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• UK10K_RARE_THYROID

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches.Two cohorts of subjects are being analysed: Individuals with Congenital Hypothyroidism (CH) due either to dysgenesis or dyshormonogenesis; Patients with Resistance to Thyroid hormone (RTH), a disorder characterized by elevated thyroid hormones and variable tissue refractoriness to hormone action. The CH cohort has been enriched for genetic aetiologies by recruiting cases that are familial, on a consanguineous background or syndromic. The RTH cohort consists of cases in which candidate gene analyses have been negative.For further information with regard to this cohort please contact Krishna Chatterjee (kkc1@medschl.cam.ac.uk).

  Study EGAS00001000131

• Kids First Pediatric Research Study in Familial Predisposition to Hematopoietic Malignancies (SJFAMILY-HM)

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. Acute lymphoblastic leukemia (ALL) is the commonest childhood tumor and a leading cause of cancer death in children, adolescents and young adults. Hodgkin and non-Hodgkin lymphoma are also important hematologic malignancies (HM) that occur in children. Each are genetic diseases with growing evidence for a germline predisposition of both familial and sporadic cases, however the inherited genetic basis of ALL/lymphoma are poorly understood. Such knowledge is essential to gain mechanistic insight into the basis of tumor formation, and to guide genetic counseling and genetic management. Here we have assembled a large collection of familial HM kindreds, and extended recurrence cohorts of ALL and HL which will be used to identify the genetic basis of familial HM, examine the frequency of germline variants in sporadic ALL and HL, and to integrate inherited and somatic genomic data. These studies have high potential to provide fundamental new insights into the inherited genetic basis of HM, to provide important information to guide clinical management, and to provide an invaluable public resource of genomic data.

