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• Longitudinal RNA-seq (whole blood) in a twin cohort

  The dataset consists of 232 RNA-seq samples (whole blood) obtained from healthy female from the TwinsUK adult registry cohort. The samples were obtained at two time points separated on average by 22 months.

  Study EGAS00001001763

• RNASeq data from one small cell prostate cancer patient (4 samples from 3 time points)

  RNASeq data from one small cell prostate cancer patient - 4 cancer samples (FFPE) from Patient 1 collected at 3 different time points. mRNA was selected using the Magnetic mRNA Isolation Module (NEB) and sequenced on the Illumina NextSeq 500 as 75bp paired end reads (total read length 150bp).

  Dataset EGAD00001011154

• Pancreatic Cancer Case Control Association Study

  Pancreatic cancer is the fourth leading cause of cancer death in the United States. This is in large part due to the rapidly fatal course of this disease, as the vast majority of patients die within months of diagnosis and the five-year survival rate is less than 5. We have brought together over 8000 participants from 9 studies of pancreatic cancer, to conduct a GWAS of pancreatic cancer. The studies were drawn from the Pancreatic Cancer Case-Control consortium and include case-control studies from the United States, Europe and Australia. Sites include: Johns Hopkins National Familial Pancreas Tumor Registry, Mayo Clinic Biospecimen Resource for Pancreas Research, Ontario Pancreas Cancer Study (OPCS), Yale University, MD Anderson Case Control Study, Queensland Pancreatic Cancer Study, University of California San Francisco Molecular Epidemiology of Pancreatic Cancer Study, International Agency of Cancer Research and Memorial Sloan Kettering Cancer Center.

  Study phs000648

• RNAseq_of_healthy_mesothelial_cells_and_primary_mesothelioma_cell_lines

  Mesothelioma is a rare and aggressive cancer associated with previous exposure to asbestos. Currently there are no effective treatments for mesothelioma and majority of patients will die within a year after diagnosis. Although a large number of preclinical and clinical trials assessed the efficacy of various therapuetic modes, including anti-angiogenic therapies, immunotherapy, antibody-drug conjugates and oncolytic viruses, none of the tested molecules entered the clinic. Thus, to better understand what drives mesothelioma carcinogenesis and to identify novel targets for therapy, in this project we aim at performing a comprehensive transcriptomic analysis of heathy mesothelial cells and a panel of mesothelioma cells lines. Primary mesothelial cell lines were established in prof. Marciniak lab from human pleural specimens, while primary mesothelioma cell lines were obtained from MesobanK. Both models constitute low passage cell lines and therefore should closely represent genetics of the original tissue.

  Study EGAS00001005728

• Variability in immune response genes and prediction of severe SARS-CoV-2 infection (INMUNGEN-Cov2 project)

  Genetic factors may contribute to explain the variable clinical response to SARS-CoV-2 infection. To this end we sequenced the DNA of 392 COVID-19 patients from Spain. Whole Exome Sequencing (WES) was performed at two different sequencing centers. Half of the samples were sequenced at a commercial service, NIMGenetics, whereas the other half were sequenced by the EASI-Genomics consortium. Finally, Variant Call Format (VCF) files for each sample was also obtained.

  Study EGAS50000000066

• Atezolizumab monotherapy following dCRT indicated a promising cCR rate in patients with unresectable locally advanced esophageal squamous cell carcinoma (EPOC1802)

  The objective is to analyze tumor and normal cell exome sequencing of esophageal cancer patients participating in the Tenergy trial before treatment and RNA sequencing specimens of tumor biopsy specimens at three points before treatment, after radiation chemotherapy, and after atezolizumab administration, in order to search for biomarkers to predict treatment response. Exome sequencing of pretreatment tumor tissue (27 specimens) and normal tissue (27 specimens) from esophageal cancer patients participating in the Tenergy trial, and RNA sequencing of tumor biopsy specimens at three time points before treatment (28 specimens), after radiation chemotherapy (25 specimens) and after atezolizumab administration (25 specimens).

  Study JGAS000708

• Oxford Nanopore long-read sequencing data of high-grade serous ovarian cancer

  This dataset comprises whole-genome Oxford Nanopore long-read sequencing data from six high-grade serous ovarian cancer (HGSOC) patients, including cryopreserved, pre-treatment tumor tissues and matched peripheral blood samples (12 samples in total). High-molecular-weight DNA was prepared using the SQK-LSK114 Ligation Sequencing Kit and sequenced on FLO-PRO114M flow cells (R10.4.1). Basecalling was conducted using the super-accurate (SUP) model, enabling simultaneous detection of 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC). The dataset includes BAM files containing base modification information for downstream genomic and epigenomic analyses.

  Dataset EGAD50000001509

• Exome sequencing of 102 gastric cancer and matched normal from Japanese cohorts (YCU)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 102 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Dataset EGAD00001004042

• Exome sequencing of 142 gastric cancer and matched normal from Japanese cohorts (UT)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 142 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Dataset EGAD00001004041

• EGAD00000000002

  WTCCC1 project samples from UK National Blood Service

  Dataset EGAD00000000002

• Whole genome sequencing of matched esophageal tumor-normal samples

  The dataset includes whole genome sequencing (WGS) data on ten matched esophageal tumor-normal pairs. WGS was performed by the cancer sequencing service of CG with an average read coverage of approximately 50-fold. Illumina HiSeq2000 instrument was used to perform the sequencing.

  Dataset EGAD00001004832

• Whole exome sequencing of 184 unrelated subjects with 22q11.2 deletion syndrome (DiGeorge syndrome/velo-cardio-facial syndrome)

  Our goal is to find genetic modifiers of major phenotypes in patients with 22q11.2 deletion syndrome, also known as DiGeorge syndrome or velo-cardio-facial syndrome. Whole exome sequencing was performed as part of a contract to the NHLBI, Resequencing and Genotyping Service. We have obtained cardiac phenotype information from the de-identified subjects enrolled in the study, either by echocardiography report or medical doctor report. All of the subjects have a 3 million base pair 22q11.2 deletion flanked by low copy repeats, LCR22, A-D.

  Study phs000987

• Tumor intrinsic and extrinsic mechanisms of response and resistance to blinatumomab in relapsed/refractory acute lymphoblastic leukemia

  Key Points• Multiple mechanisms of acquired CD19 mutations and splicing contribute to CD19 loss and relapse to blinatumomab.• Identification of CD19 ex2part levels represents a new biomarker predictive of resistance or likely failure of blinatumomab

  Study EGAS00001004027

• INCLIVA-CC-WES DAC

  Localised colon cancer WES study contaning WBCs, tissue and plasma samples at different time points

  Dac EGAC50000000156

• Genome analysis of oesophageal cancer and Barrett's oesophagus

  The median survival of oesophageal cancer this year is only 13 to 19 months after diagnosis and more than 90% will die from their disease. Therefore better treatment options are needed. The likelihood of cure for early screen-detected cancers is much higher. Barrett's oesophagus is a pre-cancerous lesion associated with a 30-40 fold increased risk of developing cancer. In an attempt to detect cancer early many patients with Barrett's are enrolled into surveillance programs involving regular endoscopies. A major problem with this approach is that the prevalence of BO in the population is estimated to be around 2%, but most patients with BO will never develop cancer. We are undertaking genomic and/or transcriptomic analysis of oesophageal tumours, Barrett's oesophagus and matched normal samples. The aim is to identify oesophageal-related genomic and transcriptomic alterations, which may reveal mutational process occurring, suggest biomarkers of tumour progression and treatment and identify novel treatment strategies.

  Study EGAS00001002864

• Combining dasatinib and IFN-α in CML – immunomodulatory effects linked to treatment response and adverse events

  We pooled 100,000 cells from the 12 scRNA+TCRab-seq samples from peripheral blood from three time points (n=4, samples at 0, 3, and 12 months) to understand the landscape of immune subsets in CML during the course of dasatinib+IFN-α treatment

  Study EGAS00001005049

• Whole Exome Sequencing of a Lung Adenocarcinoma Patient Across Three Time Points

  A 65-year-old female patient with a significant smoking history (40 pack-years) was first diagnosed with lung adenocarcinoma (LUAD) in the left lung in May 2020 (L1-T1). One year later, in May 2021, the patient progressed with a new LUAD in the right lung (L1-T2) and in May 2024, another LUAD emerged in the right lung (L1-T3). Whole Exome Sequencing (WES) analysis was conducted on three tumor biopsies obtained at different time points from the same patient to investigate clonal trajectories.

  Study EGAS50000000812

• Rapid Acceleration of Diagnostics - Digital Health Technologies (RADx-DHT): NIH Digital Health Solutions for COVID-19: Clear2Go - A Digital Identity Wallet for Health Status

  Clear2Go is a solution/app that provides digital, non-refutable cryptographic proof of testing or vaccination that can be used to evaluate risk of allowing individuals to return to normal work, travel, and public life activities. It is a mobile service that maps a person's vetted identity and biometrics to the phone and then cryptographically binds it with their COVID-19 test and vaccination records. The person can then prove their status by utilizing the credentials with a QRCode or NFC tap.DOI: https://rapids.ll.mit.edu/10.57895/b2d6-8060

  Study phs002628

• Comprehensive genetic analysis of uveal melanoma heterogeneity during metastatic progression

  Uveal melanoma (UM) is the most common primary intraocular malignancy in adults. Despite improvement of diagnosis and treatment of the primary tumor, there is no effective treatment of metastatic disease and approximately half of patients will die within one year or less following metastases detection. Tumor heterogeneity has been proposed as a key factor of drug resistance. However, it has been scarcely studied in UM. The present project aims searching for specific drivers of the metastatic progression, describing the genomic and transcriptomic landscape of metastatic UM, exploring tumor heterogeneity and investigating its role in drug resistance. Thus whole exome sequencing and transcriptomics have been performed on constitutional, primary tumor and metastatic samples from 28 UM patients.

