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• The Genomics and Randomized Trials Network (GARNET) Vitamin Intervention Stroke Prevention (VISP) Trial

  The VISP trial (PI Jim Toole, M.D., Wake Forest University School of Medicine) was a multi-center, double-blind, randomized, controlled clinical trial that enrolled patients aged 35 or older with homocysteine (Hcy) levels above the 25th percentile at screening and a non-disabling cerebral infarction (NDCI) within 120 days of randomization (Toole, 2002, PMID: 12417369). The trial was designed to determine if daily intake of a multivitamin tablet with high dose folic acid, vitamin B6 and vitamin B12 reduced recurrent cerebral infarction (primary endpoint), and nonfatal myocardial infarction (MI) or mortality (secondary endpoints). Subjects were randomly assigned to receive daily doses of the high-dose formulation (n=1,827), containing 25mg pyridoxine (B6), 0.4mg cobalamin (B12), and 2.5mg folic acid; or the low-dose formulation (n=1,853), containing 200mcg pyridoxine, 6mcg cobalamin and 20mcg folic acid. Enrollment in VISP began in August 1997, and was completed in December 2001, with 3,680 participants enrolled. Within the trial, 2,164 participants from 46 clinic sites provided DNA and agreed for it to be shared for use in a genetic subset study of VISP. This study is part of Genomics and Randomized Trials Network (GARNET), funded by the National Human Genome Research Institute (NHGRI). The overarching goal is to identify novel genetic factors that contribute to stroke through large-scale genome-wide association studies of treatment response in randomized clinical trials. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were performed at the GARNET Coordinating Center at the University of Washington. The data of the VISP trial have been released to dbGaP users in several segments: Version 1 (phs000343.v1.p1), consisted of n=4 phenotype datasets, and all raw, cleaned and imputed genotype data. Version 2 (phs000343.v2.p1) included n=14 additional phenotype datasets (plus pedigree, consent, and sample-mapping data), and increased the available data to a total of n=970 phenotype variables. Version 3 (phs000343.v3.p1) included all n=36 phenotype datasets (plus pedigree, consent, and sample-mapping data), and increased the available data to a total of n=1918 phenotype variables.Version 4 (phs000343.v4.p1), the current release, includes all previous phenotypic datasets, includes one new phenotypic dataset for the untargeted metabolomics data of 50 individuals, includes DNA methylation profiles for n=180 individuals, and sequencing data for n=179 individuals.

  Study phs000343

• Somatic mutations in endometriosis and normal uterine endometrium

  To characterize the genomic features of endometriosis, we performed whole-exome sequencing for ovarian endometriotic epithelium samples obtained from subjects without concurrent gynecological cancers. Additionally, we analyzed histologically normal uterine endometrial epithelium samples obtained from subjects with benign gynecologic diseases. All the epithelium samples were isolated by laser microdissection from frozen sections.

  Study EGAS00001003095

• multi-OMICs study of a pair of infant monozygotic twins with concordant B-cell ALL

  B-cell acute lymphoblastic leukemia (B-cell ALL) is the most common cancer in childhood. Studying identical twins with B-cell ALL provides a unique and tractable model for deciphering the developmental timing of pre- and post-natal mutations contributing to clonal evolution. To date, this has mainly focused on major cytogenetic subgroups of childhood B-cell ALL, including MLL fusions, ETV6-RUNX1, hyperdiploidy, and BCR-ABL1. However, formal demonstration of the prenatal origin and “backtracking” the natural history of the leukemia remains understudied in “B-other”/Normal Karyotype (NK) B-cell ALL. To characterize the genetic and the epigenetic landscape of this particular leukemia subtype, we performed whole genome DNA-, B-cell receptor (BCR)-, and DNA bisulfite-sequencing on a pair of 8-month-old monozygotic twins diagnosed with concordant “B-other”/NK B-cell ALL.

