Clinical characteristics and potential association to Parkinson's disease and dementia with Lewy bodies in patients with major depressive disorder who received maintenance electroconvulsive therapy: a retrospective chart review study.

BACKGROUND: Maintaining remission after electroconvulsive therapy (ECT) is clinically relevant in patients with depression, and maintenance ECT has been introduced in patients who fail to maintain remission after ECT. However, the clinical characteristics and biological background of patients who receive maintenance ECT are poorly understood. Thus, this study aimed to examine the clinical background of patients who underwent maintenance ECT. METHODS: Patients with major depressive disorder who underwent ECT followed by maintenance ECT (mECT group) and those who did not (acute ECT [aECT] group) were included. Clinical characteristics, including the results of neuroimaging examinations for Parkinson's disease (PD) and dementia with Levy body (DLB) such as myocardial 123I-metaiodobenzylguanidine (MIBG) scintigraphy and dopamine transporter imaging single-photon emission computerized tomography (DaT-SPECT), were compared between the groups. RESULTS: In total, 13 and 146 patients were included in the mECT and aECT groups, respectively. Compared to the aECT group, the mECT group showed a significantly higher prevalence of melancholic features (92.3% vs. 27.4%, p < 0.001) and catatonic features (46.2% vs. 9.6%, p = 0.002). Overall, 8 of the 13 patients in the mECT group and 22 of the 146 patients in the aECT group underwent neuroimaging examinations for PD/DLB. The rate of patients examined is significantly higher in the mECT group than in the aECT group (61.5% vs. 11.2%, p < 0.001). Among the groups examined, 7/8 patients in the mECT group and 16/22 patients in the aECT group showed relevant neuroimaging findings for PD/DLB; the positive rate was not significantly different between the two groups (87.5% vs. 72.7%, p = 0.638). CONCLUSIONS: Patients who receive acute and maintenance ECT may have underlying neurodegenerative diseases, including PD/DLB. Investigating the neurobiology of patients who receive maintenance ECT is important for developing appropriate treatments for depression.

Intergenerational concordance of brain structure between depressed mothers and their never-depressed daughters.

AIM: Parents have significant genetic and environmental influences, which are known as intergenerational effects, on the cognition, behavior, and brain of their offspring. These intergenerational effects are observed in patients with mood disorders, with a particularly strong association of depression between mothers and daughters. The main purpose of our study was to investigate female-specific intergenerational transmission patterns in the human brain among patients with depression and their never-depressed offspring. METHODS: We recruited 78 participants from 34 families, which included remitted parents with a history of depression and their never-depressed biological offspring. We used source-based and surface-based morphometry analyses of magnetic resonance imaging data to examine the degree of associations in brain structure between four types of parent-offspring dyads (i.e. mother-daughter, mother-son, father-daughter, and father-son). RESULTS: Using independent component analysis, we found a significant positive correlation of gray matter structure between exclusively the mother-daughter dyads within brain regions located in the default mode and central executive networks, such as the bilateral anterior cingulate cortex, posterior cingulate cortex, precuneus, middle frontal gyrus, middle temporal gyrus, superior parietal lobule, and left angular gyrus. These similar observations were not identified in other three parent-offspring dyads. CONCLUSIONS: The current study provides biological evidence for greater vulnerability of daughters, but not sons, in developing depression whose mothers have a history of depression. Our findings extend our knowledge on the pathophysiology of major psychiatric conditions that show sex biases and may contribute to the development of novel interventions targeting high-risk individuals.

Individual Prediction of Remission Based on Clinical Features Following Electroconvulsive Therapy: A Machine Learning Approach.

