Resting-state brain network features associated with short-term skill learning ability in humans and the influence of N-methyl-d-aspartate receptor antagonism.

Graph theoretical functional magnetic resonance imaging (fMRI) studies have demonstrated that brain networks reorganize significantly during motor skill acquisition, yet the associations between motor learning ability, brain network features, and the underlying biological mechanisms remain unclear. In the current study, we applied a visually guided sequential pinch force learning task and graph theoretical analyses to investigate the associations between short-term motor learning ability and resting-state brain network metrics in 60 healthy subjects. We further probed the test-retest reliability (n = 26) and potential effects of the N-methyl-d-aspartate (NMDA) antagonist ketamine (n = 19) in independent healthy volunteers. Our results show that the improvement of motor performance after short-term training was positively correlated with small-worldness (p = 0.032) and global efficiency (p = 0.025), whereas negatively correlated with characteristic path length (p = 0.014) and transitivity (p = 0.025). In addition, using network-based statistics (NBS), we identified a learning ability-associated (p = 0.037) and ketamine-susceptible (p = 0.027) cerebellar-cortical network with fair to good reliability (intraclass correlation coefficient [ICC] > 0.7) and higher functional connectivity in better learners. Our results provide new evidence for the association of intrinsic brain network features with motor learning and suggest a role of NMDA-related glutamatergic processes in learning-associated subnetworks.

Altered DLPFC-Hippocampus Connectivity During Working Memory: Independent Replication and Disorder Specificity of a Putative Genetic Risk Phenotype for Schizophrenia.

Altered connectivity of dorsolateral prefrontal cortex (DLPFC) and hippocampus during working memory is considered an intermediate phenotype for schizophrenia (SCZ), but the relevance for other mental disorders with shared genetic background remains unknown. Here we investigated its presence in unaffected first-degree relatives of patients with bipolar disorder (BD) or major depressive disorder (MDD). Furthermore, we aimed to provide an independent replication of this phenotype in first-degree relatives of SCZ patients. We acquired functional magnetic resonance imaging (fMRI) data from 309 healthy controls and 218 healthy first-degree relatives of index patients with SCZ (n = 62), BD (n = 66) and MDD (n = 90), who completed the n-back working memory paradigm. We observed a significant group effect on DLPFC-hippocampus coupling (PFWE = .031, all P-values region of interest [ROI] corrected). Post hoc comparisons revealed that this effect was driven by the SCZ relatives, who showed a significant increase in the negative functional connectivity of the DLPFC and right hippocampus compared to controls (PFWE = .001), BD relatives (PFWE = .015) and trend-wise also MDD relatives (PFWE = .082). Comparison of BD and MDD relatives to the controls revealed no difference (PFWE-values > .451). Supplementary analyses suggested that the SCZ relatives finding is robust to a range of potential confounds, including structural differences. Our data further support altered DLPFC-hippocampus connectivity during working memory as an intermediate phenotype for SCZ. This suggests that this phenotype is relatively specific to SCZ and does not translate to other genetically related disorders in the mood-psychosis spectrum.

Altered Functional Subnetwork During Emotional Face Processing: A Potential Intermediate Phenotype for Schizophrenia.

