Copy number variations in RNF216 and postsynaptic membrane-associated genes are associated with bipolar disorder: a case-control study in the Japanese population.

AIM: Bipolar disorder (BD) is a common psychiatric disorder characterized by alterations between manic/hypomanic and depressive states. Rare pathogenic copy number variations (CNVs) that overlap with exons of synaptic genes have been associated with BD. However, no study has comprehensively explored CNVs in synaptic genes associated with BD. Here, we evaluated the relationship between BD and rare CNVs that overlap with synaptic genes, not limited to exons, in the Japanese population. METHODS: Using array comparative genome hybridization, we detected CNVs in 1839 patients with BD and 2760 controls. We used the Synaptic Gene Ontology database to identify rare CNVs that overlap with synaptic genes. Using gene-based analysis, we compared their frequencies between the BD and control groups. We also searched for synaptic gene sets related to BD. The significance level was set to a false discovery rate of 10%. RESULTS: The RNF216 gene was significantly associated with BD (odds ratio, 4.51 [95% confidence interval, 1.66-14.89], false discovery rate < 10%). The BD-associated CNV that corresponded with RNF216 also partially overlapped with the minimal critical region of the 7p22.1 microduplication syndrome. The integral component of the postsynaptic membrane (Gene Ontology:0099055) was significantly associated with BD. The CNV overlapping with the intron region of GRM5 in this gene set showed a nominal significant association between cases and controls (P < 0.05). CONCLUSION: We provide evidence that CNVs in RNF216 and postsynaptic membrane-related genes confer a risk of BD, contributing to a better understanding of the pathogenesis of BD.

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.

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.

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.

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.

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.

Regional brain volume reductions in major depressive disorder and bipolar disorder: An analysis by voxel-based morphometry.

OBJECTIVES: The present study investigated the usefulness of evaluating the existence of volume reduction in brain regions using voxel-based morphometry (VBM) to dissociate major depressive disorder (MDD) from bipolar disorder (BD). METHODS/DESIGN: This study enrolled 92 individuals with MDD, 32 individuals with BD, and 43 healthy controls (HCs). We focused on gray matter volume (GMV) of the subgenual anterior cingulate cortex (sgACC), subcallosal area (SCA), and hippocampus. The degree of volume reduction in these brain regions was calculated as the z score, and the differences of z scores in these regions were investigated among the MDD, BD, and HC groups. We then performed a receiver operating characteristic curve analysis to dissociate the individuals with MDD and BD from the HCs based on the z scores in the GMV of these brain regions. RESULTS: While there were no significant differences in the z scores of the hippocampus among the three groups, the z score of the sgACC was significantly higher in the MDD group than in the BD and HC groups, and the SCA z score was significantly higher in the MDD and BD groups than in the HC group. CONCLUSIONS: Our findings suggest that VBM evaluation of GMV reduction in the sgACC may be useful as an objective adjunctive tool to distinguish between MDD and BD.

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.

Can we predict amyloid deposition by objective cognition and regional cerebral blood flow in patients with subjective cognitive decline?

BACKGROUND: Subjective cognitive decline (SCD) may herald the first symptoms of Alzheimer's disease (AD) whereas individuals with beta-amyloid (Aß) deposition are regarded as a high-risk group for AD. Recently, amyloid positron emission tomography (PET) studies have demonstrated clinical and cognitive feature differences between Aß-positive and negative SCD, but details of their differences remain unclear. We aimed to investigate the relationships among Aß deposition, clinical, and cognitive features in patients with SCD. METHODS: Forty-two patients with SCD (22 women, 74.5 ± 4.7 years) were examined using fluorine-18 florbetaben PET and were divided into Aß-positive (n = 10) and negative (n = 32) groups. We compared cognitive and psychological outcomes, and single photon emission computed tomography (SPECT) imaging data between the two groups. In addition, a linear regression analysis was performed to assess relationships between the severity of SCD and neuropsychological tests, affective scores, and demographic factors. RESULTS: The rate of score changes from the immediate recall to delayed recall in the logical memory subtest of the Wechsler's Memory Scale Revised were different between the groups (P = 0.04). However, the binary logistic regression analysis showed no significant differences between the two. In addition, the severity of SCD was significantly strong in women (P = 0.002). Furthermore, within the Aß-negative group, subjective memory loss correlated with word fluency category score (P = 0.023) and apathy scale (P = 0.037). CONCLUSIONS: No significant differences were observed between Aß-positive and -negative SCD on any of the neuropsychological measures, clinical measures, or SPECT imaging. Further, the severity of SCD was not predicted by the symptoms of anxiety, depression, or neuropsychological examination.

The psychological impact of disclosing amyloid status to Japanese elderly: a preliminary study on asymptomatic patients with subjective cognitive decline.

