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• A Population Genomics Study Using a Disease-Targeted Cell model: Integration of

  The common genetic variants associated with complex traits typically lie in non-coding DNA and may alter gene regulation in a cell type-specific manner. Consequently, the choice of tissue or cell model in the dissection of disease associations is important. We carried out an expression quantitative trait loci (eQTL) study of primary human osteoblasts (HOb) derived from 95 unrelated donors of Swedish origin, each represented by two independently derived primary lines to provide biological replication. We combined our data with publicly available information from a genome-wide association study (GWAS) of bone mineral density (BMD). The top 2000 BMD-associated SNPs were tested for cis-association of gene expression in HObs and in lymphoblastoid cell lines (LCLs) using publicly available data and showed that HObs have a significantly greater enrichment (threefold) of converging cis-eQTLs as compared to LCLs. The top 10 BMD loci with SNPs showing strong cis-effects on gene expression in HObs were selected for further validation using a staged design in two cohorts of Caucasian male subjects. All 10 variants were tested in the Swedish MrOS Cohort (n = 3014), providing evidence for two novel BMD loci (SRR and MSH3). These variants were then tested in the Rotterdam Study (n = 2090), yielding converging evidence for BMD association at the 17p13.3 SRR locus. The cis-regulatory effect was further fine-mapped to the proximal promoter of the SRR gene (rs3744270). Our results suggest that primary cells relevant to disease phenotypes complement traditional approaches for prioritization and validation of GWAS hits for follow-up studies. Reprinted from Grundberg E, Kwan T, Ge B et al., Genome Res Nov 2009, with permission from Genome Research, Cold Spring Harbor Press, PMID:19654370.

  Study phs000225

• Sequence Data from the phase 2 PrE0505 trial of Durvalumab with First Line Platinum-Pemetrexed for Unresectable Pleural Mesothelioma

  Mesothelioma is a rare and fatal cancer with limited therapeutic options until the recent approval of combination immune checkpoint blockade. We report the results of the phase 2 PrE0505 trial (NCT02899195) of the anti-PD-L1 antibody, durvalumab, plus platinum-based and pemetrexed chemotherapy for patients with previously untreated unresectable pleural mesothelioma. The primary endpoint was overall survival compared to historic control with cisplatin and pemetrexed chemotherapy. The combination of durvalumab with chemotherapy met the pre-specified primary endpoint reaching a median survival of 20.4 months vs. 12.1 months with historic control. Treatment emergent adverse events were consistent with known side effects of chemotherapy and all adverse events due to immunotherapy were grade ≤2. Integrated genomic and immune cell repertoire analyses revealed that a higher immunogenic mutation burden coupled with a more diverse T cell repertoire were linked with favorable clinical outcome. Structural genome-wide analyses demonstrated a higher degree of genomic instability in responding tumors of epithelioid histology. Patients with germline alterations in cancer predisposing genes, especially those involved in DNA repair, were more likely to attain long term survival. Our findings indicate that concurrent durvalumab with platinum-based chemotherapy has promising clinical activity and that responses are driven by the complex genomic background of malignant pleural mesothelioma.

  Study EGAS00001005426

• Study of Cutaneous Biology of Cutaneous T Cell Lymphoma

  This study is designed to help us understand the biological factors that contribute to the development of Cutaneous T Cell Lymphoma (CTCL) through the use of single-cell -omics technologies. The data that will be available include single-cell RNAseq and paired single-cell TCRseq data from the primary lesions of CTCL patients.The number of consented subjects listed here is artificially inflated by one to account for the pooling of all subjects.

  Study phs002717

• Identification and targeting of extremely high-risk gamma delta T-ALL in children

  Acute lymphoblastic leukemia expressing the gamma delta T cell receptor (γδ T-ALL) is an uncommon, poorly understood disease. We studied 200 pediatric γδ T-ALL enrolled on clinical trials to understand the clinical and genetic features of this disease, which showed variation in outcome according to age and genetic driver. γδ T-ALL diagnosed in children under three years of age was extremely high-risk and enriched for genetic alterations leading to both LMO2 activation and STAG2 inactivation. Using patient samples and isogenic cell lines, we show that inactivation of STAG2 profoundly perturbs chromatin organization by altering enhancer-promoter looping and results in deregulation of gene expression related to T-cell differentiation. High throughput drug screening identified a vulnerability in DNA repair pathways arising from STAG2 inactivation, which was efficaciously targeted by PARP inhibition. These data provide a diagnostic and therapeutic framework for classification and risk stratification of pediatric γδ T-ALL.

