Electrophysiological measures from human iPSC-derived neurons are associated with schizophrenia clinical status and predict individual cognitive performance.

Neurons derived from human induced pluripotent stem cells (hiPSCs) have been used to model basic cellular aspects of neuropsychiatric disorders, but the relationship between the emergent phenotypes and the clinical characteristics of donor individuals has been unclear. We analyzed RNA expression and indices of cellular function in hiPSC-derived neural progenitors and cortical neurons generated from 13 individuals with high polygenic risk scores (PRSs) for schizophrenia (SCZ) and a clinical diagnosis of SCZ, along with 15 neurotypical individuals with low PRS. We identified electrophysiological measures in the patient-derived neurons that implicated altered Na+ channel function, action potential interspike interval, and gamma-aminobutyric acid-ergic neurotransmission. Importantly, electrophysiological measures predicted cardinal clinical and cognitive features found in these SCZ patients. The identification of basic neuronal physiological properties related to core clinical characteristics of illness is a potentially critical step in generating leads for novel therapeutics.

Identification and prioritization of gene sets associated with schizophrenia risk by co-expression network analysis in human brain.

Schizophrenia polygenic risk is plausibly manifested by complex transcriptional dysregulation in the brain, involving networks of co-expressed and functionally related genes. The main purpose of this study was to identify and prioritize co-expressed gene sets in a hierarchical manner, based on the strength of the relationships with clinical diagnosis and with polygenic risk for schizophrenia. Weighted Gene Co-expression Network Analysis (WGCNA) was applied to RNA-quality-adjusted DLPFC RNA-Seq data from the LIBD Postmortem Human Brain Repository (90 controls, 74 schizophrenia cases; all Caucasians) to construct co-expression networks and detect "modules" of co-expressed genes. After multiple internal and external validation procedures, modules of selected interest were tested for enrichment in biological ontologies, for association with schizophrenia polygenic risk scores (PRSs) and with diagnosis, and also for enrichment in genes within the significant GWAS loci reported by the Psychiatric Genomic Consortium (PGC2). The association between schizophrenia genetic signals and modules of co-expression converged on one module showing not only a significant association with both diagnosis and PRS but also significant overlap with 36 PGC2 loci genes, deemed the strongest candidates for drug targets. This module contained many genes involved in synaptic signaling and neuroplasticity. Fifty-three PGC2 genes were in modules associated only with diagnosis and 59 in modules unrelated to diagnosis or PRS. Our study highlights complex relationships between gene co-expression networks in the brain and clinical state and polygenic risk for SCZ and provides a strategy for using this information in selecting and prioritizing potentially targetable gene sets for therapeutic drug development.

Correction: iPSC-derived homogeneous populations of developing schizophrenia cortical interneurons have compromised mitochondrial function.

A correction to this paper has been published and can be accessed via a link at the top of the paper.

Schizophrenia risk variants influence multiple classes of transcripts of sorting nexin 19 (SNX19).

Genome-wide association studies (GWAS) have identified many genomic loci associated with risk for schizophrenia, but unambiguous identification of the relationship between disease-associated variants and specific genes, and in particular their effect on risk conferring transcripts, has proven difficult. To better understand the specific molecular mechanism(s) at the schizophrenia locus in 11q25, we undertook cis expression quantitative trait loci (cis-eQTL) mapping for this 2 megabase genomic region using postmortem human brain samples. To comprehensively assess the effects of genetic risk upon local expression, we evaluated multiple transcript features: genes, exons, and exon-exon junctions in multiple brain regions-dorsolateral prefrontal cortex (DLPFC), hippocampus, and caudate. Genetic risk variants strongly associated with expression of SNX19 transcript features that tag multiple rare classes of SNX19 transcripts, whereas they only weakly affected expression of an exon-exon junction that tags the majority of abundant transcripts. The most prominent class of SNX19 risk-associated transcripts is predicted to be overexpressed, defined by an exon-exon splice junction between exons 8 and 10 (junc8.10) and that is predicted to encode proteins that lack the characteristic nexin C terminal domain. Risk alleles were also associated with either increased or decreased expression of multiple additional classes of transcripts. With RACE, molecular cloning, and long read sequencing, we found a number of novel SNX19 transcripts that further define the set of potential etiological transcripts. We explored epigenetic regulation of SNX19 expression and found that DNA methylation at CpG sites near the primary transcription start site and within exon 2 partially mediate the effects of risk variants on risk-associated expression. ATAC sequencing revealed that some of the most strongly risk-associated SNPs are located within a region of open chromatin, suggesting a nearby regulatory element is involved. These findings indicate a potentially complex molecular etiology, in which risk alleles for schizophrenia generate epigenetic alterations and dysregulation of multiple classes of SNX19 transcripts.

