Gene discovery through imaging genetics: identification of two novel genes associated with schizophrenia

Six drivers of aging identified among genes differentially expressed with age

Many studies have compared gene expression in young and old samples to gain insights on aging, the primary risk factor for most major chronic diseases. However, these studies only describe associations, failing to distinguish drivers of aging from compensatory geroprotective responses and incidental downstream effects. Here, we introduce a workflow to characterize the causal effects of differentially expressed genes on lifespan. First, we performed a meta-analysis of 25 gene expression datasets comprising samples of various tissues from healthy, untreated adult mammals (humans, dogs, and rodents) at two distinct ages. We ranked each gene according to the number of distinct datasets in which the gene was differentially expressed with age in a consistent direction. The top age-upregulated genes were TMEM176A, EFEMP1, CP, and HLA-A; the top age-downregulated genes were CA4, SIAH, SPARC, and UQCR10. Second, the effects of the top ranked genes on lifespan were measured by applying post-developmental RNA interference of the corresponding ortholog in the nematode C. elegans (two trials, with roughly 100 animals per genotype per trial). Out of 10 age-upregulated and 9 age-downregulated genes that were tested, two age-upregulated genes (csp-3/CASP1 and spch-2/RSRC1) and four age-downregulated genes (C42C1.8/DIRC2, ost-1/SPARC, fzy-1/CDC20, and cah-3/CA4) produced significant and reproducible lifespan extension. Notably, the data do not suggest that the direction of differential expression with age is predictive of the effect on lifespan. Our study provides novel insight into the relationship between differential gene expression and aging phenotypes, pilots an unbiased workflow that can be easily repeated and expanded, and pinpoints six genes with evolutionarily conserved, causal roles in the aging process for further study.

Genomic and Reverse Translational Analysis Discloses a Role for Small GTPase RhoA Signaling in the Pathogenesis of Schizophrenia: Rho-Kinase as a Novel Drug Target

Schizophrenia is one of the most serious psychiatric disorders and is characterized by reductions in both brain volume and spine density in the frontal cortex. RhoA belongs to the RAS homolog (Rho) family and plays critical roles in neuronal development and structural plasticity via Rho-kinase. RhoA activity is regulated by GTPase-activating proteins (GAPs) and guanine nucleotide exchange factors (GEFs). Several variants in GAPs and GEFs associated with RhoA have been reported to be significantly associated with schizophrenia. Moreover, several mouse models carrying schizophrenia-associated gene variants involved in RhoA/Rho-kinase signaling have been developed. In this review, we summarize clinical evidence showing that variants in genes regulating RhoA activity are associated with schizophrenia. In the last half of the review, we discuss preclinical evidence indicating that RhoA/Rho-kinase is a potential therapeutic target of schizophrenia. In particular, Rho-kinase inhibitors exhibit anti-psychotic-like effects not only in Arhgap10 S490P/NHEJ mice, but also in pharmacologic models of schizophrenia (methamphetamine- and MK-801-treated mice). Accordingly, we propose that Rho-kinase inhibitors may have antipsychotic effects and reduce cognitive deficits in schizophrenia despite the presence or absence of genetic variants in small GTPase signaling pathways.

microRNA Biology on Brain Development and Neuroimaging Approach

Proper brain development requires the precise coordination and orchestration of various molecular and cellular processes and dysregulation of these processes can lead to neurological diseases. In the past decades, post-transcriptional regulation of gene expression has been shown to contribute to various aspects of brain development and function in the central nervous system. MicroRNAs (miRNAs), short non-coding RNAs, are emerging as crucial players in post-transcriptional gene regulation in a variety of tissues, such as the nervous system. In recent years, miRNAs have been implicated in multiple aspects of brain development, including neurogenesis, migration, axon and dendrite formation, and synaptogenesis. Moreover, altered expression and dysregulation of miRNAs have been linked to neurodevelopmental and psychiatric disorders. Magnetic resonance imaging (MRI) is a powerful imaging technology to obtain high-quality, detailed structural and functional information from the brains of human and animal models in a non-invasive manner. Because the spatial expression patterns of miRNAs in the brain, unlike those of DNA and RNA, remain largely unknown, a whole-brain imaging approach using MRI may be useful in revealing biological and pathological information about the brain affected by miRNAs. In this review, we highlight recent advancements in the research of miRNA-mediated modulation of neuronal processes that are important for brain development and their involvement in disease pathogenesis. Also, we overview each MRI technique, and its technological considerations, and discuss the applications of MRI techniques in miRNA research. This review aims to link miRNA biological study with MRI analytical technology and deepen our understanding of how miRNAs impact brain development and pathology of neurological diseases.

Genomic deciphering of sex determination and unique immune system of a potential model species rare minnow (Gobiocypris rarus)

Gobiocypris rarus is sensitive to environmental pollution, especially to heavy metal and grass carp reovirus (GCRV). Hence, it has potential utility as a biological monitor. Genetic deciphering of its unique immune system will advance our understanding of its unique adaptive strategies, which provide cues for its better application. A de novo genome of rare minnow was obtained, and its sex determination mechanism is ZZ/ZW. We identified several specific mutation genes and specific lost genes of rare minnow, and these might be related to the sensitivity of rare minnow to environmental stimuli. We also analyzed the gene expression level of different organs/tissues and found that several IFIT genes may play key roles in GCRV resistance. In addition, knockout of the gene PCDH10L indicates that PCDH10L affects Pb²⁺-induced mortality in rare minnow. Rare minnow is ready for genetic manipulation and shows potential as an emerging experimental model.

Clustering by phenotype and genome-wide association study in autism

Autism spectrum disorder (ASD) has phenotypically and genetically heterogeneous characteristics. A simulation study demonstrated that attempts to categorize patients with a complex disease into more homogeneous subgroups could have more power to elucidate hidden heritability. We conducted cluster analyses using the k-means algorithm with a cluster number of 15 based on phenotypic variables from the Simons Simplex Collection (SSC). As a preliminary study, we conducted a conventional genome-wide association study (GWAS) with a data set of 597 ASD cases and 370 controls. In the second step, we divided cases based on the clustering results and conducted GWAS in each of the subgroups vs controls (cluster-based GWAS). We also conducted cluster-based GWAS on another SSC data set of 712 probands and 354 controls in the replication stage. In the preliminary study, which was conducted in conventional GWAS design, we observed no significant associations. In the second step of cluster-based GWASs, we identified 65 chromosomal loci, which included 30 intragenic loci located in 21 genes and 35 intergenic loci that satisfied the threshold of P < 5.0 × 10^-8. Some of these loci were located within or near previously reported candidate genes for ASD: CDH5, CNTN5, CNTNAP5, DNAH17, DPP10, DSCAM, FOXK1, GABBR2, GRIN2A5, ITPR1, NTM, SDK1, SNCA, and SRRM4. Of these 65 significant chromosomal loci, rs11064685 located within the SRRM4 gene had a significantly different distribution in the cases vs controls in the replication cohort. These findings suggest that clustering may successfully identify subgroups with relatively homogeneous disease etiologies. Further cluster validation and replication studies are warranted in larger cohorts.

Motor hyperactivation during cognitive tasks: An endophenotype of juvenile myoclonic epilepsy

OBJECTIVE

Juvenile myoclonic epilepsy (JME) is the most common genetic generalized epilepsy syndrome. Myoclonus may relate to motor system hyperexcitability and can be provoked by cognitive activities. To aid genetic mapping in complex neuropsychiatric disorders, recent research has utilized imaging intermediate phenotypes (endophenotypes). Here, we aimed to (a) characterize activation profiles of the motor system during different cognitive tasks in patients with JME and their unaffected siblings, and (b) validate those as endophenotypes of JME.

METHODS

This prospective cross-sectional investigation included 32 patients with JME, 12 unaffected siblings, and 26 controls, comparable for age, sex, handedness, language laterality, neuropsychological performance, and anxiety and depression scores. We investigated patterns of motor system activation during episodic memory encoding and verb generation functional magnetic resonance imaging (fMRI) tasks.

