Search Results - EGA European Genome-Phenome Archive

Ischemia Reperfusion Responses in Human Lung Transplants at the Single Cell Resolution

Ischemia reperfusion is an unavoidable step of organ transplantation. Development of therapeutics for lung injury during transplantation has proved challenging; understanding lung injury from human data at the single cell resolution is required to accelerate the development of therapeutics. Donor lung biopsies from six human lung transplant cases were collected at the end of cold preservation and 2-hour reperfusion and underwent single cell RNA sequencing. Donor and recipient origin of cells from the reperfusion timepoint were deconvolved. Gene expression profiles were (1) compared between each donor cell type between timepoints and (2) compared between donor and recipient cells. Inflammatory responses from donor lung macrophages were found after reperfusion with upregulation of multiple cytokines and chemokines, especially IL-1 and IL-1. Significant inflammatory responses were found in alveolar epithelial cells (featured by CXCL8) and lung endothelial cells (featured by IL-6 upregulation). Different inflammatory responses were noted between donor and recipient monocytes and CD8+ T cells. The inflammatory signals and differences between donor and recipient cells observed provide insight into the cellular and molecular mechanisms of ischemia reperfusion induced lung injury. Further investigations may lead to the development of novel targeted therapeutics.

Study EGAS50000000490

Distinct immune cell infiltration patterns in PDAC exhibit divergent immune cell selection and immunosuppressive mechanisms

Pancreatic ductal adenocarcinoma has a dismal prognosis. A comprehensive analysis of single-cell multi-omic data from matched tumour-infiltrated CD45+ cells and peripheral blood in 12 patients, and two published datasets, reveals a complex immune infiltrate. Patients have either a myeloid-enriched or adaptive-enriched tumour microenvironment. Lymphocyte enrichment is intrinsically linked with highly distinct B and T cell clonal selection, diversification, and differentiation. Using TCR data, we see the largest clonal expansions in CD8 effector memory, senescent cells, and highly activated regulatory T cells which are induced within the tumour from naïve cells. We identify pathways that potentially lead to a suppressive microenvironement, including targets of immunotherapy and checkpoints including TIGIT/PVR and SIRPA/CD47. PDAC patient tumors from the APACT clinical trial revealed that patients with myeloid enrichment had the shorter overall survival compared to those adaptive cell enrichment. We identify multiple therapeutic targets that should form the basis for rational design including boosting of B cell responses, targeting immunosuppressive macrophages, and specific Treg depletion approaches. The dataset is scRNA-seq data from PDAC patients.

Study EGAS50000000726

Mind Body Study: A Sub-Study on Psychosocial Factors and Microbiomes of Nurses in the Nurse's Health Study II

The Mind-Body Study is a sub-study of the Nurses' Health Study II (NHSII) which investigated associations between biomarkers and psychosocial factors. The prevalences of clinically meaningful depressive symptoms, mild-to-severe anxiety symptoms, experiencing major-life discrimination, and food addiction were 19%, 21%, 30%, and 5% respectively. These participants were more likely to have experienced childhood abuse and take psychotropic medications but less likely to have chronic conditions such as diabetes and hypertension than participants in the larger NHSII cohort. Participants (n = 213, mean age = 60.6) provided one or two separate stool samples for microbiome profiling between 2013 and 2014, and completed two online psychosocial assessments 10 months apart. The participants also completed two 30-day FFQs around the two microbiome collections. There was excellent reproducibility of psychosocial factors over 1 year. Moderate-to-strong positive correlations were observed between markers of distress and between positive psychosocial factors such as mindfulness and optimism. Here, the subjects' metadata including phenotypic and diet covariates have been provided. Microbial DNA sequence data from the stool microbiome collections is provided via Sequence Read Archive (SRA).

Study phs003786

The genomic basis of childhood T-lineage acute lymphoblastic leukemia

T-lineage acute lymphoblastic leukemia (T-ALL) is a high-risk tumor that has eluded comprehensive genomic characterization, in part due to the high frequency of non-coding genomic alterations resulting in oncogenic dysregulation. Here we report integrated genome and transcriptome sequencing of T-ALL tumor and remission samples obtained from over 1300 uniformly treated children with T-ALL, coupled with epigenomic and single cell analysis of malignant and normal T cell precursors. Integrated analysis identified 15 subtypes with distinct genomic drivers, gene expression, developmental state and outcome. Integration with chromatin topology analyses enabled elucidation of multiple mechanisms of enhancer deregulation that involve enhancers and genes in a subtype-specific fashion. We show that the immunophenotypically-described, high-risk entity of early T-cell precursor ALL is superseded by a broader category of leukemias of variable immunophenotype with diverse genomic alterations of a core set of genes encoding regulators of hematopoietic stem cell development. Numerous genetic alterations and disease subtypes emerged as independent predictors of survival and treatment failure in univariable and multivariable outcome models. These findings provide a roadmap for the classification, risk stratification and mechanistic understanding of this disease.

Study EGAS50000000016

Omic Studies in Children's Respiratory and Environmental Workgroup (CREW) Cohorts

Children's Respiratory Research Workgroup (CREW) is an NIH-funded project consisting of multiple individual U.S. cohorts and three scientific centers working together to identify phenotypes and causes of childhood asthma. CREW will include data from a large number of children and their families, with broad diversity in terms of ethnicity, family characteristics, neighborhoods and geographic locations. One of the primary goals of CREW is to put together sets of data and samples of participating cohorts to identify phenotypes of childhood asthma (i.e. specific subtypes of asthma that can be distinguished by clinical features such as natural history, triggers, exacerbation frequency, concurrent allergies, lung function, sex, etc). Omics studies will include genotyping, methylation, and RNA sequencing. By integrating the DNA genotyping with the expression, immunologic and clinical data, we will identify eQTL, inflammation QTL, and lung function QTL, as well as QTL associated with other biomarkers. Analyses will identify genetic, epigenetic, transcriptional and protein/metabolite profiles that are associated with specific exposures or phenotypes. As we obtain mechanistic insights about personal and early life risk factors, we will connect asthma phenotypes with underlying causes and pathogenic mechanisms to define endotypes of childhood asthma.

Study phs004036

TDP43 proteinopathy leads to divergent cryptic splicing in the cortex and spinal cord

Mislocalization of the nuclear TAR DNA-binding protein 43 (TDP43) is a hallmark of ALS and FTD which leads to de-repression and inclusion of cryptic exons, promising biomarkers of TDP43 pathology in a spectrum of neurodegenerative diseases. However, most cryptic exons to date have been identified from in vitro models or a single cortical FTD dataset, and little is known about cryptic splicing in the spinal cord, or within different neuronal subtypes. We meta-analyzed published bulk RNAseq datasets representing 1,778 RNAseq profiles of ALS and FTD post-mortem tissue, and in vitro models with experimentally depleted TDP43. We identified 142 cryptic splices, including 76 novel events. We found a novel pattern of spinal cord cryptic splicing, validated in an independent cohort by qPCR, which differed significantly from cortical and in vitro splicing. Finally, leveraging multiple public single-nucleus RNAseq datasets of ALS and FTD motor and frontal cortex, we confirmed the elevation of cortical-enriched splices in disease and localized them to layer-specific neuronal populations. This catalog of cryptic splices could inform efforts to develop biomarkers for tissue-specific and cell type-specific TDP43 pathology.

Study EGAS50000000575

Kids First: The Genomic Architecture of Hirschsprung Disease (HSCR)

Hirschsprung disease (HSCR) is a male biased developmental disorder associated with a lack of innervation of the gastrointestinal tract. Genetic studies have been instrumental in understanding its multifactorial inheritance, high heritability, syndromic associations, and genetic heterogeneity with variable penetrance and expressivity. At least 24 genes and 9 loci with pathogenic alleles (PAs) are known to underlie HSCR pathogenesis and explain 62% of its population attributable risk (PAR). Despite this heterogeneity, there is functional unity in HSCR: ~53% of HSCR PAs disrupt RET and EDNRB signaling in the developing enteric nervous system (ENS) in which 11 genes comprising a gene regulatory network control RET and EDNRB gene expression. We propose to identify the remaining 30% PAR by studying 857 unrelated HSCR cases, their 125 affected and 1,446 unaffected firstdegree relatives by whole genome sequencing to increase statistical power of gene discovery through improved detection of all types of coding and regulatory PAs. HSCR arises from cell autonomous defects in enteric neural crest cell precursors (ENCCs) affecting their proliferation, differentiation and migration in the ENS, functional studies that will guide our detection of novel genes.

Study phs003662

Pipeline Olympics: Continuous benchmarking of computational workflows for DNA methylation sequencing data

DNA methylation is a widely studied epigenetic mark and a powerful biomarker of cell type, age, environmental exposure, and disease. Genome-wide DNA methylation profiling is usually performed using whole-genome sequencing following selective conversion of unmethylated cytosines into thymines via bisulfite treatment or enzymatic methods. Numerous software tools facilitate processing of raw sequencing data for DNA methylation profiling, but a comprehensive benchmarking has been lacking. In this study, we systematically compared methods and tools for processing DNA methylation sequencing data. We established a dedicated benchmarking dataset comprising genome-wide DNA methylation profiling data for four reference samples using five experimental protocols each. The results of data processing were compared to highly quantitative locus-specific DNA methylation measurements available for 46 genomic loci. Based on this gold-standard reference dataset, we identified workflows that consistently demonstrated high performance. We present our results in an interactive application that provides a “living benchmark” ready for continuous updating as new workflows are proposed and require benchmarking against existing methods. In summary, our study provides guidance for any laboratory studying DNA methylation on a genome-wide scale.

Study EGAS50000000541

A Therapeutic Vaccine for Fibrolamellar Hepatocellular Carcinoma

Fibrolamellar hepatocellular carcinoma (FLC) is a rare form of liver cancer affecting 33 children and young adults that is driven by a chimeric protein, DNAJ-PKAc. We conducted a phase 1 clinical trial of a therapeutic vaccine targeting DNAJ-PKAc 38 (FLC-Vac), in combination with nivolumab and ipilimumab, in children and adults with advanced FLC. Among 16 patients enrolled, 12 completed the vaccine priming phase and were evaluable for both immunological and clinical endpoints. Grade 3 treatment-related adverse events were reported by six patients (37.5%). DNAJ43 PKAc-specific T cell responses were detected in 9/12 patients after treatment. In the subset of patients who completed the initial priming phase the disease control rate (DCR) was 75% (9/12), with three partial responses (25%). All patients with clinical responses also had DNAJ-PKAc specific T cell responses, from which we identified multiple class II-restricted T cell receptors (TCRs) with specificity for DNAJ-PKAc. Correlates of response included both functional neoantigen reactivity and changes in TCR repertoire features over time. Immune escape in two patients corresponded with immune exhaustion rather than neoantigen escape or HLA loss.

Study phs003970

Development of a diagnostic gene panel for Gorlin syndrome and its application to liquid biopsy

Gorlin syndrome is an autosomal dominant, rare disease caused by mutations in PTCH1, PTCH2, and SUFU with various symptoms in multiple organs making early diagnosis challenging. In this study, we generated a Gorlin syndrome gene panel that could help to overcome the difficulties in diagnosing Gorlin syndrome using a single test. This gene panel is time- and cost-efficient and highly reliable with a high-quality score of 30, on-target ratio, and coverage depth, and could detect more mutations than whole-exome sequencing of the same patient. Although the current in silico prediction tools have a limited genetic database of gene mutations in rare hereditary diseases, five prediction tools were used to identify pathological mutations. Pathogenic gene mutations were detected not only in PTCH1 but also in PTCH2 in five out of 12 patients with Gorlin syndrome diagnosed based on clinical symptoms. Using this gene panel, we showed the same gene mutation in the patients and their asymptomatic relatives; hence, it has enabled a highly reliable genetic diagnosis of Gorlin syndrome at a low cost requiring only blood sample.

Study JGAS000308

FLT3-targeting and places FLT3 as an ideal therapeutic target to selectively eradicate LSCs, while sparing HSC.

CRISPR/Cas9 FLT3 knock-out (FLT3-KO) in human HSCs and LSCs followed by functional xenograft assays to test their ability to regenerate human hematopoiesis and leukemia, respectively. FLT3-KO in HSCs from human fetal liver, cord blood and adult bone marrow showed no impairment in multilineage hematopoiesis in primary and secondary xenografts. By contrast, FLT3-KO LSCs from 6 of 7 FLT3-ITD mutated AMLs were able to generate short-term engraftment but were completely exhausted by 12 weeks. Thus, FLT3 is essential for LSC long-term propagation. This dependency was unique to FLT3-ITD AML samples as non-FLT3-ITD AML samples generated leukemic grafts upon FLT3-KO. Transcriptomic analysis revealed that FLT3-KO induced downregulation of DNA repair and cell cycle checkpoints, uniquely in FLT3-ITD AML, but not in healthy HSCs or other AMLs. Our research highlights a critical distinction between healthy HSCs and LSCs: whereas healthy hematopoiesis proceeds unperturbed upon FLT3-KO, FLT3-ITD leukemogenesis is impaired through elimination of LSCs. This evidence underscores the necessity for more potent FLT3-targeting and places FLT3 as an ideal therapeutic target to selectively eradicate LSCs, while sparing HSC.

Study EGAS50000000437

Whole-genome methylation profiling of menstrual stem cells identifies novel biomarkers for endometriosis

Endometriosis is a highly prevalent condition that remains underdiagnosed and poorly managed due to the lack of clinically validated biomarkers and limited understanding of its underlying pathophysiology. Although menstrual blood–derived stem cells (MenSCs) have been implicated in disease pathogenesis, their potential as a diagnostic source has not been systematically explored. We conducted a clinical study including 42 women (19 with endometriosis and 23 controls) to evaluate whether DNA methylation profiles from freshly isolated MenSCs could identify disease-specific biomarkers. Whole-genome DNA methylation sequencing identified differentially methylated regions (DMRs) enriched in genes associated with key features of endometriosis, including inflammation, tissue remodelling, and developmental processes. These DMRs robustly discriminated cases from controls, independently of technical and clinical confounders. Machine learning models trained and validated on these regions demonstrated strong diagnostic performance (specificity 83%, sensitivity 79%). Integration with an independent single-cell RNA sequencing dataset suggested that the identified DMRs may influence gene expression, supporting their biological relevance. Collectively, these findings highlight MenSC DNA methylation profiling as a promising, non-invasive strategy for early diagnosis and personalised management of endometriosis. (PubMed IDs will be provided once the manuscript is published.)

Study EGAS50000001640

SmMIP-tools:a computational toolset for processing and analysis of single-molecule molecular inversion probes derived data

Single-molecule molecular inversion probes (smMIPs) provides a modular and cost-effective platform for high-multiplex targeted next-generation sequencing (NGS). Nevertheless, translating the raw smMIP-derived sequencing data into accurate and meaningful information currently requires proficient computational skills and a large amount of computational work, prohibiting wide-scale adoption of smMIP-based technologies. To enable easy, efficient, and accurate interrogation of smMIP-derived data, we developed SmMIP-tools, a computational toolset that combines the critical analytic steps for smMIP data interpretation into a single computational pipeline. Here, we describe in detail two major components of the software. The first is a read processing tool that performs quality control steps, generates read-smMIP linkages and retrieves molecular tags. The second is an error-aware variant caller capable of detecting single nucleotide variants (SNVs) and short insertions and deletions (indels). Using a cell-line DNA dilution series and a cohort of blood cancer patients, we benchmarked SmMIP-tools and evaluated its performance against clinical sequencing reports. We anticipate that SmMIP-tools will increase accessibility to smMIP-technology, enabling cost-effective genetic research to push personalized medicine forward.