  Study EGAS50000000018

• Neuroblastoma heterogeneity

  Neuroblastoma is a pediatric solid tumor characterized by strong clinical heterogeneity. Although certain complex genomic alterations, such as extrachromosomal DNA amplifications (ecDNA), are associated with adverse outcomes and have been recurrently detected in neuroblastomas, the mutational processes involved in their generation remain largely unclear. By examining the topography of complex rearrangements along with mutational signatures derived from all variant classes, we identify previously unrecognized co-occurring mutational footprints, which we termed mutational scenarios. We demonstrate that clinical neuroblastoma heterogeneity is linked to differences in the processes driving these mutational scenarios. Whereas high-risk MYCN-amplified neuroblastoma genomes were characterized by signs of replication slippage and stress, homologous recombination-associated signatures defined high-risk non-MYCN-amplified patients. Non-high-risk neuroblastomas, on the other hand, were marked by footprints of chromosome missegregation and TOP1 mutational activity. This analysis provides a systematic perspective on the repertoire of mutational patterns that contribute to clinical neuroblastoma heterogeneity.

  Study EGAS00001007016

• Study of complex rearrangements and mutational signatures in neuroblastoma heterogeneous risk groups.

  Neuroblastoma is a pediatric solid tumor characterized by strong clinical heterogeneity. Although certain complex genomic alterations, such as extrachromosomal DNA amplifications (ecDNA), are associated with adverse outcome and have been recurrently detected in neuroblastomas, the mutational processes involved in their generation remain largely unclear. By examining the topography of complex rearrangements along with mutational signatures derived from all variant classes, we identify previously unrecognized co-occurring mutational footprints, which we termed mutational scenarios. We demonstrate that clinical neuroblastoma heterogeneity is linked to differences in the processes driving these mutational scenarios. Whereas high-risk MYCN-amplified neuroblastoma genomes were characterized by signs of replication slippage and stress, homologous recombination-associated signatures defined high-risk non-MYCN-amplified patients. Non-high-risk neuroblastomas, on the other hand, were marked by footprints of chromosome missegregation and TOP1 mutational activity. This analysis provides a systematic perspective on the repertoire of mutational patterns that contribute to clinical neuroblastoma heterogeneity.

  Study EGAS00001006983

• Neuroblastoma heterogeneity

  Neuroblastoma is a pediatric solid tumor characterized by strong clinical heterogeneity. Although certain complex genomic alterations, such as extrachromosomal DNA amplifications (ecDNA), are associated with adverse outcomes and have been recurrently detected in neuroblastomas, the mutational processes involved in their generation remain largely unclear. By examining the topography of complex rearrangements along with mutational signatures derived from all variant classes, we identify previously unrecognized co-occurring mutational footprints, which we termed mutational scenarios. We demonstrate that clinical neuroblastoma heterogeneity is linked to differences in the processes driving these mutational scenarios. Whereas high-risk MYCN-amplified neuroblastoma genomes were characterized by signs of replication slippage and stress, homologous recombination-associated signatures defined high-risk non-MYCN-amplified patients. Non-high-risk neuroblastomas, on the other hand, were marked by footprints of chromosome missegregation and TOP1 mutational activity. This analysis provides a systematic perspective on the repertoire of mutational patterns that contribute to clinical neuroblastoma heterogeneity.

  Study EGAS00001007019

• To determine the mutational impact of the in vitro culture, clonal human adult and pluripotent stem cell lines were subjected to a second clonal step after 3 months of culture. These subclones were whole genome sequenced to identify all the mutations that accumulated during the 3 month culture period.

  Genetic changes acquired during culture pose a potential risk for the successful application of stem cells. To assess the risk of in vitro expansion on mutation accumulation we have performed whole genome sequencing of clonally expanded human induced pluripotent stem cells (iPS cells) and adult stem cells (ASCs) to identify all mutations that accumulated over a fixed culture period. We find that ASCs acquire more single nucleotide variants (SNVs) and indels per population doubling than the iPS cells. When compared with ASCs, iPS cells are more vulnerable to mutations in genes and promoters. Mutational analysis revealed a clear in vitro induced mutational signature that is irrespective of stem cell type. This in vitro signature is characterized by C to G transversions that are probably caused by oxidative stress. Additionally, we observed stem cell specific mutational signatures and differences in transcriptional strand bias, indicating differential activity of DNA repair mechanisms between stem cell types in culture. In conclusion, in vitro culture induces mutation accumulation in iPS cells and ASCs. Culture under low-oxygen tension may help to reduce the number of culture-induced mutations.

  Study EGAS00001002955

• Differential Mutations in Matched Primary and Metastatic Colorectal Cancers

  This study compares DNA mutations detected in matched primary and metastatic colorectal cancer samples from 18 individuals across 1,321 genes. We found many more mutations were shared between tumor pairs (avg. 33.3 mutations/tumor) than were discordant (avg. 2.3 mutations / tumor). Nearly all tumors showed at least one discordance, and these were observed in genes known to be involved in colorectal cancer progression. Therefore, although primary and metastatic colorectal tumors are highly genetically concordant, evidence exists for discordance, which has clinical implications especially in situations of chemotherapy resistance or insensitivity.