RESULTS

During both tasks, patients and unaffected siblings showed increased activation of motor system areas compared to controls. Effects were more prominent during memory encoding, which entailed hand motion via joystick responses. Subgroup analyses identified stronger activation of the motor cortex in JME patients with ongoing seizures compared to seizure-free patients. Receiver-operating characteristic curves, based on measures of motor activation, accurately discriminated both patients with JME and their siblings from healthy controls (area under the curve: 0.75 and 0.77, for JME and a combined patient-sibling group against controls, respectively; P < .005).

SIGNIFICANCE

Motor system hyperactivation represents a cognitive, domain-independent endophenotype of JME. We propose measures of motor system activation as quantitative traits for future genetic imaging studies in this syndrome.

Identifying progressive imaging genetic patterns via multi-task sparse canonical correlation analysis: a longitudinal study of the ADNI cohort

MOTIVATION

Identifying the genetic basis of the brain structure, function and disorder by using the imaging quantitative traits (QTs) as endophenotypes is an important task in brain science. Brain QTs often change over time while the disorder progresses and thus understanding how the genetic factors play roles on the progressive brain QT changes is of great importance and meaning. Most existing imaging genetics methods only analyze the baseline neuroimaging data, and thus those longitudinal imaging data across multiple time points containing important disease progression information are omitted.

RESULTS

We propose a novel temporal imaging genetic model which performs the multi-task sparse canonical correlation analysis (T-MTSCCA). Our model uses longitudinal neuroimaging data to uncover that how single nucleotide polymorphisms (SNPs) play roles on affecting brain QTs over the time. Incorporating the relationship of the longitudinal imaging data and that within SNPs, T-MTSCCA could identify a trajectory of progressive imaging genetic patterns over the time. We propose an efficient algorithm to solve the problem and show its convergence. We evaluate T-MTSCCA on 408 subjects from the Alzheimer's Disease Neuroimaging Initiative database with longitudinal magnetic resonance imaging data and genetic data available. The experimental results show that T-MTSCCA performs either better than or equally to the state-of-the-art methods. In particular, T-MTSCCA could identify higher canonical correlation coefficients and capture clearer canonical weight patterns. This suggests that T-MTSCCA identifies time-consistent and time-dependent SNPs and imaging QTs, which further help understand the genetic basis of the brain QT changes over the time during the disease progression.

AVAILABILITY AND IMPLEMENTATION

The software and simulation data are publicly available at https://github.com/dulei323/TMTSCCA.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

RSRC1 mutation affects intellect and behaviour through aberrant splicing and transcription, downregulating IGFBP3

RSRC1, whose polymorphism is associated with altered brain function in schizophrenia, is a member of the serine and arginine rich-related protein family. Through homozygosity mapping and whole exome sequencing we show that RSRC1 mutation causes an autosomal recessive syndrome of intellectual disability, aberrant behaviour, hypotonia and mild facial dysmorphism with normal brain MRI. Further, we show that RSRC1 is ubiquitously expressed, and that the RSRC1 mutation triggers nonsense-mediated mRNA decay of the RSRC1 transcript in patients' fibroblasts. Short hairpin RNA (shRNA)-mediated lentiviral silencing and overexpression of RSRC1 in SH-SY5Y cells demonstrated that RSRC1 has a role in alternative splicing and transcription regulation. Transcriptome profiling of RSRC1-silenced cells unravelled specific differentially expressed genes previously associated with intellectual disability, hypotonia and schizophrenia, relevant to the disease phenotype. Protein-protein interaction network modelling suggested possible intermediate interactions by which RSRC1 affects gene-specific differential expression. Patient-derived induced pluripotent stem cells, differentiated into neural progenitor cells, showed expression dynamics similar to the RSRC1-silenced SH-SY5Y model. Notably, patient neural progenitor cells had 9.6-fold downregulated expression of IGFBP3, whose brain expression is affected by MECP2, aberrant in Rett syndrome. Interestingly, Igfbp3-null mice have behavioural impairment, abnormal synaptic function and monoaminergic neurotransmission, likely correlating with the disease phenotype.

Regulators of Rho GTPases in the Nervous System: Molecular Implication in Axon Guidance and Neurological Disorders

One of the fundamental steps during development of the nervous system is the formation of proper connections between neurons and their target cells-a process called neural wiring, failure of which causes neurological disorders ranging from autism to Down's syndrome. Axons navigate through the complex environment of a developing embryo toward their targets, which can be far away from their cell bodies. Successful implementation of neuronal wiring, which is crucial for fulfillment of all behavioral functions, is achieved through an intimate interplay between axon guidance and neural activity. In this review, our focus will be on axon pathfinding and the implication of some of its downstream molecular components in neurological disorders. More precisely, we will talk about axon guidance and the molecules implicated in this process. After, we will briefly review the Rho family of small GTPases, their regulators, and their involvement in downstream signaling pathways of the axon guidance cues/receptor complexes. We will then proceed to the final and main part of this review, where we will thoroughly comment on the implication of the regulators for Rho GTPases-GEFs (Guanine nucleotide Exchange Factors) and GAPs (GTPase-activating Proteins)-in neurological diseases and disorders.

Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions

Major depression is a debilitating psychiatric illness that is typically associated with low mood and anhedonia. Depression has a heritable component that has remained difficult to elucidate with current sample sizes due to the polygenic nature of the disorder. To maximize sample size, we meta-analyzed data on 807,553 individuals (246,363 cases and 561,190 controls) from the three largest genome-wide association studies of depression. We identified 102 independent variants, 269 genes, and 15 genesets associated with depression, including both genes and gene pathways associated with synaptic structure and neurotransmission. An enrichment analysis provided further evidence of the importance of prefrontal brain regions. In an independent replication sample of 1,306,354 individuals (414,055 cases and 892,299 controls), 87 of the 102 associated variants were significant after multiple testing correction. These findings advance our understanding of the complex genetic architecture of depression and provide several future avenues for understanding etiology and developing new treatment approaches.

Fast Multi-Task SCCA Learning with Feature Selection for Multi-Modal Brain Imaging Genetics

Brain imaging genetics studies the genetic basis of brain structures and functions via integrating both genotypic data such as single nucleotide polymorphism (SNP) and imaging quantitative traits (QTs). In this area, both multi-task learning (MTL) and sparse canonical correlation analysis (SCCA) methods are widely used since they are superior to those independent and pairwise univariate analyses. MTL methods generally incorporate a few of QTs and are not designed for feature selection from a large number of QTs; while existing SCCA methods typically employ only one modality of QTs to study its association with SNPs. Both MTL and SCCA encounter computational challenges as the number of SNPs increases. In this paper, combining the merits of MTL and SCCA, we propose a novel multi-task SCCA (MTSCCA) learning framework to identify bi-multivariate associations between SNPs and multi-modal imaging QTs. MTSCCA could make use of the complementary information carried by different imaging modalities. Using the G _2,1-norm regularization, MTSCCA treats all SNPs in the same group together to enforce sparsity at the group level. The l 2 , 1 -norm penalty is used to jointly select features across multiple tasks for SNPs, and across multiple modalities for QTs. A fast optimization algorithm is proposed using the grouping information of SNPs. Compared with conventional SCCA methods, MTSCCA obtains improved performance regarding both correlation coefficients and canonical weights patterns. In addition, our method runs very fast and is easy-to-implement, and thus could provide a powerful tool for genome-wide brain-wide imaging genetic studies.

Genome-wide definition of selective sweeps reveals molecular evidence of trait-driven domestication among elite goat (Capra species) breeds for the production of dairy, cashmere, and meat

Background

The domestication of wild goats and subsequent intensive trait-driven crossing, inbreeding, and selection have led to dramatic phenotypic purification and intermediate breeds for the high-quality production of dairy, cashmere wool, and meat. Genomic resequencing provides a powerful means for the direct identification of trait-associated sequence variations that underlie molecular mechanisms of domestication.

