Neurocognitive effects of transcranial direct current stimulation in obsessive-compulsive disorder: a systematic review.

Transcranial direct current stimulation (tDCS) has been used with increasing frequency as a therapeutic tool to alleviate clinical symptoms of obsessive compulsive-disorder (OCD). However, little is known about the effects of tDCS on neurocognitive functioning among OCD patients. The aim of this review was to provide a comprehensive overview of the literature examining the effects of tDCS on specific neurocognitive functions in OCD. A literature search following PRISMA guidelines was conducted on the following databases: PubMed, PsycINFO, Embase, the Cochrane Central Register of Controlled Trials (CENTRAL), the Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Web of Science. The search yielded 4 results: one randomized, sham-controlled study (20 patients), one randomized, controlled, partial crossover trial (12 patients), one open-label study (5 patients), and one randomized, double-blind, sham-controlled, parallel-group trial (37 patients). A total of 51 patients received active tDCS with some diversity in electrode montages targeting the dorsolateral prefrontal cortex, the pre-supplementary motor area, or the orbitofrontal cortex. tDCS was associated with improved decision-making in study 1, enhanced attentional monitoring and response inhibition in study 2, improved executive and inhibitory control in study 3, and reduced attentional bias and improved response inhibition and working memory in study 4. Limitations of this review include its small sample, the absence of a sham group in half of the studies, and the heterogeneity in tDCS parameters. These preliminary results highlight the need for future testing in randomized, sham-controlled trials to examine whether and how tDCS induces relevant cognitive benefits in OCD.

Assessing remission in major depressive disorder using a functional-structural data fusion pipeline: A CAN-BIND-1 study.

Neural network-level changes underlying symptom remission in major depressive disorder (MDD) are often studied from a single perspective. Multimodal approaches to assess neuropsychiatric disorders are evolving, as they offer richer information about brain networks. A FATCAT-awFC pipeline was developed to integrate a computationally intense data fusion method with a toolbox, to produce a faster and more intuitive pipeline for combining functional connectivity with structural connectivity (denoted as anatomically weighted functional connectivity (awFC)). Ninety-three participants from the Canadian Biomarker Integration Network for Depression study (CAN-BIND-1) were included. Patients with MDD were treated with 8 weeks of escitalopram and adjunctive aripiprazole for another 8 weeks. Between-group connectivity (SC, FC, awFC) comparisons contrasted remitters (REM) with non-remitters (NREM) at baseline and 8 weeks. Additionally, a longitudinal study analysis was performed to compare connectivity changes across time for REM, from baseline to week-8. Association between cognitive variables and connectivity were also assessed. REM were distinguished from NREM by lower awFC within the default mode, frontoparietal, and ventral attention networks. Compared to REM at baseline, REM at week-8 revealed increased awFC within the dorsal attention network and decreased awFC within the frontoparietal network. A medium effect size was observed for most results. AwFC in the frontoparietal network was associated with neurocognitive index and cognitive flexibility for the NREM group at week-8. In conclusion, the FATCAT-awFC pipeline has the benefit of providing insight on the 'full picture' of connectivity changes for REMs and NREMs while making for an easy intuitive approach.

Diagnostic deep learning algorithms that use resting EEG to distinguish major depressive disorder, bipolar disorder, and schizophrenia from each other and from healthy volunteers.

