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• Alzheimer's Disease Sequencing Project (ADSP)

  NOTICE OF CHANGE IN LOCATION FOR ALZHEIMER'S DISEASE SEQUENCING PROJECT (ADSP) GENETIC AND PHENOTYPIC DATA: ADSP whole exome and whole genome sequence data that are shared through dbGaP were mapped to the Genome Reference Consortium human genome GRCh37 (build 37). These data are from the Discovery Phase of the project (described below) and will continue to be available at this site. Please see the ADSP Design page for the complete study description. All data that are mapped to GRCh38 (hg38) are being shared through the NIA Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) Data Sharing Service (DSS). For instructions on how access the ADSP Build 38 data that are shared through NIAGADS DSS, visit the Application Instructions page. STUDY DESCRIPTION FOR dbGaP BUILD 37 ADSP DATA: The overarching goals of the Alzheimer's Disease Sequencing Project (ADSP) are to: (1) identify new genomic variants contributing to increased risk of developing Alzheimer's Disease (AD), (2) identify new genomic variants contributing to protection against developing AD, and (3) provide insight as to why individuals with known risk factor variants escape from developing AD. These factors will be studied in multi-ethnic populations in order to identify new pathways for disease prevention. Such a study of human genomic variation and its relationship to health and disease requires examination of a large number of study participants and needs to capture information about common and rare variants (both single nucleotide and copy number) in well phenotyped individuals. Using existing samples from NIH funded and other studies, three NHGRI funded Large Scale Sequencing and Analysis Centers (LSAC) - Broad, Baylor, and Washington University - produced the DNA sequence data. Variant call data are being made available to the scientific community through NIH-approved data repositories. Statistical analysis of the sequence data is anticipated to identify new genetic risk and protective factors. The ADSP will conduct and facilitate analysis of sequence data to extend previous discoveries that may ultimately result in new directions for AD therapeutics. Analysis of ADSP data will be done in two phases. The Discovery Phase analysis (2014-2018) is funded under PAR-12-183. The entire Discovery dataset contains whole-genome sequencing data on 584 subjects from 113 families, and pedigree data for > 4000 subjects; whole exome sequencing data on 5096 cases 4965 controls; and whole exome sequence data on an additional 853 (682 Cases [510 Non-Hispanic, 172 Hispanic]), and 171 Hispanic Control subjects from families that are multiply affected with AD. The Replication Phase (2016-2021) analysis will be funded under RFA-AG-16-001 and RFA-AG-16-002 and is expected to include a combination of genotyping and sequencing approaches on at least 30,000 subjects. Targeted sequencing will be done by the LSACs. GRCh37 Data Releases The first ADSP data release occurred on November 25, 2013. It included the whole-genome sequencing data in BAM file format on 410 individuals. The second ADSP data release occurred on March 31, 2014, and included the whole-genome sequencing data in BAM file format for an additional 168 individuals. The third ADSP data release occurred on November 03, 2014 and included whole-exome sequencing data in BAM file format for 10,939 individuals. The fourth ADSP data release occurred on February 13, 2015 and included revised ethnic data for subjects with whole-exome sequencing data. The fifth ADSP data release occurred on July 13, 2015 and included whole-genome genotypes and updated phenotypes as well as changes to pedigree structures and sample IDs. The sixth ADSP data release occurred on December 8, 2015, and included whole-exome genotypes and updated phenotypes as well as changes to subject IDs. This seventh ADSP data release on April 12, 2016 includes: (1) WES and WGS SNV VCF files (2) WES and WGS Indel PLINK files ADSP Data Available through dbGaP: ADSP - Whole Genome Sequencing ADSP - Whole Exome Sequencing Comments DNA-Seq (BAM) n=578 n=10913 Sequence data available (plus n=38 replications w/out genotype data) Concordant SNV Genotypes (PLINK format) N/A n=10913 QC'ed genotypes that are concordant between the Atlas (Baylor's) and GATK (Broad's) calling pipelines (a subset of the consensus genotype set) Consensus Genotypes (PLINK and VCF format) n=578 n=10913 QC'ed genotypes that are concordant between Atlas and GATK pipelines as well as those that that were called uniquely by Atlas or GATK Concordant Indel Genotypes (PLINK format) n=578 n=10913 QC'ed genotypes that are concordant between the Atlas and GATK calling pipelines Phenotype Data n=4735 n=10913 Data of n=53 phenotype variables available (plus administrative data), including APOE genotype. WGS phenotypes include data of connecting family members. Please use the release notes provided by dbGaP to obtain detailed information about study release updates. The ADSP data portal provides a customized interface for users to quickly identify and retrieve files by covariates, phenotypes, and data properties such as sequencing facility or coverage. For more information about the ADSP study and the data portal, please visit https://www.niagads.org/adsp/.

