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• GA4GH

  Standards The EGA is a long-standing supporter of the Global Alliance for Genomics & Health (GA4GH) to enhance responsible sharing of human genetic data through the development of interoperable global standards for human data access. The EGA is one of the founding GA4GH Driver Projects and has contributed to the development and implementation of several GA4GH standards and APIs. Below is a list of the GA4GH standards and APIs that are currently available or planned for implementation at EGA. TechnicalStandards Purpose SpecificationVersion SupportedVersion Implementation Large Scale Genomics htsget A protocol for secure, efficient, and reliable access to sequencing read and variation data. V1.3.0 V1.0.0 Specification Documentation Endpoint Read File Formats (SAM/BAM/CRAM) Specifications for storing next-generation sequencing read data. V3.0.0 V3.0.0 Implementation Example of Usage Variation File Formats (VCF/BCF) The specifications for Variant Call Format Files (VCF) and its binary counterpart BCF. V4.0.0 V2.0.0 V4.0.0 V2.0.0 Implementation Example of Usage Crypt4GH v1.0 Enables direct byte-level compatible random access to encrypted genetic data stored in community standards (e.g. CRAM, VCF) V1.0 V1.0 Specification Documentation Endpoint refget API Enables access to reference sequences using an identifier derived from the sequence itself. V1.2.6 NA Specification RNAget API v1 Provides a means of retrieving data from several types of RNA experiments including (i) feature-level expression data from RNA-seq type measurements and (ii) coordinate-based signal/intensity data similar to a bigwig representation via a client/server model. V1.0.0 NA Documentation Discovery Beacon v2 Supports discovery of genomic variants, phenotypes, and individuals V1.0.1 V0.3 Web UI API Source Code Service Info API v1 The Service Info API is an endpoint for describing GA4GH service metadata, designed for extension and inclusion in other APIs. Service info is used to describe a single service, while Service Registry is used to describe multiple services. V1.0.0 NA Documentation Service Registry API v1 provides information about other GA4GH services, primarily for the purpose of organizing services into networks or groups and service discovery across organizational boundaries. V1.0.0 NA Documentation Data Use Researcher Identities Data Use Ontology (DUO) Allow users to semantically tag genomic datasets with usage restrictions, allowing them to become automatically discoverable based on a health, clinical, or biomedical researcher’s authorisation level or intended use. 2021-02-23 2021-02-23 Specification Documentation Endpoint Authentication & Authorization Infrastructure (AAI) The GA4GH AAI specification leverages OpenID Connect (OIDC) Servers for use in authenticating the identity of researchers desiring to access clinical and genomic resources from data holders adhering to GA4GH standards, and to enable data holders to obtain security-related attributes of those researchers. V1.2.0 V1.2.0 API URI: ega.ebi.ac.uk:8443 Documentation Repository Researcher IDs (passport, visa) Specify the collection of researchers that may access a dataset at any given time, and the credentials they must supply. V1.0.1 V1.0.1 Specification Documentation Endpoint Cloud Tool Registry Service API TRS is a standard API for exchanging tools and workflows to analyze, read, and manipulate genomic data. V2.0.1 NA Documentation Repostiory Data Repository Service API ​DRS API is a standard for building data repositories and adapting access tools to work with those repositories, works with other approved APIs from the GA4GH Cloud Work Stream to allow researchers to discover algorithms across different cloud environments and send them to datasets they wish to analyse. V1.0.3 NA Documentation Repostiory Workflow Execution Service API This API lets users run a single workflow (defined using CWL or WDL) on multiple different platforms, clouds, and environments, and be confident that it will work the same way. The API provides methods to request that a workflow be run, pass parameters to that workflow, get information about running workflows, and cancel a running workflow. V1.0.1 NA Documentation Repostiory Genomic Knowledge Standards Variation Representation v1 Provides a flexible framework of computational models, schemas, and algorithms to precisely and consistently exchange genetic variation data across communities. V1.3.0 EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Clin/ Pheno Data Capture Phenopackets Provides information models with different levels of complexity to enable high level clinical phenotype information as well as deep clinical phenotype information to be exchanged. V2.0.0 Included in Ongoing Submissions EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Driver Project The EGA, jointly coordinated by the EBI and the CRG, was announced, in 2017, to be one of the 15 Driver Projects for GA4GH. Driver Projects are international genomic data initiatives, focussed on real projects and challenges that will guide the development efforts in order to accelerate and enable completely responsible and standarised data sharing by 2022. All chosen Driver Projects make a cross-sectional effort by playing an important role across the different workstreams. Thomas Keane, Jordi Rambla, Mallory Freeberg, and Aina Jené have been named Driver Project Champions for the EGA. All Driver Project Champions will be leading this ambitious initiative for the following years.