Study EGAS00001005359

Whole-genome sequencing of two probands with hereditary spastic paraplegia reveals novel splice-donor region mutation and known pathogenic mutation in SPG11

Hereditary spastic paraplegias (SPG) are a group of heterogeneous neurodegenerative disorders, which are often presented with overlapping phenotypes such as progressive paraparesis and spasticity. To assist the diagnosis of SPG subtypes, next-generation sequencing is often used to provide supporting evidence. In this study, we report the case of two probands from the same family with SPG symptoms, including bilateral lower limbs weakness, unsteady gait, cognitive decline, dysarthria and slurring of speech since age of 14. Subsequent whole-genome sequencing revealed that the patients are compound heterozygous for mutations in SPG11 gene, including the paternally inherited c.6856C>T (p.Arg2286*) mutation and the novel maternally inherited c.2316+5G>A splice donor region mutation. Mutations in SPG11 are the common cause of autosomal recessive Spastic Paraplegia type 11. According to the ClinVar database, there are already 101 reported pathogenic mutations in SPG11 that are associated with SPG. To our knowledge, this is the first report of SPG11 mutations in our local population. Novel splice mutation identified in this study would enrich the catalog of SPG11 mutations, potentially leading to better genetic diagnosis of SPG.

Study EGAS00001001849

The DNA methylation landscape of glioblastoma disease progression shows extensive heterogeneity in time and space

Glioblastoma is characterized by widespread genetic and transcriptional heterogeneity, yet little is known about the role of the epigenome in glioblastoma disease progression. Here, we present genome-scale maps of DNA methylation in matched primary and recurring glioblastoma tumors, using data from a highly annotated clinical cohort that was selected through a national patient registry. We demonstrate the feasibility of DNA methylation mapping in a large set of routinely collected FFPE samples, and we validate bisulfite sequencing as a multipurpose assay that allowed us to infer a range of different genetic, epigenetic, and transcriptional characteristics of the profiled tumor samples. On the basis of these data, we identified subtle differences between primary and recurring tumors, links between DNA methylation and the tumor microenvironment, and an association of epigenetic tumor heterogeneity with patient survival. In summary, this study establishes an open resource for dissecting DNA methylation heterogeneity in a genetically diverse and heterogeneous cancer, and it demonstrates the feasibility of integrating epigenomics, radiology, and digital pathology for a national cohort, thereby leveraging existing samples and data collected as part of routine clinical practice.

Study EGAS00001002538

Dissection of the molecular complexity of colorectal cancer in pre-clinical models identifies predictive signatures of sensitivity to EGFR inhibitors

Colorectal carcinoma (CRC) is a heterogeneous tumour entity, with only a fraction of the tumours responding to currently available therapies. A detailed understanding of the biology and genetics of CRC is a prerequisite for precision medicine. To address this challenge in clinical oncology, the OncoTrack consortium recruited 106 CRC patients (stages I-IV) and developed an integrated pre-clinical platform analysing drug sensitivity in the established matched patient-derived in vivo and in vitro models, 46 three-dimensional cell cultures and 59 xenografts, recapitulating many of the molecular features of the donor tumours. We generated extensive omics information on patient tumours and their derived models used to generate a compendium of drug sensitivity data. We could distinguish tumour molecular sub-groups responding differently to therapy and identified a novel independent predictor of sensitivity to the EGFR inhibitor cetuximab. The findings reported here will advance our understanding of CRC and its response to therapy.

Study EGAS00001001752

Field_effect_of_healthy_and_diseased_livers_WGS

Recent work in the Campbell group has revealed somatic mutations present in normal, non-cancerous human skin. A subset of the mutations conferred selective advantages to the host cells, leading to clonal expansions and raising the risk for future cancer development. Capturing such somatic mutations in normal tissue is important to advance our understanding about carcinogenesis and could provide prospective medical insights. In this project, our goal is to detect somatic mutations in normal (pre-cancerous) liver tissue. Using Laser Microdissection technology, we will dissect individual liver lobules from patient samples and submit these to sequencing. For each patient sample, we aim to sequence multiple lobules to characterise the mutagenic burden. Samples will be taken from patients with different liver disease aetiologies, including alcoholism and obesity, with a view on distinguishing the prevalent mutation types occurring in each disease context. We will perform both whole genome and targeted sequencing, initially using the WTSI cancer panel. Later we aim to use a novel bait set that captures both cancer genes as well as genes relevant to the non-cancerous samples (ie. genes implicated in hereditary disorders, immune sequences).

Study EGAS00001002413

SINGLE_CELL_ANALYSIS_OF_IN_VITRO_ERYTHROPOIESIS

We are developing a protocol to differentiate mouse and human induced pluripotent stem (IPS) and embryonic stem (ES) cells towards the haematopoietic pathway to generate erythrocytes in vitro. This system has many applications such as the study of the role of specific genes and human polymorphisms in infectious diseases such as malaria, as well as haematological diseases such as myelodysplastic syndrome. The nature of the in vitro differentiation process means that a heterogeneous population of cells is generated. In order to understand the types of cells produced with our protocol, we have performed a single cell analysis, which has the power to reveal the different populations of cells and their characteristics. For this, a cDNA library has been made that needs to be sequenced to obtain the gene expression profiles of the different cells. With this information we will be able to assess the quality of the differentiation protocol and improve it in order to produce better cells for the downstream applications.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 EGAS00001000764

An_exome_sequencing_study_of_the_HIV_elite_long_term_non_progressors_and_rapid_progressors__CASCADE_cohorts_

Background: A rare subgroup of HIV infected individuals naturally controls infection withouttreatment. These ?elite controllers? constitute an important model for the natural control ofHIV infection. Indeed, the study of these individuals may provide insights into strategies forthe development of HIV vaccines. Although several HLA and chemokine alleles are knownto be over-represented in elite controllers, only a small portion of HIV phenotypic variation isexplained by known genetic variants. The elite controller phenotype is rare and distinct,representing the extreme of an infectious disease trait. As such, this phenotype may be partlyexplained by variation in host immune control, which may be characterized by differences inrare functional genetic variants. Genomic regions underlying elite control can be potentiallyidentified by comparing the presence or frequency of variants in this group to thatrepresenting the opposite extreme. In this context, ?rapid progressors? is a group defined byits rapid immunological and clinical disease progression.Aim: To extend an existing study, in order to identify DNA sequence variants involved in thecontrol of HIV infection with greater statistical resolution. Specifically, we aim to sequence upto 200 exomes from multiple cohort studies within the EuroCoord CASCADE collaboration (acollaboration of 25 HIV seroconversion cohort studies across Europe).

Study EGAS00001000522

Defective T-cell expansion in RASGRP1 deficiency

Inherited CTPS1- CD27- and CD70-deficiencies in humans have revealed key factors of T-lymphocyte expansion, that is a prerequisite for an efficient immunity to Epstein-Barr virus (EBV) infection. RASGRP1 is a T-lymphocyte specific nucleotide exchange factor known to activate the MAP kinases pathway. A deleterious homozygous mutation in RASGRP1 leading to the loss RASGRP1 expression was identified in two siblings who both developed a persistent EBV infection leading to Hodgkin lymphoma. RASGRP1-deficient T cells exhibited defective MAPK activation and impaired proliferation that was restored by expression of wild-type RASGRP1. Similar defects were observed in T cells from healthy individuals when RASGRP1 was downregulated. RASGRP1-deficient T cells also exhibited decreased CD27-dependent proliferation toward CD70-expressing EBV-transformed B cells, a crucial pathway required for expansion of antigen-specific T cells in anti-EBV immunity. Furthermore, RASGRP1-deficient T cells failed to upregulate CTPS1, an important enzyme required for DNA synthesis. These results show that RASGRP1 deficiency leads to susceptibility to EBV infection, and demonstrate the key role of RASGRP1 at the crossroad of pathways required for the expansion of activated T lymphocytes.

Study EGAS00001002753

Clonal evolution in myeloma: the impact of maintenance lenalidomide and depth of response on the genetics and sub-clonal structure of relapsed disease in uniformly treated newly diagnosed patients

The emergence of treatment resistant sub-clones is a key feature of relapse in multiple myeloma. Therapeutic attempts to extend remission and prevent relapse include the maximisation of response and use of maintenance therapy. We used whole exome sequencing to study the genetics of paired presentation and relapse samples from 56 newly diagnosed patients, following induction therapy, randomised to receive either lenalidomide maintenance or observation as part of the Myeloma XI trial. Patients included were considered high risk, relapsing within 30 months of maintenance randomisation. Patients achieving a complete response had predominantly branching evolutionary patterns leading to relapse, characterised by a greater mutational burden, an altered mutational profile, bi-allelic inactivation of tumour suppressor genes, and acquired structural aberrations. Conversely, in patients achieving a partial response the evolutionary features were predominantly stable with a similar mutational and structural profile. There were no significant differences between patients relapsing after maintenance lenalidomide vs observation. This study shows that the depth of response is a key determinant of the evolutionary patterns seen at relapse.

Study EGAS00001003539

Identification of 19 novel loci reveals gene regulatory mechanisms determining susceptibility to testicular germ cell tumour

Testicular germ cell tumour (TGCT) is the most common cancer in young men1,2, and is characterised by strong inherited genetic risk factors3. Here we have undertaken large-scale genome wide association study (GWAS) for TGCT, encompassing ~7,500 cases and ~23,000 controls, through the Oncoarray consortium. We identified 19 novel loci, approximately doubling the number of known TGCT risk loci to 44 (P<5x10-8)4-14 and conduct deep, high-throughput functional annotation of all risk loci. We establish a network of physical interactions for all risk SNPs to candidate casual genes in 3D space, using high-throughput chromosome conformation capture techniques (HiC) in TGCT cells. Firstly, functional evidence reveals widespread disruption of developmental transcriptional regulators, consistent with failed primordial germ cell differentiation as an initiating step in TGCT oncogenesis15. We secondly observe multiple risk loci associated with defective microtubule assembly, compatible with the high level of aneuploidy observed in TGCTs, suggesting gross chromosomal instability. Finally KIT-MAPK signalling features as a recurrently dysregulated pathway. In summary our findings substantially increase the number of known TGCT risk alleles, and provides a functional basis for disease susceptibility.

Study EGAS00001001836

Identification of rare germline variants in familial multiple myeloma

The risk of developing multiple myeloma (MM) in first-degree relatives of affected individuals is 2 to 4 fold higher than in the general population, implying the existence of inherited susceptibility. While over 20 common, low-penetrance variants have been associated with MM risk, less is known about rare, high-penetrance germline predisposition. We aimed to identify and characterize high/moderated penetrance germline variants in MM families using whole genome sequencing. For that purpose we identified families with at least two individuals diagnosed with MM or its precursors MGUS and smoldering MM. Also, patients with solitary plasmacytoma and AL amyloidosis were enrolled. We also recruited unaffected family members, and they were screened to exclude undetected MM or its precursor stages. After whole genome sequencing of blood DNA and filtering for rare variants (minor allele frequency <0.1%) and family segregation, variants are prioritized by a range of published in silico tools and literature search. The most promising variants are subjected to experimental validation to evaluate their functional relevance. Our data will provide guidance to worldwide efforts to unravel germline predisposition in MM and validation of the proposed variants and genes.

Study EGAS00001004734

Familial psychosis associated with a missense mutation at MACF1 gene combined with the rare duplications DUP3p26.3 and DUP16p23.3, affecting the CNTN6 and CDH13 genes

Psychosis is a highly heritable and heterogeneous psychiatric condition. Its genetic architecture is thought to be the result of the joint effect of common and rare variants. Families with high prevalence are an interesting approach to shed light on the rare variant's contribution without the need of collecting large cohorts. To unravel the genomic architecture of a family enriched for psychosis, with four affected individuals, we applied a system genomic approach based on karyotyping, genotyping by whole-exome sequencing to search for rare single nucleotide polymorphisms (SNPs) and SNP array to search for copy-number variants (CNVs). We identified a rare non-synonymous variant, g.39914279 C&gt;G, in the MACF1 gene, segregating with psychosis. Rare variants in the MACF1 gene have been previously detected in SCZ patients. Besides, two rare CNVs, DUP3p26.3 and DUP16p23.3, were also identified in the family affecting relevant genes (CNTN6 and CDH13, respectively). We hypothesize that the co-segregation of these duplications with the rare variant g.39914279 C&gt;G of MACF1 gene precipitated with schizophrenia and schizoaffective disorder.

Study EGAS00001004791

H3Africa - An integrated approach to the identification of genetic determinants of susceptibility to trypanosomiasis

The objective of the TrypanoGEN project is to discover genetic variants associated with different responses to sleeping sickness infection. The project was designed in two phases:Phase 1) Variant discovery; 222 samples were sequenced to approximately 10X coverage on an Illumina 2500 with 2x150bp reads, at the University of Liverpool Center for Genomic Research. In addition, 77 samples from Cameroon and Zambia were sequenced to approximately 30X Coverage at Baylor College of Medicine. The sequenced reads were mapped onto the 1000 genomes project human_g1k_v37_decoy reference genome using BWA. The SNP calling on all the samples was done using the genome analysis tool kit GATK v3.4. Samples were selected from seven populations where Trypanosomiasis is endemic: Nilo-Saharan speakers from North-West Uganda and Niger-Congo speakers from South-East Uganda, DRC, Ivory Coast, Guinea, Cameroon and Zambia. The samples included 182 controls, 97 cases, 17 latent infections and 3 suspect cases. Phase 2) Variants discovered in Phase 1 will be used in the development of the H3Africa SNP chip. This chip will then be used in a GWAS study to identify variants associated with trypanosomiasis.

Study EGAS00001002602

Molecular_risk_stratification_in_patients_with_T1_colorectal_cancer_WES

The introduction of bowel cancer screening has led to a significant increase in the proportion of patients being diagnosed with asymptomatic, early-stage colorectal cancer (CRC). Although the majority of these patients are successfully treated with surgery alone, a small proportion of patients have ‘born-to-be-bad’ aggressive lesions with early dissemination leading to distant metastases. Current standard of care histological assessment is unable to distinguish between these aggressive versus non-aggressive early lesions which is essential to provide appropriate clinical management decisions. This study aims to carry out molecular and histological profiling of approximately 300 T1 CRCs in order to develop a molecular stratifier based on the risk of relapse in early-invasive CRC. This novel T1 cohort will represent the world’s largest molecularly characterised T1 cohort of samples, with digital pathology assessment alongside whole exome sequencing, copy number variation analysis and 3’ RNA-seq. This data will be used to generate a robust panel of molecular and/or histological markers applicable to formalin-fixed paraffin embedded (FFPE) archival tissue which discriminates between T1 lesions based on risk of relapse, which will ultimately be used to inform clinical management of CRC at the earliest stages of the disease.

Study EGAS00001005734

MGP Panel: a comprehensive targeted genomics panel for molecular profiling of multiple myeloma patients

We designed a comprehensive multiple myeloma (MM) targeted sequencing panel to identify common genomic abnormalities in a single assay and validated it against known standards. The panel comprised 228 genes/exons for mutations, 6 regions for translocations, and 56 regions for copy number abnormalities (CNAs). Toward panel validation, targeted sequencing was conducted on 233 patient samples and further validated using clinical fluorescence in situ hybridization (FISH) (translocations), multiplex ligation probe analysis (MLPA) (CNAs), whole genome sequencing (WGS) (CNAs, mutations, translocations) or droplet digital PCR (ddPCR) of known standards (mutations). Canonical IgH translocations were detected in 43.2% of patients by sequencing, and aligned with FISH except for one patient. CNAs determined by sequencing and MLPA for 22 regions were comparable in 103 samples and concordance between platforms was R2=0.969. VAFs for 74 mutations were compared between sequencing and ddPCR with concordance of R2=0.9849. In summary, we have developed a targeted sequencing panel that is as robust or superior to FISH and WGS. This molecular panel is cost effective, comprehensive, clinically actionable and can be routinely deployed to assist risk stratification at diagnosis or post-treatment to guide sequencing of therapies.

