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• DNA Methylomic Profiling of Preeclampsia Across Pregnancy

  Preeclampsia (PE) is a hypertensive, multi-system disorder of pregnancy that significantly impacts maternal and infant morbidity/mortality across the globe, as it increases risk of cardiovascular disease and remains a leading killer of women and babies. Despite PE's significant impact on morbidity/mortality, there are no clinically reliable biomarkers that predict PE. DNA methylation, a dynamic regulator of gene expression, represents a mechanism that is known to be impacted by the environment. Because PE stems from a dysfunctional placenta that releases debris into the maternal circulation, we hypothesized that the in-vivo environment created by the dysfunctional placenta will impact DNA methylation in the maternal circulation, and that these blood-based methylation profiles would serve as a systemic biomarker of the maternal response to placental dysfunction. Our overall objective of this pilot study was to longitudinally characterize DNA methylation profiles across the three trimesters of pregnancy in the maternal blood at time points before and after clinically overt PE using a targeted (endoglin and endoglin-related genes) and a discovery-based approach. For this pilot study, 28 normotensive control participants and 28 PE case participants enrolled in the NICHD funded pregnancy study entitled Prenatal Exposures and Preeclampsia Prevention: Mechanisms of Preeclampsia and the Impact of Obesity (PEPP3; P01HD30367) were 1:1 frequency matched on self-reported race, pre-pregnancy BMI, smoking history, and gestational age at sample collection. Methylation data were collected with the Infinium® MethylationEPIC Beadchip. Methylation assay data collection were carried out at Johns Hopkins University Genetic Resources Core Facility, The SNP Center, Baltimore, MD, USA.

  Study phs001937

• Longitudinal profiling of the immune response to Plasmodium vivax in naive hosts by RNA-sequencing

  Plasmodium vivax offers unique challenges for control and elimination, and may prove a tougher hurdle to overcome than Plasmodium falciparum. And yet compared to P. falciparum we know very little about the innate and adaptive immune responses that need to be harnessed to reduce disease and transmission. We recently generated a blood bank of a new clonal field isolate of P. vivax (PvW1) for human challenge studies and used systems immunology tools to track the host response throughout infection and convalescence. As part of this study, RNA-sequencing was used to resolve changes in whole blood gene expression through time in 6 volunteers (7-9 time-points per volunteer). In summary, these data show that P. vivax induces two distinct transcriptional programmes in whole blood during and after infection. During infection, transcriptional profiling reveals the rapid mobilisation of an emergency myeloid response, which leads to systemic inflammation and the recruitment of all major T cell subsets into lymphoid tissues. Six days after infection, this innate response subsides and a transcriptional signature of proliferation is revealed. This most likely represents widespread activation of lymphocytes, which return to the circulation after parasite clearance - transcriptional profiling of T cells at this time-point could therefore reveal the outcomes of critical cell-cell interactions that take place within the spleen during infection. 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/ .

  Dataset EGAD00001006924

• minION fastq files of 10 different tumor samples from the Master program (H021)

  Nanopore RNA Sequencing was done for 10 tumor samples. Direct cDNA sequencing was performed using the SQK-DCS109 kit (Oxford Nanopore Technologies). For analysis of a single sample on a MinION flow cell (version R9.4.1), 5 μg RNA was used as input. For multiplexing on a MinION flow cell, 2.5 μg RNA per sample was used as input, and the native barcoding expansion kit EXP-NBD104 was employed in conjunction with SQK-DCS109. After reverse transcription with Maxima H Minus Reverse Transcriptase (Thermo Scientific), second-strand synthesis was performed using the 2x LongAmp Taq Master Mix (New England Biolabs). The resulting double-stranded cDNA was subjected to end-repair and dA-tailing using the NEBNext Ultra End Repair/dA-Tailing Module (New England Biolabs). For multiplexed libraries, this step was followed by barcode ligation and library pooling. Next, libraries were quantified with a Qubit Fluorometer 3.0 (Life Technologies). Finally, sequencing adapters were added to the library preparations and ligated with Blunt/TA Ligase Master Mix (New England Biolabs), followed by further quality control using a Qubit. Samples ACC1 and ACC2 were analyzed on individual MinION flow cells, while the remaining eight samples were sequenced as multiplexed libraries on two MinION flow cells by pooling four samples for each run. Five ACC samples were also analyzed individually on Flongle flow cells

  Dataset EGAD00001008970

• Intergenerational Impact of Genetic and Psychological Factors on Blood Pressure (InterGEN Study)

  This research study focuses on the genomic and psychological environmental effects on blood pressure among mothers and their children. The study includes 250 mothers who self-identify as AA/black, and 250 children between the ages of 3 and 5 years old at the time of enrollment. The study is longitudinal and data collection interviews are scheduled every six months for two years after enrollment, for a total of four participant interviews. Assessment is as follows: genetic (time 1 only) and psychological factors (every six months for two years).

  Study phs001792

• Alcohol Dependence: Sequencing from Multiplex Families

  Two multiplex for alcohol dependence family studies were initiated based on the gender of a pair of probands. Ascertainment of a pair of AD probands was used to increase the density of alcohol dependence within the family. Identification of male (Cognitive and Personality Factors in Relatives of Alcoholics Family Study) and female (Biological Risk Factors in Female Alcoholics Family Study) alcohol dependent probands was accomplished by identifying an alcohol dependent proband while in treatment in a substance abuse treatment facility in Pittsburgh and surrounding communities who provided contact information for a sibling whom he/she thought might be interested in participating. The studies had identical ascertainment requirements. DNA was banked for all willing participants.