Objective: Previous prediction models for electroconvulsive therapy (ECT) responses have predominantly been based on neuroimaging data, which has precluded widespread application for severe cases in real-world clinical settings. The aims of this study were (1) to build a clinically useful prediction model for ECT remission based solely on clinical information and (2) to identify influential features in the prediction model.Methods: We conducted a retrospective chart review to collect data (registered between April 2012 and March 2019) from individuals with depression (unipolar major depressive disorder or bipolar disorder) diagnosed via DSM-IV-TR criteria who received ECT at Keio University Hospital. Clinical characteristics were used as candidate features. A light gradient boosting machine was used for prediction, and 5-fold cross-validation was performed to validate our prediction model.Results: In total, 177 patients with depression underwent ECT during the study period. The remission rate was 63%. Our model predicted individual patient outcomes with 71% accuracy (sensitivity, 86%; specificity, 46%). A shorter duration of the current episodes, lower baseline severity, higher dose of antidepressant medications before ECT, and lower body mass index were identified as important features for predicting remission following ECT.Conclusions: We developed a prediction model for ECT remission based solely on clinical information. Our prediction model demonstrated accuracy comparable to that in previous reports. Our model suggests that introducing ECT earlier in the treatment course may contribute to improvements in clinical outcomes.

Impact of Sevoflurane and Thiopental Used Over the Course of Electroconvulsive Therapy: Propensity Score Matching Analysis.

Objective: Although anesthetics play an important role in electroconvulsive therapy (ECT), the clinical efficacy and seizure adequacy of sevoflurane in the course of ECT remain unclear. The purpose of this study was to examine the clinical efficacy and seizure adequacy of sevoflurane, compared with those of thiopental, in the course of ECT in patients with mood disorders. Methods: We conducted a retrospective chart review. Patients who underwent a course of ECT and received sevoflurane (n = 26) or thiopental (n = 26) were included. Factors associated with ECT and treatment outcomes were compared between the two groups using propensity score (PS) matching. Between-group differences were examined using an independent t-test for continuous variables and a χ2-test for categorical variables. Results: Patients who received sevoflurane needed more stimulations (sevoflurane: 13.2 ± 4 times, thiopental: 10.0 ± 2.5 times, df = 51, p = 0.001) and sessions (sevoflurane: 10.0 ± 2.1 times, thiopental: 8.4 ± 2.1 times, df = 51, p = 0.01) and had more inadequate seizures (sevoflurane: 5 ± 3.9 times, thiopental: 2.7 ± 2.7 times, df = 51, p = 0.015). Remission and response rates were similar in both groups. Conclusion: The present findings indicate that sevoflurane should be used with caution in ECT and only when the clinical rationale is clear.

Evaluation of [18F]PI-2620, a second-generation selective tau tracer, for assessing four-repeat tauopathies.

Tau aggregates represent a key pathologic feature of Alzheimer's disease and other neurodegenerative diseases. Recently, PET probes have been developed for in vivo detection of tau accumulation; however, they are limited because of off-target binding and a reduced ability to detect tau in non-Alzheimer's disease tauopathies. The novel tau PET tracer, [18F]PI-2620, has a high binding affinity and specificity for aggregated tau; therefore, it was hypothesized to have desirable properties for the visualization of tau accumulation in Alzheimer's disease and non-Alzheimer's disease tauopathies. To assess the ability of [18F]PI-2620 to detect regional tau burden in non-Alzheimer's disease tauopathies compared with Alzheimer's disease, patients with progressive supranuclear palsy (n = 3), corticobasal syndrome (n = 2), corticobasal degeneration (n = 1) or Alzheimer's disease (n = 8), and healthy controls (n = 7) were recruited. All participants underwent MRI, amyloid ß assessment and [18F]PI-2620 PET (Image acquisition at 60-90 min post-injection). Cortical and subcortical tau accumulations were assessed by calculating standardized uptake value ratios using [18F]PI-2620 PET. For pathologic validation, tau pathology was assessed using tau immunohistochemistry and compared with [18F]PI-2620 retention in an autopsied case of corticobasal degeneration. In Alzheimer's disease, focal retention of [18F]PI-2620 was evident in the temporal and parietal lobes, precuneus, and cingulate cortex. Standardized uptake value ratio analyses revealed that patients with non-Alzheimer's disease tauopathies had elevated [18F]PI-2620 uptake only in the globus pallidus, as compared to patients with Alzheimer's disease, but not healthy controls. A head-to-head comparison of [18F]PI-2620 and [18F]PM-PBB3, another tau PET probe for possibly visualizing the four-repeat tau pathogenesis in non-Alzheimer's disease, revealed different retention patterns in one subject with progressive supranuclear palsy. Imaging-pathology correlation analysis of the autopsied patient with corticobasal degeneration revealed no significant correlation between [18F]PI-2620 retention in vivo. High [18F]PI-2620 uptake at 60-90 min post-injection in the globus pallidus may be a sign of neurodegeneration in four-repeat tauopathy, but not necessarily practical for diagnosis of non-Alzheimer's disease tauopathies. Collectively, this tracer is a promising tool to detect Alzheimer's disease-tau aggregation. However, late acquisition PET images of [18F]PI-2620 may have limited utility for reliable detection of four-repeat tauopathy because of lack of correlation between post-mortem tau pathology and different retention pattern than the non-Alzheimer's disease-detectable tau radiotracer, [18F]PM-PBB3. A recent study reported that [18F]PI-2620 tracer kinetics curves in four-repeat tauopathies peak earlier (within 30 min) than Alzheimer's disease; therefore, further studies are needed to determine appropriate PET acquisition times that depend on the respective interest regions and diseases.