BACKGROUND: Mood disorders and schizophrenia affect millions worldwide. Currently, diagnosis is primarily determined by reported symptomatology. As symptoms may overlap, misdiagnosis is common, potentially leading to ineffective or destabilizing treatment. Diagnostic biomarkers could significantly improve clinical care by reducing dependence on symptomatic presentation. METHODS: We used deep learning analysis (DLA) of resting electroencephalograph (EEG) to differentiate healthy control (HC) subjects (N = 239), from those with major depressive disorder (MDD) (N = 105), MDD-atypical (MDD-A) (N = 27), MDD-psychotic (MDD-P) (N = 35), bipolar disorder-depressed episode (BD-DE) (N = 71), BD-manic episode (BD-ME) (N = 49), and schizophrenia (SCZ) (N = 122) and also differentiate subjects with mental disorders on a pair-wise basis. DSM-III-R diagnoses were determined and supplemented by computerized Quick Diagnostic Interview Schedule. After EEG preprocessing, robust exact low-resolution electromagnetic tomography (ReLORETA) computed EEG sources for 82 brain regions. 20 % of all subjects were then set aside for independent testing. Feature selection methods were then used for the remaining subjects to identify brain source regions that are discriminating between diagnostic categories. RESULTS: Pair-wise classification accuracies between 90 % and 100 % were obtained using independent test subjects whose data were not used for training purposes. The most frequently selected features across various pairs are in the postcentral, supramarginal, and fusiform gyri, the hypothalamus, and the left cuneus. Brain sites discriminating SCZ from HC were mainly in the left hemisphere while those separating BD-ME from HC were on the right. LIMITATIONS: The use of superseded DSM-III-R diagnostic system and relatively small sample size in some disorder categories that may increase the risk of overestimation. CONCLUSIONS: DLA of EEG could be trained to autonomously classify psychiatric disorders with over 90 % accuracy compared to an expert clinical team using standardized operational methods.

A genome-wide association, polygenic risk score and sex study on opioid use disorder treatment outcomes.

Opioid use disorder continues to be a health concern with a high rate of opioid related deaths occurring worldwide. Medication Assisted Treatments (MAT) have been shown to reduce opioid withdrawal, cravings and opioid use, however variability exists in individual's treatment outcomes. Sex-specific differences have been reported in opioid use patterns, polysubstance use and health and social functioning. Candidate gene studies investigating methadone dose as an outcome have identified several candidate genes and only five genome-wide associations studies have been conducted for MAT outcomes. This study aimed to identify genetic variants associated with MAT outcomes through genome-wide association study (GWAS) and test the association between genetic variants previously associated with methadone dose through a polygenic risk score (PRS). Study outcomes include: continued opioid use, relapse, methadone dose and opioid overdose. No genome-wide significance SNPs or sex-specific results were identified. The PRS identified statistically significant results (p < 0.05) for the outcome of methadone dose (R2 = 3.45 × 10-3). No other PRS was statistically significant. This study provides evidence for association between a PRS and methadone dose. More research on the PRS to increase the variance explained is needed before it can be used as a tool to help identify a suitable methadone dose within this population.

Lifestyle in bipolar disorder: A cross-sectional study.

BACKGROUND: Modifiable lifestyle behaviors are important factors for improving mental health, yet there has been a lack of research studying lifestyle as a multidimensional construct in bipolar disorder (BD). The aim of this cross-sectional study was to compare the lifestyle patterns of individuals with BD in a current mood episode with healthy controls (HCs) using the Short Multidimensional Inventory Lifestyle Evaluation (SMILE). MATERIALS AND METHODS: The sample consisted of 46 individuals with BD currently experiencing a depressive or manic episode and 50 HC, assessed using the MINI International Neuropsychiatric Interview, Montgomery-Åsberg Depression Rating Scale (MADRS), and the Young Mania Rating Scale (YMRS). The SMILE scale assesses lifestyle across seven domains: diet and nutrition, substance abuse, physical activity, stress management, restorative sleep, social support, and environmental exposures. Between-groups comparisons were performed based on the presence of a psychiatric diagnosis and the type of BD episode. RESULTS: We found significant differences in the total SMILE score (r=0.75, p<0.001) and in scores from each domain of the scale between BD and HC (p<0.05), where individuals with BD in a depressive or manic episode with or without mixed features reported worse lifestyle across all domains. Differences between individuals with BD in different mood episodes across domains on the SMILE scale were non-significant. CONCLUSION: Findings from this study highlight the presence of unhealthy lifestyle patterns in people with BD regardless of the polarity of their mood episode. Implementation of multidimensional lifestyle assessments is an essential step toward detecting the clustering of unhealthy lifestyle patterns in BD.

