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• SUDC Registry and Research Collaborative

  The Sudden Unexplained Death in Childhood Registry and Research Collaborative (SUDCRRC), created at NYU Langone Health in 2014, connects academic investigators, forensic pathologists, and medical examiner and coroner partner offices to study sudden unexpected pediatric deaths, aged 1 month to 18 years, whose death is unexplained or unclear at the end of the public mandated investigation, including autopsy. Each case includes collection and analysis of all records (medical history from prenatal records throughout life, death scene investigation, autopsy/toxicology/ancillary death investigation reports including photographs and histology slides), biospecimens, and in-depth family interviews. Whole exome sequencing is performed on each deceased child and both biological parents. Additional studies are pursued when indicated by pathology review. Each case receives a multidisciplinary masked review process and parental written consent is obtained. The NYU institutional review board approved this study.

  Study phs003383

• Genomic Basis of Phenotypic Variability of Complex Disorders

  The 520-kbp deletion on chromosome 16p12.1 is associated with multiple neurodevelopmental outcomes, including intellectual disability/developmental delay (ID/DD), schizophrenia, autism, and epilepsy. This variant is inherited in >95% of cases from carrier parents manifesting neuropsychiatric features, while affected children with the deletion were more likely to carry another large Copy Number Variation (CNV) or rare deleterious mutation elsewhere in the genome, or "second-hits", compared to carrier parents. Thus, while the 16p12.1 deletion confers significant risk for a range of disorders, the ultimate phenotypic trajectory is determined by "second-hit" variants in the genetic background. However, outstanding questions remain about the genetic background in these disorders, including the functional effects of "second-hit" variants towards gene expression or developmental phenotypes, the full spectrum of "second-hit" variants, and the mechanisms driving accumulation of these variants.In version 1, we performed deep clinical phenotyping, whole-genome sequencing (WGS), SNP microarray analysis, and RNA-sequencing of lymphoblastoid cell lines of 32 individuals in five large families with the 16p12.1 deletion. We found that specific classes of rare single-nucleotide and structural variants in coding and non-coding regions contributed towards expression changes in affected children based on their inheritance patterns, including a subset of variants that acted synergistically with the deletion to alter expression. We further found that rare variant-mediated expression changes contribute to specific developmental phenotypes in the carrier children, suggesting a potential genetic mechanism for variable expressivity of the deletion.In version 2, we additionally analyzed genetic and phenotypic data from individuals with 16p12.1 deletion and their spouses to assess the role of assortative mating modulating phenotypic outcomes of the 16p12.1 deletion. We identified significant within- and cross- disorder phenotypic correlations between spouses, but observed no significant genetic correlations between spouses, in line with expectations.

  Study phs002450

• Cross-Sectional Characterization of Idiopathic Bronchiectasis

  This GDMCC protocol will study adult patients with non-CF, idiopathic bronchiectasis, whose genetic etiologies are not known. Idiopathic bronchiectasis is reportedly more common in females with certain tall, thin body types and associated with environmental organisms, such as nontuberculous mycobacterium (NTM). The other susceptibility factors predisposing to bronchiectasis or acquisition of NTM are unclear. The study will attempt to broaden the understanding of this disease by comparing gender-associated factors and NTM status. A relatively equal number of both females/males and NTM/non-NTM infected subjects will be enrolled. Approximately 300 people may be screened to find 260 eligible subjects, since a small number (e.g., 40 patients) may be diagnosed with PCD, vCF, or other known etiology as an explanation for the bronchiectasis. This single-visit protocol will use a systematic approach to characterize the physical features, radiographic patterns, and associated lower airway microbial flora. There is no natural history of disease course follow-up component to this protocol. Participants will have one outpatient clinic visit for evaluation with a physical examination including detailed body size measurements, medical history, collection of blood samples for routine lab tests and genetic analyses, and a chest X-ray if no recent one is available. Participants will also have tests of lung function, and measurement of a gas called nitric oxide in the nose. Participants whose initial tests show abnormal results may also be asked to have a nasal scrape to collect cell samples and/or a skin sweat test to measure salt concentrations. Participants will also have a sputum specimen collected during the visit and will be asked to collect two additional early morning sputum samples and a mouth rinse at home within 2 weeks of the clinic visit, and mail the sample collection materials to the research team. Careful evaluation and characterization of the physical and clinical characteristics will guide the genetic characterization of idiopathic bronchiectasis, and likely lead to an improved diagnostic approach. Identification of disease causing genes may provide new therapeutic targets.

