Search Results - EGA European Genome-Phenome Archive

The Familial Intracranial Aneurysm Linkage Study (FIA)

Our long-term objective is to identify susceptibility genes that are related to the formation of intracranial aneurysms (IA). Rupture of IAs occurs in 16,000 to 17,000 persons in the U.S. annually and nearly half of affected persons are dead within the first 30 days. An additional 6,000 to 7,000 persons with unruptured IAs are identified each year. Accumulated evidence indicates that a genetic component plays an important role in the development of IAs, but specific loci affecting the risk of IA have not been identified. The primary hypothesis of this study is that there are specific human chromosomal regions that are associated with an increased risk of IAs. Specific Aims of are: Recruitment of 400 (475) families with multiple individuals who have an IA through 23 (25) referral centers throughout North America, Australia, and New Zealand that represent 35 (40) recruitment sites. Ascertainment of interviews and blood samples from all affected family members as well as their first-degree relatives. White blood cells from living persons with an IA will be cryopreserved at Coriell Institute for Medical Research for future immortalization of cells lines as indicated. Identification of unruptured IAs by obtaining MRAs in selected asymptomatic siblings (of affected individuals). Completion of a 10 cM genome series in persons with IAs as well as the spouses and children of persons with an IA who are deceased. We will perform finer mapping of chromosomal regions with suggestive evidence of linkage in the genome screen. Performance of a nonparametric (allele sharing) linkage analysis, including relevant environmental factors such as smoking, to identify chromosomal regions linked to IA. Reconstruction of the genotypes of deceased affected family members will be performed. Identification of individuals who are genetically at high risk for the development of IAs would enable targeted and effective screening/prevention/treatment strategies to reduce the substantial mortality and morbidity associated with this devastating type of stroke. Only a multidisciplinary, collaborative effort to identify, accrue, and genotype FIA families will be successful in identifying sufficient high-risk families to characterize the genetic underpinnings of IA.

Study phs000293

Exome Sequencing of Statin-Induced Myopathy Cases

Severe myopathic events occur in 0.1-0.5% of patients taking statins. Although genetic association studies have identified some possibly associated gene loci, these have not been reproducible in additional studies with independent patient cohorts. A more reasonable explanation for susceptibility to statin-induced myopathy is the presence of rare pathogenic variants in genes important for skeletal muscle structure and function. In support of this, we have previously reported an increased incidence of pathogenic variants in genes causing metabolic myopathies in patients with statin-induced myopathy (Vladutiu et al.,2006). We also reported a patient with statin myopathy who had an RYR1 variant known to be causative of malignant hyperthermia susceptibility (MHS) (Vladutiu et al., 2011). There are a number of genes associated with metabolic myopathies triggered by various factors such as extreme exercise, fasting, extremes in temperature, viral infection and exposure to volatile anesthetics. In addition, many of the genes causing congenital myopathies, myofibrillar myopathies and muscular dystrophies have overlapping phenotypes with these genes. We propose that statins act as an additional trigger inducing myopathic symptoms and many patients with severe statin-induced myopathy have causative genetic variants within similar genes associated with MHS and congenital myopathy. We have analyzed the resultant data using a disease model in which rare pathogenic variants, possibly within multiple genes, are causative of statin-induced myopathy. In this study, we have identified potentially causative genetic variants in greater than 50% of the statin-induced myopathy cases and in particular, rare and possibly pathogenic in the RYR1 and CACNA1S genes were present in 25% of the patient samples studied. Vladutiu, G. D., Simmons, Z., Isackson, P.J., Tarnopolsky, M., Peltier, W.L., Barboi, A.C., Sripathi, N., Wortmann, R.L., Phillips, P.S., (2006). "Genetic risk factors associated with lipid-lowering drug-induced myopathies." Muscle Nerve 34: 153-162. Vladutiu, G. D., Isackson, P.J., Kaufman, K., Harley, J.B., Cobb, B., Christopher-Stine, L., Wortmann, R.L, (2011). "Genetic risk for malignant hyperthermia in non-anesthesia-induced myopathies." Mol Genet Metab 104: 167-173.

Study phs001342

Center Common Disease Genomics [CCDG] - CVD - TAICHI

The TaiChi consortium consists of 6 studies that collaborated initially in a large scale metabochip study, and became an ongoing consortium for studies of cardiometabolic disease in the Chinese population in Taiwan. The six studies included the following: 1) SAPPHIRe (Stanford-Asian Pacific Program in Hypertension and Insulin Resistance), a family based study established in 1995 with an initial goal of identifying major genetic loci underlying hypertension and insulin resistance in East Asian populations, with Taiwan subjects participating in the TaiChi consortium; 2) TCAGEN (Taiwan Coronary Artery Disease GENetic), a cohort study that the enrolled patients undergoing coronary angiography or percutaneous intervention at the National Taiwan University Hospital (NTUH) in the setting of either stable angina pectoris or prior myocardial infarction; 3) TACT (TAiwan Coronary and Transcatheter intervention), a cohort study enrolled patients with angina pectoris and objective documentation of myocardial ischemia who underwent diagnostic coronary angiography and/or revascularization any time after October 2000 at the National Taiwan University Hospital (NTUH) (similar to TCAGEN but recruitment was independent of TCAGEN); 4) Taiwan DRAGON (Taiwan Diabetes and RelAted Genetic COmplicatioN), a cohort study of Type 2 diabetes at Taichung Veterans General Hospital (Taichung VGH) in Taiwan, with participants including individuals with either newly diagnosed or established diabetes (subjects with hyperglycemia who did not meet diagnostic criteria for Type 2 DM were not included); 5) TCAD (Taichung CAD study), includes patients with a variety of cardiovascular diseases who received care at the Taichung Veterans General Hospital (Taichung VGH), i.e. specifically individuals who were hospitalized for diagnostic and interventional coronary angiography examinations and treatment; 6) TUDR (Taiwan US Diabetic Retinopathy) enrolled subjects with Type 2 diabetes who received care at Taichung Veteran General Hospital (Taichung VGH), and a small number of subjects from Taipei Tri-Service General Hospital (TSGH); TUDR subjects underwent a complete ophthalmic and fundus examination to carefully document the presence and extent of retinopathy. From these 6 studies, subjects were selected based on completeness of standard metabolic phenotyping and knowledge of cardiac disease status (early onset coronary disease), to undergo whole genome sequencing at the Broad.

Study phs001487

Investigation of Brain Nitrogen Metabolism in Partial Ornithine Transcarbamylase Deficiency (OTCD) Using 1H MRS, DTI, and fMRI

This is a case controlled, observational study. This project studies cognitive and motor dysfunction in adult and pediatric patients who are female carriers of ornithine transcarbamylase deficiency (OTCD) or are males with late onset presentation (outside of the newborn period) of OTCD, utilizing state of the art MRI (magnetic resonance imaging), a non-invasive technique. This project seeks to improve our understanding of the underlying neural mechanisms that contribute to metabolic, cognitive, sensory and motor abnormalities in urea cycle disorders, which although individually rare, collectively constitute a major cause of neonatal encephalopathy, leading to significant morbidity and mortality. As a result of this study, a greater understanding of the anatomic, cognitive, motor, and biochemical underpinnings of neurologic damage attributable to this metabolic disorder will be gained. Experimental approaches will combine sensory, cognitive and motor testing with structural, functional and molecular magnetic resonance imaging to study symptomatic and asymptomatic heterozygous female carriers of X-linked ornithine transcarbamylase deficiency (OTCD), and late onset hemizygous males. Participants to be included in the studies ranged from ages 7-60 years and were compared to an age-matched typically developed (TD) comparison group. For our research, we use anatomic MRI, functional Magnetic Resonance Imaging (fMRI), and magnetic resonance spectroscopy (MRS) to monitor brain activity. The technique of fMRI provides detailed maps of the brain areas underlying human mental activities. By using fMRI, we are able to observe how the brain is functioning while a person is performing a specific task, such as reading. We can not only observe differences in the structure of the brain, but can also measure differences in brain function and activity as well. This information will ultimately be used to provide a basis for designing more effective interventions and methods for early identification of learning disabilities in patients with OTCD and related disorders. We will also use MRS to study various brain chemicals such as glutamine using the non-invasive MRI imaging techniques.

Study phs001296

National Institutes of Health The Cancer Genome Atlas (TCGA)

The Cancer Genome Atlas (TCGA) is a comprehensive and coordinated effort to accelerate our understanding of the molecular basis of cancer through the application of genome analysis technologies, including large-scale genome sequencing. TCGA is a joint effort of the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI), which are both part of the National Institutes of Health, U.S. Department of Health and Human Services. TCGA projects are organized by cancer type or subtype. Click here for a current list of cancer types selected for study in TCGA. Data from TCGA (e.g., gene expression, copy number variation and clinical information), are available via the Genomic Data Commons (GDC). Data from TCGA projects are organized into two tiers: Open Access and Controlled Access. Open Access data tier contains data that cannot be attributed to an individual research participant. The Open Access data tier does not require user certification. Data in Open Access tier are available in the TCGA Data Portal. Controlled Access data tier contains individual-level genotype data that are unique to an individual. Access to data in the Controlled Access data tier requires user certification through dbGaP Authorized Access. Controlled Access data types consist of the following: Individual germline variant data (SNP .cel files) Primary sequence data (.bam files), which are available at GDC Clinical free text fields Exon Array files (for Glioblastoma and Ovarian projects only) NOTE: TCGA strives to release most data in the open access tier. Individual genotype or sequence files are prominent exceptions. Commonly requested files such as descriptions of somatic mutations or clinical data are open access. Please go to this page: https://tcga-data.nci.nih.gov/docs/publications/ to access all data associated with TCGA tumor specific publications. The TCGA study is utilized in the following dbGaP substudies. To view genotypes and other molecular data collected in these substudies, please click on the following substudies below or in the "Substudies" section of this top-level study page phs000178 TCGA study. phs000854 Genome-wide Analysis of Noncoding Regulatory Mutations in Cancer

Study phs000178

Integrating Genomic and Transcriptomic Data to Identify Breast Cancer Susceptibility Genes

Genetic factors play an important role in the etiology of both sporadic and familial breast cancer. Since 2007, common genetic variants in ~200 loci have been identified in genome-wide association studies (GWAS) in relation to breast cancer risk. However, it is often difficult to translate GWAS findings to disease prevention and treatment since causal genes in the large majority of GWAS-identified loci are unknown. Furthermore, a large fraction of breast cancer heritability remains unexplained. Recent studies suggest that nearly 80% of disease heritability can be explained by genetic variants regulating gene expression. Herein, we propose three well-powered transcriptome-wide association studies (TWAS) to systematically investigate the association of breast cancer risk with gene expression across the transcriptome of African, Asian and European descendants. In Aim 1, we will perform RNA sequencing and high-density genotyping assays using normal breast tissue samples, and build race-specific gene expression prediction models using data from 1000 women of African, Asian and European descent. These models will be applied to the GWAS data generated from approximately 320,000 breast cancer patients and controls to impute gene expression for association analyses of predicted gene expression with risk of breast cancer overall, and by estrogen receptor and HER2 status. In Aim 2, we will select the top 50 genes identified in Aim 1 for in vitro functional assays to assess their influence on major cell functions related to cancer biology. In Aim 3, we will evaluate whether TWAS-identified genes may express differently in normal breast tissues and breast cancer tissues collected from African, Asian, and European descendants to assess whether these genes may contribute to racial differences in breast cancer risk by molecular subtypes. With strong methodology and a large sample size, we believe that this proposed study should be able to identify and characterize a large number of novel genes related to breast cancer risk. Uncovering breast cancer susceptibility genes will greatly improve the understanding of the genetic and biological basis for breast cancer and accelerate the translation of genetic findings to disease prevention and patient care.