Genetics of cannabis use in opioid use disorder: A genome-wide association and polygenic risk score study.

BACKGROUND: Individuals with an Opioid Use Disorder (OUD) have increased rates of cannabis use in comparison to the general population. Research on the short- and long-term impacts of cannabis use in OUD patients has been inconclusive. A genetic component may contribute to cannabis cravings. AIMS: Identify genetic variants associated with cannabis use through Genome-wide Association Study (GWAS) methods and investigate a Polygenic Risk Score (PRS). In addition, we aim to identify any sex differences in effect size for genetic variants reaching or nearing genome-wide significance in the GWAS. METHODS: The study outcomes of interest were: regular cannabis use (yes/no) (n = 2616), heaviness of cannabis use (n = 1293) and cannabis cravings (n = 836). Logistic and linear regressions were preformed, respectively, to test the association between genetic variants and each outcome, regular cannabis use and heaviness of cannabis use. GWAS summary statistics from a recent large meta-GWAS investigating cannabis use disorder were used to conduct PRS's. Findings are limited to a European ancestry sample. RESULTS: No genome-wide significant associations were found. Rs1813412 (chromosome 17) for regular cannabis use and rs62378502 (chromosome 5) for heaviness of cannabis use were approaching genome-wide significance. Both these SNPs were nominally significant (p<0.05) within males and females, however sex did not modify the association. The PRS identified statistically significant association with cannabis cravings. The variance explained by all PRSs were less than 1.02x10-2. CONCLUSION: This study provides promising results in understanding the genetic contribution to cannabis use in individuals living with OUD.

Lifestyle interventions for bipolar disorders: A systematic review and meta-analysis.

This review and meta-analysis aimed to describe the existing literature on interventions for bipolar disorder (BD) targeting the 6 pillars of Lifestyle Psychiatry: diet, physical activity (PA), substance use (SU), sleep, stress management, and social relationships (SR). Randomized Controlled Trials that examined the efficacy of lifestyle interventions targeting improvement in depressive/(hypo)manic symptom severity, lifestyle patterns, functioning, quality of life, and/or circadian rhythms were included. The systematic review included 18 studies, while the meta-analysis included studies targeting the same lifestyle domains and outcomes. Sleep (n = 10), PA (n = 9), and diet (n = 8) were the most targeted domains, while SU, SM and SR were least targeted (n = 4 each). Combined diet and PA interventions led to significant improvements in depressive symptoms (SMD: -0.46; 95%CI: -0.88, -0.04; p = 0.03), and functioning (SMD: -0.47; 95%CI: -0.89, -0.05; p = 0.03). Sleep interventions also led to significant improvements in depressive symptoms (SMD: -0.80; 95%CI: -1.21, -0.39; p < 0.01). Future research should focus on developing more multidimensional lifestyle interventions for a potentially greater impact on clinical and functional outcomes of BD.

Loss of age-related laminar differentiation of intracortical myelin in bipolar disorder.

Age-related changes of intracortical myelin in bipolar disorder (BD) have been observed to deviate from the quadratic age curve observed in healthy controls (HC), but it is unclear if this holds at varying cortical depths. From BD (n = 44; age range = 17.6-45.5 years) and HC (n = 60; age range = 17.1-45.8 years) participants, we collected 3T T1-weighted (T1w) images with strong intracortical contrast. Signal values were sampled from 3 equivolume cortical depths. Linear mixed models were used to compare age-related changes in the T1w signal between depths and between groups at each depth. In HC, the age-related changes were significantly different between the superficial one-fourth depth and the deeper depths in the right ventral somatosensory (t = -4.63; FDRp = 0.00025), left dorsomedial somatosensory (t = -3.16; FDRp = 0.028), left rostral ventral premotor (t = -3.16; FDRp = 0.028), and right ventral inferior parietal cortex (t = -3.29; FDRp = 0.028). BD participants exhibited no differences in the age-related T1w signal between depths. Illness duration was negatively correlated with the T1w signal at the one-fourth depth in the right anterior cingulate cortex (rACC; rho = -0.50; FDRp = 0.029). Physiological age-related and depth-specific variation in the T1w signal were not observed in BD. The T1w signal in the rACC may reflect lifetime disease burden in the disorder.

