Brain-age prediction: Systematic evaluation of site effects, and sample age range and size.

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

Magnetic resonance imaging-based machine learning classification of schizophrenia spectrum disorders: a meta-analysis.

BACKGROUND: Recent advances in multivariate pattern recognition have fostered the search for reliable neuroimaging-based biomarkers in psychiatric conditions, including schizophrenia. These approaches consider the complex pattern of alterations in brain function and structure, overcoming the limitations of traditional univariate methods. To assess the reliability of neuroimaging-based biomarkers and the contribution of study characteristics in distinguishing individuals with schizophrenia spectrum disorder (SSD) from healthy controls (HCs), we conducted a systematic review of the studies that used multivariate pattern recognition for this objective. METHODS: We systematically searched PubMed, Scopus, and Web of Science for studies on SSD classification using multivariate pattern analysis on magnetic resonance imaging data. We employed a bivariate random-effects meta-analytic model to explore the classification of sensitivity (SE) and specificity (SP) across studies while also evaluating the moderator effects of clinical and non-clinical variables. RESULTS: A total of 119 studies (with 12,723 patients with SSD and 13,196 HCs) were identified. The meta-analysis estimated a SE of 79.1% (95% confidence interval [CI], 77.1%-81.0%) and a SP of 80.0% (95% CI, 77.8%-82.0%). In particular, the Positive and Negative Syndrome Scale and the Global Assessment of Functioning scores, age, age of onset, duration of untreated psychosis, deep learning, algorithm type, features selection, and validation methods had significant effects on classification performance. CONCLUSIONS: Multivariate pattern analysis reliably identifies neuroimaging-based biomarkers of SSD, achieving ∼80% SE and SP. Despite clinical heterogeneity, discernible brain modifications effectively differentiate SSD from HCs. Classification performance depends on patient-related and methodological factors crucial for the development, validation, and application of prospective models in clinical settings.

Greater male than female variability in regional brain structure across the lifespan.

For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.

Intelligence, educational attainment, and brain structure in those at familial high-risk for schizophrenia or bipolar disorder.

First-degree relatives of patients diagnosed with schizophrenia (SZ-FDRs) show similar patterns of brain abnormalities and cognitive alterations to patients, albeit with smaller effect sizes. First-degree relatives of patients diagnosed with bipolar disorder (BD-FDRs) show divergent patterns; on average, intracranial volume is larger compared to controls, and findings on cognitive alterations in BD-FDRs are inconsistent. Here, we performed a meta-analysis of global and regional brain measures (cortical and subcortical), current IQ, and educational attainment in 5,795 individuals (1,103 SZ-FDRs, 867 BD-FDRs, 2,190 controls, 942 schizophrenia patients, 693 bipolar patients) from 36 schizophrenia and/or bipolar disorder family cohorts, with standardized methods. Compared to controls, SZ-FDRs showed a pattern of widespread thinner cortex, while BD-FDRs had widespread larger cortical surface area. IQ was lower in SZ-FDRs (d = -0.42, p = 3 × 10-5 ), with weak evidence of IQ reductions among BD-FDRs (d = -0.23, p = .045). Both relative groups had similar educational attainment compared to controls. When adjusting for IQ or educational attainment, the group-effects on brain measures changed, albeit modestly. Changes were in the expected direction, with less pronounced brain abnormalities in SZ-FDRs and more pronounced effects in BD-FDRs. To conclude, SZ-FDRs and BD-FDRs show a differential pattern of structural brain abnormalities. In contrast, both had lower IQ scores and similar school achievements compared to controls. Given that brain differences between SZ-FDRs and BD-FDRs remain after adjusting for IQ or educational attainment, we suggest that differential brain developmental processes underlying predisposition for schizophrenia or bipolar disorder are likely independent of general cognitive impairment.

Increased power by harmonizing structural MRI site differences with the ComBat batch adjustment method in ENIGMA.