Study phs003535

Contextual and Health Behavior Effects on Epigenetic Aging Among Africans in the Family and Community Health Studies

The Family and Community Health Studies (FACHS) is a longitudinal examination of health and health related behaviors in African American families. The original study cohort consisted of 867 African American parent-child dyads from Georgia and Iowa who were ascertained in cooperation with local school districts. The key inclusion criteria for participating in the study were the presence of an adolescent in the 5th grade (approximately 10-11 years old) who self-identified as African American (i.e., the Target) and the participation of a primary caretaker (PC) for the Target. The clinical and biological data included in this collection are from the Target (i.e., FACHS-T) portion of these studies of these African American parent-child dyads. The initial wave of behavioral assessments of the FACHS-T subjects was conducted in 1997-98 (Wave 1), with seven subsequent ascertainments, Wave 2 (1999–2000), Wave 3 (2002–2003), Wave 4 (2005–2006), Wave 5 (2007–2009), Wave 6 (2010–2011), Wave 7 (2014–2016) and Wave 8 (2019-2021). Full interviews were obtained at each wave of the study with the exact content of the wave varying as a function of developmental age. These interviews of the FACHS-T subjects collected a wide variety of data including the following: perceived discrimination; socioeconomic status; substance use exposure; common internalizing and externalizing disorders such as depression, substance use, and conduct disorder; school efficacy; peer support and perceived parenting practices. Biological sampling of the FACHS-T subjects was conducted at three time points. Saliva DNA was collected at Wave 5 while full phlebotomy was conducted at Waves 7 and 8. The genome wide methylation data listed below is derived from the whole blood DNA samples collected at Wave 8 and Wave 9. The genome wide genotyping data was determined using DNA from the Wave 7 samples. The clinical and biological data available herein are those from 309 FACHS-T subjects who participated in both Wave 7 and Wave 8, and who consented for deposition of their data in dbGAP.

Study phs003723

NHLBI TOPMed: Lung Tissue Research Consortium (LTRC)

Chronic obstructive pulmonary disease (COPD), a disease state characterized by airflow limitation that is not fully reversible, is the third leading cause of death in the U.S. COPD is a heterogeneous syndrome, with affected individuals demonstrating marked differences in lung structure (emphysema vs. airway disease); physiology (airflow obstruction); and other clinical features (e.g., exacerbations, co-morbid illnesses). Multiple genomic regions influencing COPD susceptibility have been identified by genome-wide association studies (GWAS), and rare coding variants can also influence risk for COPD. However, only a small percentage of the estimated heritability for COPD risk can be explained by known genetic loci. Like most complex diseases, COPD is influenced by multiple genetic determinants (each with modest individual effects). Emerging evidence supports the paradigm that complex disease genetic determinants are part of a network of interacting genes and proteins; perturbations of this network can increase disease risk. To identify this network, multiple Omics data will need to be analyzed with methods to account for nonlinear relationships and interactions between key genes and proteins. Our overall hypothesis is that integrated network analysis of genetic, transcriptomic, proteomic, and epigenetic data from biospecimens ranging from lung tissue to nasal epithelial cells to blood in highly phenotyped subjects will provide insights into COPD pathogenesis and heterogeneity. We will leverage the well-phenotyped, NHLBI-funded Lung Tissue Research Consortium (LTRC) to address these questions. We will perform multi-omics analysis in 1548 lung tissue and blood samples from the LTRC. With these multi-omics data, we will utilize a systems biology approach to understand relationships between multiple genetic determinants and multiple types of Omics data. We will begin by performing single Omics analyses in COPD vs. control lung, nasal, and blood samples. Next, we will integrate single Omics data with genetic variants identified by WGS to assist in fine mapping genetic determinants of COPD. We will then perform integrated network analysis of COPD with genetic and multiple Omics data using correlation-based, gene regulatory, and Bayesian networks. Subjects were recruited from Mayo Clinic, Universities of Colorado, Michigan, and Pittsburgh, and Temple University.

Study phs001662

METSIM (METabolic Syndrome In Men) Study

The METSIM Study includes 10,197 men, aged from 45 to 73 years, randomly selected from the population register of the town of Kuopio, Eastern Finland, and examined in 2005-2010. The aim of the study is to investigate genetic and non-genetic factors associated with the risk of type 2 diabetes (T2D), cardiovascular disease (CVD), and insulin resistance-related traits in a cross-sectional and longitudinal setting. Study protocol includes collection of data on CVD risk factors (smoking, exercise, diet, history of chronic diseases including coronary heart disease, stroke, cardiac failure, medication, history of diabetes or early onset coronary heart disease in the family), questionnaire on the FINDRISC Score, measurement of height, weight, waist, hip, blood pressure, and bioimpedance for the evaluation of fat percentage. July 2016 - The first study release (v1) included phenotype and whole exome sequencing (WES) data of n=982 participants in substudy: Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Project 1: Metabolic Syndrome in Men Study (METSIM) - phs001100.v2.p1. The second study release (v2) included phenotype data for the entire METSIM cohort and made two additional substudies available, phs000919.v1.p1 and phs000752.v1.p1. The third study release (v3) made three subcutaneous adipose biopsy substudies available, phs003385.v1.p1, phs003386.v1.p1, and phs003387.v1.p1.The fourth study release (v4) added phenotype data for the subcutaneous adipose biopsies, made two additional substudies available, phs01579.v1.p1 and phs004033.v1.p1, and 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" section of this top-level study page phs000743 METSIM Study. phs000752 METSIM FinMetSeq Exome Sequencing phs000919 METSIM GWAS and Exome Chip phs001100 METSIM T2D-GENES Exome Sequencingphs001579 METSIM CCDG Whole Genome Sequencingphs003385 METSIM Subcutaneous Adipose Needle Biopsy RNA-Seq phs003386 METSIM Subcutaneous Adipose Needle Biopsy ATAC-Seq phs003387 METSIM Subcutaneous Adipose Surgical Biopsy RNA-Seqphs004033 METSIM Metabolomics

Study phs000743

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

Scottish High Grade Serous Ovarian Cancer

Scottish HGSOC samples were collected via local Bioresource facilities at Edinburgh, Glasgow, Dundee and Aberdeen and stored in liquid Nitrogen until required. HGSOC patients were determined from pathology records and were included in the study where there was matched tumour and whole blood samples. On receipt of tumour material the tumour was processed as follows: firstly, the tumour sample was divided into two for DNA and RNA extraction. Slivers of tissue were cut from the front and rear faces of the DNA sample, then fixed in formalin and embedded in paraffin wax. Sections from the front and rear tissues from all samples were examined by H&E staining supplemented by WT1/p53 immunohistochemistry if required. Following pathology review, samples were only included if they met the following criteria: they were confirmed as HGSOC and there was greater than 40% tumour cellularity throughout the tumour, determined using the H&E sections. Somatic DNA was extracted using the Qiagen DNeasy Blood and tissue kit (cat no 69504). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including RNase digestion step). Germline DNA was extracted from 1-3ml whole blood using the Qiagen FlexiGene kit (cat no 51206) following the manufacturers recommended protocol. The resulting DNA underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as surrogate measures of DNA purity. A260/280 had to be 1.8 or greater and A260/230 had to be 2.0 or greater. Then, DNA was quantified using LifeTechnologies Qubit dsDNA BR kit (cat no Q32850) and we required a minimum of 50ul at 25ng/ul for WGS. Thirdly, DNA was diluted to 25ng/ul and a representative sample was loaded onto a 0.8% TAE gel, ran at 100v for 60mins and then imaged using a BioRad ChemiDoc imaging system to visualise the DNA quality. Only when all 4 quality control requirements were satisfied was the DNA sequenced. The DNA was sequenced at the Glasgow Precision Oncology Laboratories.

Study EGAS00001004410

Evolution and clinical impact of genetic epistasis within EGFR-mutant lung cancers

The current understanding of tumorigenesis is largely centered on a monogenic driver oncogene model. This paradigm is incompatible with the prevailing clinical experience in most solid malignancies: monotherapy with a drug directed against an individual oncogenic driver typically results in incomplete clinical responses and eventual tumor progression1-7. By profiling the somatic genetic alterations present in over 2,000 cases of lung cancer, the leading cause of cancer mortality worldwide, we show that combinations of functional genetic alterations, i.e. genetic collectives dominate the landscape of advanced-stage disease. We highlight this polygenic landscape and evolution of advanced-stage non-small cell lung cancer (NSCLC) through the spatial-temporal genomic profiling of 7 distinct tumor biopsy specimens and 6 plasma specimens obtained from an EGFR-mutant NSCLC patient at (1) initial diagnosis of early-stage disease, (2) metastatic progression, (3) sequential treatment and resistance to 2 EGFR inhibitors, (4) death. The comprehensive genomic analysis of this case, coupled with circulating free (cf) tumor DNA profiling of additional advanced-stage EGFR-mutant NSCLC clinical cohorts with associated treatment responses uncovered features of evolutionary selection for multiple concurrent gene alterations: including the presence of EGFR inhibitor-sensitive (EGFRL858R;EGFRexon19del) or inhibitor-resistant (EGFRT790M;EGFRC797S) forms of oncogenic EGFR along with cell cycle gene alterations (e.g. in CDK4/6, CCNE1, RB1) and activating alterations in WNT/β-catenin and PI3K pathway genes, which our data suggest can cooperatively impart non-redundant functions to limit EGFR targeted therapy response and/or promote tumor progression. Moreover, evidence of an unanticipated parallel evolution of both EGFR T790M and two distinct forms of oncogenic PIK3CA was observed. Our study provides a large-scale clinical and genetic dataset of advanced-stage EGFR-mutant NSCLC, a rationale for specific polytherapy strategies such as EGFR and CDK4/6 inhibitor co-treatment to potentially enhance clinical outcomes, and prompts a re-evaluation of the prevailing paradigm of monogenic-based molecular stratification for targeted therapy. Instead, our findings highlight an alternative model of genetic collectives that operate through epistasis to drive lung cancer progression and therapy resistance.