  Dataset EGAD00001004554

• Youth-GEMs, the project using data to define the mental health trajectories of young people

  Mental health trajectories are shaped by genetic, cognitive, social, and environmental factors that are particularly influential during human development. How exactly the interplay between these factors is impacting mental health, however, is yet unknown. The project “Gene Environment interactions in Mental health trajectories of Youth (Youth-GEMs)”, funded by the European Commission under the Horizon Europe programme, aims to help reducing mental suffering among European youth. How do Youth-GEMs contribute to bettering mental health in young people? Youth-GEMs aims to identify specific neurological, (epi)genetic and environmental drivers on mental health trajectories of young people. To do so, the project is working on a public knowledge base on functional genomics of the developing human brain, between birth and 24 years old. Reliable predictive models for trajectories of onset and course of mental illness in young people of the general population in Europe will be developed. Additionally, a secure and FAIR data infrastructure in mental health is being produced. Engaging and empowering young people Youth-GEMs is also working on the engagement of young people in the scientific field of Psychiatry. For that, the project is developing initiatives such as Science Café, intended to create a learning community where ideas and stories are shared. The 10th Science Café will take place today, with the participation of Lauren Fromont from the EGA. How do the EGA contribute to Youth-GEMs? The contributions require careful data management and harmonisation: we are dealing with an extraordinary amount of data types, sources, and time points (since the studies are longitudinal). To analyse them together and to determine which factors and interactions are truly key to account for mental health trajectories, the variables need to be transformed in a common “language”, i.e., harmonised under a common data model. Further, to guarantee FAIRness of data storage and sharing for future projects that will further advance our knowledge in the mental health field, we are ensuring that data are processed securely but can also be discovered easily. Find out more information about the project in the Youth-GEMs website.

  Blog youth-gems-mental-health

• Average_5mC_genome_wide

  Average genome-wide methylation levels per sample at different time points using nanopolish calls. Data from 8 individuals.

  Dataset EGAD00010002412

• Average_5hmC_genome_wide

  Average genome-wide hydroxymethylation levels per sample at different time points using megalodon calls. Data from 8 individuals.

  Dataset EGAD00010002419

• Epigenomic timecourse of brain organoid development

  Single-cell Cut&Tag of three histone modifications and chromatin accessibility over a timecourse of brain organoid development from pluripotency. We profiled 5 time points of brain organoid development and 2 time points of retinal organoid development. At each time point used scCut&Tag to profile histone modifications (H3K27me3, H3K27ac, H3K4me3) as well as multiome-seq (10X) to jointly profile transcriptome and chromatin accessibility from the same cell suspension. Library preparation was carried out with the 10x genomics platform.

  Dataset EGAD50000000222

• GWAS for Membranous Nephropathy

  Primary membranous nephropathy (MN) is a rare autoimmune cause of kidney failure. This dataset is from a genome-wide association study (GWAS) designed to identify novel genetic risk loci for MN. The provided cohort (named as European-1 Cohort) is composed of 611 cases of primary MN and 1,246 healthy controls of European ancestry. This cohort was used in the GWAS meta-analysis, as described in the manuscript entitled "Genetic architecture of membranous nephropathy and its potential diagnostic implications" (Nature Communications 2020, in press).The genome-wide summary statistics, including trans-ethnic meta-analysis across 8 GWAS cohorts of European and East Asian ancestry and ethnicity specific meta-analyses, are freely available for download on the Kiryluk lab website: http://www.columbiamedicine.org/divisions/kiryluk/resources.php.

  Study phs001984

• Short read sequencing dataset of pathogen-stimulated PBMCs

  QuantSeq 3'-mRNAseq. 5 donors, 4 stimuli, 2 time points

  Dataset EGAD50000000012

• Methylation_PBL_IBD_LTS

  Longitudinal whole-genome DNA methylation profiling of PBL obtained from IBD patients (CD and UC) at two different time points

  Dataset EGAD00010002402

• Methylation-Based Immune Deconvolution in Prostate Cancer Patients Before and After Radical Prostatectomy

  To explore whether surgical treatment for prostate cancer leads to long-term immune changes, we conducted a pilot study of n=11 prostate cancer patients treated with radical prostatectomy. We also included n=8 patients managed with active surveillance as a comparison group. We examined intra-individual changes in circulating immune cell subsets using serial blood samples collected pre- and approximately 6-months post-prostatectomy, and from matched time points for the patients managed on active surveillance. Immune cell subsets were deconvoluted using genome-wide methylation data. We observed no meaningful changes in circulating immune cell subsets in either patient group, suggesting that any surgery-induced immune changes to the circulating immune profile may not be long-lasting. The genome-wide methylation data from the two time points will be made available through dbGaP.

  Study phs003660

• Diseased_heart_analysis__RNA_Adult

  Samples for this project are taken from adult human hearts which have been preserved using 2 different methods (cold static storage on ice, and hypothermic perfusion). Samples have been acquired at various time points during post-preservation normothermic perfusion. The aim of the project is to assess the transcriptional changes caused by these differing methods of preservation.

  Study EGAS00001008302

• ChIP-seq of primary AML patients with t(3;3)/inv(3)

  ChIP-seq was conducted in blasts from patients with t(3;3) AML to assess differences of the GATA2 super-enhancer between the translocated allele and the non-translocated allele. The dataset includes 2x H3K27ac ChIP-seq and 1x MYB ChIP-seq. ChIP samples were processed according to the Illumina TruSeq ChIP Sample Preparation Protocol (Illumina) or Diagenode Library V3 preparation protocol (Diagenode) and either sequenced single-end (1x 50 bp) on the HiSeq 2500 platform (Illumina) or paired-end (2x100 bp) on the Novaseq 6000 platform (Illumina). Briefly, reads were aligned to the human reference genome build hg19 with bowtie for single-end runs and bowtie2 for paired-end runs.

  Dataset EGAD00001006821

• Average_5mC_Roadmap_histoneMarks

  Average methylation levels based on nanopolish calls from Roadmap Epigenomics histone mark annotations using different cell types. Data from 8 individuals at different time points.

  Dataset EGAD00010002422

• Average_5hmC_Roadmap_histoneMarks

  Average hydroxymethylation levels based on megalodon calls from Roadmap Epigenomics histone mark annotations using different cell types. Data from 8 individuals at different time points.

  Dataset EGAD00010002417

• Average_5hmC_Roadmap_chromatinStates

  Average hydroxymethylation levels based on megalodon calls from Roadmap Epigenomics chromatin state annotations using different cell types. Data from 8 individuals at different time points.

  Dataset EGAD00010002414

• Average_5mC_Roadmap_chromatinStates

  Average methylation levels based on nanopolish calls from Roadmap Epigenomics chromatin state annotations using different cell types. Data from 8 individuals at different time points.

  Dataset EGAD00010002413

• Average_5hmC_TF_sites

  Average hydroxymethylation levels on transcription factor binding sites obtained from ENCODE (ChIP-sequencing of GM12878 lymphoblastoid cell line). Data from 6 individuals at different time points.

  Dataset EGAD00010002421

• Genetic_vulnerability_of_knockout_cancer_lines

  Genome-wide CRISPR/Cas9 library screen was performed in isogenic cell lines. Three biological replicates were used. Cells were harvested at initiation of screen and at specific time points following cell culture. Using this approach we aim to identify genes specifically important in cell survival in engineered cell lines. Please perform 72, instead of 36, PCR reactions as the screen performed at 200x coverage.

  Study EGAS00001002253

• Lindsey E. Jones et al. Patient-derived cells from recurrent tumors that model the evolution of IDH-mutant glioma. Neuro-Oncology Advances, 2020. We established robust, versatile, and well-characterized Patient Derived Cells (PDC) of an IDH1-mutant astrocytoma and an IDH1-mutant oligodendroglioma that represents defined evolutionary stages of chemotherapy-induced hypermutation. The PDCs retain tumor subtype defining features over time as well as classic hallmarks of cancer, including anchorage independent growth and cell immortality. The integrated phylogenies composed of PDCs,single-cell-derived PDCs, patient-derived xenografts, and corresponding spatiotemporal tumor tissue samples also provide new insight into the clonality, evolutionary pattern, and immense mutational load of hypermutated IDH mutant gliomas.

  IDH-mutant lower-grade gliomas can undergo malignant progression via temozolomide-driven hypermutation. Patient-derived cells (PDC) that model the genetically distinct hypermutated (HM) tumor subgroup are generally lacking, and few if any human brain tumor cell models are from defined evolutionary time points. Here, we characterize multiple PDC derived from independent surgical specimens of IDH1-mutant recurrences, including an ATRX and TP53-mutant astrocytoma and a 1p/19q co-deleted and TERT promoter-mutant oligodendroglioma. We determined the evolutionary time points represented by each PDC using exome sequencing and phylogenetic reconstruction, comparing the PDC and single cell clones of the PDC (scPDC) to multiple spatiotemporal tumor tissue samples, PDC-derived xenografts (PDX) and patient-matched blood. The tumor samples exhibited TMZ-induced mutagenesis and a branching pattern of evolution. We found clear evidence of two fully independent founder HM clones in the tumor tissue that are faithfully represented by independent PDC. The PDC, scPDC and PDX also shared the mutagenesis signature and represent the mid and later evolutionary time points of their corresponding tumors. The PDC maintained the tumor subtype-defining features over many passages, including heterozygosity of the IDH1 R132H mutation, production of 2-hydroxyglutarate (2-HG), and subtype-specific telomere maintenance mechanisms. The PDC from both tumors exhibited anchorage-independent growth in soft agar. The oligodendroglioma PDC formed infiltrative intracranial tumors with characteristic oligodendroglioma histology, initially with a long period to tumor formation. We conclude that the PDC, scPDC and PDX faithfully model the heterogeneous clonal origins of the corresponding tumor tissue. The multilevel analysis also provides new insight into the intratumoral heterogeneity and vast mutational load of HM glioma. The PDC from multiple evolutionary time points presented in the context of full clinical timelines may be useful to model evolution and intratumoral heterogeneity, important sources of therapeutic failure.

  Study EGAS00001003992

• RNAseq SCLC Cell lines MYC

  RNAseq data set (Mollaoglu et al., MYC drives progression of small cell lung cancer to a variant neuroendocrine subtype with vulnerability to Aurora kinase inhibition) RNA isolation from primary tumors and healthy lungs was performed using RNeasy Mini Kit (Qiagen) with the standard protocol. RNA was subjected to library construction with the Illumina TruSeq Stranded mRNA Sample Preparation Kit (cat# RS-122-2101, RS-122-2102) according to manufacturer’s protocol. Chemically denatured sequencing libraries (25 pM) are applied to an Illumina HiSeq v4 single read flow cell using an Illumina cBot. Hybridized molecules were clonally amplified and annealed to sequencing primers with reagents from an Illumina HiSeq SR Cluster Kit v4-cBot (GD-401-4001). Following transfer of the flowcell to an Illumina HiSeq 2500 instrument (HCSv2.2.38 and RTA v1.18.61), a 50 cycle single-read sequence run was performed using HiSeq SBS Kit v4 sequencing reagents (FC-401-4002).

  Dataset EGAD00001003099

• Longitudinal Single-cell Genomic Analysis of Initial and Recurrent Meningioma

  This study investigates the genomic evolution of meningioma through single-cell whole genome sequencing analysis of paired tumor samples. We analyzed tumor tissues from initial and recurrent meningiomas from the same patients to understand clonal evolution and tumor progression. The research aims to characterize copy number alterations and genomic heterogeneity at single-cell resolution across different time points of tumor development.

  Study EGAS50000000860

• NHLBI TOPMed: Rare Variants for Hypertension in Taiwan Chinese (THRV)

  The THRV-TOPMed study consists of three cohorts: The SAPPHIRe Family cohort (N=1,271), TSGH (Tri-Service General Hospital, a hospital-based cohort, N=160), and TCVGH (Taichung Veterans General Hospital, another hospital-based cohort, N=922), all based in Taiwan. 1,271 subjects were previously recruited as part of the NHLBI-sponsored SAPPHIRe Network (which is part of the Family Blood Pressure Program, FBPP). The SAPPHIRe families were recruited to have two or more hypertensive sibs, some families also with one normotensive/hypotensive sib. The two Hospital-based cohorts (TSGH and TCVGH) both recruited unrelated subjects with different recruitment criteria (matched with SAPPHIRe subjects for age, sex, and BMI category).

  Study phs001387

• UK Biobank whole cohort directly genotyped and imputed data (~500,000 participants)

  Genotype data is available for all 500,000 participants in the UK Biobank cohort. Genotyping has been performed using the Affymetrix UK BiLEVE Axiom array on an initial 50,000 participants and the remaining 450,000 participants have been genotyped using the Affymetrix UK Biobank Axiom® array. The two arrays are extremely similar (with over 95% common content).Quality control and imputation (to over 90 million SNPs, indels and large structural variants) has been performed by a collaborative group headed by the Wellcome Trust Centre for Human Genetics.The following data are available:* A clean set of QC’ed genotype calls* Confidence values that a genotype call is correct* Intensity data to generate cluster plots* Extensive QC information regarding SNPs and samples including SNP metrics, batch effects, population structure and relatedness* Imputed dataFor further information, please refer to the UK Biobank website

  Study EGAS00001002399

• Beacon v2

  Beacon v2: a tool for data discovery Motivation In the era of data-driven health research and personalised medicine, human genomic data has become extremely valuable. These are also identifiable data, as they carry information pointing to a specific individual as well as their own family; and as such, they must be protected. This makes data discovery particularly challenging: this is where “Beacon” comes in. A “Beacon” is an API aiming to enable the search of genomic variants and associated information without jeopardising the privacy of the dataset. Here, we refer to its current version, namely version 2 (v2). Definition Beacon v2 is a term that can refer to different aspects. The EGA is playing a central role in the following aspects: The Beacon v2 protocol is a Global Alliance for Health and Genomics standard. The Beacon v2 Reference Implementation (B2RI) is an “out-of-the-box” Beacon instance developed with ELIXIR, which facilitates Beacon deployment. The EGA Beacon(s) are Beacons following the v2 standard and using the B2RI, deployed on top of data hosted at the EGA and allowing for their discovery. Resources Depending on whether you are visiting us a stakeholder (you need more general information about Beacon), a deployer /implementer (you want to have your own Beacon instance), or an EGA user (you want to query Beacon and start browsing data), you will be interested in the following resources: Your role Beacon aspect Documentation type Stakeholder Beacon v2 protocol Beacon website Beacon page on the GA4GH website Deployer/Implementer Beacon v2 protocol Read the docs: Beacon v2 standard technical description GitHub repository Beacon v2 standard Beacon v2 Reference Implementation Read the docs: B2RI technical description GitHub repository B2RI Guide to deploy Beacon using B2RI EGA user EGA Beacon(s) API in construction UI in construction

  Documentation about/projects-and-funders/beacon

• Resuscitation Outcomes Consortium (ROC) Trauma Epidemiologic Registry (Trauma Epistry) (ROC-Trauma Epistry-BioLINCC)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions.Available Data: This dataset only includes traumatic injury participants. For ROC cardiac arrest Epistry data please see: ROC-Cardiac Epistry 1 and 2 and ROC-Cardiac Epistry 3.Objectives: To build a prospective population-based registry of participants with out-of-hospital traumatic injury responded to by Emergency Medical Services (EMS). Specific aims included: to establish whether the results of Resuscitation Outcomes Consortium (ROC) trials can be generalized to the larger population of people that experience traumatic injury; to more fully establish the burden of traumatic injury; and to examine the relationships between variation in EMS structure and process, regional and periodic factors, and participant outcomes.Background: Traumatic injury is a major public health problem generating substantial morbidity, mortality, and economic burden on society. The majority of seriously injured persons are initially evaluated and cared for by prehospital providers, however the effect of EMS systems, EMS clinical care, and EMS interventions on trauma patient outcomes is largely unknown. EMS factors such as service level, number of responding providers, use of procedures or drugs in the field, training, quality assurance/feedback, and response time intervals also vary significantly by region.The Resuscitation Outcomes Consortium (ROC) was established in 2004 to conduct clinical research in the areas of cardiopulmonary arrest and life-threatening traumatic injury with the overall goal of improving resuscitation outcomes. Previous trauma registries have generally focused primarily on hospitalized patients with limited prehospital information. Registries may also exclude trauma cases at far ends of the spectrum, such as those who die in the field or in a non-trauma center and/or patients that are treated and released. These limitations do not allow for detailed, outcome-based assessments of EMS system factors necessary to define prehospital resuscitation best practices. Therefore there was a need for standardized data collection of out-of-hospital traumatic injuries matched to hospital-based outcomes in diverse geographic locations in order to identify the independent effects of prognostic or treatment factors accounting for variations in survival. Participants: The registry included 13,830 traumatic events from 264 EMS agencies transporting to 287 acute care hospitals from the following regional centers: Birmingham, Alabama; Dallas, Texas; Iowa City, Iowa; Milwaukee, Wisconsin; Pittsburgh, Pennsylvania; Portland, Oregon; San Diego, California; Seattle/King County, Washington; Ottawa, Ontario; Toronto, Ontario; and Vancouver, British Columbia.Design: ROC Epistry collected standardized data regarding episode-specific factors, participant demographics, clinical information, pre-hospital interventions and disposition, hospital information, and participant outcome for all out-of-hospital traumatic injuries in the ROC regions. Cases were identified through review of emergency response system records including dispatch centers, EMS ground agencies, and air medical services. Out-of-hospital data were extracted from existing databases whenever possible and augmented with targeted review of EMS reports. Hospital data were abstracted directly from the hospital file in most cases. Sites submitted data using a web-based interface or batch uploads (Newgard, et al., 2008, PMID: 18482792).

  Study phs003809

• The application of RNA sequencing for the diagnosis and genomic classification of pediatric acute lymphoblastic leukemia

  Acute lymphoblastic leukaemia (ALL) is the most common childhood malignancy, and implementation of risk-adapted therapy has been instrumental in the dramatic improvements in clinical outcomes. A key to risk-adapted therapies includes the identification of genomic features of individual tumors, including chromosome number (for hyper- and hypodiploidy) and gene fusions, notably ETV6-RUNX1, TCF3-PBX1 and BCR-ABL1 in B-cell ALL (B-ALL). RNA-sequencing (RNA-seq) of large ALL cohorts has expanded the number of recurrent gene fusions recognized as drivers in ALL, and identification of these new entities will contribute to refining ALL risk stratification. We used RNA-seq on 126 ALL patients from our clinical service to test the utility of including RNA-seq in standard of care diagnostic pipelines to detect gene rearrangements and IKZF1 deletions. RNA-seq identified 86% of rearrangements detected by standard of care diagnostics. KMT2A-rearrangements (MLL), whilst usually identified, were the most commonly missed by RNA-seq as a result of low expression. RNA-seq identified rearrangements that were not detected by standard of care testing in nine patients. These were found in patients who were not classifiable using standard molecular assessment. We developed an approach to detect the commonest IKZF1 deletion from RNA-seq data and validated this using a RQ-PCR assay. We applied an expression classifier to identify Ph-like B-ALL patients. T-ALL proved a rich source of novel gene fusions which have clinical implications or provide insights into disease biology. Our experience shows that RNA-seq can be implemented within an individual clinical service to enhance the current molecular diagnostic risk classification of ALL.

  Study EGAS00001004212

• Mechanisms of Therapy Driven Clonal Evolution in Oncogenic RAS Mutant Relapsed Acute Lymphoblastic Leukemia

  Although multi-agent combination chemotherapy is curative in a significant fraction of childhood acute lymphoblastic leukemia (ALL) patients, 20% of cases relapse and most die due to chemo-refractory disease. Here we used whole-exome and whole-genome sequencing to analyze the mutational landscape and pattern of clonal evolution at relapse in pediatric ALL cases. These analyses showed that ALL relapses originate from a common ancestral precursor clone of the diagnosis and relapsed populations and frequently harbor mutations implicated in chemotherapy resistance. RAS-MAPK pathway activating mutations in NRAS, KRAS and PTPN11 were present in 24/55 (44%) cases in our series. Notably, while some cases showed emergence of RAS mutant clones at relapse, in others, RAS mutant clones present at diagnosis were replaced by RAS wild type populations. Mechanistically, functional dissection of mouse and human wild type Kras and mutant Kras (Kras G12D) isogenic leukemia cells demonstrated induction of methotrexate resistance, but also improved response to vincristine, in mutant Kras- expressing lymphoblasts. These results identify chemotherapy driven selection as a central mechanism of leukemia clonal evolution and pave the road for the development of tailored personalized therapies for the treatment of relapsed ALL.

  Study phs001072

• Genetic Studies of Homologous Recombination Deficiency in Hispanic Gastric Cancer

  Approximately 10% of gastric cancer cases show familial clustering and a hereditary cause is likely, however, only 1-3% cases result from known hereditary syndromes – which are predominantly associated with CDH1 and CTNNA1 genes. Hispanics are > 2 times more likely to be diagnosed and to die from gastric cancer compared to non-Hispanic whites. Not only does gastric cancer precision medicine lag behind other cancers – there is an urgent need to understand its etiology. Germline mutations in homologous recombination genes have been implicated as important risk factors for gastric cancer. The purpose of this study is to continue to generate knowledge to improve gastric cancer outcomes and disparities by 1) characterizing prevalence of germline mutations in homologous recombination genes and identify new genes associated with gastric cancer 2) perform molecular characterization of gastric tumors in Hispanic patients. Participants for germline analysis were enrolled from Chile, Colombia, Mexico, Portugal, Spain, Uruguay.Whole exome sequence capture was performed for all germline and somatic samples using Agilent SureSelect Human All Exon v7 Kit. All sequencing was performed on an Illumina NovaSeq 6000. Germline Analysis: Whole exome sequencing was performed on 536 Hispanic patients (290 males, 246 female)

  Study phs003251

• Widespread DNA hypomethylation and differential gene expression in Turner syndrome

  Adults with 45,X monosomy (Turner syndrome) reflect a surviving minority since more than 99% of fetuses with 45,X monosomy die in utero. In adulthood 45,X monosomy is associated with increased morbidity and mortality, although strikingly heterogeneous with some individuals left untouched while others suffer from cardiovascular disease, autoimmune disease and infertility. The present study investigates the leukocyte DNAmethylation profile by using the 450K-Illumina Infinium assay and the leukocyte RNA-expression profile in 45,X monosomy compared with karyotypically normal female and male controls. We present results illustrating that genome wide X-chromosome RNA-expression profile, autosomal DNA-methylation profile, and the X-chromosome methylation profile clearly distinguish Turner syndrome from controls. Our results reveal genome wide hypomethylation with most differentially methylated positions showing a medium level of methylation. Contrary to previous studies, applying a single loci specific analysis at well-defined DNA loci, our results indicate that the hypomethylation extend to repetitive elements. We describe novel candidate genes that could be involved in comorbidity in TS and explain congenital urinary malformations (PRKX), premature ovarian failure (KDM6A), and aortic aneurysm formation (ZFYVE9 and TIMP1)

  Study EGAS00001002190

• Reference Profiles of ExRNAs in Normal Human Pregnancy

  In this study, we did a comprehensive exRNA profiling of plasma and serum specimens from healthy pregnant women, sampled at different gestational time points, and including subjects with diverse geographical and ethnic backgrounds. This study also contains samples from male and female healthy donors to provide a baseline. The aim of this study is to identify miRNAs that can predict the gestation age and to build a miRNA profile across gestation using small RNA-seq data.

  Study phs003182

• Single Cell Analysis Reveals Immune Dysfunction from the Earliest Stages of CLL that can be Reversed by Ibrutinib

  We applied single cell RNA sequencing to broadly characterize circulating immune cells co-existing with leukemic cells during natural chronic lymphocytic leukemia (CLL) progression. We used peripheral blood mononuclear cells from patients diagnosed from monoclonal B-lymphocytosis (MBL) and CLL at different time-points, and age-matched healthy donors (HDs). We analyzed the differences in cell type proportions and immune cell states between MBL/CLL patients and HDs and over time.

  Study phs002705

• Single-cell RNA sequencing of human IL-18R supported CAR T cells targeting oncofetal Tenascin C

  C.TNC-CAR.Zip18R CAR-T cells are from 2 donors and multiplexed 10x Genomics scRNA-seq were performed with a hashtag to label each sample. For tumor and CAR-T cell cocluture samples, CAR-T cells were extracted from 3 time points. The raw data are fastq format for total 20 samples considering sequencing lanes. The multiplexing information, CAR and Zip18R sequences are deposited in analyses.

  Study EGAS50000000772

• Cell types of the human retina and its organoids at single-cell resolution. Cowan et al

  Human organoids recapitulating the cell-type diversity and function of their target organ are valuable for basic and translational research. We developed light-sensitive human retinal organoids with multiple nuclear and synaptic layers, and functional synapses. We sequenced the RNA of 285,441 single cells from these organoids at seven developmental time points and from the periphery, fovea, pigment epithelium and choroid of light-responsive adult human retinas.

  Study EGAS00001004561

• FFPE, buffycoat and cell free DNA from N. German esophagus cancer patients - 2021

  We recruited 28 patients and sequenced samples from their FFPE tissue, full blood buffy coat and plasma cell free DNA from diagnosis and other, longitudinal time points. The cell free DNA was sequenced ultra-deeply. The IDT PanCancer panel was used for targeted enrichment. Aims: detection of primary tumor mutations in cell free DNA, overlap and difference in mutation profiles between primary tumor, metastases and cell free DNA.

  Study EGAS00001006813

• Average_hypermethylation_TF_sites

  Average hypermethylation on transcription factor binding sites based on nanopolish calls; only positions showing higher methylation than sample’s average methylation at enhancers were included when defining the average methylation level. Data from 6 individuals at different time points.

  Dataset EGAD00010002411

• Clinical and ctDNA data for IMpassion031

  Clinical and ctDNA data for IMpassion031, including survival, response, and ctDNA data from baseline through post-surgery time points. 222 samples run on Signatera assay. File type is csv.

  Dataset EGAD50000001420

• 5hmC enrichment in human monocyte differentiation

  This dataset consists of 5hmC capture-seq data from human monocytes, monocyte-derived dendritic cells. It includes two biological replicates and three time points. Including controls, the dataset comprises 10 samples in total.

  Dataset EGAD00001006603

• Longitudinal RNA-seq in a twin cohort

  The dataset consists of 232 RNA-seq samples (whole blood) obtained from healthy female from the TwinsUK adult registry cohort. The samples were obtained at two time points separated on average by 22 months.

  Dataset EGAD00001002068

• Altered chromosomal topology drives oncogenic programs in gastrointestinal stromal tumors

  Metabolic lesions with pleiotropic effects on epigenetic regulation and other cellular processes are widely implicated in cancer, yet their oncogenic mechanisms remain poorly understood. Succinate dehydrogenase (SDH) deficiency causes a subset of gastrointestinal stromal tumors (GISTs) with DNA hyper-methylation. Here we associate this hyper-methylation with changes in chromosome topology that activate oncogenic programs. To investigate epigenetic alterations in this disease, we systematically mapped DNA methylation, CTCF insulators, enhancers and chromosome topology in KIT-mutant, PDGFRA-mutant and SDH-deficient GISTs. Although these respective subtypes share similar enhancer landscapes, we identified hundreds of putative insulators where DNA methylation replaced CTCF binding in SDH-deficient GISTs. We focused on disrupted insulators that partitions super-enhancers from FGF3, FGF4 and the KIT oncogene. Recurrent loss of this insulator alters locus topology in SDH-deficient GISTs, allowing aberrant physical interaction between enhancers and oncogenes. CRISPR-mediated excision of the corresponding CTCF motif in an SDH-intact model disrupted the boundary and up-regulated FGFs and KIT expression. Our findings reveal how a metabolic lesion destabilizes chromatin structure to facilitate the initiation and selection of epigenetic alterations that drive oncogenic programs in the absence of canonical mutations.

  Study phs001906

• Impact of allogeneic umbilical-cord derived mesenchymal stromal cells on B-cell scRNAseq in patients with systemic lupus erythematosus

  The impact of MSC(UC) on peripheral B cells from Systemic Lupus Erythematosus (SLE) patients was studied by 10X scRNAseq. This scRNAseq study encompassed 3 SLE patients at 3 time points: before or after (1 month, and 3 months) MSC injection in order to analyze B cell subsets and their DEG. The aim of this study was to observe the potential changes of B cell subsets after MSC(UC) injection in SLE patients.

  Study EGAS50000000325

• Longitudinal Transcriptomic Profiling of Endothelial Progenitor Cells in Post-COVID-19 Patients: Insights at 3 and 6-Months Post-SARS-CoV-2 Infection

  Bulk RNA-sequencing analysis of endothelial cells isolated from post-COVID patients at 3 and 6 months post-infection, alongside healthy controls. This study aims to identify differentially expressed genes in endothelial cells from post-COVID patients—at both 3- and 6-month time points—compared to those from healthy individuals. The objective is to uncover upregulated and downregulated pathways potentially associated with long-term consequences of SARS-CoV-2 infection.

  Study EGAS50000000993

• The Jerusalem Perinatal Study (JPS) aimed to examine the developmental origins of cardiometabolic risk.

  The Jerusalem Perinatal Study (JPS) aimed to examine the developmental origins of cardiometabolic risk and explore the mechanisms underlying the associations between perinatal characteristics and the development of risk for adult chronic disease. In other words, the cohort has enabled the examination of associations between maternal and paternal characteristics with cardiometabolic risk variables in offspring at various points in the life course, as well as the effect of longitudinal changes in characteristics in both parents and offspring.

  Study EGAS00001004075

• COVID_19_Challenge_Project_Single_Cell_Profiling

  Single-cell profiling of sero-negative and sero-positive humans that were inoculated with SARS-CoV-2. The cellular response during SARS-CoV-2 is profiled using single-cell transcriptomics, CITE-seq and single cell immune profiling, by sampling PBMCs and nasal swabs before and at multiple time points during SARS-CoV-2 infection. This one-of-a-kind cellular map will give unique temporal resolution of how nasal and immune cells respond to SARS-CoV-2 exposure and infection

  Study EGAS00001005696

• Exome sequencing of samples taken at multipl time points to monitor therapy response in AML

  As part of our individualized systems medicine program, personalized treatment options are identified and administered to chemorefractory AML patients based on exome sequencing and ex-vivo drug sensitivity and resistance testing data. In this study, we developed this approach further to take into account clonal heterogeneity and analyzed responses of 13 AML patients to chemotherapy and six patients to targeted treatments by using exome and ultra-deep amplicon resequencing. The data submitted includes fastq files from exome sequencing of multiple time-point samples collected from the 13 patients. In this study we identified rare subclonal variants present at diagnosis or later relapse samples and developed a correlation-based method to compare subclonal responses in serial samples across multiple time-points. Significant subclone-specific responses were observed subsequent to chemotherapy and specifically to targeted therapy in five patients.