Results

Here, we report our effort to define such variations based on data from domestic goat breeds (Capra aegagrus hircus; five each) selected for dairy, cashmere, and meat production in reference to their wild ancestors, the Sindh ibex (Capra aegagrus blythi; two) and the Markhor (Capra falconeri; two). Using ∼24 million high-quality single nucleotide polymorphisms (SNPs), ∼1.9 million insertions/deletions, and 2,317 copy number variations, we define SNP-desert-associated genes (SAGs), domestic-associated genes (DAGs), and trait-associated genes (TAGs) and attempt to associate them with quantitative trait loci (QTL), domestication, and agronomic traits. A greater majority of SAGs shared by all domestic breeds are classified into Gene Ontology categories of metabolism and cell cycle. DAGs, together with some SAGs, are most relevant to behavior, immunity, and trait specificity. Whereas, TAGs such as growth differentiation factor 5 and fibroblast growth factor 5 for bone and hair growth, respectively, appear to be directly involved in growth regulation.

Conclusions

When investigating the divergence of Capra populations, the sequence variations and candidate function-associated genes we have identified provide valuable molecular markers for trait-driven genetic mapping and breeding.

Common variants on 6q16.2, 12q24.31 and 16p13.3 are associated with major depressive disorder

Accumulating evidence suggests that genetic factors have a role in major depressive disorder (MDD). However, only limited MDD risk loci have been identified so far. Here we perform a meta-analysis (a total of 90,150 MDD cases and 246,603 controls) through combing three genome-wide association studies of MDD, including 23andMe (cases were self-reported with a clinical diagnosis or treatment of depression), CONVERGE (cases were diagnosed using the Composite International Diagnostic Interview) and PGC (cases were diagnosed using direct structured diagnostic interview (by trained interviewers) or clinician-administered DSM-IV checklists). Genetic variants from two previously unreported loci (rs10457592 on 6q16.2 and rs2004910 on 12q24.31) showed significant associations with MDD (P < 5 × 10^-8) in a total of 336,753 subjects. SNPs (a total of 171) with a P < 1 × 10^-7 in the meta-analysis were further replicated in an independent sample (GS:SFHS, 2,659 MDD cases (diagnosed with DSM-IV) and 17,237 controls) and one additional risk locus (rs3785234 on 16p13.3, P = 1.57 × 10^-8) was identified in the combined samples (a total of 92,809 cases and 263,840 controls). Risk variants on the identified risk loci were associated with gene expression in human brain tissues and mRNA expression analysis showed that FBXL4 and RSRC1 were significantly upregulated in brains of MDD cases compared with controls, suggesting that genetic variants may confer risk of MDD through regulating the expression of these two genes. Our study identified three novel risk loci (6q16.2, 12q24.31, and 16p13.3) for MDD and suggested that FBXL4 and RSRC1 may play a role in MDD. Further functional characterization of the identified risk genes may provide new insights for MDD pathogenesis.

Identification of expression quantitative trait loci associated with schizophrenia and affective disorders in normal brain tissue

Schizophrenia and the affective disorders, here comprising bipolar disorder and major depressive disorder, are psychiatric illnesses that lead to significant morbidity and mortality worldwide. Whilst understanding of their pathobiology remains limited, large case-control studies have recently identified single nucleotide polymorphisms (SNPs) associated with these disorders. However, discerning the functional effects of these SNPs has been difficult as the associated causal genes are unknown. Here we evaluated whether schizophrenia and affective disorder associated-SNPs are correlated with gene expression within human brain tissue. Specifically, to identify expression quantitative trait loci (eQTLs), we leveraged disorder-associated SNPs identified from 11 genome-wide association studies with gene expression levels in post-mortem, neurologically-normal tissue from two independent human brain tissue expression datasets (UK Brain Expression Consortium (UKBEC) and Genotype-Tissue Expression (GTEx)). Utilizing stringent multi-region meta-analyses, we identified 2,224 cis-eQTLs associated with expression of 40 genes, including 11 non-coding RNAs. One cis-eQTL, rs16969968, results in a functionally disruptive missense mutation in CHRNA5, a schizophrenia-implicated gene. Importantly, comparing across tissues, we find that blood eQTLs capture < 10% of brain cis-eQTLs. Contrastingly, > 30% of brain-associated eQTLs are significant in tibial nerve. This study identifies putatively causal genes whose expression in region-specific tissue may contribute to the risk of schizophrenia and affective disorders.

RSRC1 and CPZ gene polymorphisms with neuroblastoma susceptibility in Chinese children

Two new neuroblastoma susceptibility loci at 3q25 (RSRC1 rs6441201 G > A) and 4p16 (CPZ rs3796725 T > C and rs3796727 A > G) were identified by a genome-wide association study (GWAS) involving Italians, African Americans and European Americans. In this case-control study with 393 neuroblastoma cases and 812 controls, we investigated the association between these three polymorphisms and neuroblastoma susceptibility in Chinese population. We found that participants harboring the RSRC1 rs6441201A allele were associated with an increased risk of neuroblastoma (AA vs. GG: adjusted OR = 1.55, 95% CI = 1.03-2.34, P = 0.036). No significant association between the CPZ polymorphisms (rs3796725 T > C and rs3796727A > G) and neuroblastoma susceptibility was observed. In conclusion, our results confirm that the RSRC1 rs6441201A allele is associated with neuroblastoma susceptibility in Chinese population.

Rho GTPases in Intellectual Disability: From Genetics to Therapeutic Opportunities

Rho-class small GTPases are implicated in basic cellular processes at nearly all brain developmental steps, from neurogenesis and migration to axon guidance and synaptic plasticity. GTPases are key signal transducing enzymes that link extracellular cues to the neuronal responses required for the construction of neuronal networks, as well as for synaptic function and plasticity. Rho GTPases are highly regulated by a complex set of activating (GEFs) and inactivating (GAPs) partners, via protein:protein interactions (PPI). Misregulated RhoA, Rac1/Rac3 and cdc42 activity has been linked with intellectual disability (ID) and other neurodevelopmental conditions that comprise ID. All genetic evidences indicate that in these disorders the RhoA pathway is hyperactive while the Rac1 and cdc42 pathways are consistently hypoactive. Adopting cultured neurons for in vitro testing and specific animal models of ID for in vivo examination, the endophenotypes associated with these conditions are emerging and include altered neuronal networking, unbalanced excitation/inhibition and altered synaptic activity and plasticity. As we approach a clearer definition of these phenotype(s) and the role of hyper- and hypo-active GTPases in the construction of neuronal networks, there is an increasing possibility that selective inhibitors and activators might be designed via PPI, or identified by screening, that counteract the misregulation of small GTPases and result in alleviation of the cognitive condition. Here we review all knowledge in support of this possibility.

Genetic susceptibility to neuroblastoma: current knowledge and future directions

Neuroblastoma, a malignancy of the developing peripheral nervous system that affects infants and young children, is a complex genetic disease. Over the past two decades, significant progress has been made toward understanding the genetic determinants that predispose to this often lethal childhood cancer. Approximately 1-2% of neuroblastomas are inherited in an autosomal dominant fashion and a combination of co-morbidity and linkage studies has led to the identification of germline mutations in PHOX2B and ALK as the major genetic contributors to this familial neuroblastoma subset. The genetic basis of "sporadic" neuroblastoma is being studied through a large genome-wide association study (GWAS). These efforts have led to the discovery of many common susceptibility alleles, each with modest effect size, associated with the development and progression of sporadic neuroblastoma. More recently, next-generation sequencing efforts have expanded the list of potential neuroblastoma-predisposing mutations to include rare germline variants with a predicted larger effect size. The evolving characterization of neuroblastoma's genetic basis has led to a deeper understanding of the molecular events driving tumorigenesis, more precise risk stratification and prognostics and novel therapeutic strategies. This review details the contemporary understanding of neuroblastoma's genetic predisposition, including recent advances and discusses ongoing efforts to address gaps in our knowledge regarding this malignancy's complex genetic underpinnings.

