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Schizophrenia is increasingly recognized as a disorder of distributed neural dynamics, but the molecular and genetic contributions are poorly understood. Recent work highlights a role for altered N-methyl-d-aspartate (NMDA) receptor signaling and related impairments in the excitation-inhibitory balance and synchrony of large-scale neural networks. Here, we combined a pharmacological intervention with novel techniques from dynamic network neuroscience applied to functional magnetic resonance imaging (fMRI) to identify alterations in the dynamic reconfiguration of brain networks related to schizophrenia genetic risk and NMDA receptor hypofunction. We quantified "network flexibility," a measure of the dynamic reconfiguration of the community structure of time-variant brain networks during working memory performance. Comparing 28 patients with schizophrenia, 37 unaffected first-degree relatives, and 139 healthy controls, we detected significant differences in network flexibility [F(2,196) = 6.541, P = 0.002] in a pattern consistent with the assumed genetic risk load of the groups (highest for patients, intermediate for relatives, and lowest for controls). In an observer-blinded, placebo-controlled, randomized, cross-over pharmacological challenge study in 37 healthy controls, we further detected a significant increase in network flexibility as a result of NMDA receptor antagonism with 120 mg dextromethorphan [F(1,34) = 5.291, P = 0.028]. Our results identify a potential dynamic network intermediate phenotype related to the genetic liability for schizophrenia that manifests as altered reconfiguration of brain networks during working memory. The phenotype appears to be influenced by NMDA receptor antagonism, consistent with a critical role for glutamate in the temporal coordination of neural networks and the pathophysiology of schizophrenia., Competing Interests: A.M.-L. received consultancy fees from Astra Zeneca, Elsevier, F. Hoffmann–La Roche, the Gerson Lehrman Group, The Lundbeck Foundation, Outcome Europe Sárl, Outcome Sciences, Roche Pharma, Servier International, and Thieme Verlag, and lecture fees, including the travel fees, from Abbott, Astra Zeneca, Aula Médica Congresos, Badische Anilin- & Soda-Fabrik, Groupo Ferrer International, Janssen–Cilag, Lilly Deutschland, Landschaftsverband Rheinland Klinikum Düsseldorf, Servier Deutschland, and Otsuka Pharmaceuticals. M.Z. received scientific funding from Bristol–Myers Squibb and Servier; speaker and travel grants were provided from Pfizer Pharma GmbH, Bristol–Myers Squibb Pharmaceuticals, Otsuka, Servier, Lundbeck, Janssen–Cilag, Roche, Ferrer, and Trommsdorff.

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.

The human brain's capacity for cognitive function is thought to depend on coordinated activity in sparsely connected, complex networks organized over many scales of space and time. Recent work has demonstrated that human brain networks constructed from neuroimaging data have economical small-world properties that confer high efficiency of information processing at relatively low connection cost. However, it has been unclear how the architecture of complex brain networks functioning at different frequencies can be related to behavioral performance on cognitive tasks. Here, we show that impaired accuracy of working memory could be related to suboptimal cost efficiency of brain functional networks operating in the classical beta frequency band, 15-30 Hz. We analyzed brain functional networks derived from magnetoencephalography data recorded during working-memory task performance in 29 healthy volunteers and 28 people with schizophrenia. Networks functioning at higher frequencies had greater global cost efficiency than low-frequency networks in both groups. Superior task performance was positively correlated with global cost efficiency of the beta-band network and specifically with cost efficiency of nodes in left lateral parietal and frontal areas. These results are consistent with biophysical models highlighting the importance of beta-band oscillations for long-distance functional connections in brain networks and with pathophysiological models of schizophrenia as a dysconnection syndrome. More generally, they echo the saying that "less is more": The information processing performance of a network can be enhanced by a sparse or low-cost configuration with disproportionately high efficiency.

The G protein-coupled receptor (GPCR) family is highly diversified and involved in many forms of information processing. SREB2 (GPR85) is the most conserved GPCR throughout vertebrate evolution and is expressed abundantly in brain structures exhibiting high levels of plasticity, e.g., the hippocampal dentate gyrus. Here, we show that SREB2 is involved in determining brain size, modulating diverse behaviors, and potentially in vulnerability to schizophrenia. Mild overexpression of SREB2 caused significant brain weight reduction and ventricular enlargement in transgenic (Tg) mice as well as behavioral abnormalities mirroring psychiatric disorders, e.g., decreased social interaction, abnormal sensorimotor gating, and impaired memory. SREB2 KO mice showed a reciprocal phenotype, a significant increase in brain weight accompanying a trend toward enhanced memory without apparent other behavioral abnormalities. In both Tg and KO mice, no gross malformation of brain structures was observed. Because of phenotypic overlap between SREB2 Tg mice and schizophrenia, we sought a possible link between the two. Minor alleles of two SREB2 SNPs, located in intron 2 and in the 3' UTR, were overtransmitted to schizophrenia patients in a family-based sample and showed an allele load association with reduced hippocampal gray matter volume in patients. Our data implicate SREB2 as a potential risk factor for psychiatric disorders and its pathway as a target for psychiatric therapy.

Disrupted-in-schizophrenia 1 (DISC1) is a promising schizophrenia candidate gene expressed predominantly within the hippocampus. We typed 12 single-nucleotide polymorphisms (SNPs) that covered the DISC1 gene. A three-SNP haplotype [hCV219779 (C)-rs821597 (G)-rs821616 (A)] spanning 83 kb of the gene was associated with schizophrenia in a family-based sample (P = 0.002). A common nonconservative SNP (Ser704Cys) (rs821616) within this haplotype was associated with schizophrenia (P = 0.004). Based on primary expression of DISC1 in hippocampus, we hypothesized that allelic variation at Ser704Cys would have a measurable impact on hippocampal structure and function as assayed via specific hippocampus-related intermediate phenotypes. In addition to overtransmission in schizophrenia, the Ser allele was associated with altered hippocampal structure and function in healthy subjects, including reduced hippocampal gray matter volume and altered engagement of the hippocampus during several cognitive tasks assayed with functional magnetic resonance imaging. These convergent data suggest that allelic variation within DISC1, either at Ser704Cys or haplotypes monitored by it, increases the risk for schizophrenia and that the mechanism of this effect involves structural and functional alterations in the hippocampal formation.

Dopaminergic and glutamatergic systems are critical components responsible for prefrontal signal-to-noise tuning in working memory. Recent functional MRI (fMRI) studies of genetic variation in these systems in catechol-O-methyltransferase (COMT) and in metabotropic glutamate receptor mgluR3 (GRM3). respectively, suggest that these genes influence prefrontal physiological signal- to-noise in humans. Here, using fMRI, we extend these individual gene findings to examine the combined effects of COMT and GRM3 on dissociable components of the frontoparietal working memory network. We observed an apparent epistatic interaction of these two genes on the engagement of prefrontal cortex during working memory. Specifically, the GRM3 genotype putatively associated with suboptimal glutamatergic signaling was significantly associated with inefficient prefrontal engagement and altered prefrontal- parietal coupling on the background of COMT Val-homozygous genotype. Conversely. COMT Met-homozygous background mediated against the effect of GRM3 genotype. These findings extend putative brain dopaminergic and glutamatergic relationships indexed by COMT and GRM3 to a systems-level interaction in human cortical circuits implicated in working memory dysfunction such as in schizophrenia. [ABSTRACT FROM AUTHOR]