  Study phs001775

• Natural Killer Cell Therapies for Hematologic Malignancies

  The "Natural Killer Cell Therapies for Hematologic Malignancies" study is an umbrella repository for data pertaining to multiple related clinical trials that aim to assess NK cell therapies as part of treatment strategies for a range of hematologic malignancies. Here, data from two trials, NCT03068819 and NCT02782546, are presented.Cytokine Induced Memory-like NK Cell Adoptive Therapy for Relapsed AML after Allogeneic Hematopoietic Cell Transplant in Children and Adults (NCT03068819)Pediatric and young adult (YA) patients with acute myeloid leukemia (AML) who relapse after allogeneic hematopoietic cell transplantation (HCT) have extremely poor prognosis. Standard salvage chemotherapy and donor lymphocyte infusions (DLI) have little curative potential. Previous studies showed that natural killer (NK) cells can be stimulated ex vivo with interleukin-12 (IL-12), IL-15, and IL-18 to generate memory-like (ML) NK cells with enhanced anti-leukemia responses. We treated nine pediatric/YA patients with post-HCT relapsed AML with donor ML NK cells on a phase I trial. Patients received fludarabine, cytarabine, and filgrastim followed two weeks later by infusion of DLI and ML NK cells from the original HCT donor. ML NK cells were successfully generated from haploidentical, matched-related and matched-unrelated donors. Following infusion, donor-derived ML NK cells expanded and maintained ML multidimensional mass cytometry phenotype for over 3 months. Furthermore, ML NK cells exhibited persistent functional responses as evidenced by leukemia-triggered IFN-gamma production. Following DLI and ML NK cell adoptive transfer, 4 of 8 evaluable patients achieved complete remission at day 28. Two patients maintained a durable remission for over 3 months with one patient in remission for greater than two years. No significant toxicity was experienced. This study demonstrates that in a compatible immune environment post-HCT, donor ML NK cells robustly expand and persist with potent anti-leukemic activity in the absence of exogenous cytokines. ML NK cells in combination with DLI present a novel immunotherapy platform for AML that has relapsed after allogeneic HCT. This trial was registered at https://www.clinicaltrials.gov/study/NCT03068819.A Phase II Study of Cytokine Induced Memory-like NK Cell Adoptive Therapy after Haploidentical Donor Hematopoietic Cell Transplantation (NCT02782546)Natural killer (NK) cells are innate lymphoid cells that eliminate cancer cells, produce cytokines, and are being investigated as a nascent cellular immunotherapy. Impaired NK cell function, expansion, and persistence remain key challenges for optimal clinical translation. One promising strategy to overcome these challenges is cytokine-induced memory-like (ML) differentiation, whereby NK cells acquire enhanced anti-tumor function following stimulation with IL-12, IL-15, and IL-18. Here, reduced-intensity conditioning (RIC) for HLA-haploidentical hematopoietic cell transplantation (HCT) was augmented with same-donor ML NK cells on Day 7 and 3 weeks of N-803 (IL-15 superagonist) to treat patients with relapsed/refractory acute myeloid leukemia (AML) in the clinical trial (NCT02782546). In 15 patients, donor ML NK cells were well-tolerated and 87% of patients achieved a composite complete response at Day 28, which corresponded with clearing high-risk mutations, including TP53 variants. NK cells were the major blood lymphocytes for two months post-HCT with prolific expansion (1104-fold) over 1-2 weeks. Multidimensional mass cytometry and CITE-seq identified donor ML NK cells as distinct from conventional NK cells and persisting for over two months. ML NK cells expressed CD16, CD57, and high granzyme B and perforin, along with a unique transcription factor profile. ML NK cells differentiated in patients had enhanced ex vivo function compared to conventional NK cells from both patient and healthy donors. Overall, same-donor ML NK cell therapy with 3 weeks of N-803 support safely augmented RIC haplo-HCT for AML, with ML NK cells demonstrating enhanced in vivo persistence and functionality, overcoming barriers in the field.

  Study phs002681

• Single cell exome sequencing of lung adenocarcinoma

  Single cell exome sequencing was performed on 200 single cells isolated from a lung adenocarcinoma, female, non-smoker patient. The cells were derived from two distant tumour sectors and a far normal sector. The single cells were amplified on the Fluidigm C1 machine using the GE Healthcare illustra GenomiPhi V2 DNA Amplification Kit prior to sequencing library preparation. In addition, bulk exome sequencing was also conducted for each tumour sectors. For this study, somatic variations were detected from the single cells and phylogenetic clustering was conducted to elucidate the evolutionary trajectory of lung cancer.

  Study EGAS00001002972

• DNA methylation analysis on PBL obtained from male patients with UC-PSC, UC and HC

  Primary sclerosing cholangitis (PSC) is a chronic inflammatory liver disease affecting the intra- and extrahepatic bile ducts, and is strongly associated with ulcerative colitis (UC). In this study, we explored the peripheral blood DNA methylome and its immune cell composition in patients with PSC-UC, UC, and healthy controls (HC) with the aim to develop a predictive assay in distinguishing patients with PSC-UC from those with UC alone. The peripheral blood DNA methylome of male patients with PSC and concomitant UC, UC and HCs was profiled using the Illumina HumanMethylation Infinium EPIC BeadChip (850K) array. Differentially methylated CpG position (DMP) and region (DMR) analyses were performed alongside gradient boosting classification analyses to discern PSC-UC from UC patients. As observed differences in the DNA methylome could be the result of differences in cellular populations, we additionally employed mass cytometry to characterize the immune cell compositions. Genome wide methylation analysis revealed no differentially methylated positions between PSC-UC and UC patients. Nonetheless, using gradient boosting we were capable of discerning PSC-UC from UC with an area under the receiver operator curve (AUROC) of 0.80. Four CpG sites annotated to the NINJ2 gene were found to strongly contribute to the predictive performance. While mass cytometry analyses corroborated the largely similar blood cell composition among patients with PSC-UC, UC and HC, a higher abundance of myeloid cells was observed in UC compared to PSC-UC patients.