  Documentation about/projects-and-funders/ga4gh

• Circulating kidney injury molecule-1 (KIM-1) and association with response to adjuvant immunotherapy in renal cell carcinoma

  Adjuvant immunotherapy is currently the standard of care for patients with resected renal cell carcinoma (RCC) at increased risk of recurrence, but there are no biomarkers available to guide treatment decisions. Kidney injury molecule-1 (KIM-1) has previously been described as a potential circulating biomarker in renal cell carcinoma. We evaluated biomarkers and outcomes among patients who participated in a randomized phase III trial of adjuvant atezolizumab versus placebo in resected RCC (IMmotion010). This trial did not meet its primary DFS endpoint in the intention-to-treat population. An affinity-based proximity extension proteomics assay was used to compare levels of circulating proteins among baseline (post-nephrectomy) serum samples and also with samples taken at time of recurrence. We demonstrate that serum KIM-1 was the most significantly enriched protein at recurrence versus baseline. Patients with serum KIM-1high at baseline had worse disease-free survival (DFS) (hazard ratio 1.68, 95% CI 1.35-2.09), but also had improved DFS when treated with adjuvant atezolizumab versus placebo (hazard ratio 0.72, 95% CI 0.52-0.99). An increase in KIM-1 during follow-up was associated with worse DFS compared to patients with no increase in KIM-1. Comparison of transcriptomic expression profiles in paired primary and recurrent tumor samples revealed that metastatic recurrence is associated with upregulation of transcriptional programs associated with tumor proliferation and myeloid immune suppression. Downregulation of an MHC class I signature was seen among patients with recurrence after treatment with atezolizumab but not placebo, suggesting this is a mechanism of resistance to PD-L1 immunotherapy. These analyses suggest that elevated post-nephrectomy serum KIM-1 enriches for benefit from adjuvant immunotherapy in RCC, and that biomarker driven adjuvant therapy should be evaluated as a potential new paradigm in RCC trials.

  Study EGAS50000001285

• ctDNA quantification in Ewing sarcoma patients

  Background. Treatment stratification and response assessment in pediatric sarcomas has relied on imaging studies and surgical/histopathological evidence of vital tumor cells. Such studies and evidence collection processes often involve radiation and/or general anesthesia in children. Cell-free circulating tumor DNA (ctDNA) detection in blood plasma is one available method of so-called liquid biopsies that has been shown to correlate qualitatively and quantitatively to some extent with the existence of vital tumor cells in the body. Our clinical observational study focused on the utility and feasibility of ctDNA detection in pediatric Ewing sarcoma (EWS) as a marker of minimal residual disease (MRD). Patients and Methods. We performed whole genome sequencing to identify the exact breakpoints in tumors known to carry the EWS-FLI1 fusion gene. Patient-specific fusion breakpoints were tracked in peripheral blood plasma using digital droplet PCR (ddPCR) before, during, and after therapy in six consecutive children and young adults with EWS. Presence and levels of fusion breakpoints were correlated with clinical disease courses. The genetic changes in the tumors were defined, and inter- and intra-individual changes in the tumor DNA copy loads were observed over time. Results. We show that the detection of ctDNA in the peripheral blood of EWS patients i) is feasible in the clinical routine and ii) allows for the longitudinal real-time monitoring of MRD activity in children and young adults. Although changing ctDNA levels correlated well with clinical outcome within patients, between patients, a high variability was observed (inter-individually) for the six patients described here. Conclusions. ctDNA detection by ddPCR is a highly sensitive, specific, feasible, and highly accurate method that can be applied in EWS for follow-up assessments as an additional surrogate parameter for clinical MRD monitoring and, potentially, also for treatment stratification in the near future.

  Study EGAS00001006433

• Genome-Wide Association Study of Celiac Disease

  Celiac disease (gluten-sensitive enteropathy, celiac sprue) is a common disease with significant morbidity and mortality. It is caused by sensitivity to the dietary protein gluten, resulting in a chronic enteropathy in the small intestine. Celiac disease is now recognized to be a common disease, with reports that the disease frequency is 1:133 in the United States, similar to European estimates. There is recent evidence to suggest that the incidence of the disease is rising. Occult disease is frequently present with minimal classic symptoms or signs. The ratio of symptomatic to asymptomatic celiac disease is estimated to be 1:7. Some complications of celiac disease include lymphoma, osteoporosis, anemia, miscarriages, seizures, vitamin deficiencies, and co-occurrence of other autoimmune diseases. The only treatment is a gluten-free diet, so that recurrence of symptoms and complications may occur after minor dietary indiscretions. Identifying the underlying genetic causes of celiac disease may allow us to identify susceptible individuals, as well as advance new ways to prevent the disease and to treat it once it occurs. Several genome-wide linkage studies and one genome-wide association study of celiac disease have been conducted. Other than the common locus at HLA, few putative celiac disease loci have been replicated between studies, suggesting that the disease is heterogeneous and complex. A portion of the genetic predisposition can be attributed to HLA, but the etiology is likely due to a number of rare, high penetrant genes (as would be identified in linkage analysis) and to more common, low penetrant genes (as would be identified in association studies). The objective of this study is to identify new loci that increase risk to develop celiac disease. We will capitalize on existing North American resources, including three large collections of celiac cases and controls (Aim 1) and an independent set of celiac cases and their families (Aim 3). We propose a comprehensive multi-stage approach, with the following specific aims. In Aim 1, we will conduct a genome-wide association (GWA) study of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs). The GWA will include1900 disease cases and 3400 matched controls, genotyped using the Illumina Human 610-quad chip. Statistical analyses will be performed to test for associations with celiac disease. In Aim 2, we will conduct a combined analysis of our GWA dataset from Aim 1 and a previous GWA dataset to identify additional low-penetrance loci. In Aim 3, we will attempt to replicate significant findings from the GWA study in two independent sample sets. At the conclusion of this study, we expect to have validated a number of SNPs and CNPs from regions in the genome that alter the risk of developing celiac disease. These SNPs may prove useful at both the clinical and research level. The data from the study will be shared with the scientific community.