  Study phs001084

• Paired exome and low-coverage genome sequencing of osteosarcoma

  We perform longitudinal genome-sequencing analysis of 12 patients with metastatic or refractory osteosarcoma. The study was approved at the University Hospital Basel, following the approval of the ethical committee for mutational analysis of anonymized samples (“Ethikkommission beider Basel” ref. 274/12). All tumor samples were evaluated by an experienced bone pathologist to confirm the diagnosis.

  Study EGAS00001005199

• Chromoanasynthesis as a Cause of Jacobsen Syndrome

  Jacobsen syndrome (OMIM #147791) is a rare multisystem genomic disorder involving craniofacial abnormalities, intellectual disability, other neurodevelopmental defects and terminal truncation of chromosome 11q, typically deleting ~170 to >340 genes. We describe the first case of Jacobsen syndrome caused by congenital chromoanasynthesis, an extreme form of complex chromosomal rearrangement. Six duplications and five deletions occurred on one copy of chromosome 11q with microhomology signatures in the breakpoint junctions, indicating an all-at-once replication-based rearrangement mechanism in a gametocyte or early post-zygotic cell. Eighteen genes were deleted from the Jacobsen region, including KIRREL3, which is associated with intellectual disability. Patients of any age with abnormal immune function who have recurrent or unusual infections, whose blood tests show evidence of immune dysfunction, or who have GVHD, XSCID, CGD or LAD may be eligible for this study. Patients' parents, siblings, grandparents, children, aunts, uncles and first cousins of any age also may be included. Healthy normal volunteers between 18 and 85 years of age are recruited as controls.

  Study phs002036

• Data Access Committee for Genomics of bone marrow failure (BMF) and myelodysplastic syndromes (MDS)

  The Data Access Committee for the genomics of bone marrow failure and myelodysplastic syndrome project is responsible for reviewing applications for access to controlled human genomic and phenotypic datasets generated as part of this project. The DAC ensures that data sharing with qualified researchers is conducted in accordance with participant consent, institutional ethical approvals, and all applicable data protection regulations. 

  Dac EGAC50000000754

• ASsessing and Predicting Infant RSV Effects and Severity (AsPIRES) Study

  A prospective multi-year clinical translational study including three cohorts of term infants experiencing their first Respiratory Syncytial Virus (RSV) season. All infants are less than or equal to nine months of age at study entry. The three subject cohorts represent the full spectrum of RSV disease severity and include a birth cohort, a cohort of infants hospitalized for RSV disease and infants evaluated at ambulatory settings for RSV infection. All infants are followed longitudinally and evaluated at recognition of acute RSV infection and twice during convalescence. Innate and adaptive immune status are comprehensively measured in association with clinical, environmental, viral, and bacteriologic factors. Genome-wide expression is assessed in the nasal airways, and in sorted peripheral blood lymphocytes. The study goal is to Identify host responses to RSV infection and factors associated with severe disease.

  Study phs001201

• Targeted Illumina sequencing of 3399 plasma cfDNA samples and 1988 leukocyte DNA samples from 1995 metastatic prostate cancer patients

  Blood samples were collected from eight clinical trials and a British Columbia-based biobank. All plasma cfDNA and leukocyte DNA samples were processed with uniform methodology, and underwent targeted sequencing using a custom hybridization capture panel and Illumina instruments. Four different generations of custom hybridization capture panel were used, all providing coverage of the complete coding regions of 72 prostate cancer genes, and later panel generations also providing exhaustive coverage of the AR locus (including introns and flanking regulatory regions), as well as a genome-wide SNP grid for copy number analysis.

