Search Results - EGA European Genome-Phenome Archive

Novel mutational mechanisms and drivers in Pancreatic Neuroendocrine Tumours

Pancreatic neuroendocrine tumours (PanNETs) are increasing in prevalence due to earlier detection, consequently creating challenges in clinical care, as current classification permits unsatisfactory therapeutic stratification. We performed whole genome sequencing of 102 primary PanNETs and defined the genomic events underlying their pathogenesis. We describe the mutational signatures they harbour, including a novel G:C>T:A Base-Excision-Repair-deficiency signature due to MUTYH inactivation. We uncover a larger than expected proportion of germline mutations in clinically sporadic PanNETs. These include previously unreported mutations in DNA repair genes MUTYH, CHEK2, BRCA2, and PALB2, which together with MEN1 and VHL occur in 16% of patients. Somatic mutations (point mutations and structural rearrangements) commonly occurred in genes involved in 4 main pathways: chromatin remodelling, DNA damage repair, activation of mTOR signalling (including novel EWSR1 gene fusions) and telomere maintenance. Aberrations in these mechanisms are associated with subtypes of PanNET with potential clinical application for prognostic and therapeutic stratification.

Study EGAS00001001732

Inactivation of TGFβ receptors in stem cells drives cutaneous squamous cell carcinoma - 30 whole exomes

Melanoma patients treated with oncogenic BRAF inhibitors can develop cutaneous squamous cell carcinoma (cSCC) within weeks of treatment, driven by paradoxical RAS/RAF/MAPK pathway activation. Here, we identify frequent TGFBR1 and TGFBR2 mutations in human vemurafenib-induced skin lesions and in sporadic cSCC. Functional analysis reveals these mutations ablate canonical TGFβ Smad signaling which is localised to bulge stem cells in both normal human and murine skin. MAPK pathway hyperactivation (through BrafV600E or KrasG12D knockin) and TGFβ signaling ablation (through Tgfbr1 deletion) in LGR5+ve stem cells enables rapid cSCC development in the mouse. Mutation of Tp53 (which is commonly mutated in sporadic cSCC) coupled with Tgfbr1 deletion in LGR5+ve cells also results in cSCC development. These findings indicate that LGR5+ve stem cells can act as cells of origin for cSCC and that RAS/RAF/MAPK pathway hyperactivation or Tp53 mutation, coupled with loss of TGFβ signaling, are driving events of skin tumorigenesis.

Study EGAS00001001892

CTCF/cohesin-binding sites are frequently mutated in cancer

Cohesin is present in almost all active enhancer regions, where it is associated with transcription factors. Cohesin frequently colocalizes with CTCF (CCCTC-binding factor), affecting genomic stability, expression and epigenetic homeostasis. Cohesin subunits are mutated in cancer, but CTCF/cohesin-binding sites (CBSs) in DNA have not been examined for mutations. Here we report frequent mutations at CBSs in cancers displaying a mutational signature where mutations in A•T base pairs predominate. Integration of whole-genome sequencing data from 213 colorectal cancer (CRC) samples and chromatin immunoprecipitation sequencing (ChIP-exo) data identified frequent point mutations at CBSs. In contrast, CRCs showing an ultramutator phenotype caused by defects in the exonuclease domain of DNA polymerase ɛ (POLE) displayed significantly fewer mutations at and adjacent to CBSs. Analysis of public data showed that multiple cancer types accumulate CBS mutations. CBSs are a major mutational hotspot in the noncoding cancer genome.

Study EGAS00001003010

Metagenomic Analysis of the Structure and Function of the Human Gut Microbiota in Crohn's Disease

Inflammatory bowel diseases (IBD), such as Crohn's disease, are chronic, immunologically mediated disorders that have severe medical consequences. The current hypothesis is that these diseases are due to an overly aggressive immune response to a subset of commensal enteric bacteria. Studies to date on IBD have suggested that the disorder may be caused by a combination of bacteria and host susceptibility; however the etiologies of these diseases remain an enigma. In this application, we propose to develop and demonstrate the ability to profile Crohn's disease at an unprecedented molecular level by elucidation of specific biomarkers (bacterial strains, genes, or proteins) that correlate to disease symptoms. To achieve this goal, we will employ a multidisciplinary approach based on metagenomic and metaproteomic molecular tools to elucidate the composition of the commensal microbiota in monozygotic twins that are either healthy or exhibit Crohn's disease (for concordant, both are diseased; for discordant, one is healthy and one is diseased). The central hypotheses of this proposal are (1) that specific members and/or functional activities of the gastrointestinal (GI) microbiota differ in patients with Crohn's disease as compared to healthy individuals, and (2) that it will be possible to elucidate microbial signatures which correlate with the occurrence and progression of this disease by integration of data obtained from 16S rRNA-based molecular fingerprinting, metagenomics, and metaproteomics approaches. To address these hypotheses, three specific aims are proposed: 1) Obtain data on community gene content (metagenome) in a subset of healthy twins and twins with Crohn's Disease to assess potential differences in the metabolic capabilities of the gut microbiota associated with CD, 2) Obtain data on community protein content (metaproteome) in a subset of healthy twins and twins with Crohn's Disease to assess the state of expressed proteins associated with CD, 3) Apply various statistical clustering and classification methods to correlate/associate microbial community composition, gene and protein content with patient metadata, including metabolite profiles and clinical phenotype. The ultimate goal of these efforts is to identify novel biomarkers for non-invasive diagnostics of CD and to eventually identify drug targets (i.e. bacterial strains) for cure or suppression of disease symptoms. PUBLIC HEALTH RELEVANCE: This study aims to unravel the contribution of the bacteria that normally inhabit the human gastrointestinal tract to Crohn's disease by using a multidisciplinary approach to study changes in the structure and function of gut microbial communities in three sets of patient cohorts who have Crohn's disease. These results will be compared with those obtained from the study of healthy individuals and have the potential to identify new biomarkers of disease severity, location, and progression.

