurodevelopment that may have been hampered early in SCZ patients.

Increased medical utilization and psychiatric comorbidity following a new diagnosis of methamphetamine use disorder

BACKGROUND

Evidence of patterns of medical utilization and distribution of comorbidities among individuals using methamphetamine remains limited.

OBJECTIVE

This study aims to investigate changes in medical utilization and comorbidities before and after a diagnosis of methamphetamine use disorder.

METHODS

A total of 3321 cases (79% were male) of methamphetamine use disorder between January 1, 1996, and December 31, 2012, were identified from Psychiatric Inpatient Medical Claims database in Taiwan. Information was collected on demographics, diagnoses, and medical utilizations. The date of newly diagnosed with methamphetamine use disorder was defined as the baseline. Mirror-image study design was used to compare changes in medical utilization and comorbidities between the pre-baseline period (within 1 year before diagnosis) and the post-baseline period (within 1 year after diagnosis). Conditional logistic regression was used to estimate changes in medical utilization and comorbidities.

RESULTS

Most cases (77%) were first identified in a psychiatric department. There is a significant increase (P < .001) in psychiatric admission (odds ratio[OR] = 2.19), psychiatric emergency visits (OR = 1.31), and psychiatric outpatient visits (OR = 1.15) after diagnosis. Multivariable analysis revealed significantly increased risks (P < .001) of non-methamphetamine drug induced mental disorders (adjusted OR[aOR] = 29.47), schizophrenia (aOR = 2.62), bipolar disorder (aOR = 2.14), organic mental disorder (aOR = 1.82), and upper respiratory tract infection (aOR = 2.03) after diagnosis.

CONCLUSIONS

We found significant increases of medical utilization and psychiatric comorbidities after diagnosed with methamphetamine use disorder. These findings may reflect the problem of delayed diagnosis and treatment. Enhancement of early identification of methamphetamine use disorder in general practice is required for early intervention and decreased subsequent morbidities.

Brain morphometry in adults with gambling disorder

Little is known regarding the brain substrates of Gambling Disorder, including surface brain morphometry, and whether these are linked to the clinical profile. A better understanding of the brain substrates will likely help determine targets to treat patients. Hence, the aim of this study was two-fold, that is to examine surface-based morphometry in 17 patients with gambling disorder as compared to norms of healthy individuals (2713 and 2790 subjects for cortical and subcortical anatomical scans, respectively) and to assess the clinical relevance of morphometry in patients with Gambling Disorder. This study measured brain volume, surface and thickness in Gambling Disorder. We compared these measures to those of a normative database that controlled for factors such as age and sex. We also tested for correlations with gambling-related behaviors, such as gambling severity and duration, impulsivity, and depressive symptoms (assessed using the South Oaks Gambling Screen, years of gambling, Barratt Impulsiveness Scale, and Beck Depression Inventory, respectively). Patients displayed thinner prefrontal and parietal cortices, greater volume and thickness of the occipital and the entorhinal cortices, and greater volume of subcortical regions as compared to the norms of healthy individuals. There were positive correlations between surface area of occipital regions and depressive symptoms. This work contributes to better characterize the brain substrates of Gambling Disorder, which appear to resemble those of substance use disorders and Internet Gaming Disorder.

Methamphetamine exacerbates pathophysiology of traumatic brain injury at high altitude. Neuroprotective effects of nanodelivery of a potent antioxidant compound H-290/51

Military personnel are often exposed to high altitude (HA, ca. 4500-5000m) for combat operations associated with neurological dysfunctions. HA is a severe stressful situation and people frequently use methamphetamine (METH) or other psychostimulants to cope stress. Since military personnel are prone to different kinds of traumatic brain injury (TBI), in this review we discuss possible effects of METH on concussive head injury (CHI) at HA based on our own observations. METH exposure at HA exacerbates pathophysiology of CHI as compared to normobaric laboratory environment comparable to sea level. Increased blood-brain barrier (BBB) breakdown, edema formation and reductions in the cerebral blood flow (CBF) following CHI were exacerbated by METH intoxication at HA. Damage to cerebral microvasculature and expression of beta catenin was also exacerbated following CHI in METH treated group at HA. TiO2-nanowired delivery of H-290/51 (150mg/kg, i.p.), a potent chain-breaking antioxidant significantly enhanced CBF and reduced BBB breakdown, edema formation, beta catenin expression and brain pathology in METH exposed rats after CHI at HA. These observations are the first to point out that METH exposure in CHI exacerbated brain pathology at HA and this appears to be related with greater production of oxidative stress induced brain pathology, not reported earlier.

A web-based adapted physical activity program (e-APA) versus health education program (e-HE) in patients with schizophrenia and healthy volunteers: study protocol for a randomized controlled trial (PEPSY V@Si)

Patients with schizophrenia (SZ) have a high level of cardiovascular morbidity and some clinical symptoms of illness remain resistant to pharmacological approaches. A large number of studies support the effectiveness of physical activity (PA) in SZ. The aims of this trial is to assess the effects of a remote, web-based adapted PA program (e-APA) compared to a health education program (e-HE) on brain plasticity in SZ and healthy volunteers (HV) and on psychiatric, neurocognitive, circadian and physical variables. The study is an interventional, multicenter, randomized open-label trial. Forty-two SZ will be randomized to either the active group (e-APA, N = 21) or nonactive group (e-HE, N = 21), and 21 HV will be matched to SZ according to age, gender, and level of PA in both e-APA and e-HE groups. Interventions will consist of 32 sessions (2 × 60 min/week, for 16 weeks) via supervised home-based videoconferencing. Cerebral magnetic resonance imaging, psychiatric symptoms, neurocognitive and circadian rhythms assessments as well as physical tests and biological analyses will be assessed at baseline and 16 weeks after the intervention. To our knowledge, this is the first study aiming to evaluate the efficacy of APA delivered by supervised home-based videoconferencing in SZ. Moreover, using multimodal MRI, this study could clarify the pathophysiological mechanisms underlying the efficacy of APA. Finally, this innovative approach might also increase participation in long-term PA since PA-based programs are known to have low adherence and early dropout. Trial registration: ClinicalTrials.gov identifier: NCT03261817. Registered on 16 August 2017.