Search Results - EGA European Genome-Phenome Archive

IL2 data set including 59 samples

The dataset is referenced by EGA Study ID EGAS00001003605, which includes the short-reads data for 59 samples. All short-reads data files are in fastq format.

Dataset EGAD00001004967

WES melanoma biopsies (UV1-hTERT-mm)

The dataset contains phenotypes of 14 melanoma biopsies sequenced in connection with the study UV1-hTERT-mm, where the thereapeutic cancer vaccine UV1 is combined with ipilimumab in treatment of melanoma patients.

Dataset EGAD00001007648

Trio Sequencing results for the AnkyrinG MIPS screening study

Approximately 1000 trio's with varying degrees of cognitive disorders. All samples have been sequenced for the AnkyrinG interactome using MIPS technology. Data is presented as BAM and unfiltered VCF files.

Dataset EGAD00001006823

Nanopore medulloblastoma data

Nanopore data from 3 medulloblastoma samples of which 2 are tumor-normal pairs sequenced with the MinIon and one is tumor only data sequenced on the PromethIon. The data consists of BAM files aligned using minimap2

Dataset EGAD00001010851

Colon adenomas and adenocarcinomas and matched mucosae

Whole exome sequencing of neoplastic colorectal lesions, matched normal mucosa and peripheral blood leucocytes from 7 individuals. Data is contained within FASTQ files.

Dataset EGAD00001010875

Homozygous inactivation of CHEK2 is linked to a familial case of multiple primary lung cancer with accompanying cancers in other organs

In clinical practice, there are a number of cancer patients with clear family histories, but not belonging to existing familial malignancies. Recent advances in genomic technologies have enhanced the possibility of identifying causative genes in such cases. Two siblings, an elder sister and a younger brother, were found to have multiple primary lung cancers at the age of 60. The former subsequently developed breast cancer, and had a history of myoma uteri. The latter had initially developed prostate cancer at the age of 59, and had a history of colon cancer. SNP genotyping revealed that approximately 10% of the genomes were homozygous in both patients. Exome sequencing revealed non-synonymous mutations in four genes in the runs of homozygosity: CHEK2, FCGRT, INPP5J, and SFI1. Evolutionary conservation of primary protein structures suggested the functional importance of the CHEK2 mutation, R474C. This mutation altered the tertiary structure of CHK2 by disrupting the salt bridge between R474 and E394. No such structural changes were observed with the other three mutated genes. Subsequent cell-based transfection analysis revealed that CHK2 R474C was unstable and scarcely activated. We concluded that CHEK2 is a causative gene in this case of familial cancer. Although homozygous inactivation of CHEK2 in mice led to cancers in multiple organs, accumulation of additional human cases is needed to establish its pathogenic role in humans.

Study JGAS000057

First datasets available in the Federated EGA Network

In February 2024, a great milestone was reached for the human omics data community: the first datasets are now available in the Federated European Genome-phenome Archive (FEGA). These datasets - hosted by national nodes in Poland, Norway, and Sweden - are discoverable in the EGA portal and accessible according to national laws. These datasets include: From FEGA Poland - The Genomic Map Of Poland From FEGA Norway - CRCbiome: Gut metagenome of Norwegian screening participants using FIT sampling Also from FEGA Norway - Single cell transcriptomics in expanded Tregs of APS-1 patients From FEGA Sweden - A Combined Omics and Tissue Biobank for Paediatric Cancers The establishment of these datasets represents a significant step towards achieving the broader objectives of the FEGA; to facilitate the sharing of high-quality human genomic and phenotypic data across borders. “The value for users is twofold: it becomes easier to make data available securely compared to storing data locally, and data becomes easier to find for other researchers. The possibility of reuse improves the chances of both verifying scientific discoveries and reaching groundbreaking conclusions, of benefit to the research community and later also patients,” said Anna Hagwall, project manager and head of human data at FEGA Sweden, NBIS. About Federated EGA FEGA was launched in 2022 as a network to store and lawfully share sensitive human omics data safely. It relies on the technology originally developed by the EGA and support from ongoing collaborations with ELIXIR - a European life sciences infrastructure. FEGA has contributed to and benefitted from the implementation of community standards for sensitive data management including those developed by the Global Alliance for Genomics and Health (GA4GH). “The FEGA concept and the development of the Nordic FEGA nodes have been made possible thanks to several projects coordinated by NeIC,” said Kjell Petersen, FEGA Norway technical lead. Managing human omics data is challenging due to its sheer size and privacy concerns, often resulting in restrictions on how and where sensitive data can be shared. The FEGA network follows a federated data access model whereby sensitive data is stored securely within a local or national jurisdiction, while discovery across the network for data of interest is enabled via a central portal. As of February 2024, the FEGA network comprises seven European national nodes with tens of additional national partners working towards establishing a FEGA node. As the FEGA network continues to onboard nodes from around the world, populated with more and more data, we move closer to a vision of a truly global resource for discovery of and access to sensitive human omics data to accelerate disease research and improve human health. "The Federated EGA network is entering a key phase where the first research datasets are now available across the network. In coming years, we look forward to expanding these datasets to cover key areas such as cancer and rare diseases for the benefit of patients" said Thomas Keane, Group Leader at EMBL-EBI.