  Study EGAS00001003651

• FEGA and European GDI: working together to improve human health

  The Federated EGA is a global resource for discovery of and access to sensitive human omics and associated data consented for secondary use, through a network of human data repositories to accelerate biomedical research and improve human health. The Federated EGA network was launched in September 2022 with five inaugural nodes, and since 2023 seven operational nodes can share data across national borders in adherence to European and national laws. A few weeks after FEGA's official launch, in November 2022, the European Genomic Data Infrastructure (GDI) project was kicked-off . This European Commission co-funded project, coordinated by ELIXIR, is aimed to deliver federated, sustainable and secure data infrastructure to access genomic and related phenotypic and clinical data across Europe. This project supports the aim of the 1+MG initiative (25 EU countries, Norway and UK) to enable personalised medicine and health through a shared framework and infrastructure for securely accessing and integrating high quality genomic data and other health data across borders.1+MG will be an integral component of the European Health Data Space (EHDS) for secondary use (Healthdata@EU) as an authorised participant. How are Federated EGA and GDI similar? Given their shared visions, the Federated EGA and European GDI networks have a lot in common. To begin, they share the same overall goal of establishing networks of “nodes” that host sensitive human data within a jurisdiction and connecting these nodes in a global network to support data discovery and promote human genome data access for research and healthcare. FEGA and GDI are both initially focused on enabling access to human genomic data, while FEGA ambition is to expand the scope to clinical research data and other omics data in the future. FEGA and GDI are both built on open and interoperable software solutions, a subset of which are based on the LocalEGA components. FEGA and GDI implementation solutions are based on international community standards, for example those developed by the Global Alliance for Genomics and Health, which contributes to making them interoperable. Both FEGA and GDI allow for the nodes to make use of any solution that is fully compatible. As illustrated in Figure 1, a final key point is the significant overlap of institutions involved in envisioning and operating FEGA and GDI nodes, with the clear wish to keep them interoperable in the future. What distinguishes Federated EGA from GDI? Despite being largely similar, there are some differences between the FEGA and GDI networks, which we aim to clarify in this post. The first difference is the governance model that the nodes will operate to comply with national laws and GDPR. In the FEGA network, nodes have taken inspiration from the EGA data access model, where the infrastructure is a data processor of the hosted data and data controllership remains with the originating Data Access Committees (i.e. Data controllers) for each dataset. On the other hand, in the GDI network the controllership of datasets will be transferred to a 1+MG European Digital Infrastructure Consortium (EDIC) legal entity created by the Member States (MS), who will make data access decisions, with data holders having veto powers for their datasets. Importantly, FEGA nodes have the flexibility to choose another model to fit with their data protection framework, including becoming data controllers for their datasets. The second difference is the inclusion criteria for data. While FEGA nodes are designed to accept almost any type of omics data in need of control access (e.g. genomics, transcriptomics, genotyping, single cells sequencing, patient-tracked metagenomics), GDI nodes are initially, but not only, focused on accepting whole genome and exome sequencing data and affiliated data from sources such as (i) the Genome of Europe use case of the 1+MG initiative which specifically aims to fulfil the mission of building “a European network of national genomic reference cohorts of at least 500,000 citizens”) (ii) data collection of other types of genomic data identified by countries through the 1+MG dashboard and (iii) genomic data coming from data holders which would need to fulfil EHDS requirements. The third difference is the maturity of the software stacks. The FEGA network provides a set of software for data and metadata submission, storage, permissions management, and file distribution (the LocalEGA package). GDI is building a complete set of open source reference for the five functionalities covering the full data life cycle (a few more compared to the LocalEGA) including federated processing (analytics, AI/ML), which is still under active development. Notably, one of the GDI functionalities - storage and interfaces - can be satisfied by using the LocalEGA storage solution, highlighting the ability of FEGA and GDI to be interoperable. In both FEGA and GDI, nodes are allowed to use alternative solutions as long as they are fully interoperable with the networks. Figure 1 provides a simple overview of these described commonalities and differences. Figure1: schematic overview of the main commonalities and difference among a FEGA and a GDI node Can the same institute run a FEGA and a GDI node at the same time? The answer is Yes! We believe this is entirely possible and encouraged. As long as 1+MG requirements are continuously fulfilled in the implementation. The same trained personnel could operate the infrastructure and leverage the same national funding to run a FEGA and a GDI node. Several European nodes, especially GDI vanguard nodes like Norway, Sweden, Finland and Spain are following this model. The idea is that a lot of the work can be reused, given the overlapping scope and the interoperable technology. Thus, the hosted datasets can be discovered via the two catalogues, perhaps accessible under the same or different governance models. From a FEGA node perspective, the GDI datasets could simply be a subset of the datasets hosted in the FEGA node, which have their specific governance as any other. What's next? So, the amazing teams of people building the Federated EGA network and the European GDI network are working together to create infrastructures able to provide secure access to human genomic and associated data around Europe. Because we all know how much human genomics can improve healthcare and precision medicine. And we all want to collaborate to make it happen. This article has been reviewed collectively by members of the EGA and the GDI coordination team.