  Study phs000572

• IMCISION RNAseq

  RNA sequencing of 32 primary head and neck squamous cell carcinoma (HNSCC) samples prior to treatment with neoadjuvant anti-PD-1 (n=6) or anti-PD-1 + anti-CTLA-4 (n=26) immunotherapy, and 30 paired on-treatment HNSCC samples (i.e. after neoadjuvant immunotherapy). RNA quantity used: 10ng. Library Preparation Kit: SMART Stranded Total RNA Seq Kit (Takara). Sequencing parameters: NovaSeq 6000, 2x 100 bp. File type: fastQ

  Dataset EGAD00001008127

• Germline RUNX1 Variation and Predisposition to Childhood Acute Lymphoblastic

  Somatic mutations of RUNX1, which encodes the myeloid and lymphoid transcriptional factor RUNX1, are common in both B- and T- acute lymphoid leukemia (ALL) and are associated with poor prognosis of T-ALL. However, there has been no comprehensive investigation of the pattern or prevalence of RUNX1 germline mutation in both B- and T-ALL. Here we report germline RUNX1 variants in 1.23% of B-ALL and 2.11% of T-ALL, identifying 31 unique variants in 62 B-ALL and 18 unique variants in 26 T-ALL children. The majority of frameshift and nonsense variants affected RUNX1 function in transcriptional regulation, hematopoiesis, and cellular proliferation. We identified JAK3 as the most frequent somatic mutation in T-ALL with RUNX1 variants. These results not only identify RUNX1 as a leukemia predisposition gene but also further underline the importance of germline genetic variants to the development of ALL

  Dataset EGAD00001007793

• Out with the Java, in with the Python - new EGA data download client unveiled

  We will shortly be deprecating the Java-based download client also known as API V2. The Java client began its life at the back end of 2014, and during its time has seen many developments that have served our users well. During its tenure, the Java client enabled distribution of over 6.5 million files totalling nearly 15 petabytes of data to researchers around the globe. Recent increases in genomic and phenotypic data file sizes, the number of datasets archived in the EGA, the number of users downloading data, and the diversity of download locations has meant that at times the Java client struggled to distribute data efficiently. In response, our team of developers have built a new download client with more robust features and better functionality and reliability. Enter stage left our shiny new API V3.1! The new API V3.1 will replace both API V2 and API V3. The download client for the new API V3.1 is written in Python, and the code is openly available on Github. This Python client makes https calls to the EGA AAI (https://ega.ebi.ac.uk:8443/) and to the EGA Data API (https://ega.ebi.ac.uk:8052), both of which must be accessible from the client location. In addition to general updates to improve performance, the API V3.1 has three new features enhancing the EGA distributions services. First, requested data are now downloaded over secure https connections rather than http, meaning that data can be delivered unencrypted. Instead of separately requesting, downloading, and decrypting data using the Java client, data can now be requested and downloaded using a single command without the need for decrypting. The API V3.1 also automatically verifies each file’s unencrypted md5 after download to ensure the file has downloaded correctly. Second, the new API supports segmenting and automatic resuming. To enable quicker download speeds, the API breaks files into up to four segments and downloads them in parallel. With the new resume feature, downloads - both segmented and continuous stream - will automatically resume if they encounter any errors or the connection is interrupted. These features result in both a faster and more reliable download experience. Finally, the new API V3.1 implements the GA4GH-compliant htsget protocol for supporting requests over genomic ranges. This exciting new feature means that for data files with accompanying index files (e.g. .crai for CRAM files) users can download specific regions of interest rather than the entire file saving both time and storage space. The new features of the Python-based API V3.1 represent significant improvements in security, speed, reliability, and flexibility that are sure to provide a better data download experience. To take full advantage of these features, users must update to Python 3.X. Considering the changes in the data structures with the new API, the upgrade to a new version of the Python client is also mandatory. Updating the client to the latest version can be achieved by running the following command: pip3 install pyega3 -U We are excited for users to try out the new features and take advantage of the multifariously growing EGA distribution services for human biomedical omics data. If you have any questions or feedback, please email the EGA Helpdesk team. We'd love to hear from you!