Lifestyle Behaviors, Depression, and Anxiety Among Individuals Living in Canada During the COVID-19 Pandemic.

The aim of our study was to investigate the association between lifestyle behaviors and symptoms of depression and anxiety during the COVID-19 pandemic in Canada. A web survey was conducted between July 3-August 3, 2020, across Canada. The main outcomes considered were a positive screening for depression, as evaluated by the PHQ-2 and positive screening for anxiety, as evaluated by the GAD-7. Lifestyle behaviors were assessed using the Short Multidimensional Lifestyle Inventory Evaluation-Confinement (SMILE-C), an instrument adapted for lifestyle behaviors during the COVID-19 pandemic. The total sample size included 404 participants, of which 24.3% had a positive screen for depression, 20.5% for anxiety, and 15.5% for both. We found significant differences in SMILE-C scores between individuals with a positive and individuals with a negative screen for depression (P < .001). Likewise, there were significant differences in SMILE-C scores between individuals with a positive and individuals with a negative screen for anxiety (P < .001). We found an association between unhealthy lifestyle behaviors and symptoms of depression and anxiety during the COVID-19 lockdown in Canada. The findings highlight the importance of lifestyle medicine (LM) education and targeted lifestyle interventions to promote healthy behaviors and help reduce the burden of mental disorders.

Predictors of perceived symptom change with acute cannabis use for mental health conditions in a naturalistic sample: A machine learning approach.

BACKGROUND: Despite limited clinical evidence of its efficacy, cannabis use has been commonly reported for the management of various mental health concerns in naturalistic field studies. The aim of the current study was to use machine learning methods to investigate predictors of perceived symptom change across various mental health symptoms with acute cannabis use in a large naturalistic sample. METHODS: Data from 68,819 unique observations of cannabis use from 1307 individuals using cannabis to manage mental health symptoms were analyzed. Data were extracted from Strainprint®, a mobile app that allows users to monitor their cannabis use for therapeutic purposes. Machine learning models were employed to predict self-perceived symptom change after cannabis use, and SHapley Additive exPlanations (SHAP) value plots were used to assess feature importance of individual predictors in the model. Interaction effects of symptom severity pre-scores of anxiety, depression, insomnia, and gender were also examined. RESULTS: The factors that were most strongly associated with perceived symptom change following acute cannabis use were pre-symptom severity, age, gender, and the ratio of CBD to THC. Further examination on the impact of baseline severity for the most commonly reported symptoms revealed distinct responses, with cannabis being reported to more likely benefit individuals with lower pre-symptom severity for depression, and higher pre-symptom severity for insomnia. Responses to cannabis use also differed between genders. CONCLUSIONS: Findings from this study highlight the importance of several factors in predicting perceived symptom change with acute cannabis use for mental health symptom management. Mental health profiles and baseline symptom severity may play a large role in perceived responses to cannabis. Distinct response patterns were also noted across commonly reported mental health symptoms, emphasizing the need for placebo-controlled cannabis trials for specific user profiles.

Gray matter volume drives the brain age gap in schizophrenia: a SHAP study.