Study phs000257

Cryptococcosis in Previously Healthy Adults

Cryptococcus is a fungus that causes infections most commonly in immunocompromised patients, such as those with AIDS and solid organ transplant recipients and is currently responsible for an estimated 15% of all AIDS-related deaths globally. However, in developed countries, approximately one-third of cases fall outside these groups such that cryptococcal meningoencephalitis (CM) has become the most common cause of non-viral meningitis in the U.S. Within the U.S., approximately 15-20% have no readily identifiable immune defect and cryptococcal infection in these hosts has a mortality rate of 30-50% despite optimal antifungal therapy. NIH Clinical Study Protocol 93-I-0106 (NCT00001352). The objectives of this protocol can be broadly categorized as: 1) Characterize the immunologic and genetic mechanisms predisposing to disease acquisition; 2) Understand the post-infectious inflammatory response and distinguish its consequences from those directly due to fungal growth; and 3) Management of post-infectious neuro-inflammatory syndromes associated with cryptococcal meningitis (CM). This protocol recruits patients who have microbiological evidence of cryptococcal neurologic or non-CNS disease (typically pulmonary or bone). Cerebrospinal fluid (CSF) and blood samples collected during clinical care are used to measure serum and CNS cellular and soluble cytokines as well as to perform in-situ immunohistochemistry. CSF and blood samples are also collected to measure transcriptional (gene expression), proteomic (protein), and lipidomic (lipids) changes that occur throughout disease and treatment. Observational data detailing audiological, ophthalmological and neurocognitive deficits in these patients is also recorded. We have recently described a post-infectious inflammatory syndrome (PIIRS) associated with cryptococcal meningoencephalitis (CM) which can be best described as a neuro-inflammatory state during which CM patients present with altered mental status (Montreal Cognitive Assessment Score As part of the protocol, we treat patients for either microbiological failure or neuroinflammatory sequelae by conventional therapies utilizing FDA-approved pharmaceuticals at FDA-approved doses. To understand and identify the predominant biological pathways responsible for PIIRS neuroinflammation, we examined patient CSF at baseline (at time of PIIRS diagnosis) and post-treatment with different FDA-approved pharmaceuticals at FDA-approved doses compared to CSF from non-PIIRS donors. Upstream pathway analysis of differentially expressed genes in the CSF of PIIRS patients revealed a prominent role for the JAK/STAT pathway in the pathogenesis of PIIRS and support the use of the JAK inhibitor, ruxolinib, as a pathway-instructed therapy to treat PIIRS patients. Data available through dbGaP: single cell RNA sequencing (scRNA-seq) data from CSF cells of a patient with PIIRS at the time of diagnosis and following treatment with steroids (1g solumedrol/day) and NanoString transcriptional data from CSF cells of patients with PIIRS at the time of diagnosis compared to CSF cells from non-PIIRS donors.

Study phs003871

Exceptional Outcomes in a Phase Ib Study Combining PARP and MEK Inhibition, With or Without Anti-PD-L1, for BRCA-Wildtype Platinum-Sensitive Recurrent Ovarian Cancer

To evaluate regimens combining PARP and MEK inhibition, with or without PD-L1 inhibition, for BRCA-wildtype platinum-sensitive recurrent ovarian cancer (PSROC).

Study EGAS00001007496

PDAC Phenotype and Germline Genotype Data Access Committee

This Data Access Committee (DAC) is responsible for reviewing and approving requests for access to controlled phenotype metadata and derived germline FUT2/FUT3 genotype data from patients with pancreatic ductal adenocarcinoma (PDAC). Access is granted to bona fide researchers for non-commercial research purposes only, subject to approval by the DAC and in accordance with the original informed consent and applicable ethical regulations.

Dac EGAC50000000893

Learning from the thymic human cell atlas for T cell engineering: Paediatric RNA (2025-10-02)

T cells are central to adaptive immunity and thus crucial for understanding and treating human disease. While extensively studied in model organisms, translating this knowledge to humans can sometimes be limited by their rapid cross-species evolution and diverse . This dataset contains all the data available for this study on 2026-03-10.

Dataset EGAD00001015720

RNA Splicing Dysregulation in the Pathogenesis of Chronic Lymphocytic Leukemia

RNA splicing dysregulation is a hallmark of cancers, promoting the onset and progression of disease. In chronic lymphocytic leukemia (CLL), spliceosome mutations leading to aberrant splicing occurs in approximately 20% of patients. However, the underlying mechanism for splicing defects in spliceosome unmutated CLL cases remains elusive. To discover posttranscriptional regulation of RNA splicing, we performed RNA sequencing using RNA derived from B cells from 6 healthy donors and 36 CLL patients, along with MAZTER sequencing from 9 CLL patients (8 matched with RNA sequencing cohort) and B cells from 5 healthy donors. We found that CLL cells have dysregulated m6A modification sites on transcripts from splicing factors, suggesting a critical role of m6A modification in RNA splicing dysregulation.

Study phs003191

Genetic Association Studies in the Solomon Islanders

The goal of this study was to determine the genetics underlying blond hair in the Solomon Islands, which has the highest prevalence of blondism outside of Europe. Participants in the study were of self-reported Solomon Islands ancestry and were 6-36 years of age at enrollment. Individuals with blond (N = 43) and dark hair (N = 42) were selected, approximately matched for age, sex and local geography, and spectrophometric measurements of hair pigmentation were made as a single measurement taken from hair at the crown. Individuals with gray, white, thin, bleached or artificially colored hair were excluded from analysis. All 85 participants were evaluated in a genome-wide scan to detected association to hair pigmentation in the Solomon Islands.

Study phs000493

Assessment of de novo copy number variations in Italian patients with schizophrenia.

We investigated de novo CNVs in the whole genomic DNA of schizophrenia patients and their parents and, specifically, in putative enhancer motifs.Study participants were part of a wider multicenter study, involving an Italian cohort of schizophrenia patients recruited by members of INRP - Italian Network for Research on Psychoses.Whole genomic DNA obtained from 46 family trios of schizophrenia probands was analyzed using the Enhancer Chip, a customized array CGH developed using the Agilent SurePrint G3 8X60K format, which is able to investigate the whole genome with a 300Kb resolution, specific disease loci at a tenfold higher resolution, and that was highly enriched in probes in more than 1.250 enhancer elements selected from the Vista Enhancer Browser (PLoS One. 2012;7(12):e52264).