  Study phs000274

• National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS)

  NIAGADS is an NIH controlled-access data repository that collaborates with researchers around the world to facilitate data access and sharing for genomic and associated omics data related to Alzheimer's Disease (AD), Alzheimer's Disease Related Dementias (ADRD), as well as healthy aging. Serving as the data coordinating center for the Alzheimer's Disease Sequencing Project (ADSP), NIAGADS hosts all ADSP-generated whole-exome, whole-genome and associated phenotypes. Other data types hosted by NIAGADS include genotype SNP arrays, functional omics, fluid biomarkers, aggregated imaging data (such as volumetric data for brain regions of interest), and summary statistics. In adherence with NIH security best practices and genome data sharing policies, NIAGADS supports data access requests through review by an NIH-appointed and registered Data Access Committee. Data stored within NIAGADS cannot be requested via dbGaP. Data requests must go through the NIAGADS Data Sharing Service (DSS) via the following NIAGADS url: https://dss.niagads.org/. Questions related to the request of data should be directed to the NIAGADS admin team at: niagads@pennmedicine.upenn.edu. DSS is a FISMA certified platform built by a team of data scientists at the University of Pennsylvania to support the request and access of AD/ADRD data by qualified researchers internationally. Questions related to the use of data hosted in the DSS should be directed to the Portal admin team at: help@niagads.org.

  Study phs004180

• Diet, Genetic Factors, and the Gut Microbiome in Crohn's Disease

  We investigate the hypothesis that consistent changes in the human gut microbiome are associated with Crohn's disease, a form of inflammatory bowel disease, and that altered microbiota contributes to pathogenesis. Analysis of this problem is greatly complicated by the fact that multiple factors influence the composition of the gut microbiota, including diet, host genotype, and disease state. For example, data from us and others document a drastic impact of diet on the composition of the gut microbiome. No amount of sequencing will yield a useful picture of the role of the microbiota in disease if samples are confounded with uncontrolled variables. We aim to characterize the composition of the gut microbiome while controlling for diet, host genotype, and disease state. Diet is controlled by analyzing children treated for Crohn's disease by placing them on a standardized elemental diet, and by testing effects of different diets on the gut microbiome composition in adult volunteers. Genotype is analyzed by large scale SNP genotyping, which is already underway and separately funded--team member Hakon Hakonarson is currently genotyping 50 children a week at ~half a million loci each and investigating connections with inflammatory bowel disease. Clinical status is ascertained in the very large IBD practice in the UPenn/CHOP hospital system. Effects of diet, host genotype, and disease state on the gut microbiome are summarized in a multivariate model, allowing connections between microbiome and disease to be assessed free of confounding factors. This project is divided into four sub-studies. In the Fecal Storage Methods (FSM) study, methods of stool storage and DNA extraction are compared to examine their impact on DNA sequence analysis results. The Controlled Feeding Experiment (CaFE) addresses the effects of controlled diets on the gut microbiome. In the Cross-sectional Study of Diet and Stool Microbiome Composition (COMBO), the effects of diet analyzed using surveys and deep sequencing of stool specimens. The fourth study, Pediatric Longitudinal Study of Elemental Diet and Stool Microbiome Composition (PLEASE), examines the effects of an elemental diet treatment on pediatric patients diagnosed with inflammatory bowel disease (IBD), particularly Crohn's disease. Fecal Storage Methods (FSM): Cross-sectional study Controlled Feeding Experiment (CaFE): Controlled trial Cross-sectional Study of Diet and Stool Microbiome Composition (COMBO): Cross-sectional study Pediatric Longitudinal Study of Elemental Diet and Stool Microbiome Composition (PLEASE): Longitudinal cohort study

  Study phs000252

• DAC for Liquid CNA in High Grade Serous Ovarian Cancer

  Low pass sequencing of sequential cell free and tumour DNA with matched whole genome sequencing from five patients with high grade serous ovarian cancer presented in Hockings et al Cancer Research paper, 2025.

  Dac EGAC50000000648

• Long-read sequencing for cell-free DNA analysis (human pacbio)

  8 pregnant women at the 3rd trimesters, 4 hepatitis B carriers, and 4 patients with hepatocellular carcinoma

  Study EGAS00001006609

• NanoRCS and Reference samples

  Genome-wide NanoRCS of cell-free DNA from plasma of healthy controls (4 samples) Genome-wide sequencing of reference blood sample of healthy controls (4 samples)

  Dataset EGAD50000000974

• Long cell-free DNA molecules in maternal plasma (dataset1)

  Bam files consists PET cases and healthy cases

  Dataset EGAD00001008721