Heparan Sulfate Proteoglycans as Emerging Players in Synaptic Specificity

Neural circuits consist of distinct neuronal cell types connected in specific patterns. The specificity of these connections is achieved in a series of sequential developmental steps that involve the targeting of neurites, the identification of synaptic partners, and the formation of specific types of synapses. Cell-surface proteins play a critical role in each of these steps. The heparan sulfate proteoglycan (HSPG) family of cell-surface proteins is emerging as a key regulator of connectivity. HSPGs are expressed throughout brain development and play important roles in axon guidance, synapse development and synapse function. New insights indicate that neuronal cell types express unique combinations of HSPGs and HS-modifying enzymes. Furthermore, HSPGs interact with cell type-specific binding partners to mediate synapse development. This suggests that cell type-specific repertoires of HSPGs and specific patterns of HS modifications on the cell surface are required for the development of specific synaptic connections. Genome-wide association studies have linked these proteins to neurodevelopmental and neuropsychiatric diseases. Thus, HSPGs play an important role in the development of specific synaptic connectivity patterns important for neural circuit function, and their dysfunction may be involved in the development of brain disorders.

Proteomic Dissection of Nanotopography-Sensitive Mechanotransductive Signaling Hubs that Foster Neuronal Differentiation in PC12 Cells

Neuronal cells are competent in precisely sensing nanotopographical features of their microenvironment. The perceived microenvironmental information will be “interpreted” by mechanotransductive processes and impacts on neuronal functioning and differentiation. Attempts to influence neuronal differentiation by engineering substrates that mimic appropriate extracellular matrix (ECM) topographies are hampered by the fact that profound details of mechanosensing/-transduction complexity remain elusive. Introducing omics methods into these biomaterial approaches has the potential to provide a deeper insight into the molecular processes and signaling cascades underlying mechanosensing/-transduction but their exigence in cellular material is often opposed by technical limitations of major substrate top-down fabrication methods. Supersonic cluster beam deposition (SCBD) allows instead the bottom-up fabrication of nanostructured substrates over large areas characterized by a quantitatively controllable ECM-like nanoroughness that has been recently shown to foster neuron differentiation and maturation. Exploiting this capacity of SCBD, we challenged mechanosensing/-transduction and differentiative behavior of neuron-like PC12 cells with diverse nanotopographies and/or changes of their biomechanical status, and analyzed their phosphoproteomic profiles in these settings. Versatile proteins that can be associated to significant processes along the mechanotransductive signal sequence, i.e., cell/cell interaction, glycocalyx and ECM, membrane/f-actin linkage and integrin activation, cell/substrate interaction, integrin adhesion complex, actomyosin organization/cellular mechanics, nuclear organization, and transcriptional regulation, were affected. The phosphoproteomic data suggested furthermore an involvement of ILK, mTOR, Wnt, and calcium signaling in these nanotopography- and/or cell mechanics-related processes. Altogether, potential nanotopography-sensitive mechanotransductive signaling hubs participating in neuronal differentiation were dissected.

Neuroimaging genomics in psychiatry-a translational approach

Neuroimaging genomics is a relatively new field focused on integrating genomic and imaging data in order to investigate the mechanisms underlying brain phenotypes and neuropsychiatric disorders. While early work in neuroimaging genomics focused on mapping the associations of candidate gene variants with neuroimaging measures in small cohorts, the lack of reproducible results inspired better-powered and unbiased large-scale approaches. Notably, genome-wide association studies (GWAS) of brain imaging in thousands of individuals around the world have led to a range of promising findings. Extensions of such approaches are now addressing epigenetics, gene–gene epistasis, and gene–environment interactions, not only in brain structure, but also in brain function. Complementary developments in systems biology might facilitate the translation of findings from basic neuroscience and neuroimaging genomics to clinical practice. Here, we review recent approaches in neuroimaging genomics—we highlight the latest discoveries, discuss advantages and limitations of current approaches, and consider directions by which the field can move forward to shed light on brain disorders.

Leveraging genome characteristics to improve gene discovery for putamen subcortical brain structure

Discovering genetic variants associated with human brain structures is an on-going effort. The ENIGMA consortium conducted genome-wide association studies (GWAS) with standard multi-study analytical methodology and identified several significant single nucleotide polymorphisms (SNPs). Here we employ a novel analytical approach that incorporates functional genome annotations (e.g., exon or 5′UTR), total linkage disequilibrium (LD) scores and heterozygosity to construct enrichment scores for improved identification of relevant SNPs. The method provides increased power to detect associated SNPs by estimating stratum-specific false discovery rate (FDR), where strata are classified according to enrichment scores. Applying this approach to the GWAS summary statistics of putamen volume in the ENIGMA cohort, a total of 15 independent significant SNPs were identified (conditional FDR < 0.05). In contrast, 4 SNPs were found based on standard GWAS analysis (P < 5 × 10⁻⁸). These 11 novel loci include GATAD2B, ASCC3, DSCAML1, and HELZ, which are previously implicated in various neural related phenotypes. The current findings demonstrate the boost in power with the annotation-informed FDR method, and provide insight into the genetic architecture of the putamen.

Modulation of Neurogenesis through the Promotion of Energy Production Activity Is behind the Antidepressant-Like Effect of Colonial Green Alga, Botryococcus braunii

Algae have been recognized as important resources providing functional components due to their capacity to exert beneficial effects on health. Therefore, there is increasing interest in investigating the biological activity of algae. In this study, we evaluated the antidepressant-like effect of the administration of 100 mg/kg/day of the ethanol extract of colonial green alga Botryococcus braunii (EEB) for 14 consecutive days in the forced swimming test (FST)-induced depression in imprinting control region (ICR) mice. Imipramine, a commercial antidepressant drug, was used as a positive control. In addition, we investigated the molecular mechanisms underlying the effect of EEB by measuring ATP production and by assessing any change in gene expression at the end of the treatment using real-time polymerase chain reaction (PCR) and microarray assays. We showed that the immobility time in the water-administered control (FST stress) group gradually increased from day 1 to day 14. However, treatment with EEB caused a significant decrease of immobility time in the FST compared with that in the FST stress group. Microarray and real-time PCR results revealed that EEB treatment induced variation in the expression of several genes associated with neurogenesis, energy metabolism, and dopamine synthesis. Interestingly, we revealed that only EEB treatment enhanced the promotion of energy production, while treatment with imipramine was ineffective. Our study provides the first evidence that B. braunii enhances energy production, which may contribute to the modulation of neurogenesis and to the enhancement of dopaminergic function, in turn potentially underlying the antistress- and antidepressant-like effects that we observed.

Rho-GTPase activating-protein 18: a biomarker associated with good prognosis in invasive breast cancer

BACKGROUND

The prognostic value of lymphovascular invasion (LVI) in breast cancer (BC) has been demonstrated in several independent studies. However, identification of driver molecules for LVI remains a challenging task. Large-scale transcriptomic profiling of histologically validated LVI can potentially identify genes that regulate LVI.

METHODS

Integrative bio-informatics analyses of the METABRIC study were performed utilising a subset of strictly defined LVI using histological and immunohistochemical (IHC) criteria. ARHGAP18 was among the top differentially expressed genes between LVI+ and LVI- BC with a 1.8-fold change. The prognostic impact of ARHGAP18 gene expression was assessed in the METABRIC data set (n=1980) and externally validated using the online BC gene expression data sets utilising bc-GenExMiner v4.0 (n=2016). Subsequently, ARHGAP18 protein expression was assessed on a large cohort of invasive BC (n=959) with long-term follow-up using IHC.

