Intervention strategies in adolescents at ultra high-risk (UHR) for psychosis are promising for reducing conversion to overt illness, but have only limited impact on functional outcome. Recent studies suggest that cognition does not further decline during the UHR stage. As social and cognitive impairments typically develop before the first psychotic episode and even years before the UHR stage, prevention should also start much earlier in the groups at risk for schizophrenia and other psychiatric disorders. Early intervention strategies could aim to improve stress resilience, optimize brain maturation, and prevent or alleviate adverse environmental circumstances. These strategies should urgently be tested for efficacy: the prevalence of ~1% implies that yearly ~22 in every 100,000 people develop overt symptoms of this illness, despite the fact that for many of them-e.g., children with an affected first-degree family member or carriers of specific genetic variants-increased risk was already identifiable early in life. Our current ability to recognize several risk groups at an early age not only provides an opportunity, but also implies a clinical imperative to act. Time is pressing to investigate preventive interventions in high-risk children to mitigate or prevent the development of schizophrenia and related psychiatric disorders.

CONTEXT:Dietary interventions such as restrictive diets or supplements are common treatments for young people with autism spectrum disorder (ASD). Evidence for the efficacy of these interventions is still controversial. OBJECTIVE:To assess the efficacy of specific dietary interventions on symptoms, functions, and clinical domains in subjects with ASD by using a meta-analytic approach. DATA SOURCES:Ovid Medline, PsycINFO, Embase databases. STUDY SELECTION:We selected placebo-controlled, double-blind, randomized clinical trials assessing the efficacy of dietary interventions in ASD published from database inception through September 2017. DATA EXTRACTION:Outcome variables were subsumed under 4 clinical domains and 17 symptoms and/or functions groups. Hedges' adjusted g values were used as estimates of the effect size of each dietary intervention relative to placebo. RESULTS:In this meta-analysis, we examined 27 double-blind, randomized clinical trials, including 1028 patients with ASD: 542 in the intervention arms and 486 in the placebo arms. Participant-weighted average age was 7.1 years. Participant-weighted average intervention duration was 10.6 weeks. Dietary supplementation (including omega-3, vitamin supplementation, and/or other supplementation), omega-3 supplementation, and vitamin supplementation were more efficacious than the placebo at improving several symptoms, functions, and clinical domains. Effect sizes were small (mean Hedges' g for significant analyses was 0.31), with low statistical heterogeneity and low risk of publication bias. LIMITATIONS:Methodologic heterogeneity among the studies in terms of the intervention, clinical measures and outcomes, and sample characteristics. CONCLUSIONS:This meta-analysis does not support nonspecific dietary interventions as treatment of ASD but suggests a potential role for some specific dietary interventions in the management of some symptoms, functions, and clinical domains in patients with ASD.

Background

Epidemiological and clinical evidence points to cancer as a comorbidity in people with autism spectrum disorders (ASD). A significant overlap of genes and biological processes between both diseases has also been reported.

Methods

Here, for the first time, we compared the gene expression profiles of ASD frontal cortex tissues and 22 cancer types obtained by differential expression meta-analysis and report gene, pathway, and drug set-based overlaps between them.

Results

Four cancer types (brain, thyroid, kidney, and pancreatic cancers) presented a significant overlap in gene expression deregulations in the same direction as ASD whereas two cancer types (lung and prostate cancers) showed differential expression profiles significantly deregulated in the opposite direction from ASD. Functional enrichment and LINCS L1000 based drug set enrichment analyses revealed the implication of several biological processes and pathways that were affected jointly in both diseases, including impairments of the immune system, and impairments in oxidative phosphorylation and ATP synthesis among others. Our data also suggest that brain and kidney cancer have patterns of transcriptomic dysregulation in the PI3K/AKT/MTOR axis that are similar to those found in ASD.

Conclusions

Comparisons of ASD and cancer differential gene expression meta-analysis results suggest that brain, kidney, thyroid, and pancreatic cancers are candidates for direct comorbid associations with ASD. On the other hand, lung and prostate cancers are candidates for inverse comorbid associations with ASD. Joint perturbations in a set of specific biological processes underlie these associations which include several pathways previously implicated in both cancer and ASD encompassing immune system alterations, impairments of energy metabolism, cell cycle, and signaling through PI3K and G protein-coupled receptors among others. These findings could help to explain epidemiological observations pointing towards direct and inverse comorbid associations between ASD and specific cancer types and depict a complex scenario regarding the molecular patterns of association between ASD and cancer.

22q11.2 deletion syndrome (22q11DS)-a neurodevelopmental condition caused by a hemizygous deletion on chromosome 22-is associated with an elevated risk of psychosis and other developmental brain disorders. Prior single-site diffusion magnetic resonance imaging (dMRI) studies have reported altered white matter (WM) microstructure in 22q11DS, but small samples and variable methods have led to contradictory results. Here we present the largest study ever conducted of dMRI-derived measures of WM microstructure in 22q11DS (334 22q11.2 deletion carriers and 260 healthy age- and sex-matched controls; age range 6-52 years). Using harmonization protocols developed by the ENIGMA-DTI working group, we identified widespread reductions in mean, axial and radial diffusivities in 22q11DS, most pronounced in regions with major cortico-cortical and cortico-thalamic fibers: the corona radiata, corpus callosum, superior longitudinal fasciculus, posterior thalamic radiations, and sagittal stratum (Cohen's d's ranging from -0.9 to -1.3). Only the posterior limb of the internal capsule (IC), comprised primarily of corticofugal fibers, showed higher axial diffusivity in 22q11DS. 22q11DS patients showed higher mean fractional anisotropy (FA) in callosal and projection fibers (IC and corona radiata) relative to controls, but lower FA than controls in regions with predominantly association fibers. Psychotic illness in 22q11DS was associated with more substantial diffusivity reductions in multiple regions. Overall, these findings indicate large effects of the 22q11.2 deletion on WM microstructure, especially in major cortico-cortical connections. Taken together with findings from animal models, this pattern of abnormalities may reflect disrupted neurogenesis of projection neurons in outer cortical layers.

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).

We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain.