Search Results - EGA European Genome-Phenome Archive

Botensilimab, an Fc-enhanced Anti-CTLA-4 Antibody, is Effective Against Tumors Poorly Responsive to Conventional Immunotherapy

This study explores the genomic landscape associated with a novel Fc-engineered anti-CTLA-4 antibody (botensilimab) in advanced solid tumors. We seek to understand if enhancing the Fc-region affinity of anti-CTLA-4 antibodies can improve anti-tumor efficacy and expand clinical benefit to tumors poorly responsive to conventional immunotherapy. As part of an ongoing open-label, Phase 1, multicenter study, we conducted an exploratory sub-analysis of genomics data. The primary study evaluates the safety, tolerability, pharmacokinetics, and pharmacodynamics of botensilimab monotherapy and in combination with an anti-PD-1 antibody (balstilimab) in participants with advanced solid tumors. RNA from formalin-fixed paraffin-embedded (FFPE) tumor biopsies and matched normal blood samples were isolated and subjected to RNA-sequencing using the Personalis ImmunoID NeXT Platform. We demonstrated that anti-CTLA-4 engineered for enhanced FcγR affinity leverages FcγR-dependent mechanisms to potentiate T cell responsiveness, reduce intratumoral Tregs, and enhance antigen presenting cell activation. This genomic analysis contributes to our understanding of the molecular mechanisms underlying patient responses to Fc-engineered anti-CTLA-4 therapy and may inform future strategies to expand the clinical benefit of immune checkpoint blockade in cancer immunotherapy.

Study phs003704

Fgl2 Regulates FcγRIIB+ CD8+ T Cell Responses during Infection

While the inhibitory receptor FcγRIIB has been shown to be upregulated on activated CD8+ T cells in both mice and humans, its impact on T cell fate during infection has not been fully elucidated. We identified an increase in FcγRIIB-expressing CD8+ T cells in COVID patients relative to healthy controls, and in mouse models of viral infection. Despite its well-known role as an Fc receptor, FcγRIIB also ligates the immunosuppressive cytokine Fgl2, resulting in CD8+ T cell apoptosis. Both chronic LCMV infection in mice and COVID in humans resulted in a significant increase in plasma Fgl2. Further, plasma Fgl2 was directly proportional to CD8+ T cell lymphopenia in COVID patients. To further understand the association of Fgl2 and CD8+ T cell lymphopenia following COVID infection, we assessed the transcriptomic profiles of PBMCs with high (≥ 9.153 ng/ml) vs low (defined as

Study phs003870

Data Access Committee KCL FC

Dac EGAC00001000386

High titers and low fucosylation of early phase anti-SARS-CoV-2 IgG promote hyper-inflammation by alveolar macrophages

We show that early phase anti-Spike IgG in serum of critically ill COVID-19 patients induces hyper-inflammatory responses by human alveolar macrophages. We identified that this excessive inflammatory response is dependent on two antibody features that are specific for severe COVID-19. First, inflammation is driven by high titers of anti-Spike IgG, a hallmark of severe disease. Second, we found that anti-Spike IgG from severely ill patients is intrinsically more pro-inflammatory because of different glycosylation of the Fc tail, particularly by low fucosylation. This dataset is linked with the following ArrayExpress Experiment: E-MTAB-10431 - 2020_COVID19_FCGR_MIL10_IgGfucosylation

Study EGAS00001005206

MCF10A 12h IL6 classical signaling

Gene expression after cell culture, 12h IL6+sgp130-Fc stimulated

Dataset EGAD00010001970

MCF10A 24h IL6 classical signaling

Gene expression after cell culture, 24h IL6+sgp130-Fc stimulated

Dataset EGAD00010001963

Anti-TIGIT antibody tiragolumab improves PD-L1 blockade via myeloid and Treg cells

Tiragolumab, an anti-TIGIT antibody with an active IgG1/kappa Fc, demonstrated improved outcomes in the phase 2 CITYSCAPE trial (NCT03563716) when combined with atezolizumab (anti-PD-L1) versus atezolizumab alone1. However, there remains little consensus on the mechanism(s) of response with this combination2. We found that high baseline intratumoral macrophages and Tregs were associated with better outcomes in patients treated with atezolizumab plus tiragolumab but not with atezolizumab alone. Serum sample analysis revealed that macrophage activation was associated with clinical benefit in patients receiving the combination treatment. In mouse tumor models, tiragolumab surrogate antibodies inflamed tumor-associated macrophages, monocytes, and dendritic cells through Fc gamma receptors (FcɣR), in turn driving anti-tumor CD8+ T cells from an exhausted effector-like state to a more memory-like one. These results uncover a mechanism of action by which TIGIT checkpoint inhibitors can remodel immunosuppressive tumor microenvironments, and suggest that FcɣR engagement is an important consideration in anti-TIGIT antibody development.

Study EGAS50000000251

Characterization of a human iPSC-derived endocrine pancreas model

Directed differentiation of stem cells offers a scalable solution to the need for human cell models recapitulating islet biology and T2D pathogenesis. We profiled mRNA expression at six stages of an induced pluripotent stem cell (iPSC) model of endocrine pancreas development from two donors, and characterized the distinct transcriptomic profiles associated with each stage. Established regulators of endodermal lineage commitment, such as SOX17 (log2 fold change [FC] compared to iPSCs=14.2, p-value=4.9x10-5) and the pancreatic agenesis gene GATA6 (log2 FC=12.1, p-value=8.6x10-5), showed transcriptional variation consistent with their known developmental roles. However, these analyses highlighted many other genes with stage-specific expression patterns, some of which may be novel drivers or markers of islet development. For example, the leptin receptor gene, LEPR, was most highly expressed in published data from in vivo-matured cells compared to our endocrine pancreas-like cells (log2 FC=5.5, p-value=2.0x10-12), suggesting a role for the leptin pathway in the maturation process. Endocrine pancreas-like cells showed significant stage-selective expression of adult islet genes, including INS, ABCC8, and GLP1R, and enrichment of relevant GO-terms (e.g. "insulin secretion"; odds ratio=4.2, p-value=1.9x10-3): however, principal component analysis indicated that in vitro-differentiated cells were more immature than adult islets. Integration of the stage-specific expression information with genetic data from T2D genome-wide association studies revealed that 46 of 82 T2D-associated loci harbor genes present in at least one developmental stage, facilitating refinement of potential effector transcripts. Together, these data show that expression profiling in an iPSC islet development model can further understanding of islet biology and T2D pathogenesis.

Study EGAS00001001803

Expression profiling of a human endocrine pancreas iPSC model

Directed differentiation of stem cells offers a scalable solution to the need for human cell models recapitulating islet biology and T2D pathogenesis. We profiled mRNA expression at six stages of an induced pluripotent stem cell (iPSC) model of endocrine pancreas development from two donors, and characterized the distinct transcriptomic profiles associated with each stage. Established regulators of endodermal lineage commitment, such as SOX17 (log2 fold change [FC] compared to iPSCs=14.2, p-value=4.9x10-5) and the pancreatic agenesis gene GATA6 (log2 FC=12.1, p-value=8.6x10-5), showed transcriptional variation consistent with their known developmental roles. However, these analyses highlighted many other genes with stage-specific expression patterns, some of which may be novel drivers or markers of islet development. For example, the leptin receptor gene, LEPR, was most highly expressed in published data from in vivo-matured cells compared to the endocrine pancreas-like cells (log2 FC=5.5, p-value=2.0x10-12), suggesting a role for the leptin pathway in the maturation process. Endocrine pancreas-like cells showed significant stage-selective expression of adult islet genes, including INS, ABCC8, and GLP1R, and enrichment of relevant GO-terms (e.g. “insulin secretion”; odds ratio=4.2, p-value=1.9x10-3): however, principal component analysis indicated that in vitro-differentiated cells were more immature than adult islets. Integration of the stage-specific expression information with genetic data from T2D genome-wide association studies revealed that 46 of 82 T2D-associated loci harbor genes present in at least one developmental stage, facilitating refinement of potential effector transcripts. Together, these data show that expression profiling in an iPSC islet development model can further understanding of islet biology and T2D pathogenesis.

Dataset EGAD00001002148

A Dose Escalation Study of Efmarodocokin Alfa (UTTR1147A) in Healthy Volunteers and Patients with Ulcerative Colitis

Background: The interleukin-22 cytokine (IL-22) has demonstrated efficacy in nonclinical colitis models with a non-immunosuppressive mechanism-of-action. Efmarodocokin alfa (UTTR1147A) is a fusion protein agonist that links IL-22 to the crystallizable fragment (Fc) of human immunoglobulin (IgG4) for improved pharmacokinetic characteristics, but with a mutation to minimize Fc effector functions. Methods: This randomized, phase 1b study evaluated the safety, tolerability, pharmacokinetics, and pharmacodynamics of repeat intravenous dosing of efmarodocokin alfa in healthy volunteers (HVs; n=32) and patients with ulcerative colitis (UC; n=24) at 30–90 µg/kg doses given biweekly (Q2W) or monthly (Q4W) (6:2 active:placebo per cohort). Results: The most common adverse events (AEs) were on-target dermatological effects (dry skin, erythema, and pruritus) that were reversible. Dose-limiting non-serious dermatological AEs (severe dry skin, erythema, exfoliation, and discomfort) were seen in two HVs and one patient at 90 ug/kg Q2W. Pharmacokinetics were generally dose-proportional across the dose levels tested, but patients demonstrated lower drug exposures relative to HVs at the same dose. IL-22 serum biomarkers and IL-22 responsive genes in colon biopsies were induced with active treatment. Patients demonstrated changes in microbiota composition following active treatment, thereby reversing baseline dysbiosis. Clinical response was observed in 7/18 active- and 1/6 placebo-treated patients; clinical remission was observed in 5/18 active- and 0/6 placebo-treated patients.

Study EGAS00001006172

Whole exome sequencing of endometriod ovarian cancer tumours

Whole Exome sequencing data of tumour samples for 112 patients with endometrioid ovarian carcinoma in FASTQ format. Data was derived as summarized below: Library Preparation: Libraries were prepared from each DNA sample using the Illumina TruSeq Exome Library Prep kit (#FC-150-1002) according to the provided protocol using modifications for working with FFPE sourced material. Libraries were quantified using the Qubit 2.0 Fluorometer and the Qubit DNA HS assay (#Q32854) and the size distribution of fragments was assessed using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Library QC: Exome-captured sequencing library pools were quantified using the Qubit 2.0 Fluorometer and the Qubit DNA HS assay (#Q32854) and the size distribution of fragments was assessed using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Fragment size and quantity measurements were used to calculate molarity for each library pool. Sequencing: Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC-404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002).

Dataset EGAD00001006389

Ribo-depleted RNA-sequencing of II.3, III.1, and III.3

This datasets contains the Ribo-depleted RNA-sequencing of patients II.3, III.1, and III.3. Libraries were sequenced to a minimum depth of 195 million read pairs (2x75nts) on an Illumina NextSeq500 Midoutput FC.

Dataset EGAD50000002364

Characterizing the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft model for RNA-based liquid biopsy in a preclinical setting

This study explores the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft (PDTX) model. Blood plasma samples (n=171) derived from a DLBCL PDTX model including 27 humanized (HIS) PDTX, 8 HIS non-PDTX and 21 non-HIS PDTX NOD-scid IL2Rgnull mice were collected during humanization, xenografting, treatment, and sacrifice. The mice were treated with either R-CHOP, huCD20-Fc-AFN-CHOP, or phosphate-buffered saline (PBS). RNA was extracted using the miRNeasy serum/plasma kit and sequenced on the NovaSeq 6000 platform using the SMARTer Stranded Total RNA-seq pico v3 kit.

Study EGAS50000000566

Phenotype information

This study explores the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft (PDTX) model. Blood plasma samples (n=171) derived from a DLBCL PDTX model in-cluding 27 humanized (HIS) PDTX, 8 HIS non-PDTX and 21 non-HIS PDTX non-obese diabetic (NOD)-scid IL2Rgnull (NSG) mice were collected during humanization, xenografting, treatment, and sacrifice. The mice were treated with either rituximab, cyclophosphamide, doxorubicin, vincris-tine, and prednisone (R-CHOP), CD20-targeted human IFNα2-based AcTaferon combined with CHOP (huCD20-Fc-AFN-CHOP), or phosphate-buffered saline (PBS). RNA was extracted using the miRNeasy serum/plasma kit and sequenced on the NovaSeq 6000 platform using the using the SMARTer Stranded Total RNA-Seq Kit v3.

Dataset EGAD50000000806

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

Molecular Genetics of Schizophrenia - nonGAIN Sample (MGS_nonGAIN)

This study is part of the Molecular Genetics of Schizophrenia (MGS) genome wide association study (GWAS) of 3,972 cases (2,686 EA and 1,286 AA) and 3,629 controls (2,656 EA and 973 AA) (analyzed sample remaining after quality control exclusions), comprised of European ancestry (EA) and African American (AA) samples. We genotyped about half of the EA sample and almost all of the AA sample under the auspices of the Genetic Association Information Network (GAIN) with the Affymetrix 6.0 platform at the Broad Institute. The remainder of the included sample was also genotyped with the Affymetrix 6.0 platform at the Broad Institute, and we refer to this component as the nonGAIN sample. Cases met criteria for schizophrenia (SCZ) or schizoaffective disorder (SA) per the Diagnostic and Statistical Manual of Mental Disorders version IV (DSM-IV) for all three collections (SGI, MGS1, and MGS2) comprising these cases. However, for the older SGI collection, codes for the secondary diagnoses refer to the older DSM-III-R version. Controls were screened briefly and excluded if they endorsed a history of these illnesses.

Study phs000167

Whole Genome Association Study of Bipolar Disorder

The goal of the project is to identify genes that make individuals more susceptible to bipolar disorder (manic depressive illness) and to better understand the brain pathways involved in the disease. Dataset versioning Version 1: European-American (EA) ancestry only Version 2: Version 1 plus African-American (AA) ancestry Version 3: EA and AA samples plus updated diagnostic criteria Consent groups and participant set General research use (GRU): 1767 controls (1081 EA controls, 686 AA controls) This consent group includes all controls for the Bipolar study, which are a subset of controls for the Schizophrenia study (subset of Schizophrenia: GRU). Bipolar and related disorders (BARD): 841 cases (691 EA cases, 150 AA cases) This consent group includes a subset of the Bipolar cases. Bipolar disorder only (BDO): 653 cases (388 EA cases, 265 AA cases) This consent group includes a subset of the Bipolar cases.

Study phs000017

Barrett's and Esophageal Adenocarcinoma Genetic Susceptibility Study (BEAGESS)

BEAGESS is a genome-wide association study (GWAS) which takes advantage of the extensive data collected by investigators in the Barrett's and Esophageal Adenocarcinoma Consortium (BEACON, http://beacon.tlvnet.net), representing many of the high-quality population-based and other epidemiologic studies of BE and EA in the world. The overall goal of our research is to evaluate the influence of genetic susceptibility on risk of EA and its main precancerous condition, BE. The primary aims of the study are to identify tagSNPs most strongly associated with risk of esophageal adenocarcinoma (EA) and Barrett's esophagus (BE). In the secondary aims we will evaluate the extent to which the most significant associations vary according to key environmental and host factors for these conditions, including gender, obesity and cigarette smoking. These results will guide additional exploratory analyses examining ways in which individual SNP results might be aggregated to shed light in the importance of specific pathways relevant to the etiology of BE and EA, and to identify possible epistatic effects.

Study phs000869

MicroRNAs, Hypertension and End Organ Damage in Humans

Study 1) Profiling of microRNAs in plasma of patients with hypertension complicated or not by metabolic syndrome or chronic kidney disease Hypertension (HTN) or high blood pressure is associated with subclinical target organ damage such as cardiac, vascular and kidney injury, which may lead to complications and death. In this study, we investigated circulating microRNAs as biomarkers of target organ damage in HTN patients. We profiled circulating microRNAs by RNA sequencing in platelet-poor plasma of normotensive subjects and patients with HTN complicated or not by metabolic syndrome (MetS) or chronic kidney disease (CKD) (n=15 each group). Differentially expressed microRNAs were identified with a threshold of false discovery rate <0.1. Differentially expressed microRNAs were identified uniquely to associate with HTN (8), MetS (1) or CKD (13), and 8 were similarly differentially expressed in different groups. This study identified the association of differentially expressed circulating microRNAs with target organ damage in HTN patients, which could have some pathophysiological and therapeutic implications. Study 2) Profiling of microRNAs in gluteal subcutaneous small arteries of patients with hypertension complicated or not by chronic kidney disease Hypertension (HTN) is associated with vascular damage characterized by endothelial dysfunction and vascular remodeling and stiffening, which contributes to kidney injury leading to chronic kidney disease (CKD). MicroRNAs are short non-coding RNAs which repress/degrade target mRNAs. The microRNA role in vascular injury in HTN remains unclear. In this study, we aimed to identify differentially expressed microRNAs in small arteries of patients with HTN associated or not with CKD, in order to shed light on the pathophysiological molecular mechanisms. Normotensive subjects and HTN patients associated or not with CKD grades 3-4 were studied (n=15-16). Small arteries were isolated from subcutaneous gluteal biopsies, RNAs were extracted, and small and total RNA sequencing was performed by Illumina HiSeq-2500. Differentially expressed genes were identified with a P<0.05 and fold change (FC) >1.3. Differentially expressed microRNAs and mRNAs were identified uniquely to associate with HTN (microRNAs: 10, mRNAs: 68), CKD (microRNAs: 68, mRNAs: 395), and both groups (microRNAs: 2, mRNAs: 32). This study identified differentially expressed microRNAs and mRNAs in small arteries with target organ damage in HTN, which could have some pathophysiological and therapeutic implications.

Study phs002389

Integrating molecular imaging and transcriptomic profiling in advanced HER2-positive breast cancer receiving trastuzumab emtansine (T-DM1): an analysis of the ZEPHIR clinical trial

Purpose: The ZEPHIR clinical trial evaluated the role of [89Zr]trastuzumab-PET/CT (HER2-PET/CT) and 2-[18F]fluoro-2-deoxy-D-glucose PET/CT ([18F]FDG-PET/CT) in predicting outcomes in patients with advanced HER2-positive breast cancer treated with trastuzumab emtansine (T-DM1). Here, we combined molecular/metabolic imaging and transcriptomic data to investigate the biological processes associated with [89Zr]trastuzumab and [18F]FDG uptake, and to dissect the mechanisms involved in T-DM1 resistance. Experimental design: RNA was extracted from metastasis biopsies obtained at study inclusion in the ZEPHIR trial. HER2-PET/CT and [18F]FDG-PET/CT imaging data of biopsied lesions were integrated with RNA sequencing data. Lesions were compared based on the level of [89Zr]trastuzumab uptake (dichotomized into high/low classes) as well as on the presence/absence of metabolic response, defined comparing baseline and on-treatment [18F]FDG-PET/CT. Results: We analyzed matched transcriptomic and molecular/metabolic imaging data for 24 metastases (one lesion/patient). Pathways involved in extracellular matrix (ECM) organization, glycosylphosphatidylinositol synthesis, and collagen formation were enriched in lesions presenting low [89Zr]trastuzumab uptake. [18F]FDG uptake at baseline correlated with proliferation and immune-related processes. Hypoxia and ECM-related processes were enriched in lesions that showed no metabolic response to T-DM1. Interestingly, immune-related processes (e.g., Fc gamma receptor activation, complement cascade) were associated with high [89Zr]trastuzumab uptake and metabolic response. Conclusions: To our knowledge, this study represents the first correlative analysis between [89Zr]trastuzumab tumor uptake and gene expression profiling in humans. Our findings point toward a role of ECM in impairing [89Zr]trastuzumab tumor uptake and T-DM1 metabolic response in advanced HER2-positive breast cancer, and highlight the potential of molecular imaging to depict tumor microenvironment features.

Study EGAS50000000470

Foregut Microbiome in Development of Esophageal Adenocarcinoma

The distal esophagus is an important anatomical area where gastric acid reflux can cause reflux esophagitis (RE), Barrett's esophagus (BE) (intestinal metaplasia), and esophageal adenocarcinoma (EA). The incidence of EA has increased 6-fold in the U.S. since the 1970s, parallel to a significant increase in the prevalence of gastroesophageal reflux diseases (GERD). Although specific host factors might predispose one to disease risk, such a rapid increase in incidence must be predominantly environmental. The cause remains unknown. Our hypothesis is that changes in the foregut microbiome are associated with EA and its precursors, RE and BE in the GERD sequence. We will conduct a case control study to characterize the microbiome in every stage of the GERD sequence as well as analyze the trend in changes in the microbiome along disease progression toward EA. Specific Aim 1. To conduct a comprehensive population survey of the foregut microbiome and demonstrate its association with GERD sequence, by a 16S rRNA gene survey. We will analyze samples of the foregut microbiome at three anatomic loci: mouth, distal esophagus, and gastric corpus. Changes of the microbiota in the distal esophagus will be correlated with the phenotypes. Spatial relationship between the esophageal microbiota and upstream (mouth) and downstream (stomach) foregut microbiotas as well as temporal stability of the microbiome-disease association will also be examined. Specific Aim 2. To define distal esophageal metagenome and demonstrate its association with GERD sequence, by shotgun metagenomic analysis. We will first classify samples of the metagenome into metagenotypes by between-sample k-mer distance and correlate the metagenotypes with the four phenotypes. Subsequent detailed analyses will include pathway-disease and gene-disease associations. DNA viruses and fungi, if identified, also will be correlated with the phenotypes. A significant association between the foregut microbiome composition and GERD sequence, if demonstrated, will be the first step for eventually testing the causal hypothesis that an abnormal microbiome is required for the development of the sequence of phenotypic changes toward EA. If EA and its precursors represent a microbial ecological disease, treating the cause of GERD might become possible, for example, by normalizing the microbiome through use of antibiotics, probiotics, or prebiotics. Causative therapy for GERD could prevent its progression and reverse the current trend of increasing incidence of EA.

Study phs000260

Somatic Mutations and Their Etiological Determinants for Breast Cancer in African American Women (B-CAUSE Study)

The breast cancer health disparity between women of African ancestry (AA) and European ancestry (EA) remains a major public health challenge in the United States. AA women are afflicted by higher rate of triple-negative breast cancer (TNBC) and bear the highest mortality rate of all populations from the disease. Even within TNBC, some data suggest that AA women have poorer outcomes than EA women. Mounting evidence points to population differences in cancer biology, a fundamental question that remains unsettled. The disparity also manifests in representativeness in tumor sequencing projects, due to the low inclusion of AAs in genomic studies. A recent analysis of The Cancer Genome Atlas (TCGA) data revealed that the number of AA cases sequenced was sufficient only for studying frequently mutated genes (≥10%), and the power was worse for TNBC as a separate disease entity. As a result, the breast tumor mutational landscape elucidated to date is derived mostly from EA cases, and may not necessarily represent AA cancer genomes. Moreover, as discovery potential for new driver genes has come close to a plateau, cancer in AAs derived from distinct genetic and environmental contexts may provide a powerful venue for discovering mutations that are rare in EA cases. This is showcased in recent studies in colon and prostate cancer. Thus, we carried out a collaborative project, B-CAUSE, to characterize the mutational landscape of AA breast cancer genomes by pooling resources from five established studies, including the Women's Circle of Health Study (WCHS), the Black Women's Health Study (BWHS), the Southern Community Cohort Study (SCCS), the Nashville Breast Health Study (NBHS), and the Southern Tri-State Breast Health Study (STSBHS). This effort has created the largest AA-specific breast tumor mutation dataset to date in an efficient manner. The data deposited here are from the whole-exome sequencing (WES) of matched tumor-normal pairs of 462 TNBC in AA women from the B-CAUSE Study.

Study phs003962

Genome-Wide Association Study of Schizophrenia

The goal of the study is to find susceptibility genes for schizophrenia. Dataset versioning Version 1: European-American (EA) ancestry only Version 2: Version 1 plus African-American (AA) ancestry Consent groups and participant set General research use (GRU): 4591 cases and controls (1217 EA cases, 1442 EA controls, 953 AA cases, 979 AA controls) This consent group includes a subset of schizophrenia cases and all controls (which overlap with Bipolar study controls in Bipolar: GRU dataset). Schizophrenia and related disorders (SARC): 475 cases (187 EA cases, 288 AA cases) This consent group includes a subset of schizophrenia cases.

Study phs000021

Kids First: Genomic Analysis of Esophageal Atresia and Tracheoesophageal Fistulas and Associated Congenital Anomalies

The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. Esophageal atresia/tracheoesophageal fistula (EA/TEF) is a rare and complex aerodigestive congenital anomaly with an estimated incidence of 1 in 2500 to 1 in 4000 live births. We propose to elucidate the underlying genomic architecture of EA/TEF by performing whole genome sequencing to characterize new clinical syndromes associated with EA/TEF to provide more accurate clinical prognostic information.

Study phs002161

Cincinnati Children's Hospital Medical Center (CCHMC) - eMERGE Phase IIIA Data

This submission includes genotyping or sequencing data from separate cohorts, each is described in separate paragraphs below. Extreme early onset obesity Obesity is a serious epidemic condition and on the rise in the United States. Today, nearly one out of three children is overweight or obese in this country. According to the Center for Disease Control, 35.7% of American adults and 17% of American children are obese. The medical costs associated with obesity are estimated to be in the billions. Without a doubt, interplay of additive genetic effects and common environmental effects influence this complex disease. However, despite being exposed to so-called "obesogenic environment", a large proportion of the population remains of normal weight. These observations suggest that innate, non-environmental, factors make some individuals more susceptible to obesity providing support for biological mechanisms, and thus genetic factors, to underlie the individual's response to the obesogenic environment. In young children with severe obesity the relative role of genetics and in utero programming are likely to outweigh the short duration of environmental and lifestyle exposures. This group is therefore an ideal one to study as they are likely enriched for variants that influence the risk of developing obesity. The purpose of this project is to further study and understand obesity in childhood and to develop a repository of samples for future studies into obesity. Eosinophilic Esophagitis (EoE) Eosinophilic Esophagitis (EoE) is one of the manifestations of eosinophilic gastrointestinal inflammation which have profound effects on a patient's health and development. Results of epidemiologic studies performed through our center demonstrate that eosinophil-associated gastrointestinal disease is not an uncommon entity. While the epidemiology of eosinophilic esophagitis has not been thoroughly studied until recently, there appears to be a significant increase in the diagnosis of EoE in the last decade. Based on our research, this mainly reflects increased disease recognition, but there is also a bona-fide increase in disease incidence which coincides with the increasing incidence of asthma and allergic diseases in the industrialized world. In addition, many patients with intractable symptoms thought in the past to represent atypical GERD or other disorders are now being recognized as having EoE. Diagnosis of EoE requires endoscopy and biopsies to document the characteristic histologic findings of esophageal eosinophilia. In general, this study proposed to elucidate the mechanisms underlying eosinophil growth, survival, migration, and function, and to investigate and further characterize the pathophysiology of, clinical manifestations of, and spectrum of disease severity of eosinophilic esophagitis in humans. The de-identified genotyping and genome wide association data generated as part of this research will be used for further genome research. Familial Sample Repository (FSR) and Directed Sample Repository (DSR) De novo mutations could cause many diseases, which has been demonstrated in mental retardation, autism and many rare genetic disorders. Family-based studies have a variety of advantages over case/control studies, including the elimination of analysis artifacts related to population stratification, the detection of genes that act through a recessive mechanism of inheritance and validation that the trait is not transmitted from a parent, something not possible using a case/control design. Additionally, DNA from families can be used to identify de novo mutations suggesting strong candidate causal polymorphisms. For this project, samples will be collected from families on an on-going basis. Families may be recruited because the patient either has a disease which is thought to be of genetic origin or from the general patient population to serve as controls or future identified diseases. Some phenotypes under study include fibroblastic rheumatism, diaphragmatic hernia, polymicrogyria, severe congenital neutropenia, primary sclerosing cholangitis and staph infection. CLRR-Cincinnati Lupus Registry and Repository Systemic lupus erythematosus (SLE) is a complex, partially understood autoimmune disorder. Genetic origins for SLE are supported by high heritability (> 66%), familial aggregation, increased monozygotic twin concordance, genetic linkages, and candidate gene genetic association, including HLA genes, Fc receptors, and complement components. Relevant environmental factors likely include infections (Epstein-Barr virus), therapeutics, personal habits (smoking), and diet. To continue a research resource facility for collection of well-characterized pedigrees containing a proband with systemic lupus erythematosus we develop this repository. Juvenile Idiopathic Arthritis (JIA) Juvenile Idiopathic Arthritis (JIA) is a debilitating complex genetic disorder characterized by inflammation of the joints and other tissues and shares histopathological features with other autoimmune diseases. It is considered complex genetic traits. There are more than 50,000 children with JIA in the USA, approximately 1 per 1000 births, which is about the same incidence as juvenile diabetes. It is believed that genes in the major histocompatibility complex (MHC) play a role in defining genetic risk, and it can be hypothesized that loci in other chromosomal regions are involved in conferring risk in JIA. These candidate chromosomal regions can be identified using genome-wide association analyses. The long-term goal is a comprehensive understanding of the genetic basis of these disabling arthropathies for which the molecular basis is not presently understood. These data will contribute to a national resource for the study of autoimmunity in children. Better Outcomes for Children-Cytogenetics Since 2007, more than 4000 samples, enriched with various rare or common genetic diseases as well as specific chromosomal abnormalities such as deletions and duplications have been genotyped for the purpose of subsequent GWAS and Phewas analyses and uncovering main genetic effects.

Study phs001011

Alcohol Dependence GWAS in European- and African Americans

This study includes SSADDA (Semi Structured Assessment for Drug Dependence and Alcoholism) assessed subjects (mostly unrelated, but including some affected sibling pairs) recruited in the course of several substance dependence genetics projects. The sample includes 1889 African-American (AA) subjects and 1020 European-American (EA) subjects. Among the AAs, 1397 meet DSM-IV criteria for alcohol dependence and 491 are controls. Among the EAs, 1010 meet the criteria for alcohol dependence and 9 are controls. (One in each population meets criteria for alcohol abuse and not dependence, and is therefore counted in neither category.) Although alcohol dependence is the major focus, the sample is informative also for cocaine, nicotine, and opioid dependence.

Study phs000425

DAC Ghent University - Department of Movement and Sports Sciences

DAC of Ghent University for RNA-seq data of human skeletal muscle biopsies collected at the Department of Movement and Sports Sciences

Dac EGAC50000000263

RNA-seq of high grade serous ovarian tumours

Somatic RNA for 40 samples matched to the WGS was extracted using the Qiagen Qiasymphony RNA protcol (cat no 931636). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including DNase digestion). The resulting RNA the underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as measures of RNA purity. A260/280 had to be 2.0 and A260/230 had to be 2.0-2.2. Then RNA was quantified using LifeTechnologies Qubit RNA BR kit (cat no Q10210). RNAseq was carried out by the Edinburgh Clinical Research Facility on an Illumina NExtSeq500. Total RNA samples were assessed on the Agilent Bioanalyser (Agilent Technologies, #G2939AA) with the RNA 6000 Nano Kit (#5067-1512) for quality and integrity of total RNA, and then quantified using the Qubit 2.0 Fluorometer (Thermo Fisher Scientific Inc, #Q32866) and the Qubit RNA HS assay kit (#Q32855). Libraries were prepared from total-RNA sample using the NEBNext Ultra 2 Directional RNA library prep kit for Illumina (#E7760S) with the NEBNext rRNA Depletion kit (#E6310) according to the provided protocol. 400ng of totalRNA was then added to the ribosomal RNA (rRNA) depletion reaction using the NEBNext rRNA depletion kit (Human/mouse/rat) (#E6310). This step uses specific probes that bind to the rRNA in order to cleave it. rRNA-depleted RNA was then DNase treated and purified using Agencourt RNAClean XP beads (Beckman Coulter Inc, #66514). RNA was then fragmented using random primers before undergoing first strand and second strand synthesis to create cDNA. cDNA was end repaired before ligation of sequencing adapters, and libraries were enriched by PCR using the NEBNext Multiplex oligos for Illumina set 1 and 2 (#E7500). Final libraries had an average peak size of 271bp. Libraries were quantified by fluorometry using the Qubit dsDNA HS assay and assessed for quality and fragment size using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC- 404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002). Libraries were combined in an equimolar pool based on the library quantification results and run across 5 High-Output Flow Cell v2.5.

Dataset EGAD00001009048

RNA-seq of high grade serous ovarian tumours

Somatic RNA for 37 samples was extracted using the Qiagen Qiasymphony RNA protcol (cat no 931636). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including DNase digestion). The resulting RNA the underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as measures of RNA purity. A260/280 had to be 2.0 and A260/230 had to be 2.0-2.2. Then RNA was quantified using LifeTechnologies Qubit RNA BR kit (cat no Q10210). RNAseq was carried out by the Edinburgh Clinical Research Facility on an Illumina NExtSeq500. Total RNA samples were assessed on the Agilent Bioanalyser (Agilent Technologies, #G2939AA) with the RNA 6000 Nano Kit (#5067-1512) for quality and integrity of total RNA, and then quantified using the Qubit 2.0 Fluorometer (Thermo Fisher Scientific Inc, #Q32866) and the Qubit RNA HS assay kit (#Q32855). Libraries were prepared from total-RNA sample using the NEBNext Ultra 2 Directional RNA library prep kit for Illumina (#E7760S) with the NEBNext rRNA Depletion kit (#E6310) according to the provided protocol. 400ng of totalRNA was then added to the ribosomal RNA (rRNA) depletion reaction using the NEBNext rRNA depletion kit (Human/mouse/rat) (#E6310). This step uses specific probes that bind to the rRNA in order to cleave it. rRNA-depleted RNA was then DNase treated and purified using Agencourt RNAClean XP beads (Beckman Coulter Inc, #66514). RNA was then fragmented using random primers before undergoing first strand and second strand synthesis to create cDNA. cDNA was end repaired before ligation of sequencing adapters, and libraries were enriched by PCR using the NEBNext Multiplex oligos for Illumina set 1 and 2 (#E7500). Final libraries had an average peak size of 271bp. Libraries were quantified by fluorometry using the Qubit dsDNA HS assay and assessed for quality and fragment size using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC- 404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002). Libraries were combined in an equimolar pool based on the library quantification results and run across 5 High-Output Flow Cell v2.5.

Dataset EGAD00001010139

Episodic Ataxia Syndrome: Longitudinal Study

Individuals with episodic ataxia experience recurrent attacks of dizziness and incoordination; between attacks patients are typically normal. The majority of cases are likely caused by an inherited genetic mutation. However, in some patients we are unable to identify the mutation. So far, 2 genes have been identified which cause different types of episodic ataxia. Ultimately, when the actual mutation is identified the protein product of the gene can be studied and specific medications can be designed. During this study, we will clinically evaluate patients with EA and follow them over time to help us better characterize the disease. We will also obtain blood samples to test for the known genetic mutations. In the future, we plan to coordinate trials of medications for the treatment of these disorders.

Study phs000521

A Retrospective and Cross-Sectional Analysis of Patients Treated for SCID Since January 1, 1968

Individuals with a past diagnosis of severe combined immune deficiency (including many cases of "leaky SCID", Omenn syndrome, and reticular dysgenesis) who have undergone blood and marrow transplant, gene therapy, or enzyme replacement in the past may be eligible for 6902. The purpose of 6902 is very similar to 6901, except 6902 is looking backwards at what has already been done in the past (compared to 6901 which is looking into the future). Over 800 patients with SCID are expected to be enrolled on 6902. This makes 6902 the largest study ever to describe outcomes for patients with SCID treated at many different hospitals around North America. One of the most important components of the 6902 study is the "cross sectional" study. Patients who have received their treatments (BMT, gene therapy, enzyme replacement) many years ago are asked to come back to the hospital where they were treated. During this visit, additional research blood work is drawn and information is gathered regarding long-term transplant outcomes such as infections, graft-versus-host disease, autoimmune diseases, and quality of life. This will allow PIDTC researchers to better understand long-term outcomes from procedures that occurred many years ago (sometimes over 30 years ago) - something that is not possible at the present time with 6901. This will help researchers to best design new treatments and clinical trials in the future for children with SCID.