Study EGAS00001006222

Discovery of a highly widespread bacteriophage family and its associations to metabolic syndrome gut microbiomes

There is significant interest in altering the course of cardiometabolic disease development via the gut microbiome. Nevertheless, the highly abundant phage members of the complex gut ecosystem -which impact gut bacteria- remain understudied. Here, we characterized gut virome changes associated with metabolic syndrome (MetS), a highly prevalent clinical condition preceding cardiometabolic disease, in 196 participants with a combination of whole genome shotgun and virus like particle sequencing. MetS gut virome populations exhibited decreased richness and diversity, but larger inter-individual variation. These populations were enriched in phages infecting Bacteroidaceae and depleted in those infecting Ruminococcaeae. Differential abundance analysis identified eighteen viral clusters (VCs) as significantly associated with either MetS or healthy viromes. Among these are a MetS-associated Roseburia VC that is related to healthy control-associated Faecalibacterium and Oscillibacter VCs. Further analysis of these VCs revealed the Candidatus Heliusviridae, a highly widespread gut phage lineage found in 90+% of the participants. The identification of the temperate Ca. Heliusviridae provides a novel starting point to a better understanding of the effect that phages have on their bacterial hosts and the role that this plays in MetS

Study EGAS00001006260

Pharmacogenomic analysis of patient-derived tumor cells in gynecologic cancers

Gynecologic malignancy is one of the leading causes of mortality in female adults worldwide. Comprehensive genomic analysis has revealed a list of molecular aberrations that are essential to tumorigenesis, progression, and metastasis of gynecologic tumors. However, targeting such alterations has frequently led to treatment failures due to underlying genomic complexity and activation of various tumor cell survival pathway molecules. A compilation of molecular characterization of tumors with pharmacological drug response is the next step towards clinical application of patient-tailored treatment regimens. Toward this goal, we have established a library of 139 gynecologic tumors including cervical, endometrial, and epithelial ovarian cancers (EOCs) and uterine sarcomas that were genomically and/or pharmacologically annotated and explored dynamic pharmacogenomic associations against 37 molecularly targeted drugs. We discovered lineage-specific drug sensitivities based on subcategorization of gynecologic tumors and identified TP53 mutation as a molecular determinant that elicit therapeutic response to poly (ADP-Ribose) polymerase (PARP) inhibitor. We further identified transcriptome expression of inhibitor of DNA biding 2 (ID2) as a potential predictive biomarker for treatment response to olaparib. Together, our results demonstrate potential utility of rapid drug screening combined with genomic profiling for precision treatment of gynecologic cancers.

Study EGAS00001003556

Genomic_characterisation_of_MGUS__

he hematological malignancy multiple myeloma (MM), also called Kahler’s disease or plasma cell (PC) myeloma, is characterized by a clonal expansion of PCs originating in the bone marrow (BM). The expansion of these cells leads to an overproduction of antibodies and results in typical symptoms such as anemia, renal failure and bone lesions. All cases of MM are preceded by the asymptomatic, non-malignant pre-stage monoclonal gammopathy of undetermined significance (MGUS). Of all MGUS patients, only 1% per year will progress to MM. Despite efforts to elucidate the molecular mechanisms underlying the MGUS-to-MM progression, its pathogenesis still remains largely unknown. Additionally, the genetic profiles of MGUS patients have only been limitedly investigated due to the only incidental finding of MGUS, the difficulties in BM sampling and isolating a sufficient number of aberrant PCs from the BM aspirates of MGUS patients. Consequently, reliable biomarkers to individually predict which MGUS patients will progress to MM and which will not, are lacking. Therefore, it is highly required to study the molecular pathogenesis of MGUS and the role of genetic events in relation to the malignant transformation to MM.

Study EGAS00001004124

Case Report: Rare IKZF1 gene fusions identified in neonate with congenital KMT2A-rearranged Acute Lymphoblastic Leukemia

Here we describe a rare case of congenital KMT2Ar ALL presenting with co-occurring IKZF1 gene fusions and a predictably aggressive disease trajectory. We report for the first time, the novel IKZF1::TUT1 and KDM2A::IKZF1 gene fusions. Rearrangements in-volving KMT2A are commonly retained in relapsed infant ALL, however, in this case the KMT2A::AFF1 gene fusion did not appear to be the lesion driving leukemic relapse. Instead, our data suggest that relapse was driven by IKZF1::TUT1. This gene fusion remained in all samples investigated, including the on-blinatumomab therapy sample taken immediately prior to relapse. Conversely, the KMT2A::AFF1 gene fusion was only detected in the diagnosis and refractory post-induction samples highlighting a key role for IKZF1::TUT1 in disease pathogenesis. Intriguingly, both IKZF1 gene fusions are predicted to be out-of-frame, however, our data demonstrate the IKZF1 gene is still expressed. This is not unprecedented and it has previously been observed that out-of-frame fusions can cause transcriptional activation/repression of genes involved in the fusions leading to increases or decreases of their expression and the as-sociated functional outcomes.

Study EGAS00001006947

Gut microbiome dynamics unravelled with metagenomics sequencing

It has been already several years since we discovered that microbial therapeutics like Faecal Microbiota Transplantation can be used to treat Clostridium difficile infection (CDI) and Inflammatory bowel disease (IBD) with great success. The concept has challenged us to test the limits of our knowledge with the perspective to improve health in the most diverse conditions like Parkinson disease, depression, autism and obesity, just to mention a few. Note: the figure belongs to the original paper and is owned by the authors. Allyson L.Bird and colleagues from Genentech Inc. (San Francisco) recently published an interesting study building up on the key concept that “As microbial therapeutics are increasingly being tested in diverse patient populations, it is essential to understand the host and environmental factors influencing the microbiome.” The authors of this work analysed 1359 gut microbiome samples using shotgun metagenomics sequencing. The results of the comparison done between microbiota composition across the different groups showed that biological sex is the strongest driver of diversity, while aging (age range studied: 20–69) appears to be the second factor. As smartly outlined in the authors’ own graphical abstract (figure to the left), Bacteroidota species consistently increased with donors' age while Actinobacteriota species, including Bifidobacterium, decreased. This study also integrated data from oncological patients to draw cancer-related evidences. After correcting the biases for technical and geographic differences, they found that cancer patients show significantly altered gut bacterial communities compared with their healthy counterparts. Eg. E.coli was found to be increased in cancer patients together with Bacteroidota/Firmicutes ratios. By comparing sequential samples taken from the same donors (413) within short-distance time points, the authors found that in the short term, intra-individual differences were less than the inter-individual ones, indicating a certain community stability being the norm. One of the pivotal points from this interesting study is that the data proceeds from extremely well-defined and selected donors. Specifically, the data for 949 selected healthy donors came from the Milieu Intérieur (MI) Consortium and extensive metadata, including demographic variables, serological measures, dietary information, and systemic immune profiles, are available. This precise stratification allowed for the robust detection of smaller changes, compared to former works. All sequencing data has been deposited in the EGA archive under the accession number EGAS00001004437. Enjoy this amazing open access paper published in the Experimental Journal of Medicine on January 2021.

Blog gut-microbiome-dynamics-unravelled

Thymic epithelial transplantation for complete DiGeorge syndrome: RNA (2025-07-22)

Single cell transcriptomics study of thymic transplant biopsies Allogeneic thymus transplantation is the only curative therapy for complete DiGeorge Syndrome (cDGS), a rare severe primary immunodeficiency characterised by athymia. GOSH is one of only two centres worldwide to offer this treatment. Despite a lack of major histocompatibility complex (MHC)-matching between donor and host, transplanted thymus becomes repopulated by recipient bone marrow derived precursor cells and supports development of functional T-cells. The mechanisms underlying thymopoiesis in this context are poorly understood, but over time we observe reconstitution of T-cell immunity, with the ability to produce host naïve T-cells showing a broad T-cell receptor (TCR) repertoire and to generate MHC-restricted T-cell proliferative responses. Although lifesaving, the achieved immunological reconstitution is typically not complete with circulating T-cell numbers usually remaining below the age related normal ranges. Additionally, we observe persistence of donor-derived T-cells of unknown clinical significance. To gain more insight into the mechanisms by which MHC-mismatched transplanted thymus supports T-cell development with self-tolerance, as well as into the basis of suboptimal T-cell immunity, we now aim to investigate immune reconstitution after thymus transplantation in further detail by using single-cell transcriptomics, applied to thymic transplant biopsies and peripheral blood samples collected during standard post-transplant patient care. By identifying which lineages of host- derived cells repopulate the thymic tissue after transplantation, we will be able to address the role of MHC in positive and negative T-cell selection during T-cell differentiation. We will also be able to clarify the exact ontogeny of the persistent donor T-cells, as well as their possible role. Understanding the mechanisms of action of HLA-mismatched transplanted thymus will contribute to treatment optimisation. Additionally, our research provides a unique opportunity to further investigate key immunological concepts, such as tolerance and autoimmunity, challenging existing paradigms in thymus immunology. 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/ . This dataset contains all the data available for this study on 2025-07-22.

Dataset EGAD00001015648

Phosphoproteomics adds value to treatment recommendations in molecular tumor boards

Precision oncology approaches employing genomics-guided targeted therapies for individual patients have provided significant survival benefits in several cancer types. However, low response rates in most solid malignancies, many patients without actionable genomic lesions, and increasing evidence that non-genomic mechanisms may play an important role in tumors indicate that genomics alone is often insufficient to inform and guide the clinical care of patients. Here, we show for the first time that comprehensive (phospho)proteome profiling is feasible and informative in a real-world prospective precision oncology setting. We developed a novel tumor pathway activity (TUPAC) scoring methodology that provides a holistic perspective on dysregulated receptor tyrosine kinase (RTK) signaling in individual patients. Based on 919 tumor tissue profiles of patients enrolled in the national NCT/DKTK MASTER study and the INFORM registry trial, we illustrate how TUPAC scoring can be used to uncover individual tumor biology in rare cancers and demonstrate that TUPAC methodology identifies EGFR-driven sarcomas despite the absence of genetic EGFR alterations. Overall, our work demonstrates the utility of the additional phosphoproteome data layer to enhance therapeutic recommendations in molecular tumor boards.

Study EGAS00001007891

Pan-neuroblastoma analysis reveals age- and signature-associated driver alterations

Neuroblastoma is a pediatric malignancy with heterogeneous clinical outcomes depending on age and other factors. To better understand neuroblastoma pathogenesis, here we analyze whole-genome, whole-exome and/or transcriptome sequencing data from 702 neuroblastoma samples, half of which are new data. Over 95% of samples harbor at least one recurrent driver alteration and most aberrations, including MYCN, ATRX, and TERT alterations, differ in frequency by age. MYCN alterations occur at median 2.3 years of age, TERT at 3.8 years, and ATRX at 5.6 years, suggesting age-specific susceptibility to genetic alterations. Mutational signature analysis shows that reactive oxygen-species (ROS)-induced mutations are the most common cause of single nucleotide variant (SNV) drivers in neuroblastoma, including most ALK and Ras pathway SNVs. ROS-induced mutagenesis is both an early event, as it causes truncal variants, and continuous as it also induces relapse-specific mutations. ROS-induced mutations are more abundant in neuroblastomas with MYCN amplification, 17q gains, and increased expression of mitochondrial ribosome genes. We observe recurrent FGFR1 N546K or internal tandem duplication variants in 6 patients and ALK N-terminal structural alterations in 5 samples, identifying additional patients amenable to precision therapy.

Study EGAS00001003931

RNA-sequencing of tumors from 45 patients with recurrent or metastatic gastric cancer treated with immune checkpoint inhibitors

Genomic profiling can provide prognostic and predictive information to guide clinical care. Biomarkers that reliably predict patient response to chemotherapy and immune checkpoint inhibition in gastric cancer are lacking. In this work, we used our machine learning algorithm NTriPath to identify a gastric-cancer specific 32-gene signature. Using unsupervised clustering on expression levels of these 32 genes in tumors from 567 patients, we identified four molecular subtypes that were prognostic for survival. We then built a support vector machine with linear kernel and the binary classifier to generate a risk score that is prognostic for 5-year overall survival and validated the risk score using three independent datasets. We also found that the molecular subtypes predicted response to adjuvant 5-fluorouracil and platinum after gastrectomy and immune checkpoint inhibitors in patients with metastatic or recurrent disease. The 32-gene signature is a promising prognostic and predictive biomarker to guide the clinical care of gastric cancer patients and should be validated in a prospective manner. This EGA archive includes both St.Mary hospital cohort samples (n=28) and Yonsei immunotherapy patient samples (n=17).

Study EGAS00001005588

An alternative splicing modulator decreases mutant HTT and improves the molecular fingerprint in Huntington’s disease patient neurons

Huntington's disease (HD) is a neurodegenerative disorder caused by poly-Q expansion in the Huntingtin (HTT) protein. Here, we delineate elevated mutant HTT (mHTT) levels in patient-derived cells including fibroblasts and iPSC derived cortical neurons using a GLP approved HTT assay. HD patients’ fibroblasts and cortical neurons recapitulate aberrant alternative splicing as a molecular fingerprint of HD. Branaplam is a splicing modulator currently tested in a phase II study in HD (NCT05111249). The drug lowers total HTT (tHTT) and mHTT levels in fibroblasts, iPSC, cortical progenitors, and neurons in a dose dependent manner at an IC50 consistently below 10nm without inducing cellular toxicity. Branaplam promotes inclusion of non-annotated novel exons. Amongst, a 115bp frameshift-inducing exon in the HTT transcript in Branaplam treated cells from Ctrl and HD patients leading to a profound reduction of HTT RNA and protein levels. Importantly, Branaplam ameliorates aberrant alternative splicing in HD patients’ fibroblasts and cortical neurons. These findings highlight the applicability of splicing modulators in the treatment of CAG repeat disorders and decipher their molecular effects associated with the pharmacokinetic and -dynamic properties in patient-derived cellular models.

Study EGAS00001006289

Clean sequence of LUAD in young never-smoker

we conducted whole genome sequencing (WGS) to characterize the genomic alterations of 36 never-smoker Chinese patients with lung adenocarcinomas (LUADs). This dataset is containing clean fastq files of 36 never-smoker Chinese patients with lung adenocarcinomas (LUADs)

Dataset EGAD00001003890

WGS of human colorectal cancer organoid exposed to genotoxic pks+ E. coli

Organoid cultures were exposed to different E.Coli strains and a dye control. In total 25 organoid cultures were whole-genome sequenced using the Novaseq6000 platforms. The data is deposited as .bam format.

Dataset EGAD50000000304

A neoadjuvant, phase II trial demonstrates efficacy and tolerability of Talimogene laherparepvec in cutaneous basal cell carcinoma (NeoBCC trial)

This dataset is related to the NeoBCC trial and includes 12 human tissue samples

Dataset EGAD50000000371

DupiAERD

Dataset contains bulk RNA sequencing reads from 44 NERD patients under dupilumab therapy before and after aspirin provocation at baseline and after 24 weeks of treatment. Dataset is a multiplexed .bam file containing all sequencing reads with tagged identifiers.

Dataset EGAD50000000565

Adipose tissue macrophage dysfunction is associated with a breach of vascular integrity in NASH

We report single-cell RNA sequencing data from myeloid cells of the human visceral adipose tissue in non-alcoholic fatty liver disease patients

Dataset EGAD50000000615

BAM files from whole-exome sequencing of 5 agressive B-cell lymphoma tumour samples

This dataset contains BAM files from whole-exome sequencing (WES) of 5 agressive B-cell lymphoma tumour samples for cases 2, 3, 4 and 5. For case 2, non-tumor whole-exome sequencing is also available.

Dataset EGAD50000000803

Moroccan Genome Project: Sequencing Data from 109 Whole Genomes of Moroccan Individuals

This study is the first phase of the Moroccan Genome Project, which included the complete sequencing of 109 genomes from the Kingdom of Morocco. The sequencing was performing using the Illumina NovaSeq6000 platform, with a mean coverage of 30X.

Dac EGAC50000000353

CRC organoid RNA-seq data access committee

This DAC is responsible for granting access to RNA-seq data (paired-end FASTQ files) from 10 patient-derived colorectal cancer organoid patients. The data was ad hoc generated as part of the development of NovumRNA, a non-canonical tumor-specific antigen prediction pipeline.

Dac EGAC50000000406

PETAL trial Whole Exome Sequencing (WES)

Associated with Molecular profiling of DLBCL patients treated in the PETAL trial. Whole Exome Sequencing (WES) of 224 Samples (162 Tumor + 62 Normal). WES was used for Molecular Profiling by simultaneous screening of mutations. Data is Complementary to sWGS.

Dataset EGAD50000001172

DAC for "Establishment and characterization of circulating tumor cells-derived organoids from metastatic breast cancer patients."

This is the DAC for the study "Establishment and characterization of circulating tumor cells-derived organoids from metastatic breast cancer patients." of Andreas Trumpp (a.trumpp@dkfz.de), Roberto Würth (r.wuerth@dkfz.de) and Martin Sprick (Martin.Sprick@hi-stem.de).

