Genome-wide Association Study Points to Novel Locus for Gilles de la Tourette Syndrome.

BACKGROUND: Tourette syndrome (TS) is a childhood-onset neurodevelopmental disorder of complex genetic architecture and is characterized by multiple motor tics and at least one vocal tic persisting for more than 1 year. METHODS: We performed a genome-wide meta-analysis integrating a novel TS cohort with previously published data, resulting in a sample size of 6133 individuals with TS and 13,565 ancestry-matched control participants. RESULTS: We identified a genome-wide significant locus on chromosome 5q15. Integration of expression quantitative trait locus, Hi-C (high-throughput chromosome conformation capture), and genome-wide association study data implicated the NR2F1 gene and associated long noncoding RNAs within the 5q15 locus. Heritability partitioning identified statistically significant enrichment in brain tissue histone marks, while polygenic risk scoring of brain volume data identified statistically significant associations with right and left thalamus volumes and right putamen volume. CONCLUSIONS: Our work presents novel insights into the neurobiology of TS, thereby opening up new directions for future studies.

De Novo Sequence and Copy Number Variants Are Strongly Associated with Tourette Disorder and Implicate Cell Polarity in Pathogenesis.

We previously established the contribution of de novo damaging sequence variants to Tourette disorder (TD) through whole-exome sequencing of 511 trios. Here, we sequence an additional 291 TD trios and analyze the combined set of 802 trios. We observe an overrepresentation of de novo damaging variants in simplex, but not multiplex, families; we identify a high-confidence TD risk gene, CELSR3 (cadherin EGF LAG seven-pass G-type receptor 3); we find that the genes mutated in TD patients are enriched for those related to cell polarity, suggesting a common pathway underlying pathobiology; and we confirm a statistically significant excess of de novo copy number variants in TD. Finally, we identify significant overlap of de novo sequence variants between TD and obsessive-compulsive disorder and de novo copy number variants between TD and autism spectrum disorder, consistent with shared genetic risk.

Investigation of SNP rs2060546 Immediately Upstream to NTN4 in a Danish Gilles de la Tourette Syndrome Cohort.

Gilles de la Tourette syndrome (GTS) is a neuropsychiatric disorder characterized by multiple motor and vocal tics. GTS is a complex disorder, with environmental factors and several genes involved. Although variations within a few genes such as AADAC, NRXN1, SLITRK1, HDC, and IMMP2L have been tentatively associated with GTS (in a small number of patients), the causative genes underlying GTS pathophysiology remain unknown. In a previous genome-wide association study (GWAS) a single nucleotide polymorphism (SNP, rs2060546) near the Netrin-4 (NTN4 - MIM 610401) gene was shown to be associated with GTS [odds ratio (OR) = 1.7; p-value = 5.8 × 10-7] thus warranting further investigations. As NTN4 is one of the axon guidance molecules expressed in the central nervous system and it interacts with the encoded proteins of SLIT and WNT genes guiding the growth cone toward its target, it is an attractive candidate susceptibility gene for GTS. In this study we attempted to replicate the association of rs2060546 with GTS by genotyping a Danish cohort of 240 GTS patients and 1006 healthy controls. Our results did not reveal an association (OR = 1.363; p-value = 0.3329) in the Danish cohort alone, which may be due to the small sample size. However, a meta-analysis including the present cohort and a total of 1316 GTS patients and 5023 controls from the GTS GWAS Replication Initiative (GGRI) and the first GTS-GWAS yielded a significant signal (OR = 3.74; p-value = 0.00018) and same direction of effect in the three cohorts. Thus, our study strengthens the evidence of the possible involvement of NTN4 in GTS etiology, suggesting that further studies in even larger samples and functional studies are warranted to investigate the role of this region in GTS pathogenesis.

TS-EUROTRAIN: A European-Wide Investigation and Training Network on the Etiology and Pathophysiology of Gilles de la Tourette Syndrome.