A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this introduces heterogeneity due to different scanning devices and sequences. ENIGMA projects commonly address this heterogeneity with random-effects meta-analysis or mixed-effects mega-analysis. Here we tested whether the batch adjustment method, ComBat, can further reduce site-related heterogeneity and thus increase statistical power. We conducted random-effects meta-analyses, mixed-effects mega-analyses and ComBat mega-analyses to compare cortical thickness, surface area and subcortical volumes between 2897 individuals with a diagnosis of schizophrenia and 3141 healthy controls from 33 sites. Specifically, we compared the imaging data between individuals with schizophrenia and healthy controls, covarying for age and sex. The use of ComBat substantially increased the statistical significance of the findings as compared to random-effects meta-analyses. The findings were more similar when comparing ComBat with mixed-effects mega-analysis, although ComBat still slightly increased the statistical significance. ComBat also showed increased statistical power when we repeated the analyses with fewer sites. Results were nearly identical when we applied the ComBat harmonization separately for cortical thickness, cortical surface area and subcortical volumes. Therefore, we recommend applying the ComBat function to attenuate potential effects of site in ENIGMA projects and other multi-site structural imaging work. We provide easy-to-use functions in R that work even if imaging data are partially missing in some brain regions, and they can be trained with one data set and then applied to another (a requirement for some analyses such as machine learning).

Neural signatures of the risk for bipolar disorder: A meta-analysis of structural and functional neuroimaging studies.

OBJECTIVE: Widespread functional and structural alterations in the brain have been extensively reported in unaffected relatives (RELs) of patients with bipolar disorder (BD) who are at genetic risk for BD. A sufficiently powered meta-analysis of structural (sMRI) and functional magnetic resonance imaging (fMRI) alterations in RELs is still lacking. METHODS: Functional and structural magnetic resonance imaging studies investigating RELs and healthy controls (HCs) published by July 2017 were included in the meta-analyses. Study procedures were conducted in accordance with the Meta-analysis Of Observational Studies in Epidemiology (MOOSE) guidelines. Random-effects coordinate-based meta-analyses were performed across all the studies per imaging modality using Seed-based d Mapping (SDM). For fMRI studies, meta-analyses were calculated for each task type. For sMRI studies, regional volumetric changes-analyses were estimated using R. Finally, multimodal meta-analyses of structural and functional abnormalities were performed. RESULTS: Sixty-nine imaging studies (2195 RELs and 3169 HCs) were included in the meta-analyses. RELs showed hyperactivation in the fronto-striatal regions as well as parietal hypoactivation during cognition. Also, activation was increased in the amygdala during emotional processing and in the orbitofrontal cortex during reward, respectively. Frontal and superior temporal cortex were hypertrophic in RELs. The right inferior frontal gyrus (rIFG) showed both increased activation during cognitive tasks and greater volume in RELs. CONCLUSIONS: Our findings demonstrate that increased brain volume and activation are present in RELs and may represent intermediate phenotypes for the disorder. Furthermore, some neural changes including increased rIFG volume may be associated with the resilience to BD.

Assessing Learning Needs and Career Attitudes of Italian Psychiatry Residents: Results from a National Survey Conducted by the Italian Society of Psychopathology Young Psychiatrists Section (SOPSI-GG).

OBJECTIVE: No data are available about learning needs and career attitudes of Italian Psychiatry Residents (IPRs). Authors aimed to assess such needs through a survey to generate insight for implementing educational programs close to IPRs' perceived learning needs. METHODS: A 54-item questionnaire was developed in order to investigate career information, educational preference and learning needs of IPRs. A sample of 298 IPRs participated to the survey and was divided into four subgroups according to their location (North, Centre, South and Islands). The subgroups were compared through ANOVA for age and chi-square tests for qualitative variables (including gender and all sub-items of the survey), with Bonferroni post-hoc analysis. RESULTS: IPRs were found to pursue, along with traditional and theoretical training, a quite practical approach, characterized by working groups, discussions on clinical cases and practical interactive sessions. The topics of major interest included: clinical psychiatry, psychopharmacology, psychiatric emergencies, communication and relationship skills (97%, 98.0%, 98.3% and 95.7% of the total sample, respectively). Indeed, a strong need for interaction with healthcare professionals emerged (97% of the total sample). North and Centre IPRs were more involved in Day Hospital activities than residents from South Italy and Islands (p<.001). South IPRs appeared to be more prone to invest for their education than residents from other areas (p<.01). CONCLUSION: Reported findings should be taken into account as a starting point for planning and developing future targeted packages of educational proposals for IPRs and they should stand as a useful pilot study for further investigation in the field.

DRD2/AKT1 interaction on D2 c-AMP independent signaling, attentional processing, and response to olanzapine treatment in schizophrenia.