  Study EGAS00001005832

• Coagulation and Fibrinolysis in a Pediatric Insulin Titration Trial

  Summary of the Design and Aims: The Coagulation and Fibrinolysis in a Pediatric Insulin Titration Trial (CAF-PINT) is an ancillary study to the HALF PINT (NCT01565941) randomized, controlled trial that was originally designed to study changes in inflammatory and thrombosis pathways in the setting of an interventional trial. The parent HALF PINT study was designed to study the impact of tight glycemic control (TGC) using an explicit insulin titration algorithm to safely achieve a normal glucose in target range of 80-110 mg/dL versus 150-180mg/dL on clinical outcomes among critically ill hyperglycemic children with Heart and Lung Failure. The CAF PINT study collected blood samples pre randomization and at 2 and 4 days after randomization. Blood samples collected in EDTA tubes were centrifuged at local sites to separate the plasma from cell pellets and frozen prior to shipment. In addition, 0.5 mL of whole blood collected in PAXgene tubes modified for use in pediatrics frozen 24 hours after collection prior to shipment.Population Information: Setting: Twenty-one academic children's hospitals (HALF-PINT) and 1 academic children's hospital (IIT-SBPP). Participants: Critically ill hyperglycemic children requiring mechanical ventilation/vasoactive support (n=293).Interventions and Exposures: Patients in HALF PINT were randomized to achieve a low target glucose (80-110 mg/dL) vs. a higher target (150-180 mg/dL). The primary trial was stopped early due to low likelihood of achieving a statistically significant difference in the primary outcomes. Molecular Technologies Employed: Plasma biomarkers were assayed on thawed plasma using a Luminex panel. RNA was extracted from PAXgene Blood RNA Kits modified for pediatric use. Extracted RNA was sequenced with the Novaseq S4 system (Illumina) to generate 2 x 150 base paired end reads to a target depth of 50 million read-pairs per sample.Principal Findings of the Study: We tested for heterogeneity of treatment effects according to baseline blood inflammatory proteins using logistic regression with individual biomarkers as interaction terms and Cox regression analysis using biomarker-derived latent classes. Children with higher inflammatory proteins including TNFR-1, IL-6, IL-8, and IL-10 had lower mortality when treated with insulin to a target glucose of 80-110 mg/dL as compared to 150-180 mg/dL (interaction p<0.05). Causal forest estimates ranged from a 40% mortality reduction to a 15% mortality increase with TGC, depending on each patient’s individual biomarker profile. Latent class categorization strongly interacted with TGC with respect to mortality (Cox regression interaction p=0.005). Specifically, patients with higher inflammation benefited from TGC (6% mortality with TGC vs. 48% mortality, p=0.004) whereas hypoinflamed patients showed a trend towards harm (14% mortality with TGC vs. 7% mortality, p=0.055).Data available through dbGaP: Transcriptomic (Gene Counts) and phenotype data

  Study phs003016

• WGBS data (CancerLocator study) of cell-free DNA derived from human blood

  The blood samples of eight lung cancer patients and one benign lung tumor patient are collected for this dataset. Blood samples were centrifuged first at 1,600 × g for 10 minutes, and then the plasma was transferred into new micro tubes and centrifuged at 16,000 × g for another 10 minutes. The plasma was collected and stored at -80⁰C. CfDNA was extracted from 5 ml plasma using the Qiagen QIAamp Circulating Nucleic Acids Kit and quantified by Qubit 3.0 Fluoromter (Thermo Fisher Scientific). Bisulfite conversion of cfDNA was performed by using EZ-DNA-Methylation-GOLD kit (Zymo Research). After that, Accel-NGS Methy-Seq DNA library kit (Swift Bioscience) was used to prepare the sequencing libraries. The DNA libraries were then sequenced with 150bp paired-end reads.

  Dataset EGAD00001003168

• Open_Targets_020_Epigenomes_of_Cell_Lines

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. 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 please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001003138

• Genomic DNA analysis for malignant mesothelioma from the patients of Japan and USA.

  Malignant mesotheliomas (MMs) are highly aggressive adult malignancies and exposure to asbestos is the major factor involved in MM pathogenesis. It is desirable for a better understanding of the molecular pathogenesis of MM will lead to more specific and effective targeted therapies. In addition it is reported that germline mutation in a specific gene (ex. BAP1) associates familial MMs, and new candidate markers to determine a subject?s predisposition to MM and for early detection need to be identified. Analysis of genomic DNA from MM tumors and reference peripheral blood from Japan and USA are ongoing to find the common genomic characters beyond race.

  Study JGAS000108

• Adolescent Idiopathic Scoliosis (AIS) 1000 Exomes Study

  Adolescent idiopathic scoliosis (AIS) is the most common pediatric spinal deformity. Although the Bracing in AIS Trial (BrAIST) recently demonstrated the effectiveness of bracing for preventing scoliosis progression in some patients, more than 20,000 children undergo major spinal fusion surgery at an annual cost of $3 billion. Spinal fusion surgery is a major operation with considerable risks and complications. Accurate methods of predicting curve progression are needed to develop personalized prevention strategies for those at high risk and to eliminate screening and treatment of those at low risk of progression. Previously identified risk factors for scoliosis curve progression include sex, age of onset, curve type, and presence of an underlying disorder. However, currently available algorithms for predicting AIS curve progression are inaccurate, possibly because the role of genetic factors has been largely unexplored. Because there is little a priori knowledge of the genetic variants involved in AIS pathology, an unbiased genome-wide approach is likely to provide the best opportunity to comprehensively identify disease-associated genes. This is a multicenter exome sequencing study of extreme cases with severe scoliosis.

  Study phs001677

• Maternal-Fetal Immune Responses in Preterm Labor and Congenital Anomalies

  The purpose of this study is to provide a reference profile of small extracellular RNAs in body fluids. These samples were originally obtained in a study that had a different purpose. The purpose of the original study was to learn and understand more about the causes of preterm labor, how to prevent it, and how to treat it. What the researchers learn by studying tissue, cells, and/or fluid (including blood samples, amniotic fluid, and placental tissue) may help to prevent preterm labor and prevent preterm delivery, which will improve the prenatal care women receive and improve the health of newborns.

  Study phs001693

• Proteogenomics reveals two distinct biological pilocytic astrocytoma subgroups

  Pilocytic astrocytoma (PA) is the most common pediatric brain tumor and driven by aberrant MAPK signaling, typically mediated by BRAF alterations. While five-year overall survival rates exceed 95%, tumor recurrence constitutes a major clinical challenge in incompletely resected tumors despite chemotherapeutic or radiation based therapies. Therefore, we used proteogenomics to discern the biological heterogeneity of PA to improve classification of this tumor entity and identify novel therapeutic targets. Our proteogenomics approach integrates RNA sequencing and LC/MS-based proteomic profiling data from a cohort of 58 confirmed, primary PA samples. An integrative genomics approach was conducted to discern the biological heterogeneity of PA and to identify aberrant pathway activation in these biological subgroups. In summary, Pilocytic astrocytomas segregate into two groups where younger patients are significantly associated with Group 1. Importantly, we validate the two distinct biological subgroups in two non-overlapping cohorts. The biological heterogeneity seen here may improve biological classification and reveal novel therapeutic targets specifically useful for non-resectable tumors with high risk of recurrent or progressive disease.

  Study EGAS00001006402

• MicroRNA Biomarkers for Prediction of Preeclampsia

  Maternal serum was collected between 17-28 weeks gestation. Samples were obtained from the high-risk Placental Study at the University of California, San Diego (n=48) and from the average-risk Proteomic Assessment of Preterm Risk (PAPR) Study at Sera Prognostics (n=164). RNA was extracted from 500 microliter of maternal serum using the miRNeasy Micro kit (Qiagen). NEBNext Small RNAseq Library Preparation Kit was used for library construction.

  Study phs002016

• A blood atlas of COVID-19 defines hallmarks of disease severity and specificity

  Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete understanding of potentially druggable immune mediators of disease. To advance this, we present a comprehensive multi-omic blood atlas in patients with varying COVID-19 severity and compare with influenza, sepsis and healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity revealed cells, their inflammatory mediators and networks as potential therapeutic targets, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Tensor and matrix decomposition of the overall dataset revealed feature groupings linked with disease severity and specificity. Our systems-based integrative approach and blood atlas will inform future drug development, clinical trial design and personalised medicine approaches for COVID-19.

  Study EGAS00001005493

• The brain neurovascular epigenome and its association with dementia

  Cerebral small vessel disease (SVD) is frequently comorbid with Alzheimer’s disease (AD) and vascular brain endothelial cells (BECs) are enriched for the expression of genes associated with AD genetic risk. However, the gene regulatory landscapes of neurovascular cells and their intersection with genetic risk for disease remains unexplored. Here we have generated gene regulomes for human BECs, mural cells and other brain cell types to show that AD heritability is primarily immune-related and that it shows modest enrichment in BECs. By contrast, genetic risk for SVD is enriched across cells of the neurovascular unit, including astrocytes. Enhancer-to-gene interactomes implicate amyloid processes in both AD and SVD, though the risk genes are mostly distinct for the two disorders. Motifs for putative partners of lineage transcription factors in microglia and BECs were enriched for AD and SVD variants at genes linked to disease pathways. Gene prioritization and enrichment analyses further identified potential repurposable drugs for AD. Our findings highlight novel regulatory mechanisms and therapeutic targets within the neurovascular system.

  Study EGAS50000001160

• Projects

  Projects Jointly managed by the European Bioinformatics Institute (EMBL-EBI) in Cambridge (UK) and the Centre for Genomic Regulation (CRG) in Barcelona, the EGA provides an invaluable service to the worldwide biomedical research community. The teams leading the EGA are involved in several international partnerships and consortia in numerous scientific fields, where they contribute to ambitious projects. In addition to the project listed below, the EGA is in a long-standing partnership with the Global Alliance for Genomics and Health (GA4GH), as described on the dedicated page. On-going projects Project Duration Domain Funder Tags CANDLE | CANDLE project aims to conceptualise and advance the development of National Cancer Data Nodes (NCDNs) in European countries. These NCDNs will boost the reuse of cancer data for research, innovation and policy making, in order to improve diagnostics and treatment for cancer patients, as well as prevention and early detection. 2025-2028 Cancer Horizon Europe DOCUMENTATION EASIGEN-DS | The EASIGEN-DS project aims to conduct a design study to establish a new European Research Infrastructure on Advanced Genomics Technologies, EASIGEN. To develop an excellent scientific, technological and operational design, we will conduct landscape studies, stakeholder consultations, and community surveying. 2025-2028 Genomic and health data Horizon Europe DATA MANAGEMENT DOCUMENTATION INFRASTRUCTURE Go-IMPaCT | Go-IMPaCT will contribute sequenced genomes and provide infrastructure as part of IMPaCT-Cohort, one of the three fundamental pillars of the Precision Medicine Infrastructure associated with Science and Technology (IMPaCT) program in Spain. Along with the Genome of Europe (GoE) project, around 18.000 people will have their genomes sequenced, also contributing to Spain's commitments in 1+MG. Go-IMPaCT will fund the development of an EGA node to manage and share this genomic and phenoclinic data, laying the foundations for regional and ethnic genomic variability in Spain to be available for research purposes. The IMPaCT cohort is created with the spirit of being an open research tool, compatible with the rest of the health research ecosystem, and other international initiatives. 2025-2027 Large-scale genomics and health data; personalised medicine Instituto de Salud Carlos III ACCESS DISCOVERY INFRASTRUCTURE METADATA STANDARDS FAIR-FEGA | This project seeks to accelerate data depositions into FEGA, significantly increasing the data flow in and from FEGA nodes. It will build capacity within the FEGA nodes and increase awareness in a wide range of stakeholders, thus altogether achieving the ultimate goal of enhancing data reuse. The project will be carried out by a strategic consortium comprising seven ELIXIR nodes and two ELIXIR communities. 2025-2026 Not applicable ELIXIR ACCESS DISCOVERY DOCUMENTATION INFRASTRUCTURE METADATA STANDARDS FEGA-Connect | A consortium of six ELIXIR nodes plus the Polish FEGA node (in-kind contribution) joining forces to build a solid base to develop solutions for effective multi-omic sensitive data integration between FEGA nodes and other infrastructures and specialised Data repositories. We aim to promote a more coherent data deposition, discoverability and retrieval of multi-omics datasets, providing FAIRer data and consequently accelerating research. 2025-2026 Multi-omics data ELIXIR ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE METADATA STANDARDS IMPaCT-Data 2 | IMPaCT-Data 2 will develop a digital platform for the integration and modelling of biomedical data associated with IMPaCT (Precision Medicine Infrastructure associated with Science and Technology) projects in Spain. It will deploy a sustainable infrastructure that facilitates the integration, standardisation, interoperability and analysis of clinical, genomic, molecular and medical imaging data. This platform will be aligned with European projects such as Genome of Europe (GoE), the first project to make use of the European Genomic Data Infrastructure (GDI), and EUCAIM. IMPaCT-Data 2 will benefit from advanced Artificial Intelligence and High Computing Capacity Systems capabilities, offering robust and accessible tools for researchers from the National Health System in Spain. 2025-2026 Large-scale genomics and health data; personalised medicine Instituto de Salud Carlos III ACCESS DISCOVERY INFRASTRUCTURE METADATA STANDARDS SenSec | This project aims to establish a mechanism for orchestrating secure access to sensitive data hosted by the EGA, whether in Central EGA or any Federated Node, from Galaxy, a popular open-source, community-driven VRE (Virtual Research Environment) for bioinformatics analysis. Building on a previous prototype that enabled Galaxy users within Trusted Research Environments (TREs) to decrypt sensitive data for workflow execution without sharing private encryption keys, SenSec will expand this prototype into a comprehensive solution for secure data analysis in Galaxy, facilitating encrypted data access and transfer from FEGA/EGA repositories to designated TREs. 2025-2026 Genomic and health data; trusted research environment ELIXIR ACCESS DATA ANALYSIS ERDERA | The European Rare Disease Research Alliance (ERDERA) takes over EJPRD to deliver concrete health benefits to rare disease patients in the next decade by advancing prevention, diagnosis and treatment research. To leave no one behind, over 170 organisations championed by the European Union and member states are working hand in hand to make Europe a world leader in rare diseases research and innovation. 2024-2034 Rare diseases Horizon Europe; "La Caixa" Foundation cofunds CRG's contribution ACCESS DATA ANALYSIS DISCOVERY INFRASTRUCTURE SYNTHIA | The aim of SYNTHIA is to deliver validated, reliable tools and methods for synthetic data generation (SDG). The tools will cover multiple data types including lab results, clinical notes, genomics, imaging and m-health data. SYNTHIA also hopes to make possible the generation of longitudinal data. 2024-2029 Genomic and health data; multi-omics; AI solutions Innovative Health Initiative (IHI) DATA ANALYSIS DATA MANAGEMENT INFRASTRUCTURE GoE | The Genome of Europe initiative aims to build a European network of national genomic reference cohorts of at least 500.000 citizens. These reference cohorts will be selected to be representative of the European population. 2024-2028 Large-scale genomic and health data Horizon Europe ACCESS DISCOVERY INFRASTRUCTURE METADATA STANDARDS HEREDITARY | HEREDITARY aims to transform the way we approach disease detection, prepare treatment response, and explore medical knowledge by building a robust, interoperable, trustworthy, and secure framework that integrates multimodal health data (including genetic data) while ensuring compliance with cross-national privacy-preserving policies. 2024-2027 Neurodegenerative disorders, gut-brain interplay Horizon Europe DATA MANAGEMENT DATA ANALYSIS EOSC-ENTRUST | The mission of EOSC-ENTRUST is to create a European network of trusted research environments for sensitive data and to drive European interoperability by joint development of a common blueprint for federated data access and analysis. 2024-2026 Trusted Research Environment Horizon Europe INFRASTRUCTURE EBV-MS | "Targeting Epstein-Barr Virus Infection for Treatment and Prevention of Multiple Sclerosis". The ambitious goals of the project are to answer the questions why only a few EBV infected persons develop MS, and define the underlying mechanism of this process, as well as clarify if targeting the EBV infection can prevent MS or improve the disease course. 2023-2028 Viral-host genetics; immune response; disease modelling; disease prevention; AI/ML solutions Horizon Europe DATA MANAGEMENT DATA ANALYSIS WISDOM | WELL-BEING IMPROVEMENT THROUGH THE INTEGRATION OF HEALTHCARE AND RESEARCH DATA AND MODELS WITHOUT BORDER FOR CHRONIC IMMUNE-MEDIATED DISEASES aims to deploy novel approaches for data processing, harmonisation, management, and secure data sharing and federated access for diseases like multiple sclerosis. Using an end-user guided approach, it will facilitate responsible and critical assessment of the use of AI in healthcare. 2023-2028 Chronic immune-mediated diseases Horizon Europe DATA MANAGEMENT INFRASTRUCTURE EUCAIM | EUropean Federation for CAncer IMages is a project that will build a highly secure, federated and large-scale European cancer imaging platform, with capabilities that will greatly enhance the potential of Artificial Intelligence in oncology. 2023-2027 Cancer Digital Europe Programme (DIGITAL) DISCOVERY CONTAGIO | CONTAGIO (COhorts Network To be Activated Globally In Outbreaks) aims to create coordination mechanisms to rapidly react to infectious disease (re-)emergence in low- and middle-income countries (LMICs). 2023-2026 Infectious Diseases European Commission - Horizon Europe ACCESS DATA MANAGEMENT DISCOVERY Youth-GEMs | Youth-GEMS (Gene Environment Interactions in Mental Health TrajectorieS of Youth) will conduct research into the genetic and environmental factors of mental health in young European people. 2022-2027 Mental health European Commission - Horizon Europe DATA MANAGEMENT DISCOVERY GDI | The European Genomics Data Infrastructure project is enabling access to genomic and related phenotypic and clinical data across Europe. It is doing this by establishing a federated, sustainable and secure infrastructure to access the data. 2022-2026 Genomic and health data European Commission - Horizon Europe; "La Caixa" Foundation cofunds CRG's contribution DISCOVERY DOCUMENTATION INFRASTRUCTURE IMPaCT-T2D | The IMPaCT-T2D project aims at studying the complete genomes of a large cohort of patients with Type 2 Diabetes mellitus (T2D), using modern sequencing technologies and artificial intelligence (AI) in order to improve the stratification and pharmacological treatment in the context of precision medicine. 