  Blog new-ega-data-download-client

• PCGP Ph-like ALL

  Background: BCR-ABL1-like, or Ph-like acute lymphoblastic leukemia is characterized by a gene expression profile similar to BCR-ABL1 positive ALL, genetic alterations of lymphoid transcription factor genes, and poor outcome. Sequencing of small numbers of Ph-like ALL cases has identified genetic alterations activating kinase signaling suggesting Ph-like ALL may be amenable to treatment with tyrosine kinase inhibitors. However, the spectrum of genetic alterations in childhood and adult Ph-like ALL is incompletely understood. Methods: We performed genomic profiling of 1736 B-ALL cases and next-generation sequencing for 160 Ph-like cases. We examined the functional effects of chimeric fusion proteins in mouse cell lines. Results: The frequency of Ph-like ALL rose from 11% in children to 26% in young adults, and was associated with very poor outcome. Kinase-activating alterations were identified in 90% of Ph-like cases, most commonly fusions involving 10 kinase or cytokine receptor genes (ABL1, ABL2, CRLF2, CSF1R, EPOR, JAK2, NTRK3, PDGFRB, PTK2B and TYK2), and mutations involving FLT3, IL7R and SH2B3. Expression of ABL1, ABL2, CSF1R and JAK2 fusions resulted in cytokine-independent proliferation of cell lines and activation of pSTAT5. Cells expressing ABL1, ABL2, CSF1R and PDGFRB fusions were sensitive to dasatinib, and JAK2 fusions to ruxolitinib. Conclusions: Ph-like ALL is characterized by a diverse range of genomic alterations that converge on a limited number of kinase signaling pathways amenable to inhibition with currently available tyrosine kinase inhibitors. Trials identifying Ph-like ALL and testing the efficacy of tyrosine kinase inhibitor therapy are warranted

  Study EGAS00001000654

• Discover Cancer Image Europe, the first release of the EUCAIM platform to fuel cancer research and data sharing

  The EUCAIM consortium and the European Commission have announced the release of Cancer Image Europe, a platform to fuel collaborative innovation and data sharing across Europe. This constitutes a major milestone in EUCAIM's development and an exciting step towards achieving the project's vision and goals. The platform aims to accelerate the pace of AI development and other data-intensive cancer research activities, constituting the basis for a fully-fledged infrastructure for sharing, reusing, and exploiting cancer imaging data, especially using AI techniques. A platform paving the way for the future of cancer diagnosis and treatment Cancer Image Europe brings benefits to researchers, clinicians, and AI innovators across Europe as it addresses the fragmentation of existing cancer image repositories. The platform gathers a public catalogue of cancer imaging datasets from the repositories of the EU-funded AI for Health Imaging projects. A distributed Atlas of Cancer Imaging with over 60 million anonymised cancer image data from over 100,000 patients will be established as part of future updates. The first version of Cancer Image Europe also includes a public catalogue of cancer imaging datasets, a federated searching tool to understand the information available in the federated providers, and full integration with Life Science Login. Moreover, it reuses and adds value to key components of EU-funded research projects and infrastructure in the field of cancer. The Public Catalogue When we talk about data re-use, data discovery is key. The EUCAIM public catalogue is the result of a systematic and collaborative process to which the EGA-CRG has actively contributed. This browsing interface gathers the metadata of the available cancer imaging datasets. This descriptive information will help researchers in their data retrieval. Our contribution to the Public Catalogue comes from our experience gained in the deployment of our federated network, the Federated EGA (FEGA), and as partners in projects such as EuCanImage (AI4HI initiative), in which we worked on the definition of common data models, ontologies and data standards. The EUCAIM Project EUCAIM is a cornerstone of the European Commission-initiated European Cancer Imaging Initiative, a flagship of the Europe's Beating Cancer Plan, which aims to foster innovation and deployment of digital technologies in cancer treatment and care, to achieve more precise and faster clinical decision-making, diagnostics, treatments, and predictive medicine for cancer patients. For more information about the first release of the Cancer Image Europe platform and the EUCAIM project, please visit cancerimage.eu.