Dac EGAC50000000371

WGS dataset for malignant pleural and peritoneal mesothelioma

This dataset contains Whole Genome sequencing data of pleural and peritoneal mesothelioma. The number of samples is 40. Sequencing was performed on Illumina NovaSeq 6000 and Illumina NovaSeqXPlus. The sequencing was always paired.

Dataset EGAD50000001343

Dac for "Development of a fully human glioblastoma-in-brain-spheroid model for accelerated translational research"

This is the DAC for "Development of a fully human glioblastoma-in-brain-spheroid model for accelerated translational research" of Philipp Koch (philipp.koch@zi-mannheim.de), Frank Winkler (Frank.Winkler@med.uni-heidelberg.de), Moritz Mall( m.mall@dkfz-heidelberg.de)

Dac EGAC50000000480

Boyes Lab - DAC policy

Access to this data is controlled. Upon request from a third party for access to the data, a separate Data Sharing Agreement would be put in place between the University of Leeds and the third party prior to EGA granting access to the data to the third party.

Dac EGAC50000000283

SDR-seq_06_BCL

SDR-seq_BCL data access. Two follicular lymphoma (FL) primary patient samples and one germinal center subtype diffuse large B-cell lymphoma (GCB) primary patient sample. FL1 and GCB1 are sequenced in Run1. FL2 is sequenced in Run2.

Dataset EGAD50000000551

Whole exome DNA sequencing pre-treatment on tumor samples (n=24) matched with blood samples (n=24)

Data from NABUCCO cohort 1 (NCT03387761). This dataset includes Whole exome DNA sequencing on bladder tumor samples (n=24) matched with blood samples (n=24). The data is pre-treatment.

Dataset EGAD00001006850

Single cell karyotype sequencing of 7 samples from colorectal cancer (CRC) patients

Contains data for all cells sequenced for this study. Data is organized as one bam-file per sample. Individual cells can be identified through the CB tag in the bam-files.

Dataset EGAD00001006438

Prognostic factors in prostate cancer: deep sequencing pilot project TAPG

This is a pilot project to determine whether the TAPG FFPE DNA's are suitable for deep sequencing. If successful an investigation of SNP distribution in a larger cohort will follow.

Dataset EGAD00001001237

RNA-seq of multi-regional CRC samples

BAM files of RNA sequencing (RNA-seq) experiment on multi-regional colorectal cancer (CRC) samples. 58 samples corresponding to 16 patients were sequenced and there is one BAM file for each sample.

Dataset EGAD00001006164

ChIP sequencing in Cancer Cell Lines

The project is to evaluate the genomic binding sites of the histone demethylase JARID1C. This gene was recently identified in CGP as a novel recessive cancer gene in human renal cell carcinoma.

Dataset EGAD00001001453

PPIL4 is essential for brain angiogenesis and implicated in intracranial aneurysms in humans

Patients in IA cohort with PPIL4 mutations (Please see Supplementary Table 3 for clinical characteristics of the patients)

Dataset EGAD00001008106

TCRab sequencing of chronic-phase chronic myeloid leukemia patients

TCRab sequencing of viably frozen cells from 12 samples from four chronic-phase chronic myeloid leukemia patients. The raw data is available as fastq files.

Dataset EGAD00001009085

GENCORD2_GENOTYPES

204 individuals were genotyped with the Illumina 2.5M Omni chip. Filtered genotypes were imputed into the 1000 genomes project European panel SNPs. Beagle R2 is indicated in VCF files for further filtering. See Materials and Methods in publication for details.

Dataset EGAD00001000428

Copy number profiles detected by shallow coverage WGS

We performed shallow coverage whole genome sequencing on 147 glioma samples and analyzed their copy number profile. The coverage of each sample is about 2. Data are presented as VCF files which describe the copy number segments and their log2 ratio.

Dataset EGAD00001005062

71 Whole-exome sequencing of Esophageal Squamous Cell Carcinoma on Chinese Patients

Esophageal Squamous Cell Carcinoma (ESCC) is one of the deadliest cancers worldwide. We performed 71 Whole-exome sequencing of Esophageal Squamous Cell Carcinoma on Chinese Patients.

Dataset EGAD00001001926

WGS Dataset of Organoid drug profiling identifies methotrexate as a therapy for SCCOHT, a rare pediatric cancer

We generated and characterized tumoroids from small cell carcinoma of the ovary, hypercalcemic type. Furthermore, we identified a drug that is selective and effective against SCCOHT tumoroids.

Dataset EGAD00001015442

TCS validation of 11 lung adenos

This is the targeted capture deep sequencing (TCS) data for validation of the mutations discovered in the WES step. There are 58 bam files of TCS data including 48 tumor samples and 10 peripheral blood WBC samples.

Dataset EGAD00001000985

H3Africa TrypanoGEN Main WGS

This dataset is for TrypanoGEN Phase 1: Variant discovery, and includes 233 samples sequenced to approximately 10X coverage. Samples are from Guinea, Cote D’Ivoire, DRC and Uganda using Illumina HiSeq 2500.

Dataset EGAD00001005076

PRADO trial - Personalized response-directed surgery and adjuvant therapy after neoadjuvant ipilimumab plus nivolumab in stage III melanoma

The dataset includes RNA sequencing data on PRE- treatment biopsies of lymph node metastasis (n=80) The technology used for sequencing is llumina HiSeq 2500

Dataset EGAD00001012116

EBV-DLBCL by whole-genome and targeted amplicon-based sequencing

Whole genome sequencing data of EBV associated DLBCL of 8 matched tumor-normal patients. Additionally, targeted resequencing data of 47 patients is provided.

Dataset EGAD00001006858

Single-cell RNA sequencing of RCC patients

Single-cell RNA sequencing was performed on viable frozen tumor dissociated cells from three RCC patients. The raw data is available as fastq files.

Dataset EGAD00001011045

EORTC-26101 sequencing data

The dataset contains panel sequencing data of 170 genes from 380 patients of the EORTC-26101 trial. The corresponding methylation data is available via the Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/) repository with the accession number GSE237103.

Dataset EGAD00001011160

Study of Addiction: Genetics and Environment (SAGE)

This study is part of the Gene Environment Association Studies initiative (GENEVA) funded by the National Human Genome Research Institute. The overarching goal is to identify novel genetic factors that contribute to addiction through a large-scale genome-wide association study of DSM-IV alcohol dependent (and frequently illicit drug dependent) cases and non-dependent, unrelated control subjects of European and African American descent. The focus of this proposal is a case-control design of unrelated individuals for a genetic association study of addiction. Cases are defined as individuals with DSM-IV alcohol dependence (lifetime) and potentially other illicit drug dependence. In addition to the categorical diagnosis, we have data on ordinal measurements of number of DSM-IV symptoms for alcohol, nicotine, marijuana, cocaine, opiates and other drugs so that we will able to construct quantitative measurements of addiction severity over a wide range of substances. Controls are defined as individuals who have been exposed to alcohol (and possibly to other drugs), but have never met lifetime diagnosis for alcohol dependence or dependence on other illicit substances. Analyses that include refinement of the phenotype and incorporation of important demographic and environmental factors into association studies will be pursued. Cases and controls were selected from three large, complementary datasets: the Collaborative Study on the Genetics of Alcoholism (COGA), the Family Study of Cocaine Dependence (FSCD), and the Collaborative Genetic Study of Nicotine Dependence (COGEND). COGA: COGA was initiated in 1989 and is a large-scale family study that has had as its primary aim the identification of genes that contribute to alcoholism susceptibility and related characteristics. COGA is funded through the National Institute on Alcohol Abuse and Alcoholism (NIAAA). Subjects were recruited from 7 sites across the U.S. Alcohol dependent probands were recruited from treatment facilities and assessed by personal interview. 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 the alcohol dependent probands. Assessment involved a comprehensive 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. Families with three or more first-degree relatives who were alcohol dependent were invited for more extensive testing, including neurophysiology evaluations (ERPs and EEGs) and a battery of neuropsychological assessments. Blood was obtained for genetic studies. Institutional Review Boards at all sites approved the protocols, including sharing in the NIAAA national repository. COGA has four Co-Principal Investigators Bernice Porjesz, Victor Hesselbrock, Howard Edenberg, and Laura 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 (Victor Hesselbrock); Indiana University (Howard Edenberg, John Nurnberger, Jr., Tatiana Foroud); University of Iowa (Samuel Kuperman); SUNY Downstate (Bernice Porjesz); Washington University in St. Louis (Laura Bierut, Alison Goate, John Rice); University of California at San Diego (Marc Schuckit); Howard University (Robert Taylor); Rutgers University (Jay Tischfield); Southwest Foundation (Laura 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). Family Study of Cocaine Dependence (FSCD): This project was initiated in 2000 as a case-control family study of cocaine dependence funded through the National Institute on Drug Abuse (NIDA; PI: Laura Bierut). The primary goal was to increase the understanding of the familial and non-familial antecedents and consequences of cocaine dependence. Cocaine dependent individuals were systematically recruited from chemical dependency treatment units (both public and private; residential and outpatient) in the greater St. Louis metropolitan area. Community based control subjects were identified through a Missouri Driver's License Registry (maintained at Washington University for research purposes) and matched by age, race, gender, and residential zip code. As a supplement to this project, blood samples were collected for future genetic analysis and were included in the NIDA Genetics Consortium. Phenotypic data, DNA, and cell lines are in the NIDA Center for Genetics Studies. Collaborative Genetic Study of Nicotine Dependence (COGEND): COGEND was initiated in 2001 as a three-part program project grant funded through the National Cancer Institute (NCI; PI: Laura Bierut). The three projects included a study of the familial transmission of nicotine dependence, a genetic study of nicotine dependence, and a study of the relationship of nicotine dependence with nicotine metabolism. The primary goal is to detect, localize, and characterize genes that predispose or protect an individual with respect to heavy tobacco consumption, nicotine dependence, and related phenotypes and to integrate these findings with the family transmission and nicotine metabolism findings. The primary design is a community based case-control family study. All subjects were recruited from Detroit and St. Louis. Nicotine dependent cases and non-dependent smoking controls were identified and recruited. In addition, one sibling for each case and control subject was recruited in a subset of the sample. Over 56,000 subjects aged 25-44 years were screened by telephone, over 3,100 subjects were personally interviewed, and over 2,900 donated blood samples for genetic studies. All three studies (COGA, COGEND, FSCD) include measures of basic socio-demographic variables, including age, sex, race/ethnicity, family income, educational attainment, religious participation, and family structure. Other important covariates and/or potential moderators of genetic effects include comorbid addictions and age at initiation of use for cigarettes, alcohol and drugs. The assessments also include measures of various life stressors, such as physical and sexual abuse, which have been implicated in gene-environment interactions for several disorders. Coding for both individual variables and indices has been standardized across studies. All subjects were assessed in person by trained research assistants. Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR), was provided by the NIH GEI (U01HG004438), the National Institute on Alcohol Abuse and Alcoholism, the National Institute on Drug Abuse, and the NIH contract "High throughput genotyping for studying the genetic contributions to human disease"(HHSN268200782096C). Note for Publications Related to Study: The Study of Addiction: Genetics and Environment (SAGE) has not yet generated publications. Below is a listing of publications related to the three studies from which the SAGE sample was selected. COGA has over 228 publications listed at www.niaaagenetics.org This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to addiction through a large-scale genome-wide association study of DSM-IV alcohol dependent (and frequently illicit drug dependent) cases and non-dependent, unrelated control subjects of European and African American descent. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