2022-2025 Cardiovascular and Complex Diseases Spanish Ministry of Science and Innovation; Instituto de Salud Carlos III ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE Completed projects Project Duration Domain Funder Tags EOSC4Cancer | EOSC4Cancer builds on existing projects, research outcomes and established community solutions to create the federated FAIR data, analysis and services infrastructure needed for European Cancer research programmes. 2022-2025 Cancer European Commission - Horizon Europe DISCOVERY EuCanImage | A European Cancer Image Platform Linked to Biological and Health Data for Next-Generation Artificial Intelligence and Precision Medicine in Oncology. 2020-2025 AI Solutions in Oncology European Commission - H2020 Programme; "La Caixa" Foundation cofunds CRG's contribution DATA MANAGEMENT METADATA STANDARDS GenoMed4ALL | A consortium built to empower personalised medicine in the field of haematological diseases through the use of AI and the pooling of genomic and clinical data. 2020-2025 Hematological diseases European Commission - H2020 Programme DISCOVERY METADATA STANDARDS BY-COVID | The BeYond-COVID project aims to make COVID-19 data accessible to scientists in laboratories but also to anyone who can use it, such as medical staff in hospitals or government officials. Going beyond SARS-CoV-2 data, the project will provide a framework for making data from other infectious diseases open and accessible to everyone. 2021-2024 Infectious diseases European Commission - H2020 Programme ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE IMPaCT-Data | IMPaCT-Data aims to create the infrastructure for secondary use of data from Spanish healthcare systems - electronic health records, medical imaging and genomic repositories - and contribute with the knowledge and methodology produced to the healthcare system. 2021-2024 Large-scale genomics and health dataSpanish Ministry of Science and Innovation; Instituto de Salud Carlos III ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE LaMarato | It is a project aimed at creating and developing a catalan interhospitalary network to interrogate genetic variants from thousands of genetic tests carried out in patients with rare diseases from the main catalan hospitals. 2021-2024 Genomic and health data Fundacio La Marato de TV3 (catalan foundation) DISCOVERY HealthyCloud | This consortium will contribute a Strategic Agenda towards the European Health Research and Innovation Cloud. The project will work in collaboration with a broad range of stakeholders to ensure that all voices are included and that the results are technically and ethically sound. 2021-2023 Not Applicable European Commission - H2020 Programme DOCUMENTATION B1MG | Beyond 1 Million Genomes aims to create a network of genetic and clinical data across Europe. The project provides coordination and support to the 1+ Million Genomes Initiative (1+MG). This initiative is a commitment of 24 EU countries, the UK and Norway to give cross-border access to one million sequenced genomes by 2022. 2020-2023 Not applicable European Commission - Horizon Europe DATA MANAGEMENT INFRASTRUCTURE METADATA STANDARDS ELIXIR-CONVERGE | An alliance with the goal of Connecting and aligning ELIXIR Nodes to deliver sustainable FAIR life-science data management services. 2020-2023 Data Management and Infectious Diseases European Commission - H2020 Programme DATA MANAGEMENT INFRASTRUCTURE METADATA STANDARDS IHCC | The International HundredK+ Cohorts Consortium aims to create a global platform for translational research ? informing the biological and genetic basis for disease and improving clinical care and population health. 2020-2022 Translational research NIH; The Wellcome Trust; CZI INFRASTRUCTURE METADATA STANDARDS PPCG | The Pan Prostate Cancer Group aims to harmonise and interrogate Whole Genome DNA Sequence data generated around the world from over 2000 men with prostate cancer, with associated transcriptome and methylome data to include men from different clinical categories, and ethnicities. This project is about providing breakthrough advances through analysis of a very large series of Whole Genome DNA data from prostate cancer contributed by many of the leading scientists and clinicians working in prostate cancer genomics. 2019-2024 Cancer Cancer Research UK DATA MANAGEMENT CINECA | Consortium providing a Federated solution enabling population-scale genomic and biomolecular data accessible across international borders accelerating research and improving the health of individuals resident across continents. 2019-2023 Large-scale Genomics and Health Data European Commission - H2020 Programme ACCESS DATA MANAGEMENT DISCOVERY INFRASTRUCTURE EASI-Genomics | A project designed to provide easy access to cutting-edge DNA sequencing technologies to researchers from academia and industry, within a framework that ensures compliance with ethical and legal requirements, as well as FAIR and secure data management. 2019-2023 Next Generation Sequencing European Commission - H2020 Programme ACCESS EJP-RD | An European consortium built to create a comprehensive, sustainable ecosystem allowing a virtuous circle between research, care, and medical innovation. 2019-2023 Rare diseases European Commission - H2020 Programme ACCESS DATA MANAGEMENT DOCUMENTATION METADATA STANDARDS EOSC-Life | EOSC-Life brings together the 13 Life Science research infrastructures (LS RIs) to create an open, digital and collaborative space for biological and medical research. The project will publish 'FAIR' data and a catalogue of services provided by participating RIs for the management, storage and reuse of data in the European Open Science Cloud (EOSC). 2019-2023 Not applicable European Commission - H2020 Programme DOCUMENTATION EUCANCan | A federated network aiming at implementing a cultural, technological and legal integrated framework across Europe and Canada, to enable and facilitate the efficient sharing of cancer genomic data. 2019-2023 Cancer European Commission - H2020 Programme DATA MANAGEMENT METADATA STANDARDS The Federated EGA framework: supporting sensitive data management across the ELIXIR Nodes | This project is a direct continuation of the FHD IS with the goal to position the FEGA framework as the core infrastructure driver to support human data sharing for research. 2019-2023 Human genomic data ELIXIR INFRASTRUCTURE UK Biobank | UK Biobank is a large-scale biomedical database and research resource, containing in-depth genetic and health information from half a million UK participants. This project is to archive whole genome sequencing and other genetic data for UK Biobank participants. 2019-2023 Large-scale Genomics and Health Data The Wellcome Trust; UKRI; Amgen; AstraZeneca; GSK; Johnson & Johnson DATA MANAGEMENT INFRASTRUCTURE VEIS | The core mission of VEIS is to create an open ecosystem of technologies that will address and adapt to the requirements of the systems used to analyse and interpret -omics and clinical data in research and application environments in biomedicine. The aim of the project is to leverage the value of the EGA for both industry and society. 2019-2022 Oncology and Rare diseases Generalitat de Catalunya and European Regional Development Fund (ERDF) ACCESS DISCOVERY ELIXIR BEACON IS | This study follows on from a number of earlier activities that have established the ELIXIR Beacon Project. The main aim is to extend the Beacon protocol, developed at EGA, to become the reference ELIXIR Data Discovery product 2019-2021 Not applicable ELIXIR DISCOVERY ELIXIR FHD IS | This project coordinates the delivery of FAIR compliant metadata standards, interfaces, and reference implementation to support the federated ELIXIR network of human data resources. 2019-2021 Human genomic data ELIXIR INFRASTRUCTURE ELIXIR Rare Disease | The Rare Disease Community extends and generalises the system of access authorisation and high volume secure data transfer developed within the EGA. The goal of the Community is to create a federated infrastructure that will enable researchers to discover, access and analyse different rare disease repositories across Europe. It is doing this in partnership with other European infrastructure projects, namely RD-CONNECT, BBMRI-ERIC and E-Rare.2019-2021 Rare diseases ELIXIR INFRASTRUCTURE Solve-RD | Solve-RD - solving the unsolved rare diseases - is a research project funded by the European Commission. It echoes the ambitious goals set out by the International Rare Diseases Research Consortium (IRDiRC) to deliver diagnostic tests for most rare diseases by 2020. The current diagnostic and subsequent therapeutic management of rare diseases is still highly unsatisfactory for a large proportion of rare disease patients - the unsolved RD cases. For these unsolved rare diseases, we are unable to explain the etiology responsible for the disease phenotype, predict the individual disease risk and/or rate of disease progression, and/or quantitate the risk of relatives to develop the same disorder. 2018-2024 Rare diseases European Commission - H2020 Programme ACCESS DATA MANAGEMENT METADATA STANDARDS EuCanShare | An EU-Canada joint infrastructure for next-generation multi-Study Heart research. 2018-2022 Cardiovascular Diseases European Commission - H2020 Programme ACCESS METADATA STANDARDS

  Documentation about/projects-and-funders/projects

• NHLBI TOPMed: Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE)

  ECLIPSE was a longitudinal observational study of 2164 COPD subjects and a smaller number of smoking controls (337) and nonsmoking controls (245) followed regularly for three years, with three chest CT scans (at baseline, one year, and three years) (Vestbo et al., 2008, PMID: 18216052). Subjects were enrolled at clinical centers in the US, Canada, Europe, and New Zealand. Inclusion criteria included subjects ages 40-75, at least 10 pack-years of smoking, and spirometry in GOLD grades 2-4 (COPD cases) or normal spirometry with post-bronchodilator FEV1 >85% (predicted) and FEV1/FVC>0.7 (controls). Study visits were performed at enrollment, three months, and every six months thereafter with spirometry, questionnaires, and other clinical evaluations. The ECLIPSE CT scans have been analyzed with the VIDA software for emphysema and airway phenotypes. ECLIPSE has provided key insights into the clinical epidemiology of COPD, including COPD exacerbations (Hurst, et. al., 2010, PMID: 20843247) and lung function decline in COPD (Vestbo, et. al., 2011, PMID: 21991892). ECLIPSE has been used in a number of genetic studies of COPD susceptibility and protein biomarkers (Faner, et. al., 2014, PMID: 24310110). Genome-wide gene expression microarray data are available in 147 induced sputum samples from COPD subjects and 248 peripheral blood samples from COPD and control subjects. Phenotype data for ECLIPSE subjects is available through dbGaP phs001252.