Neuroimaging-based brain age is a biomarker that is generated by machine learning (ML) predictions. The brain age gap (BAG) is typically defined as the difference between the predicted brain age and chronological age. Studies have consistently reported a positive BAG in individuals with schizophrenia (SCZ). However, there is little understanding of which specific factors drive the ML-based brain age predictions, leading to limited biological interpretations of the BAG. We gathered data from three publicly available databases - COBRE, MCIC, and UCLA - and an additional dataset (TOPSY) of early-stage schizophrenia (82.5% untreated first-episode sample) and calculated brain age with pre-trained gradient-boosted trees. Then, we applied SHapley Additive Explanations (SHAP) to identify which brain features influence brain age predictions. We investigated the interaction between the SHAP score for each feature and group as a function of the BAG. These analyses identified total gray matter volume (group × SHAP interaction term ß = 1.71 [0.53; 3.23]; pcorr < 0.03) as the feature that influences the BAG observed in SCZ among the brain features that are most predictive of brain age. Other brain features also presented differences in SHAP values between SCZ and HC, but they were not significantly associated with the BAG. We compared the findings with a non-psychotic depression dataset (CAN-BIND), where the interaction was not significant. This study has important implications for the understanding of brain age prediction models and the BAG in SCZ and, potentially, in other psychiatric disorders.

Estradiol Replacement as a Potential Enhancer of Working Memory and Neuroplasticity in Hypogonadal Trans Women.

INTRODUCTION: The cognitive effects of cross-sex hormone therapy (CSHT) are not well understood. In cisgender individuals, sex hormone therapy can impact neurotransmitter levels and structural anatomy. Similarly, in gender-diverse persons, CSHT has been associated with neural adaptations, such as growth in brain structures resembling those observed in cisgender individuals of the same sex. Hormone-related changes in learning and memory, as seen in menopause, are associated with physiological hypogonadism or a decline in hormones, such as estradiol. The present study examined the effect of estradiol administration in humans on glutamate concentration in brain regions involved in semantic and working memory (i.e., the dorsolateral prefrontal cortex [DLPFC], the posterior hippocampus, and the pregenual anterior cingulate cortex) and its relationship with memory. METHODS: Eighteen trans women (male biological sex assigned at birth) ceased CSHT for 30 days for a washout phase (t1) upon study enrollment to reach a hypogonadal state. Working and semantic memory, cognition, hormonal assays, and brain imaging were assessed. Participants resumed CSHT for 60 days for a replacement phase (t2), after which the same evaluations from t1 were repeated. RESULTS: Estradiol increased among trans women after 60 days of resumed CSHT with significant improvements in semantic memory compared to the hypogonadal phase. Working memory recall was significantly and positively correlated to glutamate in the DLPFC during the reinstatement phase, although the relationship was not moderated by levels of estradiol. DISCUSSION: These results may have clinical implications for the therapeutic effects of estradiol replacement, serving as a protective factor against cognitive decline and impairment for trans women post-gonadectomy.

Challenges and potential solutions for physician suicide risk factors in the COVID-19 era: psychiatric comorbidities, judicialization of medicine, and burnout.

INTRODUCTION: Suicide among physicians constitutes a public health problem that deserves more consideration. A recently performed meta-analysis and systematic review evaluated suicide mortality in physicians by gender and investigated several related risk factors. It showed that the post-1980 suicide mortality was 46% higher in female physicians than among women in the general population, while the risk in male physicians was 33% lower than among men in general, despite an overall contraction in physician mortality rates in both genders. METHODS: This narrative review was conducted by searching and analyzing articles/databases that were relevant to addressing questions raised by a prior meta-analysis and how they might be affected by COVID-19. This process included unstructured searches on Pubmed for physician suicide, burnout, judicialization of medicine, healthcare organizations, and COVID-19, and Google searches for relevant databases and medical society, expert, and media commentaries on these topics. We focus on three factors critical to addressing physician suicides: epidemiological data limitations, psychiatric comorbidities, and professional overload. RESULTS: We found relevant articles on suicide reporting, physician mental health, the effects of healthcare judicialization, and organizational involvement on physician and patient health, and how COVID-19 may impact such factors. This review addresses information sources, underreporting/misreporting of physician suicide rates, inadequate diagnosis and management of psychiatric comorbidities and the chronic effects on physicians' work capacity, and, finally, judicialization of medicine and organizational failures increasing physician burnout. We discuss these factors in general and in relation to the COVID-19 pandemic. CONCLUSIONS: We present an overview of the above factors, discuss possible solutions, and specifically address how COVID-19 may impact such factors.