  Dataset EGAD50000001594

• Submission FAQ

  Submission FAQ Before Submission Is the EGA the right archive for my data? TThe most suitable archive for your data is dependent on the type of data you are wishing to submit and whether the data require public or controlled access. Public access is defined as complete and open access to all submitted data. On the contrary, controlled access, exerted by the EGA, requires formal applications to be made to access the submitted data files and metadata. EGA only accepts human-derived data subject to controlled access. If your submission contains other types of data, please choose the appropriate repository for it (see image below): ENA, EVA, ArrayExpress, BioSD and GWAS catalog.  Should your submission be subjected to controlled access? Data access conditions are normally defined in the original informed consent agreements signed by the participants involved in your study. All data submitted to the EGA is subject to controlled access. These consents prevent the derived data files, potentially identifiable, from being dispersed by open and public access. Controlled access data often refers to human data derived from medical research and consortium projects. If in doubt, consult the informed consent agreements that apply to your study The EGA enables you to hold a submission before publication. What data types can be submitted to the EGA? Data types accepted by the EGA can be split into three categories: Sequences: both in generic and platform-specific formats. Array-based: from raw signal files to processed matrices. Phenotypes: all possible phenotype formats are accepted. All manufacturer-specific raw data formats derived from major next generation sequencing platforms are accepted. Also generic sequence formats: flat reads in a FASTQ file, aligned sequences (BAM or CRAM files) as well as sequence variation files in VCF format. All array-based technologies are accepted, including raw data, intensity and analysis files, without any restriction on data formats accepted. We also accept and distribute phenotype data (associated to the samples) in almost any format: from an image to a README file. How long does a submission take? Submissions to EGA come in a variety of formats and sizes, thus it is difficult for us to exactly predict how long a submission will take. We, therefore, advise all of our submitters to allow as much time as possible to make a submission. Based on previous records, we anticipate that the submission process may take at least one month. The submitter’s familiarity with the procedures, possible technical issues that may arise during submission and the amount of data that is being submitted are the main factors that will affect the length of the submission process. However, each step of a regular submission should be considered when estimating the time it would take: Encryption of the files Upload of the files Metadata submission Archival of the files Release of the study and datasets to EGA webpage For example, the upload of the files depends on the submission size, while metadata submission mainly relies on each submitter’s expertise. Further, some steps (e.g. answering to inquiries) depend on the EGA Helpdesk team, which may take some days to be processed during busy times Is data deposited in the EGA secure? The EGA set-up consists of a secure computing facility for data processing, a shared EBI set-up for data submissions and distribution of data via data requests made through the EGA website. Data is also copied in the Barcelona Supercomputing Center (BSC) infrastructure, where all stored and distributed data is encrypted Data is encrypted along the submission process and stored securely, granting its access to authorised users exclusively. During the download process, through our Python Client or Aspera, all requested data is downloaded over secure https connections. All data at the EGA is encrypted, and only accessible (for log-in and download) through secure protocols. For further information please, visit our security overview. What documentation do I need to provide? All submissions require policy’s documentation: 'Data Access Agreement (DAA)', 'Data Processing Agreement (DPA)' and 'Authorized Submitters Formulary'. The data processors (EGA) and the data owners will also sign the DPA. Will all metadata be public? Among the submitted metadata we need to make the distinction between identifiable and unidentifiable metadata: (1) the former may allow the identification of the human the sample derived from (e.g. detailed geographical providence, personal name, family ancestry…); (2) while the latter can be used to interpret the data without compromising the anonymity of the patients. The majority of the metadata submitted to the EGA corresponds to the unidentifiable category (e.g. sequencer's model). This type of metadata is publicly available on the EGA website and other EBI resources/partners’ websites. On the other hand, some parts samples’ metadata are subject to being identifiable, and thus only accessible by authorized data requesters, with the exception of: 5 submitter-defined attributes of the sample: alias, title, subject_id, gender and phenotype. It is the submitter’s responsibility not to submit sensitive metadata in these public fields. 3 anonymised fields that pinpoint the sample record in archivals: sample’s EGA stable ID (EGAN…), BioSample ID (SAMEA…) and submitter’s center name. During Submission Are there any sample specific requirements for EGA? All samples submitted to the EGA must include the attributes of biological sex, subject ID (anonymised individual identifier) and phenotype information. These are critical for data findability and its analysis, and we highly recommend using controlled ontology terms where applicable. For example: defining tumour and non-tumour samples and/or defining disease state. The EGA recommends using the Experimental Factor Ontology Database to find ontologized terms that describe your sample phenotypes. How do I get an accession number to use in my publication? You will receive your study accession number (EGAS…) upon complete your submission, either: Programmatically. As soon as the metadata is submitted and validated your study will be assigned an accession number that will be given in the submission’s response. Manually registering your study and relevant metadata using the online metadata submission tool: the EGA submitter Portal. How are files uploaded to the EGA? Data files are uploaded into private submission drop boxes (i.e. environments to which you are granted access and where you can transfer your files) using INBOX or FTP. These spaces are provided as part of the submission procedure. Before uploading any file, you must encrypt your files, . Only encrypted files shall be uploaded to the drop boxes. Why does data need to to encrypted for my submitted files? It is one of the security steps the EGA has implemented. In case of a security breach, people without the proper encryption key will not be able to read or use the information that could have been leaked. This measure is essential when working with sensitive data, such as controlled access human data. All submitters must use crypt4gh to create EGA compliant files prior to uploading them. This encryption is GPG-based, using EGA’s public key. Why are my files not available if I see them in the INBOX? There exists a time window between the data upload and the availability of such files via the Submitter Portal. For this reason, some metadata (run and analysis objects) cannot be registered until at least 24 hours after the files have been uploaded to your box. Why are MD5 sum values generated for my submitted files? We require pre- and post- encryption MD5 (message-digest) checksum values to be provided for all submitted files. These 128-bit values are computed using the content of each file, creating unique sequences that allow us to ensure that file integrity has been maintained during the transfer process. In other words, if the MD5 checksums we generate and those you generated match, we infer that the content of the transferred files is correct (i.e. files are not corrupted or truncated). MD5 checksums are computed automatically using the crypt4gh tool provided. Your submission will not be accepted and may be significantly delayed if you do not provide MD5 checksum values for all data files in the required format. How can I check if my files are correctly uploaded to the inbox? It is important to check the status pf your file so you know whether your files are in the inbox, being processed, or if there is any issue with one of them. In order to check this, you should: Look for the file locally. Drag and drop it to the file table. Then bars will appear on the table, which means that we are processing it. Green: The files checksum are correct and your file will move to “ingested files”. No further actions are needed from your end.. Red: The files checksum does not match and your file needs to be re-uploaded. Please re-upload relevant files to your inbox using the same path. After Submission How do I use my accession number in my publication? We suggest the use of the below template, using your study accession ID (EGAS…) : 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 at https://ega-archive.org and "The European Genome-phenome Archive of human data consented for biomedical research" Your study ID will be the one that groups your whole submission, and thus its usage is recommended as such. Nevertheless, all metadata submitted to EGA hold a unique and persistent identifier (starting with EGA…) that can be used to identify specific records. For example, you could reference a specific dataset (EGAD…) or sample (EGAN…) in your publications (see full list of identifiers). How do I make my data searchable? Once you have finalized your submission, you can schedule the data release. Please take into account that the release process needs time for the files to be archived in our system, and for the Helpdesk team to validate your submission. Can I withdraw (meta)data from the EGA? We have methods in place for the secure removal of deposited (meta)data. Contact EGA-helpdesk for further details. EGA complies with FAIRness of (meta)data, and thus, even when the data is removed we keep an entry for their identifiers in our system. In other words, we execute a soft delete on canceled objects (e.g. a study): metadata is still stored in our systems, but it loses all links, cannot be queried and data files cannot be retrieved anymore. The reason behind this behaviour is so that queries using withdrawn data properly respond back (see example of a canceled study). What happens to the data once it has been submitted to the EGA? When the data is submitted, the submitter can choose either keep their data private or schedule the release of their data.