  Study phs001738

• Submitter Portal

  Submitter Portal The Submitter Portal does not support array submissions! Please refer to the array documentationAny new objects registered in the Submitter Portal will not be available for use in an array submission For further information please check our Submission FAQs, submission quickguide as well as submission terms! The metadata submission process can be difficult and time-consuming. For this reason, the EGA has developed the Submitter Portal, a tool that was created to offer a simplified and user-friendly method of registering metadata. Our portal provides features that are intended to make the input of metadata easier, ensuring that your data is registered correctly and effectively. Our page is divided into logical sections and includes a helpful video instruction to further assist you as you complete the submission process. With the Submitter Portal, you can rest assured that the submission of your data is in good hands. Submitter Portal Index Previous steps Access to Submitter Portal Start a Submission Take The Tour Tutorial Previous steps Create your EGA account To submit data, you first need to create your EGA user. Then, once your account has been verified by the Help Desk team, you will be able to request a submitter role and send the EGA Data Processing Agreement (DPA). In the case you already have an EGA account, or an ega-box (submission account), you can skip this step. Upload your files Please note that all your files must be encrypted using the Crypt4GH tool before upload them.As soon as you are assigned with a submitter role and added your public key to your profile, you will be able to connect to the EGA inbox and upload your files. Understand the EGA metadata schema It's crucial to comprehend the EGA metadata schema, a set of rules that specify how data is organised, described, and shared inside the EGA, in order to get the most out of this resource. Learn all about EGA metadata schema! Register your DAC and policy There are two objects in the EGA metadata schema that are registered in a separate portal. All DACs and policy objects are registered using the DAC Portal, a tool developed by EGA to help data controllers manage their data stored at the EGA. You can find relevant information in the DAC Portal Guide. Access to Submitter Portal 1. Request Submitter Role Once you have created your EGA user, request a Submitter Role and complete relevant information such as submission type and size. 2. Signature of the Data Processing Agreement The Data Processing Agreement (DPA) signed by CRG and EMBL-EBI (Joint Data Processors for the EGA) can be downloaded to the submitter for its signature. Further information related to the DPA can be in the Privacy Notice section. The DPA should be signed by a legal representative of the submitter with power of attorney/appointment duly authorised to sign contracts on behalf of the institution. The submitter will return a fully-executed copy of the DPA to us. Please note that due to the high volume of submissions to EGA the DPA is non-negotiable. Once you have completed all the information and attached the DPA signed, send your Submitter request and the EGA Helpdesk Team will validate it and send a confirmation to start submitting your metadata. Start a Submission The steps below will show you how to start a submission and are accompanied with a tutorial and the Take the tour of Submitter Portal. 1. Login Go to the Submitter Portal interface and log in using your EGA account credentials. 2. Create a submission The Submitter Portal interface will show you any already existing open submissions. To start a new submission, click on “Create a Submission”.In this phase, you have the option to add any collaborator(s) as well as their permissions (“Read only”, “Read & Write” or “Full Access”). Please note that to add a collaborator, they must also have a submitter role. When adding a collaborator, please enter the user’s full email address in the search field and select the user. For security reasons, the portal does not display partial matches, so the full email address must be entered.The collaborator option is available while the submission is open. In the event that the submission is closed, you will need to reopen it. To do this, you only need to make a small modification in any objects within the submission, for example, copy and paste a title or description of the submission. Once the submission is open, you can add a collaborator. Further information can be found in the Submission Tour 3. Create Study Click on Add Study and complete the form with the relevant information. The fields with an asterisk (*) are mandatory. Further information can be found in the Submission Tour4. Create Sample Sample registration can be done either individually or in batches by using a template. Batch upload: download the template and complete it with information about the sequencing samples. Upload the samples.csv, and the sample will be created.Add a single sample: complete the mandatory fields with the metadata information of your sample.  Further information can be found in the Submission Tour5. Create Experiment Register an experiment with ​information about the sequencing methods, protocols, and machines. Experiments generate the connection between the samples and the study. Further information can be found in the Submission Tour6. Create Run Samples, experiments, and files are linked through runs. To register a run, you will be asked to select the appropriate experiment and the file format. Run registration can be done either individually or in batches by using a template. Batch upload: download the template and complete it with the sample file linkage. Upload the run.csv, and the runs will register.As the INBOX is a directory, bear in mind to include the file path (/). Example: /filename.c4gh.Add single run: select the file format, sample, and experiment from the drop box. For re-using submitted samples, please use the EGA accession ID (EGANXXX). Please note that files must be uploaded to your inbox before linking your files and samples. Further information can be found in the Submission Tour7. Create Analysis Analysis should be only used for BAM/BAI or CRAM/CRAI pair, VCF, and phenotype linkage to samples. The analysis is an EGA-specific metadata object that links samples to files. This object also stores some metadata about your experiments, such as the experiment type, genome reference, or the platform used. **If only BAM or CRAM alignment files are submitted but not the original unaligned FASTQ files, then please make sure that the BAM or CRAM files also contain the unaligned reads. This is critical to enable primary re-analysis and re-alignment of the dataset using new tools or future genome assemblies.** Start by selecting the samples to be linked to the file, and then populate the required attribute fields. Please be aware of the existence of mandatory fields that must be populated.When populating the chromosome field (mandatory), please select the chromosomes from the checkbox. Please take in consideration that EGA allows for the re-use of any registered metadata. Therefore, a previously registered study or samples can be referenced for the analysis in the current data submission.Further information can be found in the Submission Tour 8. Create Dataset Dataset contains the collection of runs/analysis data files subjected to controlled access by being associated with a Policy. Complete the mandatory fields such as title, description, type and policy. Please, take in consideration that DAC and Policy must be registered in advance in the DAC Portal. Similar to other metadata objects, you can re-use previous runs or analyses, using their EGA accessions IDs (runs - EGAR, analyses - EGAZ). If you would like your dataset to be added to the cBioPortal instance, please review the cBioPortal documentation.Further information can be found in the Submission Tour 9. Finalise submission Once the files are ingested, please delete them from your SFTP INBOX after finalising your submission. This will prevent the files from reappearing in your Submitter Portal Inbox. Once you have completed your submission, click on the Finalise button and schedule an estimated release date. Afterwards, your submission will be sent to Helpdesk for approval. Please note that once the Helpdesk has approved your submission, you will receive the identifiers for your data. See the Frequently Asked Questions (FAQ) for more information. 10. Update closed submission If you want to append more files to a closed submission, you will need to reopen the submission where the dataset is registered.Please note that you can only modify datasets that begin with the ID EGAD5XXXXXXX.  Find the Submission: go to the Submitter Portal Menu -> Datasets section and find the submission ID (EGA0XXX). Reopen the submission where the dataset is located: to reopen a submission, simply register new metadata, such as runs or analyses, and the submission will automatically reopen and appear on the main page. You can also do a small edition, such as copying and pasting a title or description. Take The Tour The Submitter Portal Take The Tour is a visual guide of all the steps described previously about how to start a submission. Tutorial In this tutorial, we will show you how to use the Submitter Portal to register your metadata. Please note the video focuses on the run-based submission (for raw files - fastq - and aligned data - BAM/CRAM) and analysis-based submission (for your BAM/BAI pairs, variation -VCF - and phenotype files).