Blog first-datasets-available-in-Federated-EGA

Center for Common Disease Genomics [CCDG] - Cardiovascular: The Genetics of Atrial Fibrillation

This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1 . Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules.Source: https://ccdg.rutgers.edu/sites/default/files/CCDG_CVD_EOAF_FINAL_w_link.pdfFor this study, The Broad Institute of MIT and Harvard generated genetic data for UWO Genetic Investigation of Supraventricular Tachycardias.Patients confirmed to possess a supraventricular tachycardia and/or an accessory pathway at the time of invasive electrophysiology study at the London Health Sciences Centre, London, Ontario, Canada were eligible for enrollment. Potential supraventricular tachycardias included atrioventricular nodal reentrant tachycardia (AVNRT), atrioventricular reentrant tachycardia (AVRT), atrial tachycardia, junctional tachycardia, atriofascicular tachycardia, nodofascicular tachycardia, and nodoventricular tachycardia. Patients that did not have inducible supraventricular tachycardia, but had an accessory pathway that conducted antegrade, retrograde, or both, were also eligible for enrollment. All patients additionally underwent, at minimum, a clinical history, physical examination, 12-lead ECG, and echocardiogram. Study participants provided informed written consent under a protocol approved by the research ethics board of Western University.Raw sequencing data, metadata, vcf and phenotype data at individual level are available at https://anvilproject.org/data For questions about availability contact help@lists.anvilproject.org.

Study phs002811

Center for Common Disease Genomics [CCDG] - Cardiovascular: Pharmacokinetic Polymorphisms in Japanese General Population

This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1 . Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules.Source: https://ccdg.rutgers.edu/sites/default/files/CCDG_CVD_EOAF_FINAL_w_link.pdfAnalysis of 165 pharmacokinetic-related gene polymorphisms (the number of polymorphisms may increase) using DNA derived from the blood of approximately 1,000 Japanese general populations. Tokai University School of Medicine Molecular Life Sciences 2 Isogo Lab has been trying to find new genes which contribute to the development of multiple diseases and to develop new methods for human genome diversity analysis that will lead to the development of technology for disease screening by finding genes related to diseases and incorporating gene analysis technology. Using this method, we are trying to clarify the relationship between the characteristics of rheumatoid arthritis and psoriasis vulgaris and genes to seek effective treatments and prevention methods. Raw sequencing data, metadata, vcf and phenotype data at individual level are available at https://anvilproject.org/data. For questions about availability contact help@lists.anvilproject.org.

Study phs002985

NHLBI TOPMed - NHGRI CCDG: The Johns Hopkins University School of Medicine Atrial Fibrillation Genetics Study