iPSC-derived homogeneous populations of developing schizophrenia cortical interneurons have compromised mitochondrial function.

Schizophrenia (SCZ) is a neurodevelopmental disorder. Thus, studying pathogenetic mechanisms underlying SCZ requires studying the development of brain cells. Cortical interneurons (cINs) are consistently observed to be abnormal in SCZ postmortem brains. These abnormalities may explain altered gamma oscillation and cognitive function in patients with SCZ. Of note, currently used antipsychotic drugs ameliorate psychosis, but they are not very effective in reversing cognitive deficits. Characterizing mechanisms of SCZ pathogenesis, especially related to cognitive deficits, may lead to improved treatments. We generated homogeneous populations of developing cINs from 15 healthy control (HC) iPSC lines and 15 SCZ iPSC lines. SCZ cINs, but not SCZ glutamatergic neurons, show dysregulated Oxidative Phosphorylation (OxPhos) related gene expression, accompanied by compromised mitochondrial function. The OxPhos deficit in cINs could be reversed by Alpha Lipoic Acid/Acetyl-L-Carnitine (ALA/ALC) but not by other chemicals previously identified as increasing mitochondrial function. The restoration of mitochondrial function by ALA/ALC was accompanied by a reversal of arborization deficits in SCZ cINs. OxPhos abnormality, even in the absence of any circuit environment with other neuronal subtypes, appears to be an intrinsic deficit in SCZ cINs.

Polygenic risk score increases schizophrenia liability through cognition-relevant pathways.

Cognitive deficit is thought to represent, at least in part, genetic mechanisms of risk for schizophrenia, with recent evidence from statistical modelling of twin data suggesting direct causality from the former to the latter. However, earlier evidence was based on inferences from twin not molecular genetic data and it is unclear how much genetic influence 'passes through' cognition on the way to diagnosis. Thus, we included direct measurements of genetic risk (e.g. schizophrenia polygenic risk scores) in causation models to assess the extent to which cognitive deficit mediates some of the effect of polygenic risk scores on the disorder. Causal models of family data tested relationships among key variables and allowed parsing of genetic variance components. Polygenic risk scores were calculated from summary statistics from the current largest genome-wide association study of schizophrenia and were represented as a latent trait. Cognition was also modelled as a latent trait. Participants were 1313 members of 1078 families: 416 patients with schizophrenia, 290 unaffected siblings, and 607 controls. Modelling supported earlier findings that cognitive deficit has a putatively causal role in schizophrenia. In total, polygenic risk score explained 8.07% [confidence interval (CI) 5.45-10.74%] of schizophrenia risk in our sample. Of this, more than a third (2.71%, CI 2.41-3.85%) of the polygenic risk score influence was mediated through cognition paths, exceeding the direct influence of polygenic risk score on schizophrenia risk (1.43%, CI 0.46-3.08%). The remainder of the polygenic risk score influence (3.93%, CI 2.37-4.48%) reflected reciprocal causation between schizophrenia liability and cognition (e.g. mutual influences in a cyclical manner). Analysis of genetic variance components of schizophrenia liability indicated that 26.87% (CI 21.45-32.57%) was associated with cognition-related pathways not captured by polygenic risk score. The remaining variance in schizophrenia was through pathways other than cognition-related and polygenic risk score. Although our results are based on inference through statistical modelling and do not provide an absolute proof of causality, we find that cognition pathways mediate a significant part of the influence of cumulative genetic risk on schizophrenia. We estimate from our model that 33.51% (CI 27.34-43.82%) of overall genetic risk is mediated through influences on cognition, but this requires further studies and analyses as the genetics of schizophrenia becomes better characterized.