  Documentation submission/metadata/submission/sequencing-phenotype/submitter-portal

• Parallel Genomic Alterations of Antigen and Payload Targets Mediate Polyclonal Acquired Clinical Resistance to the Antibody Drug Conjugate Sacituzumab Govitecan

  Sacituzumab Govitecan (SG), a novel antibody drug conjugate (ADC) incorporating the anti-TROP2 antibody hRS7 conjugated to a topoisomerase-1 inhibitor (SN-38) payload, is the first ADC to be approved for advanced triple negative breast cancer (TNBC). However, mechanisms governing therapeutic resistance to SG are not known. We sought to identify mechanisms of de novo and acquired resistance to SG through unbiased whole-exome sequencing (WES) and RNA sequencing analysis of pre-treatment and multi-site post-progression (autopsy) tumor specimens. We examined three metastatic TNBC cases exhibiting (1) de novo progression, (2) stable disease, and (3) a deep response followed by progression, then mapped the temporal and spatial genomic evolution of acquired resistance in the responding patient. We then conducted additional pre-clinical experiments to validate the observed resistance mechanisms. TROP2 RNA and gene copy number were associated with de novo resistance, as case (1) was found to have absent TROP2 expression in all specimens, case (2) expressed TROP2, while case (3) exhibited both expression and focal genomic amplification of the TACSTD2/TROP2 locus. The genomic phylogeny tree inferred from case (3) post-progression specimens revealed one branch harboring an acquired canonical E418K resistance mutation in TOP1 (encoding topoisomerase 1) and a subsequent sub-clonal TOP1 inactivating frameshift mutation, while a distinct branch exhibited acquisition of a novel T256R missense mutation in TACSTD2 (encoding TROP2). Both the TOP1- and TACSTD2-mutant clones seeded multiple distinct metastatic sites. Through reconstitution experiments in TROP2 negative cells we found that TROP2 T256R is a stable protein with defective cell membrane localization and reduced cell surface binding by RS7 compared to wild-type TROP2. Collectively, these findings underscore TROP2 as a determinant of initial response to SG, and they reveal parallel and mutually exclusive polyclonal molecular mechanisms of acquired resistance involving the direct antibody target and drug payload target in distinct metastatic subclones of a single patient. While further research is needed to extend these novel findings, this study highlights the specificity of SG and illustrates how identifying such mechanisms will inform rational therapeutic strategies to overcome ADC resistance.  

