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• A Case-Controlled Study for Genotype-Phenotype Associations in Multiple Sclerosis (MS)

  This is a multi-centre, case-controlled study to develop a dataset containing 1000 MS cases and 1000 matched controls and to associate DNA sequence (allelic) variations with MS phenotypes. Study subjects were enrolled through a prospective effort initiated in 2003. Three MS clinical centres were involved in subject recruitment and biological specimen collection using identical inclusion/exclusion criteria, two in Europe (Vrije Universiteit Medical Center, Amsterdam; and University Hospital Basel) and one in the US (University of California San Francisco). This study recruited subjects of northern-European ancestry with a diagnosis of MS (McDonald et al., 2001), with dissemination in time and space. Patients with Clinically Isolated Syndromes (CIS) were also included if they fulfilled 3 of the 4 Barkhof criteria for dissemination in space as per application of the McDonald criteria (McDonald et al., 2001). While recruitment predominantly included subjects with a relapsing onset of MS, individuals with all clinical subtypes of the disease participated, including clinically isolated syndrome (CIS), relapsing remitting MS (RRMS), secondary progressive MS (SPMS), primary progressive MS (PPMS), and progressive relapsing MS (PRMS). The control group consisted of unrelated individuals, primarily spouses/partners, friends, and other volunteers. Control subjects were of northern-European ancestry and matched as a group, proportionally with cases according to age (±5 years) and gender. A familial history or current diagnosis of MS as well as a relation to another case or control subject were considered exclusionary for this group. Protocols were approved by the Committees on Human Research at all Institutions and informed consent was obtained from all participants prior to participation in the study. Primary Study Objective:To identify DNA sequence variations (genotype) and flanking sequences that are associated with clinical factors (phenotype) which differ between study subjects with and without MS. Secondary Study Objectives: To develop a clinical dataset including quantitative measures of 1000 well-characterized cases with MS, and 1000 ethnically matched controls. To identify other genotype-phenotype associations in MS study subjects such as magnetic resonance imaging (MRI) measures of disease burden and/or severity. To identify or confirm candidate surrogate markers of neurodegeneration using a variety of techniques including biochemical assays, blood transcriptome analysis, plasma proteomics and MRI*. GenotypingGenotyping of the complete dataset was performed at the Illumina facilities using the Sentrix® HumanHap550 BeadChip. *MRI results are not available on dbGaP.

  Study phs000171

• National Heart, Lung and Blood Institute: Regulation of Motile Cilia Assembly in Lung Disease

  This study of 59 primary ciliary dyskinesia (PCD) patients utilized whole-exome capture sequencing to help identify variants that may be causative for PCD. Our goal was to provide insights into disease pathophysiology in samples, most of which had no obvious phenotype from transmission electron microscopy. This class of patients has been understudied. The patient samples were collected through UNC or under the auspices of Genetic Disorders of Mucociliary Clearance Consortium (GDMCC), which consists of eight geographically diverse clinical research sites across North America. It collectively studies inherited respiratory diseases related to impaired mucociliary clearance and airway host defense, which result in chronic suppurative respiratory diseases. The goal is to enhance diagnostic capabilities as the Consortium has been pivotal in the identification and/or characterization of 34 primary ciliary dyskinesia-associated genes. In this phase of the work, we used immunocytochemistry in patient samples and in shRNA hTEC cultures to show the localization of the CFAP57 protein to cilia and the role of a short region in trafficking of CFAP57 into the cilia. This work was complemented by proteomic studies in the Chlamydomonas reinhardtii

  Study phs002035

• Khoe-San genomes reveal unique variation and confirm deepest population divergence in Homo sapiens

  The southern African indigenous Khoe-San populations harbor the most divergent lineages of all living peoples. Exploring their genomes is key to understanding deep human history. We sequenced 25 full genomes from five Khoe-San populations, revealing many novel variants, that 25% of variants are unique to the Khoe-San, and that the Khoe-San group harbors the greatest level of diversity across the globe. In line with previous studies, we found several gene-regions with extreme values in genome-wide distributions, potentially caused by natural selection early in the modern human lineage and more recent in time. These gene-regions included immunity-, sperm-, brain-, diet- and muscle-related genes. When accounting for recent admixture, all Khoe-San groups display genetic diversity approaching the levels in other African groups and a reduction in effective population size starting around 100,000 years ago. Hence, all human groups show a reduction in effective population size commencing around the time of the Out-of-Africa migrations, which coincides with changes in the paleoclimate records, changes that potentially impacted all humans at the time.

  Study EGAS00001004459

• Pediatric Papillary Thyroid Carcinoma RNA-Seq

  Papillary thyroid carcinoma (PTC) is the most common malignancy amongst adolescent and young adult women. Clinical and genomic features of PTC in children differ from those in adults. Historically, a substantial proportion (~50%) of pediatric PTC (PPTC) lack any of the common driver mutations typical of adult PTC. Thus, molecular diagnostics developed for adults may not be valid in children. We applied novel bioinformatic pipelines to RNASeq analysis of pediatric thyroid tumors to identify known and novel fusion oncogenes as drivers of tumorigenesis and to define gene expression patterns among tumors. Analysis of 38 samples resulted in identification of 16 previously reported oncogenic fusions and three novel candidate fusions. In conducting these analyses, we reduced the proportion of cancers with unknown drivers from approximately 50% to 6%. Gene expression analysis identified three distinct categories of tumors. These studies represent the first unbiased genomic approach to childhood PTC. Novel bioinformatic pipeline. GEC Identified 3 distinct classes. DICER1, PTEN segregated with benign tumors. >90% of PPTC carry identifiable ongognic driver variants, however, the landscape differs from that in adults and existing tools for tumor genotyping in adults may not be applicable to pediatric tumors. BACKGROUND: Papillary thyroid carcinoma demonstrates clinically distinct behaviour in pediatric patients when compared to adults, with increased regional and distal metastases, more frequent recurrence, yet overall highly favourable prognosis. Recent tumor genotyping has demonstrated that in pediatric tumors, ***-*** do not carry the most common genomic variants found in adult PTC, leaving a substantial proportion of driver-unknown or “dark matter” tumors. METHODS: We established a cohort of 52 pediatric PTC and performed quantitative-PCR genotyping followed in a subset by whole exome and whole transcriptome (RNASeq) sequencing using a novel, robust bioinformatic pipeline to identify oncogenic fusion transcripts. Gene expression analysis was used to derive distinct clusters. RESULTS: In 52 pediatric PTC, genotyping identified BRAFV600E(21%), NRASQ61R(2%), RET/PTC1 (21%), RET/PTC3 (17%) or PAX8-PPAR in 33 (63%) of tumors. Among the remaining 19 tumors, oncogenic variants were identified in /19 (%). The variants included SNVs in DICER1, ETV6-NTRK3, PTEN and 9 additional oncogenic fusions including two previously-undescribed fusion transcripts, *** and ***. CONCLUSIONS: The genomic landscape of PTC differs between children and adults. In children, there is a substantial fraction of tumors that are unexplained by variants typical of adult PTC. This discrepancy is explained largely by uncommon oncogenic fusions which can be identified by whole-transcriptome analysis.

  Study EGAS00001005182

• Heart Failure: A Controlled Trial Investigating Outcomes of Exercise Training (HF-ACTION-BioLINCC)

  Accessing Data Please refer to “Authorized Access” below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP.ObjectivesThe HF-ACTION study examined whether exercise training reduces a composite endpoint of all-cause mortality or all-cause hospitalization for patients with left ventricular systolic dysfunction and heart failure symptoms. Background Heart failure (HF) is a major and growing cardiovascular syndrome that is the end result of many cardiovascular disorders. Although evidence-based drug and device therapies decrease mortality, hospitalizations, and HF symptoms and improve quality of life, many patients treated with these regimens often remain burdened by dyspnea and fatigue, diminished exercise tolerance, reduced quality of life, recurrent hospitalizations, and early mortality. Whereas rest was traditionally recommended for HF patients, there has been evidence that physical deconditioning may play a key role in the progression of symptoms and poor outcomes. Previous studies have shown positive effects of exercise training on exercise capacity, quality of life, and biomarkers and suggest that exercise training might improve survival and decrease HF hospitalizations. Nonetheless, there remains a safety concern regarding exercise training in HF and a large scale, multicenter, controlled clinical trial was needed to provide definitive clinical outcome data. Participants A total of 2,331 participants were randomized. 2,130 consented to share data with non-commercial entities, and 1,753 consented to share for commercial purposes. Design All participants underwent baseline cardiopulmonary exercise testing. Test results were reviewed by investigators to identify significant arrhythmias or ischemia that would prevent safe exercise training, to determine appropriate levels of exercise training, and to establish training heart rate ranges. Demographics, socioeconomic status, past medical history, current medications, physical exam, and the most recent laboratory tests were obtained prior to randomization. All participants received detailed self-management educational materials which included information on medications, fluid management, symptom exacerbation, sodium intake, and physical activity. Participants randomized to the exercise training arm first participated in a structured, group-based, supervised exercise program, with a goal of 3 sessions per week for a total of 36 sessions in 3 months. The primary exercises were walking, treadmill, or stationary cycling. Exercise was initiated at 15 to 30 minutes per session at a heart rate corresponding to 60% of heart rate reserve, and was increased after 6 sessions to 30 to 35 minutes duration and 70% of heart rate reserve. Participants began home-based exercise after completing 18 supervised sessions and were to fully transition to home exercise after 36 supervised sessions. The target training regimen for home exercise was 5 times per week for 40 minutes at a heart rate of 60% to 70% of heart rate reserve. Participants randomized to the usual care group were not provided with a formal exercise prescription. To provide comparable levels of attention from study personnel, all participants were called every 2 weeks for the first 9 months, monthly until 24 months of follow-up, and quarterly thereafter. Participants returned for clinic visits every 3 months for the first 2 years of participation and yearly thereafter for up to 4 years. Follow-up assessments included cardiopulmonary exercise testing, a 6-minute walk test, and a physical activity questionnaire. The primary end point was a composite of all-cause mortality or all-cause hospitalization. Secondary end points included all-cause mortality, the composite of cardiovascular mortality or cardiovascular hospitalization, and the composite of cardiovascular mortality or HF hospitalization. Conclusions After adjustment for highly prognostic predictors of the primary end point, exercise training was associated with modestly significant reductions for both all-cause mortality or hospitalization and cardiovascular mortality or heart failure hospitalization.

  Study phs003599

• All you need to know about our new DAC Portal

  With the DAC Portal, it is possible to streamline the process of managing access to sensitive data, ensuring that researchers have the necessary resources to advance scientific discovery while maintaining the highest standards of data protection and privacy. We know that, as a new tool, its first use can be complex. For this reason, in this article we will try to show all the elements of interest. Enjoy! Credentials: who needs to create a new user to access the DAC Portal and who doesn't? Only new users (since September the 12th) need to create an EGA account to access the DAC Portal. The EGA team went one step ahead by creating EGA accounts for former DAC members to login to the DAC Portal. These accounts are linked to the personal email used in the DAC structure: To check the linked email, DAC members can paste the DAC ID right after this link: https://metadata.ega-archive.org/dacs/ (e.g. https://metadata.ega-archive.org/dacs/EGAC00001002543) In case of password oblivion, it is possible to set a new one. All the process is channelled through the personal email. Some DAC members may be interested in updating the DAC email. This action can be done contacting our Helpdesk team. For the correct functioning of the DAC Portal, users must add the missing information of the DAC Profile. For a deeper dive, check out our documentation. The first step: knowing your workspace on the Portal Once logged in to the platform using the EGA User credentials, note the sections available: DACs and Policies. In the first one it is possible to check all user's registered DACs by default. It provides a comprehensive overview of each DAC, including its EGA accessions (EGAC), title, status, and the number of data access requests associated with each DAC. Whereas the Policies section is where users can manage and view all their registered policies, along with their associated EGA accessions, links, and titles. A drop-down menu is available with shortcuts to the most useful pages in the top right corner. It is possible to check DACs and policies, as well as creating new ones. In this menu, users can also contact the Helpdesk team using the “Need Help?” section to make inquiries about DACs and policies. Comprehending the DACs list & making the most of all the features Colours are crucial in the DAC's section as they will indicate the user role and the status in every committee, namely: Yellow: you are the administrator of the DAC and have full control to add other contacts, modify the content, and manage data access requests. Orange: you are a member of the DAC and have the authority to manage data access requests but cannot make any changes to the content. Blue: you have been invited to join the DAC and need to either accept or decline the invitation. Grey: the DAC is currently pending validation by the EGA Helpdesk team. Red: the DAC has been declined by the EGA Helpdesk team. Discover more information on how to view the message from Helpdesk containing the declination reason or how to validate or reject a DAC invitation by taking the tour of the DAC Portal. How to create, register and edit a DAC Creating a DAC is an easy process that only requires users to complete the necessary information. After that, the EGA Helpdesk team will review the proposal and validate the proposal. Once the DAC is validated it is possible for authorised users with admin role to edit it at any time, ensuring that all information and contacts associated with the committee is accurate and up to date. Membership management is controlled by searching for the EGA user looking for their username, email, or organisation. Please, note that for a person's details to appear in this search engine, they must have registered as a EGA user. Data Access Committee administrators manage two types of permissions that apply to contacts: Main contact and Role. Both can be modified at any time: Main contact refers to the primary person we firstly contact for any inquiry about the DAC (please, note that we can contact all DAC members, and this refers to the person we will contact first). Role defines the actions that can be taken by each contact. There are two possible status, admin and member, details of which can be found in the Take the Tour. Keep in mind that, to save the modifications, it is always necessary to click on “Update”. Moreover, it is also possible to delete any contact in a DAC whenever it is needed. The data request process: how to manage access requests The data request process is now channelled through the EGA website. Once a user sends a request access, the petition will go directly to the DAC Portal profile of the DAC members liked to the requested dataset. Whenever a request is received, a sand clock symbol will be displayed next to the DAC responsible for the dataset involved. By clicking on the DAC, it is possible to discover more information about requester(s). In this section, DAC Portal users will also be able to modify the display of the data access requests. It is possible to group requests by dataset accession or username, depending on the user preferences. Additionally, it is possible to isolate specific requests by user or dataset. To accept a request, users must slide the button to the right. Once the button turns green, it signifies that the request is accepted; the requester will be granted access to the requested dataset. To make lives easier, we have implemented a “Select all” button to easily accept or revoke multiple requests at once. To decline requests, it is necessary to slide the button to the left. A red button means the requester will not be granted access to the dataset. The DAC Portal will always ask to submit the reason why the data access was denied. Please, note that any decision, grant or denial, must be confirmed clicking the "Apply" button. This will update the status of the request and notify the requester accordingly. Taking control of the activity in the DAC Portal: checking the requests history The History button is a useful feature that allows users to access a list of all the requests that have been granted. This is especially useful for auditing purposes, as it enables to keep track of who has been granted access to the data and when. To facilitate control for those users with several requests we have included a filtering option. It allows to filter requests by user, mail, dataset, EGA ID, and date (these are combinable to boost the search). Don't forget about policies: creation, management, and update Similarly to the DACs section, in the Policies one users can manage and view all their registered policies. By clicking on any policy, it is possible to view its details as well as making any necessary updates or modifications. The sheets symbol and its adjacent number indicate the quantity of objects using a policy. By clicking in the location symbol users will go directly to the DAC page on the DAC Portal to see more information about that DAC. DAC Portal users can create new policies. The first step requires to link the policy to a registered DAC. After defining the title, users can either add a link to an external URL containing terms & conditions or write the policy content directly on the DAC Portal. Keep in mind that both options can be included. Data Use Ontology (DUO) codes can be added to new policies. These codes are used to specify the permitted and prohibited uses of the data. Please, note that some of them require a modifier to provide additional specificity. Find out more by checking out this specific content on the DAC Portal Tour. Policies can be modified at any given time by clicking on one registered policy, which will display the current information.

  Blog new-dac-portal

• RNA-seq of granulosa cells from 8 IVF patients in two age groups

  This dataset contains raw sequencing data of mRNA from granulosa cell samples from 8 human patients undergoing in vitro fertilization. All patients were normal responders referred for male infertility and were grouped into two age groups (younger than 31 or older than 38 years old). Each sample contains all granulosa cells collected from one patient on one collection date. Raw sequencing fastq files are available in this dataset, count tables are available in ArrayExpress (E-MTAB-13496).

  Dataset EGAD50000001210

• Identification of drug resistance genes in melanoma by mRNA gene expression

  We aim to sequence the mRNA transcriptome of 22 human melanoma cell lines in biological triplicate in order to define the gene expression profile of each cell line. The data will be correlated to the mutation status and the sensitivity to a panel of drugs in order to identify genes whose deregulation is associated to drug resistance This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001003244

• Identification of drug resistance genes in melanoma by small RNAs expression analysis

  We aim to sequence the small RNAs of 22 human melanoma cell lines in biological triplicate in order to define the microRNAs expression profile of each cell line. The data will be correlated to the mutation status and the sensitivity to a panel of drugs in order to identify genes whose deregulation is associated to drug resistance This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001003245

• Exome Sequencing to Identify Causes of Leukaemia Predisposing Congenital Neutropenias (2019-08-19)

  The objective of this study is to identify the causative genes in two unrelated congenital neutropenia families. We aim to whole exome sequence the affected individuals, unaffected siblings and parents in both cases in an effort to idenitfy the causative genetic mutation. Exome capture will be performed using Agilent SureSelect system. Subsequently, exome libraries will sequenced using the Illumina HiSeq platform. Sequence variant calling will be done in house and common variants excluded using public databases and data from unaffected family members. . This dataset contains all the data available for this study on 2019-08-19.

  Dataset EGAD00001005264