Study EGAS00001002159

Temporal stability of circulating microRNAs in human serum

Circulating microRNA biomarkers for disease have been subject to extensive research. However, insufficient consideration of variability in the healthy population has led to few markers achieving the performance necessary in independent follow-up studies to be taken forward to clinical practice. To investigate the natural variation of circulating microRNA over time, we performed small RNA sequencing in a longitudinal study of 66 women with no history of cancer, and determined the distribution and dynamics (via intraclass correlation coefficients, ICCs) of the miRNA profile over 3 time points sampled across 2-5 years. We also investigate abundances in circulation, as well as the impact of normalization, age, BMI, and other sample collection factors on microRNA measurements from small RNA sequencing.

Study EGAS00001003221

Reconstruction of the personal information from human genome reads in gut metagenome sequencing data

Human DNA present in fecal samples can result in a small number of human reads in gut shotgun metagenomic sequencing data. However, it is currently unclear how much personal information can be reconstructed from such reads and this has not been quantitatively evaluated. Such a quantitative evaluation is necessary to clarify the ethical concerns related to data sharing and to enable the efficient use of human genetic information in stool samples, such as for research and forensics. Here, we used genomic approaches to reconstruct personal information from fecal metagenomes of 343 Japanese individuals with associated human genotype data. Our approach can be used to quantify the personal information contained within gut metagenome data.

Study EGAS00001007027

National Institute of Mental Health (NIMH) Duke Cognition Cohort

The overall goal is to identify genetic variants influencing normal variation between humans, with a focus on cognitive and neurosensory traits. Because of the focus of funding agencies on disease, very few studies of the genetics of non-disease traits have been performed. The genetic variation underlying the vast majority of differences between humans therefore remains not only undiscovered, but also unexplored. We have assessed >1,200 healthy volunteers for >70 diverse, non-disease phenotypes, with a focus on cognitive and neurosensory traits that are understudied and seem to have a strong biological basis. Our study includes measurements of face recognition, night vision, cognitive performance, auditory pitch discrimination, contagious yawn susceptibility, time perception, sense of direction, taste preferences, personality, sexual behaviors, sleep habits, acne, headache locations, synesthesia, and teeth sensitivity. This method is very different from the focus of most studies on collecting cohorts of patients with disease and controls with minimal phenotypic information. Because we phenotype the same healthy volunteers for multiple highly variable yet heritable traits, we can perform genetic analyses on a large number of phenotypes by just investing once in sequencing the DNA of these participants. An additional >2,000 participants in our cohort have been measured just for cognitive performance instead of for the more extensive phenotyping. Most of the genetic studies in this cohort have been about cognitive perfromance. The number of participants with genetic data generated who have undergone the more extensive phenotyping is limited. Our studies of the more novel traits like contagious yawning have therefore focused more on correlations between different phenotypes until we have a sufficient sample size to truly attempt to make genetic discoveries. . The dataset also includes two small challenge studies. In one study, the cognitive performance of 150 healthy volunteers was measured before and after an acute dose of the antiepileptic drug topiramate. In the other study, the cognitive performance of 13 healthy volunteers was measured before and after 24 hours of sleep deprivation.

Study phs001406

Exceptional Responders Initiative

The Exceptional Responders Initiative is a pilot study to investigate the underlying molecular factors driving exceptional treatment responses of cancer patients to drug therapies. Study researchers will examine molecular profiles of tumors from patients either enrolled in a clinical trial for an investigational drug(s) and who achieved an exceptional response relative to other trial participants, or who achieved an exceptional response to a non-investigational chemotherapy. An exceptional response is defined as achievement of either a complete response or a partial response for at least 6 months duration in a trial or treatment where the overall response rate is < 10%. The hope is to discover underlying molecular features that can be further investigated and may eventually predict benefit from a given drug or class of drugs for a particular patient. This pilot project will successfully characterize approximately 100 cases of tumor tissue and, when available, case-matched germline DNA. All samples will undergo whole exome sequencing, and cases with sufficient nucleic acids will undergo additional analyses (e.g. whole genome sequencing, mRNA-sequencing, mi RNA sequencing, promoter methylation analysis, SNP etc). Each case will be annotated with demographic and clinical information, along with follow-up information minimally sufficient to correlate molecular profiles with response. Both retrospective and prospective collections will be considered. The project will also accept sequencing data and clinical data from patients who have had sequencing performed outside of this project. All data will be de-identified and placed in a controlled access database so other investigators may use them for additional insights. Clinically annotated tissue specimens meeting the criteria will be provided by groups participating in the Exceptional Cases Initiative to a Biospecimen Core Resource (BCR), which will perform quality control on the tissues, and will use a standard operating procedure to isolate nucleic acids. The nucleic acids will be shipped to a sequencing center to perform whole exome sequencing and analysis. These findings will be made available to the broader cancer research community in a controlled access database.

Study phs001145

National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (ARIC)

The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study, the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis. Together, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African-American, Caucasian, Asian, and Hispanic ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000398 contains the Atherosclerosis Risk in Communities (ARIC) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