Atrial fibrillation (AF), the most common sustained cardiac arrhythmia, is the primary cause of many hospital admissions, and is associated with significant secondary morbidity by increasing the risk of stroke, heart failure, and all-cause mortality. The incidence of AF is on the rise, and it is projected that by the year 2050 more than 10 million patients will be affected by AF in the United States alone. Anti-arrhythmic medications have limited success in maintaining sinus rhythm, are associated with side effects, and appear ineffective at reducing mortality compared to a strategy of rate control and anticoagulation. Given the significant morbidity associated with this common arrhythmia, surgical and catheter ablation techniques have been developed to treat AF. However, despite the incorporation of various strategies for ablation, long-term recurrence rates of AF remain higher than 25 percent after ablation. Current techniques for catheter ablation of AF include pulmonary vein isolation and complex fractionated atrial electrogram (CFAE) ablation. However, the contribution of each strategy to long-term procedural success and the relative importance of each strategy for different patients remain unknown. Recent advances in cardiac imaging have allowed detailed analysis of left atrial myocardial anatomy. Parallel advances in molecular genetics have identified several candidate genes involved in familial and non-familial AF. However, the pathophysiology of AF generation and maintenance, and the potential contribution of such genetic or anatomic substrates for patient selection, and for target identification during catheter ablation have not yet been examined. Advances in molecular genetics and imaging, coupled with techniques for endocardial and epicardial mapping in the electrophysiology laboratory present an opportunity to significantly improve our understanding of (1) The relation of paroxysmal versus persistent AF with (a) structural left atrial changes (left/right atrial scar, wall thinning, pulmonary vein anomalies, and coronary sinus dilation) and with (b) candidate genetic variants. (2) The relation of candidate genetic variants with (a) structural left atrial changes and with (b) electrophysiologic properties (atrial effective refractory period (AERP) inhomogeneity, voltage abnormalities, trigger burden and location, C FAE extent and location), (3) The relation of structural left atrial changes with (a) CFAE location as targets for catheter ablation and with (b) reversible conduction block/myocardial injury after pulmonary vein isolation, and (4) Individualized endocardial targets for AF ablation based on candidate genes and anatomic substrates. The proposed study will improve our understanding of the underlying pathophysiology of AF, and may improve current techniques for treatment of this important arrhythmia.

Study phs001598

High density copy number analysis and whole exome sequencing of unselected chronic lymphocytic leukemia cases and of paired chronic lymphocytic leukemia and Richter Syndrome cases

Analysis of the chronic lymphocytic leukemia coding genome: role of NOTCH1 mutational activation The pathogenesis of chronic lymphocytic leukemia (CLL), the most common leukemia in adults, is still largely unknown since the full spectrum of genetic lesions that are present in the CLL genome, and therefore the number and identity of dysregulated cellular pathways, have not been identified. By combining next-generation sequencing and copy number analysis, we show here that the typical CLL coding genome contains less than 20 clonally represented gene alterations/case, including predominantly non-silent mutations and fewer copy number aberrations. These analyses led to the discovery of several genes not previously known to be altered in CLL. While most of these genes were affected at low frequency in an expanded CLL screening cohort, mutational activation of NOTCH1, observed in 8.3% of CLL at diagnosis, was detected at significantly higher frequency during disease progression toward Richter transformation (31.0%) as well as in chemorefractory CLL (20.8%). Consistent with the association of NOTCH1 mutations with clinically aggressive forms of the disease, NOTCH1 activation at CLL diagnosis emerged as an independent predictor of poor survival. These results provide initial data on the complexity of the CLL coding genome and identify a dysregulated pathway of diagnostic and therapeutic relevance. Genetic Lesions associated with Chronic Lymphocytic Leukemia transformation to Richter Syndrome Richter syndrome (RS) derives from the rare transformation of chronic lymphocytic leukemia (CLL) into an aggressive lymphoma, most commonly of the diffuse large B cell type (DLBCL). The molecular pathogenesis of RS is only partially understood. By combining whole-exome sequencing and copy-number analysis of 9 CLL-RS pairs and of an extended panel of 43 RS cases, we show that this aggressive disease typically arises from the predominant CLL clone by acquiring an average of ~20 genetic lesions/case. RS lesions are heterogeneous in terms of load and spectrum among patients, and include those involved in CLL progression and chemorefractoriness (TP53 disruption and NOTCH1 activation) as well as some not previously implicated in CLL or RS pathogenesis. In particular, disruption of the CDKN2A/B cell cycle regulator locus is associated with ~30% of RS cases. Finally, we report that the genomic landscape of RS is significantly different from that of de novo DLBCL, suggesting that they represent distinct disease entities. These results provide insights into RS pathogenesis, and identify dysregulated pathways of potential diagnostic and therapeutic relevance.

Study phs000364

A Genomic Atlas of Systemic Interindividual Epigenetic Variation in Humans (GTEx)

Methylation of cytosines in CpG dinucleotides is an epigenetic mechanism with essential roles in mammalian development. To explore its functions in cellular differentiation, unbiased analysis of CpG methylation by whole genome bisulfite sequencing (WGBS) has been used to characterize epigenetic differences among different human tissues and cell types. Meanwhile, human interindividual variation in DNA methylation that is not cell-type specific has attracted relatively little attention. Systemic interindividual epigenetic variation is important, however, because like genetic variation it is a potential determinant of phenotypic variation and can be assessed in any easily obtainable DNA sample. Since systemic epigenetic variants originate in the preimplantation embryo, their establishment can be influenced by periconceptional environment, and potentially provide information about lifetime risks relevant to global health, obesity, and cancer. We elucidated systemic interindividual variation in CpG methylation in the human genome. We studied brain, heart, and thyroid tissues (representing all three germ layer lineages) from each of 10 donors in the NIH Gene-Tissue Expression (GTEx) project. We performed deep whole genome bisulfite sequencing for these 30 samples, achieving a sequencing depth of over 50x coverage per sample. We identified 9,926 correlated regions of systemic interindividual variation (CoRSIVs). These regions, comprising just 0.1% of the human genome, often correlate with one another over long genomic distances, are associated with transposable elements and subtelomeric regions, conserved across various human ethnic groups, and particularly sensitive to periconceptional environment. While genetic variation appears to influence methylation at most CoRSIVs, many show no evidence of genetic influence, suggestive of 'pure' epigenetic variation. At CoRSIVs, interindividual variation in DNA methylation in an easily biopsied tissue predicts expression in other tissues, and genes associated with these loci are implicated in a range of human disorders. In addition to charting a previously unrecognized molecular level of human individuality, this atlas of human CoRSIVs provides a resource for future population-based investigations into how interindividual epigenetic variation modulates risk of disease.Version 2 now also includes Target Capture Sequencing of CoRSIVs in 808 tissues (188 GTEx Donors). Focusing on the CoRSIVs identified by analyzing WGBS data, a Target Capture Bisulfite sequencing assay was developed. Using the genotype data of 188 GTEx donors, we assessed mQTL by capturing a 1MB region at each CoRSIV and quantifying methylation by Bisulfite-seq. The Target Capture Bisulfite sequencing data will be available to download via the AnVIL project.

Study phs001746

The Lung Genomics Research Consortium (LGRC)

Chronic lung diseases represent a broad spectrum of chronic fibrosing/inflammatory lung conditions that are for the most part poorly responsive to treatment and often fatal. COPD/emphysema is the fourth leading cause of death in the United States and the incidence and rate of death from pulmonary fibrosis is increasing each year. Although progress has been made in interpretation of the clinical, radiological, and pathological features of chronic lung disorders, and progress in determining the pathobiology continues, the causes, biologic mechanisms, and therapeutic options remain obscure. Moreover, predicting individuals or populations at risk for developing any of these complex diseases, at present, is not possible. To address this challenge, we plan to create a genetic, molecular, and quantitative clinical phenotyping data warehouse with bioinformatic tools that will empower investigators to make fundamental discoveries in disease pathogenesis, refine diagnostic criteria, and lead to real gains in personalized medicine. The composite genetic, genomic, and epigenetic signature combined with quantitative clinical phenotypes has the potential to characterize the dynamic biological state of a complex disease and complement existing diagnostic approaches that are reliant on traditional clinical measures of disease. In the proposed project, we plan to extend the scope and impact of the NHLBI Lung Tissue Research Consortium (LTRC) biorepository by creating the Lung Genomics Research Consortium (LGRC), a comprehensive genetic, molecular, and quantitative clinical phenotyping warehouse. Our overall hypothesis is that a genetic, molecular, and quantitative clinical phenotyping warehouse combined with a rich clinical database will enable the lung research community to make fundamental discoveries in disease pathogenesis, refine diagnostic criteria, and lead to real gains in personalized medicine. We plan to pursue this hypothesis through the following aims. Specific Aim 1: Establish a genetic, genomic, and epigenetic molecular library to complement the existing clinical database in the LTRC. Specific Aim 2: Develop a quantitative clinical phenotyping platform using existing LTRC data, as well as an enhanced data set including novel quantitative CT and histology imaging analyses. Specific Aim 3: Establish a publicly-accessible database that would integrate the genetic, molecular, and quantitative phenotyping data with the existing clinical data in the LTRC and provide query and data exploration tools that are easily accessible to the lung research community. These discoveries will enable clinicians to Identify individuals at risk of developing chronic lung diseases; Diagnose these conditions earlier; Identify novel mechanisms that cause these diseases; Reclassify disease entities into categories more representative of molecular and cellular pathogenic mechanisms regardless of traditional disease categories; develop personalized approaches to treatment.

