Search Results - EGA European Genome-Phenome Archive

Longitudinal RNA-seq datasets from patients after abdominal surgery

This dataset consists of RNA-seq data of 126 whole-blood samples derived from patients after abdominal surgery. Total-RNA collected preoperatively and at 3-time points postoperatively (2-6, 24 and 48hrs) were analysed using RNA-sequencing. RNA was collected in PAXGene (Qiagen) tubes and extracted using the PAXGene RNA extraction kit, with a DNase step to remove contaminating DNA. Globin and ribosomal RNA were removed via a Ribo-zero kit (Illumina) and library preparation was carried out using the TruSeq Stranded Total RNA Library Prep Kit (Illumina). Next generation sequencing was performed on the NovaSeq sequencing platform (Illumina) at the Wellcome Centre for Human Genetics (WCHG) in Oxford.

Dataset EGAD00001011102

Pathogenic Neurofibromatosis type 1 (NF1) RNA splicing resolved by targeted RNAseq

Neurofibromatosis type 1 (NF1) is caused by loss-of-function variants in the NF1 gene. Approximately 10% of these variants affect RNA splicing and are either missed by conventional DNA diagnostics or are misinterpreted by in silico splicing predictions. Therefore, a targeted RNAseq-based approach was designed to detect pathogenic RNA splicing and associated pathogenic DNA variants. an in-house developed tool (QURNAS) was used to calculate the enrichment score (ERS) for each splicing event. RNA enrichment of NF1 and SPRED1 was done using SPET (NUGEN - NF1 only) and using SureSelect (Agilent - NF1 and SPRED1).

Dataset EGAD00001007978

Genomic Evolution of Breast Cancer Metastasis and Relapse

Recurrent breast cancer is almost universally fatal. We characterize 170 patients locally relapsed or distant metastatic cancers using massively parallel sequencing. We identify that the relapse-seeding clone disseminates late from the primary tumor. TP53 and AKT1 appear to be enriched in ER-positive cancers predisposed to relapse. Mutation acquisition continues at relapse as the same mutation signatures continue to operate and new signatures, such as that caused by radiotherapy appear de novo. In 49% of cases we identify drivers mutations private to the relapse and these are sampled from a wider range of cancer genes, including SWI-SNF complex and JAK-STAT signaling.

Dataset EGAD00001002698

The G2 gene expression signature and MYC overexpression are independent poor prognostic factors in childhood high-grade osteosarcoma

Key objective Are the prognostic transcriptomic G1/G2 gene expression signature, MYC overexpression, and MYC amplification replicable stratifying biomarkers for future clinical trials in high-grade osteosarcoma? Knowledge gathered In an unselected cohort, the G2 gene expression signature and MYC overexpression, but not MYC amplification, were independently associated with poor event-free and overall survival. Relevance Transcriptomic biomarkers may serve as stratifying factors that guide the management of patients with high-grade osteosarcoma. Current data underlines the importance of prospective validation of the G1/G2 signature and MYC overexpression in an international, multicenter, study.

Dataset EGAD00001015503

Chromatin accessibility (ATAC-seq) and transcriptome (RNA-seq) data from immune cells for healthy young and healthy old subjects

Dataset consisting of: (1) N=234 genome-wide chromatin accessibility (ATAC-seq) profiles for distinct N=21 healthy old and N=28 healthy young subjects. ATAC-seq biological samples provided for the following tissues: PBMC (N=24), CD14+ monocytes (N=18), CD8+ memory T cells (N=7), CD8+ naive T cells (N=7), CD4+ memory T cells (N=7), CD4+ naive T cells (N=7), and naive B cells (N=7). (2) N=39 genome-wide transcription (RNA-seq) data for distinct N=15 healthy old and N=24 healthy young subjects' PBMCs.

Dataset EGAD00001003602

Investigating low frequency variants in CAD/MI cases, controls and pedigrees using whole exome sequencing and custom pulldowns

The Cardiogenics re-sequencing study will consist of three parts: Eight pools of 25 individuals will be sequenced using a Nimblegen hybrid-capture solution specific to miRNA sequences, 80 pools of 25 individuals will be sequenced using a custom Agilent SureSelect array covering genes associated with coronary artery disease (CAD) and myocardial infarction (MI), 10 individuals from families with a history of CAD/MI will be exome sequenced using the Sanger exome array. The experiment will use the early onset patients from the German MI cohort and the UK BHF CAD/MI cohort both of which have strong family history. For controls we will consider individuals from the UKBS and KORA cohorts.