  Documentation submission/metadata/submission/FAQ

• Single Cell Targeted DNA sequencing for Variant Calling in T-ALL

  This dataset contains the raw fastq-files and the VCF files of single cell targeted DNA sequening with the MissionBio Tapestri platform. This was performed on 8 male pediatric T-ALL cases: X09-XB37-XB47-XD83-XF91-XF97-XF100-XF121. For some patients we have timepoints during treatment: XF100 and XG121. XD83 is a patient that relapsed twice.

  Dataset EGAD00001006167

• Cisplatin increases sensitivity to FGFR inhibition in patient-derived xenograft models of lung squamous cell carcinoma

  Lung squamous cell carcinoma (SqCC) is a molecularly complex and genomically unstable disease. No targeted therapy is currently approved for lung SqCC, although potential oncogenic drivers of SqCC have been identified, including amplification of the fibroblast growth factor receptor 1 (FGFR1). Reports from a recently completed clinical trial indicate low response rates in patients treated with FGFR tyrosine kinase inhibitors, suggesting inadequacy of FGFR1 amplification as a biomarker of response, or the need for combination treatment. We aimed to develop accurate models of lung SqCC and determine improved targeted therapies for these tumors. We show that detection of FGFR1 mRNA by RNA in situ hybridisation is a better predictor of response to FGFR inhibition than FGFR1 gene amplification using clinically relevant patient-derived xenograft (PDX) models of lung SqCC. FGFR1-overexpressing tumors were observed in all histological subtypes of non-small cell lung cancers (NSCLC) as assessed on a tissue microarray, indicating a broader range of tumors that may respond to FGFR inhibitors. In FGFR1-overexpressing PDX tumors, we observed increased differentiation and reduced proliferation following FGFR inhibition. Combination therapy with cisplatin was able to increase tumor cell death, and dramatically prolonged animal survival compared to single agent treatment. Our data suggest that FGFR tyrosine kinase inhibitors can benefit NSCLC patients with FGFR1-overexpressing tumors and provides a rationale for clinical trials combining cisplatin with FGFR inhibitors.