Effect of different parietal hypoperfusion on neuropsychological characteristics in mild cognitive impairment.

BACKGROUND: In early-stage amnestic mild cognitive impairment (aMCI), differences in the neuropsychological characteristics of each individual are subtle. We investigated differences in neuropsychological performance between aMCI patients with and without hypoperfusion in the medial parietal regions (MP). We further compared patients with hypoperfusion in the left and right lateral parietal regions. METHODS: We examined 165 aMCI patients (mean age: 76.8 ± 5.5 years; 87 women) who had undergone neuropsychological measurement and single-photon emission computed tomography. We classified participants into two subgroups with and without hypoperfusion: MP hypoperfusion (+) and MP hypoperfusion (-); classification was based on Z-scores (calculated by three-dimensional stereotactic surface projection technique) of three regions of interest in the parietal lobes (i.e. MP regions including posterior cingulate cortex and precuneus and left and right inferior parietal lobules (lateral parietal regions)). The MP hypoperfusion (-) group was classified into left lateral parietal hypoperfusion (+) and right lateral parietal hypoperfusion (+) subgroups. We performed either univariate or multivariate ancova to compare neuropsychological scores for continuous variables between groups and examined dichotomous variables using χ2 tests. RESULTS: In the overall aMCI sample, scores on logical memory delayed recall in the MP hypoperfusion (+) group were significantly lower than those in the MP hypoperfusion (-) group. Total scores on Rey-Osterrieth Complex Figure Test delayed recall were also marginally lower in the MP hypoperfusion (+) group than in the MP hypoperfusion (-) group. Comparisons of neuropsychological test scores between the left and right lateral parietal hypoperfusion (+) groups revealed no significant differences. CONCLUSIONS: The present findings suggest that MP hypoperfusion (+) is associated with more robust memory deficits than MP hypoperfusion (-). Combining neuropsychological tests and single-photon emission computed tomography findings may be useful for early detection of cognitive decline in aMCI.

Electroconvulsive Therapy for Patients With Depression Who Lack Capacity for Consent: Doing Good and Doing No Harm.