Dataset EGAD00001000400

STAT3 ChIPseq of PC-9 and KHM-3S with and without tarceva

Dataset EGAD00001000844

MT alignment

Alignement including 83 MT AA sequences and 2 reference sequences, rCRS and RSRS

Dataset EGAD00010001574

PDX WES for #039 and #049

Exome sequencing of PDX and matched patient blood

Dataset EGAD50000000034

Distinct Phenotypes of Human Intrahepatic and Extrahepatic Bile duct Organoids and their Applications for Biliary Disease Modeling

Study EGAS00001003792

Deep MRD profiling defines outcome and unveils different modes of treatment resistance in standard and high risk myeloma

Study EGAS00001004558

ATAC-seq/ChIP part

Epigenetics: ATAC-seq and ChIP-seq data

Study EGAS00001006520

The Primary Open-Angle Glaucoma Genes and Environment (GLAUGEN) Study

Background Information: Primary open-angle glaucoma (POAG) is an age-related, intraocular pressure (IOP)-dependent progressive optic neuropathy that ultimately leads to irreversible blindness. Vision loss from POAG is a condition of public health significance. Current evidence suggests that POAG is a polygenetic disease modified by environmental influences. Despite the fact that a positive family history of disease is an important risk factor for POAG, conventional linkage and candidate gene approaches have revealed less than 5% of the genetic component of the disease. Furthermore, there is no consensus on environment risk factors for POAG. Elevated IOP is the only modifiable risk factor for POAG; yet, lowering IOP slows, but does not halt the disease process. Study Objectives: The overall goal of our research is to elucidate the pathogenesis of POAG so that cost-effective disease detection and primary prevention strategies can be implemented. The primary aim of the Glaucoma Gene Environment Initiative (GLAUGEN), funded by the Human Genome Research Institute (NHGRI), is to discover genetic loci associated with POAG. The secondary aim of GLAUGEN, funded by NHGRI and the National Eye Institute, is to discover gene environment interactions in POAG. Methods and study populations: For this study, we have assembled cases and controls from three studies: the Nurses' Health Study (NHS), the Health Professionals Follow-up Study (HPFS) and the Genetic Etiologies of POAG (GEP) project based at Massachusetts Eye and Ear Infirmary (MEEI). This case-control group includes 1057 unrelated cases and 1272 controls. Members of the NHS and HPFS also have repeated environmental exposure data collected prior to a diagnosis of POAG. NHS - The Nurses Health Study started in 1976 under the direction of Dr. Frank E. Speizer. With funding from the NIH, registered nurses from 11 US states were invited to complete a detailed questionnaire regarding lifestyle and health biennially. Initially, 121,000 women responded to the baseline questionnaire. Currently, Dr. Susan Hankinson serves as the program director for the NHS. HPFS - The Health Professionals Follow-up Study began in 1986 under the direction of Drs. Walter Willett and Meir Stampfer. Under the auspices of the NIH, they enlisted 51,529 male health professionals from throughout the US to complete similarly designed biennial questionnaires. Beginning in 1990, questions regarding ocular health were added to biennial questionaires completed by health professionals participating in the NHS and HPFS. This allowed us to formulate (PI: S. Hankinson; NEI) and maintain (PI: L. Pasquale; NEI) a cohort at risk for POAG derived from the respective general cohorts who were under ophthalmic care. We then developed a definition of POAG that allowed us to identify cases from a population that was geographically dispersed. The centerpiece of this definition is the presence of reproducible visual field loss consistent with nerve fiber layer (NFL) dropout (the NFL contains the axons that comprise the optic nerve) on reliable tests. Reproducible visual field loss occurred in the context of anterior segment findings that did not suggest a secondary cause of elevated IOP and posterior segment findings that did not suggest a secondary cause of visual field loss. We selected controls from the cohort at risk for POAG on the basis of age, gender and time period when cases were identified. GEP - The Genetic Etiologies of POAG was initiated in 1996 with funding from the National Eye Institute under the direction of Dr. Janey Wiggs. The purpose of this work was to discover novel genetic loci associated with POAG. In the GEP, cases were derived predominantly from the Glaucoma Service at MEEI. The majority of cases had an examination by a glaucoma specialist and met the definition for POAG used in NHS and HPFS. Cases with only one reliable visual field consistent with NFL dropout were included if there was a cup-disc ratio of 0.7 or more. The majority of controls were patients who presented to the MEEI comprehensive ophthalmology service for routine eye examination or from spouses of MEEI patients with secondary forms of glaucoma. Other controls were identified from regional glaucoma screenings held throughout Massachusetts. Members of GEP have detailed ocular phenotype data but limited information on environmental exposures. 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 primary open-angle glaucoma through large-scale genome-wide association studies of three well-characterized cohorts of cases and controls, some in matched pairs. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center. Data cleaning and harmonization were performed at the GEI-funded GENEVA Coordinating Center at the University of Washington.