qSVA framework for RNA quality correction in differential expression analysis.

RNA sequencing (RNA-seq) is a powerful approach for measuring gene expression levels in cells and tissues, but it relies on high-quality RNA. We demonstrate here that statistical adjustment using existing quality measures largely fails to remove the effects of RNA degradation when RNA quality associates with the outcome of interest. Using RNA-seq data from molecular degradation experiments of human primary tissues, we introduce a method-quality surrogate variable analysis (qSVA)-as a framework for estimating and removing the confounding effect of RNA quality in differential expression analysis. We show that this approach results in greatly improved replication rates (>3×) across two large independent postmortem human brain studies of schizophrenia and also removes potential RNA quality biases in earlier published work that compared expression levels of different brain regions and other diagnostic groups. Our approach can therefore improve the interpretation of differential expression analysis of transcriptomic data from human tissue.

Schizophrenia polygenic risk score predicts mnemonic hippocampal activity.

The use of polygenic risk scores has become a practical translational approach to investigating the complex genetic architecture of schizophrenia, but the link between polygenic risk scores and pathophysiological components of this disorder has been the subject of limited research. We investigated in healthy volunteers whether schizophrenia polygenic risk score predicts hippocampal activity during simple memory encoding, which has been proposed as a risk-associated intermediate phenotype of schizophrenia. We analysed the relationship between polygenic risk scores and hippocampal activity in a discovery sample of 191 unrelated healthy volunteers from the USA and in two independent replication samples of 76 and 137 healthy unrelated participants from Europe and the USA, respectively. Polygenic risk scores for each individual were calculated as the sum of the imputation probability of reference alleles weighted by the natural log of odds ratio from the recent schizophrenia genome-wide association study. We examined hippocampal activity during simple memory encoding of novel visual stimuli assessed using blood oxygen level-dependent functional MRI. Polygenic risk scores were significantly associated with hippocampal activity in the discovery sample [P = 0.016, family-wise error (FWE) corrected within Anatomical Automatic Labeling (AAL) bilateral hippocampal-parahippocampal mask] and in both replication samples (P = 0.033, FWE corrected within AAL right posterior hippocampal-parahippocampal mask in Bari sample, and P = 0.002 uncorrected in the Duke Neurogenetics Study sample). The relationship between polygenic risk scores and hippocampal activity was consistently negative, i.e. lower hippocampal activity in individuals with higher polygenic risk scores, consistent with previous studies reporting decreased hippocampal-parahippocampal activity during declarative memory tasks in patients with schizophrenia and in their healthy siblings. Polygenic risk scores accounted for more than 8% of variance in hippocampal activity during memory encoding in discovery sample. We conclude that polygenic risk scores derived from the most recent schizophrenia genome-wide association study predict significant variability in hippocampal activity during memory encoding in healthy participants. Our findings validate mnemonic hippocampal activity as a genetic risk associated intermediate phenotype of schizophrenia, indicating that the aggregate neurobiological effect of schizophrenia risk alleles converges on this pattern of neural activity.awy004media15749593779001.

Multi-Trait Analysis of GWAS and Biological Insights Into Cognition: A Response to Hill (2018).

Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84-88) presented a critique of our recently published paper in Cell Reports entitled 'Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets' (Lam et al., Cell Reports, Vol. 21, 2017, 2597-2613). Specifically, Hill offered several interrelated comments suggesting potential problems with our use of a new analytic method called Multi-Trait Analysis of GWAS (MTAG) (Turley et al., Nature Genetics, Vol. 50, 2018, 229-237). In this brief article, we respond to each of these concerns. Using empirical data, we conclude that our MTAG results do not suffer from 'inflation in the FDR [false discovery rate]', as suggested by Hill (Twin Research and Human Genetics, Vol. 21, 2018, 84-88), and are not 'more relevant to the genetic contributions to education than they are to the genetic contributions to intelligence'.

Genomic structure and expression of the human serotonin 2A receptor gene (HTR2A) locus: identification of novel HTR2A and antisense (HTR2A-AS1) exons.

BACKGROUND: The serotonin 2A receptor is widely implicated in genetic association studies and remains an important drug target for psychiatric, neurological, and cardiovascular conditions. RNA sequencing redefined the architecture of the serotonin 2A receptor gene (HTR2A), revealing novel mRNA transcript isoforms utilizing unannotated untranslated regions of the gene. Expression of these untranslated regions is modulated by common single nucleotide polymorphisms (SNPs), namely rs6311. Previous studies did not fully capture the complexity of the sense- and antisense-encoded transcripts with respect to novel exons in the HTR2A gene locus. Here, we comprehensively catalogued exons and RNA isoforms for both HTR2A and HTR2A-AS1 using RNA-Seq from human prefrontal cortex and multiple mouse tissues. We subsequently tested associations between expression of newfound gene features and common SNPs in humans. RESULTS: We find that the human HTR2A gene spans ~66 kilobases and consists of 7, rather than 4 exons. Furthermore, the revised human HTR2A-AS1 gene spans ~474 kilobases and consists of 18, rather than 3 exons. Three HTR2A exons directly overlap with HTR2A-AS1 exons, suggesting potential for complementary nucleotide interactions. The repertoire of possible mouse Htr2a splice isoforms is remarkably similar to humans and we also find evidence for overlapping sense-antisense transcripts in the same relative positions as the human transcripts. rs6311 and SNPs in high linkage disequilibrium are associated with HTR2A-AS1 expression, in addition to previously described associations with expression of the extended 5' untranslated region of HTR2A. CONCLUSIONS: Our proposed HTR2A and HTR2A-AS1 gene structures dramatically differ from current annotations, now including overlapping exons on the sense and anti-sense strands. We also find orthologous transcript isoforms expressed in mice, providing opportunities to elucidate the biological roles of the human isoforms using a model system. Associations between rs6311 and expression of HTR2A and HTR2A-AS1 suggest this polymorphism is capable of modulating the expression of the sense or antisense transcripts. Still unclear is whether these SNPs act directly on the expression of the sense or antisense transcripts and whether overlapping exons are capable of interacting through complimentary base-pairing. Additional studies are necessary to determine the extent and nature of interactions between the SNPs and the transcripts prior to interpreting these findings in the context of phenotypes associated with HTR2A.

Characteristics of the cation cotransporter NKCC1 in human brain: alternate transcripts, expression in development, and potential relationships to brain function and schizophrenia.

Early in development, GABA, an inhibitory neurotransmitter in adults, is excitatory. NKCC1 (SLC12A2) encodes one of two cation chloride cotransporters mediating the conversion of GABA from excitatory to inhibitory. Using 3' and 5' RACE and PCR, we verified previously characterized alternative transcripts of NKCC1a (1-27) and NKCC1b (1-27(Δ21)), identified new NKCC1 transcripts, and explored their expression patterns during human prefrontal cortical development. A novel ultra-short transcript (1-2a) was expressed preferentially in the fetus. Expression of NKCC1b and 1-2a were decreased in schizophrenia compared with controls (NKCC1b: 0.8-fold decrease, p = 0.013; 1-2a: 0.8-fold decrease, p = 0.006). Furthermore, the expression of NKCC1b was associated with NKCC1 polymorphism rs3087889. The minor allele at rs3087889, associated with reduced NKCC1b expression (homozygous for major allele: N = 37; homozygous for minor allele: N = 15; 1.5-fold decrease; p < 0.01), was also associated with a modest increase in schizophrenia risk in a case-control sample (controls: N = 435; cases: N = 397, OR = 1.5). This same allele was then found associated with cognitive (n = 369) and fMRI (n = 313) intermediate phenotypes associated with schizophrenia-working memory (Cohen's d = 0.35), global cognition or g (d = 0.18), and prefrontal inefficiency (d = 0.36) as measured by BOLD fMRI during a working memory task. Together, these preclinical and clinical results suggest that variation in NKCC1 may increase risk for schizophrenia via alterations of mRNA expression at the molecular level and impairment of optimal prefrontal function at the macro or systems level.