Study phs001326

WES Elucidation of Pathogenetic Mechanisms for Immune System Disorders and NIAID Pilot of Genetic Incidental Finding Management

Background: - There are many types of immune disorders. These range from rare immune deficiencies to allergies to autoimmune disease like rheumatoid arthritis. Genes are the instructions our body uses to work and develop. A new technology called whole exome sequencing may help find the cause of these disorders. Whole exome sequencing is a way to look at many genes at once for errors. Researchers hope to find new gene changes that lead to immune disorders. Additionally, researchers are interested in finding the best way to manage unexpected but important findings by whole exome sequencing. Objectives: - To better understand genetic causes of immune system disorders. Also, to better understand people s thoughts and feelings about immune system disorders and new genomic testing. Eligibility: - People ages 0 100 with an immune disorder or a relative with an immune disorder. People must be at least 2 to be evaluated at the NIH clinical center. People must be at least 12 to do the survey/interview portion of the study. Design: Participants will have their genes sequenced. They may be asked for a new sample of blood. If participants cannot come for a study visit, they can have a blood sample collected by their local lab or doctor and sent by mail. Researchers may or may not find the cause of the participant s immune disorder. Participants will learn that information. Some participants may be asked to return to NIH to get results and have more tests. Researchers may share information with other studies. The data will be anonymous. For the survey part of the study, participants will answer questions about their or their relative s immune disorder. They will also answer about their thoughts and feelings about genomic testing. Some participants will be asked for a brief interview to ask more about the survey topics. There may be more follow-up after several months. From clinicaltrials.gov

Study phs001561

NINDS Family-Based Whole-Genome Sequencing to Find Modifiers of Age of Onset in Huntington's Disease

The goal of our studies is to identify genetic modifiers of neurodegeneration in Huntington's disease (HD). HD is caused by expansion of CAG repeats in the huntingtin (Htt) gene, with longer stretches often leading to more rapid disease onset and progression. Yet, for a given number of repeats, the age of symptom onset can be variable, differing by up to decades. Thus, the age of onset of motor symptoms in HD is only partly explained by the length of the CAG expansion. Available evidence suggests that genetic modifiers contribute to the variation in HD onset. Identifying genetic modifiers is important because they may provide critical insights into HD pathogenesis and reveal key pathways that could be targeted by novel HD therapeutics. This is important since there are no disease-modifying therapies for HD, and mHtt is an unattractive small-molecule drug target. We recruited 21 HD families with varying characteristics of disease progression and age of onset and obtained medical histories, clinical records and DNA samples that were subjected to whole-genome sequencing (WGS). These WGS data describe families of 104 subjects, including HD patients and their unaffected family members. These individuals were selected based on individual clinical histories and family structures that best fit our criteria for expressing potential genetic modifiers. We are testing the hypothesis that novel, rare genetic variants contribute to HD and those genetic modifiers can be identified by WGS.

Study phs001071

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

Ensemble learning for classifying single-cell data and projection across reference atlases

Single-cell data are being generated at an accelerating pace.How best to project data across single-cell atlases is an open problem. We developed a boosted learner that overcomes the greatest challenge with status quo classifiers: low sensitivity, especially when dealing with rare cell types.

Study EGAS00001004283

med-pchic-dac

The data are accessible under the terms of the following Data Access Agreement that needs to be filled in, signed (by yourself and your institutionâ€™s official contact) and returned by email to med-pchic-dac@lists.cam.ac.uk

Dac EGAC00001000523

North Carolina Clinical Genomic Evaluation by NextGen Exome Sequencing (NCGENES)

North Carolina Clinical Genomic Evaluation by Next-generation Exome Sequencing This study is part of a larger consortium project investigating the validity and best use of next-generation sequencing (in particular, whole exome sequencing, or WES) in clinical care. Participants are patients who were either seen in the UNC Cancer and Adult Genetics Clinic or referred to the study by their physician. They will be approached by their physician or a genetic counselor for recruitment. Once enrolled, a clinical geneticist or genetic counselor will obtain consent and collect blood samples to be analyzed using WES. Results may include information related to a diagnosis and incidental information. Medically actionable incidental findings will be CLIA-certified and returned to participants in a routine genetic counseling session, along with diagnostic findings. Eligible adult participants will be randomized to have the opportunity to choose to get certain types of non-medically actionable incidental findings, as well. Their decisions will be investigated, as will psychosocial and behavioral responses to sequencing and receiving sequencing information. This is a longitudinal, mixed methods study (i.e., multiple assessments pre- and post-return of results, with both quantitative and qualitative methods used to gather data). Because only the quantitative component of the study uses randomization, only measures and procedures associated with that component are included here. The third study release includes data of additional n=189 subjects.

Study phs000827

GEDI: A Developmental Model of Gene-Environment Interplay in SUDs: Combined Genotype Dataset from the "Great Smoky Mountains Study" and the "Caring for Children in the Community Study".

1. Great Smoky Mountains Study (GSMS; Costello et al. 1996, 1997) Three cohorts of boys and girls, aged 9, 11, and 13 years at intake in 1993, were selected from a rural population of some 20,000 children using a household equal probability design. A two-phase procedure was used for White and African-American youth to increase power by oversampling children at risk for psychiatric and SUDs. Parents (usually mothers) of the first stage random population sample completed a questionnaire about their child's behavioral problems. Of 4,195 subjects selected, 95% (N=3,896) of parents completed the screen. All children scoring above a predetermined threshold (the top 25% of the total scores), plus a 10% random sample of the remaining 75%, were recruited for detailed interviews. Results can be back-weighted to population levels for analyses. Half of the sample consists of females, and 6% are African Americans, reflecting the population of the study area. The interviewed sample of white and African-American subjects was 1,070 (80% of those recruited). American Indian youth were oversampled (100%) because they are an understudied group known to be at high risk for stressful events, substance disorders, and mood disorders. Of 431 age-eligible children, 350 (81% boys, 49% girls) participated. Thus, the size of total GSMS sample is 1,070 + 350 = 1,420. Data collection is complete for ages 9-26, and age 30 interviews are in progress. By age 26 a total of 9,858 interviews had been completed; the average number of interviews per subject was seven, and by age 26, 97.3% completed two or more interviews. 2. The Caring for Children in the Community Study (CCC; Angold et al., 2002) This representative study of psychiatric illness and service use in African-American and White youth took place in four rural counties in the southeastern USA. The two-stage sampling design and methods are similar to those used in the GSMS. Of 4,500 youth randomly selected from the 17,117 9- to 17-year-olds in the public school's database, 3,613 (80.0%) were successfully contacted and agreed to complete the behavioral screen. Of the 1,302 selected to participate in the study, 920 (70.7%) interviews were completed. Because CCC was also the only study in GEDI to contain more than a very few African-American participants, these were omitted from the multi-site analyses. Reprinted with permission from Cambridge University Press from Costello et al., 2013: PMID: 23461817 References: Costello et al., 1996: PMID: 8956679 Costello et al., 1997: PMID: 9184514 Angold et al., 2002: PMID: 12365876

Study phs000852

Nivolumab and Tumor Infiltrating Lymphocytes (TIL) in Advanced Non-Small Cell Lung Cancer

We performed a trial of adoptive cell therapy using tumor infiltrating lymphocytes (TIL) in metastatic non-small cell lung cancer (NSCLC). We conducted a single-arm open- label phase 1 trial (NCT03215810) of TIL administered with nivolumab in 20 patients with advanced NSCLC. Patients had tumor metastases resected for TIL, and the sequencing data from these tumors is included herein. The primary endpoint was safety, and secondary endpoints included objective response rate, duration of response, and T-cell persistence. Autologous TIL was expanded ex vivo from minced tumors cultured with IL-2. Patients received initial nivolumab for 4 cycles. If they had subsequent evidence of progression, then they proceeded to receive cyclophosphamide and fludarabine lymphodepletion, TIL infusion, and interleukin-2, followed by maintenance nivolumab. The endpoint of safety was met according to pre-specified criteria. Of 13 evaluable patients, 3 had confirmed responses and 11 had reduction in tumor burden, with a median best change of 35%. Two patients achieved complete responses ongoing 1.5 years later. In exploratory analyses, we found T cells recognizing multiple types of cancer mutations were detected after TIL treatment, and were enriched in responding patients.

Study phs002486

High-depth whole genome sequencing of paired ductal carcinoma in-situ (DCIS) and germline control samples from 26 individuals.

Deposited here are whole-genome sequencing data for 26 paired breast cancer DCIS and matched-normal samples taken from the same individual. Average sequence coverage is 118x for DCIS samples and 41x for matched-normals. Matched-normal samples are from blood. Sequencing was performed on an Illumina HiseqX. Due to specific restrictions imposed by the ethical approval at sample collection, the use of the germline data is restricted to filtering of somatic mutation calls only and cannot be used outside this purpose.They are a part of a broader project that uses high-depth WGS to investigate the somatic mutation genomic landscape of DCIS in order to uncover biological insights into breast cancer progression as well as possible methods to stratify DCIS patients for individualised therapy or disease monitoring.

Dataset EGAD50000002237

Natural History of and Genetic Modifiers in Spinocerebellar Ataxias

Spinocerebellar ataxias (SCA) are genetic neurological diseases that cause imbalance, poor coordination, and speech difficulties. There are different kinds of SCA and this study will focus on types 1, 2, 3, and 6 (SCA 1, SCA 2, SCA 3, also known as Machado-Joseph disease and SCA 6). The diseases are rare, slowly progressive, cause increasingly severe neurological difficulties and are variable across and within genotypes. The purpose of this research study is to bring together a group of experts in the field of SCA for the purpose of learning more about the disease. The research questions are: How does the disease progress over time? What are the best ways to measure disease progression? Do some genes, other than the gene that is abnormal in the SCA disease, have any effect on the way the disease behaves?

Study phs001332

North American Mitochondrial Disease Consortium Patient Registry and Biorepository

Mitochondrial diseases are caused by dysfunction of the mitochondria, which are specialized compartments that are present in every cell of the body except red blood cells. Mitochondria generate more than 90% of the energy that the body needs to sustain life and support growth. When they fail, less and less energy is generated within the cell. This injures the cell and can cause its death. If this process is repeated throughout the body, whole organ systems begin to fail, and the life of the person in whom this is happening is severely compromised. Mitochondrial diseases primarily affect children, but adult onset is becoming more and more common. Mitochondrial diseases are probably the most diverse human disorders at every level: clinical, biochemical, and genetic. Some affect only the nervous system but most affect many body systems, including the brain, heart, liver, skeletal muscles, kidney, and the endocrine and respiratory systems. Although mitochondrial disorders vary in severity, they are usually progressive, and often crippling. They can cause paralysis, seizures, mental retardation, dementia, hearing loss, blindness, weakness and premature death. Because of the range of symptoms and the frequent involvement of multiple body systems, mitochondrial diseases can be a great challenge to diagnose. Even when accurately diagnosed, they pose an even more formidable challenge to treat, as there are very few therapies and most are only partially effective. About this Study The first objective of this study is to establish a clinical registry of patients with suspected or confirmed mitochondrial diseases. We are collecting medical and family history, diagnostic test results, and prospective medical information for these patients and, using agreed procedures developed by the leading research clinicians in the field, providing, for the first time, standardized diagnoses of these complex disorders for the patients. The clinical information we collect from the participants will be used to learn about the spectrum of mitochondrial disorders and their prevalence. We will also develop studies which allow us to better understand how these diseases progress, which we do not understand well enough. When we begin clinical trials for mitochondrial diseases, patients enrolled in the registry who are identified as potentially eligible will be offered enrollment. Patients will only be included in studies if they give their consent in advance. The second objective of this study is to establish a biorepository for specimens and DNA from patients with mitochondrial diseases, in order to make materials easily available to consortium researchers.

Study phs001538

Best Practices for DACs

Best Practices Data access committees (DACs) are institutional safeguards responsible for ensuring a balance between data protection and accessibility. However, there are no procedural standards that apply across DACs, which can lead to inconsistencies in their reviews and compromise their quality and effectiveness. Standardising DAC processes can foster trust and mutual recognition, paving the way for greater coordination, collaboration, and delegation between DACs and other oversight bodies to improve the efficiency of data access without sacrificing protection. To provide guidance, the following are suggestions for actions a DAC might take upon receiving a data access request: Aim to respond to all initial requests in less than 2 weeks. Failure to do so may result in follow-up emails from the EGA, journals, and ultimately dataset withdrawal. First, check that the data/EGAD number is consistent with your data submission. In other words, ensure that the requester has contacted the correct DAC. Verify that the user will be using the data within the terms of consent by asking them to sign up to the terms within the DAA. Ensure that data users who are granted access to the data comply with the terms of a Data Access Agreement (DAA) and to use the data only in approved ways. Look for an institutional email address for the requester. Search for evidence that the requester is "appropriately qualified/bona fide" for using the data, for example on PubMed, Research Gate, LinkedIn, etc. Confirm that the affiliated organisation is real and that the requester still works there. Inquire with the requester about who should have accounts created at the EGA under the terms of the agreement. If a negative decision is made, promptly communicate it to the requester and support it with the terms of the Data Access Policy that the requester has not met or cannot meet. Keep the information in the DAC up to date. If you leave your institution and are unable to manage data access requests on their behalf, you should add your replacement as a new contact in the DAC. Assist with data access requests for any further questions related to your data. The EGA can only check information that has been deposited in the repository. If the user has a specific question that the EGA cannot answer, we will redirect the user to the DAC. All the EGA studies and datasets referenced in a publication under your DAC must be publicly searchable on the EGA website before the paper is released. If possible, describe the permitted purposes for subsequent research projects, including associated limits and conditions, for all resources hosted in a repository using a common ontology, such as the GA4GH Data Use Ontology (DUO). It is considered best practice to try and release data only to those with an institutional email address. This gives reassurance to the EGA, research participants, and the general public that an appropriate individual is accessing and using the data. To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security.

Documentation access/data-access-committee/best-practices

Comparison of 3 protocols for deriving pancreatic progenitors from hPSCs (RNA-seq)

This dataset contains 26 mapped bam files. The samples were generated with 3 different protocols for deriving pancreatic progenitors from hPSC. Three parallel differentiations were performed, all done in a hPSC NKX6.1-GFP reporter line. For each protocol there are three cellular populations: total (presort), GFP+ and GFP- . In summary: 3 differentiations x 3 protocols x 3 cellular populations. We prepared Smart-Seq2 RNA-seq libraries for the 27 samples, 1 sample failed library preparation and is not therefore included in this dataset.

Dataset EGAD00001004823

Adolescent Idiopathic Scoliosis (AIS) 1000 Exomes Study

Adolescent idiopathic scoliosis (AIS) is the most common pediatric spinal deformity. Although the Bracing in AIS Trial (BrAIST) recently demonstrated the effectiveness of bracing for preventing scoliosis progression in some patients, more than 20,000 children undergo major spinal fusion surgery at an annual cost of $3 billion. Spinal fusion surgery is a major operation with considerable risks and complications. Accurate methods of predicting curve progression are needed to develop personalized prevention strategies for those at high risk and to eliminate screening and treatment of those at low risk of progression. Previously identified risk factors for scoliosis curve progression include sex, age of onset, curve type, and presence of an underlying disorder. However, currently available algorithms for predicting AIS curve progression are inaccurate, possibly because the role of genetic factors has been largely unexplored. Because there is little a priori knowledge of the genetic variants involved in AIS pathology, an unbiased genome-wide approach is likely to provide the best opportunity to comprehensively identify disease-associated genes. This is a multicenter exome sequencing study of extreme cases with severe scoliosis.

Study phs001677

Evolutionary origin and methylation status of human intronic CpG islands that are not present in mouse

Imprinting of the human RB1 gene is due to the presence of a differentially methylated CpG island (CGI) in intron 2, which is part of a retrogene derived from the PPP1R26 gene on chromosome 9. The murine Rb1 gene does not have this retrogene and is not imprinted. We have investigated whether the RB1/Rb1 locus is unique with respect to these differences. For this we have compared the CGIs from human and mouse by in silico analyses and found out that there are at least 2033 human intronic CGIs that are not present in the mouse. Among these CGIs, 104 show sequences similarities elsewhere in the human genome, which suggests that they arose by retrotransposition. We could narrow down the time points when most of these CGIs appeared during evolution. Their methylation status was analysed in two monocyte methylome datasets from whole genome bisulfite sequencing and in 18 published methylomes. Five CGIs appear to be differentially methylated, which suggests that they are subject of genomic imprinting. They are located in introns of the following genes: RB1, ASRGL1, PARP11, PDXDC1 and MYO1D. Four of these CGIs are parts of retrogenes. Our study supports the notion that imprinting builds on host defence mechanisms by which the genome protects itself against retrotransposed and foreign DNA and that the epigenetic fate of the retrotransposed DNA depends on selective forces at the integration site.

Study EGAS00001000719

Federated EGA

Federated EGA Federated EGA Index Overview Map of FEGA status across the world Current status of the FEGA Network Documentation Overview Federated EGA is a global network of repositories enabling secure discovery and access to sensitive human data. Our vision is to accelerate scientific discovery and healthcare breakthroughs by creating the go-to worldwide sensitive human data resource. Our values are: Privacy & Trust: Ensuring privacy of data subjects, security of services and acting with integrity to build community trust.FAIRness: Driving reuse of data through standardisation of metadata and clear access policies.Diversity: Expanding our network and representing global diversity in the data we host to bring benefits worldwide. Federated EGA - European by name, global by nature Federated EGA collaborates with European and global initiatives (GA4GH, ELIXIR, 1+ Million Genomes Framework, GDI), demonstrating that a network for transnational discovery of and access to human data is possible. By providing a solution to emerging challenges around secure and efficient management of human omics and associated data, the FEGA Network fosters data reuse, enables reproducibility, and accelerates biomedical research. For general enquiries or to request more information about Federated EGA, please send an email to fega-info [at] lists [dot] ega-archive [dot] org. Read more about the Federated EGA in our commentary in Nature Genetics! Learn more about setting up a Federated EGA Node in our onboarding documentation. Map of FEGA status across the world Current status of the FEGA Network Node Description Joined CEGA Central EGA is managed by the Centre for Genomic Regulation (CRG) and EMBL-EBI. The EGA has been a trusted repository for sensitive data since 2008. CEGA coordinates the FEGA network, hosts central services and the EGA catalogue. 2022 Finland FEGA Finland is hosted by CSC - IT Center for Science Ltd., which is the national ELIXIR Node in Finland. CSC is a state-owned company specialising in providing high-quality IT infrastructure and services for Finnish higher education and research. 2022 Germany The German Human Genome-Phenome archive (GHGA) is part of the German National Research Data Infrastructure (NFDI). It is coordinated by the German Cancer Research Center (DKFZ) and includes over 20 academic partners. 2022 Norway FEGA Norway is a service by ELIXIR Norway, the Norwegian node of the European organisation ELIXIR. University of Oslo as a partner institution in ELIXIR Norway is hosting the service relying on the TSD infrastructure for sensitive data. ELIXIR Norway is a consortium of 5 Norwegian universities and is coordinated by University of Bergen. 2022 Spain FEGA Spain is co-hosted by the Barcelona Supercomputer Center (BSC) and the Centre for Genomic Regulation (CRG), both part of ELIXIR Spain and the Spanish National Infrastructure for Personalised Medicine associated with Science and Technology (IMPaCT). 2022 Sweden FEGA Sweden is hosted by the National Bioinformatics Infrastructure Sweden (NBIS), which legally is part of Uppsala University. NBIS forms the bioinformatics platform at SciLifeLab and constitutes the Swedish node of the European organisation ELIXIR. 2022 Poland FEGA Poland is hosted by Biobank Lodz, which is part of University of Lodz. Biobank Lodz is an element of the infrastructure of the Regional Digital Medicine Centers established by the Medical Research Agency. 2022 Portugal FEGA Portugal is managed by BioData.pt, the distributed infrastructure for Life and Health data for Portugal. This entity is a non-profit association of 15 life sciences R&I organisations spread across the country, and the home of ELIXIR Node in Portugal. 2023 Canada Canadian Genome-phenome Archive is part of the Pan Canadian Genome Library, with the mandate to allow the secure and responsible sharing and analysis of Canadian genomic information. 2024 Switzerland Swiss FEGA is hosted by SIB Swiss Institute of Bioinformatics, which is the national ELIXIR Node in Switzerland, on behalf of the Swiss FEGA Partnership which includes 4 other key partners (ETH Zurich, Health 2030 Genome Center, Swiss Data Science Center and Switch). 2025 Documentation Title Version Description Mission, vision, values Federated EGA Mission, vision, values 1.0 The official Mission-Vision-Values statement for FEGA, produced and formally approved by the FEGA Strategic Committee in September 2025. Structure and Organisation Federated EGA Structure and Organisation 2.0 The structure of the FEGA network and service expectations, responsibilities and commitments. FEGA is organised into three tiers: Central EGA, FEGA Nodes and FEGA Affiliates. Strategic Committee Federated EGA Strategic Committee 1.1 Terms of reference for the FEGA Strategic Committee describe the purpose and objectives of the committee, which is to provide direction and strategic planning for the FEGA network. The committee receives input from, and provides feedback for the EGA Strategic Committee. Operations Committee Federated EGA Operations Committee 1.1 Terms of reference for the FEGA Operations Committee describe the purpose and objectives of the committee, which is to review operational performance and coordinate technical roadmaps of FEGA Nodes and Central EGA. The committee receives advice from, and provides operational reporting to the FEGA Strategic Committee. Guidelines Node Operations guidelines 2.1 An overview of the operational areas which require resources in order to create a FEGA Node. The document is based on more than 15 years' experience of EMBL-EBI and CRG operating the EGA and initial expericences of the inaugural FEGA Nodes. The operational areas of responsability are in line with the FEGA Maturity Model, which guides establishment and operation of FEGA Nodes. Collaboration Federated EGA Node Collaboration Agreement 1.3 Nodes are welcome to make a copy of this current version of the CA to start its review with their legal teams and understand the responsibilities of joining FEGA. Nevertheless, this version (the one with a watermark) shall not be signed: the official version needs to be obtained from FEGA prior signing through its official channels.

Documentation about/projects-and-funders/federated-ega

Systematic identification of long non-coding RNAs potentially involved in gastrointestinal carncer

Recent work has suggested various important functions and molecular mechanisms for long non-coding RNAs (lncRNAs) and they are also thought to play critical roles in cancer. However the importance of lncRNAs in cancer biology is still unclear. In this study, we aim to comprehensively identify novel lncRNAs that are critically involved in tumorigenesis and progression in gastrointestinal cancer.

Study JGAS000011

Molecularly matched targeted therapies plus radiotherapy in patients with newly diagnosed glioblastoma without MGMT promoter hypermethylation (N2M2/NOA-20 phase I/IIa umbrella trial)

Background: Patients with glioblastoma without MGMT promoter hypermethylation are unlikely to benefit from temozolomide (TMZ). Trials aiming at replacing TMZ with targeted agents in not molecularly selected patient populations have failed. Methods: This phase I/IIa umbrella trial aimed at showing safety, feasibility, and preliminary efficacy of targeted compounds in addition to standard radiotherapy initiated within 42 days postoperatively. Molecular diagnostics and bioinformatic evaluation are performed within 28 days after surgery. Stratification for treatment takes place in five subtrials, including alectinib, idasanutlin, palbociclib, vismogedib and temsirolimus, according to the best matching molecular alteration. Patients without matching alterations are randomized between subtrials without strong biomarkers using atezolizumab and asunercept and TMZ as standard of care. Primary objective of the phase I parts of the trial was dose finding or dose validation. In the phase IIa trials, centrally determined progression-free survival at six months (PFS-6) is used as endpoint for efficacy with interim analyses for futility (H0: p=0.231). Results: From May 2018 through July 2022, 301 patients were enrolled and 228 treated in 13 German NOA sites. The alectinib and vismodegib subtrials were closed since no molecularly matching patients were accrued; the idasanutlin subtrial was closed prior to the optimal dose at nine patients at discretion of the company providing the drug. The TMZ subtrial showed a PFS-6 of 18.52% (10/54 patients) (p=0.831) and a median overall survival (OS) of 12.1 months. Asunercept: PFS-6 of 15.4% (4/26) (p=0.8825) and OS of 12.8 months. Atezolizumab: PFS-6 of 21.4% (9/42) (p=0.660) and OS of 11.7 months. Palbociclib with patients demonstrating CDK4 amplification or CDKN2A/B codeletion: PFS-6 of 24.4% (10/41) (p=0.4823) and OS of 12.6 months. Temsirolimus with patients demonstrating mTOR activation: PFS-6 of 39.1% (18/46) (p=0.0109) and OS of 15.4 months. The regimen-limiting toxicity (RLT)-rate is 34.8%, which is insignificantly above the predefined unacceptable rate for RLTs of 30%. Most RLTs had severity grade 3, one RLT had severity grade 4. No RLTs resulted in death. Conclusions: N2M2 allows for elaborate molecular testing being integrated into the treatment decision and efficient determination of treatment activity for patients with newly diagnosed glioblastoma. There is clinical activity of temsirolimus in patients with tumors harboring an activated mTOR pathway although this is not positively prognostic without mTOR inhibition; there is no clinical activity for asunercept and atezolizumab in not molecularly selected patients and also palbociclib in molecularly selected patients.

Study EGAS00001008033

A Genome-Wide Association Study on Cataract and HDL in the Personalized Medicine Research Project Cohort

The primary goals of this project are to develop and validate electronic phenotyping algorithms, to accurately identify cases and controls while maintaining a positive predictive value (PPV) of >95%, and to conduct a genome wide association study that advances understanding of two specific yet interrelated disease states, while simultaneously engaging the community in these research efforts. Lipid abnormalities and cataracts are both diseases of public health significance, they share common risk factors, and they are both complex diseases which likely have many genes contributing to disease development. Whole genome association studies with these two outcomes and environmental risk factors could yield novel data about the etiology of the two separate outcomes as well as their interaction. PhenX is a project designed to prioritize Phenotypes and eXposure measures for Genome-wide Association Studies (GWAS). The PhenX Toolkit is a valuable resource for researchers who are planning or expanding a study and would like to incorporate well established measures that have been recommended by experts in the field. We are currently interested in gene-environment interactions for "age related cataract".

Study phs000170

Determining Genetic Role in Treatment Response to Anti-Platelet Interventions (The PAPI Study)

CHD is the leading cause of death in the United States. One of the most common ways to prevent CHD is to take an anti-platelet agent, which lessens platelet aggregation. Two of the most common anti-platelet agents are aspirin and clopidogrel. However, up to 25% to 30% of people do not respond to these medications. Evidence indicates that treatment response may be related to genetics. The purpose of this study is to determine specific gene variants that predict response to aspirin and clopidogrel therapy. This study is part of a larger group of studies called the Pharmacogenomics Research Network (PGRN). Participants are from the Old Order Amish of Lancaster, Pennsylvania. They are well suited for genetic studies because they are a homogenous, closed, founder population. Participants received 300 mg of clopidogrel on the first day, then 75 mg of clopidogrel per day for the next 6 days. On the last day of clopidogrel treatment, participants took a single dose of 324 mg aspirin. Participants underwent platelet function tests before and after clopidogrel alone, and then again after taking clopidogrel plus aspirin. Using the gene variation profiles across the genome, researchers analyzed which variants correspond to treatment response.

Study phs000391

Establishment of an iPSC Repository Derived from Healthy Volunteers

Understanding the interaction between genetic variation and epigenetic variation remains a challenge due to the confounding role of environmental factors. We propose that human induced pluripotent stem cells (iPSCs) are an excellent model to study the relationship between genetic variation and epigenetic variation while controlling for consistent environmental factors. In this study, we have created a comprehensive resource of high-quality genomic, epigenomic, and transcriptomic data of six iPSC lines and three iPS-derived cell types (NSC, Motor Neuron, Monocyte) from three healthy donors. We found that epigenetic variation is most strongly associated with genetic variation at the iPSC stage, and that relationship weakens as epigenetic variation increases in the differentiated cells. Additionally, cell-type is a stronger source of epigenetic variation than genetic variation, highlighting that humans are far more similar than they are different, regardless of genetic background. Further, we have elucidated a utility of studying epigenetic variation in iPSCs and their derivatives for identifying important loci for GWAS studies and the cell-types in which they may be acting.

Study phs003649

Recurrent somatic DICER1 mutations in non-epithelial ovarian tumors

Background: Germline truncating mutations in DICER1, an RNase III-type endoribonuclease essential for processing of microRNAs, are seen in families with the pleuropulmonary blastoma-family tumor and dysplasia syndrome; these individuals have a propensity to develop non-epithelial ovarian tumors (i.e. sex-cord stromal and germ cell tumors). Methods: We sequenced the whole transcriptomes or exomes of 14 non-epithelial ovarian tumors and noted closely clustered mutations in the RNase IIIb domain of DICER1 in four cases. Using Sanger sequencing, we then analyzed additional ovarian tumors for mutations in this region. The impact of the mutations on the enzymatic activity of Dicer1 was determined using in vitro RNA cleavage assays. Results: RNase IIIb domain DICER1 mutations were found in 30/102 non-epithelial ovarian tumors (29%), predominantly Sertoli-Leydig cell tumors (26/43, 60%), including 4/4 from individuals with germline DICER1 mutations. The mutations were restricted to metal binding sites within the RNase IIIb catalytic centres critical for miRNA interaction and cleavage, and were somatic in all 14 cases where germline DNA was available for testing. Of 266 epithelial ovarian and endometrial cancers tested, one case, an ovarian carcinosarcoma, had a hotspot mutation. In vitro, the mutant DICER proteins showed reduced RNase IIIb activity but retained RNase IIIa activity. Conclusions: Somatic missense mutations of the RNase IIIb domain of DICER1 are common in non-epithelial ovarian tumors. Genetic, pathologic, and functional evidence suggest that these mutations do not obliterate DICER1 function, rather, they alter it in specific cell types, a novel mechanism through which perturbed microRNA expression is oncogenic.

Study EGAS00001000135

Analyzing Somatic Mutagenesis in Systemic Sclerosis

The study was undertaken with the aim of estimating differences in the mutational burden in lung tissues from healthy vs systemic sclerosis (SSc) patients. SSc is an auto-immune disease, with patients often developing cancer. However, the etiology of this phenomenon is poorly understood. As such we sought to uncover potential molecular mechanisms prevalent within SSc tissues that might be potentiating cancer. Samples were randomly collected from individuals from two broad ethnic groups, European (EA) and African American (AA). In total, samples were obtained from 7 individuals belonging to the EA group and 4 individuals from the AA group. For this study, ethnicity was not included as a confounding variable, given that the data set has roughly comparable number of individuals from both ethnicities for the healthy and SSc cohorts. Study participants ranged in age from 37-63 years old. Median age (52 years old) of healthy individuals was comparable to the SSc cohort (~48 years old). Participants were self-described as current/former smokers or non-smokers. Lung tissues were obtained under a protocol approved by the University of Pittsburgh Institutional Review Board. Written informed consent statements were provided to the University of Pittsburgh IRB by the study participants/patients. Sample sizes were determined by the ability of bulk lung fibroblast tissues to stably propagate in culture until single cell clones could be obtained. Samples for which sufficient cell density could not be achieved for downstream high-depth sequencing analysis were excluded from the study and are not reported. Five or greater than 5 samples are collected from each cohort including healthy and SSc patients. Subjects were allocated to two basic cohorts based on diagnosis at the time of explant. Participants with no reported lung anomalies were allocated to the "healthy" cohort, whereas individuals with reported lung abnormalities, primarily SSc with pulmonary fibrosis and/or hypertension were allocated to the "SSc" cohort. All tissue samples were cultured, propagated and processed in identical fashion without requiring individual-specific protocols. Additionally, equivalent amounts of DNA were used for preparing sequencing libraries from both cohorts, and all samples were sequenced using Illumina whole genome sequencing (WGS) and analyzed using identical computational pipelines. Our study primarily discovered that there is a significantly higher burden of somatic mutations in SSc samples, compared to healthy samples. We observed an overall increase in a range of mutations in genomes of SSc patients, including single base substitutions, indels, structural variants and copy number alterations. Additionally, we uncovered a novel mutation signature associated with SSc samples, hinting at the activity of POLH in these samples, and highlighting the potential nexus between inflammation, DNA damage, and cancer.

Study phs003700

The ICGC-TCGA DREAM Somatic Mutation Calling - Tumour Heterogeneity Challenge

Tumors are composed of many different cell types, ranging from the normal tissue micro-environment, infiltrating immune cells and tumour cells. This group of tumour cells is itself intrinsically highly heterogeneous, driven by the rapid mutation rate of cancer cells to become a mixture of different sub-populations. These different types of cells, called subclones, have different sets of mutations in their DNA. Because some subclones evolve from others, many subclones share mutations. While it is increasingly easy to determine what mutations are present in the tumor, it remains very difficult to determine which subclones have which mutations. The task of assigning mutations to subclones is called subclonal reconstruction.The ICGC-TCGA DREAM Somatic Mutation Calling - Tumour Heterogeneity Challenge (SMC-Het) is an international effort to improve standard methods for subclonal reconstruction: to quantify and genotype each individual cell population present within a tumor. The goal of this challenge is to identify the best subclonal reconstruction algorithms and to identify the conditions that affect their performance.

Study EGAS00001002092

A Chromatin Accessibility Atlas of the Developing Human Telencephalon

Gene expression differs between cell types and regions within complex tissues such as the developing brain. To discover regulatory elements underlying this specificity, we generated genome-wide maps of chromatin accessibility in nine anatomically-defined regions of the developing human telencephalon. Additionally, we defined the histone modification landscape of the prefrontal cortex and generated chromatin accessibility maps of its upper and deep layers. We predicted a subset of open chromatin regions (18%) that are most likely to be active enhancers, many of which are dynamic with 26% differing between early and late mid-gestation and 28% present in only one brain region. These predicted regulatory elements (pREs) are enriched proximal to genes with expression differences across developmental stages, regions, and cortical laminae; they harbor distinct sequence motifs that suggest potential upstream regulators. We leveraged this atlas to predict and validate novel regulatory elements of genes that control cortex laminar identity and genes associated with autism spectrum disorder (ASD). These include enhancers proximal to FEZF2 and BCL11A that were validated in mouse, and an enhancer of ASD gene SLC6A1 containing two functional de novo mutations in individuals with ASD whose enhancer function we validated via CRISPRa. We also include data for transcription factor binding in mid-fetal cortex tissues, using CUT&RUN methods.

Study phs002033

NHLBI TOPMed: Best ADd-on Therapy Giving Effective Response (BADGER)

BADGER is a 56-week randomized, double-blind, three-treatment, three-period cross-over trial that will evaluate the differential improvement in control that is achieved following three separate treatment interventions in children whose asthma is not acceptably controlled on a low dose of ICS (per NAEPP guidelines). All participants will enter an 8-week run-in period during which time they will receive a dose of 1x ICS (fluticasone 200 μg/day). During this 8-week time period, running 2-week averages to establish the lack of acceptable asthma control will be calculated. Thus, a child could qualify for randomization at any time during this 8-week run-in period. This approach should maximize both patient safety and successful enrollment. Children will continue to receive 1x ICS during the entire treatment phase. During each period of the treatment phase, they also will receive one add-on therapy in the form of LABA, LTRA or additional 1x ICS. The order of the add-on therapy assignment will be determined by randomization into one of six treatment sequences (order determined randomly). Each treatment period will be 16 weeks in length; the initial 4 weeks of each period will be considered to be the washout period for the previous treatment. The primary outcome measures will be frequency of asthma exacerbations, asthma control days, and FEV1.