Study EGAS00001002604

Identifying transcriptional programs underlying anti-EGFR small molecule response and resistance with TraCe-seq

Genetic and non-genetic heterogeneity within cancer cell populations represents a major challenge to anti-cancer therapies. We currently lack robust methods to determine how pre-existing and adaptive features affect cellular responses to therapies. Here, by conducting clonal fitness mapping and transcriptional characterization using expressed barcodes and single-cell RNA-sequencing, we have developed TraCe-seq, a method that captures at clonal resolution the origin, fate, and differential early adaptive transcriptional programs of cells in a complex population in response to distinct treatments. We used TraCe-seq to benchmark how next-generation dual EGFR inhibitors-degraders compare to standard EGFR kinase inhibitors in EGFR-mutant lung cancer cells. To QC the TraCe-seq strategy, single-cell RNA-seq libraries were generated from a variety of human cancer cell lines transduced with the TraCe-seq library to validate the TraCe-seq strategy. Specifically, 5 different cell lines (PC9, MCF-10A, MDA-MB-231, NCI-H358, and NCI-H1373) were each transduced with a unique TraCe-seq barcode. The transduced cells were selected with puromycin only, dissociated to single cell suspensions, and then mixed together. The complex mixture of the 5 cell lines was profiled by 10X scRNA-seq. Furthermore, transduced NCI-H1373 cells were sorted by FACS to enrich for the top 50% of eGFP positive cells, and sorted cells were cultured briefly and used to construct scRNA-seq libraries and profiled by 10x scRNA-seq. To carry out the full TraCe-seq experiment, ~600 PC9 cells carrying unique TraCe-seq barcodes were expanded over 12 doublings to establish the barcoded population. A subset of the barcoded PC9 population was used to generate scRNA-seq libraries and profiled by 10x scRNA-seq prior to treatment to establish a baseline transcription profile for each barcoded clone. The rest of the cells were then treated for four days with 1 µM erlotinib, 1 µM GNE-069, or 1 µM GNE-104 respectively. scRNA-seq libraries were then generated form the treated cells and profiled by 10x scRNA-seq.

Study EGAS00001005405

Chromatin profiles classify castration-resistant prostate cancers suggesting therapeutic targets

Untreated prostate cancers rely on androgen receptor (AR) signaling for growth and survival, forming the basis for the initial efficacy of androgen deprivation therapy (ADT). Yet, the disease can relapse and progress to a lethal stage termed castration-resistant prostate cancer (CRPC). Reactivation of AR signaling represents the most common driver of CRPC growth and next generation AR signaling inhibitors (ARSIs) are now used in combination with ADT as a first line therapy. However, ARSIs can result in selective pressure generating AR-independent tumors. The transition from AR-dependence frequently accompanies a change in phenotype resembling developmental trans-differentiation or ‘lineage plasticity’. Neuroendocrine prostate cancer, which lacks a defined pathologic classification, is the most studied type of lineage plasticity. However, most AR-null tumors do not exhibit neuroendocrine features and are classified as ‘double-negative prostate cancer’, the drivers of which are poorly defined. Lineage plasticity studies in CRPC are limited by the lack of genetically defined patient-derived models that recapitulate the disease spectrum. To address this, we developed a biobank of organoids generated from patient biopsies to study the landscape of metastatic CRPC and allow for functional validation assays. Proteins called transcription factors (TFs) are drivers of tumor lineage plasticity. To identify the key TFs that drive the growth of AR-independent tumors, we integrated epigenetic and transcriptomic data generated from CRPC models. By presenting a map of the chromatin accessibility and transcriptomic landscape of CRPC using a diverse biobank of organoids, PDXs and cell lines that recapitulate the heterogeneity of metastatic prostate cancer, we validate CRPC-AR and CRPC-NE subtypes and reveal two subtypes of AR-negative/low samples as well as their respective masterTFs. Additional analysis revealed a model in which YAP, TAZ, TEAD and AP-1 function together and drive oncogenic growth in CRPC-SCL samples. Overall, we show here how an approach to stratify CRPC patients into four subtypes using their transcriptomic signatures can potentially inform upon appropriate clinical decisions.

Study EGAS00001006059

Heart Failure Network: Functional Impact of GLP-1 for Heart Failure Treatment (HFN FIGHT-BioLINCC)

Objectives To test whether therapy with a GLP-1 agonist improves clinical stability following hospitalization for acute heart failure. Background Heart failure was the leading cause of hospitalization in the United States with more than 4 million admissions per year from 2003–2009. Abnormal cardiac metabolism contributes to the pathophysiology of advanced heart failure with reduced left ventricular ejection fraction (LVEF). As heart failure progresses, these abnormalities become more pronounced and are observed in both patients with and without type 2 diabetes. At this time of this study, there was no heart failure therapy that targeted these metabolic abnormalities; however, in earlier clinical studies, glucagon-like peptide 1 (GLP-1) agonists showed cardioprotective effects in patients with advanced heart failure, irrespective of type 2 diabetes status. Glucagon-like peptide 1 is an endogenous incretin hormone that improves insulin sensitivity with minimal risk of hypoglycemia. This study was created to determine if use of GLP-1 agonists improved clinical stability in recently hospitalized patients with acute heart failure and reduced LVEF. Participants There were 300 participants. Design Participants were identified by hospital admission records and were enrolled during either the last 24 hours of his or her hospitalization for heart failure or the 2-week interval after the hospitalization. Baseline evaluations were conducted, which included echocardiographic measures, the 6-minute walk test, the Kansas City Cardiomyopathy Questionnaire (KCCQ), and blood tests. After the baseline evaluation, patients were randomized in a 1:1 ratio to receive either the GLP-1 agonist liraglutide or placebo as a daily subcutaneous injection. The protocol involved titration of study drug dosage as tolerated every 14 days from 0.6 mg/d to 1.2 mg/d to 1.8 mg/d during the first 30 days of the trial (as tolerated). Follow-up testing was performed at 30-, 90-, and 180-day study visits. The primary end point was a global rank score in which all participants, regardless of treatment assignment, were ranked across 3 hierarchical tiers: time to death, time to rehospitalization for heart failure, and time-averaged proportional change in N-terminal pro-B-type natriuretic peptide (NT-proBNP) level from baseline to 180 days. Conclusions The GLP-1 agonist liraglutide did not improve post-hospitalization clinical stability in patients with advanced heart failure and reduced LVEF. There was no significant between-group difference in the global rank scores and furthermore, there were no significant differences detected in any of the secondary endpoints.

Study phs003542

A Genome-wide Association Study (GWAS) of Risk for Osteosarcoma

This is a genome-wide association study (GWAS) of osteosarcoma, the most common primary bone malignancy. Osteosarcoma typically occurs in adolescents and young adults. It occurs at increased frequency in several inherited cancer predisposition syndromes but the genetic contribution to sporadic osteosarcoma is largely unexplored. The objective of this study was to identify genetic risk factors for osteosarcoma by conducting a genome-wide association study. We developed collaborations with multiple institutions in order to attain the necessary sample size required to discover novel loci in the genome associated with osteosarcoma using the GWAS approach. Genomic DNA (either blood or buccal in source) derived from osteosarcoma cases was obtained from each participating institution or research group. De-identified blood or buccal cell DNA samples from osteosarcoma cases were derived from existing biobanks at the collaborative institutions. Control subjects were derived from existing NCI cohorts and matched by gender and ethnicity.

Study phs000734

Genomic Studies for Understanding Etiology of Esophageal Adenocarcinoma (EsophagealAdenocarcinoma_Chinese)

While the incidence of esophageal adenocarcinoma (EAC) has risen drastically in Western countries over the last 40 years, a similar trend has not been observed for EAC in China. Here we analyzed mutational spectrum, copy number alterations, and structural variants from whole-genome sequencing of ten Chinese EAC tumor samples and their matched normals, and compared them to EAC tumor specimens from Western countries previously reported. The mutational burden in Chinese EAC was significantly lower than that found in EAC from Western countries. The hallmark A>C mutational signature observed at high frequency in EAC from Western countries, which linked to acid reflux, is completely absent in Chinese samples. Furthermore, none of Chinese samples showed evidence of chromothripsis and genome doubling that often found in EAC from Western countries. In summary, Chinese EAC tumor samples revealed distinct genomic profiles and signatures, suggesting that Chinese EAC may arise from a different etiological pathway.

Study phs001696

Deep Sequencing Studies for Cannabis and Stimulant Dependence

Cannabis and stimulants are among the most widely used illicit drug in the United States, and their use is associated with substantial physical and psychiatric sequelae. Twin studies have shown a substantial genetic component to the etiology of cannabis and stimulant use disorders, but, genome-wide association studies using genotype data obtained from microarrays have yielded few robust results. The advent of increasingly economical whole genome sequencing provides new opportunities to identify trait-associated sequence variations. The present study proposes to identify sequence variants that affect stimulant and cannabis dependence in three cohorts. The three study cohorts were ascertained as part of the Mission Indian Study (PI Cindy Ehlers), the combined Yale-University of Connecticut Addiction Study samples (PI Joel Gelernter) and the San Francisco Family Study (PI Kirk Wilhelmsen). Because three populations with different continental origins were studied, the present study will also ascertain whether the major genetic risk factors for the traits of interest are shared or population-specific.

Study phs001458

Rapid Acceleration of Diagnostics - Digital Health Technologies (RADx-DHT): NIH Digital Health Solutions for COVID-19: Team SAE

The goal of this project is to develop a smartphone-based platform to monitor and support individuals with COVID-19 symptoms (who may need testing) and those who have already tested positive. The app will integrate a Bluetooth-enabled thermometer and pulse oximeter into an approach uniquely designed for low-resource settings and underserved populations. This project will focus on the American Indian/Alaskan Native (AI/AN) underserved population and will determine the feasibility of the digital health solution to collect symptom survey data and vital data including temperature, pulse, and oxygen saturation level. The complete study will include 300 participants 100% medically underserved with at least 51% from the AI/AN community. A combination of hard and soft data will be collected consisting of vital data, medical history and questionnaire data, and participant COVID-19 viral and antibody testing results collected during the study.DOI: https://rapids.ll.mit.edu/10.57895/wv88-by98

Study phs002534

Integrative Analysis for Multi-Omics Data in Non-Small-Cell Lung Cancer

We conducted epigenetic and transcriptomic mapping of primary non-small cell lung tumors and non-neoplastic tissues. 20 non-neoplastic lung tissues and 18 non-small cell lung tumors were obtained from Biorepository and Tissue Technology Shared Resource at Moores Cancer Center, UC San Diego. All tumor samples were in pathological stages I and II. 8 pairs of samples were "matched", meaning that the tumor and normal tissues came from the same patient. Microfluidic oscillatory washing–based chromatin immunoprecipitation followed by sequencing (MOWChIP-seq) was used to profile the binding of H3K4me1, H3K4me3, H3K9me3, H3K27ac and H3K27me3. SmartSeq-2 was used to map mRNA expression. We identified a large number of differentially modified regions for both epigenetic and transcriptomic markers between tumors and normal tissues. Deep learning model showed extensive transcription factor network rewiring. Raw sequencing data of the ChIP-seq and RNA-seq libraries are available through this dbGaP submission.

Study phs003113

Pooled Mutant KRAS-Targeted Long Peptide Vaccine Combined with Nivolumab and Ipilimumab for Patients with Resected MMR-p Colorectal and Pancreatic Cancer

We developed INtraCEllular Reverse Transcription with Sorting and sequencing (INCERTS), an approach to combine molecular indexing of receptor repertoires within intact cells and fluorescence-activated cell sorting (FACS). We demonstrate that INCERTS enables efficient processing of millions of cells from pooled human peripheral blood mononuclear cell (PBMC) samples while retaining robust association between T cell receptor (TCR) sequences and cellular phenotypes. We used INCERTS to discover antigen-specific TCRs from patients with cancer immunized with a novel mutant KRAS peptide vaccine. After ex vivo stimulation, 28 uniquely barcoded samples were pooled prior to FACS into peptide-reactive and non-reactive CD4+ and CD8+ populations. Combining complementary patient-matched single-cell RNA sequencing (scRNA-seq) data enabled retrieval of full-length, paired TCR alpha and beta chain sequences for future validation of therapeutic utility. Data available through dbGaP include scRNA-seq with matched TCR-seq.