Study phs000624

Center for Oral Health Research in Appalachia (COHRA) Genomic Studies of Oral Health and Disease

The purpose of this project is to identify the genetic factors contributing to dental caries in children and adults. The datasets come from the Center for Oral Health Research in Appalachia (COHRA), which has the long-term goal of determining the sources of oral health disparities in a high risk, Northern Appalachian population so that effective preventive interventions can be designed and targeted. The Specific Aims of this project are to perform genome-wide association scans of dental caries of the (1) primary dentition in children, and (2) permanent dentition in adults, to identify novel risk variants and to replicate previously nominated risk variants. This project brings together samples from three cohorts: COHRA1 is a cross-sectional cohort comprising members of 862 northern Appalachian families; approximately 80% of the cohort has been previously genotyped by the Center for Inherited Disease Research with support from NIDCR using the Illumina Quad W array (see dbGaP Study Accession: phs000095.v3.p1). Dental SCORE is a cross-sectional cohort comprising approximately 550 unrelated individuals who underwent the same data collection protocol as COHRA1. COHRA2 is an ongoing longitudinal cohort that recruited approximately 1100 northern Appalachian women during pregnancy, and followed them and their children through their children's early childhood; the current project period will continue data collect though age 6 of the child. Phenotypes for this project were derived from intra-oral examinations performed by trained and calibrated research hygienists. In brief, each tooth was recorded as present or absent, and each surface of each present tooth was scored for evidence of decay. From these data, dental caries indices were generated. This project contains two phases of genotyping: (1) collection of exome SNP Chip data for the previously genotyped COHRA1 samples, and (2) collection of whole-genome SNP Chip data for the remaining COHRA1 samples and all Dental SCORE and COHRA2 samples. These data will support efforts to test hypotheses regarding the causal relationships of risk factors contributing to the unusually high rates of caries formation in the Appalachian population. Ultimately, these data may inform the development of an integrated model of caries risk, in which the effects of genetics, oral ecology, diet, and other environmental/psychosocial factors and behaviors are modeled in concert to explain the disparities, including the high rate of caries onset before age 6. The gene-mapping Aims of this project, which seek to identify the genetic factors that contribute to caries risk, are a requisite step in realizing this integrated model.

Study phs001591

RNA_seq_analysis_of_transcriptome_variation_with_human_ESC_subclones

Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progenyThis 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 EGAS00001001655

DNA methylomes of monozygotic twins clinically discordant for multiple sclerosis

Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system. Although genetic susceptibility is important, a modest concordance rate for MS in monozygotic (MZ) twins suggests that interaction with other risk factors is required to develop clinical symptoms. In this study, we examined whether DNA methylation differences contribute to the discordant clinical manifestation of MS in MZ twins, and studied the impact of MS treatments on the DNA methylome. Genome-wide DNA methylation profiles of peripheral blood mononuclear cells (PBMCs) of 45 MZ twins clinically discordant for MS were generated using the Illumina HumanMethylationEPIC array. Repetitive element methylation and selected differentially methylated positions (DMPs) were validated using targeted deep bisulfite sequencing (TDBS). In addition, we performed whole genome bisulfite sequencing (WGBS) to profile CD4+ memory T-cells of a subset of four MS discordant MZ twins. Our results show that interferon treatment causes robust DNA methylation changes and several epigenetic biomarkers for interferon treatment response were identified. However, overall the PBMC-based methylomes of the MS discordant MZ twins were highly similar, since large systematic methylation differences (>5%) were absent in the data. This suggests that previously reported large methylation changes are probably caused by genetic rather than epigenetic differences. In addition, our data does not support the hypothesis that the observed maternal parent-of-origin effect in MS is due to genomic imprinting errors, and no evidence was found that copy number variations explain the discordant phenotype in these MZ twins. Although not genome-wide significant, a couple of DMPs associated with the MS phenotype were identified and successfully technically replicated using TDBS, including a differentially methylated region (DMR) in the promoter of the transmembrane protein encoding gene TMEM232. Another MS-associated DMP, located in an enhancer in the gene body of the transcription factor ZBTB16, was also associated with medium-term glucocorticoid treatment history. WGBS analysis confirmed this DMP as a promising epigenetic biomarker for glucocorticoid treatment. In conclusion, this epigenome-wide association study (EWAS) in genetically identical twins identified a DMR in the TMEM232 promoter as a candidate loci associated with the clinical manifestation of MS. In addition, epigenetic biomarkers for MS treatments were identified, revealing that not only short-term, but also medium-term treatment effects are detectable in immune cells, which should be taken into account in future EWAS designs.