Study phs001728

ACTIV-6: COVID-19 Outpatient Randomized Trial to Evaluate Efficacy of Repurposed Medications

This study is a platform protocol designed to be flexible so that it is suitable for a wide range of settings within healthcare systems and in community settings where it can be integrated into routine COVID-19 testing programs and subsequent treatment plans. This platform protocol will enroll participants in an outpatient setting with a confirmed polymerase chain reaction (PCR) or antigen test for SARS-CoV-2. Each appendix will describe a repurposed medication (study drug) to meet the protocol objectives. When only one study drug/appendix is under study, allocation between study drug and placebo will be 1:1. If multiple study drugs/appendices are under study, participants will also be randomized among the study drugs for which eligibility is confirmed. Since the route of administration of each study drug may differ, the placebos may also differ. To achieve blinding and an equitable randomization probability, a two-step randomization process will be used.In the first step, the participant will be randomized m:1 active study drug to placebo, where m is the number of active study drugs for which the participant is eligible. Then, participants will be randomized among the m study drugs for which they are eligible. Participants will carry their ‘study drug' versus ‘placebo' randomization with them into the study drug appendix. In this way, a participant allocated to placebo who is randomized to study drug A will be given the placebo that matches study drug A. This achieves equal probability of exposure to a placebo or an active study drug, and equitable distribution among all study arms for which a participant is eligible. Sites will be informed to which study drug appendix the participant is randomized, but not whether they are allocated to the study drug arm or placebo arm within that appendix. For analysis, concurrent placebo participants who were eligible for the study drug appendix will be pooled. This will result in approximately a 1:1 allocation ratio for any study drug to placebo. If a study drug appendix is stopped for efficacy and becomes standard of care, the active study drug arm may serve as a concurrent placebo for other study drugs.Participants will receive complete supply of repurposed medication (study drug) or placebo with length of treatment and amount of study drug/placebo depending on the study drug appendix and arm to which they are randomized.This study is designed so that it can be done completely remotely. However, screening and enrollment may occur in person at sites and unplanned study visits may occur in person or remotely, as deemed appropriate by an investigator for safety purposes. Participants will be on-study for up to 180 days, during which they will complete various questionnaires.

Study phs003941

Substance Dependence GWAS in European- and African - Americans

This study includes SSADDA (Semi Structured Assessment for Drug Dependence and Alcoholism) assessed subjects (mostly unrelated, but including some affected sibling pairs) recruited in the course of several substance dependence genetics projects. The sample includes 1,531 self-reported African-American (AA) subjects, 1,339 self-reported European-American (EA) subjects, and 2 who reported race as "unknown" or "missing".

Study phs000952

Foregut Microbiome and Risk of Gastric Intestinal Metaplasia, and Gastric Cancer Risk

The study is composed of two sub-studies. The first study, conducted by NYU Grossman School of Medicine, is a case-control study of 89 cases with gastric intestinal metaplasia (IM) and 89 matched controls who underwent upper gastrointestinal endoscopy at three sites affiliated with NYU Langone Health. Shotgun metagenomic sequencing using oral wash samples from the 89 case-control pairs and antral mucosal brushing samples from 55 case-control pairs were conducted. The other study, conducted by Vanderbilt University Medical Center, is a prospective case-control study on the oral microbiome and gastric cancer risk, utilizing shotgun metagenomic sequencing data of pre-diagnostic buccal samples from 319 Asians, 118 African Americans and 51 European Americans. This study includes data from three population-based studies: the Southern Community Cohort Study (SCCS), the Shanghai Women's Health Study (SWHS), and the Shanghai Men's Health Study (SMHS). The SWHS and SMHS include 74,941 women aged 40-70 years and 61,480 men aged 40-74 years, respectively, who were permanent residents of Shanghai and recruited to the cohorts between 1997 and 2006. The SCCS is an ongoing prospective cohort study, including ~86,000 participants recruited during 2002 and 2009 from 12 Southeastern states. Nearly 67% of study participants are African Americans (AAs) and the remaining are European American (EA) subjects.

Study phs002566

FEGA FAQs: a summary of the Q+A session from the FEGA workshop at ELIXIR AHM 2024

The ELIXIR All Hands Meeting (AHM) was held in Uppsala, Sweden this June. We at EGA always look forward to this meeting as a chance to see many of our partners and colleagues face-to-face. The Federated EGA (FEGA) is one initiative that always benefits from the AHM, and this year FEGA was in the spotlight, with several questions related to the advances we've made recently. We held this year's FEGA workshop a little differently, with most time for discussions on various “hot topics”. Organised in different breakouts, over 2 rounds, participants could choose which session they wanted to attend. One breakout was a general Q+A about FEGA and the path to join. We had a diverse range of participants, including experts from Central EGA (CEGA) and FEGA inaugural nodes, people from up and coming nodes at various stages of readiness, as well as participants not directly a part of FEGA but curious to learn more. It made for a great discussion! In this blog post, we highlight some of the questions for those who didn’t have a chance to be there. What is the FEGA Collaboration Agreement? It is a legal agreement between the node and Central EGA (CEGA) where both parties agree to certain responsibilities, like what services will be provided, sharing of public metadata with CEGA, interoperable technologies and more. The agreement is for 4 years, with the expectation of long-term sustainability. If a node is made up of multiple institutes, one institute must be the signatory. This could require a legal agreement within the node. CEGA is composed of CRG and EMBL-EBI (EGA itself has its own legal agreement between these institutes) Check the FEGA Collaboration Agreement What about purely medical data? Is this accepted in FEGA? CEGA only accepts data approved for secondary research use. We do accept medical data collected in this context, as do some nodes. Nodes are able to accept any data they like, as long as it is sensitive, thus in need of controlled access. What about other data types other than genomics? Like proteomics or images? They can be accepted, although CEGA is currently not designed with those formats in mind, so they might not fit with precision in the data model. The FEGA nodes are welcome to accept any data they want. Proteomic studies generating sensitive data are increasing, and specific work will likely be developed in the near future to adress this need. Does CEGA require a certain amount or type of data to be shared by the node? No, we do not and it's up to each node to decide what specific data types they accept and in what format. Nonetheless, a FEGA node has the duty to be open to data submission from any institution of their country, and can't be limited by design to a single or limited data source. Does CEGA and FEGA require a certain amount or type of details and description on the data to be submitted to the node? Data description (technical and biological), usually called metadata in this field, is crucial for the findability of the submitted data. Thus, we highly recommend including as much information as available to maximise the discoverability of the data. Specifical minimal metadata is defined in the submission schema, and thresholds are specified by the nodes. We are currently working towards a unified FEGA metadata model. What are the geographical borders of FEGA? FEGA should make the E for Everyone, because any institute worldwide could join and we indeed do have countries and use-cases worldwide. Some of them are very close to officially joining the federation. What are the main differences between FEGA and GDI? The two networks have a lot in common and also some critical differences. You can read all about this in one of our latest blog post. If you have more questions, please consider having a look at the FEGA onboarding webpage and, of course, don't miss our workshop at the ELIXIR AHM next year!

Blog fega-faqs-elixir-ahm-2024

Prostate Cancer Upgrading Reference Set

This study aimed to investigate clinical, demographic, and molecular features of men diagnosed with low-risk prostate cancer [ISUP Grade Group 1 (GG1)] at biopsy who underwent radical prostatectomy, and for whom an increased tumor grade (ISUP Grade Group 2 or above) was subsequently detected in the resected prostate. This phenomenon is termed upgrading. In collaboration with the Early Detection Research Network (EDRN), a blinded reference set was established to facilitate upgrading biomarker detection and validation. A prospective, multi-institutional, cohort of men with the GG1 prostate cancer and intention to undergo prostatectomy was recruited. Biospecimens (blood, urine) were collected and this biorepository comprises the official EDRN Upgrading Reference Set (URS). Recording of case-control status (case = upgrading at prostatectomy, control = no upgrading at prostatectomy) was coordinated by the Data Management and Coordinating Center (DMCC) of the EDRN, who ensured blinding of all participating researchers. A subset of the reference set (n = 192) was chosen to undergo whole genome sequencing (WGS) for the investigation of a germline genomic biomarker of upgrading. Variant calls from all sequenced URS whole genomes are available through dbGaP, with the exception of one sample for which sequencing was not successful. Among investigated clinical features, prostate-specific antigen (PSA) density and percent of cancer in pre-prostatectomy positive biopsy cores were significantly associated with upgrading. Two polygenic risk score-based biomarkers were computed in the genetic sub-cohort and tested against case-control status. Neither was predictive of upgrading.

Study phs003670

NHLBI TOPMed - NHGRI CCDG: The BioMe Biobank at Mount Sinai

The IPM BioMe Biobank, founded in September 2007, is an ongoing, broadly-consented electronic health record (EHR)-linked clinical care biobank that enrolls participants non-selectively from the Mount Sinai Medical Center patient population. BioMe currently comprises >42,000 participants from diverse ancestries, characterized by a broad spectrum of longitudinal biomedical traits. Participants are enrolled through an opt-in process and consent to be followed throughout their clinical care (past, present, and future) in real-time, allowing us to integrate their genomic information with their EHRs for discovery research and clinical care implementation. BioMe participants consent for recall, based on their genotype and/or phenotype, permitting in-depth follow-up and functional studies for selected participants at any time. Phenotypic and genomic data are stored in a secure database and made available to investigators, contingent on approval by the BioMe Governing Board. BioMe uses a "data-broker" system to protect confidentiality. Ancestral diversity - BioMe participants represent a broad racial, ethnic and socioeconomic diversity with a distinct and population-specific disease burden. Specifically, BioMe participants are of African (AA), Hispanic/Latino (HL), European (EA) and other/mixed ancestry. BioMe participants are predominantly of African (AA, 24%), Hispanic/Latino (HL, 35%), European (EA, 32%), and other ancestry (OA, 10%). Participants who self-identify as Hispanic/Latino further report to be of Puerto Rican (39%), Dominican (23%), Central/South American (17%), Mexican (5%) or other Hispanic (16%) ancestry. More than 40% of European ancestry participants are genetically determined to be of Ashkenazi Jewish ancestry. With this broad ancestral diversity, BioMe is uniquely positioned to examine the impact of demographic and evolutionary forces that have shaped common disease risk. Phenotypes available in BioMe - BioMe has a high-quality and validated set of fully implemented clinical phenotype data that has been culled by a multi-disciplinary team of experienced investigators, clinicians, information technologists, data-managers, and programmers who apply advanced medical informatics and data mining tools to extract and harmonize EHRs. BioMe, as a cohort, offers a great versatility for designing nested case-control sample-sets, particularly for studying longitudinal traits and co-morbidity in disease burden. Biomedical and clinical outcomes: The BioMe Biobank is linked to Mount Sinai's system-wide Epic EHR, which captures a full spectrum of biomedical phenotypes, including clinical outcomes, covariate and exposure data from past, present and future health care encounters. As such, the BioMe Biobank has a longitudinal design as participants consent to make all of their EHR data from past (dating back as far as 2003), present and future inpatient or outpatient encounters available for research, without restriction. The median number of outpatient encounters is 21 per participant, reflecting predominant enrollment of participants with common chronic conditions from primary care facilities. Environmental data: The clinical and EHR information is complemented by detailed demographic and lifestyle information, including ancestry, residence history, country of origin, personal and familial medical history, education, socio-economic status, physical activity, smoking, dietary habits, alcohol intake, and body weight history, which is collected in a systematic manner by interview-based questionnaire at time of enrollment. The IPM BioMe Biobank contributed ~10,600 DNA samples for whole genome sequencing to the TOPMed program. Samples were selected for the Coronary Artery Disease (CAD) and the Chronic Obstructive Pulmonary Disease (COPD) working groups. Using a Case-Definition-Algorithm (CDA), we identified ~4,100 individuals with CAD (~50% women) and ~3,000 individuals as controls (65% women). In addition, we identified ~800 individuals with COPD (62% women) and 1800 individuals as controls (72% women). Another 600 BioMe participants with Atrial Fibrillation, all of African ancestry, were included.

Study phs001644

Detection of cancers three years prior to diagnosis using plasma cell-free DNA

A major goal of early cancer detection is to identify subclinical disease when the tumor burden is low, so that treatments are more effective. But how early can cancers be detected prior to clinical signs or symptoms? This question can be answered only through the evaluation of participants whose clinical course has not been altered by the study itself. We here describe such an evaluation, performed on prospectively collected plasma samples from the Atherosclerosis Risk in Communities (ARIC) study, including 26 participants diagnosed with cancer and 26 matched controls. At the index time point, eight of these 52 participants scored positively with a multicancer early detection (MCED) blood test. All eight of these participants were diagnosed with cancer within 4 months after blood collection. In six of these 8 participants, we were able to assess an earlier plasma sample collected 3.1 to 3.5 years prior to clinical diagnosis. In four of these six participants, the same mutations detected by the MCED test could be identified, but at 8.6 to 79-fold lower levels. These results demonstrate that it is possible to detect circulating tumor DNA (ctDNA) more than three years prior to clinical diagnosis, and provide benchmark sensitivities required for the success of ctDNA-based tests for this purpose.

Study EGAS00001008068

Single_Cell_Sequencing_of_Sperm__scSperm_

The aim of this project is to genotype and sequence single spermatozoa from two men, one in his twenties and the other in his seventies. The resulting data is used to quantify the mutations that have arisen in the gametes of both individuals in order to better understand the effect of aging on mutation rates and modes.Project Outline. In order to quantify mutations, semen from two individuals are sequenced. 48 single sperm cells are isolated from each individual, and their DNA is extracted. The resulting genomes are amplified using PicoPlex, GenomiPhi MDA, Repli-G MDA, and MALBAC. QC step is applied to check the quality of WGA DNA using standard Sequenom plex (26 SNPs). A subset of 32 amplification products which pass the intiall QC, are genotyped using Affymetrix SNP6 chips. 12 of the genotyped amplification products are also sequenced. In addition, one multi-cell sample per individual is sequenced as a reference and for validation purposes.Altogether, 12 single cell sperm genomes and two multi-cell genomes are sequenced, coming to a total of 14 genomes. Of the single cell sperm genomes, 2 are sequenced to 50x coverage, and the other 10 to 25x coverage. Both multi-cell genomes are sequenced to 25x coverage.

Study EGAS00001000935

Genome-wide DNA-methylation assessment by MethylCap-seq and Infinium HumanMethylation450 BeadChips: an independent large-scale comparison

DNA-methylation is an important epigenetic feature in health and disease. Two cost-efficient genome-scale methodologies to assess DNA-methylation are MethylCap-seq and Illumina's Infinium HumanMethylation450 BeadChips (HM450). However, objective information regarding the best-suited methodology for a specific research question is scant. Therefore, we performed a large-scale evaluation on a set of 70 brain tissue samples obtained from 65 glioblastoma and 5 non-tumoral brain tissues, using a gold standard free Bayesian modeling procedure. While conditional specificity was adequate for both approaches, conditional sensitivity was systematically higher for HM450. Also the genome-wide characteristics were compared, revealing that the HM450 probes assess less than 10% of the regions identified as methylated by MethylCap-seq. Hence the latter method may detect more potentially relevant DNA-methylation, defined by either functional location or previously reported differentially methylated candidate regions. Our results therefore indicate that – at least for the tissue under study - both methodologies are complementary, with a higher sensitivity for HM450, but a far larger genome-wide coverage for MethylCap-seq. Note that here only the relevant MethylCap-seq data is deposited, for the HM450 data we refer to GEO (GSE60274).

Study EGAS00001001191

Somatic Genome Dynamics of Barrett's Esophagus Patients with Non-Cancer and Cancer Outcomes

A case-control study was designed with 80 participants diagnosed with Barrett's Esophagus (BE) selected from a larger case-cohort study (Li et al., 2014, PMID: 24253313) within the Seattle Barrett's Esophagus Program (SBEP) at the Fred Hutchinson Cancer Research Center. The study included 40 cases with BE with non-cancer outcomes, "NCO", who did not progress to esophageal adenocarcinoma (EA), and 40 controls who progressed to an endoscopically detected, incident EA (cancer outcome, "CO"). For each patient, two timepoints were evaluated (T1 and T2). NCO were matched to CO based on age at T1 (T1=first endoscopy with sufficient sample availability), and time between T1 and T2 (T2 in CO=time of diagnosis of incident EA). In 10 NCO, a third time point (T3), a mean of 13.2 years after T1, was also sequenced. Mapped endoscopic biopsies, at 1/3 and 2/3 annotated distances from the gastroesophageal junction within the Barrett's segment, were sampled per patient at each timepoint. Each biopsy was purified to separate BE epithelium from stroma, and DNA was extracted from purified epithelium for 60X WGS and 2.5M SNP array; normal control blood (N=62) or normal gastric sample (N=18) were analyzed by 30X WGS and 2.5M SNP array. An additional seven normal gastric biopsy samples in seven patients with normal control blood were also sequenced at 60X as controls. All research participants contributing clinical data and esophageal samples to this study provided written informed consent, subject to oversight by the Fred Hutchinson Cancer Research Center IRB Committee D (Reg ID 5619).

Study phs001912

What is a DAC?