  Blog discover-cancer-image-europe

• OpACIN-neo – A Multicenter Phase 2 Study to identify the Optimal neo-Adjuvant Combination scheme of Ipilimumab and Nivolumab – Whole exome sequencing

  The outcome of patients with macroscopic stage III melanoma is poor. Neoadjuvant treatment with ipilimumab plus nivolumab at the standard dosing schedule induced pathological responses in a high proportion of patients in two small independent early-phase trials. However, toxicity of the standard ipilimumab plus nivolumab dosing schedule was high, preventing its broader clinical use. The aim of the OpACIN-neo study (NCT02977052) to identify a dosing schedule of ipilimumab plus nivolumab that is less toxic but equally effective. 86 patients with macroscopic stage III melanoma were randomised to one of three dosing schedules: arm A, two cycles of ipilimumab 3 mg/kg plus nivolumab 1 mg/kg once every 3 weeks; arm B, two cycles of ipilimumab 1 mg/kg plus nivolumab 3 mg/kg once every 3 weeks; or arm C, two cycles of ipilimumab 3 mg/kg once every 3 weeks directly followed by two cycles of nivolumab 3mg/kg once every 2 weeks. Within the first 12 weeks, grade 3–4 immune-related adverse events were observed in 12 (40%) of 30 patients in group A, six (20%) of 30 in group B, and 13 (50%) of 26 in group C. Pathological responses occurred in 24 (80%) patients in group A, 23 (77%) in group B, and 17 (65%) in group C. The 2-year estimated relapse-free survival was 84% for all patients, 97% for patients achieving a pathologic response and 36% for nonresponders (p<0.001). High tumor mutational burden (TMB) and high interferon-gamma-related gene expression signature score (IFN-γ score) were associated with pathologic response and low risk of relapse; pathologic response rate (pRR) was 100% in patients with high IFN-γ score/high TMB, patients with high IFN-γ score/low TMB or low IFN-γ score/high TMB had pRRs of 91% and 88%; while patients with low IFN-γ score/low TMB had a pRR of only 39%. These data demonstrate long-term benefit in patients with a pathologic response and show the predictive potential of TMB and IFN-γ score.

  Study EGAS00001004832

• OpACIN-neo – A Multicenter Phase 2 Study to identify the Optimal neo-Adjuvant Combination scheme of Ipilimumab and Nivolumab – RNA sequencing

  The outcome of patients with macroscopic stage III melanoma is poor. Neoadjuvant treatment with ipilimumab plus nivolumab at the standard dosing schedule induced pathological responses in a high proportion of patients in two small independent early-phase trials. However, toxicity of the standard ipilimumab plus nivolumab dosing schedule was high, preventing its broader clinical use. The aim of the OpACIN-neo study (NCT02977052) to identify a dosing schedule of ipilimumab plus nivolumab that is less toxic but equally effective. 86 patients with macroscopic stage III melanoma were randomised to one of three dosing schedules: arm A, two cycles of ipilimumab 3 mg/kg plus nivolumab 1 mg/kg once every 3 weeks; arm B, two cycles of ipilimumab 1 mg/kg plus nivolumab 3 mg/kg once every 3 weeks; or arm C, two cycles of ipilimumab 3 mg/kg once every 3 weeks directly followed by two cycles of nivolumab 3mg/kg once every 2 weeks. Within the first 12 weeks, grade 3–4 immune-related adverse events were observed in 12 (40%) of 30 patients in group A, six (20%) of 30 in group B, and 13 (50%) of 26 in group C. Pathological responses occurred in 24 (80%) patients in group A, 23 (77%) in group B, and 17 (65%) in group C. The 2-year estimated relapse-free survival was 84% for all patients, 97% for patients achieving a pathologic response and 36% for nonresponders (p<0.001). High tumor mutational burden (TMB) and high interferon-gamma-related gene expression signature score (IFN-γ score) were associated with pathologic response and low risk of relapse; pathologic response rate (pRR) was 100% in patients with high IFN-γ score/high TMB, patients with high IFN-γ score/low TMB or low IFN-γ score/high TMB had pRRs of 91% and 88%; while patients with low IFN-γ score/low TMB had a pRR of only 39%. These data demonstrate long-term benefit in patients with a pathologic response and show the predictive potential of TMB and IFN-γ score.

