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

  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 phs000401 contains the Framingham Heart Study (FHS) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

  Study phs000401

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

  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 phs000402 contains the Jackson Heart Study (JHS) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

  Study phs000402

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

  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 phs000400 contains the Cardiovascular Health Study (CHS) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

  Study phs000400

• Multi-omics data of 1000 Inflammatory Bowel Disease patients

  Portal available at https://1000ibd.org Inflammatory bowel disease (IBD) is a chronic complex disease of the gastrointestinal (GI) tract. Patients with IBD can experience a wide range of symptoms, but the pathophysiological mechanisms that cause these individual differences in clinical presentation remain largely unknown. In consequence, IBD is currently classified into subtypes using clinical characteristics. If we are to develop a more targeted treatment approach, molecular subtypes of IBD need to be discovered that can be used as new drug targets. To achieve this, we need multiple layers of molecular data are generated from the same IBD patients.We initiated the 1000IBD project to prospectively follow more than 1000 IBD patients from the Northern provinces of the Netherlands. For these patients, we have collected a uniquely large number of phenotypes and generated multi-omics profiles. To date, 1,215 participants have been enrolled in the project and enrolment is on-going, with 609 patients being present in the first data release. Phenotype data collected for these participants includes information on dietary and environmental factors, drug responses, and adverse drug events. Genome information has been generated using genotyping (ImmunoChip, Global Screening Array and HumanExomeChip) and sequencing (whole exome sequencing and targeted resequencing of IBD susceptibility loci), transcriptome information generated using RNA-sequencing of intestinal biopsies and microbiome information generated using both sequencing of the 16S rRNA gene and whole genome shotgun metagenomic sequencing.All molecular data generated within the 1000IBD project will be shared in multiple data on the European Genome-Phenome Archive (www.ega-archive.org). The first data release, will contain basic phenotypes for 609 participants, genotypes of 314 participants, gut microbiome data generated by tag sequencing the 16S gene of feces from 315 participants and intestinal biopsies from 107 participants, and gut microbiome metagenomic sequencing of feces of 355 participants . Future releases will comprise many more additional phenotypes and -omics data layers. 1000IBD data can be used by other researchers as a replication cohort, a dataset to test new software tools, or a dataset for applying new statistical models.

  Study EGAS00001002702

• The Immune Microenvironment Shapes Transcriptional and Genetic Heterogeneity in Chronic Lymphocytic Leukemia

  Tumor microenvironment (TME) and somatic mutations drive progression of chronic lymphocytic leukemia (CLL). Integrated bulk and single-cell RNA sequencing (RNA-seq) of paired peripheral blood (PB) and lymph node (LN) samples from patients with treatment-naïve CLL showed upregulation of oncogenic processes in LN attributable to a minor population of activated tumor cells. A 10-gene tumor signature derived from this population was positively correlated with activated CD4+ T cells and M2 macrophages in the TME. Whole exome sequencing of paired PB and LN samples showed subclonal expansion in LN in some patients. In remaining patients with clonal stability between PB and LN, a T-cell inflamed TME was detected by RNA-seq. These data connect the TME with molecular events in the evolution of CLL.This cohort was later augmented with whole exome sequencing for 15 additional CLL samples. In an integrative analysis of genetic, transcriptomic, and epigenetic data, including the data from this study, we built new models to improve CLL patient prognostication.

  Study phs002297

• Infiltrative and drug-resistant slow-cycling cells support metabolic heterogeneity in glioblastoma

  Metabolic reprogramming has been described in rapidly growing tumors, which are thought to mostly contain fast-cycling cells (FCCs) that have impaired mitochondrial function and rely on aerobic glycolysis. Here, we characterize the metabolic landscape of glioblastoma (GBM) and explore metabolic specificities as targetable vulnerabilities. Our studies highlight the metabolic heterogeneity in GBM, in which FCCs harness aerobic glycolysis, and slow-cycling cells (SCCs) preferentially utilize mitochondrial oxidative phosphorylation for their functions. SCCs display enhanced invasion and chemoresistance, suggesting their important role in tumor recurrence. SCCs also demonstrate increased lipid contents that are specifically metabolized under glucose-deprived conditions. Increased fatty acid transport in SCCs is targetable by pharmacological inhibition or genomic deletion of FABP7, both of which sensitize SCCs to metabolic stress. Furthermore, FABP7 inhibition, whether alone or in combination with glycolysis inhibition, leads to overall increased survival. Our studies reveal the existence of GBM cell subpopulations with distinct metabolic requirements and suggest that FABP7 is central to lipid metabolism in SCCs and that targeting FABP7-related metabolic pathways is a viable therapeutic strategy.