Study phs000092

Projects

Projects Jointly managed by the European Bioinformatics Institute (EMBL-EBI) in Cambridge (UK) and the Centre for Genomic Regulation (CRG) in Barcelona, the EGA provides an invaluable service to the worldwide biomedical research community. The teams leading the EGA are involved in several international partnerships and consortia in numerous scientific fields, where they contribute to ambitious projects. In addition to the project listed below, The EGA is in a long-standing partnership with the Global Alliance for Genomics and Health (GA4GH), as described on the dedicated page. On-going projects Project Duration Domain Funder Tags EASIGEN-DS | The EASIGEN-DS project aims to conduct a design study to establish a new European Research Infrastructure on Advanced Genomics Technologies, EASIGEN. To develop an excellent scientific, technological and operational design, we will conduct landscape studies, stakeholder consultations, and community surveying. 2025-2028 Genomic and health data Horizon Europe DATA MANAGEMENT DOCUMENTATION INFRASTRUCTURE Go-IMPaCT | Go-IMPaCT will contribute sequenced genomes and provide infrastructure as part of IMPaCT-Cohort, one of the three fundamental pillars of the Precision Medicine Infrastructure associated with Science and Technology (IMPaCT) program in Spain. Along with the Genome of Europe (GoE) project, around 18.000 people will have their genomes sequenced, also contributing to Spain's commitments in 1+MG. Go-IMPaCT will fund the development of an EGA node to manage and share this genomic and phenoclinic data, laying the foundations for regional and ethnic genomic variability in Spain to be available for research purposes. The IMPaCT cohort is created with the spirit of being an open research tool, compatible with the rest of the health research ecosystem, and other international initiatives. 2025-2027 Large-scale genomics and health data; personalised medicine Instituto de Salud Carlos III ACCESS DISCOVERY INFRASTRUCTURE METADATA STANDARDS FAIR-FEGA | This project seeks to accelerate data depositions into FEGA, significantly increasing the data flow in and from FEGA nodes. It will build capacity within the FEGA nodes and increase awareness in a wide range of stakeholders, thus altogether achieving the ultimate goal of enhancing data reuse. The project will be carried out by a strategic consortium comprising seven ELIXIR nodes and two ELIXIR communities. 2025-2026 Not applicable ELIXIR ACCESS DISCOVERY DOCUMENTATION INFRASTRUCTURE METADATA STANDARDS FEGA-Connect | A consortium of six ELIXIR nodes plus the Polish FEGA node (in-kind contribution) joining forces to build a solid base to develop solutions for effective multi-omic sensitive data integration between FEGA nodes and other infrastructures and specialised Data repositories. We aim to promote a more coherent data deposition, discoverability and retrieval of multi-omics datasets, providing FAIRer data and consequently accelerating research. 2025-2026 Multi-omics data ELIXIR ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE METADATA STANDARDS IMPaCT-Data 2 | IMPaCT-Data 2 will develop a digital platform for the integration and modelling of biomedical data associated with IMPaCT (Precision Medicine Infrastructure associated with Science and Technology) projects in Spain. It will deploy a sustainable infrastructure that facilitates the integration, standardisation, interoperability and analysis of clinical, genomic, molecular and medical imaging data. This platform will be aligned with European projects such as Genome of Europe (GoE), the first project to make use of the European Genomic Data Infrastructure (GDI), and EUCAIM. IMPaCT-Data 2 will benefit from advanced Artificial Intelligence and High Computing Capacity Systems capabilities, offering robust and accessible tools for researchers from the National Health System in Spain. 2025-2026 Large-scale genomics and health data; personalised medicine Instituto de Salud Carlos III ACCESS DISCOVERY INFRASTRUCTURE METADATA STANDARDS ERDERA | The European Rare Disease Research Alliance (ERDERA) takes over EJPRD to deliver concrete health benefits to rare disease patients in the next decade by advancing prevention, diagnosis and treatment research. To leave no one behind, over 170 organisations championed by the European Union and member states are working hand in hand to make Europe a world leader in rare diseases research and innovation. 2024-2034 Rare diseases Horizon Europe; "La Caixa" Foundation cofunds CRG's contribution ACCESS DATA ANALYSIS DISCOVERY INFRASTRUCTURE GoE | The Genome of Europe initiative aims to build a European network of national genomic reference cohorts of at least 500.000 citizens. These reference cohorts will be selected to be representative of the European population. 2024-2028 Large-scale genomic and health data Horizon Europe ACCESS DISCOVERY INFRASTRUCTURE METADATA STANDARDS HEREDITARY | HEREDITARY aims to transform the way we approach disease detection, prepare treatment response, and explore medical knowledge by building a robust, interoperable, trustworthy, and secure framework that integrates multimodal health data (including genetic data) while ensuring compliance with cross-national privacy-preserving policies. 2024-2027 Neurodegenerative disorders, gut-brain interplay Horizon Europe DATA MANAGEMENT DATA ANALYSIS EOSC-ENTRUST | The mission of EOSC-ENTRUST is to create a European network of trusted research environments for sensitive data and to drive European interoperability by joint development of a common blueprint for federated data access and analysis. 2024-2026 Trusted Research Environment Horizon Europe INFRASTRUCTURE EBV-MS | "Targeting Epstein-Barr Virus Infection for Treatment and Prevention of Multiple Sclerosis". The ambitious goals of the project are to answer the questions why only a few EBV infected persons develop MS, and define the underlying mechanism of this process, as well as clarify if targeting the EBV infection can prevent MS or improve the disease course. 2023-2028 Viral-host genetics; immune response; disease modelling; Disease prevention Horizon Europe DATA MANAGEMENT DATA ANALYSIS WISDOM | WELL-BEING IMPROVEMENT THROUGH THE INTEGRATION OF HEALTHCARE AND RESEARCH DATA AND MODELS WITHOUT BORDER FOR CHRONIC IMMUNE-MEDIATED DISEASES aims to deploy novel approaches for data processing, harmonisation, management, and secure data sharing and federated access for diseases like multiple sclerosis. Using an end-user guided approach, it will facilitate responsible and critical assessment of the use of AI in healthcare. 2023-2028 Chronic immune-mediated diseases Horizon Europe DATA MANAGEMENT INFRASTRUCTURE EUCAIM | EUropean Federation for CAncer IMages is a project that will build a highly secure, federated and large-scale European cancer imaging platform, with capabilities that will greatly enhance the potential of Artificial Intelligence in oncology. 2023-2027 Cancer Digital Europe Programme (DIGITAL) DISCOVERY CONTAGIO | CONTAGIO (COhorts Network To be Activated Globally In Outbreaks) aims to create coordination mechanisms to rapidly react to infectious disease (re-)emergence in low- and middle-income countries (LMICs). 2023-2026 Infectious Diseases European Commission - Horizon Europe ACCESS DATA MANAGEMENT DISCOVERY Youth-GEMs | Youth-GEMS (Gene Environment Interactions in Mental Health TrajectorieS of Youth) will conduct research into the genetic and environmental factors of mental health in young European people. 2022-2027 Mental health European Commission - Horizon Europe DATA MANAGEMENT DISCOVERY GDI | The European Genomics Data Infrastructure project is enabling access to genomic and related phenotypic and clinical data across Europe. It is doing this by establishing a federated, sustainable and secure infrastructure to access the data. 2022-2026 Genomic and health data European Commission - Horizon Europe; "La Caixa" Foundation cofunds CRG's contribution DISCOVERY DOCUMENTATION INFRASTRUCTURE EOSC4Cancer | EOSC4Cancer builds on existing projects, research outcomes and established community solutions to create the federated FAIR data, analysis and services infrastructure needed for European Cancer research programmes. 2022-2025 Cancer European Commission - Horizon Europe DISCOVERY IMPaCT-T2D | The IMPaCT-T2D project aims at studying the complete genomes of a large cohort of patients with Type 2 Diabetes mellitus (T2D), using modern sequencing technologies and artificial intelligence (AI) in order to improve the stratification and pharmacological treatment in the context of precision medicine. 2022-2025 Cardiovascular and Complex Diseases Spanish Ministry of Science and Innovation; Instituto de Salud Carlos III ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE EuCanImage | A European Cancer Image Platform Linked to Biological and Health Data for Next-Generation Artificial Intelligence and Precision Medicine in Oncology. 2020-2025 AI Solutions in Oncology European Commission - H2020 Programme; "La Caixa" Foundation cofunds CRG's contribution DATA MANAGEMENT METADATA STANDARDS GenoMed4ALL | A consortium built to empower personalised medicine in the field of haematological diseases through the use of AI and the pooling of genomic and clinical data. 2020-2025 Hematological diseases European Commission - H2020 Programme DISCOVERY METADATA STANDARDS Completed projects Project Duration Domain Funder Tags BY-COVID | The BeYond-COVID project aims to make COVID-19 data accessible to scientists in laboratories but also to anyone who can use it, such as medical staff in hospitals or government officials. Going beyond SARS-CoV-2 data, the project will provide a framework for making data from other infectious diseases open and accessible to everyone. 2021-2024 Infectious diseases European Commission - H2020 Programme ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE IMPaCT-Data | IMPaCT-Data aims to create the infrastructure for secondary use of data from Spanish healthcare systems - electronic health records, medical imaging and genomic repositories - and contribute with the knowledge and methodology produced to the healthcare system. 2021-2024 Large-scale genomics and health dataSpanish Ministry of Science and Innovation; Instituto de Salud Carlos III ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE LaMarató | It is a project aimed at creating and developing a catalan interhospitalary network to interrogate genetic variants from thousands of genetic tests carried out in patients with rare diseases from the main catalan hospitals. 2021-2024 Genomic and health data Fundació La Marató de TV3 (catalan foundation) DISCOVERY HealthyCloud | This consortium will contribute a Strategic Agenda towards the European Health Research and Innovation Cloud. The project will work in collaboration with a broad range of stakeholders to ensure that all voices are included and that the results are technically and ethically sound. 2021-2023 Not Applicable European Commission - H2020 Programme DOCUMENTATION B1MG | Beyond 1 Million Genomes aims to create a network of genetic and clinical data across Europe. The project provides coordination and support to the 1+ Million Genomes Initiative (1+MG). This initiative is a commitment of 24 EU countries, the UK and Norway to give cross-border access to one million sequenced genomes by 2022. 2020-2023 Not applicable European Commission - Horizon Europe DATA MANAGEMENT INFRASTRUCTURE METADATA STANDARDS ELIXIR-CONVERGE | An alliance with the goal of Connecting and aligning ELIXIR Nodes to deliver sustainable FAIR life-science data management services. 2020-2023 Data Management and Infectious Diseases European Commission - H2020 Programme DATA MANAGEMENT INFRASTRUCTURE METADATA STANDARDS IHCC | The International HundredK+ Cohorts Consortium aims to create a global platform for translational research – informing the biological and genetic basis for disease and improving clinical care and population health. 2020-2022 Translational research NIH; The Wellcome Trust; CZI INFRASTRUCTURE METADATA STANDARDS PPCG | The Pan Prostate Cancer Group aims to harmonise and interrogate Whole Genome DNA Sequence data generated around the world from over 2000 men with prostate cancer, with associated transcriptome and methylome data to include men from different clinical categories, and ethnicities. This project is about providing breakthrough advances through analysis of a very large series of Whole Genome DNA data from prostate cancer contributed by many of the leading scientists and clinicians working in prostate cancer genomics. 2019-2024 Cancer Cancer Research UK DATA MANAGEMENT CINECA | Consortium providing a Federated solution enabling population-scale genomic and biomolecular data accessible across international borders accelerating research and improving the health of individuals resident across continents. 2019-2023 Large-scale Genomics and Health Data European Commission - H2020 Programme ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE EASI-Genomics | A project designed to provide easy access to cutting-edge DNA sequencing technologies to researchers from academia and industry, within a framework that ensures compliance with ethical and legal requirements, as well as FAIR and secure data management. 2019-2023 Next Generation Sequencing European Commission - H2020 Programme ACCESS EJP-RD | An European consortium built to create a comprehensive, sustainable ecosystem allowing a virtuous circle between research, care, and medical innovation. 2019-2023 Rare diseases European Commission - H2020 Programme ACCESS DATA MANAGEMENT DOCUMENTATION METADATA STANDARDS EOSC-Life | EOSC-Life brings together the 13 Life Science research infrastructures (LS RIs) to create an open, digital and collaborative space for biological and medical research. The project will publish 'FAIR' data and a catalogue of services provided by participating RIs for the management, storage and reuse of data in the European Open Science Cloud (EOSC). 2019-2023 Not applicable European Commission - H2020 Programme DOCUMENTATION EUCANCan | A federated network aiming at implementing a cultural, technological and legal integrated framework across Europe and Canada, to enable and facilitate the efficient sharing of cancer genomic data. 2019-2023 Cancer European Commission - H2020 Programme DATA MANAGEMENT METADATA STANDARDS The Federated EGA framework: supporting sensitive data management across the ELIXIR Nodes | This project is a direct continuation of the FHD IS with the goal to position the FEGA framework as the core infrastructure driver to support human data sharing for research. 2019-2023 Human genomic data ELIXIR INFRASTRUCTURE UK Biobank | UK Biobank is a large-scale biomedical database and research resource, containing in-depth genetic and health information from half a million UK participants. This project is to archive whole genome sequencing and other genetic data for UK Biobank participants. 2019-2023 Large-scale Genomics and Health Data The Wellcome Trust; UKRI; Amgen; AstraZeneca; GSK; Johnson & Johnson DATA MANAGEMENT INFRASTRUCTURE VEIS | The core mission of VEIS is to create an open ecosystem of technologies that will address and adapt to the requirements of the systems used to analyse and interpret -omics and clinical data in research and application environments in biomedicine. The aim of the project is to leverage the value of the EGA for both industry and society. 2019-2022 Oncology and Rare diseases Generalitat de Catalunya and European Regional Development Fund (ERDF) ACCESS DISCOVERY ELIXIR BEACON IS | This study follows on from a number of earlier activities that have established the ELIXIR Beacon Project. The main aim is to extend the Beacon protocol, developed at EGA, to become the reference ELIXIR Data Discovery product 2019-2021 Not applicable ELIXIR DISCOVERY ELIXIR FHD IS | This project coordinates the delivery of FAIR compliant metadata standards, interfaces, and reference implementation to support the federated ELIXIR network of human data resources. 2019-2021 Human genomic data ELIXIR INFRASTRUCTURE ELIXIR Rare Disease | The Rare Disease Community extends and generalises the system of access authorisation and high volume secure data transfer developed within the EGA. The goal of the Community is to create a federated infrastructure that will enable researchers to discover, access and analyse different rare disease repositories across Europe. It is doing this in partnership with other European infrastructure projects, namely RD-CONNECT, BBMRI-ERIC and E-Rare.2019-2021 Rare diseases ELIXIR INFRASTRUCTURE Solve-RD | Solve-RD - solving the unsolved rare diseases - is a research project funded by the European Commission. It echoes the ambitious goals set out by the International Rare Diseases Research Consortium (IRDiRC) to deliver diagnostic tests for most rare diseases by 2020. The current diagnostic and subsequent therapeutic management of rare diseases is still highly unsatisfactory for a large proportion of rare disease patients - the unsolved RD cases. For these unsolved rare diseases, we are unable to explain the etiology responsible for the disease phenotype, predict the individual disease risk and/or rate of disease progression, and/or quantitate the risk of relatives to develop the same disorder. 2018-2024 Rare diseases European Commission - H2020 Programme ACCESS DATA MANAGEMENT METADATA STANDARDS EuCanShare | An EU-Canada joint infrastructure for next-generation multi-Study Heart research. 2018-2022 Cardiovascular Diseases European Commission - H2020 Programme ACCESS METADATA STANDARDS

Documentation about/projects-and-funders/projects

Assessment of Health-related Quality of Life in Rare Kidney Stones

The purpose of this study is to learn about Health-related Quality Of Life (HRQoL) in patients enrolled in the Rare Kidney Stone Consortium (RKSC) registries. Quality of life studies look at different aspects of both physical and mental components of people's lives. HRQoL data for people affected by kidney stones are not currently available for people followed over time. All participants enrolled in the RKSC registries will be invited, via email or postal mail, to participate in this study. Health-related quality of life in people with rare kidney stones enrolled in the RKSC registries will be measured. Instruments used in this study are the SF-10 for pediatric participants and SF-36v2 for adult participants. The surveys will be completed online. Participants without a computer or internet access will participate using a paper version of the survey. These surveys will be done at enrollment and annually thereafter. The SF-36v2 includes 36 questions and is estimated to take 15 minutes for its completion, while the SF-10 includes 10 questions and could be completed in 5 minutes. The research questions are: Assessment of HRQoL in patients with rare kidney stones. Comparison of HRQoL results between rare kidney stone formers, general population and other populations with relevant chronic diseases. Comparison of HRQoL results in the same populations affected by different stones and analyzed with attention to the effects of various factors included in the disease registry, such as stone activity, burden of urologic interventions, medication and other treatments. Evaluation of HRQoL and its trends over time in patients undergoing treatment for rare kidney stones. About this study: The plan is to have 400 participants from all four registries take part in this multi-center study. The assessment of your HRQoL will be done annually for 5 years.

Study phs001770

NINDS-Genome-Wide Genotyping in Parkinson's Disease: First Stage Analysis and Public Release of Data

Epidemiological studies have estimated a cumulative prevalence of PD of greater than 1 per thousand. When prevalence is limited to senior populations, this proportion increases nearly 10-fold. The estimated genetic risk ratio for PD is approximately 1.7 (70% increased risk for PD if a sibling has PD) for all ages, and increases over 7-fold for those under age 66 years. The role for genes contributing to the risk of PD is therefore significant. This study utilized the well characterized collection of North American Caucasians with Parkinson's disease, and neurologically normal controls from the sample population which are banked in the National Institute of Neurological Disorders and Stroke (NINDS Repository) collection for a first stage whole genome analysis. Genome-wide, single nucleotide polymorphism (SNP) genotyping of these publicly available samples was originally done in 267 Parkinson's disease patients and 270 controls, and this has been extended to include genome wide genotyping in 939 Parkinson's disease cases and 802 controls. The NINDS repository was established in 10-2001 towards the goal of developing standardized, broadly useful diagnostic and other clinical data and a collection of DNA and cell line samples to further advances in gene discovery of neurological disorders. All samples, phenotypic, and genotypic data are available to the research community including to academics and industry scientists. In addition, well characterized neurologically normal control subjects are a part of the collection. This collection formed the basis of this first stage study by Fung et al., and the expanded study by Simon-Sanchez et al. The genotyping data was generated and provided by the laboratory of Dr. Andrew Singleton NIA, and Dr. John Hardy NIA (NIH Intramural, funding from NIA and NINDS). Important links to apply for individual-level data Data Use Certification Requirements (DUC) Apply here for controlled access to individual level data Participant Protection Policy FAQ

Study phs000089

Whole Exome Sequencing of Calcitonin Producing Pancreatic Neuroendocrine Neoplasms (CT-pNENs) Indicates a Unique Molecular Signature

Calcitonin-producing pancreatic neuroendocrine neoplasms (CT-pNENs), which can mimic clinical and laboratory features of medullary thyroid carcinoma, are an extremely rare clinical entity with approximately 60 cases reported worldwide. The molecular profile of CT-pNENs is not yet known. Whole-exome sequencing (WES) was performed on tumor and corresponding serum samples of five patients with increased calcitonin serum levels and histologically proven calcitonin-positive CT-pNENs. cBioPortal analysis and gene enrichment analysis with DAVID were performed to validate candidate genes. Immunohistochemistry was used to detect protein expression of MUC4 and MUC16 in CT-pNEN specimens. Common somatic mutations of pNENs like MEN1, ATRX and PIK3CA were identified in cases of CT-pNENs. New somatic SNVs in ATP4A, HES4, and CAV3 have not yet been described in CT-pNENs. Pathogenic germline mutations in FGFR4 and DPYD were found in three of five cases. Mutations of CALCA (calcitonin) and the corresponding receptor CALCAR were found in all five tumor samples, but none of them resulted in clinical or protein sequelae. All five tumor cases showed single nucleotide variations (SNVs) in MUC4, and four cases showed SNVs in MUC16, both of which were membrane-bound mucins. Immunohistochemistry showed protein expression of MUC4 and MUC16 in one case each, and the liver metastasis of a third case was double positive for MUC4 and MUC16. The homologous recombination deficiency (HRD) score of all tumors was low.CT-pNENs have a unique molecular signature compared to other pNEN subtypes, specifically involving the FGFR4, DPYD, MUC4, MUC16 and the KRT family genes. However, these WES data from only five cases must be interpreted with caution because causal interpretation of the mutational landscape in CT-pNENs is difficult. Further research is needed to explain differences in pathogenesis compared with other pNENs. In particular, multi-omics data such as RNASeq, methylation, and whole genome sequencing could be informative.