The D2/AKT1/GSK-3ß signaling pathway has been involved in the downstream intracellular effects of dopamine, in the pathophysiology of cognitive deficits and related brain activity in schizophrenia, as well as in response to treatment with antipsychotics. Polymorphisms in the D2 (DRD2 rs1076560) and AKT1 (AKT1 rs1130233) genes have been associated with their respective protein expression and with higher-order cognition and brain function, including attention. Given the strong potential for their relationship, we investigated the interaction of these polymorphisms on multiple molecular and in vivo phenotypes associated with this signaling pathway. We measured AKT1 and GSK-3ß proteins and phosphorylation in human peripheral blood mononuclear cells, functional MRI cingulate response during attentional control, behavioral accuracy during sustained attention, and response to 8 wk of treatment with olanzapine in a total of 190 healthy subjects and 66 patients with schizophrenia. In healthy subjects, we found that the interaction between the T allele of DRD2 rs1076560 and the A allele of AKT1 rs1130233 was associated with reduced AKT1 protein levels and reduced phosphorylation of GSK-3ß, as well as with altered cingulate response and reduced behavioral accuracy during attentional processing. On the other hand, interaction of these two alleles was associated with greater improvement of Positive and Negative Syndrome Scale scores in patients with schizophrenia after treatment with olanzapine. The present results indicate that these functional polymorphisms are epistatically associated with multiple phenotypes of relevance to schizophrenia. Our results also lend support to further investigation of this downstream molecular pathway in the etiology and treatment of this disorder.

Cerebellar dysconnectivity in schizophrenia and bipolar disorder is associated with cognitive and clinical variables.

BACKGROUND: Abnormal cerebellar functional connectivity (FC) has been implicated in the pathophysiology of schizophrenia (SCZ) and bipolar disorder (BD). However, the patterns of cerebellar dysconnectivity in these two disorders and their association with cognitive functioning and clinical symptoms have not been fully clarified. In this study, we examined cerebellar FC alterations in SCZ and BD-I and their association with cognition and psychotic symptoms. METHODS: Resting-state functional magnetic resonance imaging (rs-fMRI) data of 39 SCZ, 43 BD-I, and 61 healthy controls from the Consortium for Neuropsychiatric Phenomics dataset were examined. The cerebellum was parcellated into ten functional networks, and seed-based FC was calculated for each cerebellar system. Principal component analyses were used to reduce the dimensionality of the diagnosis-related FC and cognitive variables. Multiple regression analyses were used to assess the relationship between FC and cognitive and clinical data. RESULTS: We observed decreased cerebellar FC with the frontal, temporal, occipital, and thalamic areas in individuals with SCZ, and a more widespread decrease in cerebellar FC in individuals with BD-I, involving the frontal, cingulate, parietal, temporal, occipital, and thalamic regions. SCZ had increased within-cerebellum and cerebellar frontal FC compared to BD-I. In BD-I, memory and verbal learning performances, which were higher compared to SCZ, showed a greater interaction with cerebellar FC patterns. Additionally, patterns of increased cortico-cerebellar FC were marginally associated with positive symptoms in patients. CONCLUSIONS: Our findings suggest that shared and distinct patterns of cortico-cerebellar dysconnectivity in SCZ and BD-I could underlie cognitive impairments and psychotic symptoms in these disorders.

Sex differences in deep brain shape and asymmetry persist across schizophrenia and healthy individuals: A meta-analysis from the ENIGMA-Schizophrenia Working Group.