IMPORTANCE: Although deficits in emotional processing are prominent in schizophrenia, it has been difficult to identify neural mechanisms related to the genetic risk for this highly heritable illness. Prior studies have not found consistent regional activation or connectivity alterations in first-degree relatives compared with healthy controls, suggesting that a more comprehensive search for connectomic biomarkers is warranted. OBJECTIVES: To identify a potential systems-level intermediate phenotype linked to emotion processing in schizophrenia and to examine the psychological association, task specificity, test-retest reliability, and clinical validity of the identified phenotype. DESIGN, SETTING, AND PARTICIPATIONS: The study was performed in university research hospitals from June 1, 2008, through December 31, 2013. We examined 58 unaffected first-degree relatives of patients with schizophrenia and 94 healthy controls with an emotional face-matching functional magnetic resonance imaging paradigm. Test-retest reliability was analyzed with an independent sample of 26 healthy participants. A clinical association study was performed in 31 patients with schizophrenia and 45 healthy controls. Data analysis was performed from January 1 to September 30, 2014. MAIN OUTCOMES AND MEASURES: Conventional amygdala activity and seeded connectivity measures, graph-based global and local network connectivity measures, Spearman rank correlation, intraclass correlation, and gray matter volumes. RESULTS: Among the 152 volunteers included in the relative-control sample, 58 were unaffected first-degree relatives of patients with schizophrenia (mean [SD] age, 33.29 [12.56]; 38 were women), and 94 were healthy controls without a first-degree relative with mental illness (mean [SD] age, 32.69 [10.09] years; 55 were women). A graph-theoretical connectivity approach identified significantly decreased connectivity in a subnetwork that primarily included the limbic cortex, visual cortex, and subcortex during emotional face processing (cluster-level P corrected for familywise error = .006) in relatives compared with controls. The connectivity of the same subnetwork was significantly decreased in patients with schizophrenia (F = 6.29, P = .01). Furthermore, we found that this subnetwork connectivity measure was negatively correlated with trait anxiety scores (P = .04), test-retest reliable (intraclass correlation coefficient = 0.57), specific to emotional face processing (F = 17.97, P < .001), and independent of gray matter volumes of the identified brain areas (F = 1.84, P = .18). Replicating previous results, no significant group differences were found in face-related amygdala activation and amygdala-anterior cingulate cortex connectivity (P corrected for familywise error =.37 and .11, respectively). CONCLUSIONS AND RELEVANCE: Our results indicate that altered connectivity in a visual-limbic subnetwork during emotional face processing may be a functional connectomic intermediate phenotype for schizophrenia. The phenotype is reliable, task specific, related to trait anxiety, and associated with manifest illness. These data encourage the further investigation of this phenotype in clinical and pharmacologic studies.

Functional connectivity measures as schizophrenia intermediate phenotypes: advances, limitations, and future directions.

The search for quantifiable biological mediators of genetic risk or 'intermediate phenotypes' is an essential strategy in psychiatric neuroscience and a useful tool for exploring the complex relationships between genes, neural circuits and behaviors. In recent years, the examination of connectivity-based intermediate phenotypes has gained increasing popularity in the study of schizophrenia, a brain disorder that manifests in early adulthood and disturbs a wide range of neural network functions. To date, several potential connectivity phenotypes have been identified that link neuroimaging measures of neural circuit interaction to genetic susceptibility for schizophrenia. This paper briefly reviews recent advances, current limitations and future directions in the search for functional connectivity intermediate phenotypes for schizophrenia across different cognitive domains.

Neuroinformatic analyses of common and distinct genetic components associated with major neuropsychiatric disorders.

Major neuropsychiatric disorders are highly heritable, with mounting evidence suggesting that these disorders share overlapping sets of molecular and cellular underpinnings. In the current article we systematically test the degree of genetic commonality across six major neuropsychiatric disorders-attention deficit hyperactivity disorder (ADHD), anxiety disorders (Anx), autistic spectrum disorders (ASD), bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SCZ). We curated a well-vetted list of genes based on large-scale human genetic studies based on the NHGRI catalog of published genome-wide association studies (GWAS). A total of 180 genes were accepted into the analysis on the basis of low but liberal GWAS p-values (<10(-5)). 22% of genes overlapped two or more disorders. The most widely shared subset of genes-common to five of six disorders-included ANK3, AS3MT, CACNA1C, CACNB2, CNNM2, CSMD1, DPCR1, ITIH3, NT5C2, PPP1R11, SYNE1, TCF4, TENM4, TRIM26, and ZNRD1. Using a suite of neuroinformatic resources, we showed that many of the shared genes are implicated in the postsynaptic density (PSD), expressed in immune tissues and co-expressed in developing human brain. Using a translational cross-species approach, we detected two distinct genetic components that were both shared by each of the six disorders; the 1st component is involved in CNS development, neural projections and synaptic transmission, while the 2nd is implicated in various cytoplasmic organelles and cellular processes. Combined, these genetic components account for 20-30% of the genetic load. The remaining risk is conferred by distinct, disorder-specific variants. Our systematic comparative analysis of shared and unique genetic factors highlights key gene sets and molecular processes that may ultimately translate into improved diagnosis and treatment of these debilitating disorders.