Study phs003060

Population Architecture using Genomics and Epidemiology (PAGE): Multiethnic Cohort (MEC)

The Multiethnic Cohort (MEC) has established a large biorepository of blood and urine (N=67,000) and cryopreserved lymphocytes (N=15,000) linked to extensive, prospectively collected risk factors (e.g., diet, smoking, physical activity), biomarkers and clinical data for five racial/ethnic groups. This cohort study of over 215,000 men and women in Hawaii and California is unique in that it is population-based and includes large representations of older adults (45-75 yrs at baseline) for five US racial/ethnic groups (Japanese Americans, African Americans, European Americans, Latinos and Native Hawaiians) at varying risks of chronic diseases. Within the PAGE investigation, the MEC proposes to study: 1) diseases for which we have DNA available for large numbers of cases and controls (breast, prostate, and colorectal cancer, diabetes, and obesity); 2) important cancers that are less common (e.g., lung, pancreas, endometrial cancers, NHL) but for which we propose to pool our data with other funded groups; 3) common traits that are risk factors for these diseases (e.g., body mass index/weight, waist-to-hip ratio, height) and 4) relevant disease-associated biomarkers (e.g., fasting insulin and lipids, steroid hormones). The specific aims are: 1) To determine the population-based epidemiologic profile (allele frequency, main effect, heterogeneity by disease characteristics) of putative causal variants in the five racial/ethnic groups in the MEC; 2) for variants displaying effect heterogeneity across ethnic/racial groups, we will utilize differences in LD to identify a more complete spectrum of associated variants at these loci; 3) investigate gene x gene and gene x environment interactions to identify modifiers; 4) examine the associations of putative causal variants with already measured intermediate phenotypes (e.g., plasma insulin, lipids, steroid hormones); and 5) for variants that do not fall within known genes, start to investigate their relationships with gene expression and epigenetic patterns in small genomic studies. This study is part of the Population Architecture using Genomics and Epidemiology (PAGE) study phs000356.

Study phs000220

Genome-wide Association Study for Non-syndromic Clefts in the African Population: CIDR

The focus of this project is to identify genetic variants that are associated with orofacial clefts in African populations in sub-Saharan Africa. Most genetic studies of CLP (including the vast majority of GWAS) have been conducted in populations of European origin with only a few focused on Asian or African populations. We choose to study the genetics of these complex traits in African populations because, African populations have the greatest genetic variation amongst the various populations in the world by virtue of being the primary ancestral population to modern humans (Cavalli-Sforza and Feldman, 2003; Ramsay et al., 2011). Therefore, the potential for finding novel loci for CLP is quite high. To date 6 genome wide association studies (GWAS) for cleft lip with or without cleft palate (CL/P) have been conducted and 18 risk loci identified (Birnbaum et al., 2009; Grant et al., 2009 ; Beaty et al., 2010; Mangold et al., 2010; Ludwig et al., 2012; Sun et al., 2015). All these studies have either been conducted in European populations, Asian populations or both. There is currently no published GWAS for clefts in African populations. African populations represent a novel and richly productive populations for genetic and environmental exposure studies for CL/P. Investigating the presence of genetic variants in diverse population groups can identify novel variants and candidate genes that are population specific. Environmental factors may also increase the risks in certain population groups due to genetic susceptibility and/or specific exposures. Understanding the role these susceptibility genes play in the effects of environmental risk factors can inform strategies designed towards reducing the outcome of these complex traits, e.g. through the modification of the environmental influences. The study population comprises a large number of individuals (3205 individuals) from Africa (Ghana, Ethiopia and Nigeria). There are cases, case triads (nuclear families), as well as controls with no history of OFC nor other developmental defects.

Study phs001090

Metagenomic Analysis to Identify Novel Infectious Agents in Systemic Anaplastic Large Cell Lymphoma

Anaplastic large cell lymphoma (ALCL) is a rare T-cell non-Hodgkin lymphoma (NHL). Risk of systemic ALCL is markedly increased among immunosuppressed people, such as those with human immunodeficiency virus (HIV) infection or solid organ transplant recipients. This increased risk in immunosuppressed populations suggests a viral etiology, given similar elevations for diffuse large B-cell lymphoma (DLBCL), Burkitt lymphoma, and Hodgkin lymphoma (caused by Epstein-Barr virus [EBV]) and other virus-related cancers in immunosuppressed individuals. EBV might be a plausible candidate, but most reported ALCL tumors are EBV-negative. Therefore, we conducted a metagenomic analysis of microbial associations with ALCL to determine whether a known or novel pathogen is associated with the tumor. We obtained archived formal fixed paraffin embedded (FFPE) ALCL tumor tissue from the Iowa cancer registry and an additional case from an immunosuppressed individual infected with human immunodeficiency virus. Controls included 3 diffuse large B-cell lymphomas (DLBCLs) in transplant recipients (shown to be related to Epstein-Barr virus [EBV] by in situ hybridization) and 3 breast cancers (no known viral etiology). RNA was extracted from FFPE specimens, and total RNA libraries were prepared using the KAPA RNA HyperPrep Kit (Roche). Five samples (IA01, IA53, IA57, IA07, and IA17) were sequenced on a NextSeq 500 (Illumina) and the remainder on a NovSeq 6000 (Illumina). Using novel computational approaches, we eliminated human reads and aligned residual non-human reads to known microbial references using GATK-PathSeq or conducted de novo assembly of unassigned reads using virID pipeline. Although EBV was detected in the 3 DLBCL controls, we did not detect EBV or any novel pathogen in ALCL tumors or in the breast cancers. Our study had a modest sample size and only one case arising in HIV-infected individual. Therefore, further studies are required to characterize the metagenome of systemic ALCLs, especially cases arising in immunosuppressed people.

Study phs002064

Bone Microarchitecture

Osteoporosis affects more than 28 million people in the United States and the lifetime risk for osteoporosis-related morbidity is higher than a woman's combined risk for breast cancer, endometrial cancer and ovarian cancer. Health care expenditures for osteoporotic patients in this country are currently nearly 13 billion dollars per annum and are predicted to increase markedly in the next decades due the aging of the population; therefore, it is important to understand the factors that contribute to bone strength and fracture risk. With the advent of skeletal imaging modalities such as high resolution peripheral quantitative computed tomography (HR-pQCT), it is now possible to study the genetics of more highly refined peripheral skeletal microarchitecture phenotypes. Because these refined phenotypes have not been measured in many cohort studies, this project was a collaborative effort to include almost all the existing data on HR-pQCT of the radius and tibia, and genetics from around the world. Cohorts involved in the discovery included: 1) Framingham Osteoporosis Study, 2) Mayo Clinic cohort; 3) Geneva Retirees cohort; 4) OFELY cohort from Lyon France; 5) STRAMBO cohort from Lyon France; 6) Swedish Male cohorts. Replication cohorts undergoing de novo genotyping include: 1) QUALYOR cohort from Lyon France; 2) CaMOS cohort from Canada. Other than the Framingham cohort and the Swedish male cohorts, all discovery cohorts underwent genome wide genotyping with the Affymetrix Axiom Biobank array that had common variants along with exome content based on the early findings from the Exome Sequencing Project. All genotype data from the discovery cohorts were then imputed using the Haplotype Reference Consortium reference panel. Variants for replication genotyping using the Kasp technology were selected based on novelty compared with previously identified loci using DXA phenotypes, minor allele frequency, underlying LD structure within a locus, and likelihood of a variant being functional as assessed using various algorithms for coding and non-coding variants.    

Study phs002102

The Sea Islands Genetic Network (SIGNET): Identifying genetic contributors to diabetes and dyslipidemia in African Americans

Recent genome-wide association studies (GWAS) have successfully identified genetic variants that influence diabetes risk in European populations, however most do not have a major impact on diabetes risk in populations of African descent. The African American (AA) population from the Sea Islands of coastal South Carolina and Georgia has high rates of type 2 diabetes, low levels of admixture, and in general, consume a diet rich in saturated fats. We postulate that this unique combination of ancestral and environmental factors results in a more consistent penetrance of diabetes risk alleles, as well as enrichment of risk alleles of African origin. The existing DNA samples and rich phenotypic data from the Sea Island Families Project comprise a unique resource for genetic studies of type 2 diabetes and related metabolic traits such as dyslipidemia. Our central hypothesis is that the increased risk for T2DM in AA compared with European American (EA) is due, in part, to susceptibility alleles of African origin, and that these alleles can be identified using a GWAS. The Specific Aims are to: 1) Identify genetic risk factors for type 2 diabetes utilizing DNA samples and data from the Sea Island Families Project, Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study recruited from SC, GA, NC, and AL; and a GWAS approach; 2) Identify genetic contributors to lipoprotein subclasses in African Americans using the lipoprotein subclass profile (particle size and concentration for multiple subclasses of VLDL, LDL, and HDL) assessed by NMR at LipoScience, Inc., and the GWAS data from Aim 1. The rationale for this project is that identification and validation of novel pathophysiological pathways and informed selection of candidate genes for diabetes risk will inform development of new, targeted prevention and treatment strategies in this underserved, high risk population.

Study phs000433

National Institute on Aging - Late Onset Alzheimer's Disease Family Study: Genome-Wide Association Study for Susceptibility Loci

Alzheimer disease is the most common neurodegenerative disorder of the elderly affecting an estimated five million Americans. Genetic factors contribute to the risk for disease with heritability estimates ranging from 57% to 79%. More than a decade ago, the ε4 variant of APOE was identified and remains the most consistently replicated genetic variant influencing the risk of late onset Alzheimer disease. A segregation analysis suggests there may be four additional genes influencing the age-at-onset of Alzheimer disease. In 2007 there were 968 association studies in 398 candidate genes reported, but none replicated consistently. There are many reasons for the lack of consistency, but one important reason for the lack of progress is the paucity of a sufficient number of well characterized families and patients available to the entire scientific community. The extensive effort and expense required to ascertain such a population has been addressed by the NIA-LOAD Family Study. Its goal is to identify and recruit families with two or more siblings with the late-onset form of Alzheimer's disease and a cohort of unrelated, non-demented controls similar in age and ethnic background, and to make the samples, the clinical and genotyping data and preliminary analyses available to qualified investigators world-wide. Genotyping by the Center for Inherited Disease Research (CIDR) was performed using the Illumina Infinium II assay protocol with hybridization to Illumina Human 610Quadv1_B Beadchips. This genotyping represents the largest collection of families ever assembled with Alzheimer's disease combining the NIA-LOAD Genetics Initiative Multiplex Family Study, the National Cell Repository for Alzheimer's Disease (NCRAD) with additional controls from the University of Kentucky. These genotyping results will serve as a focal point for future research that will identify all of the remaining genetic variants in Alzheimer's disease.

Study phs000168

Foundation Medicine Adult Cancer Clinical Dataset (FM-AD)

The Foundation Medicine adult cancer clinical dataset consists of 18,004 unique solid tumor samples that underwent genomic profiling on a single uniform platform as part of standard clinical care. The dataset is derived from the FoundationOne® genomic profiling assay version 2 that interrogates exonic regions of 287 cancer-related genes and selected introns from 19 genes known to undergo rearrangements in human cancer. Genomic DNA samples were sequenced to over 500x median coverage, and custom computational analyses identified all classes of genomic alterations (base substitutions, insertions and deletions, copy number alterations, and rearrangements). Since matched normal tissue was unavailable for analysis, these data underwent additional filtering to enrich for cancer-related events. The reported data includes genomic alterations that are known and suspected tumor drivers, as well as variants of unknown significance. To preserve patient anonymity, all known or suspected germline variants were removed from the data unless known to be associated with cancer development. The dataset contains genomic alteration profiles generated by FoundationOne version 2 testing for adult cancer patients (over 18 y.o.), and represents a vast diversity of tumor subtypes, including many rare diseases not profiled as part of large-scale profiling efforts. Cases are grouped into 16 broad disease categories containing tumors from 162 unique disease subtypes. Since specimens were profiled as part of clinical care, limited clinical parameters were available, including age, gender, tissue of origin, % of tumor nuclei, and diagnosis. Publication of this dataset is intended to allow the broad scientific community access to this unique cohort for use in scientific research projects of common and rare types of cancer, both for generating leads regarding causal mechanisms as well as cross-testing and confirming existing hypotheses. A pediatric cancer clinical dataset consisting of data from 1,215 patients under 18 y.o. is available separately at: FOUNDATION MEDICINE

Study phs001179

National Institute of Neurological Disorders and Stroke (NINDS), Family Study of Essential Tremor (FASET), Identification of Susceptibility Genes for Essential Tremor

The Familial Study of Essential Tremor (FASET) was designed to identify susceptibility genes for Essential Tremor. ET is among the most common neurological diseases with a prevalence (age > 40 years) estimated to be 4.0% and prevalence in advanced age (> 90 years) exceeding 20%. ET, often referred to as "familial tremor", is generally regarded as a highly genetic disorder with families, with affected members over multiple generations, and twin studies show high concordance among monozygotic twins. Probands (affected with ET) and relatives were enrolled in a family study of ET at Columbia University, New York between 2011 - 2014. The study was approved by the Institutional Review Board at Columbia University and written informed consent was obtained from all enrollees. The criteria for enrollment were: 1) the proband had early-onset ET with age at onset < 50 years, 2) the proband had a diagnosis of definite or probable ET, 3) in addition to the proband, there were at least two affected relatives in the family, 4) additional affected and unaffected family members were willing to participate in the study, and 5) the families contained more than two affected individuals in different generations. Blood samples were also collected for genetic research. For the genetic analyses, we excluded enrollees that we or others had diagnosed with Parkinson's disease (PD) or dystonia. The final sample includes 52 families (52 probands [affected with ET]) and 155 relatives). The number of affected individuals enrolled per family ranged from 3 - 7 (mean = 4.1). Genetic samples from FASET were analyzed with whole genome SNP genotyping (for linkage analyses) and whole exome sequencing. It is hoped that this resource will better help researchers to understand the genetic causes of ET and underlying disease pathogenesis.

Study phs000966

Functional Significance of Prostate Cancer Risk-SNPs

Prostate Cancer (PrCa), the most frequently diagnosed solid tumor in men in the U.S., results in ~192,000 new cases and ~27,000 deaths per year. Although the variation of PrCa incidence is likely to be the result of several factors, there is a large body of literature that strongly implicates a genetic etiology. Genome-wide association studies (GWAS) have emerged as the most widely used contemporary approach to identify genetic variants (in particular SNPs) that are associated with increased risk of human disease. For PrCa, at least five GWAS have now been performed yielding a substantial number of well-validated SNPs that are associated with an increased risk of PrCa, and that number continues to grow. A significant problem for many of the PrCa risk-SNPs identified so far, however, is that they do not lie within or near a known gene and they have no obvious functional properties. These findings suggest that many (if not most) of these risk-SNPs will be located in regulatory regions that control gene expression rather than in coding regions that may directly affect protein function. Therefore, in order to define the functional role of currently known risk-SNPs, the target genes must first be identified. A promising strategy to address this problem involves the use of expression quantitative trait loci (eQTL) analysis. Unfortunately, most of the publically available SNP-Transcript eQTL datasets utilize lymphoblastoid cells with only a handful using tissue from target organs. Although useful, these datasets alone are unlikely to be sufficient. Recent studies have demonstrated that gene expression and gene regulation occur in both a tissue-specific and tissue independent fashion and suggest that a complete repertoire of regulatory SNPs can only be uncovered in the context of cell type specificity. To date, such a tissue-specific dataset for normal prostate tissue does not exist. In this study, we have constructed a normal prostate tissue specific eQTL data set.