Study phs000398

Genomic Characterization of Head and Neck Squamous Cell Carcinoma Cell Lines

Head and neck squamous cell carcinoma (HNSCC) is the sixth leading cancer by incidence worldwide(1). Various chemical carcinogens (tobacco, alcohol and betel nut), human papillomavirus (HPV) infection, and genetic predisposition contribute to the etiology of HNSCC, and to the complex genetic alterations in tumor subsets that differ in prognosis and response to therapies (2). Recently, a comprehensive landscape of genomic and transcriptomic alterations in HNSCC tumors has emerged from The Cancer Genome Atlas (TCGA) Network (3). TCGA revealed novel and previously recognized gene and chromosomal region copy number alterations (CNAs), mutations, and expression clusters, and defined their frequency, co-occurrence, and relationship to common and rare subtypes of HPV(-) and (+) tumors that vary in prognosis. To identify cell line models for determining the functional role and therapeutic importance of these alterations, we are performing whole exome and RNA sequencing and bioinformatic analysis of an expanded panel of 15 HPV(-) and 11 HPV(+) HNSCC cell lines and primary oral keratinocytes. We find that the recurrent genomic alterations in cell lines are remarkably consistent with those found in more aggressive tumors, from which cell lines have traditionally been most readily adapted to culture (4). Genome-wide correlation of CN (copy number) with expression identified a suite of potential drivers or modifier genes that differ by HPV status, and are of potential biologic and therapeutic relevance. Further, our findings elucidate and validate genomic alterations underpinning numerous discoveries made with these widely-used and recently derived HNSCC lines, and provide a roadmap for their potential use as models for future studies of tumor subtypes with worse prognosis. References Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin. 2015;65(2):87-108. Van Waes C, Musbahi O. Genomics and advances towards precision medicine for head and neck squamous cell carcinoma. Laryngoscope Investig Otolaryngol. 2017;2(5):310-9. Cancer Genome Atlas N. Comprehensive genomic characterization of head and neck squamous cell carcinomas. Nature. 2015;517(7536):576-82. White JS, Weissfeld JL, Ragin CC, Rossie KM, Martin CL, Shuster M, et al. The influence of clinical and demographic risk factors on the establishment of head and neck squamous cell carcinoma cell lines. Oral Oncol. 2007;43(7):701-12.

Study phs001581

RNA_Seq_in_Patients_with_Primordial_Dwarfism

Transcriptome studies in patients with rare genetic diseases can potentially aid in theinterpretation of likely causal genetic variation through identification of altered transcriptabundance and/or structure. RNA-Seq is the most sensitive assay for both investigatingtranscript structure and abundanceThe primary aim of this pilot project is to investigate to what degree integrating exome-Seqand RNA-Seq data on the same individual can accelerate the identification of causal allelesfor rare genetic diseases. There are two main strands to this: (i) identifying which variantsdiscovered in exome-seq appear to be having a functional impact on transcripts, and (ii)identifying transcript outliers, especially among known causal genes, that may not necessarilyhave a causal variant identified from exome sequencing. The latter may identify the presenceof causal variants that lie far from coding regions (e.g. the formation of cryptic splice sitesdeep within introns, or loss of long range regulatory elements), which can be confirmed withfurther targeted genetic assays. Just over 50% of all disease-causing variants recorded in theHuman Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g.nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs).This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients withprimordial dwarfism syndromes, for 10 of these samples we have previously generate exomedata as part of our collaboration with the group of Prof Andrew Jackson. The two remainingsamples are positive controls where the causal mutation is known, and is known to affecttranscript structure and/or abundance.Primordial dwarfism is a prime candidate for these RNA-seq studies because all knowncausal mutations to date have key roles in DNA replication and thus, unsurprisingly, theproducts of the causal genes are typically ubiquitously expressed.Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) persample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Study EGAS00001000283

Framingham Heart Study-Cohort (FHS-Cohort) - 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. Related Studies Other Framingham data available include: Imaging studies (Framingham Heart Study-Cohort (FHS-Cohort)-Imaging, phs003593), Genetics and genomics (Framingham Cohort, phs000007), Collaborative Cohort of Cohorts for COVID-19 Research (C4R): (Framingham Heart Study, phs002911), and as a component of the Sleep Heart Health Study (SHHS-BioLINCC, phs003637). Available Data Original cohort: data now include examination data from the first 32 clinical exams, selected ancillary data, and event follow-up through 2018. Offspring/Omni1 cohort: Data available include Framingham Offspring examination data from the first 9 clinical exams and selected ancillary data and event follow-up through 2019. Also included are the first 4 exams from the OMNI 1 cohort. Third Generation/Omni2/New Offspring Cohort: Data available include Framingham Generation 3 examination data from the first 3 clinical exams, selected ancillary data and event follow-up through 2019. Also included are the OMNI 2 and New Offspring (NOS) cohorts. A genetic pedigree is not provided for the Framingham phenotype only data. Objectives The objectives of the Framingham Study are to study the incidence and prevalence of cardiovascular disease (CVD) and its risk factors, trends in CVD incidence and its risk factors over time, and familial patterns of CVD and risk factors. Other important objectives include the estimation of incidence rates of disease and description of the natural history of cardiovascular disease, including the sequence of clinical signs and systems that precede the clinically recognizable syndrome and the consequences and course of clinically manifest disease. Background Original cohort: The original cohort of the Framingham Study began in 1948 under the U.S. Public Health Service and was transferred under the direct operations of the new National Heart Institute, NIH, in 1949. Participants were sampled from Framingham, Massachusetts, including both men and women. This was the first prospective study of cardiovascular disease and identified the concept of risk factors and their joint effects. Offspring/Omni1 cohort: With the aging of the Framingham cohort and with interest in familiar aggregation and heritability, a new cohort consisting of the offspring of the original cohort was sampled. Spouses of offspring were also included. This new sample, began enrollment in 1971 and constituted a second generation of participants, permitting new assessment of risk factors and outcomes, and provided a resource for the genetic analyses which were yet to come. The Offspring participants have had repeated examinations, though at typically longer intervals than the original cohort. Third Generation/Omni2/New Offspring Cohort: Thirty-one years after enrollment began for the second generation of the Framingham Heart Study (Framingham Offspring Study), Framingham investigators began enrolling adults with at least one parent enrolled in the Offspring study into the Framingham Generation 3 cohort. The addition of the third generation was expected to facilitate investigation of secular trends in risk factors and indicators of health and disease within families, to enhance statistical power to detect genetic and environmental determinants of complex diseases, and to clarify how subclinical cardiovascular disease predicts occurrence of overt clinical events. Participants Original cohort: At entry to the study in 1948-1952, the study recruited 5,209 men and women, ages 28-62 years, living in Framingham, MA. Offspring/Omni1 cohort: 5,124 men and women, ages 5-70 years at entry consisting of offspring of the original Framingham cohort (and spouses of the offspring). In 1994, the Omni Cohort 1 enrolled 507 men and women of African-American, Hispanic, Asian, Indian, Pacific Islander and Native American origins, who at the time of enrollment were residents of Framingham and the surrounding towns. Third Generation/Omni2/New Offspring Cohort: 4095 men and women, almost all who self reported their ethnicity as white, ages 19+ years at entry, with at least one parent in the Framingham Offspring study, participated in the Gen III cohort. The New Offspring Cohort enrolled spouses of Offspring participants that were not otherwise enrolled and had at least two biological children participating in Gen III. 103 New Offspring Spouses (47 men and 56 women) participated. The OMNI 2 cohort enrolled additional ethnically diverse participants, including many individuals related to the participants of Omni Cohort 1 and also individuals unrelated to Omni Cohort 1 members for a total of 410 new participants. Design The cardiovascular disease conditions under investigation include coronary heart disease (angina pectoris, myocardial infarction, coronary insufficiency and sudden and non-sudden death), stroke, hypertension, peripheral arterial disease and congestive heart failure. Original cohort: The Framingham Study is a longitudinal investigation of constitutional and environmental factors influencing the development of CVD in men and women. Examination of participants has taken place every two years and the cohort has been followed for morbidity and mortality over that time period. Offspring/Omni1 cohort: By 1975, a sample of 5,124 men and women, consisting of offspring of the original Framingham cohort (and spouses of the offspring) had participated in the study. Additional studies of these subjects have continued under research contracts. Third Generation/Omni2/New Offspring Cohort: The children of Offspring Cohort participants were initially identified who would be 20 years of age or older by the end of the enrollment period. A higher priority for recruitment was assigned to individuals who belonged to large extended families, in order to complement phenotypic and genotypic information already obtained from prior generations. The baseline examination was begun in 2002 and completed in 2005.