Neuregulin 1-ErbB4-PI3K signaling in schizophrenia and phosphoinositide 3-kinase-p110δ inhibition as a potential therapeutic strategy.

Neuregulin 1 (NRG1) and ErbB4, critical neurodevelopmental genes, are implicated in schizophrenia, but the mediating mechanisms are unknown. Here we identify a genetically regulated, pharmacologically targetable, risk pathway associated with schizophrenia and with ErbB4 genetic variation involving increased expression of a PI3K-linked ErbB4 receptor (CYT-1) and the phosphoinositide 3-kinase subunit, p110δ (PIK3CD). In human lymphoblasts, NRG1-mediated phosphatidyl-inositol,3,4,5 triphosphate [PI(3,4,5)P3] signaling is predicted by schizophrenia-associated ErbB4 genotype and PIK3CD levels and is impaired in patients with schizophrenia. In human brain, the same ErbB4 genotype again predicts increased PIK3CD expression. Pharmacological inhibition of p110δ using the small molecule inhibitor, IC87114, blocks the effects of amphetamine in a mouse pharmacological model of psychosis and reverses schizophrenia-related phenotypes in a rat neonatal ventral hippocampal lesion model. Consistent with these antipsychotic-like properties, IC87114 increases AKT phosphorylation in brains of treated mice, implicating a mechanism of action. Finally, in two family-based genetic studies, PIK3CD shows evidence of association with schizophrenia. Our data provide insight into a mechanism of ErbB4 association with schizophrenia; reveal a previously unidentified biological and disease link between NRG1-ErbB4, p110δ, and AKT; and suggest that p110δ is a previously undescribed therapeutic target for the treatment of psychiatric disorders.

Independent evidence for an association between general cognitive ability and a genetic locus for educational attainment.

Cognitive deficits and reduced educational achievement are common in psychiatric illness; understanding the genetic basis of cognitive and educational deficits may be informative about the etiology of psychiatric disorders. A recent, large genome-wide association study (GWAS) reported a genome-wide significant locus for years of education, which subsequently demonstrated association to general cognitive ability ("g") in overlapping cohorts. The current study was designed to test whether GWAS hits for educational attainment are involved in general cognitive ability in an independent, large-scale collection of cohorts. Using cohorts in the Cognitive Genomics Consortium (COGENT; up to 20,495 healthy individuals), we examined the relationship between g and variants associated with educational attainment. We next conducted meta-analyses with 24,189 individuals with neurocognitive data from the educational attainment studies, and then with 53,188 largely independent individuals from a recent GWAS of cognition. A SNP (rs1906252) located at chromosome 6q16.1, previously associated with years of schooling, was significantly associated with g (P = 1.47 × 10(-4) ) in COGENT. The first joint analysis of 43,381 non-overlapping individuals for this a priori-designated locus was strongly significant (P = 4.94 × 10(-7) ), and the second joint analysis of 68,159 non-overlapping individuals was even more robust (P = 1.65 × 10(-9) ). These results provide independent replication, in a large-scale dataset, of a genetic locus associated with cognitive function and education. As sample sizes grow, cognitive GWAS will identify increasing numbers of associated loci, as has been accomplished in other polygenic quantitative traits, which may be relevant to psychiatric illness.

scMeFormer: a transformer-based deep learning model for imputing DNA methylation states in single cells enhances the detection of epigenetic alterations in schizophrenia.