Study phs003425

Loss of presentation of estimated neoantigens from mutated genes in ctDNA was essential for fostering primary to recurrent tumors in postoperative colorectal cancer cases

Specific parameters regarding mutations at primary sites for the detection of postoperative recurrence using circulating tumor (ct)DNA liquid biopsy are lacking. In the current retrospective study, we conducted target resequencing of ctDNA using 47 plasma samples and established a cancer panel carrying the commonly mutated genes between primary and recurrent tumors. We found that mutated genes in ctDNA indicated immune-resistance traits with respect to the impaired ability to present neoantigens by loss of expression or binding affinity to HLA in the primary tumor. Compared with the estimated neoantigens from all mutated genes in primary tumors, the neoantigen peptides from commonly mutated genes between primary and recurrent tumors showed abundant and significant expression with no binding affinity to HLA. Therefore, ctDNA mutations can be frequently and postoperatively detected to identify recurrence; however, these mutated genes were derived from immune-tolerated clones owing to the loss of neoantigen presentation in primary CRC tumors.

Study JGAS000549

Bulk RNA sequencing of day 2 and day 7 biopsies from the tuberculin skin test in people with latent tuberculosis, and of day 2 biopsies from saline controls

We used the tuberculin skin test (TST) as human challenge model to study the temporal evolution of the immune response to Mycobacterium tuberculosis (Mtb) antigens in vivo. Study participants comprised healthy HIV seronegative adults, 18-60 years of age. Latent tuberculosis (TB) infection was defined as immune memory for Mtb-specific antigens identified by positive peripheral blood IFNg release assays, but no clinical or radiological evidence of active TB. Two units tuberculin each were injected intradermally into the contralateral forearms of participants. After 2 days (n=216) or 7 days (n=158), 3 mm skin punch biopsies were taken from the injection sites and processed for whole genome transcriptional profiling by bulk RNA sequencing. The time points reflect maximum clinical inflammation (day 2) and maximum T cell infiltration (day 7) of the TST. TST samples were compared to skin biopsies taken two days after control injection of saline in a separate group of individuals (n=33), comprising healthy volunteers as well as patients with active or latent TB, ranging from 18-75 years of age. This dataset includes 407 samples from 256 individuals (n=33 saline, n=223 with Day 2 and/or Day 7 TST). Skin biopsies were collected into RNAlater (Qiagen) for RNA extraction. Total RNA was obtained with the Precellys Evolution homogenizer (Bertin Instruments) and Qiagen RNeasy mini kit. RNA was subjected to DNase treatment to remove contaminating genomic DNA using a TURBO DNA-free kit (Ambion, Life Technologies). The KAPA mRNA HyperPrep Kit (Roche Diagnostics) was used to construct stranded mRNA-Seq libraries from up to 500 ng intact total RNA. Paired-end sequencing was performed on the Illumina Nextseq using the Nextseq 500/550 High Output 75 cycle kit (Illumina). Runs were demultiplexed using bcl2fastq by Illumina.

Dataset EGAD50000001208

Quick Guide for data submission

Quick Guide This is a quick guide to submit data to the EGA. Please select data type to display the right detailed instructions. Sequence data Array-based data Get your submission account You first need to create your EGA user. Then, once your account has been verified by the Help Desk team, request your submission account and provide details of the data type and platform(s) in your submission. Register Study/DAC Use Submitter Portal to register your study, samples, Data Access Committee (DAC) and Policy. Upload data Encrypt your data files using the and upload it to your inbox using SFTP. Register experiments and runs Associate each data file to a registered sample and study by Linking files to samples. Details of the experimental procedure you followed must be provided. Finalise your submission Group your runs/analysis into datasets and link them to your new or existing DAC and policy using DAC Portal. Data request are done at a dataset level, thus files within a datasets must share release conditions. Release and admin When finalising the submission, set a released date to instruct our Helpdesk to release your study. All registered studies are automatically placed on hold until the named submission or DAC contact instructs our Helpdesk for the study to be released. Get your submission account Fill the submission form and provide details of the data type and platform(s) in your submission. Register Study/DAC Use EGA Programmatic submission to register your study, samples, Data Access Committee (DAC) and Policy. Upload data Encrypt your data files using the EgaCryptor and upload it using default FTP clients or Aspera. Complete the Array-Format (AF) spreadsheet Download the AF spreadsheet and complete all four sections. Return the spreadsheet to the EGA helpdesk. Release and admin Instruct our Helpdesk to release your study. All registered studies are automatically placed on hold until the named submission or DAC contact instructs our Helpdesk for the study to be released.

Documentation submission/quickguide

Coverage bias and sensitivity of variant calling for four whole-genome sequencing technologies

Massively parallel sequencing has revolutionized research in cancer genetics and genomics and enhanced our understanding of natural human genetic variation. Recently, Lam et al. have performed a detailed comparison of two next-generation sequencing technologies with respect to their sensitivity to call single nucleotide variants (SNV) and indels. Here, we sequenced two tumor/normal pairs obtained from two paedriatic medulloblastoma patients with Life Technologies’ SOLiD 4 and 5500xl SOLiD, Illumina’s HiSeq2000, and Complete Genomics’ technology. We then compared their ability to call SNVs with high confidence. As gold standard for SNV calling, we used genotypes determined by an Affymetrix SNP array. Additionally, we performed a detailed analysis of how evenly each technology covers the genome and how the reads are distributed across functional genomic regions. Finally, we studied how a combination of data from different technologies might help to overcome the limitations in SNV calling by any of the four technologies alone.

Study EGAS00001000274

Natural history of clonal haematopoiesis (2017-09-04)

The incidence of acute myeloid leukemia (AML) increases with age and mortality exceeds 90% when diagnosed after age 60. Only 10-15% of cases evolve from a pre-existing myeloproliferative or myelodysplastic disorder; the remaining cases arise de novo without a detectable prodrome and are diagnosed upon development of bone marrow failure. Analysis of diagnostic blood samples has demonstrated that de novo AML is preceded by the accumulation of somatic mutations in pre-leukemic hematopoietic stem and progenitor cells (preL-HSPCs) that subsequently undergo clonal expansion. If individuals in this pre-leukemic phase could be identified, methods for determination of risk and monitoring for progression to overt AML could be developed. However recurrent AML mutations also accumulate during aging in healthy individuals who never develop AML, referred to as age related clonal hematopoiesis (ARCH). To distinguish individuals with preL-HSPCs at high risk of developing AML from those with ARCH, we undertook deep targeted sequencing of genes recurrently mutated in AML in blood samples from 133 individuals in the European Prospective Investigation into Cancer and Nutrition (EPIC) study taken on average 6 years before they developed AML (pre-AML group), together with 683 matched healthy individuals (Control group). Pre-AML cases displayed accelerated age-correlated accumulation of somatic mutations.The identity, number and variant allele frequency (VAF) of mutations differed between the two groups, and were incorporated into a computational model of AML risk prediction that accurately distinguished pre-AML cases from controls on average 7 years prior to AML development. Our findings provide proof of concept that early prediction of AML development is feasible in high-risk populations, paving the way for early disease detection, monitoring, and potentially prevention.

Dataset EGAD00001003703

A comprehensive characterization of the cell-free transcriptome reveals tissue- and subtype-specific biomarkers for cancer detection

Cell-free RNA (cfRNA) is a promising analyte for cancer detection. However, a comprehensive assessment of cfRNA in individuals with and without cancer has not been conducted. We performed the first transcriptome-wide characterization of cfRNA in cancer (stage III breast [n=46], lung [n=30]) and non-cancer (n=89) participants from the Circulating Cell-free Genome Atlas (NCT02889978). Of 57,820 annotated genes, 39,564 (68%) were not detected in cfRNA from non-cancer individuals. Within these low-noise regions, we identified tissue- and cancer-specific genes, defined as "dark channel biomarker" (DCB) genes, that were recurrently detected in individuals with cancer. DCB levels in plasma were correlated with tumor shedding rate and RNA expression in matched tissue, suggesting that DCBs with high expression in tumor tissue could enhance cancer detection in patients with low levels of circulating tumor DNA. Overall, cfRNA provides a unique opportunity to detect cancer, predict the tumor tissue of origin, and determine the cancer subtype.

Study EGAS00001004704

RaScALL: Rapid (Ra) screening (Sc) of RNA-seq data for prognostically significant genomic alterations in acute lymphoblastic leukaemia (ALL)

RNA-sequencing (RNA-seq) efforts in acute lymphoblastic leukaemia (ALL) have identified numerous prognostically significant genomic alterations which can guide diagnostic risk stratification and treatment choices when detected early. However, a full RNA-seq Bioinformatics workflow is time-consuming and costly in a clinical setting where rapid detection and accurate reporting of clinically relevant alterations are essential. To accelerate the identification of ALL-specific alterations (including gene fusions, single nucleotide variants and focal gene deletions), we developed the rapid screening tool RaScALL, capable of identifying more than 100 prognostically significant lesions directly from raw sequencing reads. RaScALL uses the k-mer based targeted detection tool km and known ALL variant information to achieve a high degree of accuracy for reporting subtype defining genomic alterations compared to standard alignment-based pipelines. Gene fusions, including difficult to detect fusions involving EPOR and DUX4, were accurately identified in 98% (164 samples) of reported cases in a 180-patient Australian study cohort and 95% (n=63) of samples in a North American validation cohort. Pathogenic sequence variants were correctly identified in 75% of tested samples, including all cases involving subtype defining variants PAX5 p.P80R (n=12) and IKZF1 p.N159Y (n=4). Accurate detection of intragenic IKZF1 deletions resulting in aberrant transcript isoforms was also detectable with 98% accuracy. Importantly, the median analysis time for detection of all targeted alterations averaged 22 minutes per sample, significantly shorter than standard alignment-based approaches, ensuring accelerated risk-stratification and therapeutic triage.

Dataset EGAD00001009087

Diagnostic utility of whole genome sequencing in adults with B-other acute lymphoblastic leukemia

Genomic profiling at diagnosis of B-cell precursor Acute Lymphoblastic Leukemia (BCP-ALL) in adults is used to guide disease classification, risk stratification and treatment decisions. Patients for which diagnostic screening fails to identify disease defining or risk stratifying lesions are classified as B-other ALL. We screened a cohort of 652 BCP-ALL cases enrolled in UKALL14 to identify and perform whole genome sequencing (WGS) on paired tumor-normal samples. For 52 B-other patients we compared WGS findings to data from clinical and research cytogenetics. WGS identifies a cancer associated event in 51/52 cases, this includes an established subtype defining genetic alteration in 5/52 that were previously missed by standard-of-care genetics. Of the 47 true B-other ALL we identified a recurrent driver in 87% (41). Complex karyotype by cytogenetics emerges as a heterogeneous group, underlied by distinct genetic alterations associated with either favorable (DUX4-r) or poor outcomes (MEF2D-r, IGK::BCL2). For a subset of 31 cases, we integrate findings from RNA-sequencing (RNA-seq) analysis to include fusion gene detection, and classification by gene expression. Compared to RNA-seq, WGS was sufficient to detect and resolve recurrent genetic subtypes, however RNA-seq can provide orthogonal validation of findings. In conclusion, we demonstrate that WGS can identify clinically relevant genetic abnormalities missed by standard-of-care testing and identify leukemia driver events in virtually all cases of B-other ALL.