Study phs000308

NextGen Consortium: The iPSCORE (iPSC Collection for Omic Research) Resource for Studying the Impact of Genetic Variation on Molecular and Physiological Phenotypes - Whole Genome Sequence

The iPSC Collection for Omic Research (iPSCORE) Resource was created as part of the Next-Gen Consortium funded by NHLBI. The overarching purpose of the resource is to provide a large collection of human induced pluripotent stem cells (iPSCs) for use in studying the impact of genetic variation on molecular and physiological phenotypes. The resource has been used in a number of studies in the Dr. Kelly A. Frazer's Lab examining both the characteristics of human iPSCs and a variety of iPSC-derived cell types including cardiovascular progenitor cells (iPSC-CVPCs), pancreatic precursor cells (iPSC-PPCs), and retina pigment epithelium cells (iPSC-RPEs). We have shown that the iPSCs, CVPCs, and PPCs are suitable surrogate models to identify genetic factors active in early developmental processes because they exhibit fetal-like molecular properties.A total of 273 individuals have participated in the study, of which 222 have had iPSCs generated from fibroblasts. Of the 273 individuals, 181 are part of 55 families that include 24 monozygotic twin pairs and 5 dizygotic twin pairs, allowing for the incorporation of familial relationships into genetic analyses.Germline DNA has been sequenced from blood or fibroblast samples for all 273 individuals (available through dbGaP phs001325) and other genomic data (RNA-seq, DNA methylation, genotype arrays, ATAC-seq, H3K27ac ChIP-seq, HiC-seq) have been generated from the 222 iPSCs as well as derived cell types (available through dbGaP phs000924).QTL analyses were conducted for multiple omics data types and summary statistics are available through dbGaP phs0001325.Important note: Of the 273 individuals, 268 are consented for general research use and 5 are consented for cardiac research only.For detailed information about iPSCORE Collection including samples, methods used to generate the data, and how to access the datasets visit the Frazer lab website.The 222 well characterized iPSC lines that constitute the iPSCORE resource are available, please contact Dr. Kelly A. Frazer (kafrazer@health.ucsd.edu) if you are interested in obtaining the collection.

Study phs001325

Acute Respiratory Distress Syndrome Clinical Network: Fluid and Catheter Treatment Trial (ARDSNet FACTT-BioLINCC)

Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-FACTT include plasma, DNA, and serum. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives: This study evaluated the benefits and risks of Pulmonary Artery Catheters (PACs) in patients with established acute lung injury in a trial comparing hemodynamic management guided by a PAC with hemodynamic management guided by a central venous catheter (CVC) using an explicit management protocol.Background: Optimal fluid management in patients with acute lung injury is unknown. Diuresis or fluid restriction may improve lung function but could jeopardize extrapulmonary organ perfusion.Participants: This randomized study compared a conservative and a liberal strategy of fluid management using explicit protocols applied for seven days in 1000 patients with acute lung injury. The primary end point was death at 60 days. Secondary end points included the number of ventilator-free days and organ-failure-free days and measures of lung physiology. Design: Participants were randomly assigned to a strategy involving either conservative or liberal use of fluids with concealed allocation in permuted blocks of eight with the use of an automated system. Participants were simultaneously and randomly assigned to receive either a pulmonary-artery catheter or a central venous catheter in a two-by-two factorial design.Conclusions: There was no significant difference in the primary outcome of 60-day mortality; however, the conservative strategy of fluid management was associated with improved lung function and shortened the duration of mechanical ventilation and intensive care without increasing non-pulmonary organ failures. These results support the use of a conservative strategy of fluid management in patients with acute lung injury. (NEJM June 15, 2006; Vol 354, No. 24, pp 2564-75; NEJM May 25, 2006; Vol 354, No. 21, pp 2213-24)