DNA methylation (DNAm), a crucial epigenetic mark, plays a key role in gene regulation, mammalian development, and various human diseases. Single-cell technologies enable the profiling of DNAm states at cytosines within the DNA sequence of individual cells, but they often suffer from limited coverage of CpG sites. In this study, we introduce scMeFormer, a transformer-based deep learning model designed to impute DNAm states for each CpG site in single cells. Through comprehensive evaluations, we demonstrate the superior performance of scMeFormer compared to alternative models across four single-nucleus DNAm datasets generated by distinct technologies. Remarkably, scMeFormer exhibits high-fidelity imputation, even when dealing with significantly reduced coverage, as low as 10% of the original CpG sites. Furthermore, we applied scMeFormer to a single-nucleus DNAm dataset generated from the prefrontal cortex of four schizophrenia patients and four neurotypical controls. This enabled the identification of thousands of differentially methylated regions associated with schizophrenia that would have remained undetectable without imputation and added granularity to our understanding of epigenetic alterations in schizophrenia within specific cell types. Our study highlights the power of deep learning in imputing DNAm states in single cells, and we expect scMeFormer to be a valuable tool for single-cell DNAm studies.

Expression of GABA signaling molecules KCC2, NKCC1, and GAD1 in cortical development and schizophrenia.

GABA signaling molecules are critical for both human brain development and the pathophysiology of schizophrenia. We examined the expression of transcripts derived from three genes related to GABA signaling [GAD1 (GAD67 and GAD25), SLC12A2 (NKCC1), and SLC12A5 (KCC2)] in the prefrontal cortex (PFC) and hippocampal formation of a large cohort of nonpsychiatric control human brains (n = 240) across the lifespan (from fetal week 14 to 80 years) and in patients with schizophrenia (n = 30-31), using quantitative RT-PCR. We also examined whether a schizophrenia risk-associated promoter SNP in GAD1 (rs3749034) is related to expression of these transcripts. Our studies revealed that development and maturation of both the PFC and hippocampal formation are characterized by progressive switches in expression from GAD25 to GAD67 and from NKCC1 to KCC2. Previous studies have demonstrated that the former leads to GABA synthesis, and the latter leads to switching from excitatory to inhibitory neurotransmission. In the hippocampal formation, GAD25/GAD67 and NKCC1/KCC2 ratios are increased in patients with schizophrenia, reflecting a potentially immature GABA physiology. Remarkably, GAD25/GAD67 and NKCC1/KCC2 expression ratios are associated with rs3749034 genotype, with risk alleles again predicting a relatively less mature pattern. These findings suggest that abnormalities in GABA signaling critical to brain development contribute to genetic risk for schizophrenia.

Analysis of somatic mutations in 131 human brains reveals aging-associated hypermutability.

We analyzed 131 human brains (44 neurotypical, 19 with Tourette syndrome, 9 with schizophrenia, and 59 with autism) for somatic mutations after whole genome sequencing to a depth of more than 200×. Typically, brains had 20 to 60 detectable single-nucleotide mutations, but ~6% of brains harbored hundreds of somatic mutations. Hypermutability was associated with age and damaging mutations in genes implicated in cancers and, in some brains, reflected in vivo clonal expansions. Somatic duplications, likely arising during development, were found in ~5% of normal and diseased brains, reflecting background mutagenesis. Brains with autism were associated with mutations creating putative transcription factor binding motifs in enhancer-like regions in the developing brain. The top-ranked affected motifs corresponded to MEIS (myeloid ectopic viral integration site) transcription factors, suggesting a potential link between their involvement in gene regulation and autism.

Genetic variation in FGF20 modulates hippocampal biology.