Dataset EGAD00001009304

Identification of the Global miR-130a Targetome Reveals a Novel Role for TBL1XR1 in Hematopoietic Stem Cell Self-Renewal and t(8;21) AML

In this study, we identified miR-130a as a regulator of HSC self-renewal and differentiation. To characterize gene expression changes following enforced expression of miR-130a OE, we performed RNA-seq in CD34+ cord blood (CB) cells transduced with control and miR-130a OE lentiviruses. To capture miRNA targets in an unbiased, transcriptome-wide manner, we perfomed enhanced CLIPseq procol in 2 replicates of CD34+ CB cells and Kasumi-1 cell line, which represent a model system for t(8;21) AML. We chose this cell line, as we found miR-130a to be highly expressed in this AML subtype where it is critical for maintaining the oncogenic molecular program mediated by AML1-ETO. Chimeric Ago2 eCLIPseq in CD34+ CB cells combined with Mass Spectrometry data analysis identified TBL1XR1 as a principal target of miR-130a. To elucidate gene expression changes associated with TBL1XR1 loss of function, we performed RNA-seq in CD34+CD38- CB cells transduced with control and shRNA targeted against TBL1XR1. To determine the functional significance of high miR-130a expression levels in Kasumi-1 cells on the molecular network controlled by AML1-ETO, we performed CUT&RUN assay and RNA-seq in Kasumi-1 cells following miR-130a knock-down (KD). Collectively, our findings reveal a unique role of miR-130a in regulating normal hematopoietic stem cell self-renewal and how elevated levels of miR-130a in t(8;21) AML contribute to the leukemogenesis of this AML subtype.

Dataset EGAD00001008412

National Eye Institute Glaucoma Human Genetics Collaboration (NEIGHBOR) Consortium Glaucoma Genome-Wide Association Study: Whole Exome Resequencing in Glaucoma

This is a study of primary open angle glaucoma (POAG) conducted through exome sequencing of cases and comparison of variant frequencies with general population frequencies available in dbGAP and controlled for sequencing platform artifact to minimize false positives. POAG is an intraocular pressure (IOP) related progressive optic neuropathy that ultimately leads to blindness. This study builds upon the efforts of an on-going collaborative consortium that studied 2,170 POAG cases and 2,347 controls with a unified definition of POAG (the NEIGHBOR consortium: NEI Glaucoma Human genetic collaBORation). The case definition for NEIGHBOR was harmonized with an additional 976 cases and 1140 controls from the NHGRI supported GENEVA (gene-environment) study of glaucoma (GLAUGEN) (NIH/NHGRI U01HG004728, Pasquale PI). In NEIGHBOR, cases and controls were recruited from ophthalmology clinics and were examined by ophthalmologists. For cases, the clinical exam included intraocular pressure measurements, optic nerve assessment and visual field evaluation. Controls had no family history of glaucoma, normal intraocular pressure and normal optic nerves. Cases and controls were also drawn from two clinical trial populations: Advanced Glaucoma Intervention Study (AGIS, NEI U10EY006827, D. Gaasterland PI) and Collaborative Initial Glaucoma Treatment Study (CIGTS, NEI U10 EY009149, P. Lichter PI). The Glaucoma Exome Sequencing study has one Principal Investigator: Theresa Gaasterland (UCSD) and two Co-Investigators: Robert Weinreb, MD, and Kang Zhang, MD, PhD, all of whom are part of the NEIGHBOR, subsequently NEIGHBORHOOD, consortium, which in turn has two Co-Principal Investigators: J. Wiggs (Harvard, MEEI), and M. Hauser (Duke). NEIGHBOR collaborators who contributed samples and/or expertise to the Glaucoma Exome Sequencing study included the following: Harvard Medical School (Massachusetts Eye and Ear Infirmary) (J. Wiggs, L. Pasquale); Duke University Medical Center (M. Hauser, E. Hauser, R. Allingham, S. Schmidt); University of Michigan (J. Richards, S. Moroi, P. Lichter); University of Miami (M. Pericak-Vance, R. Lee, D. Budenz); Vanderbilt University (J. Haines); University of California San Diego (K. Zhang, R. Weinreb; T. Gaasterland); University of Pittsburgh (J. Schuman, G. Wollenstein); University of West Virginia (A. Realini, J. Charlton, S. Zareparsi); Johns Hopkins University (D. Friedman); Stanford University (D. Vollrath, K. Singh), Eye Doctors of Washington (D. Gaasterland), Marshfield Clinic (Cathy McCarty). Hemin Chin serves as the NEI Staff Collaborator. This national collaborative study is supported by multiple NIH grants: NEI R01 EY015543 (Allingham); NEI U10 EY006827 (D. Gaasterland); NHLBI R01 HL073389 (E. Hauser); NEI R01 EY13315 (M. Hauser); NEI U10 EY009149 (Lichter); NEI R01 EY015473 (Pasquale); NEI U10 EY012118 (Pericak-Vance); NEI R03 EY015682 (Realini); NEI R01 EY011671 (Richards); NEI R01 EY09580 (Richards); NEI R01 EY013178 (Schuman); NEI R01 EY015872 (Wiggs); NEI R01 EY009847 (Wiggs); NEI R01 EY010886 (Wiggs); NEI R01 EY144428 (Zhang); NEI R01 EY144448 (Zhang); NEI R01 EY18660 (Zhang). Funding support for genotyping through exome sequencing, which was performed at the University of California, San Diego, was provided by the National Eye Institute (RC2 EY020678-01).

Study phs000558

Population Architecture using Genomics and Epidemiology (PAGE)

PAGE II (2013-2017) seeks to expand understanding gained during PAGE I and similar studies of how ancestry-specific differences in allele frequencies and LD may explain differences in risks of common traits and conditions. Recent studies have identified rare genetic variants that are likely to contribute to common diseases and traits and observed that rare variants likely to be functional, such as those in coding and regulatory regions, tend to be population-specific. PAGE II has genotyped over 50,000 samples using MEGA, an Illumina high density custom exomechip array. The MEGA data is being imputed in PAGE to the 1000 Genomes panel. PAGE also sequenced 1,000 samples representative of 21 populations from the Americas. PAGE has harmonized phenotype data for ~300 trait variables. These datasets will be analyzed to continue emphasis on characterizing population-level disease risks in non-European-descent individuals. Cohorts in PAGE II are: CALiCo (Causal Variants Across the Life Course, a consortium of ARIC, CARDIA, HCHS/SOL, Strong Heart Studies), ISMMS (Mount Sinai BioMe Biobank), MEC (Multiethnic Cohort), WHI (Women's Health Initiative), and Stanford University (PAGE Global Reference Panel). Genotyping services were provided by the Center for Inherited Disease Research (CIDR) and sequence data were provided by the McDonnell Genome Institute at Washington University School of Medicine. PAGE I (2008-2013): The first phase of PAGE examined putative causal genetic variants across approximately 100,000 African Americans, Asian Americans, American Indians, European Americans, Hispanic Americans, and Native Hawaiians from four groups representing nine large U.S.-based cohorts. Two genotyping approaches were employed - targeted genotyping of selected SNPs identified in genome-wide association studies of common disease, and a large-scale effort focused on the Metabochip array, which facilitated trans-ethnic fine mapping of several diseases of public health importance. Cohorts in PAGE I were: CALiCo (Causal Variants Across the Life Course, a consortium of ARIC, CARDIA, CHS, HCHS/SOL, Strong Heart Cohort Study, Strong Heart Family Study), EAGLE (Epidemiologic Architecture for Genes Linked to Environment, based on 3 National Health and Nutrition Examination Surveys (NHANES)), MEC (Multiethnic Cohort) and WHI (Women's Health Initiative). Logistical and scientific support is provided by the PAGE Coordinating Center and the NHGRI Division of Genomic Medicine. PAGE II is funded by the NHGRI and the NIMHD. To access PAGE studies currently available in dbGaP, please click on the links below.Please note that some PAGE studies belong to larger cohorts and have been included as PAGE substudies. For those studies, there is an additional link to the parent study. phs000223 PAGE-ARIC and phs000280 ARIC Cohort phs000236 PAGE-CARDIA and phs000285 CARDIA Cohort phs000301 PAGE-CHS and phs000287 CHS Cohort phs000559 PAGE-EAGLE-BioVu phs000208 PAGE-EAGLE-NHANES phs000555 PAGE-HCHS/SOL and phs000810 HCHS/SOL Cohort phs000220 PAGE-MEC phs000580 PAGE-SHS and SHFS phs001033 PAGE Global Reference Panel phs000227 PAGE-WHI and phs000200 WHI Cohort

Study phs000356

Heart Failure Network: Inorganic Nitrite Delivery to Improve Exercise Capacity in HFpEF (HFN INDIE-BioLINCC)

Data Access NOTEPlease refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.ObjectiveTo determine the effect of inhaled, nebulized inorganic nitrite on exercise capacity in patients with heart failure with preserved ejection fraction. Background Approximately half of patients with heart failure have a preserved ejection fraction (HFpEF). However, there are no proven effective medical treatments for this syndrome. Evidence suggests that impairments in nitric oxide availability have a potentially important role in the pathophysiology of HFpEF. Unlike organic nitrates, inorganic nitrite is converted to nitric oxide in the presence of hypoxia and acidosis, conditions that develop during exercise. Because the cardiac, vascular, and skeletal muscle abnormalities that limit physical capacity and contribute to symptoms in patients with HFpEF characteristically develop during exercise, inorganic nitrite may provide the best way to target nitric oxide delivery precisely at the time of greatest need. The HFN-INDIE trial was initiated to test the hypothesis that compared to placebo, longer-term use of inhaled, nebulized inorganic nitrite would enhance peak exercise capacity in patients with HFpEF. Participants A total of 105 participants were randomized. 53 were randomized to receive nitrite first and 52 were randomized to receive placebo first. Design HFN-INDIE was a multicenter, randomized, double-blind, placebo-controlled, crossover study. After enrollment, patients underwent baseline studies to determine eligibility. All patients were required to display objective exercise limitation, evidenced by reduced peak oxygen consumption (V̇O2) on cardiopulmonary exercise testing of less than 75% predicted, with a respiratory exchange ratio indicative of maximal effort (≥1.0). Following qualifying exercise testing, eligible participants received an open-label, single-dose run-in of inhaled, nebulized sodium nitrite (80 mg) to assess tolerability, symptoms, and orthostatic vital signs. Patients developing hypotension (systolic blood pressure The prespecified primary end point was peak V̇o2, measured as the highest 30-second average during upright cycle ergometry, during the 4-week period in which patients were receiving inorganic nitrite as compared with placebo. Accelerometry, health-related quality-of-life scores on the self-administered Kansas City Cardiomyopathy Questionnaire (score range, 0-100, with higher scores indicating better quality of life), echocardiographic indicators of cardiac filling pressures measured at trough drug levels (E/e' ratio, estimated pulmonary artery systolic pressure, and left atrial volume index; lower scores indicate better health for all), ventilatory efficiency (VE/V̇co2, lower indicating better health), exercise time (higher indicating better health), and NT-proBNP levels (lower indicating better health) were also collected. Conclusions Among patients with HFpEF, administration of inhaled inorganic nitrite for 4 weeks, compared with placebo, did not result in significant improvement in exercise capacity. Borlaug et al., 2018, PMID: 30398602.