Study phs004165

Upcycling and merging data to challenge the dogma and identify new therapeutic targets for Glioblastoma

Glioblastoma is the most common brain tumour. Characterised by a poor prognosis and its recurrence after multimodal treatments, the search for preventable risk factors has been mainly inconclusive up to date. Recently, the data merge from datasetsdeposited at the EGA allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. Challenges in glioblastoma research As for virtually all cancer types, many efforts have been made to unveil the molecular features responsible of the disease, and several cellular pathways have indeed been identified as being frequently mutated in glioblastoma. Nonetheless, targeted therapies based on identified genes have so far failed to improve outcome, thus survival mostly relies on a standard treatment unchanged since 2005. This is a frustrating situation for both the scientific and medical communities, and above all for the patients, still facing a dreadful path. Some researchers hypothesised that this may be due to the inability to efficiently target cancer stem cells, the originators of the other cell types, thus inducing cancer relapse. In 2019 Charles P. Couturier and colleagues sequenced RNA from single cells of freshly excised glioblastomas of 16 patients, and demonstrated that glioblastoma cells replicate normal brain cell development with a conserved neural cancer cell hierarchy centered around glial progenitor-like cells. In this way, they helped identify the possible target cells to improve efficacy and durability of treatment. Data upcycling at the EGA: the glioblastoma case study Single cell RNA sequencing is generated with a laborious and expensive protocol. The quality of the starting material is crucial (cells sample freshly extracted from the patients) and often several attempts are needed before producing reliable quality sequencing results. Collecting big numbers of patients is also challenging. The sequencing data produced by Kevin Petrecca’s group in Montreal, Canada and deposited at the EGA (EGAS00001004422) was recently upcycled by Lin Wang in San Francisco, California and pooled with their freshly produced ones, and then deposited at the EGA as Dataset EGAS00001004909 The data merge allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. They profiled 86 primary-recurrent patient-matched paired glioblastoma samples with single-nucleus RNA, among other techniques. These very comprehensive results lead the team to challenge the findings from several other cancer fields where chemotherapy standard chemo-radiation therapy selection pressure at the level of genomic alterations; this is indeed not the case for glioblastoma, where the pressure results in phenotypic transition between cellular states. Several technical controls were made to ensure that the merge of the data was not introducing a bias in the results, and an Inter-table analysis demonstrated nearly equal contribution to overall variance from each of the studies included, indicating that the findings were not due to inter-laboratory technical effect. A novel principal-component analysis showed that the largest contribution to variation in primary glioblastoma neoplastic cells was an axis between MES (mesenchymal) and proneural expression programs. In summary, treating glioblastoma often makes a MES, as commented by Lucy Stead about this remarkable work. Check Aaron Diaz’s team Nature Cancer paper, with strong technical tools, state of the art analysis and data from different sources converging to the same outcomes that made possible a significant step toward a better handling of a frightful cancer. References Couturier, C.P., Ayyadhury, S., Le, P.U. et al. Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy. Nat Commun 11, 3406 (2020). Stead, L.F. Treating glioblastoma often makes a MES. Nat Cancer 3, 1446–1448 (2022). Wang, L., Jung, J., Babikir, H. et al. A single-cell atlas of glioblastoma evolution under therapy reveals cell-intrinsic and cell-extrinsic therapeutic targets. Nat Cancer 3, 1534–1552 (2022). Related links: Kevin Petrecca’s group dataset deposited at the EGA: EGAS00001004422 Lin Wang dataset deposited at the EGA: EGAS00001004909

Blog upcycling-and-merging-data-to-challenge-glioblastoma

Raw sequencing files from WGS and RNA-Seq

Acute leukemias are the most common malignancies in children with an onset of the disease among 0-6 years-old. The early development of theses malignancies has been proposed as an indicator of their prenatal origin, hypothesis that has been confirmed especially in the case of acute lymphoblastic leukemia. For acute myeloid leukemia (AML), comprising an heterogenous group of different cytogenetics subtypes, this prenatal origin has also been confirmed specially for MLL-rearranged and t(8;21) subgroups. AMLs carrying t(7;12) constitute up to 30% of cases under 2-years-old, frequently being associated with a trisomy of chromosome 19 and an overexpression of MNX1 gene. An in utero origin of this specific subgroup has been suggested but not clearly confirmed. Here, we present the case of a 5-months-old AML patient with t(7;12) in which we have fully characterized a novel breakpoint occurring among ETV6 and NOM1 genes. We demonstrate the presence of this specific ETV6-NOM1 fusion in CD34+ hematopoietic stem and progenitor cells isolated from the cord blood unit from the same patient and stored at birth. Moreover, trisomy +19 present at diagnosis was not detected at birth. Together, our results demonstrate the prenatal origin of the t(7;12) in infant AML, and establish trisomy +19 as a secondary event in this leukemia.