What is a DAC? Given the complexity, scale, and diversity of global submitters and studies, the EGA operates a distributed data access model in which requests are made to the data controller, not to the EGA. The European Commission defines a data controller, in the General Data Protection Regulation (GDPR), as the person that determines the purposes for which and the means by which personal data is processed. A Data Access Committees, commonly referred to as DACs, comprise on or more individuals (or data controllers) that review data access requests and make decisions on who can access personally identifiable genetic, phenotypic, and clinical data deposited at the EGA. Therefore, the members of a DAC should be individuals who have the authority to approve data access requests. The animation describes how you can authorise access to your sensitive data with the help of Data Access Committee and Authorisation tool. Acknowledgement to CSC - IT Center for Finland, Elixir Finland, Elixir Europe. Frequently Asked Questions How can I create a Data Access Committee? How can I create a Data Access Committee? The members of a DAC can come from different areas of expertise, such as data management, data analysis, information technology, legal and compliance, subject matter experts, privacy and security, and representatives from the organisations or individuals that provide data to the DAC. The specific members of a DAC can vary depending on the needs of the organisation and the type of data being managed. The EGA strongly suggests checking with your organisation to align with its regulations How should a DAC be named? The chosen name must be informative to the applicant. For example, internal identifiers, such as grant numbers, should not be used. Individual PI names should also not be used. DAC's are often named after the organisation or department of the data source. Browse the full list of DAC names currently in the EGA. How can I become an EGA DAC contact? To register a DAC at the EGA you must create first as an EGA user. Once your EGA user has been approved by the Helpdesk team, you will be able to log in to the DAC Portal. How can I register a DAC? To register a DAC, follow the DAC Portal instructions. You will be required to provide a DAC name, name of the individual(s) that make up your DAC and contact details for your DAC including your Institutional email(s). Wherever possible, the DAC should make sure that all points of contact are readily available and able to answer any initial data requests/queries in < 2 weeks. Once your DAC is registered, you will have to wait upon the validation from our Helpdesk team. As soon as all the validations have been completed, your DAC will be activated. Alternatively, you can also establish a DAC at the EGA during a programmatic submission through Webin API. Which are the possible roles of a DAC contact? There are two possible roles for DAC contacts: member and admin. An admin has additional privileges compared to a member: An “admin” can manage data requests, create and edit policies, edit the content of the DAC, add or remove contacts, and decide the role of each contact. A “member” can manage data requests and create policies. However, a member does not have permission to modify DAC details, edit information from policies where they are not admins, or add/remove contacts. There is no limit to the number of admins in a DAC, and each admin is responsible for deciding who should have editing privileges. This allows for a more decentralised and democratic approach to managing the DAC. How can I modify the information of a DAC? To modify a DAC, follow the instructions here. Keep in mind that only DAC contact with an admin role can modify the information of a DAC. If your DAC was registered before the lauch of the DAC Portal, and its ID is EGAC0 (not EGAC5), you must use the programmatic submission to modify it. Please, do not hesitate to contact our Helpdesk team if you need help with this! To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security. What’s the link between DAC, policy and dataset? A dataset is linked to one single policy. At the same time, one policy has a one to one relationship with a DAC. In this example, you can see that in this dataset page, we are only showing the information of one DAC (1 dataset - 1 DAC). However, the ratio of objects does not work the same in the other direction. One DAC can own multiple policy objects. And each policy object can be reused in several datasets. Thus, one DAC can manage one or more datasets. In this example, you can see that in this DAC page, we are showing all the datasets that are managed by one DAC (1 DAC - >400 datasets). EGA Data Access Committee Best Practices Which are the EGA DAC best practices? Refer to DAC Best Practices What happens if a DAC member changes institutions? EGA is committed to the protection and ownership of the data stored in our systems. We respect the institution's ownership of the data, and as such, if a DAC member changes institutions, the ownership of the data will not be transferred to the new institution. Therefore, before changing institutions, we request that the DAC contact add a new member who will replace them once they no longer work at the institution. This ensures that the data remains protected and is accessible to authorised personnel at the institution. To prevent potential data breaches and ensure adherence to GDPR regulations, it is essential that the European Genome-Phenome Archive (EGA) is informed via the Helpdesk team of any changes to the Data Access Committee (DAC). This should be done in addition to any changes being made on the DAC portal. Data Controllers (as per the definition in the DPA) are also responsible for notifying the previous DAC of any modifications. Without proper notification, changes might not be automatically updated in our system, leading to the risk of incorrect permissions being applied and potential data access issues. Therefore, it is imperative that all Data Controllers follow this protocol to maintain data integrity and security. What happens if EGA detects an unresponsive DAC? EGA defines an unresponsive DAC as a DAC with one or more contacts who do not respond to data access requests. EGA has procedures in place to identify these types of DACs, escalate the issue, and attempt to reassign the DAC to a responsive contact. This is a crucial step in ensuring that data can be accessed and utilised by researchers. If EGA identifies an unresponsive DAC, the organisation will first try to resolve the issue by escalating it to the appropriate parties. This may involve attempting to reassign the DAC to a more responsive contact. Unfortunately, in situations where we cannot reassign the DAC, the dataset will be withdrawn from the public website and the files will be removed from our system. If an EGA ID is referenced in a publication, the EGA will take extra steps to ensure that the public is made aware of the data's unavailability. I don't want to receive an email notification for pending requests. How can I do that? If you are an EGA DAC with pending requests, you will always receive emails for new data access requests. However, the EGA understands that a request resolution can take some time, for this reason, if you add a comment (make sure you save it by clicking the APPLY button!) we will filter those requests at the time of sending the notification! How can I manage data access requests? What documentation does the DAC need to provide? Each dataset that is submitted to the EGA must be linked to a policy object. The policy is a Data Access Agreement (DAA), which defines the terms and conditions of using the dataset, such as how the data files should be stored once downloaded or details of publication embargoes that should be observed by the approved user. As part of the Data Access Agreement, information regarding the application can be captured to help inform the DAC when making its decision. For example, requestors could be asked to provide a proposed title for their research and a proposal of how the data will be used. By asking for provision of such information the DAC can be assured that the requestor fully understands any consents associated with the data. It is important that accounts created at the EGA, are created solely for those individuals that will be downloading the data from the EGA. As part of the data access request, we strongly encourage you to identify individuals that will need an account at the EGA in order to prevent sharing of login details, which is strictly prohibited under EGA user account policy. Such information can easily be captured in the DAA. NOTICE The data access agreement template below is provided for guidance only and should be adapted as you see fit to suit your own purpose. In the interest of promoting data sharing, we suggest that if an agreement cannot be met around clause 19 in this example that both parties should agree to remain silent, and that the clause should be removed from the agreement. Example DAA How can the DAC provide the DAA? The DAC should provide their own DAA when registering a policy. Data requestors will download this document and should fill it in and send it back to the DAC. Data access decisions should be based on such documentation. The DAA can be downloaded through the request data webpage. Once it has been filled in, the signed copy of the DAA can be uploaded back to the request data webpage and sent to the DAC for review. How can I grant access to the data? Once you receive a data access request, you can login to the DAC Portal. In this portal you will see all your pending requests and will be able to grant or decline access to the requestors. I am a member of the Data Access Committee. Could I approve somebody else to deal with the requests on my behalf? If you want to delegate data access decisions to someone else, make sure that the individual's account is officially registered as a member of the DAC. Remember that a DAC contact with an "admin" role can always add new members to an existing DAC, remove members, and modify contact details through the DAC Portal. Can I automatise the process of managing data access requests? The answer is yes! You can use a programmatic approach using our DAC API! Check out the DAC API specification! Data Breach What should a DAC do if they suspect a breach? If a DAC suspects a data breach of one or more of their datasets, they should immediately contact the EGA Helpdesk team at this link. The DAC must provide the following information when contacting the EGA Helpdesk team: A list of affected datasets An estimated date of the data breach (or interval of dates) A list of unauthorised users who accessed the data (if available). Otherwise, they can provide a list of authorised users for the affected datasets Any observations they would like to raise to the EGA team Once the DAC has contacted the EGA team, we will respond within 48 hours (please allow some leeway during peak times) and activate our data breach protocol. What can I expect from the EGA if they detect a breach? Once the EGA determines that a security incident has occurred, we will notify all DAC members that a data breach has been detected, and take steps to contain the incident. Containment approaches may include: Revoking a data provider's access to the EGA resources, such as by changing passwords. Removing affected EGA datasets from distribution, such as by withdrawing a dataset. Disabling certain functions or services, such as the EGA ingestion pipeline. Shutting down the system or disconnecting it from the network. After the incident has been contained, the EGA will determine whether it is necessary to eradicate components related to the incident. Finally, the EGA will enable recovery of the service to normal operation and confirm that all services are functioning normally.

Documentation access/data-access-committee/what-is-dac

StrattonWGS_RCC___Japan

The Stratton team uses DNA sequencing for somatic mutations to advance understanding of the causes of cancer. In particular, the investigation of “mutational signatures”, which report the mutational processes operative over the lifetime of each individual, to understand whether they are generated by endogenous or exogenous exposures and the extent to which these vary between human populations. Our work brings together global cancer epidemiology and genomics and is particularly characterised by large-scale multinational studies.

Study EGAS00001008001

Autoimmune-wide landscape of circulating CD4+ T cells unveils disease-specific heritability and phenotypic changes

While CD4+ T cells are involved in autoimmunity, how they contribute to the pathogenesis is unclear due to their cellular heterogeneity. Here, to analyze the heterogeneity, we utilized decomposition-based transcriptome characterization for evaluating non-discrete subsets of CD4+ T cells in addition to canonical clustering strategies. This approach identified 12 independent transcriptional gene programs governing whole CD4+ T cell heterogeneity, which can explain the ambiguity of the canonical clustering.

Study JGAS000578

Aspirin and Inflammation: Mutations, Genes, Pathways and Prevention in Barrett's Esophagus

Background: Use of aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) has been shown to protect against tetraploidy, aneuploidy, and chromosomal alterations in the metaplastic condition Barrett's esophagus (BE) and to lower the incidence and mortality of esophageal adenocarcinoma (EA). The esophagus is exposed to both intrinsic and extrinsic mutagens resulting from gastric reflux, chronic inflammation and exposure to environmental carcinogens such as those found in cigarettes. Here we test the hypothesis that NSAID use inhibits accumulation of point mutations/indels during somatic genomic evolution in BE. Methods: Whole exome sequences were generated from 82 purified epithelial biopsies and paired blood samples from a cross-sectional study of 41 NSAID users and 41 nonusers matched by sex, age, smoking, and continuous time using or not using NSAIDs. Results: NSAID use reduced overall frequency of point mutations across the spectrum of mutation types, lowered the frequency of mutations even when adjusted for both TP53 mutation and smoking status, and decreased the prevalence of clones with high variant allele frequency. Never smokers who consistently used NSAIDs had fewer point mutations in signature 17, which is commonly found in EA. NSAID users had on average a 50% reduction in functional gene mutations in nine cancer-associated pathways and also had less diversity in pathway mutational burden compared to nonusers. Conclusions: These results indicate NSAID use functions to limit overall mutations on which selection can act and supports a model in which specific mutant cell populations survive or expand better in the absence of NSAIDs. Galipeau PC, et al. Genome Med. 2018 Feb 27;10(1):17. PMID: 29486792.

Study phs001654

The Pioneer 100 Wellness Project (P100)

108 individuals (age 21-89+ years; 59% males, 41% females; 89% Caucasian; not recruited based on any specific phenotype) participated in an IRB-approved study from April 2014 to January 2015. Each individual had the genome sequenced in full. Blood was collected in clinics every three months. Additionally, participants completed at-home collections of saliva, stool, and first morning void urine every three months. Stool and saliva samples were shipped directly to the vendor by the participant, while urine was given back to the study coordinators for distribution to the proper sample vendor. For each successful participant in each round we carried out 218 clinical laboratory tests, measured up to 643 metabolites and 262 proteins, and measured the abundance of 4616 operational taxonomic units (OTUs) in the gut microbiome using 16S rRNA sequencing. The P100 study had four objectives: 1) Establish cost-efficient procedures for generating, storing and analyzing multiple sources of health data obtained over time from participants and analyzed in combination with genomic data; 2) Develop and deploy analytic tools for integrating these diverse datasets and deriving actionable information from their observed interrelationships; 3) Identify novel patterns within the streams of health data that indicate either wellness, or transitions between wellness and disease; 4) Learn how to best interface with and present longitudinal health information to individuals by studying the reactions and feedback from participants as they are presented actionable information.

Study phs001363

Gabriella Miller Kids First Pediatric Research Program in Enchondromatoses and Related Malignant Tumors

Chondrosarcoma is a malignant tumor that originates from cartilaginous cells. It is the third most common primary malignancy of bone after myeloma and osteosarcoma. It accounts for about 20% of bone tumors and is diagnosed in approximately 600 patients each year in the United States. Up to 40% of the chondrosarcomas arise from an enchondroma. Enchondromas are benign, intramedullary cartilaginous tumors of bone. They can be solitary or multiple and are present in >3% of the population. Enchondromatosis refers to a group of diseases characterized by multiple enchondromas including metachondromatosis (MC), Ollier disease (OD), and Maffucci syndrome (MS) among others. All have skeletal abnormalities with or without associated vascular anomalies that can cause severe limb deformities during early childhood. The risk for chondrosarcoma is up to 30% in OD and MS. Currently, the only treatment for patients with these disorders is surgical; there is no effective pharmacologic therapy. The molecular bases of these two conditions is not well understood.

Study phs001987

Investigating Host Genetic Risk Factors for Tuberculosis in Highly Endemic South African Populations

It is apparent from our recent population genetic and admixture mapping work 1–3 that a substantial part of the ancestral input into the South African Coloured (SAC) population is from the San or Khoe groups, which are not well represented in publicly available genetic databases. It is a reasonable assumption that the SAC population in the Western Cape may have derived more genetic input from the present KhoeSan population in the Northern Cape than the San residing in Namibia. It was concluded by our group that it is indeed the southern African KhoeSan group, the ≠Khomani, that best represent the KhoeSan contribution seen in the SAC 4. More recently, it has been shown that there are ancestry related increases in TB susceptibility, especially with increased Bantu-speaking African and KhoeSan ancestry 5. We aim to elucidate the epidemiological and human-host genetic risk factors for TB and the immunological pathways modulating TB infection. The proposed sub-study will enroll people evaluated for TB at Northern Cape community health clinics and their contacts from their households and/or community. We will conduct a demographic interview, collect saliva, which will be used for genetic analysis, and blood to determine latent TB infection status and capture immunological responses to mycobacterial infections at the cellular level and RNA sequencing.

Study EGAS00001007850

DNA methylation database for gynecological cancer detection, classification and assay development

DNA methylation changes are associated with cancer the best predictor of the presence of cancer. In order to detect and classify gynecological cancer, we performed MeD-seq to generate DNA methylation profiles of vulvar, cervical, endometrial, fallopian tube and ovarian cancers and their associated healthy tissues. DNA methylation profiles were used to find general cancer, regional cancer and specific cancer biomarkers that can be used for cancer detection, classification and treatment monitoring.

Study EGAS50000000417

A Cancer Cell-Line Titration Series for Evaluating Somatic Classification

Accurate detection of somatic single nucleotide variants and small insertions and deletions from DNA sequencing experiments of tumour-normal pairs is a challenging task. Tumour samples are often contaminated with normal cells confounding the available evidence for the somatic variants. Furthermore, tumours are heterogeneous so sub-clonal variants are observed at reduced allele frequencies. We present here a cell-line titration series dataset that can be used to evaluate somatic variant calling pipelines with the goal of reliably calling true somatic mutations at low allele frequencies. Cell-line DNA was mixed with matched normal DNA at 8 different ratios to generate samples with known tumour cellularities, and exome sequenced on Illumina HiSeq to depths of >300x. The data was processed with several different variant calling pipelines and verification experiments were performed to assay >1,500 somatic variant candidates using Ion Torrent PGM as an orthogonal technology. By examining the variants called at varying cellularities and depths of coverage, we show that the best performing pipelines are able to maintain a high level of precision at any cellularity. In addition, we estimate the number of true somatic variants undetected as cellularity and coverage decrease. Our cell-line titration series dataset, along with the associated verification results, is effective for this evaluation and will serve as a valuable dataset for future somatic calling algorithm development.

Study EGAS00001001016

Differential Transcription Start Site Usage in Brain-related Samples

RNA-Seq is an effective method to study the transcriptome, but specialized methods are required to identify 5' ends of transcripts. Several published strategies exist for this specific purpose, but their relative merits have not been systematically analyzed. Here, we directly compare the performance of six such methods - testing five with cellular RNA as well as a novel spike-in RNA assay that helps address interpretation challenges that arise from uncertainties in annotation or RNA processing. Using a single human RNA sample, we constructed and sequenced 18 libraries with these methods and one standard, control RNA-Seq library. We find that the CAGE method performed best for mRNA and that most of its unannotated peaks are supported by evidence from other genomic methods. We then applied CAGE to eight brain-related samples and revealed sample-specific transcription start site (TSS) usage as well as a transcriptome-wide shift in TSS usage between fetal and adult brain.

Study phs001463

NIHR BioResource Common Disease Patients 2016

NIHR BioResource Common Disease Patients 2016. The dataset includes 13489 samples from blood donors, they were not screened for any particular disease, and therefore they are representative of the general population. Genomic data includes 845487 snps collected using the UK BioBank V1 Affymetrix array. Phenotypic data includes gender, age, ethnicity and disease. According to our internal quality check there are 81 duplicates in this dataset.

Study EGAS00001004870

Circulating cell-free DNA analysis in Small Cell Lung Cancer

Small cell lung cancer (SCLC) accounts for ~250,000 deaths worldwide each year. Acquisition of adequate tumour biopsies is challenging and liquid biopsies present the best option for patient stratification and response monitoring. We present genome-wide and targeted plasma DNA sequencing data that identifies tumour related changes in 91% of limited (LS-SCLC) and 100% of extensive stage (ES-SCLC) patients. Parallel analysis of circulating tumour cells (CTCs, by CellSearch) based on ≥ 1 CTC/7.5ml blood increased tumour detection frequencies to 98% patients (95% for LS-SCLC) where CTC count and plasma DNA readouts correlated with disease stage and overall survival (OS). Targeted plasma DNA sequencing identified potential therapeutic targets in >50% of patients. This approach will support trials of targeted therapies where improved patients outcomes are urgently required.