Challenges and potential solutions for physician suicide risk factors in the COVID-19 era: psychiatric comorbidities, judicialization of medicine, and burnout

Abstract Introduction Suicide among physicians constitutes a public health problem that deserves more consideration. A recently performed meta-analysis and systematic review evaluated suicide mortality in physicians by gender and investigated several related risk factors. It showed that the post-1980 suicide mortality was 46% higher in female physicians than among women in the general population, while the risk in male physicians was 33% lower than among men in general, despite an overall contraction in physician mortality rates in both genders. Methods This narrative review was conducted by searching and analyzing articles/databases that were relevant to addressing questions raised by a prior meta-analysis and how they might be affected by COVID-19. This process included unstructured searches on Pubmed for physician suicide, burnout, judicialization of medicine, healthcare organizations, and COVID-19, and Google searches for relevant databases and medical society, expert, and media commentaries on these topics. We focus on three factors critical to addressing physician suicides: epidemiological data limitations, psychiatric comorbidities, and professional overload. Results We found relevant articles on suicide reporting, physician mental health, the effects of healthcare judicialization, and organizational involvement on physician and patient health, and how COVID-19 may impact such factors. This review addresses information sources, underreporting/misreporting of physician suicide rates, inadequate diagnosis and management of psychiatric comorbidities and the chronic effects on physicians' work capacity, and, finally, judicialization of medicine and organizational failures increasing physician burnout. We discuss these factors in general and in relation to the COVID-19 pandemic. Conclusions We present an overview of the above factors, discuss possible solutions, and specifically address how COVID-19 may impact such factors.

A detailed manual segmentation procedure for the hypothalamus for 3T T1-weighted MRI.

The hypothalamus is a small grey matter structure which plays a crucial role in many physiological functions. Some studies have found an association between hypothalamic volume and psychopathology, which stresses the need for a standardized method to maximize segmentation accuracy. Here, we provide a detailed step-by-step method outlining the procedures to manually segment the hypothalamus using anatomical T1w images from 3T scanners, which many neuroimaging studies collect as a standard anatomical reference image. We compared volumes generated by manual segmentation and those generated by an automatic algorithm, observing a significant difference between automatically and manually segmented hypothalamus volumes on both sides (left: U = 222842, p-value < 2.2e-16; right: U = 218520, p- value < 2.2e-16).•Significant difference exists between existing automatic segmentation methods and the manual segmentation procedure.•We discuss potential drift effects, segmentation quality issues, and suggestions on how to mitigate them.•We demonstrate that the present manual segmentation procedure using standard T1-weighted MRI may be significantly more accurate than automatic segmentation outputs.

Intracortical myelin in individuals with alcohol use disorder: An initial proof-of-concept study.

INTRODUCTION: Disruption of cortical gray matter and white matter tracts are well-established markers of alcohol use disorder (AUD), but less is known about whether similar differences are present in intracortical myelin (ICM, i.e., highly myelinated gray matter in deeper cortical layers). The goal of this study was to provide initial proof-of-concept for using an optimized structural magnetic resonance imaging (MRI) sequence to detect differences in ICM in individuals with AUD compared to control participants reporting drinking within recommended guidelines. METHODS: This study used an optimized 3T MRI sequence for high intracortical contrast to examine ICM-related MRI signal in 30 individuals with AUD and 33 healthy social drinkers. Surface-based analytic techniques were used to quantify ICM-related MRI signal in 20 bilateral a priori regions of interest based on prior cortical thickness studies, and exploratory vertex-wise analyses were examined using Cohen's d effect size. RESULTS: The global distribution of ICM-related signal was largely comparable between groups. Region of interest analysis indicated that AUD group exhibited greater ICM-related MRI signal in precuneus, ventromedial prefrontal cortex, posterior cingulate, middle anterior cingulate, middle/posterior insula, and dorsolateral prefrontal cortex (Cohen's ds = 0.50-0.75). Four regions (right precuneus, ventromedial prefrontal cortex, posterior cingulate and left dorsolateral prefrontal cortex) remained significant (p < .05) after covarying for smoking status. CONCLUSION: These findings provide initial evidence of ICM differences in a moderately sized sample of individuals with AUD compared to controls, although the inflation of type 1 error rate necessitates caution in drawing conclusions. Robustly establishing these differences in larger samples is necessary. The cross-sectional design cannot address whether the observed differences predate AUD or are consequences of heavy alcohol consumption.