RESULTS

Pooled analysis of ARHGAP18 mRNA expression showed that overexpression was associated with better outcome (P<0.001, hazard ratio (HR)=0.82, 95% CI 0.75-0.90). ARHGAP18 protein was expressed in the cytoplasm and nuclei of the tumour cells and its expression was positively associated with good prognostic variables. Lack of cytoplasmic expression showed associations with LVI (P=0.006), epithelial-mesenchymal transition and the HER+ subtype (P=0.01). Loss of nuclear expression was associated with higher grade, HER2+ and high Ki67LI (P=0.001). Cytoplasmic and nuclear expression showed a positive association with improved survival independent of other variables (P=0.01, HR=0.74, 95% CI 0.60-87).

CONCLUSIONS

ARHGAP18 expression at transcriptomic and protein levels is associated with improved patients' outcomes whose deregulation may play a role in tumour progression and the development of LVI in BC. Further assessment of its potential therapeutic value in BC is warranted.

Common variants upstream of MLF1 at 3q25 and within CPZ at 4p16 associated with neuroblastoma

Neuroblastoma is a cancer of the developing sympathetic nervous system that most commonly presents in young children and accounts for approximately 12% of pediatric oncology deaths. Here, we report on a genome-wide association study (GWAS) in a discovery cohort or 2,101 cases and 4,202 controls of European ancestry. We identify two new association signals at 3q25 and 4p16 that replicated robustly in multiple independent cohorts comprising 1,163 cases and 4,396 controls (3q25: rs6441201 combined P = 1.2x10^-11, Odds Ratio 1.23, 95% CI:1.16–1.31; 4p16: rs3796727 combined P = 1.26x10^-12, Odds Ratio 1.30, 95% CI: 1.21–1.40). The 4p16 signal maps within the carboxypeptidase Z (CPZ) gene. The 3q25 signal resides within the arginine/serine-rich coiled-coil 1 (RSRC1) gene and upstream of the myeloid leukemia factor 1 (MLF1) gene. Increased expression of MLF1 was observed in neuroblastoma cells homozygous for the rs6441201 risk allele (P = 0.02), and significant growth inhibition was observed upon depletion of MLF1 (P < 0.0001) in neuroblastoma cells. Taken together, we show that common DNA variants within CPZ at 4p16 and upstream of MLF1 at 3q25 influence neuroblastoma susceptibility and MLF1 likely plays an important role in neuroblastoma tumorigenesis.

Neuroblastoma is an embryonal tumor of the developing sympathetic nervous system that accounts for 12% of childhood cancer deaths. Approximately 1–2% of cases are inherited in an autosomal dominant fashion. These familial cases often harbor germline mutations in ALK or PHOX2B. However, the vast majority of neuroblastomas appear to arise sporadically. We are studying sporadic neuroblastoma through an ongoing genome-wide association study (GWAS). To date, this effort has identified single nucleotide polymorphisms (SNPs) within or upstream of CASC15 and CASC14, BARD1, LMO1, DUSP12, HSD17B12, DDX4/IL31RA, HACE1, LIN28B, and TP53, along with a common copy number variation (CNV) within NBPF23 at chromosome 1q21.1, each being highly associated with neuroblastoma. Here, we report on genome-wide association study (GWAS) comprising 3,264 neuroblastoma patients and 8,598 control subjects. We identify two new association signals at 3q25 and 4p16 (3q25: rs6441201 combined P = 1.2x10^-11, Odds Ratio 1.23, 95% CI:1.16–1.31; 4p16: rs3796727 combined P = 1.26x10^-12, Odds Ratio 1.30, 95% CI: 1.21–1.40). The 3q25 signal resides upstream of the MLF1 gene and the 4p16 signal maps to the CPZ gene. We further demonstrate that neuroblastoma cells homozygous for the risk allele at 3q25 express higher levels of MLF1 and that silencing of MLF1 in neuroblastoma cells results in significant growth inhibition.

Altered learning, memory, and social behavior in type 1 taste receptor subunit 3 knock-out mice are associated with neuronal dysfunction

The type 1 taste receptor member 3 (T1R3) is a G protein-coupled receptor involved in sweet-taste perception. Besides the tongue, the T1R3 receptor is highly expressed in brain areas implicated in cognition, including the hippocampus and cortex. As cognitive decline is often preceded by significant metabolic or endocrinological dysfunctions regulated by the sweet-taste perception system, we hypothesized that a disruption of the sweet-taste perception in the brain could have a key role in the development of cognitive dysfunction. To assess the importance of the sweet-taste receptors in the brain, we conducted transcriptomic and proteomic analyses of cortical and hippocampal tissues isolated from T1R3 knock-out (T1R3KO) mice. The effect of an impaired sweet-taste perception system on cognition functions were examined by analyzing synaptic integrity and performing animal behavior on T1R3KO mice. Although T1R3KO mice did not present a metabolically disrupted phenotype, bioinformatic interpretation of the high-dimensionality data indicated a strong neurodegenerative signature associated with significant alterations in pathways involved in neuritogenesis, dendritic growth, and synaptogenesis. Furthermore, a significantly reduced dendritic spine density was observed in T1R3KO mice together with alterations in learning and memory functions as well as sociability deficits. Taken together our data suggest that the sweet-taste receptor system plays an important neurotrophic role in the extralingual central nervous tissue that underpins synaptic function, memory acquisition, and social behavior.

Genome-wide association study of working memory brain activation

In a population-based genome-wide association (GWA) study of n-back working memory task-related brain activation, we extracted the average percent BOLD signal change (2-back minus 0-back) from 46 regions-of-interest (ROIs) in functional MRI scans from 863 healthy twins and siblings. ROIs were obtained by creating spheres around group random effects analysis local maxima, and by thresholding a voxel-based heritability map of working memory brain activation at 50%. Quality control for test-retest reliability and heritability of ROI measures yielded 20 reliable (r>0.7) and heritable (h2>20%) ROIs. For GWA analysis, the cohort was divided into a discovery (n=679) and replication (n=97) sample. No variants survived the stringent multiple-testing-corrected genome-wide significance threshold (p<4.5×10-9), or were replicated (p<0.0016), but several genes were identified that are worthy of further investigation. A search of 529,379 genomic markers resulted in discovery of 31 independent single nucleotide polymorphisms (SNPs) associated with BOLD signal change at a discovery level of p<1×10-5. Two SNPs (rs7917410 and rs7672408) were associated at a significance level of p<1×10-7. Only one, most strongly affecting BOLD signal change in the left supramarginal gyrus (R2=5.5%), had multiple SNPs associated at p<1×10-5 in linkage disequilibrium with it, all located in and around the BANK1 gene. BANK1 encodes a B-cell-specific scaffold protein and has been shown to negatively regulate CD40-mediated AKT activation. AKT is part of the dopamine-signaling pathway, suggesting a mechanism for the involvement of BANK1 in the BOLD response to working memory. Variants identified here may be relevant to (the susceptibility to) common disorders affecting brain function.

Association of ARHGAP18 polymorphisms with schizophrenia in the Chinese-Han population

Numerous developmental genes have been linked to schizophrenia (SZ) by case-control and genome-wide association studies, suggesting that neurodevelopmental disturbances are major pathogenic mechanisms. However, no neurodevelopmental deficit has been definitively linked to SZ occurrence, likely due to disease heterogeneity and the differential effects of various gene variants across ethnicities. Hence, it is critical to examine linkages in specific ethnic populations, such as Han Chinese. The newly identified RhoGAP ARHGAP18 is likely involved in neurodevelopment through regulation of RhoA/C. Here we describe four single nucleotide polymorphisms (SNPs) in ARHGAP18 associated with SZ across a cohort of >2000 cases and controls from the Han population. Two SNPs, rs7758025 and rs9483050, displayed significant differences between case and control groups both in genotype (P = 0.0002 and P = 7.54×10⁻⁶) and allelic frequencies (P = 4.36×10⁻⁵ and P = 5.98×10⁻⁷), respectively. The AG haplotype in rs7758025−rs9385502 was strongly associated with the occurrence of SZ (P = 0.0012, OR = 0.67, 95% CI = 0.48–0.93), an association that still held following a 1000-times random permutation test (P = 0.022). In an independently collected validation cohort, rs9483050 was the SNP most strongly associated with SZ. In addition, the allelic frequencies of rs12197901 remained associated with SZ in the combined cohort (P = 0.021), although not in the validation cohort alone (P = 0.251). Collectively, our data suggest the ARHGAP18 may confer vulnerability to SZ in the Chinese Han population, providing additional evidence for the involvement of neurodevelopmental dysfunction in the pathogenesis of schizophrenia.