Study EGAS00001003110

Atezolizumab and Bevacizumab in Treating Patients With Rare Solid Tumors

This phase Ib/II single-arm study evaluated atezolizumab + bevacizumab for patients with treatment-refractory metastatic HPV+ anal cancer. The primary endpoint was best overall response, and secondary endpoints included progression-free survival, overall survival, and safety/tolerability. Paired tissue biopsies were collected in patients before treatment and at the time of first restaging and analyzed for whole-exome sequencing, RNAseq (Bulk), and multiplex immunofluorescence. The overall response rate among 20 patients was 10%. WES and RNAseq data are provided here.

Study phs003845

StrattonWGS_Identification_of_Early_Life_Exposures_in_Paediatric_Colonic_Crypts_of_Healthy_Individuals

The Stratton team uses DNA sequencing for somatic mutations to advance understanding of the causes of cancer. In particular, the investigation of “mutational signatures”, which report the mutational processes operative over the lifetime of each individual, to understand whether they are generated by endogenous or exogenous exposures and the extent to which these vary between human populations. Our work brings together global cancer epidemiology and genomics and is particularly characterised by large-scale multinational studies. Whole genome sequencing of colon crypts from healthy paediatric individuals for identification of early life exposure to carcinogens.

Study EGAS00001007921

Identification of improved IL28B SNPs and haplotypes for prediction of drug response in treatment of hepatitis C using massively parallel sequencing in a cross-sectional European cohort

The hepatitis C virus infects nearly 3% of the World’s population, causing severe liver disease in many. Standard of care therapy is currently pegylated interferon alpha and ribavirin (PegIFN/R), which is effective in less than half of those infected with the most common viral genotype. Two IL28B SNPs, rs8099917 and rs12979860, predict response to (PegIFN/R) therapy in treatment of hepatitis C virus infection. These SNPs were identified in genome wide analyses using Illumina genotyping chips. In people of European ancestry, there are 6 common (>1%) haplotypes for IL28B, one tagged by rs8099917 minor allele, four tagged by rs12979860. We used massive parallel sequencing of the IL28B and IL28A gene regions generated by PCR from pooled DNA samples from 100 responders and 99 non-responders to therapy, to identify common variants. Variants that had high odds ratios and were validated were then genotyped in a cohort of 905 responders and non-responders. Their predictive power was assessed, alone and in combination with HLA-C. Only SNPs in the IL28B linkage disequilibrium block predicted drug response. Eighteen SNPs were identified with evidence for association with drug response, and with a high degree of confidence in the sequence call. We found that two SNPs, rs4803221 (homozygote minor allele positive predictive value (PPV) of 77%) and rs7248668 (PPV 78%), predicted failure to respond better than the current best, rs8099917 (PPV 73%) and rs12979860 (PPV 68%) in this cross-sectional cohort. The best SNPs tagged a single common haplotype, haplotype 2. Genotypes predicted lack of response better than alleles. However, combination of IL28B haplotype 2 carrier status with the HLA-C C2C2 genotype, which has previousl y been reported to improve prediction in combination with IL28B, provides the highest PPV (80%). The haplotypes present alternative putative transcription factor binding and methylation sites. Massive parallel sequencing allowed identification and comparison of the best common SNPs for identifying treatment failure in therapy for HCV SNPs tagging a single haplotype have the highest PPV, especially in combination with HLA-C. The functional basis for the association may be due to altered regulation of the gene. These approaches have utility in improving diagnostic testing and identifying causal haplotypes or SNPs.

Study EGAS00001000096

FEGA and European GDI: working together to improve human health

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

Blog fega-and-gdi

PE-CGS: Optimizing Engagement of Hispanic Colorectal Cancer Patients in Cancer Genomic Characterization Studies

Colorectal Cancer (CRC) is the second leading cause of cancer death in the US. Hispanic/Latinos (H/L) are the largest and fasting growing ethnic group in the US, and cancer is the leading cause of death among H/L in the US. Therefore, we need to fully understand the full complexity of the molecular etiology of cancer in this ethnic group. For instance, although incidence rates of CRC are lower among Latinos as compared to Whites or African Americans, Hispanics with metastatic disease have shorter overall survival when adjusted for health care setting, demographics, disease characteristics and treatment factors. H/L also tend to be diagnosed at a younger age and with higher stage, and we have previously reported that Mexican H/L in California have the greatest proportion of young (The Cancer Genome Atlas has provided a deep overview of the molecular taxonomy of CRC in 594 cases, however, less than 1% of the cases (n=5) were H/L. Therefore, it is imperative for us to take more detailed assessment of the molecular genomic landscape of CRC in H/L. One of the major issues likely limiting our ability to perform these large genomic initiatives in minority patients is that Patient or Participant Engagement practices may not be investigated to identify best practices for accruing and consenting patients into clinical translational biomedical research studies. This concept of Participant Engagement is critically important for both the patients and the translational cancer research community. Optimizing and improving our approaches for directly engaging patients at initial contact, throughout the course of a translational genomic study, and during the time of return of results is likely to lead to stronger relationships between the medical community and patients, but could also lead to significant improvement in outcomes for patients and for the cancer care community as a whole. As such, we propose the creation of the USC Center for Optimization of Participant Engagement in Cancer Characterization (COPECC) with a focus on optimizing the engagement of Latinos in CRC Genomic Characterization research studies. USC COPECC would serve as a member of the NCI U2C Participant Engagement and Cancer Genome Sequencing (PE-CGS) Network. Our investigative team includes experts in all relevant areas of research for genomic characterization, participant engagement, and engagement optimization. We have an established platform for consenting patients into cancer genomics studies that will serve as a standard process. The overall goal of USC COPECC is to generate results on participant engagement optimization and CRC genomic research that will be shared with the broader community to distribute best practices for engaging Latinos in hopes of improving overall outcomes for CRC in this underserved population.

Study phs003985

Single individual whole genome sequencing of Jakun, Indigenous Peoples of the Peninsular Malaysia

This study disected the genetic structure of a Jakun individual, a sub-tribe of Indigenous Proto-Malay from Peninsular Malaysia. They are postulated to have settled in Peninsular Malaysia approximately 4-6 KYA, during the last agricultural expansion. However, their genetic structure is still not well understood.

Study EGAS50000000740

A Prospective Natural History Study of Diagnosis, Treatment and Outcomes of Children with SCID Disorders

Individuals with a recent or new diagnosis of severe combined immune deficiency (including infants who were identified by newborn screening) may be eligible to be enrolled on the PIDTC research study 6901. Speak to your doctor to determine if you or your child may be eligible. Protocol 6901 follows patients with SCID prospectively, meaning the 6901 study enrolls participants where there is a plan to receive a blood and marrow transplant, enzyme therapy, or gene therapy in the future. Patients are then followed according to a schedule set out by the study protocol after the procedure. The times the study requests follow up will be the same as when your doctor would want to be seeing you or your child as part of their regular ongoing medical care. Patients with "leaky SCID", reticular dysgenesis, and Omenn syndrome may also be eligible to participate in 6901. The 6901 research study does NOT dictate how your or your child's doctors should treat you or your child, as the PIDTC recognizes that there are many complex factors that go into this decision. The decision about how you or your child with SCID will be treated is made by your doctor. The 6901 study simply follows how you or your child do over time. There are no experimental therapies on this study. The 6901 study has been open since August 2010, and continues to be open and enrolling patients to the present day. The study plans to enroll approximately 250 patients with SCID. By studying new patients undergoing treatment for SCID, the goal is to learn more about: (1) outcomes from the treatment of SCID in the modern era of medicine, (2) what factors lead to the best long-term outcomes, such as best donor, conditioning regimen, timing of transplant, etc. and (3) what impact newborn screening and the early diagnosis of SCID has had on the long-term outcomes following BMT or gene therapy. A significant amount of information is also being gathered on how and when the immune system recovers after BMT, quality of life for long-term survivors, and about whether children develop normally after treatment. The 6901 study is the largest coordinated prospective study of patients with SCID ever performed. Information that we will learn, both now and in the future, will help doctors and other health professionals to better treat children with SCID. All hospitals within the PIDTC are enrolling patients with SCID on 6901, ensuring that the outcomes are reflective of what happens in the "real world" as opposed to at just one or two large centers.

Study phs001392

Profiling_molecular_heterogeneity_in_human_primary_microglia

In the brain the cells that control inflammation are called a type of white blood cell called microglia. Microglia are located throughout the brain and spinal cord and account for 10–15% of all cells found within the brain. As the resident white blood cells, they are the main active immune defence in the central nervous system (CNS). Microglia are part of an important class of cells known as macrophages that have two main states: M1 and M2. M1 cells are pro- inflammatory, leading to more inflammation, while M2 are anti-inflammatory, and drive wound healing. In this study, we will collect primary microglia from surgical biospies of 100 individuals. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Study EGAS00001002494

20 years after the first human genome release. Where are we heading?

The genomic revolution equipped the scientists with millions of human genomes, entirely changing the way we envision, project and interpret science. Together with the amounts of data, it also evolved the need to respect the donors' right to privacy. Data protection laws flourished and, while they undeniably served to improve human rights and good practices in research, they added new layers of complication to the goal of data sharing. Nature Journal has dedicated a collection of remarkable articles to this 20th anniversary, where they portray how scientists did not fulfil the promise at the core of the HGP. The call for efficient sharing of human genomic data is nowadays more live than ever, with the animate issue regarding the faulty availability of data from COVID-19 patients, right when the pandemic is setting an unprecedented pressure on the scientific and medical community. Given its importance, this multi-faceted debate does not lack controversial opinions. Some researchers indeed consider that we should move toward more restrictive data access, giving more decisional power to the donors, despite that would inevitably diminish the usability and value of the data. Even if 20 years after we are still not there, at the EGA we are committed to make the dream behind the HGP a reality, working day by day to enable law-compliant data sharing.

Blog 20-years-after-the-first-human-genome-release

CIDR: Collaborative Study on the Genetics of Alcoholism Case Control Study

This is a case-control study of alcoholism, in which the subjects have been drawn from the Collaborative Study on the Genetics of Alcoholism (COGA), a large, ongoing family-based study that includes subjects from seven sites around the US. COGA has gathered detailed, standardized data on study participants, including diagnostic and neurophysiological assessments. This sample has already proved successful in identifying several genes that influence the risk for alcoholism and neurophysiological endophenotypes, which have been independently replicated. COGA data were included as part of two Genetic Analysis Workshops, and the phenotypes are familiar to the genetics community. Alcoholic probands were recruited from treatment facilities, assessed by personal interview, and after securing permission, other family members were also assessed. A set of comparison families was drawn from the same communities as the families recruited through an alcoholic proband. Assessment involved a detailed personal interview developed for this project, the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA), which gathers detailed information on alcoholism related symptoms along with other drugs and psychiatric symptoms. Many participants also came to the laboratories for electroencephalographic studies. Neurophysiological features that have been shown to be useful endophenotypes for which we have linkage and in some cases association results are included on a subset of the case-control sample: the beta power of the resting electroencephalogram (EEG), the P3(00) amplitude of the visual event-related potential (ERP), and the theta and delta event-related oscillations (EROs) underlying the P3 (See Porjesz et al., 2005; Porjesz and Rangaswamy, 2007 for reviews). A brief description of COGA is in Edenberg, H. J. (2002) The Collaborative Study on the Genetics of Alcoholism: an update. Alcohol Res Health 26, 214-218., Bierut, LJ, NL Saccone, JP Rice, A Goate, T Foroud, HJ Edenberg, L Almasy, PM Conneally, R Crowe, V Hesselbrock, T-K Li, JI Nurnberger, Jr, B Porjesz, MA Schuckit, J Tischfield, H Begleiter, and T Reich (2002) Defining alcohol-related phenotypes in humans: The Collaborative Study on the Genetics of Alcoholism. Alcohol Res Health 26, 208-213. Edenberg HJ and Foroud T (2006) The genetics of alcoholism: identifying specific genes through family studies. Addiction Biology 11, 386-396. This case-control sample of biologically unrelated individuals was drawn from COGA subjects. All cases meet DSM-IV criteria for alcohol dependence. Controls are individuals who have consumed alcohol, but did not meet any definition of alcohol dependence or alcohol abuse, nor did they meet any DSM-IIIR or DSM-IV definition of abuse or dependence for other drugs (except nicotine). All cases and controls have undergone identical clinical assessments. Many individuals in this case-control sample have not previously been genotyped. The Collaborative Study on the Genetics of Alcoholism (COGA) has four Co-Principal Investigators: B. Porjesz, V. Hesselbrock, H. Edenberg, L. Bierut. COGA includes nine different centers where data collection, analysis, and storage take place. The nine sites and Principal Investigators and Co-Investigators are: University of Connecticut (V. Hesselbrock); Indiana University (H.J. Edenberg, J. Nurnberger Jr., T. Foroud); University of Iowa (S. Kuperman); SUNY Downstate (B. Porjesz); Washington University in St. Louis (L. Bierut, A. Goate, J. Rice); University of California at San Diego (M. Schuckit); Howard University (R. Taylor); Rutgers University (J. Tischfield); Southwest Foundation (L. Almasy). Q. Max Guo serves as the NIAAA Staff Collaborator. This national collaborative study is supported by the NIH Grant U10AA008401 from the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and the National Institute on Drug Abuse (NIDA). Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research, was provided by the National Institute on Alcohol Abuse and Alcoholism, the NIH GEI (U01HG004438),and the NIH contract "High throughput genotyping for studying the genetic contributions to human disease" (HHSN268200782096C). COGA has over 250 publications listed at www.niaaagenetics.org

Study phs000125

Systems biology of Colorectal Cancer

Colorectal cancer (CRC) is one of the most common cancers in both males and females, and it is perhaps the best understood of all epithelial tumors in terms of its molecular origin. Yet, despite large amount of work that has concentrated on understanding of colon tumorigenesis, we still do not know the full complement of molecular lesions that are individually necessary – and together sufficient – to cause colorectal cancer. Neither do we understand why some specific mutations that are relatively rare in other tumors (e.g. loss of the APC tumor suppressor) are extremely common in colorectal cancer. We propose here to use the tools of systems biology to develop a quantitative and comprehensive model of colorectal tumorigenesis. The model will include identification of cell-type specific and oncogenic pathways that contribute to colon tumorigenesis, and explain in molecular detail how a genotype of an individual CRC leads to activation of downstream genes that drive uncontrolled cell growth. This model will subsequently be used to find novel therapeutic targets, to guide genetic screening to identify individuals with elevated risk for developing CRC, and to classify patients into molecular subgroups to select the treatment combination that is optimal for each patient (personalized medicine). The specific objectives of the SYSCOL project are: 1. Identify genetic markers for individual risk using genotyping and sequencing of constitutional DNA from sporadic and familial CRC cases and controls 2. Identify genes and regulatory elements that contribute to colorectal cancer cell growth 3. Use data from Aims 1-2 to develop a quantitative model for colorectal tumorigenesis 4. Apply the model for identification of high-risk individuals, for molecular classification of the disease, and for identification of novel molecular treatment targets

Study EGAS00001000854

Exome Sequencing of Esophageal Adenocarcinoma

The incidence of esophageal adenocarcinoma (EAC) has risen 600% over the last 30 years. When coupled to the five-year survival rate of only 15% for this disease, identification of new therapeutic targets for EAC is of great importance. Here, we analyze the mutational spectra identified from the whole genome sequencing of 16 EACs and complete exome sequencing of 149 EAC tumors and matched germline samples. We identify a novel mutation signature marked by high prevalence of A to C transversions at AA*(N) trinucleotides. Notably, the development of EAC is preceded by pathologic intestinal metaplasia of the lower esophagus, Barrett's esophagus, itself a response to injury from gastric-esophageal reflux disease (GERD). Thus, we hypothesize to represent these AA*(N) mutations to a novel signature of GERD-induced mutagenesis. Analysis of the exome data identified 26 genes subject to statistically significant recurrent mutation. Of these 26 genes, only TP53, CDKN2A, SMAD4, and PIK3CA had been previously implicated in EAC. Novel mutations include those targeting chromatin modifying factors and novel candidate contributors to EAC: SPG20, TLR4, ELMO1 and DOCK2. Of these, ELMO1 and DOCK2 are notably direct dimerization partners that act to activate Rac1 to enhance cellular invasiveness, thus generating new hypotheses about the potential for the Rac1 pathway to be a novel target for therapy of EAC. "Reprinted from 'Unraveling the mutational complexity of esophageal adenocarcinoma', with permission from Nature Genetics."

Study phs000598

Genomic Diagnosis and Individualized Therapy of Highly Penetrant Genetic Diabetes

The most common and well-known causes of diabetes are type 1 and type 2 diabetes; however, there are many other etiologies of diabetes. At least 1-2% of diabetes cases result from high penetrance single gene defects, most commonly in a gene encoding either a transcription factor involved in beta cell development and function or the enzyme glucokinase (GCK). Others have mutations in transcription factors necessary for beta cell development and function. This subset of monogenic diabetes cases is autosomal dominant and is known as "Maturity-Onset Diabetes of the Young" (MODY). Patients with type 1 diabetes are insulin dependent, meaning they lack insulin production and therefore require multiple daily injections of insulin, as well as multiple times a day blood glucose monitoring. This can be quite burdensome. Type 2 diabetes is predominantly an insulin resistance problem and can often be managed with pills initially, but there are many who also require insulin either at diagnosis or later on in their disease course. Usually, monogenic diabetes is misdiagnosed as type 1 or type 2 diabetes and thus treated suboptimally. Those with monogenic diabetes, due to a defect in a gene encoding a transcription factor, respond extremely well to a class of oral diabetes medications called sulfonylureas. Those with GCK-MODY often have a mild, stable, fasting, nonprogressive hyperglycemia for which pharmacological treatment is often not necessary. It is important to accurately diagnose our patients with the correct etiology to their diabetes for a multitude of reasons. Accurately diagnosing a patient with MODY, for example, can predict their clinical course and we can tailor treatment accordingly. If diagnosed with a transcription factor MODY, we can try switching the patient from insulin to an oral sulfonylurea, and if diagnosed with a GCK-MODY, we can consider discontinuing pharmacological treatment altogether. With specific tailoring of treatment, we would hope to improve quality of life by discontinuing perhaps multiple daily injections of insulin and glucose checking as these may not be necessary. In addition, we would hope to improve glycemic control with an eventual decreased cost to society by decreasing the complication rate of diabetes, resulting in less specialty referrals, lab tests, supplies and procedures. Further, given MODY is an autosomal dominant condition with a 50% chance of inheritance to first-degree family members, we could offer testing to asymptomatic family members which could lead to prevention and/or early diagnosis and treatment. Overall, testing for monogenic diabetes is underutilized clinically. Testing is being done in the U.K., but in the U.S. we are lagging behind. This is most predominantly due to lack of knowledge and concern over cost. In addition, it is difficult to differentiate the relatively small number of monogenic diabetes cases from the larger number with type 1 and type 2 diabetes as each of these etiologies have overlapping characteristics. In fact, many patients with monogenic diabetes are being misdiagnosed with type 1 and type 2 diabetes. There are recommendations set forth by different societies on who to consider screening for monogenic diabetes. However, these recommendations are difficult to employ clinically as they are general recommendations, there is no specific algorithm, and they are based on varying levels of evidence. The purpose of this study is to implement a personalized diabetes medicine program to enhance the identification of individuals and families affected by highly penetrant diabetes gene mutations through a combination of systematic screening and genetic testing at the University of Maryland Center for Diabetes and Endocrinology, the Baltimore VA Medical Center and additional partner centers at Geisinger Health System and Bay West Endocrinology Associates, and other UM outpatient clinics. Our hope is to develop an approach that can be eventually implemented across the United States so that we can more often uncover the correct etiology to diabetes, tailor treatment accordingly, and test asymptomatic family members.