OBJECTIVE: Electroconvulsive therapy (ECT) is provided in real-world clinical settings for patients lacking capacity for consent. The aim of this study was to investigate the clinical characteristics and clinical effectiveness of ECT in this population. METHODS: A retrospective chart review was conducted to collect data from patients who received ECT to treat their depressive episodes between April 2012 and March 2019. Differences in clinical characteristics and short-/long-term clinical outcomes between patients who received ECT with their relatives' consent and patients who received ECT by their own consent were examined. The short-/long-term clinical outcomes were determined by clinical global impression scores and readmission rate, respectively. RESULTS: Of 168 patients with depressive episodes, 34 (20.2%) received ECT with their relatives' consent. Those patients were older, had lower body mass index, and had shorter episode duration. They also exhibited more frequent psychotic, melancholic, and catatonic features. The main indication for ECT in this population was the need for rapid recovery. Patients lacking capacity for consent showed similar remission (61.8%) and response (82.4%) rates to those with capacity for consent. Readmission rate was not significantly different between groups. CONCLUSIONS: There were no significant differences in short-/long-term ECT effectiveness between patients with/without capacity for consent. Electroconvulsive therapy is the only established and effective treatment in clinical settings for the most severe cases, wherein patients are incapable of giving consent but need rapid recovery. A general rejection of this practice due to concerns surrounding consent may be unethical under the ethical principles of medical care.

Association of electroconvulsive therapy-induced structural plasticity with clinical remission.

BACKGROUND: Electroconvulsive therapy (ECT) is the most effective treatment for severe depression. Recent neuroimaging studies have consistently reported that ECT induces volume increases in widely distributed brain regions. However, it still remains unclear about ECT-induced volume changes associated with clinical improvement. METHODS: Longitudinal assessments of structural magnetic resonance imaging were conducted in 48 participants. Twenty-seven elderly melancholic depressed individuals (mean 67.5 ± 8.1 years old; 19 female) were scanned before (TP1) and after (TP2) ECT. Twenty-one healthy controls were also scanned twice. Whole-brain gray matter volume (GMV) was analyzed via group (remitters, nonremitters, and controls) by time (TP1 and TP2) analysis of covariance to identify ECT-related GMV changes and GMV changes specific to remitters. Within-subject and between-subjects correlation analyses were conducted to investigate the associations between clinical improvement and GMV changes. Depressive symptoms were evaluated using the 17-item Hamilton Depression Rating Scale (HAM-D), and remission was defined as HAM-D total score ≤ 7. RESULTS: Bilateral ECT increased GMV in multiple brain regions bilaterally regardless of clinical improvement. Remitters showed a larger GMV increase in the right-lateralized frontolimbic brain regions compared to nonremitters and healthy controls. GMV changes in the right hippocampus/amygdala and right middle frontal gyrus showed correlations with clinical improvement in within-/between-subjects correlation analyses. CONCLUSIONS: ECT-induced GMV increase in the right frontolimbic regions was associated with clinical remission.

Similar Hemodynamic Signal Patterns Between Compact NIRS and 52-Channel NIRS During a Verbal Fluency Task.

Multichannel near-infrared spectroscopy (NIRS), including 52-channel NIRS (52ch-NIRS), has been used increasingly to capture hemodynamic changes in the brain because of its safety, low cost, portability, and high temporal resolution. However, optode caps might cause pain and motion artifacts if worn for extended periods of time because of the weight of the cables and the pressure of the optodes on the scalp. Recently, a small NIRS apparatus called compact NIRS (cNIRS) has been developed, and uses only a few flexible sensors. Because this device is expected to be more suitable than 52ch-NIRS in the clinical practice for patients with children or psychiatric conditions, we tested whether the two systems were clinically comparable. Specifically, we evaluated the correlation between patterns of hemodynamic changes generated by 52ch-NIRS and cNIRS in the frontopolar region. We scanned 14 healthy adults with 52ch-NIRS and cNIRS, and measured activation patterns of oxygenated-hemoglobin [oxy-Hb] and deoxygenated-hemoglobin [deoxy-Hb] in the frontal pole while they performed a verbal fluency task. We performed detailed temporal domain comparisons of time-course patterns between the two NIRS-based signals. We found that 52ch-NIRS and cNIRS showed significant correlations in [oxy-Hb] and [deoxy-Hb] time-course changes in numerous channels. Our findings indicate that cNIRS and 52ch-NIRS capture similar task-dependent hemodynamic changes due to metabolic demand, which supports the validity of cNIRS measurement techniques. Therefore, this small device has a strong potential for clinical application with infants and children, as well as for use in the rehabilitation or treatment of patients with psychiatric disorders using biofeedback.