Study phs003594

California Pacific Medical Center Research Breast Health Cohort

Description of Cohort: The California Pacific Medical Center (CPMC) Breast Health Cohort is a cohort study based at CPMC and is linked to the San Francisco Mammography Registry, one of the sites of the NCI-funded Breast Cancer Screening Consortium (U01CA063740). CPMC is a community hospital in San Francisco, which has one of the highest volumes for mammography in San Francisco. Between September 2004 and June 2007, >90,000 mammograms were performed at CPMC. The CPMC breast health cohort collects demographic and risk factor data on women receiving mammography through participation in the San Francisco Mammography Registry, as part of the Breast Cancer Screening Consortium (U01CA063740). The SFMR database collects information from all sources, including a questionnaire on demographic and risk factor information, the clinical results of the breast examination, the measures of breast density by Dr. John Shepherd and the women who agreed to donate a blood sample. By merging these various sources of information we have very efficiently developed a large sample of women who have donated blood and have had a measure of mamographic density. Blood Collection: Dr. Steve Cummings is leading an effort to collect and archive blood samples from women who are receiving mammography screening. All women who are sent for a screening mammogram at CPMC are considered eligible. Since the cohort began collecting blood samples in July 2004 until June 2007, samples have been collected from over 11,000 women. Measurement of Breast Density: Dr. John Shepherd is currently measuring breast density in a large fraction of the cohort using an automated approach with single X-ray absorptiometry. Dr. Shepherd has established a link with the CPMC mammography center that allows him to collect routine digital mammography information. Using the data from the mammogram, Dr. Shepherd and his group have developed the single X-ray absorptiometry (SXA) technique for measuring density which is described in more detail below. The table demonstrates the distribution of demographic variables and some breast cancer risk factors of women who donated blood and had a breast density measurement in the CPMC breast health cohort. Nearly 80% of the participants are Caucasian and most of the women are post-menopausal with a median age of ~52. Since it will be difficult to accrue a large enough sample from each ethnic group, our study will focus only on Caucasian women. Table: Demographic variables, reproductive history and family history of breast cancer among 2962 women participating in the CPMC cohort study who contributed blood samples between 1994-1997. Variable Median/Percentage Age (Median/IQR) 52 (46-59) Ethnicity Caucasian/White 0.76 Asian/Pacific Islander 0.141 Hispanic 0.029 Mixed Race/Ethnicity 0.039 African American/Black 0.022 American Indian 0.001 Other 0.009 First degree relative with breast cancer 0.17 Age at first birth Nulliparous 0.39 Age<20 0.043 Age>40 0.032 Age<30, ≥20 0.251 Age>30, ≤40 0.282 Measurement of Breast Density in Cohort: Measurement of breast density is accomplished using an automated technique for all mammograms obtained by Dr. Shepherd using Single X-Ray absorptiometry (SXA). SXA measurement of breast density is done on approximately 30% of all screening mammograms. Below we describe the method for measurement of breast density by SXA by Dr. Shepherd's group and its validation and association with breast cancer. As we demonstrate below, breast density, as measured by SXA, is an automated, highly reproducible measure of the density of breast tissue and is associated with breast cancer risk. SXA for Quantifying Breast Density: Single x-ray absorptiometry (SXA) was initially developed for measuring bone density. SXA can determine the fraction of each of two densities simultaneously using the fact the sample is a constant thickness, the thickness in known, and the total attenuation is known. In applying this technique to breast density, we assume a two compartment model: fat and non-fatty (fibroglandular tissue). We use a reference material composed of various concentrations of two materials: one which is the same density as fat and another which is the same density as fibroglandular tissue. The reference material (phantom) is placed in the X-ray field with each mammogram. We have been able to implement this in a way that is unintrusive to the patient and technologist at CPMC. Assuming this two-compartment model and a constant known breast thickness, we can then calculate the percent density at any region of the breast based on the assumption that % pixel grey-scale is proportion to the mass fractions of breast fat and lean tissue. If reference materials (a phantom) of fat and fibroglandular tissue are imaged with the patient's breast and the reference materials have the same thickness as the patient's breast, then the breast's grey-scale values can be converted to fat/fibroglandular mass fractions by interpolating between those two references. The total percent density is found by averaging the volume fraction over all breast pixels. The phantom being used for breast density assessment at CPMC began to be used in September 2004. The phantom does not have to be manipulated by the technologist and stays attached on the mammography device during standard craniocaudal (CC) views. Thus it creates minimal to no interference with the clinical mammogram. Reproducibility of breast density measures: Traditional measures of mammographic density require some human interpretation. A human reader outlines the area perceived to be dense and a computer then calculates the percent area outlined as a percent of the entire image. Thus, while traditional mammographic density is associated with breast cancer risk, it has some limitations. In a study by Drs. Shepherd, Kerlikowske, et al., the correlation coefficient (Pearson's R) between different readers was 0.8-0.9. In contrast to the traditional mammographic density measurement, the SXA measurement is fully automated and, therefore, the reproducibility of the measurement is higher. Dr. Shepherd and colleagues have performed a replication study of SXA as a measurement of breast density. They have estimated the correlation coefficient of the SXA measurement of breast density to be >0.98. Thus, as expected for an automated measure, SXA is a highly reproducible measure of mammographic breast density. Drs. Shepherd and Kerlikowske have recently analyzed the association between breast cancer risk and breast density as measured by SXA (Shepherd et al., Cancer Epi Biomarkers and Prev, 2011, PMID: 21610220). They found that women in the highest quintile of % volumetric density had an odds ratio of 4.1 (95% CI: 2.3 - 7.2) for breast cancer risk compared to women in the lowest quintile of volumetric density. Thus volumetric density appears to be a highly reproducible, automated measure of breast cancer.