ABSTRACTIn Japan, 4.6 million people are living with dementia and the number is expected to rise to 7 million by 2025. Amyloid-ß (Aß) positron emission tomography (PET) is used for cognitively normal Japanese people with or without subjective cognitive decline (SCD) for the purpose of clinical trials or diagnosis. Nevertheless, no empirical studies have been conducted on the safety of disclosing amyloid status to such populations. We conducted amyloid PET imaging on 42 participants (Aß positive (n = 10) and negative (n = 32)). State anxiety and depression were measured at pre- and post-disclosure, and test-related distress at post-disclosure. Mean state anxiety and depression scores were below the cut-off through pre- and post-disclosure in the Aß positive and negative groups. State anxiety and depression did not change over time and were not different between groups. Mean test-related distress scores were within normal limits at post-disclosure in both groups. No significant difference was found between groups. Disclosing Aß positive results did not cause greater mood disturbance than negative results in a short period of time. The short-term psychological safety of disclosing Aß PET results to asymptomatic Japanese adults with SCD was indicated.

Female-Specific Intergenerational Transmission Patterns of the Human Corticolimbic Circuitry.

Parents have large genetic and environmental influences on offspring's cognition, behavior, and brain. These intergenerational effects are observed in mood disorders, with particularly robust association in depression between mothers and daughters. No studies have thus far examined the neural bases of these intergenerational effects in humans. Corticolimbic circuitry is known to be highly relevant in a wide range of processes, including mood regulation and depression. These findings suggest that corticolimbic circuitry may also show matrilineal transmission patterns. Therefore, we examined human parent-offspring association in this neurocircuitry and investigated the degree of association in gray matter volume between parent and offspring. We used voxelwise correlation analysis in a total of 35 healthy families, consisting of parents and their biological offspring. We found positive associations of regional gray matter volume in the corticolimbic circuit, including the amygdala, hippocampus, anterior cingulate cortex, and ventromedial prefrontal cortex between biological mothers and daughters. This association was significantly greater than mother-son, father-daughter, and father-son associations. The current study suggests that the corticolimbic circuitry, which has been implicated in mood regulation, shows a matrilineal-specific transmission patterns. Our preliminary findings are consistent with what has been found behaviorally in depression and may have clinical implications for disorders known to have dysfunction in mood regulation such as depression. Studies such as ours will likely bridge animal work examining gene expression in the brains and clinical symptom-based observations and provide promising ways to investigate intergenerational transmission patterns in the human brain. SIGNIFICANCE STATEMENT: Parents have large genetic and environmental influences on the offspring, known as intergenerational effects. Specifically, depression has been shown to exhibit strong matrilineal transmission patterns. Although intergenerational transmission patterns in the human brain are virtually unknown, this would suggest that the corticolimbic circuitry relevant to a wide range of processes including mood regulation may also show matrilineal transmission patterns. Therefore, we examined the degree of association in corticolimbic gray matter volume (GMV) between parent and offspring in 35 healthy families. We found that positive correlations in maternal corticolimbic GMV with daughters were significantly greater than other parent-offspring dyads. Our findings provide new insight into the potential neuroanatomical basis of circuit-based female-specific intergenerational transmission patterns in depression.

Altered microstructure within social-cognitive brain networks during childhood in Williams syndrome.

Williams syndrome (WS) is a neurodevelopmental condition caused by a hemizygous deletion of ∼26-28 genes on chromosome 7q11.23. WS is associated with a distinctive pattern of social cognition. Accordingly, neuroimaging studies show that WS is associated with structural alterations of key brain regions involved in social cognition during adulthood. However, very little is currently known regarding the neuroanatomical structure of social cognitive brain networks during childhood in WS. This study used diffusion tensor imaging to investigate the structural integrity of a specific set of white matter pathways (inferior fronto-occipital fasciculus [IFOF] and uncinate fasciculus [UF]) and associated brain regions [fusiform gyrus (FG), amygdala, hippocampus, medial orbitofrontal gyrus (MOG)] known to be involved in social cognition in children with WS and a typically developing (TD) control group. Children with WS exhibited higher fractional anisotropy (FA) and axial diffusivity values and lower radial diffusivity and apparent diffusion coefficient (ADC) values within the IFOF and UF, higher FA values within the FG, amygdala, and hippocampus and lower ADC values within the FG and MOG compared to controls. These findings provide evidence that the WS genetic deletion affects the development of key white matter pathways and brain regions important for social cognition.

Glymphatic system dysfunction in mood disorders: Evaluation by diffusion magnetic resonance imaging.