Genetics of Schizophrenia: Historical Insights and Prevailing Evidence

Schizophrenia's (SZ's) heritability and familial transmission have been known for several decades; however, despite the clear evidence for a genetic component, it has been very difficult to pinpoint specific causative genes. Even so genetic studies have taught us a lot, even in the pregenomic era, about the molecular underpinnings and disease-relevant pathways. Recurring themes emerged revealing the involvement of neurodevelopmental processes, glutamate regulation, and immune system differential activation in SZ etiology. The recent emergence of epigenetic studies aimed at shedding light on the biological mechanisms underlying SZ has provided another layer of information in the investigation of gene and environment interactions. However, this epigenetic insight also brings forth another layer of complexity to the (epi)genomic landscape such as interactions between genetic variants, epigenetic marks-including cross-talk between DNA methylation and histone modification processes-, gene expression regulation, and environmental influences. In this review, we seek to synthesize perspectives, including limitations and obstacles yet to overcome, from genetic and epigenetic literature on SZ through a qualitative review of risk factors and prevailing hypotheses. Encouraged by the findings of both genetic and epigenetic studies to date, as well as the continued development of new technologies to collect and interpret large-scale studies, we are left with a positive outlook for the future of elucidating the molecular genetic mechanisms underlying SZ and other complex neuropsychiatric disorders.

Currently recognized genes for schizophrenia: High-resolution chromosome ideogram representation

A large body of genetic data from schizophrenia-related research has identified an assortment of genes and disturbed pathways supporting involvement of complex genetic components for schizophrenia spectrum and other psychotic disorders. Advances in genetic technology and expanding studies with searchable genomic databases have led to multiple published reports, allowing us to compile a master list of known, clinically relevant, or susceptibility genes contributing to schizophrenia. We searched key words related to schizophrenia and genetics from peer-reviewed medical literature sources, authoritative public access psychiatric websites and genomic databases dedicated to gene discovery and characterization of schizophrenia. Our list of 560 genes were arranged in alphabetical order in tabular form with gene symbols placed on high-resolution human chromosome ideograms. Genome wide pathway analysis using GeneAnalytics was carried out on the resulting list of genes to assess the underlying genetic architecture for schizophrenia. Recognized genes of clinical relevance, susceptibility or causation impact a broad range of biological pathways and mechanisms including ion channels (e.g., CACNA1B, CACNA1C, CACNA1H), metabolism (e.g., CYP1A2, CYP2C19, CYP2D6), multiple targets of neurotransmitter pathways impacting dopamine, GABA, glutamate, and serotonin function, brain development (e.g., NRG1, RELN), signaling peptides (e.g., PIK3CA, PIK4CA) and immune function (e.g., HLA-DRB1, HLA-DQA1) and interleukins (e.g., IL1A, IL10, IL6). This summary will enable clinical and laboratory geneticists, genetic counselors, and other clinicians to access convenient pictorial images of the distribution and location of contributing genes to inform diagnosis and gene-based treatment as well as provide risk estimates for genetic counseling of families with affected relatives.

The Function Biomedical Informatics Research Network Data Repository

The Function Biomedical Informatics Research Network (FBIRN) developed methods and tools for conducting multi-scanner functional magnetic resonance imaging (fMRI) studies. Method and tool development were based on two major goals: 1) to assess the major sources of variation in fMRI studies conducted across scanners, including instrumentation, acquisition protocols, challenge tasks, and analysis methods, and 2) to provide a distributed network infrastructure and an associated federated database to host and query large, multi-site, fMRI and clinical data sets. In the process of achieving these goals the FBIRN test bed generated several multi-scanner brain imaging data sets to be shared with the wider scientific community via the BIRN Data Repository (BDR). The FBIRN Phase 1 data set consists of a traveling subject study of 5 healthy subjects, each scanned on 10 different 1.5 to 4 T scanners. The FBIRN Phase 2 and Phase 3 data sets consist of subjects with schizophrenia or schizoaffective disorder along with healthy comparison subjects scanned at multiple sites. In this paper, we provide concise descriptions of FBIRN's multi-scanner brain imaging data sets and details about the BIRN Data Repository instance of the Human Imaging Database (HID) used to publicly share the data.

Unravelling genes and pathways implicated in working memory of schizophrenia in Han Chinese

Working memory deficit is the core neurocognitive disorder in schizophrenia patients. To identify the factors underlying working memory deficit in schizophrenia patients and to explore the implication of possible genes in the working memory using genome-wide association study (GWAS) of schizophrenia, computerized delay-matching-to-sample (DMS) and whole genome genotyping data were obtained from 100 first-episode, treatment-naïve patients with schizophrenia and 140 healthy controls from the Mental Health Centre of the West China Hospital, Sichuan University. A composite score, delay-matching-to-sample total correct numbers (DMS-TC), was found to be significantly different between the patients and control. On associating quantitative DMS-TC with interactive variables of groups × genotype, one SNP (rs1411832), located downstream of YWHAZP5 in chromosome 10, was found to be associated with the working memory deficit in schizophrenia patients with lowest p-value (p = 2.02 × 10(-7)). ConsensusPathDB identified that genes with SNPs for which p values below the threshold of 5 × 10(-5) were significantly enriched in GO:0007155 (cell adhesion, p < 0.001). This study indicates that working memory, as an endophenotype of schizophrenia, could improve the efficacy of GWAS in schizophrenia. However, further study is required to replicate the results from our study.

Transcriptome alterations of mitochondrial and coagulation function in schizophrenia by cortical sequencing analysis

Background

Transcriptome sequencing of brain samples provides detailed enrichment analysis of differential expression and genetic interactions for evaluation of mitochondrial and coagulation function of schizophrenia. It is implicated that schizophrenia genetic and protein interactions may give rise to biological dysfunction of energy metabolism and hemostasis. These findings may explain the biological mechanisms responsible for negative and withdraw symptoms of schizophrenia and antipsychotic-induced venous thromboembolism.

We conducted a comparison of schizophrenic candidate genes from literature reviews and constructed the schizophrenia-mediator network (SCZMN) which consists of schizophrenic candidate genes and associated mediator genes by applying differential expression analysis to BA22 RNA-Seq brain data. The network was searched against pathway databases such as PID, Reactome, HumanCyc, and Cell-Map. The candidate complexes were identified by MCL clustering using CORUM for potential pathogenesis of schizophrenia.

Results

Published BA22 RNA-Seq brain data of 9 schizophrenic patients and 9 controls samples were analyzed. The differentially expressed genes in the BA22 brain samples of schizophrenia are proposed as schizophrenia candidate marker genes (SCZCGs). The genetic interactions between mitochondrial genes and many under-expressed SCZCGs indicate the genetic predisposition of mitochondria dysfunction in schizophrenia. The biological functions of SCZCGs, as listed in the Pathway Interaction Database (PID), indicate that these genes have roles in DNA binding transcription factor, signal and cancer-related pathways, coagulation and cell cycle regulation and differentiation pathways.

In the query-query protein-protein interaction (QQPPI) network of SCZCGs, TP53, PRKACA, STAT3 and SP1 were identified as the central "hub" genes. Mitochondrial function was modulated by dopamine inhibition of respiratory complex I activity. The genetic interaction between mitochondria function and schizophrenia may be revealed by DRD2 linked to NDUFS7 through protein-protein interactions of FLNA and ARRB2.