Study phs000985

ARDSnet and the iSPAAR Consortium: Genomic Basis of Susceptibility and Outcomes in Patients with the Acute Respiratory Distress Syndrome (ARDS)

Acute Respiratory Distress Syndrome (ARDS)/ Acute Lung Injury (ALI) is a syndrome defined by the presence of acute hypoxemic respiratory failure, bilateral pulmonary infiltrates on chest radiograph, a known clinical risk factor (e.g. sepsis, pneumonia, trauma, gastric fluid aspiration, pancreatitis, massive transfusion), and the absence of physiologic or clinical evidence of congestive heart failure. The Identification of SNPs Predisposing to Altered ALI Risk (iSPAAR) study is a multi-institutional cooperative study, funded through the NHLBI Recovery Act, that assembled samples and phenotype information from existing cohorts. The consortium included samples from patients with ARDS from the NIH NHLBI ARDS Clinical Trials Network (ARDSNet). Samples were obtained from 3 interventional treatment trials in patients with ARDS, including the Fluid and Catheter Treatment Trial (FACTT), the Albuterol to Treat Acute Lung Injury (ALTA) trial, and the Omega-3 Fatty Acid/Antioxidant Supplementation for ALI trial (Omega). In addition to ARDSnet samples, samples from the other cohorts included cases of established ARDS but also controls: critically ill patients who were at-risk for ARDS but who did not develop ARDS during their hospital course. These cohorts included the Molecular Epidemiology of Acute Respiratory Distress (MEA) Study enrolled at the Harvard University/Massachusetts General Hospital, the Systemic Inflammatory Immune Response Syndrome (SIRS) Patient Database and ICU Traumatic Injury cohorts from Harborview Medical Center, and cohorts collected from the ALI research programs at the University of Pennsylvania and the University of California, San Francisco. The Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000631 ARDSnet iSPAAR Consortium. phs000334 ESP_LungGO_ALI phs000686 ALI_GeneticRisk

Study phs000631

Gene Environment Association Studies (GENEVA): Genetics of Early Onset Stroke (GEOS) Study

The Genetics of Early Onset Stroke (GEOS) Study is a population-based case-control study designed to identify genes associated with early-onset ischemic stroke and to characterize interactions of identified stroke genes and/or SNPs with environmental risk factors such as smoking and oral contraceptive use. The GEOS study consists of 921 ischemic stroke cases with age of first stroke 16-50 years and a similar number of controls, identified from the Baltimore-Washington area. Cases and controls were recruited in 3 different time periods: Stroke Prevention in Young Women-1 (SPYW-1) conducted from 1992-1996, Stroke Prevention in Young Women-2 (SPYW-2) conducted from 2001-2003, and Stroke Prevention in Young Men (SPYM) conducted from 2003-2007. The overall GEOS sample includes 477 cases who self-reported their race as "white" and 396 cases who self-reported their race as "African American." Traditional stroke risk factors and other study variables, including age, ethnicity, and history of hypertension, diabetes, myocardial infarction (MI), current smoking status, and current oral contraceptive use (both defined as use within one month prior to event for cases and at a comparable reference time for controls), were also collected during standardized interview and were included as covariates in our analyses. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to early-onset ischemic stroke through large-scale genome-wide association studies of cases and controls of European and African descent from the Baltimore-Washington area. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

Study phs000292

POPRES: Population Reference Sample

POPRES version 1 and 2 Technological and scientific advances, stemming in large part from the Human Genome and HapMap projects, have made large-scale, genome-wide investigations feasible and cost-effective. These advances have the potential to dramatically impact drug discovery and development by identifying genetic factors that contribute to variation in disease risk as well as drug pharmacokinetics, treatment efficacy, and adverse drug reactions. In spite of the technological advancements, successful application in biomedical research would be limited without access to suitable sample collections. To facilitate exploratory genetic research, we have assembled a DNA resource from a large number of subjects participating in multiple studies throughout the world. This resource was initially genotyped using the Affymetrix 500K SNP panel. This project includes nearly 6,000 subjects of African American, East Asian, South Asian, Mexican, and European origin. POPRES version 3 The discovery and development of novel drugs is challenging and with high attrition rates. Selection of the right target and optimal indications for novel therapeutics represent key decision points in this process, and are often hampered by our limited understanding of the biology of the target in humans. Building a robust body of knowledge of variation within drug target genes has in several cases increased the probability of success for novel therapeutics. Our knowledge of variation within drug target genes and their influence on traits of medical interest is still very limited. In an effort to fill this gap, we resequenced the exons of 202 known or suspected drug target genes in over 16,000 well-phenotyped individuals. A total of 863,883 bases were targeted, including 351 kb of coding and 323 kb of untranslated exon regions. The sequenced subjects included 3,381 from two studies that were part of the Population Reference Sample (POPRES) project: CoLaus (N = 2,059) and LOLIPOP (N = 1,322). Genotyping data generated through the targeted next generation sequencing is available through the dbGaP.

Study phs000145

Childhood Cancer Data Initiative (CCDI): Genomic Analysis in Pediatric Malignancies

Pediatric solid tumors are highly heterogeneous, encompassing a large number of histotypes. The genomic landscape of these diseases is characterized by few single-nucleotide variants (SNVs) compared to adult cancers. In contrast, many exhibit a high prevalence of structural or epigenetic changes that alter gene expression, underlining the need for comprehensive genomic approaches such as whole-genome sequencing (WGS). Several studies have specifically addressed the clinical utility of genomic analysis in the pediatric and AYA cancer setting. Review of these studies point to key challenges that must be addressed in order to advance the routine use of genomics in this population. We have established a large collection of solid tumor tissue samples through our biobanking efforts. Where possible, we obtain longitudinal samples from the same patient. These primary patient samples and their corresponding germline have been analyzed using whole genome and whole transcriptome sequencing methods and have been linked to clinical metadata using both manual curation and robust methods for automatic extraction from the electronic health record (EHR). Importantly, research-grade genomic analysis is performed in parallel to our CLIA-grade sequencing (“UCSF500”) efforts for some of the patients in this study cohort and have been submitted as part of the American Association for Cancer Research's project GENIE and/or the National Childhood Cancer Registry. For our sequenced tumor samples, we have retrospective clinical data and ongoing efforts to prospectively record key events throughout the patient's cancer journey. In our solid tumor program, we have developed many patient-derived xenograft models and a number of PDX-derived cell lines. These unique models have been evaluated using genomic and functional approaches including (in some cases) treatment with conventional chemotherapy or investigational agents. Lastly, these samples were collected from a population that is among the most diverse in the nation and includes significant numbers of Asian, Latino, Indigenous and African-American patients, groups that are traditionally underrepresented in many banking efforts.

Study phs002430

Heart Failure Network - Effectiveness of Ultrafiltration in Treating People with Acute Decompensated Heart Failure and Cardiorenal Syndrome (HFN CARRESS - BioLINCC)

ObjectiveThe CARRESS trial examined the effectiveness of ultrafiltration compared with a strategy of diuretic-based stepped pharmacologic therapy on renal function and weight loss in patients with heart failure who have worsening renal function and persistent congestion.BackgroundAcute cardiorenal syndrome is defined as worsening renal function in patients with acute decompensated heart failure. It occurs in 25 to 33% of patients and is associated with poor outcomes. Current heart failure treatments focus on removing excess fluid buildup, however administration of intravenous diuretics may contribute to worsening renal function. Venovenous ultrafiltration is one alternative therapy that may be effective in patients with acute decompensated heart failure complicated by acute cardiorenal syndrome and persistent congestionSubjectsA total of 188 patients were randomized.DesignHospitalized subjects were randomly assigned to receive either ultrafiltration therapy or pharmacologic therapy. Ultrafiltration was performed at a fluid-removal rate of 200 ml per hour and loop diuretics were discontinued for the duration of the intervention. The addition of intravenous vasodilators or positive inotropic agents was prohibited, unless they were deemed to be necessary as rescue therapy. Patients assigned to stepped pharmacologic therapy received intravenous diuretics to manage congestion and maintain a urine output of 3 to 5 liters per day. In both groups, the assigned treatment strategy was to be continued until the signs and symptoms of congestion in the patient were reduced as much as possible. The primary end points were baseline changes in serum creatinine and weight as assessed at 96 hours after treatment assignment.ConclusionsThe use of a stepped pharmacologic-therapy algorithm was superior to a strategy of ultrafiltration for the preservation of renal function, and there was a similar amount of weight loss between the two groups. Ultrafiltration was associated with a higher rate of adverse events (Bart, et al., 2012, PMID: 23131078).

Study phs003510

GATA2 Deficiency and the MonoMAC Syndrome

The aim of this study was to identify the germline mutation(s) in an extended family with individuals having MonoMAC Syndrome/GATA2 deficiency but lacking a canonical GATA2 mutation. GATA2 deficiency patients develop bone marrow failure, severe immunodeficiency and may progress to myeloid malignancies, including myelodysplastic syndrome (MDS), acute myeloid leukemia (AML), and chronic myelomonocytic leukemia (CMML). The definitive treatment for GATA2 deficiency is a bone marrow transplant. Approximately 90% of GATA2 deficiency patients have a known de novo or inherited germline mutation in the GATA2 gene, but ~10% have no identified mutation. The study was initiated with the first patient and her second cousin, both of whom were treated for MonoMAC Syndrome and received bone marrow transplants at the NIH. Pedigree analysis and clinical evaluation identified the individuals in several generations of these patients' near and distant relatives who are/were presenting or carrying the disease manifestations of GATA2 deficiency. Whole Genome Sequencing (WGS) was employed on these patients' two related nuclear families to identify variants that segregated with the disease trait and carrier status of their families. Genotyping was confirmed with direct DNA sequencing of these and other family members within the extended family across generations. A single base adenine-to-thymidine change was identified in a highly conserved enhancer element ~117,000 bp upstream of the GATA2 gene. It creates a new Composite Element, a DNA motif known to be critical in the regulation of hematopoiesis. This variant is unique to this family and is not present in dbSNP or other variant databases. It segregates with the disease trait and obligate carriers throughout a large pedigree. In vitro studies show that this variant drives allele-specific overexpression of the GATA2 gene in cultured cells and luciferase assays. The WGS sequence from the nuclear families will be shared on dbGaP.

Study phs003269

Adult Eosinophilic Esophagitis Registry Atlas

Eosinophilic esophagitis (EoE) arises in the setting of type 2 cytokine-driven inflammation, is characterized by the infiltration of eosinophils in the esophageal mucosa, and is associated with dysphagia and fibrostenotic complications. Disease development and progression involve complex interactions between epithelial cells, stromal cells and immune cells. Indeed, increased epithelial permeability is consistently found in EoE, potentially leading to increased antigen exposure and inflammation. Persistent inflammation can in turn lead to fibroblast activation and fibrosis, which, together with the mediators produced by eosinophils and mast cells, leads to dysmotility. To decipher the interactions between these cell types across distinct disease states, we obtained biopsies from 7 healthy controls and 15 EoE subjects, including both active disease and clinical remission, to perform single cell RNA-sequencing (scRNA-seq).Each biopsy sample was enzymatically digested within 3 hours of collection with collagenase/dispase to generate a single cell suspension. Suspensions were then loaded on a 10x Chromium controller, and libraries were generated with the 3' Chemistry pipeline (v2 or v3) before sequencing on an Illumina sequencer. The resulting sequence data was demultiplexed and analyzed with the CellRanger pipeline to generate raw fastq files and processed gene-count matrices for each sample. Altogether, our study generated transcriptomic profiles from 421,312 individual cells after quality control and filtering.Our analyses reveal 60 cell subsets and functional alterations in cell states, compositions, and interactions that highlight previously unknown features of EoE. Active disease displayed enrichment of ALOX15+ macrophages, novel PRDM16+ dendritic cells expressing the EoE risk gene ATP10A, and cycling mast cells, with concomitant reduction of TH17 cells. Receptor–ligand expression uncovered eosinophil recruitment programs, increased fibroblast interactions in disease, and IL-9+IL-4+IL-13+TH2 and endothelial cells as potential mast cell interactors. Resolution of inflammation-associated signatures included mast and CD4+ Tissue-resident memory T (TRM) cell contraction and cell type-specific downregulation of eosinophil chemoattractant, growth, and survival factors.

Study phs003574

Genomic Basis of Phenotypic Variability of Complex Disorders

The 520-kbp deletion on chromosome 16p12.1 is associated with multiple neurodevelopmental outcomes, including intellectual disability/developmental delay (ID/DD), schizophrenia, autism, and epilepsy. This variant is inherited in >95% of cases from carrier parents manifesting neuropsychiatric features, while affected children with the deletion were more likely to carry another large Copy Number Variation (CNV) or rare deleterious mutation elsewhere in the genome, or "second-hits", compared to carrier parents. Thus, while the 16p12.1 deletion confers significant risk for a range of disorders, the ultimate phenotypic trajectory is determined by "second-hit" variants in the genetic background. However, outstanding questions remain about the genetic background in these disorders, including the functional effects of "second-hit" variants towards gene expression or developmental phenotypes, the full spectrum of "second-hit" variants, and the mechanisms driving accumulation of these variants.In version 1, we performed deep clinical phenotyping, whole-genome sequencing (WGS), SNP microarray analysis, and RNA-sequencing of lymphoblastoid cell lines of 32 individuals in five large families with the 16p12.1 deletion. We found that specific classes of rare single-nucleotide and structural variants in coding and non-coding regions contributed towards expression changes in affected children based on their inheritance patterns, including a subset of variants that acted synergistically with the deletion to alter expression. We further found that rare variant-mediated expression changes contribute to specific developmental phenotypes in the carrier children, suggesting a potential genetic mechanism for variable expressivity of the deletion.In version 2, we additionally analyzed genetic and phenotypic data from individuals with 16p12.1 deletion and their spouses to assess the role of assortative mating modulating phenotypic outcomes of the 16p12.1 deletion. We identified significant within- and cross- disorder phenotypic correlations between spouses, but observed no significant genetic correlations between spouses, in line with expectations.

Study phs002450

A prospective study identifies MisMatch Repair genes as candidate predisposing genes for uveal melanoma.

Objective: The aim of this study is to identify new predisposing genes for uveal melanoma (UM), the most common intraocular malignancy in adults. Design: Prospective cohort study from Institut Curie. Participants: 381 unselected patients diagnosed with UM between July 2021 and February 2023 at Institut Curie. Methods: All patients received genetic counseling and consented to extended genetic testing. A panel of 122 genes was analyzed by targeted sequencing on germline DNA from these patients. Main outcomes measures: UM was diagnosed by ophthalmologists at Institut Curie, and a senior pathologist confirmed the diagnosis when tumor or biopsy was available. Classification of the germline genetic variants was performed according to the ACMG guidelines. Results: We identified at least one pathogenic variant (PV) in 79 patients. Among those variants, 20 were found in clinically relevant genes for the patient’s follow-up and genetic counseling. We found a significant enrichment of germline pathogenic variants in Mismatch Repair (MMR) MLH1, MSH2 and MSH6 genes in this UM cohort, suggesting that MMR germline alterations could predispose to UM. From this cohort, one tumor was available from a patient carrying a MLH1 germline mutation. The tumor was characterized by a monosomy 3, in line with a loss of heterozygosity (LOH) of MLH1, located on chromosome 3. Loss of expression of MLH1 and PMS2 was observed by immunohistochemistry, and MMR mutational signatures SBS6, ID1 and ID2 were identified from the whole genome sequencing of the tumor. These data suggest that MLH1 is implicated in the oncogenesis of this UM. Conclusions: This study is the largest prospective constitutional study performed on UM patients, and the first demonstrating that MMR germline alterations are significantly enriched among these patients. Further analyses will be needed to estimate the risk of developing UM for patients with Lynch syndrome

Study EGAS50000000914

Copy number profiling of primary samples and cell lines of retinoblastoma

While RB1 loss initiates retinoblastoma development, additional somatic copy number alterations (SCNAs) can drive tumor progression. Although SCNAs have been identified with good concordance between studies at a cytoband resolution, accurate identification of single genes for all recurrent SCNAs is still challenging. This study presents a comprehensive meta-analysis of genome-wide SCNAs integrated with gene expression profiling data, narrowing down the list of plausible retinoblastoma driver genes. We performed SCNA profiling of 45 primary retinoblastoma samples and 8 retinoblastoma cell lines by high-resolution microarrays. We combined our data with genomic, clinical and histopathological data of ten published genome-wide SCNA studies, which strongly enhanced the power of our analyses (N=310). Comprehensive recurrence analysis of SCNAs in all studies integrated with gene expression data allowed us to reduce candidate gene lists for 1q, 2p, 6p, 7q and 13q to a limited gene set. Besides the well-established driver genes RB1 (13q-loss) and MYCN (2p-gain) we identified CRB1 and NEK7 (1q-gain), SOX4 (6p-gain) and NUP205 (7q-gain) as novel retinoblastoma driver candidates. Depending on the sample subset and algorithms used, alternative candidates were identified including MIR181 (1q-gain) and DEK (6p gain). Remarkably, our study showed that copy number gains rarely exceeded change of one copy, even in pure tumor samples with 100% homozygosity at the RB1 locus (N=34), which is indicative for intra-tumor heterogeneity. In addition, profound between-tumor variability was observed that was associated with age at diagnosis and differentiation grades. Since focal alterations at commonly altered chromosome regions were rare except for 2p24.3 (MYCN), further functional validation of the oncogenic potential of the described candidate genes is now required. For further investigations, our study provides a refined and revised set of candidate retinoblastoma driver genes.

