Near zero stroke rates can be achieved in carotid endarterectomy (CEA) surgery with selective shunting and electrophysiological neuromonitoring. though false negative rates as high as 40% have been reported. We sought to determine if improved training for interpretation of the monitoring signals can advance the efficacy of selective shunting with electrophysiological monitoring across multiple centers, and determine if other factors could contribute to the differences in reports. Processed and raw beta band (12.5-30 Hz) electroencephalogram (EEG) and median and tibial nerve somatosensory evoked potentials (SSEP) were monitored in 668 CEA cases at six surgical centers. A decrease in amplitude of 50% or more in any EEG or SSEP channel was the criteria for shunting or initiating a neuroprotective protocol. A reduction of 50% or greater in the beta band of the EEG or amplitude of the SSEP was observed in 150 cases. No patient showed signs of a cerebral infarct after surgery. Selective shunting based on EEG and SSEP monitoring can reduce CEA intraoperative stroke rate to a near zero level if trained personnel adopted standardized protocols. We also found that the rapid administration of a protective stroke protocol by attending anesthesiologists was an important aspect of this success rate.

We show the feasibility of spectroscopic cosmological surveys with the SAFARI instrument onboard of SPICA. The work is done through simulations that make use of both empirical methods, i.e. the use of observed luminosity functions and theoretical models for galaxy formation and evolution. The relations assumed between the line emission to trace AGN and star formation activity have been derived from the observations of local samples of galaxies. The results converge to indicate the use of blind spectroscopy with the SAFARI FTS at various resolutions to study galaxy evolution from the local to the distant (z~3) Universe. Specifically, two different and independent galaxy evolution models predict about 7-10 sources to be spectroscopically detected in more than one line in a 2'x 2'SAFARI field of view, down to the expected flux limits of SAFARI, with about 20% of sources to be detected at z>2. SPICA-SAFARI will be therefore excellent at detecting high-z sources and at assessing in a direct way their nature (e.g whether mainly AGN or Star Formation powered) thanks to blind spectroscopy.

Kisspeptin, encoded by Kiss1, stimulates reproduction and is synthesized in the hypothalamic anteroventral periventricular and arcuate nuclei. Kiss1 is also expressed at lower levels in the medial amygdala (MeA) and bed nucleus of the stria terminalis (BNST), but the regulation and function of Kiss1 there is poorly understood. γ-Aminobutyric acid (GABA) also regulates reproduction, and female GABAB1 receptor knockout (KO) mice have compromised fertility. However, the interaction between GABAB receptors and Kiss1 neurons is unknown. Here, using double-label in situ hybridization, we first demonstrated that a majority of hypothalamic Kiss1 neurons coexpress GABAB1 subunit, a finding also confirmed for most MeA Kiss1 neurons. Yet, despite known reproductive impairments in GABAB1KO mice, Kiss1 expression in the anteroventral periventricular and arcuate nuclei, assessed by both in situ hybridization and real-time PCR, was identical between adult wild-type and GABAB1KO mice. Surprisingly, however, Kiss1 levels in the BNST and MeA, as well as the lateral septum (a region normally lacking Kiss1 expression), were dramatically increased in both GABAB1KO males and females. The increased Kiss1 levels in extrahypothalamic regions were not caused by elevated sex steroids (which can increase Kiss1 expression), because circulating estradiol and testosterone were equivalent between genotypes. Interestingly, increased Kiss1 expression was not detected in the MeA or BNST in prepubertal KO mice of either sex, indicating that the enhancements in extrahypothalamic Kiss1 levels initiate during/after puberty. These findings suggest that GABAB signaling may normally directly or indirectly inhibit Kiss1 expression, particularly in the BNST and MeA, and highlight the importance of studying kisspeptin populations outside the hypothalamus.

Background

Our understanding of the complex relationship between schizophrenia symptomatology and etiological factors can be improved by studying brain-based correlates of schizophrenia. Research showed that impairments in value processing and executive functioning, which have been associated with prefrontal brain areas [particularly the medial orbitofrontal cortex (MOFC)], are linked to negative symptoms. Here we tested the hypothesis that MOFC thickness is associated with negative symptom severity.