Study EGAS00001003147

PSCP_bisulphite_analysis_in_hESCs

Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny. 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 EGAS00001001625

PSCP_mutation_analysis_in_hESCs

Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny. This data is part of a pre-publication release. For information on the proper use of pre-publication data shred by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Study EGAS00001001561

EGA synthetic data

Synthetic Data One of the limitations in genomics research is that human genomics data is not openly available; access must be controlled according to participant consent agreements and data protection regulations such as GDPR. Obtaining authorization to access such data can sometimes take a long time, resulting in delays to important research work. In this context, synthetic genomic and phenotype data can be useful resources for researchers to avoid these delays. Synthetic data are artificially generated datasets, often created with algorithms, which can be used without the need for authorization to test new products and tools, build technical demonstrators, validate data models, and train AI models. The EGA provides access to synthetic cohort datasets augmented with rich synthetic metadata that overcomes these real data usage restrictions. Whilst synthetic datasets are not included in the general EGA mandate and services, we can consider such submissions and evaluate their acceptance on the basis of their unique use cases not already covered by existing synthetic datasets. Access to synthetic data studies is managed by the EGA Helpdesk Data Access Committee. Study ID Title Located in EGAS00001002472 CINECA synthetic cohort EUROPE UK1 referencing fake samples Central EGA EGAS00001005591 Synthetic data - Genome in a Bottle Central EGA EGAS00001005042 Test Study for EGA using data from 1000 Genomes Project - Phase 3 Central EGA EGAS00001005702 Human genomic and phenotypic synthetic data for the study of rare diseases Central EGA EGAS50000000190 EOSC4Cancer Synthetic Colorectal Cancer Genomic data Central EGA EGAS50000000086 Synthetic - FEGA Sweden Heilsa synthetic dataset December 2023 Federated EGA Sweden EGAS50000000678 Synthetic - GDI synthetic data Federated EGA Spain

Documentation synthetic-data

Memory-like HCV-specific CD8+ T cells retain a chronic scar after cure of chronic HCV infection

Chronic hepatitis C virus (HCV) infection is associated with CD8+ T-cell exhaustion characterized by limited effector functions and thus compromised anti-viral activity. Exhausted HCV-specific CD8+ T cells are comprised of memory-like and terminally exhausted CD8+ T-cell subsets. So far, little is not known about the molecular profile and fate of these cells after elimination of chronic antigen stimulation by direct acting antiviral therapy (DAA). Here, we report an antigen-driven molecular core signature underlying exhausted CD8+ T-cell subset heterogeneity in chronic viral infection with a progenitor/progeny relationship of memory-like and terminally exhausted HCV-specific CD8+ T cells via an intermediate stage. Furthermore, transcriptional profiling reveals that the memory-like cells remain after DAA-mediated cure while terminally exhausted HCV-specific CD8+ T-cell subsets are lost. Thus, the memory polarization of the overall HCV-specific CD8+ T-cell response after cure does not result from re-differentiation of exhausted T cells. Consequently, antigen elimination has little impact on the exhausted core signature of memory-like CD8+ T cells that remains clearly different from bona fide T-cell memory. These results identify a molecular signature of T-cell exhaustion that is imprinted like a chronic scar in HCV-specific CD8+ T cells even after HCV cure, highlighting the requirement of re-programming to elicit full effector potential of exhausted T cells.

