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• CINECA synthetic data.Please note: This study contains synthetic data (with cohort “participants” / ”subjects” marked with FAKE) has no identifiable data and cannot be used to make any inference about cohort data or results.

  Please note: This study contains synthetic data (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

  Study EGAS00001002472

• The mutational landscape of normal human endometrial epithelium - Additional Samples

  All normal somatic cells are thought to acquire mutations but understanding of the rates, patterns, causes and consequences of somatic mutation in normal cells is limited. Uterine endometrium adopts multiple physiological states over a lifetime and is lined by a gland-forming epithelium. Whole genome sequencing of normal endometrial glands from women aged 19 to 81 years showed them to be clonal cell populations derived from recent common ancestors, with total mutation burdens that increase with age at ~29 base substitutions/year and which are many-fold lower than endometrial cancers. Normal endometrial glands frequently carry driver mutations in cancer genes. Driver mutation burdens increase with age and correlate negatively with parity. Phylogenetic trees of normal endometrial glands constructed using whole genome sequences indicated that clones with drivers often originate during the first decades and spread to colonise the endometrial epithelial lining. The results show that driver mutation landscapes differ between normal cell types, perhaps shaped by differences in normal tissue physiology, and suggest that the procession of neoplastic changes leading to endometrial cancer is initiated early in life.

  Dataset EGAD00001005214

• Whole Exome Sequencing for Familial Intracranial Aneurysm (FIA I-II) Study

  The goal of this study is to identify the genes underlying the risk of intracranial aneurysm (IA). The FIA Study initially recruited families appropriate for linkage analysis. Therefore, the recruitment focus was not only on probands with a family history of IA but also required that biological samples be obtained for at least two affected family members. Family members underwent detailed interviews for medical, social and family history, and provided blood samples for DNA extraction. Over 400 multiplex IA families were recruited and enrolled. The whole exome sequencing project aims to identify novel and rare (in the general population) genetic variants that are enriched in seven extended multiplex families with a strong familial aggregation of intracranial aneurysms.

  Study phs000636

• Whole genome sequencing of six ethnic groups from Burkina Faso, Cameroon, and Tanzania

  We conducted low-coverage (~10x) sequencing of six ethnic groups from three malaria-endemic countries in sub-Saharan Africa, with the aim of characterising genetic diversity and improving imputation performance for genotyped samples in these populations. This data is part of a pre-publication release and is available under managed access. Please see https://www.malariagen.net/data/terms-use/human-gwas-data for more information on MalariaGEN data access policies. The purpose of the project was to support the discovery and understanding of genetic variants that influence human disease. Specifically defined goals were: a. the discovery of single nucleotide variants at frequencies of 1% or higher in diverse populations, b. even more comprehensive discovery (variants down to frequencies of 0.1 - 0.5%) in functional gene regions, and c. discovery of structural variants, such as copy number variants, other insertions and deletions, and inversions, including sequence-level understanding of breakpoints.

  Study EGAS00001003648

• A Universal Gut Metagenomic-Derived Signature Predicts Cirrhosis

  Dysregulation of the gut microbiome has been implicated in the progression of nonalcoholic fatty liver disease (NAFLD) to advanced fibrosis and cirrhosis. To determine the diagnostic capacity of this association, stool microbiomes were compared across 163 well-characterized participants encompassing non-NAFLD controls, NAFLD-cirrhosis patients and their first-degree relatives. Interrogation of shotgun metagenomic and untargeted metabolomic profiles using the Random Forest machine learning algorithm and differential abundance analysis identified discrete metagenomic and metabolomic signatures that were similarly effective in detecting cirrhosis (diagnostic accuracy 0.91, AUC). Combining the metagenomic signature with age and serum albumin levels accurately distinguished cirrhosis in etiologically and genetically distinct cohorts from geographically separated regions. Additional inclusion of serum aspartate aminotransferase levels, which are increased in cirrhosis patients, enabled discrimination of cirrhosis from earlier stages of fibrosis. These findings demonstrate that a core set of gut microbiome species may offer universal utility as a non-invasive diagnostic test for cirrhosis.