Study phs003667

The Finland-United States Investigation of NIDDM Genetics (FUSION) Study - Islet Expression and Regulation by RNAseq and ATACseq

This study evaluates gene expression and its regulation in human pancreatic islets, a tissue relevant in the study of genetic risk factors contributing to diabetes. We obtained pancreatic tissue sections and purified pancreatic islets from deceased donors and processed these biological samples to generate various data types. We generated spatial transcriptomic data from pancreatic tissue samples using the 10X Genomics VISIUM technology with sequencing on the Illumina NovaSeq platform. We also generated multiple data types from the purified pancreatic islets using genome-wide SNP chips, bulk RNA-Seq, microRNA (miRNA)-Seq, whole genome sequence, DNA methylation (methyl)-Seq, cap analysis of gene expression (CAGE)-Seq, single cell RNA-seq, and single nuclei ATAC-seq approaches. These data include ATAC-seq of two islet subjects, RNA-seq of 31 additional subjects, genome-wide chip genotypes, and imputed genotypes of the 33 subjects released with phs001188.v1. For genotyping, 500-1000 islet equivalents (IEQ) were cultured as in Gershengorn (Science, 2004, PMID: 15564314); genomic DNA isolated from islet cultures. For RNA analyses, 2500-5000 IEQ from each islet source were used for bulk or single-cell RNA isolation. Messenger RNA was isolated with trizol extraction and 12-plex libraries were generated using the Illumina TruSeq directional mRNA-seq library protocol. Bulk RNA sequencing was performed on HiSeq2000/HiSeq2500/Hiseq4000/NovaSeq6000 sequencers using paired-end reads at the NIH Intramural Sequencing Center (NISC). miRNA libraries were prepared from total RNA from 68 samples, pooled and sequenced 50bp single-end reads on Illumina HiSeq2500. CAGE libraries were prepared from total RNA samples using the nAnT-iCAGE protocol at DNAFORM, Japan. CAGE libraries were sequenced at the NIH Intramural Sequencing Center (NISC) on the HiSeq2000 sequencer. Genotyping on the Illumina Omni2.5M array was performed at the NHGRI Genomics Core facility. Genotypes were imputed using the HRC.r1.1.2016 reference panel. To assess regions of open chromatin in islets, we performed bulk ATAC-seq on HiSeq2000 sequencers using paired-end reads at NISC. Single-nuclei ATAC-seq libraries were prepared using single-cell-combinatorial-indexing (sci-) ATAC-seq protocol and sequenced on Illumina NextSeq using paired-end reads. scRNA-seq libraries were generated using the 10X Genomics platform and sequenced on Illumina HiSeq3000 at the Genomics Technology Core of the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS). Greater than 90% of the loci associated with T2D through genome-wide association studies occur in non-coding regions, suggesting a strong regulatory component to disease susceptibility. Therefore, there is a critical need to understand the full spectrum of genetic variation and regulatory element usage in T2D-relevant tissues. To that end, this study contains multiple genomic and transcriptomic data sets from pancreas tissue sections and pancreatic islets, a resource that will contribute to our efforts to investigate the genetic risk factors for type 2 diabetes.

Study phs001188

Resuscitation Outcomes Consortium (ROC) Controlled Study of the Clinical Effectiveness of Automated Real-Time Feedback on CPR Process Conducted at a Subset of ROC Sites (CPR) (ROC-CPR-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.Objectives: A substudy of the ROC PRIMED trial, the ROC CPR trial sought to investigate whether real-time audio and visual feedback during cardiopulmonary resuscitation (CPR) outside a hospital increases the proportion of participants who achieved prehospital return of spontaneous circulation.Background: Cardiopulmonary resuscitation is an essential link in the chain of survival for treating cardiac arrest. However, performance of CPR is highly variable both outside hospital and in hospital. Interruptions in chest compression, inadequate depth of chest compression, and high rates of ventilation adversely affect blood flow during chest compressions and can hinder resuscitation. Suboptimal CPR, particularly time spent without chest compressions (low chest compression fraction), can reduce survival of cardiac arrest patients.Current technology incorporated into a monitor-defibrillator can assess core components of CPR through the use of an accelerometer and impedance changes across the defibrillation electrodes. This technology can also provide real-time audiovisual feedback so that the rescuer is prompted to perform according to guideline specifications. Use of such feedback increases the likelihood of performing CPR in accordance with guidelines during training and simulation. Participants: There were 1586 participants: 771 treated without feedback and 815 with feedback.Design: CPR feedback was provided through proprietary Q-CPR software operating in the Philips MRx monitor-defibrillator. The feedback feature of the defibrillator includes audible voice prompts and visual messages on the monitor screen that are triggered when measured chest compressions or ventilation deviate from guidelines or are interrupted.The study was conducted in 21 emergency medical service (EMS) agencies at three ROC regions in the U.S. and Canada. Randomized treatment clusters, which ranged from individual emergency medical vehicles to groups of emergency agencies, were assigned to feedback-on or feedback-off treatments. Each cluster remained in its assigned mode for two to seven months, after which it switched to the opposite treatment arm. At the end of those two treatment periods, each cluster was again randomly assigned to feedback-on or feedback-off. This cycle continued for the duration of the study. Each cluster switched treatment arms at least once, and up to four times, during the study. Conclusions: Real-time visual and audible feedback during CPR altered performance to more closely conform with CPR guidelines. Clusters assigned to feedback were associated with increased proportion of time in which chest compressions were provided, increased compression depth, and decreased proportion of compressions with incomplete release. However, frequency of prehospital return of spontaneous circulation did not differ according to feedback status, nor did the presence of a pulse at hospital arrival, survival to discharge, or awake at hospital discharge (Hostler, et al., 2011, PMID: 21296838).

Study phs003818

Capturing sex-specific and infertility-linked effects of assisted reproductive technologies on the cord blood DNA methylome

Background: Children conceived through assisted reproduction are at an increased risk for growth and genomic imprinting disorders, often linked to DNA methylation defects. It has been suggested that assisted reproductive technologies (ART) and the underlying parental infertility can induce epigenetic instability, specifically interfering with DNA methylation reprogramming events during germ cell and preimplantation development. To date, human studies exploring the association between ART and DNA methylation defects report inconsistent or inconclusive results, likely due to population heterogeneity and the use of technologies with limited coverage of the epigenome. In our study, we explore the epigenetic risk of ART by comprehensively profiling the DNA methylome of 73 human cord blood samples from singleton pregnancies (n=36 control group, n=37 ART/infertility group) from a human prospective longitudinal birth cohort, the Design, Develop, Discover (3D) Study using a high resolution sequencing based custom capture panel that interrogates over 2.4 million autosomal CpGs in the genome. Results: the main findings We identified striking sex-specific effects of ART on cord blood DNA methylation patterning both genome-wide and for imprinted genes. When compared to less invasive procedures such as in utero insemination, more invasive ARTs (IVF, ICSI, embryo culture) resulted in more marked and distinct effects on the cord blood DNA methylome, including targeting of loci involved in development. Background: Children conceived through assisted reproduction are at an increased risk for growth and genomic imprinting disorders, often linked to DNA methylation defects. It has been suggested that assisted reproductive technologies (ART) and the underlying parental infertility can induce epigenetic instability, specifically interfering with DNA methylation reprogramming events during germ cell and preimplantation development. To date, human studies exploring the association between ART and DNA methylation defects report inconsistent or inconclusive results, likely due to population heterogeneity and the use of technologies with limited coverage of the epigenome. In our study, we explore the epigenetic risk of ART by comprehensively profiling the DNA methylome of 73 human cord blood samples from singleton pregnancies (n=36 control group, n=37 ART/infertility group) from a human prospective longitudinal birth cohort, the Design, Develop, Discover (3D) Study, using a high resolution sequencing based custom capture panel that interrogates over 2.4 million autosomal CpGs in the genome. Results: We identified striking sex-specific effects of ART on cord blood DNA methylation patterning both genome-wide and for imprinted genes. When compared to less invasive procedures such as in utero insemination, more invasive ARTs (in vitro fertilization (IVF), intracytoplasmic sperm injection (ICSI), embryo culture) resulted in more marked and distinct effects on the cord blood DNA methylome, including targeting of loci involved in development. Conclusions: Our study highlights the ability of a sensitive, targeted, sequencing based approach to uncover DNA methylation perturbations in cord blood associated with infertility and ART and influenced by offspring sex and ART technique invasiveness.

Study EGAS00001006643

Genome-Wide Association Study of Anorexia Nervosa (Price Foundation, Klarman Family Foundation, Center for Applied Genomics at the Children's Hospital of Philadelphia, Scripps Translational Sciences Institute Clinical Translational Science Award)

Twin studies are consistent with substantial heritability in anorexia nervosa (AN), although detecting and confirming individual risk alleles has been difficult, due to small effects of single alleles and limited samples in prior studies. Methods: 1105 AN DNA samples obtained in a multisite study and 3733 pediatric patients of normal body weight were genotyped using the Illumina 610Q chip at The Center for Applied Genomics at The Children's Hospital of Philadelphia. Cases and controls were of European ancestry. Single nucleotide polymorphism (SNP) genotypes were subjected to quality control procedures, including elimination of SNPs with: call rates < 95%, minor allele frequency < 5%, and if Hardy-Weinberg equilibrium testing yielded p < 0.0001. Samples were removed if not of European ancestry or if showing cryptic relatedness. Eight AN DNA samples were deleted for low call rate, and 51 AN samples were deleted for cryptic relatedness. The statistical program, PLINK, was used to calculate a P value for each SNP passing quality control using the Cochran-Armitage trend test. The PennCNV program was used to define copy number variation (CNV). Results: We performed a genome-wide association study (GWAS) using with 1033 AN cases and 3733 controls (genomic inflation factor = 1.08). There were 11 SNPs with P<1X10-5 [(rsID, chromosome location, nearest gene, distance to nearest gene (base-pair), P value) rs6959888, 7q21.13, ZNF804B, 0, 1.63E-06; rs17725255, 20p11.23, CSRP2BP, 39396, 1.72E-06; rs10494067, 1p13.3, NTNG1, 0, 5.83E-06; rs2383378, 14q12, AKAP6, 0, 6.41E-06; rs410644, 5q14.1, SSBP2, 40462, 6.74E-06; rs4479806, 5p14.1, CDH9, 156926, 7.79E-06; rs957788, 13q33.3, FAM155A, 0, 8.11E-06; rs830998, 2q31.1, LRP2, 0, 8.68E-06; rs6782029, 3p25.3, VGLL4, 0, 9.04E-06; rs512089, 9p21.3, ELAVL2, 47984, 9.85E-06; rs3808986, 11q24.3, APLP2, 29217, 9.92E-6]. CNV analyses were performed on 1015 AN cases and 3532 controls. Overall frequencies of common or rare CNVs were similar between cases and controls. Specific rare and large (>500 kb, <1%) CNVs of interest included deletion of a large (~1.4Mbp) region of chr13q12 found in 2 AN samples and at a 10 fold lower frequency in a large sample (72,918) of subjects containing the genes SGCG, SACS, TNFRSF19, MIPEP, PCOTH, C1QTNF9B, SPATA13, MIR2276, and C1QTNF9, and an overlapping deletion and a duplication observed in 3 AN samples overlapping the CNTN6 and CNTN4 genes. Partially overlapping ~ 30 kb duplications were seen in 12 AN cases and in 1 control at the CDC5L gene on chromosome 6. Partially overlapping deletion of the 3' half of the PSTPIP1 gene was seen in 5 AN cases and no controls. Finally, a ~ 60 kb deletion of the PLEC1 gene was observed in 5 AN cases and in none of 3532 controls. Discussion: This is the first GWAS of AN. These preliminary results are consistent with absence of a major gene effect in AN. These results are consistent with genetic risk conveyed by multiple common alleles of small effect, as well as some uncommon CNVs of potentially larger effect. None of the implicated genes has a clear role in eating behavior. It must be emphasized that these results are preliminary and an additional ~ 400 AN cases will be analyzed as time and resources permit. These results require confirmation through study of independent populations of AN women.

Study phs000679

WTCCC case-control study for T1D and RA - combined cases

WTCCC genome-wide case-control association study using two disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

Study EGAS00000000013

ICGC Benchmarking Exercise

The main objective of this benchmark is the comparison of the full sequencing pipeline of different ICGC partners, including procedures, methods and performance of library preparation and whole-genome deep-sequencing. A secondary objective will be a follow-up comparison of data analysis pipelines for identification of germline and somatic variants subsequent to the results of the ICGC Somatic Variant Calling Pipeline Benchmark.

Dataset EGAD00001000625

Set_of_human_mesenchymal_CSA

51 DNA methylation arrays of human samples initially diagnosed as mesenchymal chondrosarcoma. Microdissection of the cartilage and/or the small round cell component from the same sample may have occurred. As mentioned in the sample descriptions, the diagnoses of four samples have been revised. Additional molecular investigations were conducted for a subset of samples as described in the related publication.

Dataset EGAD00010002515

Exome Sequencing for brazilian patients with Idiopathic Collapsing Glomerulopathy

This dataset contains 2 BAM files sequenced with Illumina NextSeq 500 e NovaSeq 600 and 20 files with variant calling sequenced with Illumina NextSeq 500 e NovaSeq 600.

Dataset EGAD50000000091

AmsterdamUMC Data Access Committee for the study entitled "Carboxylesterase 1 mediates a distinctive metabolic profile of dendritic cells to attain an inflammatory phenotype"

The current data access committee reviews and assesses data requests of researchers that seek to gain access to data presented in the manuscript entitled "Carboxylesterase 1 mediates a distinctive metabolic profile of dendritic cells to attain an inflammatory phenotype" as performed at the AmsterdamUMC, Amsterdam, Netherlands.

Dac EGAC50000000178

BAM files from capture-based targeted sequencing of 4 agressive B-cell lymphoma tumour samples (DLBCL-panel)

This dataset contains BAM files from capture-based targeted sequencing of 4 agressive B-cell lymphoma tumour samples for cases 2, 3, 4 and 13. The sequencing panel used is a DLBCL-oriented panel containing 136 genes, described in Mozas P. et al., Hematol Oncol 2023.

Dataset EGAD50000000802

Cas9-targeted-based long-read sequencing for genetic screening of RPE65 locus

The dataset includes sequencing data from five inherited retinal dystrophies (IRD) patients using three diferent platforms: Clinical Exome (CES), Long-read sequencing of RPE65 locus, and 3) whole genome sequencing.

Dataset EGAD50000000847

BIOMIROX

This dataset regroups RNAseq of paired primary colorectal cancers and liver metastases extracted from 113 patients In Paris and Besançon University Hospitals. 216 FASTQ files from single-end 3' PolyA (QuantSeq 3′mRNA-Seq Kit FWD for Illumina (Lexogen)) RNAseq samples were generated On NOVASEQ 6000 (ILLUMINA).

Dataset EGAD50000000443

Asan Medical Center Data Access Committee

This DAC is responsible for reviewing and approving data access requests to protect the sensitive information of patients. The dataset includes RNA-seq data from CRLM patients treated with FOLFOX, bevacizumab, and atezolizumab, and supports research in gene expression analysis and therapeutic response. Data access requests require an approved ethical research plan, limited to projects related to cancer biology and therapy development.

Dac EGAC50000000439

WES for CNV-verified CTCs from 2 patients with metastatic prostate cancer

This dataset contains 4 paired fastq files sequenced by illumina Novoseq 6000. WES analysis (illumina platform, PE150, 100x coverage) was performed on a pool of CNV-verified CTCs that were enriched using high-throughout microfluidic device from entire leukopak from patients with metastatic prostate cancer (GU-1 and GU-2).

Dataset EGAD50000001005

Saliva_Fulani_Database

In total, 90 DNA samples were genotyped on the Illumina Infinium H3Africa Consortium array (designed for 2,271,503 SNPs; using BeadChip type: H3Africa_2019_20037295_B1). Genotyping was performed at the SNP&SEQ Technology Platform (NGI/SciLifeLab Genomics, Sweden). Saliva Fulani dataset includes individuals from the following populations: 30 individuals from Senegal_FulaniLinguere, 30 individuals from Mauritania_FulaniAssaba, and 30 individuals from Mali_FulaniInnerDelta.

Dataset EGAD50000000653

DAC of "Gene expression adaptation of metastases to their host tissue"

The DAC consists of Prof. Axel Hillmer, University of Cologne, Faculty of Medicine and University Hospital Cologne, Institute of Pathology, Cologne, Germany, e-mail: ahillmer@uni-koeln.de and Prof. Andreas Beyer, University of Cologne, Faculty of Mathematics and Natural Sciences, Cologne Excellence Cluster for Aging and Aging-Associated Diseases (CECAD), Cologne, Germany, e-mail: andreas.beyer@uni-koeln.de

Dac EGAC50000000514

Single-Cell Profiling of the Human Endometrium in Polycystic Ovary Syndrome: Uncovering Disease Signatures and Treatment Responses

Single-nuclei map of human endometrial biopsies from women with and without PCOS to identify cell-type-specific disease signatures, compositional variations, and transcriptomic reversibility after a 16-week intervention with metformin or lifestyle. Single nuclei were extracted from 27 frozen endometrial biopsies for snRNA-seq using the 10X Genomics protocol.

Dac EGAC50000000468

HIV-phyloTSI: PANGEA (veSEQ-HIV)

This dataset includes sample numbers TSI_0001 to TSI_0202 and TSI_0316 to TSI_0425 for the PANGEA (veSEQ-HIV) cohort of the study. Samples were sequenced using the Illumina NovaSeq system and the veSEQ-HIV method (see Bonsall, Golubchik et al 2020, DOI: 10.1128/JCM.00382-20). Each sample has a BAM file, and its associated reference file.

Dataset EGAD50000001309

HIV-phyloTSI: PANGEA (PCR amplicon)

This dataset includes sample numbers TSI_0426 to TSI_0527 for the PANGEA (PCR amplicon) cohort of the study. Samples were generated by pooling four overlapping PCR amplicons (see Gall et al 2012, DOI: 10.1128/JCM.01516-12). The sequencing was conducted using the Illumina NovaSeq system. Each sample has a BAM file, and its associated reference file.

Dataset EGAD50000001308

Scalable ultra-high-throughput multiplexed single-cell chromatin and RNA profiling reveals gene regulatory dynamics during stimulation time courses and CRISPR perturbation screens

Data for 1) hiPSC-derived macrophages across a polarization time course from the naive M0-state to the M1- and M2-states, 2) Primary T-cells differentiated to helper subtypes, and 3) spontaneous differentiation of hiPSCs upon perturbation of GATA2, NR4A2 or SOX17

Dac EGAC50000000485

Spatial and temporal transcriptome analysis on human skeletal muscle regeneration

Skeletal muscle carries a unique ability for adaptation as well as regeneration that highly depends on a supportive cellular microenvironment. Here we show that spatial and single-cell transcriptomic analysis in human skeletal muscle is a unique approach to illuminate cellular interactions in the microenvironment.

Dataset EGAD50000000263

Dataset for single cell transcriptome sequencing

This datasets contains single cell transcriptome sequencing of 10 control samples. Sequencing has been performed on Illumina NovaSeq 6000 using 10xGenomics Chromium Next GEM Single Cell 5 Reagent Kits. Sequencing was always paired. This dataset additionally contains a .QS file from Seurat Analysis performed in R, generated as described in the related publication.

Dataset EGAD50000001549

Paired FastQ files from deep targeted DNA sequencing

This dataset comprises paired-end and time-matched FastQ files from 356 cell-free DNA samples and 356 white blood cell DNA samples, derived from 299 patients with metastatic renal cell carcinoma or urothelial carcinoma. A baseline sample was available for all patients. Sequencing was performed using Illumina technology.

Dataset EGAD50000001267

Single-cell RNA-sequencing for peripheral blood mononuclear cells and plasma proteomics data from COVID-19 patients and healthy controls of Japanese

We performed single-cell RNA-sequencing of peripheral blood mononuclear cells and measured plasma protein expression from COVID-19 patients and healthy controls.

Study JGAS000783

Methylation Array data for: Three-dimensional patient-derived models of glioblastoma retain intra-tumoral heterogeneity

3 sets of matched patient-derived-organoids (PDOs),Â -neurospheres (PDNs), and parent glioblastoma tissue (9 samples total) underwent methylation array analysis. 200ng of each sample DNA extracted via a commercial kit (Qiagen) and loaded onto the Illumina EPIC v2.0 array. Data is provided as raw red and green .idat files.

Dataset EGAD00010002745

WGS of thymic epithelial tumors and paired normal

Among the 20 newly sequenced cases, we conducted additional whole-genome sequencing (WGS) on five out of eight CN-type thymomas, excluding three with low tumor cell fractions (< 0.1). Libraries for WGS were prepared using the TrueSeq DNA PCR-free Prep Kit following standard Illumina protocols.

Dataset EGAD50000001160

MissionBio single cell DNA and protein seq for 2 samples

This dataset contains MissionBio Targeted single-cell DNA and Protein sequencing data from a primary sample and a patient-derived xenograft (PDX) model, which is used to investigate the clonal evolution in the FOXF1/FENDRR ALL subtype. All the 2 samples are in bam file type.

Dataset EGAD50000001793

Leiomyosarcoma Cancer Transcriptome Sequencing

RNA-Seq data (fastq raw read sequences) for French ICGC leiomyosarcoma cancer sequencing project, 78 samples representing 67 donors. Sequencing was performed on Illumina HiSeq. The libraries were then sequenced with a 2 x 75bp paired-end protocol to a minimum mean reads of 50 million.

Dataset EGAD00001003192

Survival Benefit and Genetic Profile of Pemetrexed as Initial Chemotherapy in Selected Chinese Patients with Advanced Lung Adenocarcinoma

NGS data of 12 patients enrolled in the Chinese Patient Assistance Program from multiple centers who received pemetrexed alone or combined with platinum as initial chemotherapy and continued pemetrexed maintenance therapy for advanced lung adenocarcinoma from November 2014 to June 2017.

