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• Next Generation Mendelian Genetics: Neonatal Diabetes

  The NHGRI Next Generation Mendelian Genetics project uses exome resequencing to identify variants in unsolved Mendelian diseases. Neonatal diabetes mellitus (ND) is a rare form of monogenic diabetes (90,000-260,000 live births) that is diagnosed in the first 6 months of life. The disease has been classified as transient or permanent and although it can be inherited, more frequently is sporadic as a result of 'de novo' mutations. Defects in 12 genes have been found as responsible for the disease (defects in the paternally imprinted chromosomal region 6q24, IPF1, SLCA2A, INS, EIF2AK3, GCK, FOXP3, GLIS3, PTF1A, HNF1Beta, KCNJ11 and ABCC8). The two subunits of the ATP-sensitive K channel (ABCC8 and KCNJ11) and the insulin gene (INS), account for almost half of the cases and similar to CHI, the other half, remains genetically unexplained. We became part of this study when we submitted 4 DNA samples for exome sequencing, from patients with NDM of Caucasian ancestry, which had no mutations identified in ABCC8 or KCNJ1, with the goal to identify new mutations in known genes or new mutations or genetic variants in new genes.

  Study phs000542

• SNPs and Extent of Atherosclerosis (SEA) Study

  The SEA study is a genome-wide association study to identify genetic variants associated with premature atherosclerosis in subjects included in the Pathobiological Determinants of Atherosclerosis in Youth (PDAY) repository - a unique NHLBI resource including data, DNA and arterial specimens from over 3000 multi-ethnic subjects 15-34 years of age who died of non-atherosclerotic causes (mostly trauma). All PDAY subjects had post-mortem quantitative assessment of raised atherosclerotic lesions in their aorta and coronary arteries - making this the largest and most carefully phenotyped cohort for premature atherosclerosis in the world. The goal of the current project was to use the quantitative measure of raised atherosclerotic lesions in the PDAY cohort as the target phenotype for a genome-wide association study and to use quantitative measures of subclinical atherosclerosis (coronary calcium and carotid IMT) in the Multi-Ethnic Study of Atherosclerosis (MESA) to confirm or refute candidate loci identified from the PDAY analysis. Identifying genetic factors that predispose individuals to premature atherosclerosis could lead to more effective screening and early treatment of high risk individuals and suggest novel molecular targets for treatment and prevention interventions.

  Study phs000349

• SHANK2 mutations associated with Autism Spectrum Disorder cause hyperconnectivity of human neurons

  Heterozygous loss-of-function mutations in the synaptic scaffolding gene SHANK2 are strongly associated with autism spectrum disorder (ASD). To investigate their effect on synaptic connectivity, we generated cortical neurons from induced pluripotent stem cells (iPSC) derived from neurotypic and ASD-affected donors. We developed Sparse coculture for Connectivity (SparCon) assays where SHANK2 and control neurons were differentially labeled and sparsely seeded together on a lawn of unlabeled control neurons. We observed striking increases in dendrite length, dendrite complexity, total synapse number, and frequency of spontaneous excitatory postsynaptic currents. These findings were phenocopied in gene-edited homozygous SHANK2 knockout cells and rescued by gene correction of an ASD SHANK2 muation, supporting a role for SHANK2 as a regulator of connectivity in developing human neurons. Dendrite length increases were exacerbated by IGF1, TG003, or BDNF, and suppressed by DHPG treatment. The transcriptome in these isogenic SHANK2 neurons was deeply perturbed in synapse, plasticity, and neuronal morphogenesis gene sets and ASD gene modules, and activity-dependent dendrite extension was impaired. Our unexpected findings provide evidence for hyperconnectivity and profoundly altered transcriptome in SHANK2 neurons derived from ASD subjects.

  Study EGAS00001003436

• University of Miami Study on Genetics of Autism and Related Disorders (AutismDisorders)