Associations of medication with subcortical morphology across the lifespan in OCD: Results from the international ENIGMA Consortium.

BACKGROUND: Widely used psychotropic medications for obsessive-compulsive disorder (OCD) may change the volumes of subcortical brain structures, and differently in children vs. adults. We measured subcortical volumes cross-sectionally in patients finely stratified for age taking various common classes of OCD drugs. METHODS: The ENIGMA-OCD consortium sample (1081 medicated/1159 unmedicated OCD patients and 2057 healthy controls aged 6-65) was divided into six successive 6-10-year age-groups. Individual structural MRIs were parcellated automatically using FreeSurfer into 8 regions-of-interest (ROIs). ROI volumes were compared between unmedicated and medicated patients and controls, and between patients taking serotonin reuptake inhibitors (SRIs), tricyclics (TCs), antipsychotics (APs), or benzodiazepines (BZs) and unmedicated patients. RESULTS: Compared to unmedicated patients, volumes of accumbens, caudate, and/or putamen were lower in children aged 6-13 and adults aged 50-65 with OCD taking SRIs (Cohen's d = -0.24 to -0.74). Volumes of putamen, pallidum (d = 0.18-0.40), and ventricles (d = 0.31-0.66) were greater in patients aged 20-29 receiving APs. Hippocampal volumes were smaller in patients aged 20 and older taking TCs and/or BZs (d = -0.27 to -1.31). CONCLUSIONS: Results suggest that TCs and BZs could potentially aggravate hippocampal atrophy of normal aging in older adults with OCD, whereas SRIs may reduce striatal volumes in young children and older adults. Similar to patients with psychotic disorders, OCD patients aged 20-29 may experience subcortical nuclear and ventricular hypertrophy in relation to APs. Although cross-sectional, present results suggest that commonly prescribed agents exert macroscopic effects on subcortical nuclei of unknown relation to therapeutic response.

Reduced Metabotropic Glutamate Receptor Type 5 Availability in the Epileptogenic Hippocampus: An in vitro Study.

Abnormalities in the expression of metabotropic glutamate receptor type 5 (mGluR5) have been observed in the hippocampus of patients with drug-resistant mesial Temporal Lobe Epilepsy (mTLE). Ex-vivo studies in mTLE hippocampal surgical specimens have shown increased mGluR5 immunoreactivity, while in vivo whole brain imaging using positron emission tomography (PET) demonstrated reduced hippocampal mGluR5 availability. To further understand mGluR5 abnormalities in mTLE, we performed a saturation autoradiography study with [3H]ABP688 (a negative mGluR5 allosteric modulator). We aimed to evaluate receptor density (Bmax) and dissociation constants (KD) in hippocampal mTLE surgical specimens and in non-epilepsy hippocampi from necropsy controls. mTLE specimens showed a 43.4% reduction in receptor density compared to control hippocampi, which was independent of age, sex and KD (multiple linear regression analysis). There was no significant difference in KD between the groups, which suggests that the decreased mGluR5 availability found in vivo with PET cannot be attributed to reduced affinity between ligand and binding site. The present study supports that changes within the epileptogenic tissue include mGluR5 internalization or conformational changes that reduce [3H]ABP688 binding, as previously suggested in mTLE patients studied in vivo.