Study phs001771

Genetic_mechanisms_of_resistance_to_chemotherapy_in_breast_cancer

Resistance towards chemotherapy is one of the main causes of treatment failure and deathamong breast cancer patients.The main objective of this project is to identify genetic mechanisms causing some breastcancer patients not to respond to a particluar type of chemotherapy (epirubicin) while otherpatients respond very well to the same treatment.In the project we will perform genome / exome sequencing of a selection of breast cancerpatients (n=30). These patients are drawn from a cohort where all patients have recievedtreatment with epirubicin monotherapy before surgical removal of a locally advanced breasttumour, and where all patients have been subjected to objective evaluation of the response tothe therapy.Subsequent to sequencing, we will analyse the data and compare with the clinical data foreach patient (object response to therapy). The main aim being to identify mutations that areassociated with resistance to epirubicin.Identification of mutations with strong predictive value, may have a direct impact on cancertreatment since it opens the possibility for genetic testing of a tumour, and desicion on whichdrug is likely to work best, prior to treatment start.

Study EGAS00001000276

Single Cell Sequencing of Sperm (scSperm)

The aim of this project is to genotype and sequence single spermatozoa from two men, one in his twenties and the other in his seventies. The resulting data is used to quantify the mutations that have arisen in the gametes of both individuals in order to better understand the effect of aging on mutation rates and modes.Project Outline. In order to quantify mutations, semen from two individuals are sequenced. 48 single sperm cells are isolated from each individual, and their DNA is extracted. The resulting genomes are amplified using PicoPlex, GenomiPhi MDA, Repli-G MDA, and MALBAC. QC step is applied to check the quality of WGA DNA using standard Sequenom plex (26 SNPs). A subset of 32 amplification products which pass the intiall QC, are genotyped using Affymetrix SNP6 chips. 12 of the genotyped amplification products are also sequenced. In addition, one multi-cell sample per individual is sequenced as a reference and for validation purposes.Altogether, 12 single cell sperm genomes and two multi-cell genomes are sequenced, coming to a total of 14 genomes. Of the single cell sperm genomes, 2 are sequenced to 50x coverage, and the other 10 to 25x coverage. Both multi-cell genomes are sequenced to 25x coverage.

Dataset EGAD00001001216

Whole genome sequencing data of pediatric B-other subtype acute lymphoblastic leukemia

For a long time, approximately 70% of childhood B-ALL cases could be classified routinely, and the remaining 30% were classified into the “B-other” group lacking the known genetic features. However, more recently, new genomic tools have uncovered new subtypes among the B-other groups. Approximately 10% of B-ALL cases lack the recurrent genetic abnormalities, and are referred as "B-other". They are typically more heterogeneous than other subtypes of B-ALL, and their prognoses are more variable. In a more recent update of the B-ALL classification, 27 subtypes were identified (Arber et al., 2022). The identification of some of these subtypes is dependent on NGS methods, such as RNA sequencing, which are not routinely used in all clinical laboratories. For example, ETV6::RUNX1-like and DUX4-rearranged subtypes have been identified using RNA sequencing. For this study, subtype predictions for some of the cases is acquired from ALLIUM (Krali et al., NPJ Precis Oncol., 2023) and ALLCatchR (Beder et al., Blood, 2022) based on the RNA-seq profiles.

Study EGAS50000001497

Relevance of TMPRSS2, CD163/CD206 and CD33 in clinical severity stratification of COVID-19

Our main objective is to incorporate new markers to classify COVID-19 patients based on mild or severe disease progression. To achieve this, we characterize SNP genotypes in critical genes involved in SARS-CoV infection (ACE2 (rs2285666), MX1 (rs469390), and TMPRSS2 (rs2070788) variants) and study the monocyte population by mass cytometry (CyTOF). Finally, the results obtained will be integrated to search for the best set of predictors of disease aggressiveness.

Study EGAS00001007003

Transcriptome analysis of endometrial organoids derived from patients with Mayer-Rokitansky-Küster-Hauser syndrome

The Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome is characterized by agenesis of the uterus and upper part of the vagina in females with normal ovarian function. The cause of the disease is still enigmatic. Here, we developed organoid cultures from endometrium found in uterine rudiment horns of MRKH patients. Phenotypically they share great similarity between healthy control organoids and are fully hormone responsive. Transcriptome analysis using RNA-seq identified possible disease-causing pathways altered in MRKH patients during development of the female reproductive tract. Thus, the organoid cultures provide a powerful research model for further insight into disease-causing alterations.

Study EGAS00001005908

Transcriptomic analysis of cell-of-origin CNS neuroblastoma, FOXR2 activated

The transcription factor FOXR2 is the universal driver of childhood central nervous system neuroblastoma, FOXR2 activated (NB-FOXR2). NB-FOXR2 tumors arise exclusively in the brain hemispheres, and despite morphological similarities to other pediatric brain tumors, they are a molecularly distinct entity based on DNA methylation profiling. The cell-of-origin is unknown. Here, we profiled a cohort of rare NB-FOXR2 tumors by bulk and single-cell transcriptomics. Through systematic comparative analyses, we delineate tumor transcriptional states and candidate cell-of-origin. More broadly, we demonstrate systematic molecular profiling of childhood cancers to orient oncogenic targeting for in vivo modeling, a critical resource for the study of rare tumors and development of therapeutics.

Study EGAS00001007247

Creatine in Huntington's Disease (HD) (CREST-E)

This is a multi-center, randomized, double-blind, placebo-controlled trial of creatine monohydrate involving 553 ambulatory subjects with HD who are not requiring skilled care or institutionalization. Eligible subjects were randomized to receive up to 40 grams daily of creatine monohydrate or matching placebo. Randomization will be followed by a Titration Phase, a Maintenance Phase, an Optional Extended Maintenance Phase, and Washout. During the Titration Phase, which may last up to six months, study drug will be initially escalated in 5-gram increments starting at 5 g/day until the 40 g/day target dose is reached. Should subjects be unable to reach or stay at the maximum dose during the Titration Phase, they will remain on the highest tolerated dose (HTD) for which they have no significant side effects. During the Maintenance Phase, subjects will be followed prospectively and systematically. Subjects completing 36 months of follow-up on study drug will be eligible to continue in the study for an additional twelve months of follow-up in the Extended Maintenance Phase. The primary measure of efficacy is the annualized rate of change in TFC. The primary hypothesis of the study is that chronic treatment of early-stage HD subjects with creatine monohydrate will slow the progressive functional decline of HD.

Study phs001488

Security Overview

Security Overview The European Genome-phenome Archive (EGA) houses consented human data under controlled access. Access decisions are handled by the relevant Data Access Committee (DAC), which autonomously manages requests through the DAC Portal. This document provides an overview of EGA’s practices in ensuring the security of data stored at EGA. As security is a prime concern of the EGA, the EGA is a member of the Global Alliance for Genomics and Health (GA4GH) Data Security work stream. The EGA contributes and helps develop the recommendations outlined the GA4GH Security Technology Infrastructure document, which defines guidelines, best practices, and standards for building and operating an infrastructure that promotes responsible data sharing in accordance with the GA4GH Privacy and Security Policy. Explore the EGA dataflow to gain deeper insights! Accessing data in the EGA involves several steps. First, users need to create an EGA account. Once logged in, they can request access to data controlled by a DAC through the EGA website (see documentation). The DAC oversees these requests through the DAC Portal, and if approved, grants the necessary permissions to the user's EGA account, allowing them to access and download all relevant data and metadata for the requested dataset(s). The key points of EGA security strategy are: 1 Regular Risk Assessment The EGA regularly identifies and assesses risk related to the following: Breach of confidentiality,Breach of privacy or autonomy,Malicious or accidental corruption or destruction of data archived at EGA,Disruption of services provided by the EGA. 2 Risk mitigation The EGA implements and maintains safeguards to minimise the risks identified above in accordance with the 6 control objectives listed in Appendix 1 and outlined in the GA4GH Security and Infrastructure document.If a breach is discovered, the EGA applies a defined protocol to minimise damage. 3 Identity and authorisation management The EGA authenticates the identity of individuals or software accessing controlled access data held at the EGA.The EGA ensures an appropriate level of assurance (LoA) is applied to the identity consistent with the risk associated with that individual, such as multi-factor authentication for DACs.The EGA provides the minimum access rights and privileges consistent with the user’s identity, allowing access consistent with the GA4GH Privacy and Security Policy, as determined by the appropriate DAC. 4 Audit Logs The EGA maintains a set of logs recording: Changes to user access rights,Data access requests,Resource usage. 5 Cryptography, communication security, and data integrity The EGA ensures data transmission integrity using a hash function.All data transmitted to or from the EGA is end-to-end encrypted.All data at EGA is stored using strong encryption.Encryption keys are not stored in the same system as the encrypted data.All data archived at EGA must be accompanied by a signed submission statement ensuring appropriate consent or ethical approval has been obtained, and is in accordance with all applicable laws and regulations. The EGA has a defined protocol defining the response in the event of a security breach, and is continuing to work with the GA4GH Data Security Work Stream to help define best practice and associated standards for breach responses. Appendix 1 GA4GH Control Objectives Control Objective 1: Implement technology safeguards to minimise the risk of unauthorised access, use, or disclosure of confidential and private data.Control Objective 2: Implement technology safeguards to minimise the risk of discovery, access, and use of individuals’ clinical and genomic data, and individual identities, other than as authorised by applicable jurisdictional law, institutional policy, and individual consents.Control Objective 3: Implement technology safeguards to minimise the risk of accidental or malicious corruption or destruction of data.Control Objective 4: Implement technology safeguards to minimise the risk of disruption, degradation, and interruption of services enabling access to data.Control Objective 5: Implement technology safeguards to minimise the risk of potential security attacks and misuse of authorised accesses and privileges.Control Objective 6: Implement technology safeguards to promptly detect the failure to attain the above control objectives and to respond with proper countermeasures.Appendix 2Refer to the document below to learn more about EGA long-term data preservation policy and procedures at EMBL-EBI.Long-term data preservation

Documentation about/security

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in 96.03 milliseconds.

Botensilimab, an Fc-enhanced Anti-CTLA-4 Antibody, is Effective Against Tumors Poorly Responsive to Conventional Immunotherapy

Fgl2 Regulates FcγRIIB+ CD8+ T Cell Responses during Infection

Data Access Committee KCL FC

High titers and low fucosylation of early phase anti-SARS-CoV-2 IgG promote hyper-inflammation by alveolar macrophages

MCF10A 12h IL6 classical signaling

MCF10A 24h IL6 classical signaling

Anti-TIGIT antibody tiragolumab improves PD-L1 blockade via myeloid and Treg cells

Characterization of a human iPSC-derived endocrine pancreas model

Expression profiling of a human endocrine pancreas iPSC model

A Dose Escalation Study of Efmarodocokin Alfa (UTTR1147A) in Healthy Volunteers and Patients with Ulcerative Colitis

Whole exome sequencing of endometriod ovarian cancer tumours

Ribo-depleted RNA-sequencing of II.3, III.1, and III.3

Characterizing the cell-free transcriptome in a humanized DLBCL patient-derived tumor xenograft model for RNA-based liquid biopsy in a preclinical setting

Phenotype information

RNAseq SCLC Cell lines MYC

Molecular Genetics of Schizophrenia - nonGAIN Sample (MGS_nonGAIN)

Whole Genome Association Study of Bipolar Disorder

Barrett's and Esophageal Adenocarcinoma Genetic Susceptibility Study (BEAGESS)

MicroRNAs, Hypertension and End Organ Damage in Humans

Integrating molecular imaging and transcriptomic profiling in advanced HER2-positive breast cancer receiving trastuzumab emtansine (T-DM1): an analysis of the ZEPHIR clinical trial

Foregut Microbiome in Development of Esophageal Adenocarcinoma

Somatic Mutations and Their Etiological Determinants for Breast Cancer in African American Women (B-CAUSE Study)

Genome-Wide Association Study of Schizophrenia

Kids First: Genomic Analysis of Esophageal Atresia and Tracheoesophageal Fistulas and Associated Congenital Anomalies

Cincinnati Children's Hospital Medical Center (CCHMC) - eMERGE Phase IIIA Data

Alcohol Dependence GWAS in European- and African Americans

DAC Ghent University - Department of Movement and Sports Sciences

RNA-seq of high grade serous ovarian tumours

RNA-seq of high grade serous ovarian tumours

Episodic Ataxia Syndrome: Longitudinal Study

A Retrospective and Cross-Sectional Analysis of Patients Treated for SCID Since January 1, 1968

WES Elucidation of Pathogenetic Mechanisms for Immune System Disorders and NIAID Pilot of Genetic Incidental Finding Management

NINDS Family-Based Whole-Genome Sequencing to Find Modifiers of Age of Onset in Huntington's Disease

Sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC)

Ensemble learning for classifying single-cell data and projection across reference atlases

med-pchic-dac

North Carolina Clinical Genomic Evaluation by NextGen Exome Sequencing (NCGENES)

GEDI: A Developmental Model of Gene-Environment Interplay in SUDs: Combined Genotype Dataset from the "Great Smoky Mountains Study" and the "Caring for Children in the Community Study".

Nivolumab and Tumor Infiltrating Lymphocytes (TIL) in Advanced Non-Small Cell Lung Cancer

High-depth whole genome sequencing of paired ductal carcinoma in-situ (DCIS) and germline control samples from 26 individuals.

Natural History of and Genetic Modifiers in Spinocerebellar Ataxias

North American Mitochondrial Disease Consortium Patient Registry and Biorepository

Best Practices for DACs

Comparison of 3 protocols for deriving pancreatic progenitors from hPSCs (RNA-seq)

Adolescent Idiopathic Scoliosis (AIS) 1000 Exomes Study

Evolutionary origin and methylation status of human intronic CpG islands that are not present in mouse

Federated EGA

Systematic identification of long non-coding RNAs potentially involved in gastrointestinal carncer

Molecularly matched targeted therapies plus radiotherapy in patients with newly diagnosed glioblastoma without MGMT promoter hypermethylation (N2M2/NOA-20 phase I/IIa umbrella trial)

A Genome-Wide Association Study on Cataract and HDL in the Personalized Medicine Research Project Cohort

Determining Genetic Role in Treatment Response to Anti-Platelet Interventions (The PAPI Study)

Establishment of an iPSC Repository Derived from Healthy Volunteers

Recurrent somatic DICER1 mutations in non-epithelial ovarian tumors

Analyzing Somatic Mutagenesis in Systemic Sclerosis

The ICGC-TCGA DREAM Somatic Mutation Calling - Tumour Heterogeneity Challenge

A Chromatin Accessibility Atlas of the Developing Human Telencephalon

NHLBI TOPMed: Best ADd-on Therapy Giving Effective Response (BADGER)

ACTIV-6: COVID-19 Outpatient Randomized Trial to Evaluate Efficacy of Repurposed Medications

Substance Dependence GWAS in European- and African - Americans

Foregut Microbiome and Risk of Gastric Intestinal Metaplasia, and Gastric Cancer Risk

FEGA FAQs: a summary of the Q+A session from the FEGA workshop at ELIXIR AHM 2024

Prostate Cancer Upgrading Reference Set

NHLBI TOPMed - NHGRI CCDG: The BioMe Biobank at Mount Sinai

Detection of cancers three years prior to diagnosis using plasma cell-free DNA

Single_Cell_Sequencing_of_Sperm__scSperm_

Genome-wide DNA-methylation assessment by MethylCap-seq and Infinium HumanMethylation450 BeadChips: an independent large-scale comparison

Somatic Genome Dynamics of Barrett's Esophagus Patients with Non-Cancer and Cancer Outcomes

What is a DAC?

Stratton__WGS___RCC___Japan

Autoimmune-wide landscape of circulating CD4+ T cells unveils disease-specific heritability and phenotypic changes

Aspirin and Inflammation: Mutations, Genes, Pathways and Prevention in Barrett's Esophagus

The Pioneer 100 Wellness Project (P100)

Gabriella Miller Kids First Pediatric Research Program in Enchondromatoses and Related Malignant Tumors

Investigating Host Genetic Risk Factors for Tuberculosis in Highly Endemic South African Populations

DNA methylation database for gynecological cancer detection, classification and assay development

A Cancer Cell-Line Titration Series for Evaluating Somatic Classification

Differential Transcription Start Site Usage in Brain-related Samples

NIHR BioResource Common Disease Patients 2016

StrattonWGS_RCC___Japan

StrattonWGS_Identification_of_Early_Life_Exposures_in_Paediatric_Colonic_Crypts_of_Healthy_Individuals