  Study phs001279

• Submitting array based metadata

  Submitting array based metadata For further information please check our Submission FAQs, submission quickguide as well as submission terms! The submission metadata required for Array-based submission must be submitted using EGA programmatic submission and by completing the Array-based format (AF) template. The guidelines for this workflow are described on this page. Please notice that all files should be encrypted and uploaded prior to the processing of your EGA Array-based-Format (AF) template. You can request a legacy EGA submission account (ega-box-XXXX) by populating this form. Please, allow two business days for our Helpdesk team to contact you after populating this form. Please notice that all files should be encrypted and uploaded prior to the processing of your EGA-Array-based-Format (AF) template. Metadata Model Registering Metadata Use the EGA programmatic submission to register your Study, Samples, Data Access Committee (DAC) and Policy. This online interface enables you to create new and edit existing submissions. Do not use the Submitter Portal to register the metadata objects for array submissions. Please, go to the EGA programmatic submission. Registering Study Go to the EGA programmatic submission Submit an study XML Take a note of your study accession number (EGASXXXXXXXXXXX) To use the study accession number in a publication, we suggest the following format: "Sequence data has been deposited at the European Genome-phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGASXXXXXXXXXXX. Further information about EGA can be found on https://ega-archive.org "The European Genome-phenome Archive of human data consented for biomedical research"(https://doi.org/10.1093/nar/gkab1059 ). Registering Samples Go to the EGA programmatic submission Submit a sample XML Save the list of accession numbers. These will be needed for the AF template. Registering Data Access Committee Further information on the role of your DAC. Go to the EGA programmatic submission Submit a DAC XML Take a note of the DAC accession number (EGACXXXXXXXXXXX) Registering Policy Your Data Access Policy provides the terms and conditions of data use. This is also referred to as the Data Access Agreement (DAA). Completion of a DAA by the applicant/s should form part of the application process to the Data Access Committee (DAA) Go to the EGA programmatic submission Submit a Policy XML Take a note of the Policy accession number (EGAPXXXXXXXXXXX) Complete the Array-based format (AF) spreadsheet Once you have completed the registration of your Study, DAC and Policy using the programmatix submission, you must then complete and return the AF spreadsheet The AF spreadsheet consists on four components: Do not use EGA IDs registered using the Submitter Portal. You can easily identify objects registered in the Submitter Portal by their EGA ID pattern: EGA[A-Z]5{10 more digits} (e.g. for a sample EGAN50000002506). For populating an AF spreadsheet, please exclusively use EGA IDs following this specific pattern: EGA[A-Z]0{10 more digits} (e.g. for a sample EGAN00001691542). Tab1) Webin accessions : Provide the accession numbers for your study, DAC and policy. Please, also add your ega-box number. Tab2) Sample & phenotypes: Please, leave this tab blank. Tab3) Dataset: Describe the dataset to be created Tab4) Data files: Define how your data is going to be organised into datasets and packets for distribution (linkage between samples and files). Should further assistance be required after going through the guide below; please do not hesitate to contact the EGA helpdesk Once the AF spreadsheet is populated, please send it to our EGA helpdesk for further validation. AF spreadsheet Should your submission require multiple DAC's or policies, use ' ; ' to separate the accession numbers. Accessions AF spreadsheet: Samples & phenotypes Samples and phenotypes AF spreadsheet: Datasets We suggest that each dataset consists of a common set of data. The example below consists of two datasets, grouped according to shared data type, technology and by case/control. We also like to capture the number of unique samples that make up the dataset and the Data Access Committee (DAC) responsible for providing the named dataset and their policy (EGAP). Datasets AF spreadsheet: Data files What follows is an example of how to map your samples to the array based files added to your upload account (4th tab). Data Files Please, find below some practical examples on how to register the linkage between samples-files Case 1) 1 sample or list of samples in different datasets: Data Files In case you have a list of samples that belong to different datasets, please, repeat the samples accession number/s in the first column and link the sample to the corresponding dataset each time (each row). Each row is one linkage between sample-file-dataset. Case 2) 1 sample links to several files: Data Files In order to add multiple files to one sample you MUST use “ ; “ between filenames. Example: file1.gpg;file2.gpg;file3.gpg In case that you want to add an extra file to the sample (phenotype or .Rdata), please use “Additional files” column. Important note: You MUST upload the encrypted and unencrypted md5sum values of all files uploaded to your submission account using the filename nomenclature (file.gpg, file.md5,file.md5.gpg). Your submission will not be processed without md5values supplied for all files in the CORRECT format. What happens after the submission of a dataset? All datasets affiliated to unreleased studies are automatically placed on hold until the authorised submitted or DAC contact instructs our EGA helpdesk for the study to be released. Finally, your data is archived within our databases and prepared for encrypted distribution upon the request of permitted EGA account holders. We strongly advise you NOT to delete your data until we confirm that your data has been successfully archived.

  Documentation submission/metadata/submission/array

• Combined gene expression and digital pathology identifies molecular mediators of T cell exclusion and immune suppression in ovarian cancer

  Close proximity between cytotoxic T lymphocytes and tumour cells is required for effective immunotherapy. However, what determines the spatial distribution of T cells in the tumour microenvironment is not well understood. Coupling digital pathology and transcriptome analysis on a large ovarian tumour cohort, we develop a machine learning approach to molecularly classify and characterize tumour-immune phenotypes. Our study identifies two important hallmarks characterizing T cell excluded tumours: 1) loss of antigen presentation on tumour cells and 2) upregulation of TGFb and activated stroma. Furthermore, we identify TGFb as a key mediator of T cell exclusion. TGFb reduces MHC-I expression in ovarian cancer cells in vitro; TGFb also activates fibroblasts and induced extracellular matrix (ECM) production as a potential physical barrier to hinder T cell infiltration. Our findings indicate that targeting TGFb may represent a promising strategy to overcome T cell exclusion and improve clinical benefits of cancer immunotherapy.

  Study EGAS00001003487

• Washington University PDX Development and Trial Center

  This data set is a collection of patient specimens from common and rare cancers that have been developed into patient-derived xenograft (PDX) models at the Washington University PDX Development and Trial Center (WU-PDTC). The goal of the PDTC is to develop and characterize PDX models, gaining insight into tumor biology, and validating biomarkers across all major tumor types. Pre-clinical experiments in these PDX models will be used to advance our ability to predict clinical responses to new molecularly targeted agents under development.

  Study phs002305

• Biesecker Lab (NHGRI) Whole Genome Medical Sequencing for Gene Discovery

  We aim to use whole-genome medical sequencing (WGMS) to discover causative molecular lesions for a set of rare, severe phenotypes hypothesized to be caused by either somatic mutations, germline de nova heterozygous mutations, germline inherited recessive, or germline inherited dominant mutations in currently unknown or uncharacterized genes. The goal of this research is threefold: to identify causative sequence variants for disorders whose molecular etiology was previously unknown, to apply this insight to both the rare disorders under study and more common phenotypes, and to enhance the study of mutation on a genome-wide level.

  Study phs001348

• Identification of ALS Associated Genes Using Whole Genome Sequencing

  The overall aim of this study is to discover of novel genetic elements associated with amyotrophic lateral sclerosis (ALS). Towards this goal, we have performed exome and whole genome sequencing for over 2000 samples. This data will be process and harmonized to yield high quality variant calling. These variants will be combined with control cohorts to identify novel genetic elements associated with ALS through case: control analyses.

  Study phs001585

• Warm_autopsy__mutational_signatures_and_clonal_units

  Aims and objectives 1. To produce a ‘first generation map’ of mutational burdens and mutational processes that operate in normal human tissues. 2. To examine clonal units and their distribution across normal human tissues with the emphasis on these particular areas: a) Tissues with an architecturally defined unit: Are architectural structures populated by a progeny derived from a single stem cell? Are clonal units confined to a given architectural structure? Examples of tissues where such approach will be used include prostate gland (acini and ducts), small bowel (crypts), thyroid gland (follicles) and others. b) Tissues without an architecturally defined unit: What is the average size of clonal populations? This group includes stratified/pseudostratified epithelia with a basal layer within which there are stem cells that give rise to a progeny of cells showing upwards migration and lateral expansion (e.g. urothelium, cervical squamous epithelium, respiratory epithelium). This approach can also be used in tissues with a sheet-like cell arrangement, for example brain and adrenal gland. Methods To answer these questions, we will use a range of normal human tissue samples which have already been collected from a single deceased individual. The samples are currently stored in a -80C freezer. Ethanol fixed frozen sections will be prepared from these biopsies. Putative clonal units will be identified and dissected out using laser capture microscopy. DNA extraction will be performed using the in-house (CGP) protease based method. In terms of sequencing methods, the project will be split into 2 phases (2 different approaches): - Phase 1: This part of the project will utilise a combination of low input library preparation (developed by Peter Ellis) and standard whole genome sequencing (HiSeqX). The phase has already started (December 2016). This approach will be particularly useful in investigation of mitotically active tissues. - Phase 2: This part of the project will utilise a combination of low input library method (Peter Ellis) and Bottle-neck sequencing (BotSeqS). BotSeqS is a type of duplex sequencing method that offers a more accurate variant calling and allows genome interrogation at a single cell level. This method is currently being developed and is expected to be implemented in 3-6 months (March-April 2017). This approach will be particularly useful for post-mitotic tissues and tissues without pre-defined architectural units.

  Study EGAS00001002216

• Clonal expansion and epigenetic reprogramming following deletion or amplification of mutant IDH1

  IDH1 mutation is the earliest genetic alteration in low-grade gliomas (LGGs), but its role in tumor recurrence is unclear. Mutant IDH1 drives overproduction of the oncometabolite D-2-hydroxyglutarate (2HG) and a CpG island (CGI) hypermethylation phenotype (G-CIMP). To investigate the role of mutant IDH1 at recurrence, we performed a longitudinal analysis of 50 IDH1 mutant LGGs. We discovered six cases with copy number alterations (CNAs) at the IDH1 locus at recurrence. Deletion or amplification of IDH1 was followed by clonal expansion and recurrence at a higher grade. Successful cultures derived from IDH1 mutant, but not IDH1 wild-type, gliomas systematically deleted IDH1 in vitro and in vivo, further suggestive of selection against the heterozygous mutant state as tumors progress. Tumors and cultures with IDH1 CNA had decreased 2HG, maintenance of G-CIMP, and DNA methylation reprogramming outside CGI. Thus, while IDH1 mutation initiates gliomagenesis, in some patients, mutant IDH1 and 2HG are not required for later clonal expansions.

  Study EGAS00001001854