  Study EGAS00001004833

• NHLBI TOPMed: The Cleveland Family Study (CFS)

  The Cleveland Family Study (CFS) is one cohort involved in the WGS project. The CFS was designed to provide fundamental epidemiological data on genetic and non-genetic risk factors for sleep disordered breathing (SDB). In brief, the CFS is a family-based study that enrolled a total of 2284 individuals from 361 families between 1990 and 2006. The sample was selected by identifying affected probands who had laboratory diagnosed obstructive sleep apnea. All first degree relatives, spouses and available second degree relatives of affected probands were studied. In addition, during the first 5 study years, neighborhood control families were identified through a neighborhood proband, and his/her spouses and first degree relatives. Each exam, occurring at approximately 4 year intervals, included new enrollment as well as follow up exams for previously enrolled subjects. For the first three visits, data, including an overnight sleep study, were collected in the participants' homes while the last visit occurred in a general clinical research center (GCRC). Phenotypic characterization of the entire cohort included overnight sleep apnea studies, blood pressure, spirometry, anthropometry and questionnaires. The GCRC exam (n=735 selected individuals) included more comprehensive phenotype data on a focused subsample of the larger cohort, to permit linking SDB phenotypes with cardio-metabolic phenotypes, with an interest in identifying genetic loci that are associated with these related phenotypes. In this last round of data collection, a subset of 735 individuals was selected based on expected genetic informativity by choosing pedigrees where siblings had extremes of the apnea hypopnea index (AHI). Participants underwent detailed phenotyping including laboratory polysomnography (PSG), ECG, spirometry, nasal and oral acoustic reflectometry, vigilance testing, and blood and urine collection before and after sleep and after an oral glucose tolerance test. A wide range of biochemical measures of inflammation and metabolism were assayed by a Core Laboratory at the University of Vermont. 994 individuals were sequenced as part of TOPMed Phase 1, including 507 African-Americans and 487 European-Americans. Among the sequenced individuals, 156 were probands with diagnosed sleep apnea, an additional 706 were members of families with probands, and 132 were from neighborhood control families. 298 individuals were sequenced as part of TOPMed Phase 3.5, including 169 African-Americans and 129 European-Americans. Among the newly sequenced individuals, 33 were probands with diagnosed sleep apnea, an additional 214 were members of families with probands, and 51 were from neighborhood control families. Please note: Phenotype and pedigree data are available through "NHLBI Cleveland Family Study (CFS) Candidate Gene Association Resource (CARe)", phs000284.

  Study phs000954

• University of Illinois at Chicago (UIC) Autism Centers of Excellence (ACE) Exome Sequencing Analysis

  Autism spectrum disorder (ASD) is highly heritable with recent sibling recurrence risk estimates of 19% overall and 26% in males. The heritable phenotype of hyperserotonemia, or elevated levels of platelet serotonin (5HT), in ~35% of people with ASD is a well-established biomarker. The efficacy of drugs like risperidone and potent serotonin transporter inhibitors at treating behaviors related to Insistence on Sameness, along with evidence of the contribution of hyperserotonemia to autism susceptibility collectively support the hypothesis that dysfunction in the 5HT system is a significant etiological target for investigation of the genetic component to autism. ASD genetic architecture is complex; common variants of large effect do not contribute substantially to overall ASD risk, but there are clearly common variants with small effects and rare genetic/genomic variation of larger effect among ASD genetic risk factors. The NIH ARRA Autism Sequencing Consortium, including Dr. Sutcliffe and Dr. Cook among others, has initiated exome sequencing studies to identify more of the rare variants contributing to ASD. Data from our group and others reveal numerous rare de novo and inherited sequence mutations, and the number of de novo and other functional mutations that are found to affect molecules encoding 5HT signaling and its regulation further reinforces our hypothesis that regulation of serotonin levels is important in autism genetic susceptibility. Integrin receptor signaling pathways were prominently featured among identified de novo mutations, thus defining a set of interrelated gene networks that control 5HT signaling. We propose to extend our findings to date by conducting exome sequencing on ACE subjects, for whom we also have 5HT biochemical data, to identify rare variants (including CNVs) in 5HT-related gene networks. In total we propose to have exome sequencing completed on 523 samples. The purpose of the proposed research is two-fold: 1) we will conduct more extensive investigations to determine the support for the hypothesis that genetic variation at genes regulating platelet serotonin levels affect susceptibility to ASD and 2) we will combine the exome sequence data from these studies with sequence data for autism being accumulated in a variety of other research projects to further the goal of identifying and characterizing the genetic component to ASD.

  Study phs000712