The biological mechanism of signaling pathway of coagulation cascade was illustrated by the PPI network of the SCZCGs and the coagulation-associated genes. The relationship between antipsychotic target genes (DRD2/3 and HTR2A) and coagulation factor genes (F3, F7 and F10) appeared to cascade the following hemostatic process implicating the bottleneck of coagulation genetic network by the bridging of actin-binding protein (FLNA).

Conclusions

It is implicated that the energy metabolism and hemostatic process have important roles in the pathogenesis for schizophrenia. The cross-talk of genetic interaction by these co-expressed genes and reached candidate genes may address the key network in disease pathology. The accuracy of candidate genes evaluated from different quantification tools could be improved by crosstalk analysis of overlapping genes in genetic networks.

The rise of large-scale imaging studies in psychiatry

From the initial arguments over whether 12 to 20 subjects were sufficient for an fMRI study, sample sizes in psychiatric neuroimaging studies have expanded into the tens of thousands. These large-scale imaging studies fall into several categories, each of which has specific advantages and challenges. The different study types can be grouped based on their level of control: meta-analyses, at one extreme of the spectrum, control nothing about the imaging protocol or subject selection criteria in the datasets they include, On the other hand, planned multi-site mega studies pour intense efforts into strictly having the same protocols. However, there are several other combinations possible, each of which is best used to address certain questions. The growing investment of all these studies is delivering on the promises of neuroimaging for psychiatry, and holds incredible potential for impact at the level of the individual patient. However, to realize this potential requires both standardized data-sharing efforts, so that there is more staying power in the datasets for re-use and new applications, as well as training the next generation of neuropsychiatric researchers in "Big Data" techniques in addition to traditional experimental methods. The increased access to thousands of datasets along with the needed informatics demands a new emphasis on integrative scientific methods.

Novel treatment strategies for schizophrenia from improved understanding of genetic risk

Recent years have seen significant advances in our understanding of the genetic basis of schizophrenia. In particular, genome-wide approaches have suggested the involvement of many common genetic variants of small effect, together with a few rare variants exerting relatively large effects. While unequivocal identification of the relevant genes has, for the most part, remained elusive, the genes revealed as potential candidates can in many cases be clustered into functionally related groups which are potentially open to therapeutic intervention. In this review, we summarise this information, focusing on the accumulating evidence that genetic dysfunction at glutamatergic synapses and post-synaptic signalling complexes contributes to the aetiology of the disease. In particular, there is converging support for involvement of post-synaptic JNK pathways in disease aetiology. An expansion of our neurobiological knowledge of the basis of schizophrenia is urgently needed, yet some promising novel pharmacological targets can already be discerned.

MicroRNAs: Small molecules with big roles in neurodevelopment and diseases

MicroRNAs (miRNAs) are single-stranded, non-coding RNA molecules that play important roles in the development and functions of the brain. Extensive studies have revealed critical roles for miRNAs in brain development and function. Dysregulation or altered expression of miRNAs is associated with abnormal brain development and pathogenesis of neurodevelopmental diseases. This review serves to highlight the versatile roles of these small RNA molecules in normal brain development and their association with neurodevelopmental disorders, in particular, two closely related neuropsychiatric disorders of neurodevelopmental origin, schizophrenia and bipolar disorder.

Motor co-activation in siblings of patients with juvenile myoclonic epilepsy: an imaging endophenotype?

In juvenile myoclonic epilepsy (JME), myoclonic jerks are often triggered by cognitive effort. Wandschneider et al. report co-activation of the motor and prefrontal cognitive networks in unaffected siblings, similar to that previously reported in patients themselves. This co-activation could constitute a heritable marker for further genetic studies of JME.

Juvenile myoclonic epilepsy is a heritable idiopathic generalized epilepsy syndrome, characterized by myoclonic jerks and frequently triggered by cognitive effort. Impairment of frontal lobe cognitive functions has been reported in patients with juvenile myoclonic epilepsy and their unaffected siblings. In a recent functional magnetic resonance imaging study we reported abnormal co-activation of the motor cortex and increased functional connectivity between the motor system and prefrontal cognitive networks during a working memory paradigm, providing an underlying mechanism for cognitively triggered jerks. In this study, we used the same task in 15 unaffected siblings (10 female; age range 18–65 years, median 40) of 11 of those patients with juvenile myoclonic epilepsy (six female; age range 22–54 years, median 35) and compared functional magnetic resonance imaging activations with 20 age- and gender-matched healthy control subjects (12 female; age range 23–46 years, median 30.5). Unaffected siblings showed abnormal primary motor cortex and supplementary motor area co-activation with increasing cognitive load, as well as increased task-related functional connectivity between motor and prefrontal cognitive networks, with a similar pattern to patients (P < 0.001 uncorrected; 20-voxel threshold extent). This finding in unaffected siblings suggests that altered motor system activation and functional connectivity is not medication- or seizure-related, but represents a potential underlying mechanism for impairment of frontal lobe functions in both patients and siblings, and so constitutes an endophenotype of juvenile myoclonic epilepsy.

Genetic analysis of quantitative phenotypes in AD and MCI: imaging, cognition and biomarkers

The Genetics Core of the Alzheimer's Disease Neuroimaging Initiative (ADNI), formally established in 2009, aims to provide resources and facilitate research related to genetic predictors of multidimensional Alzheimer's disease (AD)-related phenotypes. Here, we provide a systematic review of genetic studies published between 2009 and 2012 where either ADNI APOE genotype or genome-wide association study (GWAS) data were used. We review and synthesize ADNI genetic associations with disease status or quantitative disease endophenotypes including structural and functional neuroimaging, fluid biomarker assays, and cognitive performance. We also discuss the diverse analytical strategies used in these studies, including univariate and multivariate analysis, meta-analysis, pathway analysis, and interaction and network analysis. Finally, we perform pathway and network enrichment analyses of these ADNI genetic associations to highlight key mechanisms that may drive disease onset and trajectory. Major ADNI findings included all the top 10 AD genes and several of these (e.g., APOE, BIN1, CLU, CR1, and PICALM) were corroborated by ADNI imaging, fluid and cognitive phenotypes. ADNI imaging genetics studies discovered novel findings (e.g., FRMD6) that were later replicated on different data sets. Several other genes (e.g., APOC1, FTO, GRIN2B, MAGI2, and TOMM40) were associated with multiple ADNI phenotypes, warranting further investigation on other data sets. The broad availability and wide scope of ADNI genetic and phenotypic data has advanced our understanding of the genetic basis of AD and has nominated novel targets for future studies employing next-generation sequencing and convergent multi-omics approaches, and for clinical drug and biomarker development.

When less is more--microRNAs and psychiatric disorders

OBJECTIVE

MicroRNAs are small non-coding RNA molecules that regulate gene expression, including genes involved in neuronal function and plasticity that have relevance for brain function and mental health. We therefore performed a systematic review of miRNAs in general adult psychiatric disorders.

METHOD

Systematic searches in PubMed/MEDLINE and Web of Science were conducted to identify published clinical articles on microRNAs in general adult psychiatric disorders. We also reviewed references from included articles.

RESULTS

There is mounting evidence of microRNAs' regulatory roles in a number of central nervous system processes, including neurogenesis and synaptic plasticity. The majority of clinical studies of microRNAs in psychiatric disorders are in schizophrenia, where a number of specific microRNAs have been identified in separate studies. There is some evidence of marked downregulation of some microRNAs in affective disorders. Treatment with antidepressants appears to upregulate microRNA levels. There is currently little evidence from human studies in anxiety, addiction or other psychiatric disorders.

CONCLUSION

MicroRNA research in psychiatry is currently in a nascent period, but represents an emerging and exciting area, with the potential to clarify molecular mechanisms of disease and identify novel biomarkers and therapeutic agents.