Gilles de la Tourette Syndrome (GTS) is characterized by the presence of multiple motor and phonic tics with a fluctuating course of intensity, frequency, and severity. Up to 90% of patients with GTS present with comorbid conditions, most commonly attention-deficit/hyperactivity disorder (ADHD), and obsessive-compulsive disorder (OCD), thus providing an excellent model for the exploration of shared etiology across disorders. TS-EUROTRAIN (FP7-PEOPLE-2012-ITN, Grant Agr.No. 316978) is a Marie Curie Initial Training Network (http://ts-eurotrain.eu) that aims to elucidate the complex etiology of the onset and clinical course of GTS, investigate the neurobiological underpinnings of GTS and related disorders, translate research findings into clinical applications, and establish a pan-European infrastructure for the study of GTS. This includes the challenges of (i) assembling a large genetic database for the evaluation of the genetic architecture with high statistical power; (ii) exploring the role of gene-environment interactions including the effects of epigenetic phenomena; (iii) employing endophenotype-based approaches to understand the shared etiology between GTS, OCD, and ADHD; (iv) establishing a developmental animal model for GTS; (v) gaining new insights into the neurobiological mechanisms of GTS via cross-sectional and longitudinal neuroimaging studies; and (vi) partaking in outreach activities including the dissemination of scientific knowledge about GTS to the public. Fifteen partners from academia and industry and 12 PhD candidates pursue the project. Here, we aim to share the design of an interdisciplinary project, showcasing the potential of large-scale collaborative efforts in the field of GTS. Our ultimate aims are to elucidate the complex etiology and neurobiological underpinnings of GTS, translate research findings into clinical applications, and establish Pan-European infrastructure for the study of GTS and associated disorders.

Meta-Analysis of Tourette Syndrome and Attention Deficit Hyperactivity Disorder Provides Support for a Shared Genetic Basis.

Gilles de la Tourette Sydrome (TS) is a childhood onset neurodevelopmental disorder, characterized phenotypically by the presence of multiple motor and vocal tics. It is often accompanied by multiple psychiatric comorbidities, with Attention Deficit/Hyperactivity Disorder (ADHD) among the most common. The extensive co-occurrence of the two disorders suggests a shared genetic background. A major step toward the elucidation of the genetic architecture of TS was undertaken by the first TS Genome-wide Association Study (GWAS) reporting 552 SNPs that were moderately associated with TS (p < 1E-3). Similarly, initial ADHD GWAS attempts and meta-analysis were not able to produce genome-wide significant findings, but have provided insight to the genetic basis of the disorder. Here, we examine the common genetic background of the two neuropsychiatric phenotypes, by meta-analyzing the 552 top hits in the TS GWAS with the results of ADHD first GWASs. We identify 19 significant SNPs, with the top four implicated genes being TBC1D7, GUCY1A3, RAP1GDS1, and CHST11. TBCD17 harbors the top scoring SNP, rs1866863 (p:3.23E-07), located in a regulatory region downstream of the gene, and the third best-scoring SNP, rs2458304 (p:2.54E-06), located within an intron of the gene. Both variants were in linkage disequilibrium with eQTL rs499818, indicating a role in the expression levels of the gene. TBC1D7 is the third subunit of the TSC1/TSC2 complex, an inhibitor of the mTOR signaling pathway, with a central role in cell growth and autophagy. The top genes implicated by our study indicate a complex and intricate interplay between them, warranting further investigation into a possibly shared etiological mechanism for TS and ADHD.

Epigenome-Wide Association Study of Tic Disorders.