Identification of gene ontologies linked to prefrontal-hippocampal functional coupling in the human brain.

Functional interactions between the dorsolateral prefrontal cortex and hippocampus during working memory have been studied extensively as an intermediate phenotype for schizophrenia. Coupling abnormalities have been found in patients, their unaffected siblings, and carriers of common genetic variants associated with schizophrenia, but the global genetic architecture of this imaging phenotype is unclear. To achieve genome-wide hypothesis-free identification of genes and pathways associated with prefrontal-hippocampal interactions, we combined gene set enrichment analysis with whole-genome genotyping and functional magnetic resonance imaging data from 269 healthy German volunteers. We found significant enrichment of the synapse organization and biogenesis gene set. This gene set included known schizophrenia risk genes, such as neural cell adhesion molecule (NRCAM) and calcium channel, voltage-dependent, beta 2 subunit (CACNB2), as well as genes with well-defined roles in neurodevelopmental and plasticity processes that are dysfunctional in schizophrenia and have mechanistic links to prefrontal-hippocampal functional interactions. Our results demonstrate a readily generalizable approach that can be used to identify the neurogenetic basis of systems-level phenotypes. Moreover, our findings identify gene sets in which genetic variation may contribute to disease risk through altered prefrontal-hippocampal functional interactions and suggest a link to both ongoing and developmental synaptic plasticity.

Characterising the plasma-target occupancy relationship of the neurokinin antagonist GSK1144814 with PET.

GSK1144814 is a potent, insurmountable antagonist at human NK1 and NK3 receptors. Understanding the relationship between plasma pharmacokinetics and receptor occupancy in the human brain, was crucial for dose selection in future clinical studies. GSK1144814 occupancy data were acquired in parallel with the first-time-in-human safety and tolerability study. [¹¹C]GR-205171 a selective NK1 receptor PET ligand was used to estimate NK1 occupancy at several time-points following single dose administration of GSK1144814. The time-plasma concentration-occupancy relationship post-single dose administration was assessed, and used to predict the plasma concentration-occupancy relationship following repeat dose administration. Repeat dose predictions were tested in a subsequent cohort of subjects examined following approximately 7 and 14 days dosing with GSK1144814. GSK1144814 was shown to demonstrate a dose-dependent occupancy of the NK1 receptor with an estimated in vivo EC50~0.9 ng/mL in the human brain. A direct relationship was seen between the GSK1144814 plasma concentration and its occupancy of the brain NK1 receptor, indicating that in future clinical trials the occupancy of brain receptors can be accurately inferred from the measured plasma concentration. Our data provided support for the further progression of this compound and have optimised the likely therapeutic dose range.

Thyroid hormone transporter genes and grey matter changes in patients with major depressive disorder and healthy controls.

OBJECTIVE: Several studies have established links between thyroid gland dysfunction and mood disorders, in particular major depressive disorder (MDD). Preliminary evidence also suggests that thyroid hormone gene variants influence grey matter (GM) volume, which is reportedly altered in patients with MDD. This study tested for associations of single nucleotide polymorphisms (SNPs) in two thyroid hormone transporter genes with regional GM volume differences in a large sample population of patients with recurrent MDD and healthy volunteers. METHODS: High-resolution T1-weighted magnetic resonance images were acquired at the Max Planck Institute, Munich, Germany. After quality control procedures were applied to images and genotypes, data for 134 patients and 144 well-matched controls were included in a stringent voxel-based morphometry analysis using non-stationary cluster-based inference. We first tested for associations between 10 candidate SNPs and regional GM volume differences across the combined sample population. We then tested for group-by-genotype interactions (i.e., differential associations determined by group status). RESULTS: No significant associations were found between SNPs and regional GM volume when testing across the combined sample population. However, group-by-genotype interactions for two highly correlated SNPs (rs496549 and rs479640) revealed co-localised association clusters in the left occipital cortex (P-values 0.002 and 0.004, respectively, after full correction for whole brain and multiple SNP testing). The effect magnitudes within the average modulated GM clusters were greater in the control group relative to the MDD group. This study provides supporting evidence to the existing literature that thyroid-related gene variants influence regional GM volume. We propose that future studies should consider neuroimaging phenotypes when investigating the effects of thyroid hormones on brain structure and function.