  Study EGAS00001002423

• Genetic Underpinnings of Ethnic Disparities in Bone Toxicities Between Hispanic and Non-Hispanic Children Treated for Acute Lymphoblastic Leukemia

  Acute lymphoblastic leukemia (ALL) is the most common malignancy among children and young adolescents. More than 90% of children are cured with a combination of multiple chemotherapeutic drugs. Some may suffer from debilitating toxicities due to the cytotoxic drugs, necessitating pharmacogenetic research to search for genetic markers predictive of treatment toxicities, so that treatment can be better tailored based on patients' genetic makeup. Bone toxicities, including osteonecrosis and fractures, most often due to glucocorticoids, are the most common complications in ALL, which have long-lasting detrimental impact on the still developing skeletons in children. In DFCI ALL Consortium Protocol 05-001, a multi-center clinical trial for childhood ALL conducted in Canada and the US, we found that Hispanic children had less drug toxicities to their bones than non-Hispanic children. Although reasons for the observed ethnic differences are largely unknown, patients' inherited genetic background may be at play. This study seeks to perform a novel pharmacogenomic study based on multi-site clinical trials DFCI ALL Consortium Protocol 05-001 and 11-001 to identify genetic underpinnings of ethnic disparities in bone toxicities.

  Study phs002317

• eMERGE Network Phase III Clinical Sequencing: eMERGEseq Panel

  The Electronic Medical Records and Genomics (eMERGE) Network is a National Institutes of Health (NIH)-organized and funded consortium of U.S. medical research institutions. The primary goal of the eMERGE Network is to develop, disseminate, and apply approaches to research that combine biorepositories with electronic medical record (EMR) systems for genomic discovery and genomic medicine implementation research. eMERGE was announced in September 2007 and began its third phase in September 2015. eMERGE III consists of nine study sites, two central sequencing and genotyping facilities, and a coordinating center. eMERGE Phase III aims to: 1) sequence and assess the phenotypic implication of rare variants in a custom designed eMERGEseq panel consisting of 109 genes (including 56 ACMG actionable finding list genes and the top 6 genes from each site relevant to their specific aims), as well as approximately 1400 SNPs; 2) assess the phenotypic implications of these variants by developing, validating and implementing new phenotype algorithms, 3) integrate genetic variants into EMRs to inform clinical care; and 4) create community resources. Included in this study are: ~24,000 eMERGE participants from 10 eMERGE III study sites. Corresponding demographics, body mass index measurements. Top PheWAS codes generated from a collated list of ICD codes from all study sites. Study sites and participants include: Cincinnati Children's Hospital Medical Center (CCHMC): Cincinnati Children's Hospital Medical Center (CCHMC) is a not-for-profit hospital and research center pioneering breakthrough treatments, providing outstanding family-centered patient care and training healthcare professionals for the future, and dedicated to improving health and welfare of children and to the shared purpose of discovery and practical application of new genomic information to the ordinary care of children. We bring a comprehensive electronic health record (EPIC), a deidentified i2b2 data warehouse of 680K patient records, a biobank with >261,000 consents that allow return of results to >84,000 patients and guardians who have provided DNA samples, and hundreds of faculty and senior staff who make genomics or informatics an active focus of their research. CCHMC will help the eMERGE III Steering Committee identify genes for the eMERGE III targeted sequencing panel, provide 3,000 DNA samples from CCHMC patients to be sequenced, review targeted gene panels from clinical care at CCHMC for somatic mosaicism and reinterpretation, and further develop and disseminate a software workflow suite for sequence analysis. We will also extend our work generating phenotype algorithms using heuristic and machine learning methods to many new childhood diseases. We will develop tools to evaluate adolescent return of results preferences, examine the ethical and legal obligations and potential to reanalyze results, and develop clinical decision support for phenotyping, test ordering, and returning sequencing results. Children's Hospital of Philadelphia (CHOP): The Center for Applied Genomics (CAG) is a specialized Center of Emphasis at the Children's Hospital of Philadelphia (CHOP), and one of the world's largest genetics research programs, with to state-of-the-art high-throughput sequencing and genotyping technology. Our primary goal is to translate basic research findings to medical innovations. We aim to develop new and better ways to diagnose and treat children affected by rare and complex medical disorders, including asthma, autism, epilepsy, pediatric cancer, learning disabilities, and a range of rare diseases. Ultimately, our objective is to generate new diagnostic tests and to guide physicians to the most appropriate therapies. Participants were recruited from the CAG biorepository (n>450,000), specifically from >100,000 CHOP pediatric patients and family members, which is enriched for rare-diseases (n>12,000). Center for Applied Genomics, The Children's Hospital of Philadelphia We gratefully thank all the children and their families who enrolled in this study, and all individuals who donated blood samples for research purposes. Genotyping for this project was performed at the Center for Applied Genomics and supported by an Institutional Development Award from The Children's Hospital of Philadelphia. Sequencing was supported by the National Institutes of Health through an award from the National Human Genome Research Institute's Electronic Medical Records and Genomics (eMERGE) program (U01HG008684). Columbia University: The goal of the Columbia eMERGE III project is to develop methods for integrating genomic data in EHRs and to study the impact of such genomic informatics interventions on the health of a diverse, underserved urban adult English- and Spanish-speaking patient population in Northern Manhattan served by Columbia University Medical Center/New York-Presbyterian Hospital system. The study group is 2500 patients recruited from diverse clinics and community outreach centers of self-reported White (~61%), Asian (~11%), African-American (~11%), American Indian/Alaska Native (<1%) racial and Hispanic (~33%) ethnic backgrounds. There are two subgroups in the study cohort - a retrospective group (N=1052) that includes patients from oncology and nephrology clinics, and a prospective one (N=1448) that includes healthy individuals as well as participants with diverse medical conditions. Confirmed pathogenic variants in 70 selected genes will be returned to participants and their healthcare providers through the EHR integration. Participants are able to choose the results they receive and will have the freedom to meet with a genetic counselor and a geneticist to review results. The impact of genetic testing on clinical care is determined by periodic monitoring of EHRs. Geisinger: Samples and phenotype data in this study were provided by the Geisinger MyCode® Community Health Initiative. Participants are recruited across the Geisinger System via online consents or in-person consents at a hospital or clinic visit. Enrollment is ongoing with over 100,000 individuals currently consented. Partners Healthcare (Harvard University): The Partners HealthCare Biobank is a large research program designed to help researchers understand