  Study phs002555

• Genetic Testing to Understand and Address Renal Disease Disparities

  People of African ancestry (Blacks) have increased risk of kidney failure due to numerous socioeconomic, environmental, and clinical factors. Two variants in the APOL1 gene (GeneID: 8542) are now thought to account for much of the racial disparity associated with hypertensive kidney failure in Blacks. One in 7 AAs carry this risk allele, but it is nearly absent in other populations; the variants protect against infection with African trypanosomiasis which is endemic to Africa. However, this knowledge has not been translated into clinical care to help improve patient outcomes and address disparities. It is unknown whether patient or clinician knowledge of genetic risk impacts patient care (i.e., renal surveillance, BP medication use/intensification) or outcomes such as BP control and CKD. GUARDD is a randomized trial to evaluate the effects and challenges of incorporating genetic risk information into primary care. Hypertensive, nondiabetic, adults with self-reported African ancestry, without kidney dysfunction, are recruited from diverse clinical settings and randomized to undergo APOL1 genetic testing at baseline (intervention) or at one year (waitlist control). Prior to enrolling their patients, providers are educated about genomics and APOL1. Guided by a genetic counselor, trained staff return APOL1 results to patients and provide low-literacy educational materials. Real-time clinical decision support tools alert clinicians of their patients' APOL1 results and associated risk status at the point of care. Our academic - community clinical partnership designed a study to generate information about the impact of genetic risk information on our primary outcome - patient care (renal surveillance by clinicians, of serum creatinine and/or urine albumin tests. with a sub-aim of reduction of systolic blood pressure). Secondary outcomes include impact on primary outcomes at 12 months, psycho-behavioral differences of patients between groups and over time, clinician knowledge, attitudes and beliefs at baseline and 12 months, and differences in outcomes between those tested and not tested. GUARDD will help establish the effective implementation of APOL1 risk informed management of hypertensive patients at high risk of CKD, and will provide a robust framework for future endeavors to implement genomic medicine in diverse clinical practices. It will also add to the important dialog about factors that contribute to and may help eliminate racial disparities in kidney disease.

  Study phs001620

• NHLBI GO-ESP Family Studies: Idiopathic Bronchiectasis of unknown etiology that is not related to cystic fibrosis or classic primary ciliary dyskinesia or immune deficiency or any other known causes

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The major goal of this project is to apply next generation resequencing technology to identify disease-causing variants that cause bronchiectasis of unknown etiology (e.g. non cystic fibrosis (CF), classic primary ciliary dyskinesia (PCD), immune deficiency, or any other known cause of bronchiectasis), i.e., "idiopathic bronchiectasis." As part of our ongoing efforts to define the genetic cause of rare lung diseases, we have also studied families in whom diagnosis of PCD or other known etiologies could not be confirmed. We have systematically collected and stored the DNA and phenotypic data on each of the families in our cohort. The phenotypic data includes age, gender, ethnicity information, clinical data pertaining to the airways disease, including neonatal respiratory distress, otitis media, sinusitis and bronchiectasis, ciliary ultrastructure analysis, and microbial colonization (status of nontuberculosis mycobacterium). During the course of our study, we have acquired 98 unrelated patients in whom bronchiectasis seemed to be of unknown causes. We will be using 11 unrelated patients, 5 unrelated affected sib-pairs, and 3 affected sibs from a family from this cohort, based on 1) development of bronchiectasis in the absence of smoking, 2) a good family pedigree with available DNA, and 3) a family history of bronchiectasis and/or occurrence of airways disease in a sibling. Classic CF, PCD and immune deficiency were ruled out, based on the tests described above. Alpha-1 antiprotease deficiency work up was negative and none of the patients were tobacco users or smokers.

  Study phs000518

• AmsterdamUMC Data Access Committee for the study entitled "Carboxylesterase 1 mediates a distinctive metabolic profile of dendritic cells to attain an inflammatory phenotype"

  The current data access committee reviews and assesses data requests of researchers that seek to gain access to data presented in the manuscript entitled "Carboxylesterase 1 mediates a distinctive metabolic profile of dendritic cells to attain an inflammatory phenotype" as performed at the AmsterdamUMC, Amsterdam, Netherlands.

  Dac EGAC50000000178

• Human Tumor Atlas Network (HTAN)

  An NCI-funded Cancer Moonshot initiative to construct 3-dimensional atlases of the dynamic cellular, morphological, and molecular features of human cancers as they evolve from precancerous lesions to advanced disease.

  Study phs002371

• Whole genome sequencing of chondrosarcoma

  Massive parallel sequencing of 10 chondrosarcoma genomes was conducted to identify somatic mutations, structural alterations including fusion genes and mutation signatures that may help to comprehensively characterize the molecular features.

  Study EGAS00001000505

• A mathematical model of cell-free DNA fragment size reveals cancer-specific fragmentomic patterns

  This study aim to test a mathematical model of cfDNA length distribution across multiple biodiy flulids. It try to investigate biological mechanisms of cfDNA fragmentation and release.

  Study EGAS50000001560