Study EGAS50000000186

National Heart, Lung, and Blood Institute (NHLBI) Bench to Bassinet Program: The Pediatric Cardiac Genetics Consortium (PCGC) Study

Multi-center, prospective observational cohort study of individuals with congenital heart defects (CHD). Phenotypic data and source DNA derived from 10,000 probands, parents, and families of interest are being collected to investigate relationships between genetic factors and phenotypic and clinical outcomes in patients with CHD. Phenotype data will be stored at dbGaP, while molecular and sequence data will be stored at BioData Catalyst. The PCGC Cohort is utilized in the following dbGaP substudies. Please click on the following substudies below or in the "Substudies" section of this top-level study page phs001194 PCGC Cohort. phs000571 PCGC: whole exome sequences, whole genome sequences, targeted sequences, MIP sequences, and SNP array data phs001843 PCGC-CMG Collaboration: whole genome sequences The Gabriella Miller Kids First Pediatric Research Program (Kids First) subset of the PCGC project (phs001194) is now accessible through a separate dbGaP study accession: phs001138. To access this dataset, please submit a Data Access Request (DAR) for phs001138. Approval of this DAR will be expedited for approved users of phs001194. To learn about other Kids First datasets visit https://kidsfirstdrc.org/.NHLBI's TOPMed program has provided additional Whole Genome Sequencing for PCGC participants - that data is accessible through a separate dbGaP sudy accession: phs001735. Access to this data set should be requested through a Data Access Request (DAR) for phs001735.

Study phs001194

MRCA and MRCE SNP genotypes

Gene expression levels can be an important link DNA between variation and phenotypic manifestations. Our previous map of global gene expression based on approximately 400K SNPs and 50K transcripts in 400 sib pairs from the MRCA family panel has been widely used to interpret the results of GWAS. Here, we more than double the size of our initial dataset with expression data on 550 additional individuals from the MRCE family panel using the Illumina whole genome expression array. We have used new statistical methods for dimension reduction to account for non-genetic effects in estimates of expression levels and we have also included SNPs imputed from the 1000 Genomes Project. Our methods reduced false discovery rates and increased the number of eQTLs mapped either locally or at a distance (i.e. in cis or trans) from 1,534 in the MRCA dataset to 4,452 (with <5% FDR). Imputation of 1000 Genomes SNPs further increased the number of eQTLs to 7,302. Using the same methods and imputed SNPs in the newly acquired MRCE dataset we identified eQTLs for 9000 genes. The combined results identify strong local and distant effects for transcripts from 14,177 genes. Our eQTL database (http://www.hsph.harvard.edu/faculty/liming-liang/software/eqtl/) based on these results is freely available to help define the function of disease-associated variants.

Study EGAS00000000137

The Federated EGA network

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

Blog the-federated-ega-network

Genomic insights into the pathogenesis of Epstein-Barr virus-associated diffuse large B-cell lymphoma by whole-genome and targeted amplicon-based sequencing

Epstein–Barr virus (EBV)-associated diffuse large B-cell lymphoma not otherwise specified (DLBCL NOS) constitutes a distinct clinicopathological entity in the current World Health Organization (WHO) classification, yet its genomic features remain sparsely characterized. Combining whole-genome sequencing (WGS), targeted amplicon sequencing (tNGS) and fluorescence in-situ hybridization (FISH) of tumours from 47 cases of EBV+ DLBCL we delineate the genomic landscape of this rare disease. Interrogating WGS data by sequential gene-set enrichment and network-diffusion we describe an accumulation of mutations affecting the nuclear factor κB (NFκB) pathway (CSNK2A2, CARD10), IL-6/JAK/STAT (SOCS1/3, STAT3) and WNT signalling (FRAT1, SFRP5) alongside aberrations in immunological processes like interferon-response. Further, WGS uncovered structural aberrations including 6q deletions (5/8 patients), which were subsequently validated by FISH (14/32 cases). Integrated WGS and tNGS analysis emphasized a profile distinct from EBV-negative DLBCL enriched for mutations in ARID1A (45%), KMT2A/D (32/30%), ANKRD11 (32%), NOTCH2 (32%). Expanding on previous reports, we identified recurrent alterations in CCR6 (15%), DAPK1 (15%), TNFRSF21 (13%), CCR7 (11%) and YY1 (6%). Our comprehensive description of the mutational landscape in EBV+ DLBCL substantiates the evidence of its pathobiological independence. Further, these observations aid in the refinement of the molecular taxonomy for aggressive lymphomas and guides future therapeutic strategies.

Study EGAS00001004941

cfDNA dataset from extracelular vesicles and paired non-fractionated samples

Liquid biopsies contain multiple analytes that can be mined to improve the detection and management of cancer. Beyond cell-free DNA (cfDNA), mutations have been detected in DNA associated with extracellular vesicles (EV-DNA). The genome-wide composition and structure of EV-DNA remains poorly characterized, and whether circulating EVs are enriched in tumor signal compared to unfractionated cfDNA is still unclear. Here, using whole genome sequencing from selected lung cancer patients with a relatively high cfDNA tumor content >5%, we determined that the tumor fraction and heterogeneity are comparable between DNA associated with small (<200 nm) EVs and matched plasma cfDNA. DNA in EV fractions, obtained with standardized size-exclusion chromatography, are comprised of short ~150-180 bp fragments and long >1000 bp fragments that are poor in tumor signal. Other fractions only exhibit short fragments with similar tumor DNA content. The composition in bases at the end of EV-DNA fragments, as well as their fragmentation patterns are similar to total plasma cfDNA. Mitochondrial DNA however is relatively enriched in EV fractions. Our results suggests that cfDNA in plasma may be of dual nature, either bound to proteins (including the nucleosome) but also associated to EVs. cfDNA associated to small EV (including exosomes) is however not preferentially enriched in tumor signal.

Study EGAS00001006848

What is metadata?

What is metadata? Data represents units of information and metadata can be seen, simply put, as data about other data. For example, in a simple experiment in which a patient genome was sequenced, there are multiple and diverse fields of metadata: from the biological sex of the patient to the sequencing platform used. Another way to understand metadata, following our genomic experiment example, is going through the different layers of (meta)data: One of the basic units of information (data) would be the sequence of nucleotides (e.g. GCTGG and GCCGG). This DNA sequence can be contextualised within a chromosome by providing its locus (e.g. β-globin gene). This data, the locus, is about other data, the sequence of nucleotides, which would render it metadata. We can go one step further, and provide more context, by giving the associated phenotype of each of these sequences: GCTGG corresponds to a healthy individual, while GCCGG corresponds to a person with β-thalassaemia. Once again, this data is contextualising the data we have provided up to this point, which makes it metadata. With this simple example, what we are doing is adding layers of data that describe the ones below. Had we given the sequences alone, little would be possible from the researchers' point of view. But, now that the data has its accompanying metadata, a researcher could compare both sequences and their phenotypes to infer a possible cause of the disorder. Each layer of information broadens the possible applications of the data. Now that we know what metadata is, it is time to emphasise the importance of submitting good quality metadata. The quality of the metadata will determine whether the data is usable, discoverable, and interpretable by researchers and clinicians. One example that highlights the importance of good quality metadata is the description of biological sex of a patient: while the terms "female," "girl," or "woman" all represent the same concept, they are not harmonised. These different representations of a concept can create confusion and errors in data analysis. By applying standard definitions and terminologies to biological sex metadata, we can avoid misunderstandings and facilitate the integration of different datasets. In order to comply with the FAIR principles and, more specifically, to allow for the (meta)data to be interoperable (i.e. used universally and unambiguously), we need to place some standards onto the (meta)data EGA archives. These can be as simple as asserting that the given patient's biological sex is one of the correct terms (e.g. female or male); or as complex as multiple layers and combinations of validation steps with existing records. You can find further details on how EGA manages these standards on our metadata model page.