Study EGAS00001001715

In this study, blood-brain barrier (BBB)-forming brain endothelial-like cells were generated from apolipoprotein E gene allele E4 (APOE4, high AD risk) and allele E3 (APOE3, lower AD risk) carrying patient-derived induced pluripotent stem cells (iPSCs). Cells were subsequently exposed to focused ultrasound and microbubbles (FUS+MB) to induce BBB opening and their transcriptome analysed. RNA sequencing (RNA-seq) results demonstrated minimal changes in the gene expression following FUS+MB suggesting safety of FUS+MB application in the clinical setting.

The blood-brain barrier (BBB) is a major impediment to therapeutic intracranial drug delivery for the treatment of neurodegenerative diseases, including Alzheimer’s disease (AD). Focused ultrasound applied together with microbubbles (FUS+MB) is a novel technique to transiently open the BBB and increase drug delivery. Evidence suggests that FUS+MB is safe, however the effects of FUS+MB on human BBB cells, especially in relation to AD, remain sparsely investigated. Here we developed a human sporadic AD BBB cell platform to investigate the effects of FUS+MB on BBB cells and screen for the delivery of two potentially therapeutic AD antibodies. We generated BBB cells from apolipoprotein E gene allele E4 (APOE4, high AD risk) and allele E3 (APOE3, lower AD risk) carrying patient-derived induced pluripotent stem cells (iPSCs). We utilized this robust and reproducible platform to demonstrate increased delivery of potentially therapeutic antibodies across the BBB, including an analogue of Aducanumab (AduhelmTM) following FUS+MB treatment. Our results also demonstrate the safety of FUS+MB indicated by minimal changes in the cell transcriptome as well as little or no changes in cell viability and inflammatory responses within first 24 h post FUS+MB, with potentially important implications in a clinical setting. Finally, we report a more physiologically relevant hydrogel-based 2.5D BBB model as a key development for FUS+MB-mediated drug delivery screening, with potentially higher translational utility. Our results provide an important advancement for identifying FUS+MB-deliverable drugs and screening for cell- and patient-specific effects of FUS+MB, accelerating its use as a therapy in AD.

Study EGAS00001005944

Local In Time Statistics for processual research

Background: Functional genomics in a processual analysis cover the time-dependent changes in transcriptomics and epigenetics before diagnosis of a disease, reflecting the changes in both life style and disease processes. The aim of this paper is to explore the dynamic, time-dependent mechanisms of the metastatic processes, using blood transcriptomics and including time in a continuous manner. For achieving this goal we develop new statistical methods based on statistics that are local in time. Methods: The new statistical method, Local In Time Statistics (LITS), is based on calculating statistics in moving windows and randomization. The method has been tested for the analysis of a dataset that collectively provides information on the blood transcriptome up to eight years before breast cancer diagnosis. The dataset from the NOWAC Post-genome Cohort consists of 467 case-control pairs matched on birth year and time of blood sampling. The data for a pair is the difference in log2 gene expression between the case and control. The stratified analyses are based on important biological differences like metastatic versus non-metastatic cancer, and the mode of cancer detection, i.e. screening detected versus clinically detected cancers. The dataset was used for examining whether the gene expression profile varies between cases and controls, with time, or between cases with and without metastases. Results: The null hypotheses of no differences between cases and controls, no time-dependent changes, and no differences between different strata were all rejected. For screening detected cancers the probability of correct prediction of metastasis status was best in year 1 before diagnosis compared to year 3 and 4 before diagnosis for clinically detected cancers. The predictor was not very sensitive to the number of genes included.Conclusions: Using a new statistical method, LITS, we have demonstrated time-dependent changes of the blood transcriptome up to eight years before breast cancer diagnosis.

Study EGAS00001002520

Genetic_Heterogeneity_of_the_familial_gastric_neuroendocrine_tumors

Gastric neuroendocrine tumors (gNETs) occur with an estimated frequency of 2 per 100,000 in the general population. Type I gastric neuroendocrine tumors (NETs) represent the 75% of gNTEs and arise from gastric enterochromaffin-like (ECL) cells. They have late age of onset and usually benigh course. Classically, hypergastrinemia in patients who have autoimmune atrophic gastritis, causes hyperplasia of gastric ECL cells that progresses into type I gastric NETs and parietal cell (PC) destruction. The genetic bases in families with this disease are unknown. We performed an exome sequencing study of an atypical aggressive familial gNETs case (with early age onset, nodal infiltrations and gastric adenocarcinomas) that followed a recessive model. We identified a deleterious mutation in homozygosis in the ATP4A gene, which encodes the proton pump responsible for acid secretion by gastric parietal cells. This mutation lead to achlorhydria first, and hypergastrinemia and gNET developing as consequence (Calvete et al. 2014). Recently, two more families with gNETs, classical clinical traits and recessive model have been studies by WES but we didn't find any mutation in the ATP4a gene. However, putative mutations affecting genes that contribute to the development and the integrity of PC have been found suggesting that genetic alterations associated to this disorder target to a unique cell type (parietal cells). In order to cinfirm this hypothesis, it is necessary the search for new genes implicated in the gNETs, more familial cases are needed to be studied. We have identified four more new familial gNETs cases. Here, we propose their study by WES. The first family is formed by thress siblings with gNETs. The other families include two siblings with gNETs. 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 EGAS00001002273

Exome Sequencing to Define the Landscape of Plasma Cells in Systemic Light chain Amyloidosis

Systemic light chain amyloidosis (AL) is characterized by the deposition of immunoglobulin light chains as amyloid fibrils in different organs, where they form toxic protein aggregates. The underlying disease is a plasma cell disorder, but limited whole exome data are available. We report the findings of an exome sequencing study in AL to define a plasma cell signature and compare this to monoclonal gammopathy of undefined significance (MGUS) and myeloma (MM). Twenty-four samples from unselected newly diagnosed untreated AL patients were analysed. CD138+ cells were isolated from bone marrow cells using MACSorting (Miltenyi Biotech, Bisley, UK). Cells were lysed in RLT+ buffer and DNA/RNA extracted using the AllPrep kit (Qiagen, Manchester, UK). Peripheral blood was isolated from patients, white blood cells purified by Ficoll-Pacque and DNA extracted using the QIAamp DNA mini kit (Qiagen). There were a median of 47 acquired nonsynonymous variants (range 4-253) per patient. Thirty percent of patients yielded a mutation in a myeloma driver gene. These mutations were either clonal or sub-clonal. There was evidence of MAPK activation with NRAS mutations, NF-κB activation and DNA repair pathway alterations. Exome data were used to determine the cytogenetic groups of AL samples and identified hyperdiploidy in 33% of cases and t(11;14) in 33% of cases. All translocations were generated via class switch recombination and breakpoints on chromosome 11 fell into the expected regions. A novel translocation, unlikely to be driving disease progression was identified involving RCC1. Finally, further analysis of the APCS gene encoding for the SAP protein did not show any biased genotype in the AL population in comparison to the general population. We conclude that exome sequencing identifies a genetic make-up of AL that is similar to other plasma cell disorders such as MM and MGUS. This not only includes copy number abnormalities and translocations but also nonsynonymous mutations.

Study EGAS00001001418

Liver biopsy derived induced pluripotent stem cells provide an unlimited supply for the generation of patient-specific hepatocyte-like cells

Background: Hepatocyte-like cells (HLCs) differentiated from induced pluripotent stem cells (iPSCs) have emerged as a promising cell culture model to study metabolism, biotransformation, viral infections and genetic liver diseases. However the derivation of iPSCs is restricted by ethical and procedural constraints. Furthermore, incomplete HLC differentiation remains a major challenge. iPSC may carry-on a tissue of origin dependent expression memory influencing iPSC differentiation into different cell types. If liver derived iPSCs (Li-iPSCs) maintain a liver specific gene expression profile is not known. It is also not known, if Li-iPSCs would allow the generation of more fully differentiated HLCs.Methods: Primary liver cells (PLCs) were expanded from liver needle biopsies and reprogrammed into Li-iPSCs using a non-integrative Sendai virus-based system. Li-iPSCs were differentiated into HLCs using established differentiation protocols. The HLC phenotype was characterized at the protein, functional and transcriptional level. RNA sequencing data were generated from the originating liver biopsies, the Li-iPSCs, fibroblast derived iPSCs, and differentiated HLCs, and used to characterize and compare their transcriptome profiles.Results: PLCs were obtained from small pieces of liver biopsies and could be reprogrammed into Li-iPSCs. Li-iPSCs indeed retain a liver specific transcriptional footprint. Li-iPSCs can be propagated to provide an unlimited supply of cells for differentiation into Li-HLCs. Similar to HLCs derived from fibroblasts, Li-HLCs could not be fully differentiated into hepatocytes. Relative to the originating liver, Li-HLCs showed lower expression of liver specific transcription factors and increased expression of genes involved in the differentiation of other tissues.Conclusions: PLCs and Li-iPSCs obtained from small pieces of human needle liver biopsies constitute a novel unlimited source for the production of HLCs. Despite the preservation of a liver specific gene expression footprint in Li-iPSCs, the generation of fully differentiated hepatocytes cannot be achieved with the current differentiation protocols.

Study EGAS00001002676

High-throughput telomere length measurement at nucleotide resolution using the PacBio high fidelity sequencing platform

Telomeres are specialized nucleoprotein structures at the ends of linear chromosomes that are essential for the stability as well as the complete replication of the human genome. The progressive shortening of steady-state telomere length in normal human somatic cells is a promising biomarker for age-associated diseases. However, there remain substantial challenges in quantifying telomere length in clinics and research laboratories due to the lack of accurate and high-throughput telomere length measurement method. Here, we describe a novel workflow to capture and analyze telomeres accurately at the single-nucleotide resolution. By using newly designed telobaits that are complementary to the single-stranded G-rich 3’ telomeric overhangs, we can specifically and efficiently capture full-length telomeres and subject them to single-molecule real-time (SMRT) sequencing. We show that the telomere length can be measured at nucleotide resolution using the PacBio high fidelity (HiFi) sequencing platform, which provides the necessary accuracy and throughput to uncover the steady-state telomere length distribution in human culture cell lines as well as clinical patient samples. This new method is a valuable tool not only in population-wide epidemiology studies but also for the longitudinal assessment of telomere attrition in individuals. Our results also reveal the extreme heterogeneity of telomeric variant sequences (TVSs) that is dispersed throughout the telomere repeat region. Importantly, the unique distribution pattern and sequence of TVSs in individuals may be used as a fingerprint for sample identification. In addition, the presence of TVSs disrupts the continuity of the canonical (5’-TTAGGG-3’)n telomere repeats, which could affect the binding of shelterin complexes at the chromosomal ends. Therefore, TVSs may act as a form of genetic polymorphisms that impairs telomere protection. Together with the absolute telomere length in each individual, TVSs may have profound implications in human aging and diseases.

Study EGAS00001006103

High-throughput telomere length measurement at nucleotide resolution using the PacBio high fidelity sequencing platform, P49-P104 and run1 replicates

Telomeres are specialized nucleoprotein structures at the ends of linear chromosomes that are essential for the stability as well as the complete replication of the human genome. The progressive shortening of steady-state telomere length in normal human somatic cells is a promising biomarker for age-associated diseases. However, there remain substantial challenges in quantifying telomere length in clinics and research laboratories due to the lack of accurate and high-throughput telomere length measurement method. Here, we describe a novel workflow to capture and analyze telomeres accurately at the single-nucleotide resolution. By using newly designed telobaits that are complementary to the single-stranded G-rich 3’ telomeric overhangs, we can specifically and efficiently capture full-length telomeres and subject them to single-molecule real-time (SMRT) sequencing. We show that the telomere length can be measured at nucleotide resolution using the PacBio high fidelity (HiFi) sequencing platform, which provides the necessary accuracy and throughput to uncover the steady-state telomere length distribution in human culture cell lines as well as clinical patient samples. This new method is a valuable tool not only in population-wide epidemiology studies but also for the longitudinal assessment of telomere attrition in individuals. Our results also reveal the extreme heterogeneity of telomeric variant sequences (TVSs) that is dispersed throughout the telomere repeat region. Importantly, the unique distribution pattern and sequence of TVSs in individuals may be used as a fingerprint for sample identification. In addition, the presence of TVSs disrupts the continuity of the canonical (5’-TTAGGG-3’)n telomere repeats, which could affect the binding of shelterin complexes at the chromosomal ends. Therefore, TVSs may act as a form of genetic polymorphisms that impairs telomere protection. Together with the absolute telomere length in each individual, TVSs may have profound implications in human aging and diseases.

Study EGAS00001006595

Everything you need to know about Federated EGA Affiliates: Q&A

Addressing common questions about Federated EGA (FEGA) Affiliates and providing answers. FEGA Affiliates have recently been defined as the third tier within the newly approved “Federated EGA Structure and Organisation” document, alongside Central EGA (CEGA) and the FEGA Nodes. In this blog post, we aim to answer the questions that may arise on this topic. For more general information about FEGA Affiliates, you can refer to this blog post. Let's now start with the questions and answers! What is the difference between a FEGA Affiliate and a FEGA Node? FEGA Nodes A FEGA Node is a national-level service that accepts submissions and provides archiving and access services within a single country's jurisdiction. Nodes provide end-to-end services for submitters in that jurisdiction, including submission support, processing, permissions management, and distribution. FEGA Affiliates A FEGA Affiliate is not a national submission service. Instead, it archives data from its own legal entity and/or selected partner institutions (for example, consortium partners). Affiliates are designed for organisations and consortia that need to keep data stewardship and access decisions within their own governance model, while still enabling discovery through the broader FEGA ecosystem. What do Affiliates commit to? Here is a practical checklist of the core expectations for a FEGA Affiliate. FEGA Affiliate checklist Discovery and metadata Submit non-personal metadata to CEGA to obtain EGA accessions and enable discovery (with metadata validation handled by the CEGA Helpdesk). Operations and resilience Maintain a data storage system and a defined backup/recovery approach. Ensure operational capacity (personnel and infrastructure) to deliver Affiliate services. Maintain systems and practices that support local data security and align with EGA best-practices. Access and user support Provide data distribution or access (e.g in a trusted research environment) to authorised users to datasets hosted at the Affiliate. Provide permissions management for datasets archived by the Affiliate (the CEGA DAC (Data Access Committee) Portal is always at your disposal to use). Provide a minimal helpdesk with sufficient capacity to support relevant DACs and approved users. Membership term Commit to a minimum membership term of four years. Governance and participation (lightweight by design) Affiliates integrate into the FEGA network operationally, but without the committee obligations associated with Nodes. When is becoming an Affiliate the right fit? Consider the Affiliate tier if: You host (or plan to host) controlled-access datasets that must be managed under your organisation’s or consortium’s governance, you want studies to be discoverable through EGA, but need access control and/or distribution to remain local, and you are not aiming to operate a national submission service tier.. What if a FEGA Node already exists in my jurisdiction? We encourage any potential Affiliate to reach out to their national FEGA Node to explore collaboration at the national level. Why? Federated models within a country already exist in FEGA, where a national Node operates like a Central EGA for their country. FEGA Nodes can also represent the interests of any Affiliates within their jurisdiction at the FEGA Committees. FEGA Nodes have experience and can support you on your FEGA journey. Ready to join as a FEGA Affiliate? We’re excited to open this formally defined pathway for organisations and consortia to participate in the federation. If you think the FEGA Affiliate tier fits your needs, start by assessing: Your scope (organisation/consortium-held data rather than public external submissions), Your ability to provide the core services (permissions, distribution/access, helpdesk, monitoring), and Your readiness to submit non-personal metadata to CEGA for accessioning and discovery. To express interest, please contact us here, and we'll help you understand the onboarding steps and how Affiliates integrate into the FEGA network.

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