  Study EGAS00001004600

• Genomic variants in 121 genes associated with ovarian cancer in cancer tissue and derived organoids

  High-grade serous ovarian cancer (HGSOC) likely originates from the fallopian tube (FT) epithelium, but advanced stages are mostly found outside the FT. We used ex-vivo cultures of HGSOC and knock-out of tumor suppressors in FT organoids to study changes in epithelial cells and niche requirements for normal and transformed FT cells. We found that transformed cells require BMP signaling and are growth arrested in Wnt rich medium. A SureSelectXT Automation Custom Capture Library (Agilent) target enrichment panel was designed. The enrichment panel comprised all coding exons of 121 genes associated with ovarian cancer. Capture was performed according to the manufacturer’s instructions using an NGS Workstation Option B (Agilent) for automated library preparation starting with 3 μg DNA per sample. Sequencing was performed on a Illumina Hiseq 2500 system gnerating 2x100bp paired end reads and a target coverage of >200 per sample. Sequence reads were mapped to the haploid human reference genome (hg19) using BWA. Variants where called with FreeBayes v1.1.

  Dataset EGAD00001005279

• Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions

  Full and partial loss of chromosome 7 (del7, 7q-) are prevalent cytogenetic abnormalities in pediatric myeloid neoplasms resulting in haploinsufficiency of key hematopoietic regulators on chromosome 7. While the genomic landscape of myeloid neoplasms in adults with del7 and 7q- has been described, pediatric patients with similar chromosome 7 losses have not been compiled into a single, comprehensive study utilizing modern sequencing strategies. To this end, we assembled a cohort of 108 pediatric and young adult patients representing a mixture of diagnoses. Using WGS, WES, and RNAseq, we compared the co-occurring mutations and gene expression levels in our cohort to those found in pediatric and young adult patients with two intact copies of chromosome 7. We also performed single-cell multi-omics on a subset of eight samples.

  Study EGAS00001008055

• Single-cell landscapes of primary glioblastomas and matched organoids and cell lines reveal variable retention of inter- and intra-tumor heterogeneity

  Glioblastomas (GBMs) are aggressive primary malignant brain tumors characterized by extensive levels of inter- and intra-tumor genetic and phenotypic heterogeneity. Patient-derived organoids (PDOs) have recently emerged as useful models to study such heterogeneity. Here, we present bulk exome as well as single-cell genome and transcriptome profiles of primary IDH wild type GBMs from ten patients, including two recurrent tumors, as well as PDOs and brain tumor-initiating cell (BTIC) lines derived from these patients. We find that PDOs are genetically similar to and variably retain gene expression characteristics of their parent tumors. At the phenotypic level, PDOs appear to exhibit similar levels of transcriptional heterogeneity as their parent tumors, whereas BTIC lines tend to be enriched for cells in a more uniform transcriptional state. The datasets introduced here will provide a valuable resource to help guide experiments using GBM-derived organoids, especially in the context of studying cellular heterogeneity.

  Study EGAS00001005227

• The Genetic Basis of Progression in Multiple Sclerosis

  This study examined the genetic determinants of multiple sclerosis (MS) severity in an international cohort of people with MS assembled by the International Multiple Sclerosis Genetics Consortium (IMSGC) and the MultipleMS Consortium. A total of 12,584 people with MS of European ancestry were included in the main genome-wide association study (GWAS). Participants were enriched for older individuals with longer disease duration (mean age 51.7 years and mean disease duration 18.2 years). All individuals were whole-genome genotyped on the Illumina Global Screen Array (GSAMD-24v2-0). Imputation was performed using the Haplotype Reference Consortium reference panel. The primary outcome was the age-related MS severity score. All individuals had at least 1 expanded disability status scale (EDSS) measure. When multiple EDSS scores were available, the last one was selected to calculate the age-related MS severity score.Of those 12,584 people with MS, this data release includes 4,623 participants recruited from non-European sites in the US, Canada and Australia. This release includes individual-level genotype and phenotype files necessary to replicate our GWAS of MS severity, including covariates.

  Study phs002929

• Germline Whole-Exome Sequencing of Lung Cancer in EAGLE

  EAGLE is a large population-based case-control study designed and conducted to investigate the genetic and environmental determinants of lung cancer and smoking persistence using an integrative approach that allows combined analysis of genetic, environmental, clinical, and behavioral data. Here, we applied whole exome sequencing (WES) to EAGLE study, in a group of 2,777 Italian subjects (including 1,461 lung cancer cases and 1,316 healthy controls). We derived gene-level burden tests to explore the cumulative effect of deleterious rare variants within protein-coding genes and the lung cancer risk. Additionally, at this site we include WES datasets of 1259 healthy controls from 1054 PLCO (The Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial) subjects and 205 ACS (The American Cancer Society study) subjects.

  Study phs002496