Methods

This study included 1985 individuals with schizophrenia from 17 research groups around the world contributing to the ENIGMA Schizophrenia Working Group. Cortical thickness values were obtained from T1-weighted structural brain scans using FreeSurfer. A meta-analysis across sites was conducted over effect sizes from a model predicting cortical thickness by negative symptom score (harmonized Scale for the Assessment of Negative Symptoms or Positive and Negative Syndrome Scale scores).

Results

Meta-analytical results showed that left, but not right, MOFC thickness was significantly associated with negative symptom severity (β std = -0.075; p = 0.019) after accounting for age, gender, and site. This effect remained significant (p = 0.036) in a model including overall illness severity. Covarying for duration of illness, age of onset, antipsychotic medication or handedness weakened the association of negative symptoms with left MOFC thickness. As part of a secondary analysis including 10 other prefrontal regions further associations in the left lateral orbitofrontal gyrus and pars opercularis emerged.

Conclusions

Using an unusually large cohort and a meta-analytical approach, our findings point towards a link between prefrontal thinning and negative symptom severity in schizophrenia. This finding provides further insight into the relationship between structural brain abnormalities and negative symptoms in schizophrenia.

Objective

Based on the role of the superior temporal gyrus (STG) in auditory processing, language comprehension and self-monitoring, this study aimed to investigate the relationship between STG cortical thickness and positive symptom severity in schizophrenia.

Method

This prospective meta-analysis includes data from 1987 individuals with schizophrenia collected at seventeen centres around the world that contribute to the ENIGMA Schizophrenia Working Group. STG thickness measures were extracted from T1-weighted brain scans using FreeSurfer. The study performed a meta-analysis of effect sizes across sites generated by a model predicting left or right STG thickness with a positive symptom severity score (harmonized SAPS or PANSS-positive scores), while controlling for age, sex and site. Secondary models investigated relationships between antipsychotic medication, duration of illness, overall illness severity, handedness and STG thickness.

Results

Positive symptom severity was negatively related to STG thickness in both hemispheres (left: β_std = -0.052; P = 0.021; right: β_std = -0.073; P = 0.001) when statistically controlling for age, sex and site. This effect remained stable in models including duration of illness, antipsychotic medication or handedness.

Conclusion

Our findings further underline the important role of the STG in hallmark symptoms in schizophrenia. These findings can assist in advancing insight into symptom-relevant pathophysiological mechanisms in schizophrenia.

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).

Background

Schizophrenia and bipolar disorder share genetic liability, and some structural brain abnormalities are common to both conditions. First-degree relatives of patients with schizophrenia (FDRs-SZ) show similar brain abnormalities to patients, albeit with smaller effect sizes. Imaging findings in first-degree relatives of patients with bipolar disorder (FDRs-BD) have been inconsistent in the past, but recent studies report regionally greater volumes compared with control subjects.

Methods

We performed a meta-analysis of global and subcortical brain measures of 6008 individuals (1228 FDRs-SZ, 852 FDRs-BD, 2246 control subjects, 1016 patients with schizophrenia, 666 patients with bipolar disorder) from 34 schizophrenia and/or bipolar disorder family cohorts with standardized methods. Analyses were repeated with a correction for intracranial volume (ICV) and for the presence of any psychopathology in the relatives and control subjects.

Results

FDRs-BD had significantly larger ICV (d = +0.16, q < .05 corrected), whereas FDRs-SZ showed smaller thalamic volumes than control subjects (d = -0.12, q < .05 corrected). ICV explained the enlargements in the brain measures in FDRs-BD. In FDRs-SZ, after correction for ICV, total brain, cortical gray matter, cerebral white matter, cerebellar gray and white matter, and thalamus volumes were significantly smaller; the cortex was thinner (d < -0.09, q < .05 corrected); and third ventricle was larger (d = +0.15, q < .05 corrected). The findings were not explained by psychopathology in the relatives or control subjects.

Conclusions

Despite shared genetic liability, FDRs-SZ and FDRs-BD show a differential pattern of structural brain abnormalities, specifically a divergent effect in ICV. This may imply that the neurodevelopmental trajectories leading to brain anomalies in schizophrenia or bipolar disorder are distinct.

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.

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.

Background

The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group.

Methods

The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11-78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10-87 years; 53% male) assessed with standardized methods at 39 centers worldwide.

Results

Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset.

Conclusions

The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia.