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• Modeling Malignant Progression in Glioma

  Gliomas are the most common primary brain tumor in humans. Low-grade gliomas (WHO grade II) invariably progress to high-grade gliomas (WHO grade III or IV). Although malignant progression may take many years, the survival rate after transformation to a high-grade glioma is poor, often only 12-15 months. In this data set, we have identified low-grade gliomas that have progressed to high-grade gliomas or high-grade gliomas that have progressed from low-grade gliomas. Some cases are matched pairs (meaning we have both the original low-grade tumor and the subsequent high-grade tumor). The samples deposited have been analyzed with bulk-RNA sequencing. They are also de-identified but are clinically annotated. When available, genetic information including IDH mutation status, 1p/19q deletion and histological subtype are also included.

  Study phs002607

• Genetic Modifiers of Huntington's Disease

  Huntington's disease (HD) is a neurodegenerative disorder typically diagnosed in mid-life that is caused by expansion of an otherwise polymorphic CAG trinucleotide repeat. The mutation causes a gain-of-function of the huntingtin protein to trigger a pathogenic process that produces detectable phenotypic differences many years before the traditional diagnosis, which is based upon characteristic motor symptoms. The prediagnosis phase of pathogenesis is now the subject of intense scrutiny by an NINDS-funded longitudinal study, PREDICT-HD, in which undiagnosed gene carriers are followed longitudinally and subjected to detailed phenotyping (PREDICT-HD Huntington Disease Study -- dbGaP Study Accession: phs000222). This powerful approach, which offers the potential for moving the focus of therapeutic development to the decades prior to neurological disease diagnosis, is enabled by the fact that all individuals with HD have the same type of mutation, which can be determined at any time in life by a single HD CAG repeat PCR amplification assay. The precise length of the HD CAG repeat differs between individuals. There is a strong negative correlation between the number of CAG repeats and the age at onset of diagnostic neurological abnormalities in HD, such that the CAG repeat accounts for ~50% of the variation in age at diagnosis. Analysis of the remaining variance not explained by the length of the CAG repeat has shown that it is highly heritable, being due to genetic variation, elsewhere in the genome. The intent of the Genetic Modifiers of Huntington's Disease study is to identify genetic modifiers of HD pathogenesis by using genomewide association techniques in diagnosed HD individuals to identify genetic factors associated with the residual variance in age at onset not explained by the CAG repeat, and to extend these analyses to pre-diagnosis phenotypes, for example, those defined in the PREDICT-HD study. Identification of modifier genes is a top priority for HD research (and an example of an approach that can be applied in other late-onset genetic disorders), as it could provide clues to developing rational treatments that delay or prevent the pathogenic process from causing the ravages of the disease that ensue in the ~15 years of inexorable decline to ultimate death that now follows clinical diagnosis. To further that goal, the release of study version 2 makes available whole exome sequencing data of n=221 study participants.

  Study phs000371

• Identification of rare germline variants in familial multiple myeloma

  The risk of developing multiple myeloma (MM) in first-degree relatives of affected individuals is 2 to 4 fold higher than in the general population, implying the existence of inherited susceptibility. While over 20 common, low-penetrance variants have been associated with MM risk, less is known about rare, high-penetrance germline predisposition. We aimed to identify and characterize high/moderated penetrance germline variants in MM families using whole genome sequencing. For that purpose we identified families with at least two individuals diagnosed with MM or its precursors MGUS and smoldering MM. Also, patients with solitary plasmacytoma and AL amyloidosis were enrolled. We also recruited unaffected family members, and they were screened to exclude undetected MM or its precursor stages. After whole genome sequencing of blood DNA and filtering for rare variants (minor allele frequency <0.1%) and family segregation, variants are prioritized by a range of published in silico tools and literature search. The most promising variants are subjected to experimental validation to evaluate their functional relevance. Our data will provide guidance to worldwide efforts to unravel germline predisposition in MM and validation of the proposed variants and genes.

  Study EGAS00001004734

• Dataset for NSCLC-RNA

  Rare cancer sequencing data of 45 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008846

• Circulating RNAs in Acute Heart Failure (CRUCIAL)

  The purpose of this American Heart Association-funded and NIH-funded study is to examine circulating RNAs in the acute congestive heart failure (CHF) setting, and how they change with decongestive therapy, and their function in vitro and in vivo. The investigators are testing the hypothesis that ex-RNA levels change significantly during decongestion therapy and can be used as a marker of those individuals who respond to CHF therapy (in terms of cardiac structure or outcome). Additionally, the translational research design allows the investigators to assay the effects of these RNAs on tissue phenotypes in vitro.

  Study phs003403

• NINDS Family-Based Whole-Genome Sequencing to Find Modifiers of Age of Onset in Huntington's Disease

  The goal of our studies is to identify genetic modifiers of neurodegeneration in Huntington's disease (HD). HD is caused by expansion of CAG repeats in the huntingtin (Htt) gene, with longer stretches often leading to more rapid disease onset and progression. Yet, for a given number of repeats, the age of symptom onset can be variable, differing by up to decades. Thus, the age of onset of motor symptoms in HD is only partly explained by the length of the CAG expansion. Available evidence suggests that genetic modifiers contribute to the variation in HD onset. Identifying genetic modifiers is important because they may provide critical insights into HD pathogenesis and reveal key pathways that could be targeted by novel HD therapeutics. This is important since there are no disease-modifying therapies for HD, and mHtt is an unattractive small-molecule drug target. We recruited 21 HD families with varying characteristics of disease progression and age of onset and obtained medical histories, clinical records and DNA samples that were subjected to whole-genome sequencing (WGS). These WGS data describe families of 104 subjects, including HD patients and their unaffected family members. These individuals were selected based on individual clinical histories and family structures that best fit our criteria for expressing potential genetic modifiers. We are testing the hypothesis that novel, rare genetic variants contribute to HD and those genetic modifiers can be identified by WGS.

  Study phs001071

• 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

• NHLBI and NIA The New England Centenarian Study (NECS)

  Supercentenarians (age 110+ years old) generally delay or escape age-related diseases and disability well beyond the age one hundred and this exceptional survival is likely to be influenced by a genetic predisposition that includes both common and rare genetic variants. In this report, we describe the complete genomic sequences of male and female supercentenarians, both age >114 years old. We show that: (1) the sequence variant spectrum of these two individuals' DNA sequences is largely comparable to existing non-supercentenarian genomes; (2) the two individuals do not appear to carry most of the well-established human longevity enabling variants already reported in the literature; (3) they have a comparable number of known disease-associated variants relative to most human genomes sequenced to date; (4) approximately 1% of the variants these individuals possess are novel and may point to new genes involved in exceptional longevity; and (5) both individuals are enriched for longevity-associated variants that we discovered through a large genome-wide association study. These analyses suggest that there are both common and rare longevity associated variants that may counter the effects of disease predisposing variants and extend lifespan. The continued analysis of the genomes of these rare individuals who have survived to extremely old ages should provide insight into the processes that contribute to the maintenance of health during extreme ageing.

  Study phs000451

• Host whole genome variations are associated with neurocognitive outcome in survivors of pediatric medulloblastoma

  Host whole genome analysis is a promising source of predictive information for long-term morbidity in cancer survivors. However, studies on genetic predictors of long-term outcome, particularly neurocognitive function following chemoradiation in pediatric oncology are limited. In the present study, we evaluated variations in host whole genome single nucleotide polymorphisms (SNPs) and their association with cognitive outcome. Whole-genome SNP analysis of host peripheral blood was conducted on 22 medulloblastoma long-term survivors, of whom 18 completed neuropsychological testing. First, unsupervised consensus clustering of the most variable SNPs within 409 genes involved in DNA repair was performed. Discrete variant groups were identified, although they were not associated with cognitive outcome, suggesting that variations in genes corresponding to a single functional group may be insufficient to predict long-term outcome alone. In support of this interpretation, unsupervised hierarchical clustering analysis using disease-associated gene variants by cognitive impairment status yielded two distinct variant clusters comprised of 36 variants, 34 of which were in noncoding regions. These findings illustrate for the first time that cognitively impaired survivors have a distinct variant profile compared to other medulloblastoma survivors. Future research in larger cohorts is needed to validate host genome predictors of cognitive impairment that may impact clinical management.

  Study EGAS00001002996

• Genetic Analysis of Normal Human Facial Variation

  The purpose of this project is to identify genes associated with normal human quantitative facial variation. The motivation for this project stems from the fact that very little is known about how variation in specific genes relates to the diversity of facial forms commonly observed in humans. Viable candidates for these morphogenes originate from a number of sources: tissue expression studies, animal models with targeted or spontaneous mutations, and genetic syndromes with craniofacial manifestations. Importantly, understanding the genetic basis for normal facial variation also has important implications for health-related research. For example, this work has the potential to shed light on the factors influencing liability to common craniofacial anomalies such as orofacial clefts. There is now ample evidence that certain facial features (e.g., increased midfacial retrusion) characterize individuals genetically at-risk for orofacial clefts (e.g., biological relatives of affected cases). While these predisposing facial features are statistically over-represented in at-risk groups, they are also common in the general population. Since many of the current candidate genes for clefting are thought to play a critical role in facial morphogenesis, variation in these genes may also underlie normal variation in these facial features. These candidate genes, however, probably represent only a small fraction of the total number of loci influencing normal human facial variation. Phenotypes for this project were obtained from over 3000 healthy Caucasian subjects recruited through three separate studies. The majority of the subjects were recruited as part of the 3D Facial Norms Project, which is described in extensive detail here: (https://www.facebase.org/facial_norms/notes). The provided dbGaP phenotypes include a series of anthropometric craniofacial measurements (linear distances) primarily derived from 3D photographic facial surface scans (see previous hyperlink). The specific genotyping requested is described elsewhere in this document. Our analysis team is pursuing a variety of different analytic approaches to derive genetically informative phenotypes, including various shape-based morphometric methods. For those interested in pursuing more advanced phenotypic approaches, the original 3D surface scans and additional phenotypic traits are available to researchers through the FaceBase Consortium. This dataset has the potential to facilitate the discovery of new genetic loci with an important role in both normal and abnormal facial development. It may also serve as a dataset to test hypotheses regarding specific SNP associations (e.g. as a replication dataset) or as part of a larger meta-analysis.

  Study phs000949