Background: Schizophrenia (SCZ) is characterized by a disconnect from reality that manifests as various clinical and cognitive symptoms, and persistent neurobiological abnormalities. Sex-related differences in clinical presentation imply separate brain substrates. The present study characterized deep brain morphology using shape features to understand the independent effects of diagnosis and sex on the brain, and to determine whether the neurobiology of schizophrenia varies as a function of sex. Methods: This study analyzed multi-site archival data from 1,871 male (M) and 955 female (F) participants with SCZ, and 2,158 male and 1,877 female healthy controls (CON) from twenty-three cross-sectional samples from the ENIGMA Schizophrenia Workgroup. Harmonized shape analysis protocols were applied to each site's data for seven deep brain regions obtained from T1-weighted structural MRI scans. Effect sizes were calculated for the following main contrasts: 1) Sex effects;2) Diagnosis-by-Sex interaction; 3) within sex tests of diagnosis; 4) within diagnosis tests of sex differences. Meta-regression models between brain structure and clinical variables were also computed separately in men and women with schizophrenia. Results: Mass univariate meta-analyses revealed more concave-than-convex shape differences in all regions for women relative to men, across diagnostic groups ( d = -0.35 to 0.20, SE = 0.02 to 0.07); there were no significant diagnosis-by-sex interaction effects. Within men and women separately, we identified more-concave-than-convex shape differences for the hippocampus, amygdala, accumbens, and thalamus, with more-convex-than-concave differences in the putamen and pallidum in SCZ ( d = -0.30 to 0.30, SE = 0.03 to 0.10). Within CON and SZ separately, we found more-concave-than-convex shape differences in the thalamus, pallidum, putamen, and amygdala among females compared to males, with mixed findings in the hippocampus and caudate ( d = -0.30 to 0.20, SE = 0.03 to 0.09). Meta-regression models revealed similarly small, but significant relationships, with medication and positive symptoms in both SCZ-M and SCZ-F. Conclusions: Sex-specific variation is an overriding feature of deep brain shape regardless of disease status, underscoring persistent patterns of sex differences observed both within and across diagnostic categories, and highlighting the importance of including it as a critical variable in studies of neurobiology. Future work should continue to explore these dimensions independently to determine whether these patterns of brain morphology extend to other aspects of neurobiology in schizophrenia, potentially uncovering broader implications for diagnosis and treatment. Key Points: Statistical analyses revealed significant main effects for diagnosis and sex in deep brain shape morphology. Among patients with schizophrenia, there was a pattern of thinning and surface contraction in the bilateral hippocampus, amygdala, accumbens, and thalamus, and a pattern of significant thickening and surface expansion in the bilateral putamen and pallidum compared to healthy control participants. Between males and females, there was a pattern of significant thinning and surface contraction in the bilateral thalamus, pallidum, putamen, and amygdala in females compared to males.There was no significant interaction between diagnosis and biological sex, suggesting that sex differences in deep brain shape and asymmetry among patients with schizophrenia reflect those observed in healthy individuals.Small but statistically significant relationships exist between brain structure and clinical correlates of schizophrenia were similar for both men and women with the disease, such that higher CPZ was associated with shape-derived thinning and surface contraction in the caudate, accumbens, hippocampus, amygdala, and thalamus, and elevated positive symptoms were associated with shape-derived thinning and surface contraction in the bilateral caudate, right hippocampus, and right amygdala.

Dynamic functional connectivity in schizophrenia and bipolar disorder: A review of the evidence and associations with psychopathological features.

Alterations of functional network connectivity have been implicated in the pathophysiology of schizophrenia (SCZ) and bipolar disorder (BD). Recent studies also suggest that the temporal dynamics of functional connectivity (dFC) can be altered in these disorders. Here, we summarized the existing literature on dFC in SCZ and BD, and their association with psychopathological and cognitive features. We systematically searched PubMed, Web of Science, and Scopus for studies investigating dFC in SCZ and BD and identified 77 studies. Our findings support a general model of dysconnectivity of dFC in SCZ, whereas a heterogeneous picture arose in BD. Although dFC alterations are more severe and widespread in SCZ compared to BD, dysfunctions of a triple network system underlying goal-directed behavior and sensory-motor networks were present in both disorders. Furthermore, in SCZ, positive and negative symptoms were associated with abnormal dFC. Implications for understanding the pathophysiology of disorders, the role of neurotransmitters, and treatments on dFC are discussed. The lack of standards for dFC metrics, replication studies, and the use of small samples represent major limitations for the field.

Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization.

We present an empirically benchmarked framework for sex-specific normative modeling of brain morphometry that can inform about the biological and behavioral significance of deviations from typical age-related neuroanatomical changes and support future study designs. This framework was developed using regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The Multivariate Factorial Polynomial Regression (MFPR) emerged as the preferred algorithm optimized using nonlinear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins, and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3,000 study participants. The model and scripts described here are freely available through CentileBrain (https://centilebrain.org/).

Stress-related methylation of the catechol-O-methyltransferase Val 158 allele predicts human prefrontal cognition and activity.