Comparison of White Matter Structure of Drug-Naïve Patients With Bipolar Disorder and Major Depressive Disorder Using Diffusion Tensor Tractography.

BACKGROUND: The presence of microstructural white matter (WM) abnormalities in individuals with bipolar disorder (BD) has previously been reported. However, the interpretation of data is challenging because pharmacological treatment has a potential effect on WM integrity. To date, no study has compared the differences in WM structure among drug-naïve BD patients, drug-naïve major depression disorder (MDD) patients, and healthy controls (HC) using the visual evaluation method of diffusion tensor tractography (DTT). METHODS: This retrospective study included 12 drug-naïve patients with BD, 15 drug-naïve patients with MDD, and 27 age- and sex-matched HC individuals. Visual evaluation, fractional anisotropy (FA), and apparent diffusion coefficient (ADC) were analysed in the anterior thalamic radiation (ATR) as a tract of interest using the optimal follow-up truncation threshold. They were also analysed in the cingulate fasciculus, superior longitudinal fasciculus, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, uncinate fasciculus, and fornix. RESULTS: No significant differences were found in the FA or ADC of any tract. However, visual evaluation revealed poorer depiction of ATR in patients with BD than in patients with MDD and HC individuals (p = 0.004). Our post-hoc analysis showed a significant difference between BD and HC patients (p = 0.018). CONCLUSIONS: The visual evaluation method of DTT revealed poor depiction of ATR in patients with BD compared with HC individuals and MDD patients, suggesting microstructural WM abnormalities of ATR in BD.

Neuronal network mechanisms associated with depressive symptom improvement following electroconvulsive therapy.

BACKGROUND: Electroconvulsive therapy (ECT) is the most effective antidepressant treatment for severe depression. Although recent structural magnetic resonance imaging (MRI) studies have consistently reported ECT-induced hippocampal volume increases, most studies did not find the association of the hippocampal volume changes with clinical improvement. To understand the underlying mechanisms of ECT action, we aimed to identify the longitudinal effects of ECT on hippocampal functional connectivity (FC) and their associations with clinical improvement. METHODS: Resting-state functional MRI was acquired before and after bilateral ECT in 27 depressed individuals. A priori hippocampal seed-based FC analysis and a data-driven multivoxel pattern analysis (MVPA) were conducted to investigate FC changes associated with clinical improvement. The statistical threshold was set at cluster-level false discovery rate-corrected p < 0.05. RESULTS: Depressive symptom improvement after ECT was positively associated with the change in the right hippocampus-ventromedial prefrontal cortex FC, and negatively associated with the right hippocampus-superior frontal gyrus FC. MVPA confirmed the results of hippocampal seed-based analyses and identified the following additional clusters associated with clinical improvement following ECT: the thalamus, the sensorimotor cortex, and the precuneus. CONCLUSIONS: ECT-induced change in the right frontotemporal connectivity and thalamocortical connectivity, and changes in the nodes of the default mode network were associated with clinical improvement. Modulation of these networks may explain the underlying mechanisms by which ECT exert its potent and rapid antidepressant effect.

Regional Gray Matter Volume Identifies High Risk of Unsafe Driving in Healthy Older People.