Study phs000395

CINECA_synthetic_cohort_EUROPE_UK1 referencing fake samples

Please note: This synthetic data set (with cohort “participants” / ”subjects” marked with FAKE) has no identifiable data and cannot be used to make any inference about cohort data or results. The purpose of this dataset is to aid development of technical implementations for cohort data discovery, harmonization, access, and federated analysis. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure this preamble is included with this dataset and that the CINECA project (funding: EC H2020 grant 825775) is acknowledged. For any questions please contact isuru@ebi.ac.uk or cthomas@ebi.ac.uk This dataset (CINECA_synthetic_cohort_EUROPE_UK1) consists of 2521 samples which have genetic data based on 1000 Genomes data (https://www.nature.com/articles/nature15393), and synthetic subject attributes and phenotypic data derived from UKBiobank (https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001779). These data were initially derived using the TOFU tool (https://github.com/spiros/tofu), which generates randomly generated values based on the UKBiobank data dictionary. Categorical values were randomly generated based on the data dictionary, continuous variables generated based on the distribution of values reported by the UK Biobank showcase, and date / time values were random. Additionally we split the phenotypes and attributes into 4 main classes - general, cancer, diabetes mellitus, and cardiac. We assigned the general attributes to all the samples, and the cardiac / diabetes mellitus / cancer attributes to a proportion of the total samples. Once the initial set of phenotypes and attributes were generated, the data data was checked for consistency and where possible dependent attributes were calculated from the independent variables generated by TOFU. For example, BMI was calculated from height and weight data, and age at death generated by date of death and date of birth. These data were then loaded to the development instance of Biosamples (https://www.ebi.ac.uk/biosamples/) which accessioned each of the samples. The genetic data are derived from the 1000 Genomes Phase 3 release (https://www.internationalgenome.org/category/phase-3/). The genotype data consists of a single joint call vcf files with call genotypes for all 2504 samples, plus bed, bim, fam, and nosex files generated via plink for these samples and genotypes. The genotype data has had a variety of errors introduced to mimic real data and as a test for quality control pipelines. These include gender mismatches, ethnic background mislabelling and low call rates for a randomly chosen subset of sample data as well as deviations from Hardy Weinberg equilibrium and low call rates for a random selection of variants. Additionally 40 samples have raw genetic data available in the form of both bam and cram files, including unmapped data. The gender of the samples in the 1000 genomes data has been matched to the synthetic phenotypic data generated for these samples. The genetic data was then linked to the synthetic data in BioSamples, and submitted to EGA.

Dataset EGAD00001006673

Genetics of Hypertension Associated Treatment (GenHAT) Study, Genomic Background of Blood Pressure Response to Treatment in African Americans

The GenHAT study is an ancillary pharmacogenomics study to the Antihypertensive and Lipid Lowering Treatment to Prevent Heart Attack Trial (ALLHAT). ALLHAT was a randomized, double-blind, multi-center trial that enrolled 42,418 participants ≥55 years of age with hypertension and at least one additional risk factor for cardiovascular disease (CVD). Participants were randomized to treatment with one of four primary antihypertensive drugs: chlorthalidone (thiazide-like diuretic), amlodipine (CCB), lisinopril (ACE-i), or doxazosin (alpha-adrenergic blocker) in a ratio of 1.7:1:1:1, respectively. Participants were followed for treatment response and CVD outcomes. The original GenHAT study (N=39,114) evaluated the association of candidate hypertensive genetic variants with CVD outcomes for participants consenting to genetic research. The current GWAS study focuses on a subset of African American GenHAT participants (n=6908).  

Study phs002716

NHLBI TOPMed - NHGRI CCDG: Genes-Environments and Admixture in Latino Asthmatics (GALA II)

This is a case-only pharmacogenetic study of bronchodilator drug response among racially admixed Latino children with asthma. Each participant had two spirometry measurements using the KoKo PFT System. With the first spirometry test, participant was administered with 4 puffs of HFA Albuterol. The second albuterol measurement was based on age, for participants under 16 years of age, additional 2 puffs were administered and for those over 16 years of age, additional 4 puffs were administered. The overall goal is to identify genetic factors which are predictive of drug response in children with asthma. The principal tools include a questionnaire and biological specimen collection. Participants are 8-21 years old at time of recruitment. Children with asthma have physician-diagnosed asthma, symptoms and medications. Comprehensive phenotypic data for GALAII study participants are available through dbGaP phs001180.