Smartphone-based interventions in bipolar disorder: Systematic review and meta-analyses of efficacy. A position paper from the International Society for Bipolar Disorders (ISBD) Big Data Task Force.

BACKGROUND: The clinical effects of smartphone-based interventions for bipolar disorder (BD) have yet to be established. OBJECTIVES: To examine the efficacy of smartphone-based interventions in BD and how the included studies reported user-engagement indicators. METHODS: We conducted a systematic search on January 24, 2022, in PubMed, Scopus, Embase, APA PsycINFO, and Web of Science. We used random-effects meta-analysis to calculate the standardized difference (Hedges' g) in pre-post change scores between smartphone intervention and control conditions. The study was pre-registered with PROSPERO (CRD42021226668). RESULTS: The literature search identified 6034 studies. Thirteen articles fulfilled the selection criteria. We included seven RCTs and performed meta-analyses comparing the pre-post change in depressive and (hypo)manic symptom severity, functioning, quality of life, and perceived stress between smartphone interventions and control conditions. There was significant heterogeneity among studies and no meta-analysis reached statistical significance. Results were also inconclusive regarding affective relapses and psychiatric readmissions. All studies reported positive user-engagement indicators. CONCLUSION: We did not find evidence to support that smartphone interventions may reduce the severity of depressive or manic symptoms in BD. The high heterogeneity of studies supports the need for expert consensus to establish ideally how studies should be designed and the use of more sensitive outcomes, such as affective relapses and psychiatric hospitalizations, as well as the quantification of mood instability. The ISBD Big Data Task Force provides preliminary recommendations to reduce the heterogeneity and achieve more valid evidence in the field.

Thrifty-Eating Behavior Phenotype at the Food Court - Programming Goes Beyond Food Preferences.

Introduction: Prenatal growth impairment leads to higher preference for palatable foods in comparison to normal prenatal growth subjects, which can contribute to increased body fat mass and a higher risk for developing chronic diseases in small-for-gestational-age (SGA) individuals throughout life. This study aimed to investigate the effect of SGA on feeding behavior in children and adolescents, as well as resting-state connectivity between areas related to reward, self-control, and value determination, such as orbitofrontal cortex (OFC), dorsolateral prefrontal cortex (DL-PFC), amygdala and dorsal striatum (DS). Methods: Caregivers and their offspring were recruited from two independent cohorts in Brazil (PROTAIA) and Canada (MAVAN). Both cohorts included anthropometric measurements, food choice tasks, and resting-state functional magnetic resonance imaging (fMRI) data. Results: In the Brazilian sample (17 ± 0.28 years, n=70), 21.4% of adolescents were classified as SGA. They exhibited lower monetary-related expenditure to buy a snack compared to controls in the food choice test. Decreased functional connectivity (n=40) between left OFC and left DL-PFC; and between right OFC and: left amygdala, right DS, and left DS were observed in the Brazilian SGA participants. Canadian SGA participants (14.9%) had non-significant differences in comparison with controls in a food choice task at 4 years old ( ± 0.01, n=315). At a follow-up brain scan visit (10.21 ± 0.140 years, n=49), SGA participants (28.6%) exhibited higher connectivity between the left OFC and left DL-PFC, also higher connectivity between the left OFC and right DL-PFC. We did not observe significant anthropometric neither nutrients' intake differences between groups in both samples. Conclusions: Resting-state fMRI results showed that SGA individuals had altered connectivity between areas involved in encoding the subjective value for available goods and decision-making in both samples, which can pose them in disadvantage when facing food options daily. Over the years, the cumulative exposure to particular food cues together with the altered behavior towards food, such as food purchasing, as seen in the adolescent cohort, can play a role in the long-term risk for developing chronic non-communicable diseases.