In developed countries, the number of traffic accidents caused by older drivers is increasing. Approximately half of the older drivers who cause fatal accidents are cognitively normal. Thus, it is important to identify older drivers who are cognitively normal but at high risk of causing fatal traffic accidents. However, no standardized method for assessing the driving ability of older drivers has been established. We aimed to establish an objective assessment of driving ability and to clarify the neural basis of unsafe driving in healthy older people. We enrolled 32 healthy older individuals aged over 65 years and classified unsafe drivers using an on-road driving test. We then utilized a machine learning approach to distinguish unsafe drivers from safe drivers based on clinical features and gray matter volume data. Twenty-one participants were classified as safe drivers and 11 participants as unsafe drivers. A linear support vector machine classifier successfully distinguished unsafe drivers from safe drivers with 87.5% accuracy (sensitivity of 63.6% and specificity of 100%). Five parameters (age and gray matter volume in four cortical regions, including the left superior part of the precentral sulcus, the left sulcus intermedius primus [of Jensen], the right orbital part of the inferior frontal gyrus, and the right superior frontal sulcus), were consistently selected as features for the final classification model. Our findings indicate that the cortical regions implicated in voluntary orienting of attention, decision making, and working memory may constitute the essential neural basis of driving behavior.

Machine-learning approach to predict on-road driving ability in healthy older people.

AIM: In Japan, fatal traffic accidents due to older drivers are on the rise. Considering that approximately half the older drivers who have caused fatal accidents are cognitively normal healthy people, it has been required to detect older drivers who are cognitively normal but at high risk of having fatal traffic accidents. However, a standardized method for assessing the driving ability of older drivers has not yet been established. We thus aimed to identify a new sensing method for the evaluation of the on-road driving ability of healthy older people on the basis of vehicle behaviors. METHODS: We enrolled 33 healthy older individuals aged over 65 years and utilized a machine-learning approach to dissociate unsafe drivers from safe drivers based on cognitive assessments and a functional visual acuity test. RESULTS: The linear support vector machine classifier successfully dissociated unsafe drivers from safe drivers with accuracy of 84.8% (sensitivity of 66.7% and specificity of 95.2%). Five clinical parameters, namely age, the first trial of the Rey Auditory Verbal Learning Test immediate recall, the delayed recall of the Rey-Osterrieth Complex Figure Test, the result of the free-drawn Clock Drawing Test, and maximal visual acuity, were consistently selected as essential features for the best classification model. CONCLUSION: Our findings improve our understanding of clinical risk factors leading to unsafe driving and may provide insight into a new intervention that prevents fatal traffic accidents caused by healthy older people.

Predicting Individual Remission After Electroconvulsive Therapy Based on Structural Magnetic Resonance Imaging: A Machine Learning Approach.

OBJECTIVE: To identify important clinical or imaging features predictive of an individual's response to electroconvulsive therapy (ECT) by utilizing a machine learning approach. METHODS: Twenty-seven depressed patients who received ECT were recruited. Clinical demographics and pretreatment structural magnetic resonance imaging (MRI) data were used as candidate features to build models to predict remission and post-ECT Hamilton Depression Rating Scale scores. Support vector machine and support vector regression with elastic-net regularization were used to build models using (i) only clinical features, (ii) only MRI features, and (iii) both clinical and MRI features. Consistently selected features across all individuals were identified through leave-one-out cross-validation. RESULTS: Compared with models that include only clinical variables, the models including MRI data improved the prediction of ECT remission: the prediction accuracy improved from 70% to 93%. Features selected consistently across all individuals included volumes in the gyrus rectus, the right anterior lateral temporal lobe, the cuneus, and the third ventricle, as well as 2 clinical features: psychotic features and family history of mood disorder. CONCLUSIONS: Pretreatment structural MRI data improved the individual predictive accuracy of ECT remission, and only a small subset of features was important for prediction.

Disclosure of Amyloid Status for Risk of Alzheimer Disease to Cognitively Normal Research Participants With Subjective Cognitive Decline: A Longitudinal Study.

This study aimed to investigate the long-term impacts of disclosing amyloid status for a risk of Alzheimer disease (AD) to cognitively normal research participants with subjective cognitive decline (SCD), which represents an initial manifestation of AD. Forty-two participants were classified as the amyloid-positive (n = 10) or amyloid-negative (n = 32) groups. We assessed symptoms of anxiety, depression, and test-related distress at 6, 24, and 52 weeks after results disclosure. No difference was found over time in anxiety, depression, and test-related distress in either group. Although no significant differences were observed between groups in anxiety or depression, the amyloid-negative group had a significantly higher level of test-related distress than the amyloid-positive group at 52 weeks. Disclosing amyloid status to cognitively healthy research participants with SCD did not cause significant long-term psychological risks. However, a theoretical spectrum of subjective concern may exist about cognitive decline in amyloid-negative individuals.