DNA methylation at CpG dinucleotides is associated with gene silencing, stress, and memory. The catechol-O-methyltransferase (COMT) Val(158) allele in rs4680 is associated with differential enzyme activity, stress responsivity, and prefrontal activity during working memory (WM), and it creates a CpG dinucleotide. We report that methylation of the Val(158) allele measured from peripheral blood mononuclear cells (PBMCs) of Val/Val humans is associated negatively with lifetime stress and positively with WM performance; it interacts with stress to modulate prefrontal activity during WM, such that greater stress and lower methylation are related to reduced cortical efficiency; and it is inversely related to mRNA expression and protein levels, potentially explaining the in vivo effects. Finally, methylation of COMT in prefrontal cortex and that in PBMCs of rats are correlated. The relationship of methylation of the COMT Val(158) allele with stress, gene expression, WM performance, and related brain activity suggests that stress-related methylation is associated with silencing of the gene, which partially compensates the physiological role of the high-activity Val allele in prefrontal cognition and activity. Moreover, these results demonstrate how stress-related DNA methylation of specific functional alleles impacts directly on human brain physiology beyond sequence variation.

Factors Associated with Delirium in COVID-19 Patients and Their Outcome: A Single-Center Cohort Study.

BACKGROUND: A significant proportion of patients with coronavirus disease 2019 (COVID-19) suffer from delirium during hospitalization. This single-center observational study investigates the occurrence of delirium, the associated risk factors and its impact on in-hospital mortality in an Italian cohort of COVID 19 inpatients. METHODS: Data were collected in the COVID units of a general medical hospital in the South of Italy. Socio-demographic, clinical and pharmacological features were collected. Diagnosis of delirium was based on a two-step approach according to 4AT criteria and DSM5 criteria. Outcomes were: dates of hospital discharge, Intensive Care Unit (ICU) admission, or death, whichever came first. Univariable and multivariable proportional hazards Cox regression models were estimated, and risks were reported as hazard ratios (HR) along with their 95% confidence intervals (95% CI). RESULTS: A total of 47/214 patients (22%) were diagnosed with delirium (21 hypoactive, 15 hyperactive, and 11 mixed). In the multivariable model, four independent variables were independently associated with the presence of delirium: dementia, followed by age at admission, C-reactive protein (CRP), and Glasgow Coma Scale. In turn, delirium was the strongest independent predictor of death/admission to ICU (composite outcome), followed by Charlson Index (not including dementia), CRP, and neutrophil-to-lymphocyte ratio. The probability of reaching the composite outcome was higher for patients with the hypoactive subtype than for those with the hyperactive subtype. CONCLUSIONS: Delirium was the strongest predictor of poor outcome in COVID-19 patients, especially in the hypoactive subtype. Several clinical features and inflammatory markers were associated with the increased risk of its occurrence. The early recognition of these factors may help clinicians to select patients who would benefit from both non-pharmacological and pharmacological interventions in order to prevent delirium, and in turn, reduce the risk of admission to ICU or death.

D2 receptor genotype and striatal dopamine signaling predict motor cortical activity and behavior in humans.

OBJECTIVE: Pre-synaptic D2 receptors regulate striatal dopamine release and DAT activity, key factors for modulation of motor pathways. A functional SNP of DRD2 (rs1076560 G>T) is associated with alternative splicing such that the relative expression of D2S (mainly pre-synaptic) vs. D2L (mainly post-synaptic) receptor isoforms is decreased in subjects with the T allele with a putative increase of striatal dopamine levels. To evaluate how DRD2 genotype and striatal dopamine signaling predict motor cortical activity and behavior in humans, we have investigated the association of rs1076560 with BOLD fMRI activity during a motor task. To further evaluate the relationship of this circuitry with dopamine signaling, we also explored the correlation between genotype based differences in motor brain activity and pre-synaptic striatal DAT binding measured with [(123)I] FP-CIT SPECT. METHODS: Fifty healthy subjects, genotyped for DRD2 rs1076560 were studied with BOLD-fMRI at 3T while performing a visually paced motor task with their right hand; eleven of these subjects also underwent [(123)I]FP-CIT SPECT. SPM5 random-effects models were used for statistical analyses. RESULTS: Subjects carrying the T allele had greater BOLD responses in left basal ganglia, thalamus, supplementary motor area, and primary motor cortex, whose activity was also negatively correlated with reaction time at the task. Moreover, left striatal DAT binding and activity of left supplementary motor area were negatively correlated. INTERPRETATION: The present results suggest that DRD2 genetic variation was associated with focusing of responses in the whole motor network, in which activity of predictable nodes was correlated with reaction time and with striatal pre-synaptic dopamine signaling. Our results in humans may help shed light on genetic risk for neurobiological mechanisms involved in the pathophysiology of disorders with dysregulation of striatal dopamine like Parkinson's disease.