The glymphatic system, an expansive cerebral waste-disposal network, harbors myriad enigmatic facets necessitating elucidation of their nexus with diverse pathologies. Murine investigations have revealed a relationship between the glymphatic system and affective disorders. This study aimed to illuminate the interplay between bipolar disorder and the glymphatic system. Fifty-eight individuals afflicted with bipolar disorder were identified through meticulous psychiatric assessment. These individuals were juxtaposed with a cohort of 66 comparably aged and sex-matched, mentally stable subjects. Subsequent analysis entailed the application of covariance analysis to evaluate along with the perivascular space (ALPS) index, a novel magnetic resonance imaging method for assessing brain interstitial fluid dynamics via diffusion tensor imaging within the bipolar and control cohorts. We also evaluated the correlation between the ALPS index and clinical parameters, which included the Hamilton Depression scale scores, disease duration, and other clinical assessments. Moreover, partial correlation analyses, incorporating age and sex as covariates, were performed to investigate the relationships between the ALPS index and clinical measures within the two cohorts. A noteworthy adverse correlation was observed between the ALPS index and illness duration. A free-water imaging analysis revealed a substantial elevation in the free-water index within the white-matter tracts, prominently centered on the corpus callosum, within the bipolar cohort relative to that in the control group. In analogous cerebral regions, a conspicuous affirmative correlation was observed between the free-water-corrected radial diffusivity and depression rating scales. Our results showed that the protracted course of bipolar disorder concomitantly exacerbated glymphatic system dysregulation.

Alterations of striatal phosphodiesterase 10 A and their association with recurrence rate in bipolar I disorder.

Phosphodiesterase 10 A (PDE10A), a pivotal element of the second messenger signaling downstream of the dopamine receptor stimulation, is conceived to be crucially involved in the mood instability of bipolar I disorder (BD-I) as a primary causal factor or in response to dysregulated dopaminergic tone. We aimed to determine whether striatal PDE10A availability is altered in patients with BD-I and assessed its relationship with the clinical characteristics of BD-I. This case-control study used positron emission tomography (PET) with 2-(2-(3-(4-(2-[18F]fluoroethoxy)phenyl)-7-methyl-4-oxo-3,4-dihydroquinazolin-2-yl)ethyl)-4-isopropoxyisoindoline-1,3-dione ([18F]MNI-659), a radioligand that binds to PDE10A, to examine the alterations of the striatal PDE10A availability in the living brains of individuals with BD-I and their association with the clinical characteristics of BD-I. [18F]MNI-659 PET data were acquired from 25 patients with BD-I and 27 age- and sex-matched healthy controls. Patients with BD-I had significantly lower PDE10A availability than controls in the executive (F = 8.86; P = 0.005) and sensorimotor (F = 6.13; P = 0.017) subregions of the striatum. Lower PDE10A availability in the executive subregion was significantly associated with a higher frequency of mood episodes in patients with BD-I (r = -0.546; P = 0.007). This study provides the first evidence of altered PDE10A availability in patients with BD-I. Lower PDE10A availability in the executive subregion of the striatum is associated with an increased recurrence risk, suggesting that PDE10A may prevent BD-I relapse. Further studies are required to elucidate the role of PDE10A in BD-I pathophysiology and explore its potential as a treatment target.

White matter aberrations in prepubertal estrogen-naive girls with monosomic Turner syndrome.

Turner syndrome (TS) offers a unique opportunity to investigate associations among genes, the brain, and cognitive phenotypes. In this study, we used 3 complementary analyses of diffusion tensor imaging (DTI) data (whole brain, region of interest, and fiber tractography) and a whole brain volumetric imaging technique to investigate white matter (WM) structure in prepubertal, nonmosaic, estrogen-naive girls with TS compared with age and sex matched typically developing controls. The TS group demonstrated significant WM aberrations in brain regions implicated in visuospatial abilities, face processing, and sensorimotor and social abilities compared with controls. Extensive spatial overlap between regions of aberrant WM structure (from DTI) and regions of aberrant WM volume were observed in TS. Our findings indicate that complete absence of an X chromosome in young females (prior to receiving exogenous estrogen) is associated with WM aberrations in specific regions implicated in characteristic cognitive features of TS.

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.

White matter alterations in the dorsal attention network contribute to a high risk of unsafe driving in healthy older people.

Aim: Healthy older drivers may be at high risk of fatal traffic accidents. Our recent study showed that volumetric alterations in gray matter in the brain regions within the dorsal attention network (DAN) were strongly related to the risk of unsafe driving in healthy older people. However, the relationship between white matter (WM) structural connectivity and driving ability in healthy older people is still unclear. Methods: We used diffusion tensor imaging to examine the association between microstructural alterations in the DAN and the risk of unsafe driving among healthy older people. We enrolled 32 healthy older individuals aged over 65 years and screened unsafe drivers using an on-road driving test. We then determined the pattern of WM aberrations in unsafe drivers using tract-based spatial statistics. Results: The analysis demonstrated that unsafe drivers had significantly higher axial diffusivity values in nine WM clusters compared with safe drivers. These results were primarily observed bilaterally in the dorsal superior longitudinal fasciculus, which is involved in the DAN. Furthermore, correlation analyses showed that higher axial diffusivity values in the superior longitudinal fasciculus were associated with lower Trail Making Test A scores within unsafe drivers. This result suggests that functionally, WM microstructural alterations in the DAN are associated with attention problems, which may contribute to the risk of unsafe driving among healthy older people. Conclusion: Our findings may elucidate the neurobiological mechanisms underlying the increased risk of unsafe driving in healthy older people, potentially facilitating the development of new interventions to prevent fatal accidents.