Study phs000920

African American Adolescent Idiopathic Scoliosis Whole Genome and Whole Exome Study

Adolescent idiopathic scoliosis (AIS) is the most common pediatric spinal deformity. The causes of scoliosis are only now being discovered yet are important for predicting outcome and need for surgery. Prior studies have investigated the causes of scoliosis, including common and rare variant risk factors, but have mostly used populations consisting of Asian or European ancestry. It is essential that we determine what the risk factors are in all populations so that we can delivery equitable care to all individuals.

Study phs003136

CCG Multicentric Italian Lung Detection (MILD)

For the CCG-MILD project, NCI will utilize whole genome sequencing and/or whole exome sequencing in conjunction with transcriptome sequencing to try to identify recurrent genetic alterations (mutations, deletions, amplifications, rearrangements) and/or gene expression signatures that would be important to the hypothesis(es) submitted by the investigators. The samples will be processed and submitted for genomic characterization using the established NCI Genome Characterization Pipeline. Subsequent genomic and clinical data will be hosted at the NCI Genomic Data Commons (GDC).

Study phs002253

Tumor-associated neutrophil 1 precursors impair homologous DNA repair and promote sensitivity to PARP-inhibition

Tumor evolution is one of the major mechanisms responsible for acquiring therapy resistant and more aggressive cancer clones. Whether the tumor microenvironment through immune-mediated mechanisms might promote the development of more aggressive cancer types is crucial for the identification of additional therapeutical opportunities. Here, we identify a subset of tumor-associated neutrophils, defined as tumor-associated neutrophil precursors (PreNeu). These PreNeu are enriched in highly proliferative hormone-dependent breast cancers and impair DNA repair capacity

Study EGAS00001008154

Jeju Genome Project

The Jeju Genome Project (JGP) is a multi-omics resource for precision medicine in a geographically distinct South Korean population. It comprises 5,309 participants (3,001 community-based; 2,308 hospital-based) with data spanning Whole-Genome Sequencing (WGS) and genotyping arrays. The hospital cohort is specifically enriched for neurological and rheumatic diseases and malignancies. By providing a population-specific reference panel, JGP enables high-resolution genetic architecture analysis, risk stratification, and the discovery of rare variants relevant to Jeju and broader East Asian populations.

Study EGAS50000001706

Emirati Diploid Single Samples Assemblies

This study, as part of the Emirati Genome Project, aims to establish a foundational pangenome reference to advance precision medicine in the United Arab Emirates. We are generating single-sample diploid whole genome assemblies for 30 Emirati nationals using deep PacBio HiFi sequencing. This process yielded 60 distinct assemblies representing both the maternal and paternal genomes for each individual. The resulting high-quality reference will capture the unique genetic landscape of the Emirati population, thereby accelerating translational research and genomic discovery.

Study EGAS50000001233

ENU_LS_411N_TripleTherapy

BRAF V600E colorectal cancers do not respond to the only currently FDA approved targeted therapy for CRC. There is currently a trial underway in the UK recruiting V600E CRC patients for treatment with a triple therapy combination of Cetuximab, Trametinib and Dabrafenib. We have mutagenized a pool of V600E CRC cell lines and treated with this triple therapy to select out drug resistant clones. We will now sequence these drug resistant clones with the aim of identifying common point mutations engendering resistance to this new therapy.

Study EGAS00001001777

Characterization of MCSP+ melanoma DCC and MelDCC lines

To dissect the sequence of genotypic and phenotypic progression during early metastatic colonization, we searched for the earliest detectable disseminated cancer cells (DCC) and identified MCSP+ melanoma cells as strong candidates for metastasis founder cells (MFC) in lymph nodes. We isolated MCSP+ DCC from various stages of metastatic colony-formation, performed scRNA-seq and unravelled their phenotypic progression. Further we performed bulk sequencing on patient-derived DCC models (MelDCC) and showed that they exhibit an immunosuppressive activity on CD8 T cells.

Study EGAS00001006702

Zimbabwe Mendelian Disorders Genomics DAC

Data Access Committee responsible for reviewing and approving access requests to human genomic data generated from individuals with suspected Mendelian disorders. The DAC ensures ethical use of genomic data in accordance with institutional, national, and international guidelines, protecting participant privacy while enabling responsible data sharing for research purposes.

Dac EGAC50000000963

miRNA

miRNA Sequencing of olfactory mucosa (OM) cells derived from cognitively healthy and individuals with AD exposed to traffic-related ultrafine particles (UFPs) for 72h in submerged cultures. The UFPs used for exposures were: A0 and A20. Exposures were compared to the corresponding blank samples.

Dataset EGAD50000001532

Dataset for "HPV integration induces gene fusions" (pacBio)

pacBio whole-genome sequencing data for "HPV integration induces gene fusions" We performed long read whole-genome sequencing on four HPV+ head and neck cancer samples using pacBio HiFi. The sequence reads were submitted in fastq format.

Dataset EGAD50000001304

Exome sequencing of patients with acute promyelocytic leukemia

The dataset consists in 64 fastq files from 23 patients with acute promyelocytic leukemia. Exome sequencing was conducted on several stages (Diagnosis, Remission, Relapse) for each patient. For 5 patients, only Diagnosis and Relapse samples are available.

Dataset EGAD00001004043

RNAseq files for Mullighan_GL_reALL RNASEQ2

RNAseq files for Mullighan_GL_reALL RNASEQ2 paper titled "Mutational landscape and patterns of clonal evolution in relapsed pediatric acute lymphoblastic leukemia"

Dataset EGAD00001005510

RNASeq files for Mullighan_GL_reALL RNASEQ1

RNASeq files for Mullighan_GL_reALL RNASEQ1 paper titled "Mutational landscape and patterns of clonal evolution in relapsed pediatric acute lymphoblastic leukemia"

Dataset EGAD00001005511

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

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

Dataset EGAD00001006438

Data for the genome‐wide association study of cutaneous leishmaniasis in Brazil

DNAs were genotyped on Illumina Infinium HumanCoreExome Beadchips (Illumina Inc., San Diego, CA, USA) with probes for 551,004 single nucleotide variants (SNVs): 282,373 informative across ancestries; 268,631 exome-focused. Human genome build 37 (hg19) was used.