Dataset EGAD00001006259

The Finland-United States Investigation of NIDDM Genetics (FUSION) Tissue Biopsy Study

The Finland-United States Investigation of NIDDM Genetics (FUSION) study is a long-term effort to identify genetic variants that predispose to type 2 diabetes (T2D) or that impact the variability of T2D-related quantitative traits (QTs). Most of the variants associated with T2D and related traits (glucose and insulin, anthropometrics, lipids) through genome-wide association studies (GWAS) occur in non-coding regions, suggesting a strong regulatory component to disease susceptibility. Regulatory element activity is often tissue-specific, which further complicates discovery of the causal/functional variation. Therefore, there is a critical need to identify the appropriate cell type, regulatory elements, target genes, and causal variants(s) in T2D-relevant tissues. We hypothesize that a subset of T2D and related variants alter gene expression regulation in skeletal muscle and adipose tissue - two major insulin target tissues and play key roles in insulin resistance. To that end, our study contains a comprehensive survey of genomics, epigenomics and transcriptomics in skeletal muscle and adipose tissue from individuals with glucose tolerance categories ranging from normal to T2D.For this FUSION Tissue Biopsy Study, we obtained RNA-Seq, microRNA (miRNA)-Seq, and DNA methylation (methyl)-Seq data on biopsy samples from 331 individuals from across the range of glucose tolerance: 124 normal glucose tolerance (NGT), 77 impaired glucose tolerance (IGT), 44 impaired fasting glucose (IFG), and 86 newly-diagnosed T2Ds. Participants completed two study visits, two weeks apart. First visits comprised most of the clinical phenotyping, including four-point OGTT (fasting, and 30, 60, and 120 minute post-load); BMI, WHR; lipids; blood pressure; and many other variables. Participants also completed FUSION health history, medication, and lifestyle questionnaires. On the second visit, we obtained ~250mg vastus lateralis skeletal muscle, ~750mg abdominal subcutaneous adipose, and a ~5x15mm section of abdominal skin. Visits were completed in March 2013. RNA isolation is ongoing in the Collins laboratory at the NIH, RNA and miRNA sequencing at the NIH Intramural Sequencing Center (NISC), and genotyping at the Center for Inherited Disease Research (CIDR). Individual-level data is available here for the 306 individuals who consented to data deposit. To focus on evaluation of gene expression and its regulation in skeletal muscle, we analyzed mRNA extracted from vastus lateralis skeletal muscle obtained from 271 of the 331 individual subjects from Finland, along with genome-wide genotypes. Individual-level data is available here for the 250 subjects who consented to the use of their data.Release phs001048.v2.p1 adds muscle data for an additional 42 subjects and data from adipose tissue for 276 subjects. Total RNA was isolated using Trizol extraction in the Collins laboratory at the NIH. The mRNA was poly-A selected, 24-plex libraries were generated using the Illumina TruSeq directional mRNA-seq library protocol and RNA sequencing was performed on HiSeq2000 sequencers using 101bp paired-end reads at NISC. miRNA libraries were prepared from total RNA from 296 muscle and 270 adipose samples, pooled and sequenced 50bp single-end reads on Illumina HiSeq2500. Data for 272 muscle and 251 adipose samples are available here for individuals with consent for data deposit. DNA was extracted from blood in the Collins laboratory, and genotyping on the Illumina Omni2.5M array was performed at CIDR. Genotypes were imputed using the HRC 2016 reference panel. In order to assess regions of open chromatin in skeletal muscle, we obtained muscle tissue from a commercial provider to perform ATAC-seq; these samples were sequenced at the University of Michigan DNA Sequencing Core.Release phs001048.v3.p1 adds single-nucleus (sn) RNA-seq and ATAC-seq data in 287 skeletal muscle samples out of the original 331 individuals. Individual-level data is available here for the 265 subjects who consented to the use of their data. The frozen tissue biopsy samples were processed in ten batches, each consisting of 40-41 samples. These batches were organized using a randomized block design to protect against experimental contrasts of interest including cohort, age, sex, BMI among others. Samples in each batch were pulverized, pooled together followed by nuclei isolation. The nuclei were processed on the 10X Genomics Chromium platform separately for snATAC-seq and snRNA-seq (v. 3.1 chemistry for snRNA-seq).Release phs001048.v4.p1 adds additional phenotypes and provides some corrections to several previous phenotypes.

Study phs001048

Meniere Disease Genomic Data Access Committee

This Data Access Committee is responsible for reviewing and managing data access requests related to genomic variant files from whole exome sequencing of patients diagnosed with Meniere disease. This includes data from both familial and sporadic forms of the disease.

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