how people's health is affected by their genes, lifestyle, and environment. This large research data and sample repository provides access to high-quality, consented blood samples to help foster research, advance our understanding of the causes of common diseases, and advance the practice of medicine. For the Partners research community (Massachusetts General Hospital and Brigham and Women's Hospital), the Biobank provides: Banked samples (plasma, serum, and DNA) collected from consented patients Blood samples that were discarded after clinical testing in the Crimson Cores maintained in the Brigham and Women's Hospital and Massachusetts General Hospital Pathology Departments Sample handling and preparation services Link to the biobank data to the Partners Research Patient Data Registry (RPDR) a research instance of our electronic clinical chart Data access through our research portal. To date, over 70,000 Partners patients have given their consent to enroll, give a blood sample, receive research results and agreed to be re-contacted for additional research studies. The Biobank has enabled Partners investigators to compete for nationally recognized grants in personalized medicine such as a clinical electronic Medical Records and Genomics network (eMERGE) site and the national All of US program. The Biobank currently supports over 120 Partners investigators and over 130 million dollars in NIH research. Kaiser Permanente Washington/ (KPWA) / University of Washington (UW): KPWA participants were enrolled in the eMERGE Network through the Northwest Institute of Genetic Medicine (NWIGM) biorepository, and provided the appropriate consent to receive clinically relevant genetic results (N=2,500.) NWIGM is based at the University of Washington and co-managed by the University of Washington and KPWA. The purpose of the NWIGM biorepository is to build infrastructure and resources to carry out a broad range of future genetic research. KPWA members enrolled in the biorepository are asked to provide informed consent to providing a DNA sample for storage in the NWIGM biorepository. The consent is purposefully broad to serve the dual purpose of reducing the burden on researchers who wish to use this biorepository and the IRB committees who will be responsible for reviewing these requests in the future. Participants were eligible if aged 50 - 65 years old at the time of their enrollment into the NWIGM repository, living, enrolled in KPWA's integrated group practice, and had completed an online Health Risk Appraisal. The selection algorithm was based on several data sources from the EHR at KPWA. 1) Demographics - participants with self-reported race as Asian ancestry were prioritized and selected to enrich for non-European ancestry. The KPWA eMERGE cohort includes N=1,245 members of Asian ancestry. 2) Participants were also selected for a history of colorectal cancer (N=1,255), in order to allow us to enrich germline pathogenic variants. Mayo Clinic: The Return of Actionable Variants Empirical (RAVE) Study was approved by the Mayo Clinic IRB. We recruited 2537 participants from Mayo Clinic biobanks in Rochester, MN, who had hypercholesterolemia or colon polyps, thereby enriching for Familial hypercholesterolemia (FH) and monogenic causes of colorectal cancer (CRC). Additional eligibility criteria were: 1) residents of Southeast MN who were alive and aged 18-70 years; 2) LDL-C level >155 or >120 mg/dl while on lipid-lowering therapy; 3) no known cause of secondary hyperlipidemia; and 4) no cognitive impairment or dementia that would compromise their ability to give written informed consent. Based on these criteria, we identified 5270 eligible patients and obtained informed consent from 3030 participants. Recruitment was conducted in waves and utilized mailed recruitment packets consisting of a study brochure, a written informed consent form, a baseline psychosocial questionnaire, and a return postage-paid envelope. DNA of 2537 participants was sent for CLIA-certified targeted sequencing of 109 genes including genes associated with FH and CRC. Targeted sequencing and genotyping was performed in a Central Laboratory Improvement Amendment (CLIA)-certified laboratory. Northwestern University: Samples and data used in this study were obtained from patients from Northwestern Medicine, an integrated healthcare system, formed through a partnership of Northwestern Memorial HealthCare and Northwestern University Feinberg School of Medicine. Participants include a retrospective cohort from the Northwestern Pharmacogenomics Study, funded through the eMERGE II project, NHGRI (3U01HG006388-02S1) and a prospective cohort from the Genetic Testing and Your Health Study, funded through the eMERGE III project, NHGRI (U01HG008673). Patients were eligible to participate if they were18 years or older and see a physician at Northwestern Medicine. Patients consented to genetic testing and to allow their results to be placed in their electronic medical record. Vanderbilt University Medical Center: Vanderbilt University Medical Center (VUMC) participants were enrolled in the eMERGE Network through the Vanderbilt Genome-Electronic Records (VGER) project. Patients were provided the appropriate consent to receive clinically relevant genetic results (N=2,700). Participants were eligible if aged 21 or over, had a healthcare provider at VUMC, and visited the provider at least 3 times in the past 3 years. Meharry Medical College: Inclusion of ethnic groups in genomic research is critical to identify possible reasons for health disparities. African-Americans are being enrolled in various outpatient clinics of Nashville General Hospital at Meharry, an inner city hospital primary serving a poorer patient group. A total of 500 African Americans with four cancer types demonstrating health disparities in this population - prostate, colon, breast, lung are identified and approached by clinical research coordinators. The purpose of the study is to determine if any genetic information can be identified from these patients who have or are at high risk of one of these disparate cancers. All participants provide written informed consent and HIPAA authorization to provide blood samples for broad research use and permission to access data in their hospital electronic medical record for research now and in the future. An extensive demographic profile is obtained and entered into a REDCap database. Blood samples are obtained for a panel of alleles from extracted DNA at Baylor. In addition, de-identified coded samples are processed and stored in a central biorepository for further DNA, RNA and proteomic analyses. The survey and phlebotomy are performed at the time of the initial contact and agreement to participate. Nearly all patients approached willingly agree to participate for potential benefit to themselves, family members, or humankind. Little concern is voiced of providing samples for genetic analysis. Study investigators will share results with the participants and providers if testing does not indicate high risk. Results indicating increased risk or actionable alleles for the patient and/or family will be returned by a genetic counselor. Monitoring of the patients' health in this cohort will continue to be followed in the EMR to identify any future associations that might explain health disparities in African Americans. Proposals will be reviewed from investigators to study the genetic or proteomic samples as well as the clinical and demographic information in the repository. Please note that this version of the dataset has a handful of mismatches between genotyped and provided sex. Data with the following IDs should be removed prior to analysis: 420252874213744142412243424569384245694642672223