  Study phs001472

• Identification of improved IL28B SNPs and haplotypes for prediction of drug response in treatment of hepatitis C using massively parallel sequencing in a cross-sectional European cohort

  The hepatitis C virus infects nearly 3% of the World’s population, causing severe liver disease in many. Standard of care therapy is currently pegylated interferon alpha and ribavirin (PegIFN/R), which is effective in less than half of those infected with the most common viral genotype. Two IL28B SNPs, rs8099917 and rs12979860, predict response to (PegIFN/R) therapy in treatment of hepatitis C virus infection. These SNPs were identified in genome wide analyses using Illumina genotyping chips. In people of European ancestry, there are 6 common (>1%) haplotypes for IL28B, one tagged by rs8099917 minor allele, four tagged by rs12979860. We used massive parallel sequencing of the IL28B and IL28A gene regions generated by PCR from pooled DNA samples from 100 responders and 99 non-responders to therapy, to identify common variants. Variants that had high odds ratios and were validated were then genotyped in a cohort of 905 responders and non-responders. Their predictive power was assessed, alone and in combination with HLA-C. Only SNPs in the IL28B linkage disequilibrium block predicted drug response. Eighteen SNPs were identified with evidence for association with drug response, and with a high degree of confidence in the sequence call. We found that two SNPs, rs4803221 (homozygote minor allele positive predictive value (PPV) of 77%) and rs7248668 (PPV 78%), predicted failure to respond better than the current best, rs8099917 (PPV 73%) and rs12979860 (PPV 68%) in this cross-sectional cohort. The best SNPs tagged a single common haplotype, haplotype 2. Genotypes predicted lack of response better than alleles. However, combination of IL28B haplotype 2 carrier status with the HLA-C C2C2 genotype, which has previousl y been reported to improve prediction in combination with IL28B, provides the highest PPV (80%). The haplotypes present alternative putative transcription factor binding and methylation sites. Massive parallel sequencing allowed identification and comparison of the best common SNPs for identifying treatment failure in therapy for HCV SNPs tagging a single haplotype have the highest PPV, especially in combination with HLA-C. The functional basis for the association may be due to altered regulation of the gene. These approaches have utility in improving diagnostic testing and identifying causal haplotypes or SNPs.

  Study EGAS00001000096

• Multi-omic analysis of SDHB-related PCPG

  Hereditary SDHB-mutant pheochromocytomas (PC) and paragangliomas (PG) are rare tumours with a high propensity to metastasize although their clinical behaviour is unpredictable. To characterize the genomic landscape of these tumours and identify metastasis biomarkers, we performed multi-omic analysis on 94 tumours from 79 patients using six molecular methods including: whole-genome sequencing (WGS) of tumour and matched blood (n=94), whole transcriptome sequencing (RNA-seq) (n=91), small-RNA seq (n=90), DNA methylation profiling (n=93). Droplet-based (10x) single nuclei (sn)RNA-seq and snATAC-seq was applied to 9 and 7 cases, respectively. Additionally snATAC-seq was applied to one sample of normal adrenal medulla.

  Study EGAS50000000346

• ARRA - NHLBI Lung Cohorts Sequencing Project: Genetic modifiers of

  The major goal of this project is to apply second generation resequencing technology to identify disease causing variants influencing pediatric and adult lung diseases in a collection of two longitudinal population cohorts of cystic fibrosis patients that have been well characterized for a comprehensive set of clinical traits. In Phase I, exome sequencing was performed on 43 cystic fibrosis patients with early Pa infection and 48 cystic fibrosis patients with late Pa infection to identify variants influencing the time to onset of Pa infection. In Phase II, additional exomes were added to the study, to reach a total of 91 individuals with early Pa infection and 96 with late Pa infection. The majority of the 340 subjects of Phase II do not have a Pa infection phenotype, but instead have a pulmonary function phenotype (121 severe vs. 124 mild impairment) as determined by the survival corrected Kulich FEV percentile of Corey et al. A small minority have intermediate phenotypes and/or show severe decline in lung function during childhood.

  Study phs000254

• Early Family Prevention of Adolescent Alcohol, Drug Use, and Psychopathology

  The Early Steps Multisite Study is comprised of researchers from the University of Virginia, the University of Pittsburgh, Arizona State University, and Oregon Research Institute. This longitudinal study has been funded by the National Institute on Drug Abuse at the National Institutes of Health since 2002. The Early Steps Multisite Study conducted a randomized control trial to examine the effects of an intervention program called the Family Check-Up (FCU) offered in early to middle childhood. Outcomes include problem behaviors including substance use. Primary caregivers (PC) and their children (TC) were recruited from Women, Infant, and Children's (WIC) Nutritional Supplement centers in and around Pittsburgh, PA, Eugene, OR and Charlottesville, VA when target participating children were age 2. Participants were screened in three key areas of risk for later child conduct problems: (1) sociodemographic risk (e.g., poverty, teen parent status), (2) family risk (e.g. maternal stress, depressive symptoms), and (3) child conduct problems. Randomization to the intervention condition was balanced on gender to assure an equal number of males and females in the control and intervention groups. Data submitted to dbGaP are from the 515 subjects who were consented to provide a saliva sample.

  Study phs003442

• 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