Tic disorders are moderately heritable common psychiatric disorders that can be highly troubling, both in childhood and in adulthood. In this study, we report results obtained in the first epigenome-wide association study (EWAS) of tic disorders. The subjects are participants in surveys at the Netherlands Twin Register (NTR) and the NTR biobank project. Tic disorders were measured with a self-report version of the Yale Global Tic Severity Scale Abbreviated version (YGTSS-ABBR), included in the 8th wave NTR data collection (2008). DNA methylation data consisted of 411,169 autosomal methylation sites assessed by the Illumina Infinium HumanMethylation450 BeadChip Kit (HM450k array). Phenotype and DNA methylation data were available in 1,678 subjects (mean age = 41.5). No probes reached genome-wide significance (p < 1.2 × 10(-7)). The strongest associated probe was cg15583738, located in an intergenic region on chromosome 8 (p = 1.98 × 10(-6)). Several of the top ranking probes (p < 1 × 10(-4)) were in or nearby genes previously associated with neurological disorders (e.g., GABBRI, BLM, and ADAM10), warranting their further investigation in relation to tic disorders. The top significantly enriched gene ontology (GO) terms among higher ranking methylation sites included anatomical structure morphogenesis (GO:0009653, p = 4.6 × 10-(15)) developmental process (GO:0032502, p = 2.96 × 10(-12)), and cellular developmental process (GO:0048869, p = 1.96 × 10(-12)). Overall, these results provide a first insight into the epigenetic mechanisms of tic disorders. This first study assesses the role of DNA methylation in tic disorders, and it lays the foundations for future work aiming to unravel the biological mechanisms underlying the architecture of this disorder.

TopFed: TCGA tailored federated query processing and linking to LOD.

BACKGROUD: The Cancer Genome Atlas (TCGA) is a multidisciplinary, multi-institutional effort to catalogue genetic mutations responsible for cancer using genome analysis techniques. One of the aims of this project is to create a comprehensive and open repository of cancer related molecular analysis, to be exploited by bioinformaticians towards advancing cancer knowledge. However, devising bioinformatics applications to analyse such large dataset is still challenging, as it often requires downloading large archives and parsing the relevant text files. Therefore, it is making it difficult to enable virtual data integration in order to collect the critical co-variates necessary for analysis. METHODS: We address these issues by transforming the TCGA data into the Semantic Web standard Resource Description Format (RDF), link it to relevant datasets in the Linked Open Data (LOD) cloud and further propose an efficient data distribution strategy to host the resulting 20.4 billion triples data via several SPARQL endpoints. Having the TCGA data distributed across multiple SPARQL endpoints, we enable biomedical scientists to query and retrieve information from these SPARQL endpoints by proposing a TCGA tailored federated SPARQL query processing engine named TopFed. RESULTS: We compare TopFed with a well established federation engine FedX in terms of source selection and query execution time by using 10 different federated SPARQL queries with varying requirements. Our evaluation results show that TopFed selects on average less than half of the sources (with 100% recall) with query execution time equal to one third to that of FedX. CONCLUSION: With TopFed, we aim to offer biomedical scientists a single-point-of-access through which distributed TCGA data can be accessed in unison. We believe the proposed system can greatly help researchers in the biomedical domain to carry out their research effectively with TCGA as the amount and diversity of data exceeds the ability of local resources to handle its retrieval and parsing.

Combining evidence of preferential gene-tissue relationships from multiple sources.

An important challenge in drug discovery and disease prognosis is to predict genes that are preferentially expressed in one or a few tissues, i.e. showing a considerably higher expression in one tissue(s) compared to the others. Although several data sources and methods have been published explicitly for this purpose, they often disagree and it is not evident how to retrieve these genes and how to distinguish true biological findings from those that are due to choice-of-method and/or experimental settings. In this work we have developed a computational approach that combines results from multiple methods and datasets with the aim to eliminate method/study-specific biases and to improve the predictability of preferentially expressed human genes. A rule-based score is used to merge and assign support to the results. Five sets of genes with known tissue specificity were used for parameter pruning and cross-validation. In total we identify 3434 tissue-specific genes. We compare the genes of highest scores with the public databases: PaGenBase (microarray), TiGER (EST) and HPA (protein expression data). The results have 85% overlap to PaGenBase, 71% to TiGER and only 28% to HPA. 99% of our predictions have support from at least one of these databases. Our approach also performs better than any of the databases on identifying drug targets and biomarkers with known tissue-specificity.