Widespread White Matter Aberrations Are Associated with Phonemic Verbal Fluency Impairment in Chronic Traumatic Brain Injury.

Microstructural white matter (WM) disruption and resulting abnormal structural connectivity form a potential underlying pathology in traumatic brain injury (TBI). Herein, to determine the potential mechanism of cognitive deterioration in TBI, we examined the association of damage to specific WM tracts with cognitive function in TBI patients. We recruited 18 individuals with mild-to-moderate/severe TBI in the chronic phase and 17 age-matched controls. We determined the pattern of WM aberrations in TBI using tract-based spatial statistics (TBSS) and then examined the relationship between cognitive impairment and WM damage using the threshold-free cluster enhancement correction in TBSS. TBSS analysis showed that TBI patients exhibited WM aberrations in a wide range of brain regions. In the majority of these regions, lower fractional anisotropy (FA) largely overlapped with increased radial diffusivity, but not with axial diffusivity. Further, voxel-wise correction in TBSS demonstrated that higher FA values were associated with better performance in the phonemic verbal fluency task (VFT) in widespread WM regions, but not with the semantic VFT. Despite variation in the magnitude and location of brain injury between individual cases, chronic TBI patients exhibited widespread WM aberrations. We confirmed the findings of previous studies that WM integrity is lower across the spectrum of TBI severity in chronic subjects compared to controls. Further, phonemic VFT may be a more sensitive cognitive measure of executive dysfunction associated with WM aberrations in TBI compared with semantic VFT.

In Vitro Modeling of the Bipolar Disorder and Schizophrenia Using Patient-Derived Induced Pluripotent Stem Cells with Copy Number Variations of PCDH15 and RELN.

Bipolar disorder (BP) and schizophrenia (SCZ) are major psychiatric disorders, but the molecular mechanisms underlying the complicated pathologies of these disorders remain unclear. It is difficult to establish adequate in vitro models for pathological analysis because of the heterogeneity of these disorders. In the present study, to recapitulate the pathologies of these disorders in vitro, we established in vitro models by differentiating mature neurons from human induced pluripotent stem cells (hiPSCs) derived from BP and SCZ patient with contributive copy number variations, as follows: two BP patients with PCDH15 deletion and one SCZ patient with RELN deletion. Glutamatergic neurons and GABAergic neurons were induced from hiPSCs under optimized conditions. Both types of induced neurons from both hiPSCs exhibited similar phenotypes of MAP2 (microtubule-associated protein 2)-positive dendrite shortening and decreasing synapse numbers. Additionally, we analyzed isogenic PCDH15- or RELN-deleted cells. The dendrite and synapse phenotypes of isogenic neurons were partially similar to those of patient-derived neurons. These results suggest that the observed phenotypes are general phenotypes of psychiatric disorders, and our in vitro models using hiPSC-based technology may be suitable for analysis of the pathologies of psychiatric disorders.

Thalamic volume, resting-state activity, and their association with the efficacy of electroconvulsive therapy.