  Study phs001616

• NCI's Datasets for General Research Use

  This collection contains all of NCIs authorized individual-level genomic datasets currently in dbGaP that are approved for General Research Use (GRU) and have no further limitations beyond those outlined in the model Data Use Certification Agreement. Access to this study will include any additional authorized individual-level GRU datasets that become available. Renewal of this study is required annually.

  Study phs003014

• Genetic Epidemiology of Chronic Lymphocytic Leukemia

  Chronic lymphocytic leukemia (CLL) is a subtype of B-cell lymphoproliferative disorders (LPD), and is the most common form of adult leukemia in Caucasians in the United States. Small lymphocytic lymphoma (SLL) is also a B-cell LPD and is typically considered to be the same disease as CLL, based on pathology. We consider CLL and SLL as the same disease entity, and hereafter refer to both simply as "CLL". Using genealogical databases and cancer records, the familial clustering for CLL is one of the strongest for all cancer sites, strongly implicating germline genetic risk. We ascertained CLL cases and controls for a genomewide association study (GWAS) that was undertaken as part of the International Lymphoma Epidemiology (InterLymph) consortium GWAS. Some CLL cases are also part of extended high-risk CLLpedigrees.

  Study phs001568

• Small variants in mtDNA Canary Islands - WES Illumina (ITER)

  The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

  Study EGAS00001005678

• Small variants in mtDNA Canary Islands - WGS Illumina (ITER)

  The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

  Study EGAS00001005679

• Small variants in mtDNA Canary Islands - WGS Oxford Nanopore Technologies (ITER)

  The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

  Study EGAS00001005677

• Deregulation of DUX4 and ERG in acute lymphoblastic leukemia

  Chromosomal rearrangements deregulating hematopoietic transcription factors are common leukemia-initiating lesions in acute lymphoblastic leukemia (ALL). Here, we show that deregulation of the homeobox transcription factor gene DUX4 and the ETS transcription factor gene ERG are hallmarks of a subtype of B-progenitor ALL with a distinct gene expression profile that comprises up to 7% of B-ALL. DUX4 rearrangement and overexpression is present in all cases, and is accompanied by profound transcriptional deregulation of ERG, frequent ERG deletion and expression of a truncated ERG isoform, ERGalt. ERGalt utilizes a non-canonical first exon that is bound by DUX4 and induces its expression....

  Study EGAS00001001923