Cortical gray matter changes in primary blepharospasm: a voxel-based morphometry study.

Previous voxel-based morphometry studies of patients with primary blepharospasm documented gray matter volumetric differences of the striatum, cerebellum, thalamus, and parietal lobe areas. However, these results were inconsistent across studies, which recruited relatively small samples and did not always provide detailed clinical information on patients with blepharospasm. The objective of this study was to analyze whole-brain gray matter volume in a larger sample of patients with blepharospasm and to expand on previous works by evaluating whether clinical features of blepharospasm correlate to whole-brain gray matter changes. Voxel-based morphometry was performed on 25 patients with primary adult-onset blepharospasm and 24 healthy subjects (controls) matched for age, sex, and handedness. Clinical data were collected through a standardized interview. Severity of blepharospasm was measured using the Jankovic Rating Scale. Patients with blepharospasm had greater gray matter volume than controls in the right middle frontal gyrus, whereas patients with blepharospasm had smaller gray matter volume than controls in the left postcentral gyrus and left superior temporal gyrus. Spearman correlation analysis with Bonferroni correction failed to show significant correlations between gray matter volume and the explored clinical variables, comprising age at onset, disease duration, blepharospasm severity, presence of an effective geste antagoniste, and dose and duration of botulinum toxin treatment. Patients with blepharospasm exhibited gray matter volume differences exclusively in cortical regions highly relevant to sensory processing and cognitive modulation of motor behavior. Gray matter changes in the primary sensory cortex may represent a common trait of primary dystonias, including blepharospasm.

Nonlinear response of the anterior cingulate and prefrontal cortex in schizophrenia as a function of variable attentional control.

Previous studies have reported abnormal prefrontal and cingulate activity during attentional control processing in schizophrenia. However, it is not clear how variation in attentional control load modulates activity within these brain regions in this brain disorder. The aim of this study in schizophrenia is to investigate the impact of increasing levels of attentional control processing on prefrontal and cingulate activity. Blood oxygen level-dependent (BOLD) responses of 16 outpatients with schizophrenia were compared with those of 21 healthy subjects while performing a task eliciting increasing levels of attentional control during event-related functional magnetic resonance imaging at 3 T. Results showed reduced behavioral performance in patients at greater attentional control levels. Imaging data indicated greater prefrontal activity at intermediate attentional control levels in patients but greater prefrontal and cingulate responses at high attentional control demands in controls. The BOLD activity profile of these regions in controls increased linearly with increasing cognitive loads, whereas in patients, it was nonlinear. Correlation analysis consistently showed differential region and load-specific relationships between brain activity and behavior in the 2 groups. These results indicate that varying attentional control load is associated in schizophrenia with load- and region-specific modification of the relationship between behavior and brain activity, possibly suggesting earlier saturation of cognitive capacity.

Mental Health in Patients With Adrenal Incidentalomas: Is There a Relation With Different Degrees of Cortisol Secretion?

