Background

Error processing and inhibitory control enable the adjustment of behaviors to meet task demands. Functional magnetic resonance imaging studies report brain activation abnormalities in patients with obsessive-compulsive disorder (OCD) during both processes. However, conclusions are limited by inconsistencies in the literature and small sample sizes. Therefore, the aim here was to perform a meta-analysis of the existing literature using unthresholded statistical maps from previous studies.

Methods

A voxelwise seed-based d mapping meta-analysis was performed using t-maps from studies comparing patients with OCD and healthy control subjects (HCs) during error processing and inhibitory control. For the error processing analysis, 239 patients with OCD (120 male; 79 medicated) and 229 HCs (129 male) were included, while the inhibitory control analysis included 245 patients with OCD (120 male; 91 medicated) and 239 HCs (135 male).

Results

Patients with OCD, relative to HCs, showed longer inhibitory control reaction time (standardized mean difference = 0.20, p = .03, 95% confidence interval = 0.016, 0.393) and more inhibitory control errors (standardized mean difference = 0.22, p = .02, 95% confidence interval = 0.039, 0.399). In the brain, patients showed hyperactivation in the bilateral dorsal anterior cingulate cortex, supplementary motor area, and pre-supplementary motor area as well as right anterior insula/frontal operculum and anterior lateral prefrontal cortex during error processing but showed hypoactivation during inhibitory control in the rostral and ventral anterior cingulate cortices and bilateral thalamus/caudate, as well as the right anterior insula/frontal operculum, supramarginal gyrus, and medial orbitofrontal cortex (all seed-based d mapping z value >2, p < .001).

Conclusions

A hyperactive error processing mechanism in conjunction with impairments in implementing inhibitory control may underlie deficits in stopping unwanted compulsive behaviors in the disorder.

Background

The negative symptoms of schizophrenia include deficits in emotional expression and motivation. These deficits are stable over the course of illness and respond poorly to current medications. Previous studies have focused on negative symptoms as a single category; however, individual symptoms might be related to separate neurological disturbances. We analyzed data from the Functional Biomedical Informatics Research Network dataset to explore the relationship between individual negative symptoms and functional brain activity during an auditory oddball task.

Methods

Functional magnetic resonance imaging was conducted on 89 schizophrenia patients and 106 healthy controls during a two-tone auditory oddball task. Blood oxygenation level-dependent (BOLD) signal during the target tone was correlated with severity of five negative symptom domains from the Scale for the Assessment of Negative Symptoms.

Results

The severity of alogia, avolition/apathy and anhedonia/asociality was negatively correlated with BOLD activity in distinct sets of brain regions associated with processing of the target tone, including basal ganglia, thalamus, insular cortex, prefrontal cortex, posterior cingulate and parietal cortex.

Conclusions

Individual symptoms were related to different patterns of functional activation during the oddball task, suggesting that individual symptoms might arise from distinct neural mechanisms. This work has potential to inform interventions that target these symptom-related neural disruptions.

Some individuals with autism spectrum disorder (ASD) carry functional mutations rarely observed in the general population. We explored the genes disrupted by these variants from joint analysis of protein-truncating variants (PTVs), missense variants and copy number variants (CNVs) in a cohort of 63,237 individuals. We discovered 72 genes associated with ASD at false discovery rate (FDR) ≤ 0.001 (185 at FDR ≤ 0.05). De novo PTVs, damaging missense variants and CNVs represented 57.5%, 21.1% and 8.44% of association evidence, while CNVs conferred greatest relative risk. Meta-analysis with cohorts ascertained for developmental delay (DD) (n = 91,605) yielded 373 genes associated with ASD/DD at FDR ≤ 0.001 (664 at FDR ≤ 0.05), some of which differed in relative frequency of mutation between ASD and DD cohorts. The DD-associated genes were enriched in transcriptomes of progenitor and immature neuronal cells, whereas genes showing stronger evidence in ASD were more enriched in maturing neurons and overlapped with schizophrenia-associated genes, emphasizing that these neuropsychiatric disorders may share common pathways to risk.

We present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n = 35,584 total samples, 11,986 with ASD). Using an enhanced analytical framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate of 0.1 or less. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained to have severe neurodevelopmental delay, whereas 53 show higher frequencies in individuals ascertained to have ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In cells from the human cortex, expression of risk genes is enriched in excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory-inhibitory imbalance underlying ASD.

We present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n = 35,584 total samples, 11,986 with ASD). Using an enhanced analytical framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate of 0.1 or less. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained to have severe neurodevelopmental delay, whereas 53 show higher frequencies in individuals ascertained to have ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In cells from the human cortex, expression of risk genes is enriched in excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory-inhibitory imbalance underlying ASD.

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.