Smoking status as a potential confounder in the study of brain structure in schizophrenia

Several but not all MRI studies have reported volume reductions in the hippocampus and dorsolateral prefrontal cortex (DLPFC) in patients with schizophrenia. Given the high prevalence of smoking among schizophrenia patients and the fact that smoking has also been associated with alterations in brain morphology, this study evaluated whether a proportion of the known gray matter reductions in key brain regions may be attributed to smoking rather than to schizophrenia alone. We examined structural MRI data of 112 schizophrenia patients (53 smokers and 59 non-smokers) and 77 healthy non-smoker controls collected by the MCIC study of schizophrenia. An automated atlas based probabilistic method was used to generate volumetric measures of the hippocampus and DLPFC. The two patient groups were matched with respect to demographic and clinical variables. Smoker schizophrenia patients showed significantly lower hippocampal and DLPFC volumes than non-smoker schizophrenia patients. Gray matter volume reductions associated with smoking status ranged between 2.2% and 2.8%. Furthermore, we found significant volume differences between smoker patients and healthy controls in the hippocampus and DLPFC, but not between non-smoker patients and healthy controls. Our data suggest that a proportion of the volume reduction seen in the hippocampus and DLPFC in schizophrenia is associated with smoking rather than with the diagnosis of schizophrenia. These results may have important implications for brain imaging studies comparing schizophrenia patients and other groups with a lower smoking prevalence.

Schizophrenia miR-137 locus risk genotype is associated with dorsolateral prefrontal cortex hyperactivation

BACKGROUND

miR-137 dysregulation has been implicated in the etiology of schizophrenia, but its functional role remains to be determined.

METHODS

Functional magnetic resonance imaging scans were acquired on 48 schizophrenia patients and 63 healthy volunteers (total sample size N = 111 subjects), with similar mean age and sex distribution, while subjects performed a Sternberg Item Response Paradigm with memory loads of one, three, and five numbers. Dorsolateral prefrontal cortex (DLPFC) retrieval activation for the working memory load of three numbers, for which hyperactivation had been shown in schizophrenia patients compared with control subjects, was extracted. The genome-wide association study confirmed schizophrenia risk single nucleotide polymorphism rs1625579 (miR-137 locus) was genotyped (schizophrenia: GG n = 0, GT n = 9, TT n = 39; healthy volunteers: GG = 2, GT n = 15, and TT n = 46). Fisher's exact test examined the effect of diagnosis on rs1625579 allele frequency distribution (p = nonsignificant). Mixed model regression analyses examined the effects of diagnosis and genotype on working memory performance measures and DLPFC activation.

RESULTS

Patients showed significantly higher left DLPFC retrieval activation on working memory load 3, lower working memory performance, and longer response times compared with controls. There was no effect of genotype on working memory performance or response times in either group. However, individuals with the rs1625579 TT genotype had significantly higher left DLPFC activation than those with the GG/GT genotypes.

CONCLUSIONS

Our study suggests that the rs1625579 TT (miR-137 locus) schizophrenia risk genotype is associated with the schizophrenia risk phenotype DLPFC hyperactivation commonly considered a measure of brain inefficiency.

Neuroimaging as a potential biomarker to optimize psychiatric research and treatment

Complex, polygenic phenotypes in psychiatry hamper our understanding of the underlying molecular pathways and mechanisms of many diseases. The unknown aetiology, together with symptoms which often show a large variability both across individuals and over time and also tend to respond comparatively slowly to medication, can be a problem for patient treatment and drug development. We argue that neuroimaging has the potential to improve psychiatric treatment in two ways. First, by reducing phenotypic complexity, neuroimaging intermediate phenotypes can help to identify disease-related genes and can shed light into the biological mechanisms of known risk genes. Second, quantitative neuroimaging markers - reflecting the spectrum of impairment on a brain-based level - can be used as a more sensitive, reliable and immediate treatment response biomarker. In the end, enhancing both our understanding of the pathophysiology of psychiatric disorders and the prediction of treatment success could eventually optimise current therapy plans.

Genome-wide association study of obsessive-compulsive disorder

Obsessive-compulsive disorder (OCD) is a common, debilitating neuropsychiatric illness with complex genetic etiology. The International OCD Foundation Genetics Collaborative (IOCDF-GC) is a multi-national collaboration established to discover the genetic variation predisposing to OCD. A set of individuals affected with DSM-IV OCD, a subset of their parents, and unselected controls, were genotyped with several different Illumina SNP microarrays. After extensive data cleaning, 1465 cases, 5557 ancestry-matched controls and 400 complete trios remained, with a common set of 469,410 autosomal and 9657 X-chromosome single nucleotide polymorphisms (SNPs). Ancestry-stratified case-control association analyses were conducted for three genetically-defined subpopulations and combined in two meta-analyses, with and without the trio-based analysis. In the case-control analysis, the lowest two P-values were located within DLGAP1 (P=2.49 × 10(-6) and P=3.44 × 10(-6)), a member of the neuronal postsynaptic density complex. In the trio analysis, rs6131295, near BTBD3, exceeded the genome-wide significance threshold with a P-value=3.84 × 10(-8). However, when trios were meta-analyzed with the case-control samples, the P-value for this variant was 3.62 × 10(-5), losing genome-wide significance. Although no SNPs were identified to be associated with OCD at a genome-wide significant level in the combined trio-case-control sample, a significant enrichment of methylation QTLs (P<0.001) and frontal lobe expression quantitative trait loci (eQTLs) (P=0.001) was observed within the top-ranked SNPs (P<0.01) from the trio-case-control analysis, suggesting these top signals may have a broad role in gene expression in the brain, and possibly in the etiology of OCD.

Epigenetic changes at gene promoters in response to immune activation in utero

Increasing evidence suggests that maternal infection increases the risk of psychiatric disorders, such as schizophrenia and autism in offspring. However, the molecular mechanisms associated with these effects are unclear. Here, we have studied epigenetic gene regulation in mice exposed to non-specific immune activation elicited by polyI:C injection to pregnant dams. Using Western blot analysis, we detected global hypoacetylation of histone H3, at lysine residues 9 and 14, and histone H4, at lysine residue 8, in the cortex from juvenile (∼24days of age) offspring exposed to polyI:C in utero, but not from adult (3months of age) offspring, which exhibit significant behavioral abnormalities. Accordingly, we detected robust deficits in the expression of genes associated with neuronal development, synaptic transmission and immune signaling in the cortex of polyI:C-exposed juvenile mice. In particular, we found that several genes in the glutamate receptor signaling pathway, including Gria1 and Slc17a7, showed decreases in promoter-specific histone acetylation, and corresponding gene expression deficits, in polyI:C-exposed offspring at both juvenile and adult ages. In contrast, the expression of these same genes, in addition to Disc1 and Ntrk3, was elevated in the hippocampus of juvenile mice, in concordance with elevated levels of promoter-specific histone acetylation. We suggest that these early epigenetic changes contribute to the delayed behavioral abnormalities that are observed in adult animals after exposure to polyI:C, and which resemble symptoms seen in schizophrenia and related disorders.

White matter integrity as an intermediate phenotype: exploratory genome-wide association analysis in individuals at high risk of bipolar disorder

White matter integrity, as measured using diffusion tensor imaging (DTI), is reduced in individuals with bipolar disorder (BD), their unaffected relatives and carriers of specific risk-alleles. Fractional anisotropy (FA), an index of white matter integrity, is highly heritable but the genetic architecture of this trait has received little investigation. In this study we performed a genome-wide association study with FA as quantitative phenotype, in unaffected relatives of patients with BD (N=70) and a matched control group (N=80). Amongst our top results were SNPs located in genes involved in cell adhesion, white matter development and neuronal plasticity. Pathway analysis of the top associated polymorphisms and genes confirmed the enrichment of processes relevant to BD and white matter development, including axon guidance, ErbB-signalling neurotrophin signalling, phosphatidylinositol signalling, and cell adhesion. The majority of genes implicated in these pathways were differentially associated with FA in individuals at high familial risk, suggesting interactions with genetic background or environmental factors secondary to familial risk for BD. Although the present findings require independent replication, the results encourage the use of global FA as a quantitative phenotype in future large-scale studies which may help to identify the biological processes underlying reduced FA in BD and other psychiatric disorders.