  Study EGAS00001001948

• Cardiovascular disease biomarkers derived from circulating cell-free DNA methylation

  Acute coronary syndrome (ACS) remains a major cause of worldwide mortality. The syndrome occurs when blood flow to the heart muscle is decreased or blocked, causing muscle tissues to die or malfunction. There are three main types of ACS: Non-ST-elevation myocardial infarction, ST-elevation myocardial infarction, and unstable angina. The treatment depends on the type of ACS, and this is decided by a combination of clinical findings, such as electrocardiogram and plasma biomarkers. Circulating cell-free DNA (ccfDNA) is proposed as an additional marker for ACS since the damaged tissues can release DNA to the bloodstream. We used ccfDNA methylation profiles for differentiating between the ACS types and provided computational tools to repeat similar analysis for other diseases. We leveraged cell type specificity of DNA methylation to deconvolute the ccfDNA cell types of origin and to find methylation-based biomarkers that stratify patients. We identified hundreds of methylation markers associated with ACS types and validated them in an independent cohort. Many such markers were associated with genes involved in cardiovascular conditions and inflammation. ccfDNA methylation showed promise as a non-invasive diagnostic for acute coronary events. These methods are not limited to acute events, and may be used for chronic cardiovascular diseases as well.

  Study EGAS00001007263

• Whole-genome bisulfite sequencing

  Raw reads from whole-genome bisulfite sequencing. Whole-genome bisulfite sequencing library preparations and Illumina sequencing of DNA samples from TET2 mutation carriers (Ly9, Ly11, Ly14, Id1) and their age-matched controls (Ly8, Ly10, Ly13, Id2, Id3) was done as a service at BGI (BGI Tech Solutions Co., Ltd., China). Bisulfite treatment was done with EZ DNA Methylation-Gold Kit (Zymo Research, CA, USA) for 300-400bp size-range fragments with methylated adapters in 5' and 3' ends. Sequencing was done with the HiSeq X-Ten platform using paired-end 150 base-pair read length.

  Dataset EGAD00001004779

• The Federated EGA network

  In the last 10 years, most human omics data has been generated in the context of research consortia while recently there has been an emergence of large cohorts of human data generated by healthcare initiatives. Many countries in Europe now have nascent personalised medicine programmes. Thus, human genomics is shifting from being predominantly research-driven to being funded through healthcare systems. Genetic data generated in a healthcare context is subject to more stringent information governance than research data and nonetheless all data must adhere to national data protections laws. In this context, EGA identified the need for the development of a federated network to enable secure sharing of data whilst enabling genetic data to remain within the jurisdiction in which it was generated. The Federated EGA is designed to support national data management requirements for genomic and clinical data collected from citizens as part of healthcare or biomedical research projects. It includes a secure authorised access mechanism to support research use of these data across Europe and worldwide. We have engaged with over 14 ELIXIR countries to develop the federation model. The EGA federated configuration is composed of Central EGA, Federated EGA nodes and Community EGA nodes: Central EGA offers international submissions and helpdesk support, currently EGA co-managed by EMBL-EBI and CRG, Federated EGA nodes offer EGA services to researchers within their national jurisdiction, Community EGA nodes are individual institutions or initiatives with human genetic data intended to be shared with the research community. Key services available in the Federated EGA structure are: Central EGA Federated EGA node Community EGA nodes Data submission Offers international submissions service Offers submission service in a particular jurisdiction Does not offer an external submissions service Helpdesk support Provides external international helpdesk Provides helpdesk support for submitters in its jurisdiction and for approved users of data managed at its facilities Provides helpdesk support only for approved users of data managed at its facilities Data distribution Manages worldwide distribution for data hosted at Central EGA Manages worldwide distribution for data hosted at Federated EGA node Distribution for data hosted at Community EGA node EMBL-EBI and CRG have prepared a series of documents describing the overall governance and coordination framework. These describe the Federated EGA structure, the rights and responsibilities of the different parties and governing committees, and node operation guidelines. The federation governance proposal is under review by the first countries invited to join as Federated nodes, with further interested countries likely to join in the coming years. The Central EGA team has been working closely with many ELIXIR partners, including ELIXIR Finland, Luxembourg, Germany, Norway, Spain and Sweden.

  Blog the-federated-ega-network

• Childhood Cancer Data Initiative (CCDI): OncoKids - NGS Panel for Pediatric Malignancies

  This study aimed to systematically collect clinical, registry and genomic data on pediatric cancer patients, and to contribute to the CCDI Pediatric Data Ecosystem. Clinical, treatment and outcome data on 1,039 pediatric cancer patients whose molecular profile was characterized on OncoKids gene panel at Children's Hospital Los Angeles was abstracted and harmonized for submission to the NCI’s Cancer Data Service. The OncoKids panel was designed to detect DNA mutations and amplification in almost 200 oncogenes and tumor suppressor genes, a limited number of pharmacogenomic targets and 1,700 disease-associated gene fusions at the RNA level. The panel encompasses the vast majority of FDA’s relevant pediatric molecular target list, as well as additional genes associated with ultra-rare pediatric tumors. The final data elements included DNA/RNA sequence data, OncoKids test results, clinical data on demographics, diagnosis, comorbidity and adverse events and treatment data.

  Study phs002518

• Cord blood progenitor CITE-seq dataset

  Sequencing results of single-cell transcriptome and antibody libraries from two biological experiments of cord blood progenitor cells. Four samples from different time points were processed using 10X Genomics Chromium Next GEM Single Cell 3’ Reagent Kits v3.1. Gene expression and antibody-derived libraries were sequenced separately.

  Dataset EGAD50000000405

• About

  About What's the EGA? The European Genome-phenome Archive (EGA) is a global network for permanent archiving and sharing of personally identifiable genetic, phenotypic, and clinical data generated for the purposes of biomedical research projects or in the context of research-focused healthcare systems. Jointly managed by the European Bioinformatics Institute (EMBL-EBI) in Cambridge (UK) and the Centre for Genomic Regulation (CRG) in Barcelona, we aim to advance biomedical research and promote personalised medicine worldwide by enabling discovery of and access to human genomic and health research data. The EGA contains data collected from individuals whose consent agreements authorise data release for specific research use to bona fide researchers. We ensure strict security measures to control access to the data and maintain patient confidentiality. With expertise in data management and technical infrastructure, we promote FAIR data reuse and enable researchers to share their data securely. By leveraging public funding and our strategic partnerships, the EGA provides a free service for permanent data storage, data discovery, and secure data access. In addition, we foster a federated network to provide transnational access to human research data in compliance with legal frameworks. For additional information about the EGA, please contact: Helen Parkinson and Mallory Freeberg EMBL European Bioinformatics Institute Arcadi Navarro, Roderic Guigó, and Jordi Rambla Center for Genomic Regulation History The European Genome-phenome Archive was launched in 2008 at the European Bioinformatics Institute (EMBL-EBI), an outstation of the European Molecular Biology Laboratory (EMBL), to address an identified need for archiving and sharing the results of genome-wide association studies from the Wellcome Trust Case Control Consortium. With the signing of a memorandum of understanding in 2013 and a formal agreement in 2016, the EGA became a joint project of EMBL-EBI and the Centre for Genomic Regulation (CRG). The two institutes work together to support the EGA services, including supporting submissions, website, strategic leadership, and data infrastructure developments. In 2022, the Federated EGA was officially launched with the signature of the first five countries: Finland, Germany, Norway, Spain, and Sweden. With more than 20 additional nodes worldwide preparing to join, the Federated EGA aims to become the largest human omics data sharing initiative towards understanding human health and disease. EGA overview If you're a researcher you may need to deposit, manage, or access genomic data in a secure and regulated way. The European Genome-phenome Archive (EGA) is a platform that facilitates these processes, ensuring that sensitive data is stored and shared in accordance with legal and ethical regulations. Submission process To start a submission, you need to become an EGA submitter. For that, you’ll need to sign a Data Processing Agreement (DPA) with us, that defines the terms and conditions under which your data will be processed and shared within the EGA system. The access to each study is controlled by its Data Access Committee (DAC). The DAC is responsible for managing data access requests and ensuring that the release of data is in accordance with the General Data Protection Regulation (GDPR). Please, note that once your data is released, all public metadata related to your study and dataset(s) will be searchable on the EGA website. However, the files are only accessible under controlled access, which means that a DAC has to agree to a previous data access request. Request process It is possible to submit an access request to data stored at the EGA. The DAC assigned to the study will assess the request and, if approved, grant access to the data. Requesters must provide sufficient justification for your request and comply with the intended data usage in order to get access to it. Each dataset is covered by a Data Access Agreement (DAA) that defines the terms and conditions of use for the specified dataset/s. The DAA is created and provided by the DAC, and must be signed by the individual requesting access to the given dataset/s. Download process Once the request for access is approved, the data and metadata can be downloaded. The EGA offers various download options to fit the needs: it is possible to preview files without downloading them, download specific files of interest, or even download terabytes of data. Overall, the EGA provides a secure and regulated environment for depositing, managing, and accessing human data. Regardless of the role - submitter, DAC member, or requester - the EGA provides assistance for each while ensuring that sensitive data is managed in an ethical and responsible manner. More information on how EGA handles data is available in the EGA dataflow.

  Documentation about/ega

• In Vivo Cytokine eQTL Interactions from a Lupus Clinical Trial

  The purpose of this study is to discover in vivo cytokine expression quantitative trait locus (eQTL) interactions from a cohort of patients with systemic lupus erythematosus. 157 lupus patients were enrolled in a clinical trial to test the efficacy and safety of an anti-IL-6 monoclonal antibody. At three time points, we measured interferon (IFN) status, anti-IL-6 drug exposure and genome-wide gen expression. We identified 4,818 cis-eQTLs and then observed a statistically significant enrichment of in vivo eQTL interactions with IFN status and anti-IL-6 exposure.

  Study phs001702

• Acquired Cross-Resistance in Small Cell Lung Cancer Patient-Derived Xenografts

  Here we present whole genome sequencing and RNA sequencing of patient-derived xenograft (PDX) models of small cell lung cancer (SCLC). These models were derived at a variety of clinical time points from either biopsy/resection samples, malignant effusions, or circulating tumor cells (CTCs), and grown in the subcutaneous flank of NSG (NOD.Cg-Prkdcscid Il2rgtm1Wjl /SzJ) mice. The first analysis published with these data was to determine the genomic and transcriptomic features of PDX models derived after relapse that demonstrated in vivo resistance to multiple chemotherapy regimens (cross-resistance).