  Study EGAS00001003251

• Upper cortical layer-driven network impairment in schizophrenia

  Schizophrenia is one of the most wide-spread and complex mental disorders. To characterize the impact of schizophrenia, we performed single nucleus RNA sequencing (snRNA-seq) of >220,000 neurons from the dorsolateral prefrontal cortex of patients with schizophrenia and matched controls. Additionally, >115,000 neurons were analyzed topographically by immunohistochemistry. Compositional analysis of snRNA-seq data revealed a reduction in abundance of GABAergic neurons and a concomitant increase in principal neurons, most pronounced for upper cortical layer subtypes, which was substantiated by histological analysis. Many neuronal subtypes showed extensive transcriptomic changes, the most dramatic - in upper layer GABAergic neurons, including downregulation in energy metabolism and upregulation in neurotransmission. Transcription factor network analysis demonstrated a developmental origin of transcriptomic changes. Finally, Visium spatial transcriptomics further corroborated upper layer neuron vulnerability in schizophrenia. Overall, our results point towards general network impairment within upper cortical layers as a core substrate associated with schizophrenia symptomatology. Study is available on bioRxiv (https://doi.org/10.1101/2020.11.17.386458) and in upcoming publication.

  Study EGAS00001006495

• Structural Expression of BMMF in tissues of colorectal, lung and pancreatic cancer patients

  Chronic inflammation, linked to the presence of bovine milk and meat factors (BMMF) and specific subsets of macrophages, results in oxygen radical synthesis and induction of mutations in DNA of actively replicating cells and replicating single stranded DNA (zur Hausen et al., 2017). Cancers arising from this process have been characterized as indirect carcinogenesis by infectious agents (without persistence of genes of the agent in premalignant or cancers cells). Here we investigate structural properties of pleomorphic vesicles, regularly identified by staining peritumour tissues of colorectal, lung and pancreatic cancer for expression of BMMF Rep. The latter represents a subgroup of BMMF1 proteins involved in replication of small single-stranded circular plasmids of BMMF, but most likely also contributing to pleomorphic vesicular structures found in the periphery of colorectal, lung and pancreatic cancers. Structurally dense regions are demonstrated in preselected areas of colorectal cancer, after staining with monoclonal antibodies against BMMF1 Rep. Similar structures were observed in human embryonic cells (HEK293TT) overexpressing Rep. These data suggest that Rep or Rep isoforms contribute to the structural formation of vesicles.

  Study EGAS00001006744

• Assessing the suitability of formalin-fixed paraffin-embedded (FFPE) tissue for genome-wide association studies (GWAS)

  This study evaluates the feasibility of conducting genome-wide association studies (GWAS) using DNA extracted from formalin-fixed paraffin-embedded (FFPE) tissue. Genotyping results from paired FFPE and blood samples were compared using both microarray technology and low-coverage whole-genome sequencing (lcWGS). The analysis demonstrated high concordance between FFPE- and blood-derived genotypes. Although both platforms performed well, microarrays achieved significantly higher recall and precision and currently offer greater cost-effectiveness and computational efficiency. These findings support the suitability of FFPE-derived DNA for GWAS, with microarrays representing the preferred approach at present. However, the broader variant detection enabled by lcWGS may represent an additional advantage to be explored in future studies, particularly in diverse populations.

  Study EGAS00001008103

• Identification of cardiovascular biomarkers through an integrative omics approach

  Recent GWAS studies have made extensive use of large eQTL data sets to functionally annotate index SNPs. With a large number of association signals located outside coding regions there has been an intense search among sequence variants affecting gene expression at the transcriptional level. However, little progress has been made in mapping regulatory variants that affect protein levels at the translational or post-translational level. It is now possible to undertake a protein QTL scan for focused sets of e.g. oxidized proteins by mass spectrometry. We have established a collaboration with a longitudinal, family-based study in France, the Stanislas cohort, which comprises circa 1000 nuclear families (4,295 individuals) and has follow up data for 10 years (three visits). We have undertaken a pilot study in a focus set of 257 subjects from 79 families with the aim to integrate GWAS, transcriptomic and DNA methylation data with proteomic data on a set of 100 proteins measured in PBMCs. We have already generated GWAS data using Illumina's core-exome chip as well as DNA methylation profiles with the 450K array. We propose to use RNA seq to generate transcriptomic data of the corresponding PBMCs. 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 EGAD00001002197