Electroconvulsive therapy (ECT) is the most effective antidepressant treatment. Biological predictors of clinical outcome to ECT are valuable. We aimed to examine multimodal magnetic resonance imaging (MRI) data that correlates to the efficacy of ECT. Structural and resting-state functional MRI data were acquired from 46 individuals (25 depressed individuals who received ECT, and 21 healthy controls). Whole-brain grey matter volume (GMV) and fractional amplitude of low frequency fluctuations (fALFF) were investigated to identify brain regions associated with post-ECT Hamilton Depression Rating Scale (HAM-D) total scores. GMV and fALFF values were compared with those in healthy controls using analysis of covariance (ANCOVA). Remission was defined by HAM-D ≤7. A multiple regression analysis revealed that pretreatment smaller GMV in the left thalamus was associated with worse response to ECT (i.e. higher post-ECT HAM-D). Pretreatment higher fALFF in the right anterior insula, and lower fALFF in the left thalamus and the cerebellum were associated with worse outcomes. The left thalamus was identified in both GMV and fALFF analyses. Nonremitters showed significantly smaller thalamic GMV compared to remitters and controls. We found that pretreatment thalamic volume and resting-state activity were associated with the efficacy of ECT. Our results highlight the importance of the thalamus as a possible biological predictor and its role in the underlying mechanisms of ECT action.

Cortical surface architecture endophenotype and correlates of clinical diagnosis of autism spectrum disorder.

AIM: Prior structural magnetic resonance imaging studies demonstrated atypical gray matter characteristics in siblings of individuals with autism spectrum disorder (ASD). However, they did not clarify which aspect of gray matter is related to the endophenotype (i.e., genetic vulnerability) of ASD. Further, because they did not enroll siblings of typically developing (TD) people, they may have underestimated the difference between individuals with ASD and their unaffected siblings. The current study aimed to address these gaps. METHODS: We recruited 30 pairs of adult male siblings (15 pairs with an ASD endophenotype and 15 pairs without) and focused on four gray matter parameters: cortical volume and three surface-based parameters (cortical thickness, fractal dimension, and sulcal depth [SD]). First, we sought to identify a pattern of an ASD endophenotype, comparing the four parameters. Then, we compared individuals with ASD and their unaffected siblings in the cortical parameters to identify neural correlates for the clinical diagnosis accounting for the difference between TD siblings. RESULTS: A sparse logistic regression with a leave-one-pair-out cross-validation showed the SD as having the highest accuracy for the identification of an ASD endophenotype (73.3%) compared with the other three parameters. A bootstrapping analysis accounting for the difference in the SD between TD siblings showed a significantly large difference between individuals with ASD and their unaffected siblings in six out of 68 regions of interest. CONCLUSION: This proof-of-concept study suggests that an ASD endophenotype emerges in the SD and that neural bases for ASD diagnosis can be discerned from the endophenotype when accounting for the difference between TD siblings.

Brain functional alterations observed 4-weekly in major depressive disorder following antidepressant treatment.

BACKGROUND: Major depressive disorder (MDD) is a heterogeneous condition. Identifying the brain responses to antidepressant treatment is of particular interest as these may represent potential neural networks related to treatment response, forming one aspect of the biological markers of MDD. Near-infrared spectroscopy (NIRS) is suitable for repeated measurements with short intervals because of its noninvasiveness, and can provide detailed time courses of functional alterations in prefrontal regions. METHODS: We conducted a 12-week longitudinal study to explore prefrontal hemodynamic changes at 4-week intervals following sertraline treatment in 11 medication-naïve participants with MDD using 52-channel NIRS. RESULTS: While all participants achieved remission after treatment, intra-class correlation coefficient of oxygenated hemoglobin [oxy-Hb] values throughout the 12-week observation was moderate at the spatially and temporally contiguous cluster located in the left inferior frontal and temporal gyri. There was a significant negative correlation between mean [oxy-Hb] values in the significant cluster at 4 weeks and changes in Hamilton Rating Scale for Depression total score from 4 to 8 weeks (r = -0.73, P = 0.011) and from 4 to 12 weeks (r = -0.63, P = 0.039). LIMITATIONS: Without healthy controls for comparison, we were unable to fully evaluate whether improvement of [oxy-Hb] activations after treatment in MDD reached normal levels or not. CONCLUSION: Our NIRS findings of detailed prefrontal hemodynamic alterations over short interval observations such as 4 weeks may have revealed potential trait marker for MDD and biological maker for predicting clinical response to sertraline treatment in MDD.