  Study phs003486

• ImmunoAgeing_Longitudinal

  The objective is to establish whether immunosenescence is associated with the development of clonal haematopoiesis in a healthy ageing population. This will be addressed in collaboration with the European consortium running the ImmunoAgeing project (www.immunoageing.eu). Genomic DNA derived from the peripheral blood of 394 individuals at 3-5 time-points over a 20-year period will be analysed. RNA bait pulldown (Agilent) will be used to perform targeted sequencing of genes known to be recurrently mutated in myeloid malignancies The presence, size and nature of clonal haematopoiesis will be correlated with quantitative measures of immunosenescence.

  Study EGAS00001003183

• PROMETEO

  The SOLTI-1503 PROMETEO trial was a single-arm, preoperative, window-of-opportunity phase II study conducted at four sites in Spain between December 2018 and February 2022. It enrolled female patients with operable HER2-negative breast cancer (triple-negative or Luminal B-like) and residual disease after neoadjuvant chemotherapy. Tumor biopsies were collected at five time points (baseline, post-NAC screening, C2D1, C3D1, and surgery) for translational research. This dataset includes raw paired-end RNA sequencing data (~110M reads per library) generated from the 113 biopy samples, archived in FASTQ format.

  Study EGAS50000001499

• All you need to know about the new Submitter Portal

  In September we launched new services for all EGA users, including a new version of the former Submitter Portal. Our main objective with this Portal is to transform the metadata submission in a simplified and user-friendly method. Although it is possible to find documentation about the Submitter Portal on our website, we wanted to highlight the new features in this article. Enjoy! Credentials: who needs to create a new user to access the Submitter Portal and who doesn't? Users with an old submission account (ega-box) can already access the new Submitter Portal. If it is the first time that you want to access, it is time to request a submitter role linked to the EGA User. In the form, it is mandatory to explain which type of data you want to deposit, the size of your submission, add any comment you’d like us to read, and manage the EGA Data Processing Agreement (DPA) document. This document should be checked by the legal department of your institution and signed by a person with authority to sign contracts on behalf of the institution. Note that we provide a DPA template for new Users; it can be found and downloaded in the Submitter Request section. With the DPA signed and the Submitter Request sent, it is time to wait for our Helpdesk team to validate the request. Metadata submission now can be collaborative It is possible to add collaborator(s) to your submissions. Only registered EGA Users will appear on the search bar. When adding a collaborator, it is mandatory to define the permission granted: Read only: collaborators with this permission can check if the information of the submission is correct but cannot modify anything. Read & write: collaborators with this label can register new objects and modify the registered ones. We wanted to save time for submitters that usually rely on the same collaborators. For that, we have implemented the possibility of adding the same collaborators from previous submissions; all you need to do is to search the submission, and the exact set of EGA users will have access to your submission. You can check the collaborators and their permissions at any point of the submission by going to the collaborators section. Even adding more people to complete the submission is allowed by following the same steps: looking for the EGA User and defining the permission granted (please, note that during the submission it is not possible to add collaborators from previous submissions). Use external links to complement the study information When filling the information about the study we recommend users to enrich the submission with complementary fields such as PubMeds IDs, custom tags and external links. External links are used to connect a study to an external repository. We have implemented an external link to Euro-Bioimaging for a European Project (EuCanImage). Now, we are looking forward to keeping increasing the list of external repositories! Choose the expected release date for your metadata to be searchable on our website Once all the metadata objects are registered it is time to finalise the submission so that the Helpdesk team can approve it. In the new version of the Submitter Portal users can choose the expected release date for the metadata to be searchable on the EGA website. Please, note that the selected date will have a minimum of one week margin from the day of finalisation. This time is necessary for your files to be archived and for the submission to be validated by the Helpdesk Team. Are you looking for the Array submission within the Submitter Portal? Our Submitter Portal does not support array submissions. The submission of Array-based metadata must be done using the EGA programmatic submission. You will find our Array-based format template and all the necessary information on our website, and you can find all the steps in our submission quickguide! More information about the submission process at the EGA Our Team has developed an extended documentation related to metadata submission. A good first step is to take a closer look at the Submission FAQ. To have a general overview of all the metadata submission process we recommend taking a glimpse of our take-the-tour or watching the tutorial available on our YouTube Channel. Don't miss our section on EGA Schemas, to learn more about how the EGA is built. It can be useful to fully ensure that your submissions comply with the EGA's standards and contribute to a valuable and accessible genomic resource.

  Blog new-submitter-portal

• scRNAseq dataset of circulating T cells in FL patient before and after Lenalidomide treatment

  scRNAseq dataset of circulating T cells from 3 FL patients (P011, P014 and P020) included in the GALEN clinical trial. There is two time points for each patient : One before treatment (D0) and one at day 7 of Lenalidomide treatment (D7).

  Dataset EGAD50000001529

• Delineate genomic and epigenomic changes in esophageal squamous cell carcinoma following radiotherapy

  We performed whole-exome sequencing and whole epigenome sequencing (RRBS) of samples collected from different time points during radiotherapy from thirty-four ESCC patients. We compared the genetic and epigenetic features of the different time biopsy samples to reveal the changes in ESCC received radiotherapy.

  Dataset EGAD00001003799

• NIH RECOVER: A Multi-Site Pathology Study of Post-Acute Sequelae of SARS-CoV-2 Infection

  The RECOVER tissue pathology study is a cross-sectional study designed to define and characterize the epidemiology, natural history, clinical spectrum, and underlying mechanisms of post-acute effects of SARS-CoV-2 infection in a diverse population representative of the general COVID-19 population in the US. The autopsy study will characterize the pathology of PASC in decedents who die more than 60 days after initial onset or after hospital discharge, whether in-hospital or out-of-hospital at time of death, and who meet the working definition of PASC as defined by the recent World Health Organization publication given in Section 5.4. The autopsy study will also explore the pathology of acute SARS-CoV-2 infection in a smaller subset of decedents who died between15-60 days from symptom onset. This protocol defines the common set of clinical data elements, autopsy procedures for tissue collection, core measures, pathology protocols, shared pathology tissues, data elements, and methodology. Each investigator site is expected to perform autopsies on the decedents to address the pathophysiology of the potential long-term effects of SARS-CoV-2 infection on human health. The Consortium analysis plan aims to address research questions by incorporating: 1) tissue obtained from autopsies performed at each Phase II participant's site; and 2) tissue available from other pathology investigators/autopsy sites within the Consortium.

  Study phs003768

• Genomic profiling of patient-derived xenograft models of myxoid liposarcoma either sensitive or resistant to trabectedin

  The dataset consists of two patient-derived xenograft model of myxoid liposarcoma one sensitive and one resistant to trabectedin. Both models underwent the same treatment schedule with trabectedin (tree time points and one treatment with doxorubicin). We performed genomic profiling using Agilent OneSeq assay.

  Dataset EGAD00001005099

• A Perioperative Study of Safusidenib in Patients with IDH1-Mutated Glioma

  10 participants with a radiological or pathological diagnosis of WHO Grade 2 lower-grade glioma (LGG) were recruited at a single center starting in December, 2022. Eligibility criteria permitted participants who had undergone prior surgery for WHO Grade 2 LGG, but excluded those with a history of prior radiation or chemotherapy.In Part A of the study, participants underwent an initial craniotomy with tumor biopsy and a lumbar puncture for cerebrospinal fluid (CSF) collection at study entry. Following sample collection, participants received safusidenib at the recommended phase 2 doses of 250 mg twice daily (b.i.d.) for a period of 22–36 days. This was followed by a second craniotomy for maximal safe tumor resection and a repeat lumbar puncture within 5 hours of the final pre-resection dose of safusidenib. Tumor, blood, and CSF samples were collected at both surgical time points for comprehensive translational research.Molecular analyses were performed on samples collected at both time points. These included pharmacokinetics (PK), targeted metabolomics, whole-genome sequencing (WGS) of tumor tissue, single-nucleus RNA sequencing (snRNA-seq), and DNA methylation profiling on all patients. Targeted metabolomics was conducted on samples from 9 participants, while spatial transcriptomics and spatial metabolomics were performed on tumor tissue from 3 participants each. Histone methylation profiling was conducted on samples from 8 participants.

  Study phs003976

• scRNAseq of distal colon biopsies from patients with ulcerative colitis and healthy controls

  scRNAseq dataset of colonic epithelium from distal colon biopsies from 4 patients with ulcerative colitis and 4 healthy individuals. Includes 11 samples split into three conditions: healthy, healthy margin and ulcerated. Dataset includes raw Fastq files and processed csv count matrices. Fastq files are divided into 4 lanes and into index (I1) and read (R1, R2) files. Count matrices contain comma-separated values with cell barcodes as column names and gene names as row names. Cell Ranger (v3.0.1) software from 10x Genomics was used to process the output and align the reads. The refdata-cellranger-GRCh38-3.0.0 reference was downloaded from the 10x Genomics website. First, cellranger mkfastq function was used to demultiplex raw base call files into FASTQ files. Then, the FASTQ files were aligned and filtered with cellranger count function.