  Blog fega-and-gdi

• ONGOING CHROMOSOMAL INSTABILITY ACROSS ANEUPLOID SUBTYPES OF CHILDHOOD B-CELL ACUTE LYMPHOBLASTIC LEUKEMIA ASSOCIATES WITH DISEASE PROGRESSION

  This is the DAC for the scDNA data on the c-B-ALL datasets

  Dac EGAC50000000005

• 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

• Heart Failure Network - Renal Optimization Strategies Evaluation in Acute Heart Failure and Reliable Evaluation of Dyspnea (HFN ROSE-BioLINCC)

  ObjectivesTo test the two independent hypotheses that when compared to placebo, addition of: (1) low dose dopamine; or (2) low dose nesiritide to diuretic therapy will enhance decongestion and preserve renal function in patients with acute heart failure and renal dysfunction.Background A primary treatment goal in acute heart failure is to achieve adequate decongestion while avoiding renal dysfunction and other side effects. Patients with acute heart failure and moderate or severe renal dysfunction are at risk for inadequate decongestion and worsening renal function - both of which are associated with worse outcomes. Renal adjuvant therapies that enhance decongestion and preserve renal function during treatment of acute heart failure are needed. Dopamine is an endogenous catecholamine which, at low doses, may selectively activate dopamine receptors and promote renal vasodilatation. Previous studies have suggested that the addition of low dose dopamine to diuretic therapy enhances decongestion and preserves renal function during diuretic therapy in acute heart failure; however, these studies were small with variable study designs and dopamine doses. B-type natriuretic peptide (BNP) is a cardiac peptide with vasodilating, renin and aldosterone inhibiting, natriuretic and diuretic properties. Nesiritide is human recombinant BNP approved for management of acute heart failure. The recommended dose lowers blood pressure and atrial pressures and produces modest improvement in dyspnea, but does not favorably impact clinical outcomes or renal function, potentially due to its hypotensive effects. Small studies using low dose nesiritide in acute heart failure and cardiac surgery patients have demonstrated favorable effects on urine output and renal function. Therefore, the Renal Optimization Strategies Evaluation (ROSE) trial was initiated to determine the benefits and safety of intravenous administration of low dose nesiritide or low dose dopamine in patients with congestive heart failure and kidney dysfunction. ParticipantsA total of 360 participants were enrolled. Design Participants were enrolled within 24 hours of hospital admission and randomized in a 1:1 ratio to the nesiritide or dopamine strategies. Participants randomized to the dopamine strategy were randomized in a double-blind 2:1 ratio to low dose dopamine (2 µg/kg/min for 72 hours infused via local guideline stipulated vascular access) or placebo. Participants randomized to the nesiritide strategy were randomized in a double-blind 2:1 ratio to low dose nesiritide (0.005 μg/kg/min for 72 hours infused via peripheral intravenous access without initial bolus) or placebo. All participants received open-label, intravenous loop diuretic treatment with a recommended total daily dose equal to 2.5x the total daily oral outpatient furosemide (or equivalent) dose at 7 days prior to admission up to a maximum of 600 mg/day. Participants naive to outpatient loop diuretics received 80 mg/day of intravenous furosemide. One-half of the total daily diuretic dose was administered as a bolus twice daily for at least 24 hours. Use of other medications and diuretic dosing after 24 hours were at the discretion of the clinician. All participants were placed on a 2000 mg sodium diet and 2000 cc fluid restriction. After the primary endpoint assessment at 72 hours, study drug was discontinued and subsequent treatment was at the clinician's discretion. The two co-primary endpoints were the 72-hour cumulative urinary volume as an index of decongestion efficacy and the change in cystatin-C from randomization to 72 hours as a measure of renal function preservation. Conclusions In participants with acute heart failure and renal dysfunction, neither low-dose dopamine nor low-dose nesiritide enhanced decongestion or improved renal function when added to diuretic therapy.

  Study phs003589

• SCLC study MGH - RNAseq dataset

  RNA-seq analyses were performed on cDNA libraries prepared from PolyA+ RNA using the Illumina TruSeq protocol for mRNA. The final libraries were sequenced with a paired-end 2×75 bp protocol aiming at 8.5 Gb per sample for a 30x mean coverage of the annotated transcriptome. All sequencing reactions were conducted on an Illumina HiSeq instrument (Illumina, San Diego, CA, USA).

  Dataset EGAD00001003969

• Whole genome sequencing data for five Japanese subjects

  WGS was performed for five Japanese subjects. DNA samples isolated from whole blood were sequenced at Macrogen Japan Corporation. All libraries were constructed using the TruSeq DNA PCR-Free Library Preparation Kit according to the manufacturer’s protocols. Libraries were sequenced on HiSeqX (Illumina, San Diego, CA, USA) or Novaseq6000 (Illumina, San Diego, CA, USA).

  Dataset EGAD00001010075

• NHLBI TOPMed: Pathways to Immunologically Mediated Asthma (PIMA)

  Study designed to further our understanding of the pathogenesis of asthma exacerbations in children. Children enrolled in the study (n=217) were all asthmatic and primarily Hispanic white. The children were followed for 18 months until they experienced an asthma exacerbation or completed the follow-up without an exacerbation. The time to the first asthma exacerbation was considered the outcome. The acute and convalescent immune phenotype of each asthma exacerbation was documented.

  Study phs001727