CONTEXT: Cushing's syndrome frequently causes mental health impairment. Data in patients with adrenal incidentaloma (AI) are lacking. OBJECTIVE: We aimed to evaluate psychiatric and neurocognitive functions in AI patients, in relation to the presence of subclinical hypercortisolism (SH), and the effect of adrenalectomy on mental health. DESIGN: We enrolled 62 AI patients (64.8 ±â€…8.9 years) referred to our centers. Subclinical hypercortisolism was diagnosed when cortisol after 1mg-dexamethasone suppression test was >50 nmol/L, in the absence of signs of overt hypercortisolism, in 43 patients (SH+). INTERVENTIONS: The structured clinical interview for the Diagnostic and Statistical Manual of Mental Disorders-5, and 5 psychiatric scales were performed. The Brief Assessment of Cognition in Schizophrenia (Verbal and Working Memory, Token and Symbol Task, Verbal Fluency, Tower of London) was explored in 26 patients (≤65 years). RESULTS: The prevalence of psychiatric disorders was 27.4% (SH+ 30.2% vs SH- 21.1%, P = 0.45). SH+ showed a higher prevalence of middle insomnia (by the Hamilton Depression Rating Scale) compared with SH- (51% vs 22%, P = 0.039). Considering the Sheehan Disability Scale, SH+ showed a higher disability score (7 vs 3, P = 0.019), higher perceived stress (4.2 ±â€…1.9 vs 2.9 ±â€…1.9, P = 0.015), and lower perceived social support (75 vs 80, P = 0.036) than SH-. High perceived stress was independently associated with SH (odds ratio [OR] = 5.46, confidence interval 95% 1.4-21.8, P = 0.016). Interestingly, SH+ performed better in verbal fluency (49.5 ±â€…38.9 vs 38.9 ±â€…9.0, P = 0.012), symbol coding (54.1 ±â€…6.7 vs 42.3 ±â€…15.5, P = 0.013), and Tower of London (15.1 vs 10.9, P = 0.009) than SH-. In 8 operated SH+, no significant changes were found. CONCLUSIONS: Subclinical hypercortisolism may influence patients' mental health and cognitive performances, requiring an integrated treatment.

Diagnosis of COVID-19 in Patients with Negative Nasopharyngeal Swabs: Reliability of Radiological and Clinical Diagnosis and Accuracy Versus Serology.

BACKGROUND: The diagnosis of Coronavirus disease 2019 (COVID-19) relies on the positivity of nasopharyngeal swab. However, a significant percentage of symptomatic patients may test negative. We evaluated the reliability of COVID-19 diagnosis made by radiologists and clinicians and its accuracy versus serology in a sample of patients hospitalized for suspected COVID-19 with multiple negative swabs. METHODS: Admission chest CT-scans and clinical records of swab-negative patients, treated according to the COVID-19 protocol or deceased during hospitalization, were retrospectively evaluated by two radiologists and two clinicians, respectively. RESULTS: Of 254 patients, 169 swab-confirmed cases and one patient without chest CT-scan were excluded. A total of 84 patients were eligible for the reliability study. Of these, 21 patients died during hospitalization; the remaining 63 underwent serological testing and were eligible for the accuracy evaluation. Of the 63, 26 patients showed anti-Sars-Cov-2 antibodies, while 37 did not. The inter-rater agreement was "substantial" (kappa 0.683) between radiologists, "moderate" (kappa 0.454) between clinicians, and only "fair" (kappa 0.341) between radiologists and clinicians. Both radiologic and clinical evaluations showed good accuracy compared to serology. CONCLUSIONS: The radiologic and clinical diagnosis of COVID-19 for swab-negative patients proved to be sufficiently reliable and accurate to allow a diagnosis of COVID-19, which needs to be confirmed by serology and follow-up.

Genetically determined interaction between the dopamine transporter and the D2 receptor on prefronto-striatal activity and volume in humans.

Dopamine modulation of neuronal activity during memory tasks identifies a nonlinear inverted-U shaped function. Both the dopamine transporter (DAT) and dopamine D(2) receptors (encoded by DRD(2)) critically regulate dopamine signaling in the striatum and in prefrontal cortex during memory. Moreover, in vitro studies have demonstrated that DAT and D(2) proteins reciprocally regulate each other presynaptically. Therefore, we have evaluated the genetic interaction between a DRD(2) polymorphism (rs1076560) causing reduced presynaptic D(2) receptor expression and the DAT 3'-VNTR variant (affecting DAT expression) in a large sample of healthy subjects undergoing blood oxygenation level-dependent (BOLD)-functional magnetic resonance imaging (MRI) during memory tasks and structural MRI. Results indicated a significant DRD(2)/DAT interaction in prefrontal cortex and striatum BOLD activity during both working memory and encoding of recognition memory. The differential effect on BOLD activity of the DAT variant was mostly manifest in the context of the DRD(2) allele associated with lower presynaptic expression. Similar results were also evident for gray matter volume in caudate. These interactions describe a nonlinear relationship between compound genotypes and brain activity or gray matter volume. Complementary data from striatal protein extracts from wild-type and D(2) knock-out animals (D2R(-/-)) indicate that DAT and D(2) proteins interact in vivo. Together, our results demonstrate that the interaction between genetic variants in DRD(2) and DAT critically modulates the nonlinear relationship between dopamine and neuronal activity during memory processing.