  Dataset EGAD00001010167

• Sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC)

  In 2016 we established the Sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC) funded by the Ice Bucket Challenge Grant administered by the Motor Neurone Disease Research Institute of Australia. The goals of the SALSA-SGC are to collect biological samples from clinics across Australia with matched in depth clinical and self-report phenotypes and to generate multiple levels of genetic and genomic data. In this first data generation exercise of the SALSA-SGC the majority of the samples were collected prior to the formal establishment of SALSA-SGC from clinics across Australia.Briefly, the cohort includes the University of Sydney’s Australian Motor Neuron Disease DNA Bank (MND Bank) cohort recruited April 2000 to June 2011), with study protocol approved by the Sydney South West Area Health Service Human Research Ethics Committee (HREC). Cases were recruited from around Australia via state-based MND associations with diagnosis verified by a neurologist. The remainder of the cases were recruited from clinics across Australia between 2015 and 2017 under HREC approvals from Royal Brisbane and Women’s Hospital, Macquarie University Multidisciplinary Motor Neurone Disease Clinic,  Calvary Health Care Bethlehem in Melbourne , Fiona Stanley Hospital in Perth, and from 2016 under HREC approvals at each site for the sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC). The ALS cases were diagnosed with definite or probable ALS according to the revised El Escorial criteria. Some controls were recruited as either partners or friends of patients, healthy individuals free of neuromuscular diseases. We are providing GWAS and MWAS data in this dataset. Individual level GWAS data were generated using Illumina Infinium CoreExome-24 version 1.1 chips for N= 846 cases and N=665 controls. Individual MWAS data was generated using the Illumina Human methylation 450K array for N=782 cases and N=613 controls. There 1315 individuals where GWAS and MWAS data has been generated and is available. Further information on these data sets can be found: Paper 1: Restuadi, R, Garton, FC, Benyamin, B, Lin, T, et al. Amyotrophic Lateral Sclerosis Genetic Correlation with Cognitive Performance, educational attainment and schizophrenia: evidence from polygenic risk score analysis. (submitted) Paper 2: Nabais, MF, Lin, T, Benyamin, B et al. Significant out-of-sample classification from methylation profile scoring for amyotrophic lateral sclerosis. 2020. NPJ genomic medicine. 5(10). Files provided in this submission include: GWAS: This folder contains QCed genotype for the Australian ALS case-control cohort. Contains PLINK files for genotyping data (not imputed yet). The individuals selected here have: good consistency on phenotype data ethics approval registered as part of sporadic ALS studies unrelated by GRM cut-off 0.05 No ancestry QC yet MWAS: This folder contains the IDAT and post-QC normalized DNAm (beta) for the Australian ALS case-control cohort. 2019_AUS_ALS_PCTG_DNAm.tar.gz - IDATS for 1315 individuals analyzed in the MWAS study normalized_beta_values - Binary files (created with the OSCA software) containing information on the individuals, probes and the DNAm (beta) values obtained after QC phenotype_file - contains all the covariates analysed in the MWAS including: case-control status, coded 0 = Control and 1 = ALS, predicted age, predicted cell-type proportions, predicted smoking scores, slide and chip position and sex Important Notes: The DNAm data were normalized together with samples that were not part of this ALS case/control study and thus, the normalization procedure may not be 100% reproducible using only the IDAT files uploaded here. Summary data has been made publicly available and can be accessed directly: Data collection and sample processing were performed at several clinics across Australia. Genotyping and DNA methylation arrays were performed by the Human Studies Unit, at the Institute for Molecular Bioscience (University of Queensland). Quality control of the genotypic, phenotypic and DNA methylation data was done by the Program of Complex Traits Genomics, at the Institute for Molecular Bioscience (University of Queensland).

  Study phs002068

• Human four week embryo head as reference for generating an enhancer compendium for neuronal and neural crest development using neural tube organoids.

  This study has the aim of generating an enhancer code compendium of early human neuronal and neural crest development. For this purpose, we generated human neural tube organoids from single cells from two induced pluripotent stem cell lines. The organoids were subject to combined single cell multiomics at four time points of differentiation. To evaluate the biological relevance of the cell types and states obtained from the organoids, we compared with data obtained from 10XGenomics single cell multiomics on the head of a single four weeks post conception human embryo.

  Study EGAS50000001031

• B cell activation

  To investigate the gene programs involved in B cell activation and antibody switching, we profiled the gene expression at the single cell level as well as the antibody repertoire of human naive and memory B cells at resting and following three time points of activation. Through CRISPR perturbations, we defined IRF4 as a central regulator of both GC and plasma cell fates, acting independently of PRDM1 in GC commitment. Finally, leveraging machine learning classification methods trained solely on transcriptomic profiles, we accurately predicted sister cell relationships, revealing that plasma cell gene expression programs are heritable and tightly conserved within a clone.

  Study EGAS50000001468

• Premalignant SOX2 overexpression in the fallopian tubes of ovarian cancer patients: Discovery and validation studies

  To identify early driver mutations in ovarian cancer cells, we used dense whole genome sequencing of micrometastases and microscopic residual disease collected at three time points from a single patient during treatment for high-grade serous ovarian cancer (HGSOC). Laser capture microdissection of tumour islets was performed on samples prior to chemotherapy, after three cycles of chemotherapy and at recurrence. Long frament read whole genome sequencing was performed and mutations were identified. To our knowledge, this is the first longitudinal study that attempts to investigate spatial and temporal micro-heterogeneity in cancer.

  Study EGAS00001001909

• Fecal metagenomics and plasma metabolomics

  This dataset contains all fecal shotgun metagenomics and metabolomics of the study which investigated the effects of the probiotic strain Anaerobutyricum soehngenii. Shotgun data is from three different time points, baseline and two follow up. Metabolomics sets are pre and post intervention, both fasted and post prandially. Data on randomization and metformin use can be found in the analysis.

  Dataset EGAD50000000608

• UK renal cancer samples genotyped on Illumina OmniExpress BeadChip

  Renal cell carcinoma (RCC) cases comprised adult patients with histologically proven RCC were collected through two sources within the UK. First, 856 cases from SORCE, a MRC collection of surgically treated RCC cases ascertained through UK clinical oncology centres. Second, 189 RCC cases collected through the ICR and Royal Marsden NHS Hospitals Trust. Cases included 590 clear cell carcinomas (CCCs), 42 papillary carcinomas (PCs), 33 chromophobe carcinomas (CCs) and 19 mixed or other histological subtypes. DNA was extracted from EDTA-venous blood samples using the conventional methods and quantified using PicoGreen (Invitrogen). Cases were genotyped using the Human OmniExpress-12 BeadChip according to the manufacturer's recommendations (Illumina Inc, San Diego, CA, USA). After strict QC, 944 cases were retained. Data provided in plink format. Controls used were data from the Wellcome Trust Case Control Consortium 2 (WTCCC2) 1958 birth cohort and the UK Blood Service Control Group (available as EGAS00000000028).

  Study EGAS00001002336

• Glioblastoma epigenome profiling identifies SOX10 as a master regulator of molecular tumour subtype

  Glioblastoma in adult patients are classified into four subtypes, IDH, MES, RTK I, and RTK II, based on DNA methylation and RNA expression data. Tumour subtype transitions commonly occur during the treatment of glioblastoma patients, and transitions to the mesenchymal (MES) subtype have been associated with therapy resistance and adverse prognosis. Here, we generate DNA methylome and histone modification data of glioblastoma primary tumours and show that glioblastoma subtypes differ by their enhancer landscapes. Using Core Regulatory Circuitry analysis of H3K27ac data, and independent analysis of RNA-derived gene regulatory networks, we identified 38 subtype master regulators whose cell type-specific activities we mapped in single-cell RNA sequencing data. These analyses identified the chromatin modifier SRY-Box 10 (SOX10) as a master regulator in tumours of the RTK I subtype. In functional studies we demonstrate that SOX10 loss causes a transition of RTK I tumour cells to a mesenchymal cellular state by altering the accessibility of enhancer-rich chromatin regions and their occupancy by Bromodomain Containing 4 (BRD4), a dynamic constituent of super-enhancers. Treatment with the BRD4 inhibitor JQ1 blocked this transition. These data demonstrate the fundamental role of enhancer chromatin remodelling and master regulator activity in the establishment, maintenance and plasticity of glioblastoma cellular states. We also make our data publically browsable at https://dkfz-b060.github.io/gb_browse/

  Study EGAS00001003953

• Genomic and Phenotypic Profile of Sickle Cell Disease in Human Population in Cameroon

  Sickle cell disease (SCD) is caused by a biallelic single nucleotide substitution in the beta-globin gene (HBB), resulting in an amino acid substitution, Glu7Val, formerly known as Glu6Val. An estimated 300,000 babies with SCD are born worldwide each year, with nearly 75% of these births being in sub-Saharan Africa. In Africa, at least 30-50% of children with untreated SCD die before the age of 5 years. Therefore, accelerating the path for novel therapies for SCD through genomics research on fetal hemoglobin (HbF) is critical. Variants in the currently known HbF‐modulating genes/loci, i.e., BCL11A, HBS1L-MYB, and XmnI-HBG2, explain only 10-20% of the variation of HbF levels in African individuals with SCD, compared with nearly 50% of the variation in HbF levels among Europeans. Expanding genomic research in populations of African ancestry could uncover the missing heritability of HbF-promoting loci. This study used the Human Heredity and Health (H3Africa) consortium SNP genotyping array developed from whole genome enriched for common variants in sub-Saharan Africans to investigate genomic variations associated with HbF levels in individuals with sickle cell anemia of the HbSS genotype from Cameroon. Two of the previously described loci, BCL11A and HBS1L-MYB were replicated, while a novel locus on chromosome 13 mapping to FLT1 was uncovered. The study therefore opens up a novel avenue for exploring SCD gene therapy.

  Study phs003748

• Genomics of Blastic Plasmacytoid Dendritic Cell Neoplasm

  The goal of this study was to understand the genetic evolution and tumor phylogeny of blastic plasmacytoid dendritic cell neoplasm (BPDCN). BPDCN can present in patients with skin tumors of leukemia cells and no bone marrow or blood involvement, or alternatively, with both skin tumors and blood/bone marrow leukemia cells at the time of diagnosis. Here, we performed longitudinal sampling of tissues from patients with BPDCN, including both skin tumors and bone marrow, and in some cases serially at different time points through the course of diagnosis and treatment. These were studied by whole exome or whole genome DNA sequencing, comparing tumor samples to matched normal samples.

  Study phs003228

• Neutrophils infected with Leishmania donovani

  In the context of studying visceral leishmaniasis, neutrophils infected with Leishmania donovani have been compared to uninfected neutrophils. Compared time points are 0, 6 and 24 hours post infection. Neutrophils of three human donors have been used. Overall 6 samples for infected neutrophils at time point 6 hours and 6 samples for infected neutrophils at time point 24 hours exist, including three biological samples and two technical samples. Uninfected neutrophils represent 3 samples at time point 0 hours, 3 samples at time point 6 hours and 3 samples at time point 24 hours. Transcriptome of Leishmania donovani culture has been assessed in two replicates.

  Study EGAS00001004912

• Exome sequencing data from two small cell prostate cancer patients

  Exome sequencing data from two small cell prostate cancer patients - 4 cancer samples (FFPE) from Patient 1 collected at 3 different time points and 2 cancer samples (FFPE) from Patient 2 collected at 1 time point. Exonic DNA was enriched using the TruSeq Exome Kit (Illumina) and sequenced on the Illumina NextSeq 500 as 75bp paired end reads (total read length 150bp).