  Autism spectrum disorders (ASD) are neurodevelopmental in origin and characterized by impairments in reciprocal social interaction and communication accompanied by restricted and repetitive patterns of interest or behavior. With improved surveillance and a broadening of the diagnostic criteria, the most recent prevalence studies suggest that ASD may affect as many as 1/166 children in the US. Treatments are limited resulting in little impact on the profound morbidity. Little is known about the etiology of ASD, but there is a strong genetic component. Genetic studies over the past decade have failed to identify definitive ASD genes, but have clearly shown that the underlying genetics are more complex than anticipated with the likelihood that multiple genes are acting independently and/or interactively. With this realization the field of ASD genetics is at a critical juncture. To move forward we must embrace new and creative paradigms to successfully dissect the genetic etiology of this disease. Specifically the current study will: Extend our ascertainment to the full range of ASD. We will increase our ASD dataset by collecting 600 families who meet clinical diagnostic criteria for the three most common ASDs: autism (AUT), Asperger disorder (ASP) and Pervasive Developmental Disorder-NOS (PDD-NOS). Phenotype assessment will be expanded to include the Social Responsiveness Scale (SRS) and detailed seizure data. Ascertainment will focus on parent-child trios. Further characterize the ASD-associated variations in the Gamma-Aminobutyric Acid (GABA) receptor (GABR) subunits. We will complete our GABR subunit variant analysis, including coding, UTR, regulatory, and conserved intronic sequence, concentrating on GABRA4 and GABRB1. We will also investigate the role of variation in other GABR subunits. All AUT specific findings will be examined in the entire ASD dataset. Identify the chromosome 19p ASD gene. Multiple genome-wide screens have provided significant evidence for linkage to Chromosome 19p and we have found evidence for significant association in the linked families within an ~3 Mb region. We will genotype 768 SNPs spaced at ~4 kb to refine the candidate region and delineate specific candidate genes for further testing. We will screen the strongest associated candidate genes for additional variants and evaluate evidence for association in the entire ASD dataset (SA5). Develop and apply the Phenotypic Homogeneity Distinction (PHD) algorithm for identification of the phenotypic signature of linkage and/or association signals. The PHD algorithm identifies phenotypic covariates that discriminate a target sample subset (e.g. the positively linked families or families carrying the associated risk allele) from its complement. The resulting PHD discriminators will define a homogeneous subset from our newly-ascertained ASD dataset to use, as a confirmatory dataset and for localization within genes under study in our other aims. Test for gene-gene interactions. To fully explain the spectrum of autism risk, we will test for interactions between genetic variations associated with ASD (such as those in GABR subunit genes). We will build upon our experience using the MDR method and extend our analyses across biological pathways using the entire ASD data set.

  Study phs000436

• Genomic DNA analysis for malignant mesothelioma from the patients of Japan and USA.

  Malignant mesotheliomas (MMs) are highly aggressive adult malignancies and exposure to asbestos is the major factor involved in MM pathogenesis. It is desirable for a better understanding of the molecular pathogenesis of MM will lead to more specific and effective targeted therapies. In addition it is reported that germline mutation in a specific gene (ex. BAP1) associates familial MMs, and new candidate markers to determine a subject?s predisposition to MM and for early detection need to be identified. Analysis of genomic DNA from MM tumors and reference peripheral blood from Japan and USA are ongoing to find the common genomic characters beyond race.

  Study JGAS000108

• Non Dystrophic Myotonias: Genotype-Phenotype Correlation and Longitudinal

  NMD are rare ion channel disorders. The optimal management and treatment of these disorders are not known. This multi-center proposal will allow the prospective collection of standardized data from a critical number of patients to help better define the clinical features of NDM. The data will also be used to establish clinically relevant endpoints for use in therapeutic trials. The identification and genetic characterization of patients will facilitate recruitment of participants for future therapeutic trials. Ultimately, the information gained will lead to the improvements in the treatment and management of NMD with an associated reduction in morbidity and improvement in patient quality of life.

  Study phs000578

• RNA sequencing of a glioblastoma PDX cohort

  Patient-derived xenograft (PDX) models represent an essential tool for the preclinical evaluation of novel targeted therapies and their combinations. In this project, we molecularly characterized a comprehensive panel of glioma PDX models with well conserved molecular and pathological features over multiple passages. PDX samples were subjected to next generation sequencing (NGS). Characterization of cancer-relevant features including driver mutations or cellular processes was performed using mutational and gene expression data in order to identify potential biomarker or treatment targets in glioblastoma. In summary, we reported a newly established and molecularly characterized panel of glioma PDX models with high relevance for translational preclinical research.

  Study EGAS00001007119

• Primary Neuroblastoma Circle-seq

  We generated Circle-seq data for primary neuroblastoma to describe the landscape of extrachromosomal circular DNA in neuroblastoma.

  Study EGAS00001004797

• Myeloma_Follow_up_Pilot

  Targeted capture of exonic and intronic regions of interest for the study of genomic alterations in multiple myeloma.

  Study EGAS00001000743

• Shallow-whole genome sequencing for copy numbers in resectable gastric cancer treated with surgery alone

  Shallow-whole genome sequencing for copy numbers in resectable gastric cancer treated with surgery alone

  Dataset EGAD00001011994