We explored the effect of single-nucleotide polymorphisms (SNPs) in the fibroblast growth factor 20 gene (FGF20) associated with risk for Parkinson's disease on brain structure and function in a large sample of healthy young-adult human subjects and also in elderly subjects to look at the interaction between genetic variations and age (N = 237; 116 men; 18-87 years). We analyzed high-resolution anatomical magnetic resonance images using voxel-based morphometry, a quantitative neuroanatomical technique. We also measured FGF20 mRNA expression in postmortem human brain tissue to determine the molecular correlates of these SNPs (N = 108; 72 men; 18-74 years). We found that the T allele carriers of rs12720208 in the 3'-untranslated region had relatively larger hippocampal volume (p = 0.0059) and diminished verbal episodic memory (p = 0.048) and showed steeper decreases of hippocampal volume with normal aging (p = 0.026). In postmortem brain, T allele carriers had greater expression of hippocampal FGF20 mRNA (p = 0.037), consistent with a previously characterized microRNA mechanism. The C allele matches a predicted miR-433 microRNA binding domain, whereas the T allele disrupts it, resulting in higher FGF20 protein translation. The strong FGF20 genetic effects in hippocampus are presumably mediated by activation of the FGFR1 (FGF receptor 1), which is expressed in mammalian brain most abundantly in the hippocampus. These associations, from mRNA expression to brain morphology to cognition and an interaction with aging, confirm a role of FGF20 in human brain structure and function during development and aging.

Genetic variation in AKT1 is linked to dopamine-associated prefrontal cortical structure and function in humans.

AKT1-dependent molecular pathways control diverse aspects of cellular development and adaptation, including interactions with neuronal dopaminergic signaling. If AKT1 has an impact on dopaminergic signaling, then genetic variation in AKT1 would be associated with brain phenotypes related to cortical dopaminergic function. Here, we provide evidence that a coding variation in AKT1 that affects protein expression in human B lymphoblasts influenced several brain measures related to dopaminergic function. Cognitive performance linked to frontostriatal circuitry, prefrontal physiology during executive function, and frontostriatal gray-matter volume on MRI were altered in subjects with the AKT1 variation. Moreover, on neuroimaging measures with a main effect of the AKT1 genotype, there was significant epistasis with a functional polymorphism (Val158Met) in catechol-O-methyltransferase [COMT], a gene that indexes cortical synaptic dopamine. This genetic interaction was consistent with the putative role of AKT1 in dopaminergic signaling. Supportive of an earlier tentative association of AKT1 with schizophrenia, we also found that this AKT1 variant was associated with risk for schizophrenia. These data implicate AKT1 in modulating human prefrontal-striatal structure and function and suggest that the mechanism of this effect may be coupled to dopaminergic signaling and relevant to the expression of psychosis.

Functional polymorphisms in PRODH are associated with risk and protection for schizophrenia and fronto-striatal structure and function.

PRODH, encoding proline oxidase (POX), has been associated with schizophrenia through linkage, association, and the 22q11 deletion syndrome (Velo-Cardio-Facial syndrome). Here, we show in a family-based sample that functional polymorphisms in PRODH are associated with schizophrenia, with protective and risk alleles having opposite effects on POX activity. Using a multimodal imaging genetics approach, we demonstrate that haplotypes constructed from these risk and protective functional polymorphisms have dissociable correlations with structure, function, and connectivity of striatum and prefrontal cortex, impacting critical circuitry implicated in the pathophysiology of schizophrenia. Specifically, the schizophrenia risk haplotype was associated with decreased striatal volume and increased striatal-frontal functional connectivity, while the protective haplotype was associated with decreased striatal-frontal functional connectivity. Our findings suggest a role for functional genetic variation in POX on neostriatal-frontal circuits mediating risk and protection for schizophrenia.

The evolutionarily conserved G protein-coupled receptor SREB2/GPR85 influences brain size, behavior, and vulnerability to schizophrenia.

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.