Documentation submission/metadata/what-is-metadata

A Multiethnic Genome-wide Scan of Prostate Cancer

Multiple GWA studies of prostate cancer conducted in European White populations are ongoing. These studies will continue to have a dramatic impact on our understanding of the contribution of common genetic variation on inter-individual susceptibility to this common cancer. Important questions that will remain unanswered, however, are whether all common risk alleles for prostate cancer will be revealed in studies limited to populations of European ancestry. A comprehensive examination of common genetic variation in men of Japanese, Latino, and African ancestry will be required to understand population differences in disease risk and to reveal the full spectrum of causal alleles that exist in these populations. Further, genetic and environmental diversity is likely to contribute to ethnic heterogeneity of genetic effects. Elucidating gene x gene and gene x environment interactions is also likely to provide knowledge that may be critical for understanding the contribution of genetic susceptibility to racial/ethnic disparities in prostate cancer incidence and for translating the findings from GWA studies into interventions. In this study we plan to undertake a genome-wide association study (GWAS) of prostate cancer in the Multiethnic Cohort (MEC) Study. We propose the following hypotheses: (a) that inherited DNA variation influences risk of prostate cancer; (b) that many of the causal alleles will be outside known "candidate genes" requiring an agnostic, comprehensive search; and (c) that performing this search in a multi-ethnic cohort is more powerful than a study limited to a single population to reveal the full range of causal alleles relevant to the U.S. population. The version 1 release of this dataset will include genotype data for the Japanese and Latino populations in the study. The version 2 release will include data for the African ancestry population along with the Japanese and Latino subjects. The version 3 release will include fully-cleaned genotype data for all three populations. 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 prostate cancer through large-scale genome-wide association studies of a well-characterized multi-ethnic cohort. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center and at the University of Southern California. Data cleaning and harmonization were performed at the GEI-funded GENEVA Coordinating Center at the University of Washington. As an add-on to this GWAS we performed a targeted re-sequencing of all known prostate cancer risk loci in the samples from the MEC. Sequencing was performed in Dr. Reich's lab at Harvard Medical School.

Study phs000306

Heart Failure Network Aldosterone Targeted Neurohormonal Combined with Natriuresis Therapy - (HFN ATHENA-BioLINCC)

ObjectiveTo assess whether high-dose spironolactone treatment for patients with acute heart failure lowers natriuretic peptide levels and improves outcomes better than usual care.BackgroundAcute heart failure (AHF) accounts for more than a million hospitalizations in the United States annually. The role of low-dose mineralocorticoid receptors antagonists (MRAs) therapy as a neurohormonal antagonist is well established for the treatment of chronic heart failure and reduced ejection fraction. However, the role of high-dose MRA therapy in AHF remained uncertain. A previous clinical trial suggested that the benefits of high-dose MRA therapy in AHF included lower natriuretic peptide levels, less congestion, better renal function, and less need for an intravenous diuretic. The use of intravenous loop diuretics can intensify secondary hyperaldosteronism among AHF patients, and hyperaldosteronism directly contributes to diuretic resistance in AHF. Elevated aldosterone levels in AHF are associated with an increased risk of cardiovascular mortality and HF readmission. Hospitalizations for heart failure are associated with increased risk of mortality and/or readmission.The HFN-ATHENA trial was conducted to determine if mineralocorticoid receptor antagonists administered at high doses relieved congestion, decreased diuretic resistance, and mitigated the effects of adverse neurohormonal activation in AHF.SubjectsThe ATHENA trial enrolled 360 participants. Of these, 178 participants were randomized to usual care treatment (placebo or low-dose spironolactone) and 182 participants were randomized to high-dose spironolactone.DesignThe study intervention was initiated within 24 hours of patients receiving the first dose of intravenous diuretics. Participants not taking spironolactone at enrollment were randomized to 100 mg spironolactone or a placebo. Participants taking low-dose spironolactone before their hospital admission were randomized to 100 mg or 25 mg per day in the usual care treatment arm. Prescription of all other medications, including diuretics, was left at the discretion of the treating physician. The study drug was discontinued after 96 hours and further MRA use was left to the treating physician's discretion. The primary end point was the proportional change in the log NT-proBNP levels from randomization to 96 hours (or at the hospital discharge if the discharge occurred earlier than 96 hours). Secondary endpoints included: (1) a clinical congestion score; (2) dyspnea relief; (3) daily cumulative net urine output for up to 96 hours; (4) net weight change from baseline to 96 hours or discharge (whichever came first); (5) furosemide equivalents of the loop diuretic dosage at discharge; and (6) the development of in-hospital worsening HF, with signs and symptoms requiring additional therapy.ConclusionsThere was no significant difference in the primary or secondary endpoints between the high-dose treatment arm and the usual care treatment arm.

Study phs003506

16488 results for "sec+and+unspecified+malignant+neoplasm"

in 29.55 milliseconds.