Dataset EGAD00001006681

CUTRUN files for Klco-NUP98 data

CUTRUN files for paper titled "Fusion oncoproteins and cooperating mutations define disease phenotypes in NUP98-rearranged leukemia"

Dataset EGAD00001015478

Profiling Chromatin Accessibility in Humans Using Adenine Methylation and Long-Read Sequencing

This dataset includes raw nanopore, base-called, and 6mA frequency data for EcoGII-treated NA12878 and MCF7 chromatin samples. It also includes raw nanopore data for the HG002 EcoGII-treated DNA.

Dataset EGAD00001015374

The data access committee for Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer

Dac EGAC00001001331

Data Access Commitee for study Fine-Scale Genomic Analyses Of Admixed Individuals Reveal Unrecognized Genetic Ancestry Components In Argentina

Dac EGAC00001001634

Access to aligned sequencing data for study "Loss of SNAI2 in prostate cancer correlates with clinical response to androgen deprivation therapy".

Dac EGAC00001001809

CDK4 phosphorylation status and rational use for combining CDK4/6 and BRAF/MEK inhibition in advanced thyroid carcinomas

Study EGAS00001007577

DAC for "CUT&RUN-sequencing identifies PTK7 as a direct Wnt target in patient-derived colorectal cancer organoids"

Dac EGAC00001003592

ICGC PedBrain: Deep-sequencing of childhood brain tumors.

Brain tumors constitute the childhood tumors with the highest mortality rates and survival is often associated with severe long-term sequelae due to intensive multimodal treatment regimens. Thus, the PedBrainTumor network aims at the identification of robust biomarkers for clinical management and novel molecular targets for therapeutic interventions. Using massively parallel whole-genome sequencing, and transcriptome and methylome sequencing for subsets of cases, we aim to decipher the molecular causes of medulloblastoma as well as low-grade astrocytoma, and to identify markers to stratify patients for specialized treatment. As the PedBrain network is affiliated with clinical trials in medulloblastoma and pilocytic astrocytoma, validation cohorts for the translation of key findings into clinical settings are readily available.

Study EGAS00001000215

TRACERx: TRAcking non-small cell lung Cancer Evolution through therapy (Rx). Pilot Study. Multi-region sequencing of early-stage NSCLCs.

Deciphering the complexity of non-small cell lung cancer (NSCLC) evolutionary histories may elucidate the basis for its dismal outcome. We performed multi-region sequencing of early-stage NSCLCs. Spatial dissection revealed branched tumor evolution, with driver mutations occurring before and after subclonal diversification. Intra-tumor heterogeneity in DNA copy number alterations, translocations and endogenous APOBEC mutational processes demonstrates that NSCLC may follow multiple distinct evolutionary trajectories simultaneously. In smokers, despite maintained carcinogen exposure, temporal dissection reveals a relative decrease in smoking-related mutations during tumor progression, accompanied by an increase in APOBEC-related mutations. In the tumors from ex-smokers, genome-doubling occurred before subclonal diversification, suggesting prolonged latency before clinical detection. Multi-region sequencing demonstrates the relentless and heterogeneous nature of genomic instability processes in early-stage NSCLCs.

Study EGAS00001000809

Combination_therapies_for_personalized_cancer_medicine

It is the ambition of the team formed by members of the Netherlands Cancer Institute (NKI) and the Cancer Genome Project at the Wellcome Trust Sanger Institute (WTSI) to unravel the genomic and phenotypic complexity of human cancers in order to identify optimal drug combinations for personalized cancer therapy. Our integrated approach will entail (i) deep sequencing of human tumours and cognate mouse tumours; (ii) drug screens in a 1000+ fully characterized tumour cell line panel; (iii) high-throughput in vitro and in vivo shRNA and cDNA drug resistance and enhancement screens; (iv) computational analysis of the acquired data, leading to significant response predictions; (v) rigorous validation of these predictions in genetically engineered mouse models and patient-derived xenografts. This integrated effort is expected to yield a number of combination therapies and companion-diagnostics biomarkers that will be further explored in our existing clinical trial networks.

Study EGAS00001000655

BLUEPRINT DNase accessibility of Epigenetic programming during monocyte to macrophage differentiation and trained innate immunity

Monocyte differentiation into macrophages represents a cornerstone process for host defense. Concomitantly, immunological imprinting of either tolerance or trained immunity determines the functional fate of macrophages and susceptibility to secondary infections. Transcriptomes and epigenomes in four primary cell types: monocytes, in vitro differentiated naïve, tolerized and trained macrophages were characterized. Inflammatory and metabolic pathways were modulated in macrophages, including decreased inflammasome activation, and pathways functionally implicated in trained immunity were identified. Strikingly, β-glucan training elicits an exclusive epigenetic signature, revealing a complex network of enhancers and promoters. Analysis of transcription factor motifs in DNase I hypersensitive sites at cell-type specific epigenetic loci unveiled differentiation and treatment specific repertoires. Altogether, this study provides a resource to understand the epigenetic changes that underlie innate immunity in humans.

Study EGAS00001000954

BLUEPRINT RNA-seq of Epigenetic programming during monocyte to macrophage differentiation and trained innate immunity

Monocyte differentiation into macrophages represents a cornerstone process for host defense. Concomitantly, immunological imprinting of either tolerance or trained immunity determines the functional fate of macrophages and susceptibility to secondary infections. Transcriptomes and epigenomes in four primary cell types: monocytes, in vitro differentiated naïve, tolerized and trained macrophages were characterized. Inflammatory and metabolic pathways were modulated in macrophages, including decreased inflammasome activation, and pathways functionally implicated in trained immunity were identified. Strikingly, β-glucan training elicits an exclusive epigenetic signature, revealing a complex network of enhancers and promoters. Analysis of transcription factor motifs in DNase I hypersensitive sites at cell-type specific epigenetic loci unveiled differentiation and treatment specific repertoires. Altogether, this study provides a resource to understand the epigenetic changes that underlie innate immunity in humans.

Study EGAS00001000953

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