Dataset EGAD00001006287

SF11136 scRNA-Seq Primary astrocytoma IDH mutant

Single cell RNA-Seq Primary diffuse astrocytoma G2. IDH mutant, ATRX mutant. Gender Male Age 34. Single Cell RNA seq from primary astrocytoma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference through Cellranger count (10xGenomics.)

Dataset EGAD00001005394

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96213A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 522 samples; filetype=bam

Dataset EGAD00001004771

Genomic stratification and liquid biopsy in a rare adrenocortical carcinoma (ACC) case, with dual lung metastases

Dataset consisting of three WGS BAM files, representing the two dual lung metastases with matched germline control, for a 37 year old female patient, with primary adrenocortical carcinoma. Work conducted at Garvan Institute of Medical Research, Sydney, Australia.

Dataset EGAD00001004833

DKFZ-St.Jude Medulloblastoma - 8 MB cases, exome/WGS data

Tumor/Control pairs for 8 medulloblastoma cases, MB cohort, mixed exome and whole genome data, sequenced on Illumina machines from the paper "Germline Elongator mutations in Sonic Hedgehog medulloblastoma" (Waszak et al. 2020 Nature).

Dataset EGAD00001006660

Spatial transcriptomics of 1 untreated prostate cancer.

Two sections of cryopreserved prostate cancer tissue from one untreated prostate cancer patient were profiled for spatial transcriptomics using the Visium Spatial library preparation protocol from 10x Genomics. The GRCh38 aligned sequencing reads from the two prostate cancer tissue sections are provided as BAM files.

Dataset EGAD00001007921

Moles (2019-04-01)

In this project we have sequenced the exome of skin moles (melanocytic naevi) and also normal skin from young and old people. We are interested in looking at the clonality of these lesions and the burden of UV mutations . This dataset contains all the data available for this study on 2019-04-01.

Dataset EGAD00001004876

Whole genome sequencing data to study therapeutic targeting of ependymoma

This dataset contains whole genome sequencing data from 24 patients. For each patient a tumour and control sample has been sequenced on a Illumina HiSeq2000 instrument in paired-end mode. Up to three lanes per sample have been sequenced resulting in 112 Fastq files.

Dataset EGAD00001003940

Prostate Cancer Whole Genome Validations

We propose to definitively characterise the somatic genetics of Prostate cancer through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing. This study will aim to validate the findings of the whole genome study by re-sequencing regions of interest using a bespoke pulldown bait. See ICGC website for more information: http://icgc.org/icgc/cgp/70/508/71331

Dataset EGAD00001000621

Human brain development single cell sequencing

379 tissue samples from various parts of the developing human embryo brain were dissociated and single cells were collected and processed without bias for mRNA-seq using 10X chromium 3' protocol. Libraries were sequenced on Illumina NovaSeq and reads aligned against the human GRCh38 genome.

Dataset EGAD00001006049

Whole genome sequencing of GM09237 cells with and without folate depletion

Two DNA samples extracted from GM09237 cell line cultured with either normal medium or medium with no folic acid for 5 days were sequenced using the BGISEQ500 platform (BGI whole genome 100 bp paired-end sequencing 60x) as well as PacBio Sequel long read sequencing.

Dataset EGAD00001007732

Exome sequencing of control DNA samples from patients with BPLL

DNA extracted from sorted CD3+ cells (16 patients) was used for exome capture with the SureSelect V5 Mb All Exon Kit following the standard protocols. Paired-end sequencing (2 x 100 bp) was performed using HiSeq2000 sequencing instruments.The files are in FASTQ format.

Dataset EGAD00001004411

20190219_EGA_MelanomaOnTreatment

Illumina platform sequencing data for matched tumour-normal DNA samples from 77 melanoma patients participating in a study investigating response to immunotherapy. Selected cases also have RNA sequencing of the tumour.

Dataset EGAD00001004869

Small RNA sequencing from CSF extracellular vesicles - PD/CTR

The dataset contains FASTQ files referring to the study "Small RNA sequencing from CSF extracellular vesicles - PD/CTR". For this project, RNA was isolated from CSF extracellular vesicles obtained by ultracentrifugation. Libraries were prepared with the TruSeq Small RNA library prep Illumina, and sequencing conducted in the Illumina HiSeq4000.

Dataset EGAD00001006629

RNA-seq TPM matrices

Matrices of TPM-normalized counts from RNAseq data for the three phase II clinical trials (IMvigor210, POPLAR, IMmotion150) and the phase I clinical trial PCD4989g.

Dataset EGAD00001006741

Whole exome Sequencing (WES) of multiple tumor biopsies, patient-derived spheroids and leukocyte DNA from colorectal cancer patients (BAM files)

WES was performed using the KAPA-Hyper prep kit from Illumina (Roche, Basel, Switzerland) for library construction, followed by exome capture using Niblegen SeqCap EZ Human Exome Library v3.0 (Roche). Reads were mapped using BWA MEM against the humane reference genome HG19.

Dataset EGAD00001003821

Pleomorphic invasive lobular carcinoma targeted exome sequencing

Fifteen pleomorphic invasive lobular carcionoma samples and their matched normal controls were subjected to targeted exome sequencing using the Beijing Genomics Institute TumorCare gene panel. Genomic DNA samples were randomly fragmented and captured libraries of each exome were sequenced on an Illumina Hiseq2000 system. CRAM files are provided for each tumor and normal pair.

Dataset EGAD00001003995

Whole Exome Sequencing

The Whole Exome Sequencing dataset contains 30 whole exome sequencing files (tumor, germ line DNA) and phenotype metadata for 15 patients on the phase II clinical trial of neoadjuvant immune checkpoint blockade in high-risk resectable melanoma at MD Anderson Cancer Center (NCT02519322). Included are data from baseline samples.

Dataset EGAD00001004352

Exome sequencing of tumor DNA samples from patients with BPLL

DNA extracted from sorted CD19+ tumor cells (16 patients) was used for exome capture with the SureSelect V5 All Exon Kit following the standard protocols. Paired-end sequencing (2 x 100 bp) was performed using HiSeq2000 sequencing instruments. The files are in FASTQ format.

Dataset EGAD00001004410

WGS profiling of pediatric osteosarcoma

Primary pediatric osteosarcoma samples were collected and profiled using WGS. When possible, germline and tumor samples were collected. For some patients, multiple tumor tissues were collected and sequenced. Some of the samples were used to derive PDTX models, which were also profiled with WGS. Paired end sequencing was performed on Illumina HiSeq instruments and FASTQ files reported.

Dataset EGAD00001004537

MNM - 16S rDNA amplicon dataset of 20 dense timeseries of fecal samples from Belgian women

Fastq files for the 16S rDNA amplicon library of 714 fecal samples of 20 time series (as described in Vandeputte et al. 2021, Nature Communications)

Dataset EGAD00001008275

Whole Exome Sequencing of 15 Human Embryonic Stem Cell Lines

This dataset includes deep coverage (>60x) whole exomes of 15 human embryonic stem cell lines. Genomic DNA was purified and fragmented using the Illumina Nextera system for library preparation and sequenced using 150bp paired-end reads. Sequencing reads were aligned to the hg19 reference genome using the BWA MEM alignment program.

Dataset EGAD00001003446

A study of the molecular pathogenesis of Splenic Marginal Zone and Diffuse Large B-Cell Lymphoma

We will perform exome sequencing on selected cases of splenic marginal zone lymphoma (SMZL) and diffuse large B-cell lymphoma (DLBCL) in order to characterise their genetic makeup and identify biomarkers for prognosis and prediction of treatment response.

Dataset EGAD00001000410

Achilles tendinopathy exome data

Exemplar asymptomatic controls (n=10, 6 males) and exemplar cases with chronic Achilles tendinopathy (n=10, 6 males), representing divergent extremes of the phenotype spectrum were selected for WES. Individual samples were sequenced at paired ends on the Illumina HiSeq 2000/2500 platform at 30X coverage using the Agilent V5+UTR (71Mbp) capture kit.

Dataset EGAD00001004362

Oxford Human Islet whole genome bisulphite data of 10 human pancreatic islet samples

DNA from 10 human pancreatic islet samples was processed for Whole-genome Bisulphite Sequencing. The resulting libraries were sequenced on an Illumina Hiseq 2000 to generate 100bp paired-end read data. The resulting fastq.gz and mapped bam files were deposited.

Dataset EGAD00001003946

H3Africa - Trauma And Neurobiology: Maternal stress and transgenerational impact. Search for Epigenetic Markers

This project aims to characterize the transgenerational genomic impact of genocide exposure and post-traumatic stress disorder (PTSD) in women survivors of the Rwandan genocide and their offspring.

Study EGAS00001006645

Dataset for melanoma-WHOLE_GENOME

Rare cancer sequencing data of 22 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

Dataset EGAD00001008889

Dataset for cancer_of_unknown_primary-EXON

Rare cancer sequencing data of 62 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

Dataset EGAD00001008870

Dataset for synovial_sarcoma-EXON

Rare cancer sequencing data of 34 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

Dataset EGAD00001008898

The immunopeptidome landscape associated with T cell infiltration, inflammation and immune-editing in lung cancer

WES sequencing of multiple regions per tumor from 8 lung cancer patients (LUSC, LCNEC and LUAD) and adjacent healthy lung tissue for each patient.

Dataset EGAD00001008950

Oxford Nanopore Technologies (ONT) long-read sequencing in a paired diagnostic and post- therapy medulloblastoma

Oxford Nanopore Technologies (ONT) long-read sequencing in a paired diagnostic and post- therapy medulloblastoma (2 samples). One sequencing was done on GridION, the other one on a P2 Solo. In both cases the SQK LSK-109 Kit was used for preparation.

Dataset EGAD00001009490

RNA-seq on neuroblastoma PDX model COG-N-519 treated with control miR-1283 and test miR-99b-5p mimics

RNA-sequencing on neuroblastoma PDX model COG-N-519 treated with control miR-1283 and test miR-99b-5p mimics. Three samples from each of the treatment condition were analysed. Next-Seq platform was used for sequencing.

Dataset EGAD00001007754

Exome-sequencing of H3-K27M glioma.

Fastq or bam files are deposited for 28 patient H3-K27M diffuse midline gliomas. UMPEDD65 was profiled by targeted exome-sequencing using the TSO500 Illumina assay, while all other samples were sequenced by whole-exome sequencing.

Dataset EGAD00001009269

Primary_DIPG_expression_profiles

In this study, we used RNA-sequencing gene expression profiling in order to characterize specific phenotypic traits in DIPG. Seventeen primary tumor samples stereotactically biopsied at diagnosis by neurosurgeons in the Necker-Enfants Malades hospital (Paris, France) and snap-frozen for RNA extraction and subsequent poly-A mRNA purification.

Dataset EGAD00001011080

Low-coverage whole-genome sequencing (lcWGS) data of Genome in a Bottle (GIAB) reference samples

This dataset contains low-coverage whole-genome sequencing (lcWGS) data generated from three GIAB reference samples (HG001–HG003) for method benchmarking and concordance analysis in FFPE-GWAS workflows. The data were generated using Illumina NovaSeq with paired-end 150bp reads and downsampled to 2x coverage.

Dataset EGAD00001015533

Novel method for efficient establishment, expansion and drug response profiling of high-grade serous ovarian cancer organoids

HGSOC patient-derived organoids and their tissue of origin

Dataset EGAD00001008753

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