  Dataset EGAD00001011149

• Bulk RNA sequencing data of high-grade serous ovarian cancer samples (set 18-19)

  The dataset contains RNA sequencing data of 66 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 155 samples are fresh frozen tissue samples that have been collected from different tissues and time points before and during treatment. The files provided are paired fastq files.

  Dataset EGAD50000002370

• WGBS of CD14 monocytes dataset of covid19 patients from Quebec, Canada

  this dataset contains the raw data generated for CD14 monocytes WGBSof 7 covid19 hospitalized patients sampled at various time points (Admission, Day 5 and Day 15) in total 15 biospecimen are available. WGBS libraries have been sequenced on Illumina NovaSeq 6000.

  Dataset EGAD00001008718

• Exome and RNA-sequencing data from a relapsed t(1;19) acute lymphoblastic leukemia

  Sequence data is from 4 samples from an adult patient with TCF3-PBX1 t(1;19)-positive acute lymphoblastic leukemia. Exome sequencing was performed on a skin biopsy (normal tissue control) and leukemic bone marrow biopsies taken at diagnosis and at two relapse time points. RNA-sequence data is from leukemic bone marrow from two relapse biopsies.

  Dataset EGAD00001002203

• Diseased heart analysis: RNA Adult (2025-10-14)

  Samples for this project are taken from adult human hearts which have been preserved using 2 different methods (cold static storage on ice, and hypothermic perfusion). Samples have been acquired at various time points during post-preservation normothermic perfusion. The aim of the project is to assess the transcriptional changes caused by these differing methods of preservation. . This dataset contains all the data available for this study on 2025-10-14.

  Dataset EGAD00001015738

• Peripheral blood DNA methylome in adalimumab-treated patients with rheumatoid arthritis

  Background and aims Rheumatoid arthritis (RA) patients are currently treated with biological agents mostly aimed at cytokine blockade such as anti-TNFα therapy. Currently, there are no biomarkers to predict therapy response to these agents. Here, we aimed to predict response to adalimumab (ADA) treatment in RA patients using DNA methylation in peripheral blood Methods DNA methylation profiling on whole peripheral blood from 92 RA patients before the start of adalimumab (ADA) was determined using Illumina HumanMethylationEPIC BeadChip Array. After 6 months, treatment response was assessed according to the Alliance of Associations for Rheumatology (EULAR) criteria for disease response. Patients were classified as responders (DAS28<3.2 or decrease of 1.2 points) or as non-responders (DAS28>5.1 or decrease of less than 0.6 points). Machine learning models were built with gradient boosting and stability selection models to predict response prior to ADA treatment with predictor DNA methylation markers. Results We demonstrated a 27-feature panel of DNA methylation markers or CpG classifiers that predict response in RA patients treated with ADA. Forty-nine patients were assigned as responder and 43 patients assigned as non-responders. We differentiate responders from non-responders with a high sensitivity (AUC 0.76). The predictor CpGs annotated to genes involved in immunological- and pathophysiological pathways related to RA such as T-cell signaling, B-cell pathology and angiogenesis. Conclusion Our findings indicate that DNA methylation signatures discriminate responders and non-responders to ADA treatment and can serve as a tool for therapy prediction.

  Study EGAS00001007578

• Geriatric Oncology Database of genotypes and methylation, gene expression, clinical data, and survey results on psychosocial and physical conditions in Japanese elderly cancer patients to establish truly effective treatment strategy

  Owing to the advent of super-aged society, cancer mortality in Japan is forecasted to become an all-time high. The management of elderly patients with cancer is a serious health issue and the need for specific care guidelines for this population is critical in Japan. The significant individual differences in comorbidity, physical and mental functioning, and social problems among aging individuals are obstacles to the progress. The response to cancer treatment varies significantly among patients, even in the same stage of the same type of cancer. Older aged patients are still less likely to be offered participation in clinical trials, thus the number of clinical evidences is limited. The molecular mechanisms regulating the physiological process of ageing and senescence, and cancer are far from understood. To establish a truly effective treatment algorithm, we attempted to develop a geriatric oncology database for genotypes and methylation, gene expression, clinical data, and survey results on psychosocial and physical conditions in Japanese elderly cancer patients in this retrospective study. The genomic analysis was performed in 62, 106, and 173 cases, respectively for gastric, colon and lung cancers. The clinical data and survey results on psychosocial and physical conditions were collected from 166, 313, and 344 patients respectively for gastric, colon and lung cancers, and also collected from 357, 49, and 300 benign cases respectively for cardiovascular disorder, respiratory dysfunction, diabetes and nephropathy as the analysis control.

  Study JGAS000061

• Atypical 3q26/MECOM rearrangements genocopy inv(3)/t(3;3) in acute myeloid leukemia

  Acute myeloid leukemia (AML) with inv(3)/t(3;3)(q21q26) is a distinct WHO recognized entity, characterized by its aggressive course and poor prognosis. In this subtype of AML, the translocation of a GATA2 enhancer (3q21) to MECOM (3q26) results in overexpression of the MECOM isoform EVI1 and monoallelic expression of GATA2 from the unaffected allele. The full-length MECOM transcript, MDS1-EVI1, is not expressed as the result of the 3q26 rearrangement. Besides the classical inv(3)/t(3;3), a number of other 3q26/MECOM rearrangements with poor treatment response have been reported in AML. Here we demonstrate, in a group of 33 AML patients with atypical 3q26 rearrangements, MECOM involvement with EVI1 overexpression, but no or low MDS1-EVI1 levels. Moreover, the 3q26 translocations in these AML patients often involve super-enhancers of genes active in myeloid development (e.g. CD164, PROM1, CDK6 or MYC). In more than 50% of these cases allele specific GATA2 expression was observed, either by copy number loss or by an unexplained allelic imbalance. Altogether, atypical 3q26 recapitulate the main leukemic mechanism of inv(3)/t(3;3) AML, namely EVI1 overexpression driven by enhancer hijacking, absent MDS1-EVI1 expression and potential GATA2 involvement. Therefore, we conclude that both atypical 3q26/MECOM and inv(3)/t(3;3) can be classified as a single entity of 3q26-rearranged AMLs. Routine analyses determining MECOM rearrangements, EVI1 and MDS1-EVI1 expression are required to recognize 3q-rearranged AML cases.

  Study EGAS00001004325

• Neurogenetic Investigations of Obsessive-Compulsive Disorder

  Obsessive-compulsive disorder (OCD) is a disabling early-onset neuropsychiatric disorder with a clear genetic contribution to risk but unclear underlying pathophysiology, which has hindered the development of new treatments and interventions. This study uses high-throughput sequencing approaches to identify OCD risk genes, detect gene expression differences in OCD, and determine epigenetic signatures driving gene expression in OCD brain. These studies will improve our understanding of the underlying mechanisms of OCD and identify points of traction for mechanistic studies in model systems, ultimately leading to novel therapeutics, and reducing the significant morbidity and mortality associated with this disabling illness. Furthermore, insights gained in these studies can inform gene discovery approaches to other complex neuropsychiatric disorders.

  Study phs001929

• Neoadjuvant chemotherapy alters the genomic landscape and immune microenvironment of breast cancers

  To characterize the effects of neoadjuvant chemotherapy (NAC) on the genome, transcriptome and tumor infiltrating leukocytes (TILs), we have conducted whole exome and whole transcriptome sequencing of a comprehensive, longitudinal breast cancer cohort consisting of 146 cases and 281 paired tumor samples. In total, 52 (38%) patients achieved pathologic complete response (pCR) while 85 patients (62%) had residual disease with standard chemotherapy regimen. Tumor biopsies were collected for each patient at three time points – pre-treatment, three weeks after the first cycle of anthracycline and cyclophosphamide (AC) and at the time of surgery after 3 more cycles of AC followed by 4 cycles of taxane or taxane plus Herceptin in case of HER2+ subtype.

  Study EGAS00001003354

• Integrated single-cell profiling dissects cell-state-specific enhancer landscapes of human tumor infiltrating T cells.

  Despite extensive studies on the chromatin landscape of exhausted T cells, the transcriptional wiring underlying functional and dysfunctional states of human tumor infiltrating lymphocytes (TILs) is incompletely understood. Here, we identify tissue-specific and general gene-regulatory landscapes in the wide breadth of CD8+ TIL functional states covering four cancer entities using single-cell chromatin profiling. We map enhancer-promoter interactions in human TILs by integrating single-cell chromatin accessibility with single-cell RNA-seq data from tumor entity-matching samples and prioritize key elements by super enhancer analysis. Our analysis reveals a human core chromatin trajectory to TIL dysfunction and identifies key enhancers, transcriptional regulators, and deregulated target genes involved in this process. Finally, we validate enhancer regulation at loci encoding PD1, TCF1, and TIM3 by targeting non-coding regulatory elements with potent CRISPR activators and repressors. In summary, our study advances the understanding of molecular regulation of TIL (dys-)function and provides a framework for modulating immunotherapeutic relevant TIL genes via their enhancers.

  Dataset EGAD00001008662

• Genetic analysis of Hirschsprung disease

  Hirschsprung disease (HSCR) is a birth defect resulting from the absence of nerve (ganglion) cells in the gastrointestinal tract. Hirschsprung disease has a population incidence of 1/5,000 live births and most often occurs as an isolated condition. However, approximately 30% of HSCR cases are associated with other birth defects such as Down syndrome, deafness, hypopigmentation, and Congenital Central Hypoventilation syndrome (CCHS). Hirschsprung disease is a genetic condition with autosomal dominant, autosomal recessive, and multigenic patterns of inheritance described. The goal of the research study is to identify genes harboring causative HSCR mutations and to better understand the complex inheritance of HSCR in families using whole genome mapping and sequencing studies with functional follow-up of candidate genes and variants. We intend to ascertain the frequency with which mutations in any human gene lead to familial and isolated forms of HSCR. Clinical information is collected to allow investigation of possible genotype - phenotype correlations. The subject population consists of individuals diagnosed with HSCR and their unaffected relatives. Individuals/families are ascertained through support groups, web-based listings of research studies and genetic testing services, an educational study website, and referrals from genetic counselors and physicians. Blood, or tissue, samples are requested from affected individuals and their unaffected relatives.

  Study phs000497