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• A panel of reference haplotypes for imputing complement component 4 (C4) gene structural variation

  Neuropsychiatric and autoimmune disorders have substantial epidemiological correlations (Benros et al., JAMA Psychiatry 2013, PMID: 23760347) and broad, genome-wide patterns of shared genetic risk (Pouget et al., Hum Mol Genet, PMID: 31211845; Tylee et al., Am J Med Genet B Neuropsychiatr Genet 2018, PMID: 30325587). Some cases of psychosis involve autoantibodies against the NMDA receptor, AMPA receptor, or other synaptic proteins (reviewed in Dalmau et al, Lancet Neurol 2011, PMID: 21163445). The related autoimmune conditions lupus and Sjogren's Syndrome also involve the development of autoantibodies. The possibility that neuropsychiatric disorders can have molecular mechanisms in common with autoimmune disorders - for example, that psychosis involves an inflammatory or autoimmune component in some patients, or that immune molecules are re-used in the brain to underlie other important biological activities (Stevens et al., Cell 2007, PMID: 18083105) - could open novel therapeutic possibilities for neuropsychiatric disorders. At a genetic level, the strongest genetic associations of schizophrenia, lupus, and Sjogren's Syndrome to common genetic variation involve associations to genetic markers in the Major Histocompatibility Complex (MHC) locus. Bipolar disorder in some studies also associates with variation in or near the MHC locus, though less strongly than schizophrenia does. Intriguingly, the same specific SNPs appear to associate strongly with schizophrenia, lupus, and Sjogren's; these strongly associating SNPs span a genomic segment that includes the HLA class II genes (which have an important role in antibody production) and the complement component 4 (C4) genes. The specific genes and alleles responsible for these associations need to be completely defined, and the extent to which they represent shared or distinct genetic influences in neuropsychiatric and autoimmune illnesses needs to be clarified. The complement component 4 (C4A and C4B) genes are present in the MHC locus, between the class I and class II HLA genes. C4A and C4B commonly vary in genomic copy number and encode complement proteins with distinct affinities for molecular targets. The complex genetic variation at C4 - arising from many alleles with different numbers of C4A and C4B genes - has been challenging to analyze in large cohorts. We recently developed an approach to this problem based on imputation: people share long haplotypes with the same combinations of SNP and C4 alleles, such that C4A and C4B gene copy numbers can be imputed from SNP data (Sekar et al., Nature 2016, PMID: 26814963). In the current work, to analyze C4 in large cohorts, we developed a way to identify C4 alleles from whole-genome sequence (WGS) data, then analyzed WGS data from 1,234 individuals to create a large multi-ancestry panel of 2,530 reference haplotypes of MHC SNPs and C4 alleles that can then be imputed into still-larger cohorts for which SNP data are available. With this dbGaP submission, we make this reference panel available for other studies. Protocols and software for imputing C4 alleles into genome-wide SNP data, and for performing molecular analyses on the C4 genes (such as direct measurement of copy number from genomic DNA), can be found on the McCarroll Lab web site (http://mccarrolllab.org/resources). We are also working to create additional reference panels for imputation of C4 alleles that will be based on still-larger and more diverse population samples; links to these will also be available on the McCarroll Lab web site as we create and validate them.

  Study phs001992

• MP2PRT: Comprehensive Genomic Profiling to Identify Alterations Associated with Relapse for NCI Standard Risk (SR) B-Lineage ALL and NCI High Risk (HR) B-Lineage ALL with Favorable Genetic Features

  The Molecular Profiling to Predict Response to Treatment (MP2PRT) program is part of the NCI's Cancer Moonshot Initiative. The aim of this program is the retrospective characterization and analysis of biospecimens collected from completed NCI-sponsored trials of the National Clinical Trials Network and the NCI Community Oncology Research Program. This study, titled "Comprehensive Genomic Profiling to Identify Alterations Associated with Relapse for NCI Standard Risk (SR) B-Lineage ALL and NCI High Risk (HR) B-Lineage ALL with Favorable Genetic Features," is one of the selected studies under this program. For this study, genomic characterization (WGS 30X, WXS, Total RNAseq) was performed on NCI Standard Risk B-lineage ALL patients who relapse and subsets of NCI High Risk B-lineage ALL patients who relapse as well as two non-relapse control cases for each relapse case. It was hypothesized that the comprehensive characterization of these sample sets will allow the identification of somatic genetic features that will facilitate early intervention to improve cure rates for those enrolled on future trials. Data were generated and genetic subtype was integrated with clinical variables, including age, presenting white blood cell count, sex, race, and levels of minimal residual disease at the end of induction. Additional secondary alterations were identified and included if they occurred in more than 10 patients. The study has been completed and a manuscript has been prepared.

  Study phs002005

• Pediatric Investigation for Genetic Factors Linked with Renal Progression (PediGFR)

  The Pediatric Investigation for Genetic Factors Associated with Renal Progression (PediGFR) (RO1-DK082394) is an international collaborative study among three large prospective cohort studies of children with chronic kidney disease. The participating parent cohort studies are the Chronic Kidney Disease in Children (CKiD), the Effect of Strict Blood Pressure Control and ACE Inhibition on CRF Progression in Pediatric Patients (ESCAPE), and the Cardiovascular Comorbidity in Children with Chronic Kidney Disease (4C) study. In these cohorts, pediatric subjects with CKD have been prospectively followed with standardized measurements for renal progression. The dbGaP data upload will utilize the structure of sub-studies to include the genotype and baseline phenotype for the three cohorts, as well as the RBC trait and anemia data for a sub-study under PI Susan Furth: Role of Genetic Variation in the Anemia of Chronic Kidney Disease (K24DK078737). In brief PediGFR is a prospective study of children with chronic kidney disease (CKD) to determine genetic factors associated with kidney function measured by the estimated glomerular filtration rate (eGFR) by Schwartz equation. The PediGFR_v2 Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000842 PediGFR_v2 Cohort. phs000843 4C phs000650 CKiD phs000844 ESCAPE

  Study phs000842

• First datasets available in the Federated EGA Network

  In February 2024, a great milestone was reached for the human omics data community: the first datasets are now available in the Federated European Genome-phenome Archive (FEGA). These datasets - hosted by national nodes in Poland, Norway, and Sweden - are discoverable in the EGA portal and accessible according to national laws. These datasets include: From FEGA Poland - The Genomic Map Of Poland From FEGA Norway - CRCbiome: Gut metagenome of Norwegian screening participants using FIT sampling Also from FEGA Norway - Single cell transcriptomics in expanded Tregs of APS-1 patients From FEGA Sweden - A Combined Omics and Tissue Biobank for Paediatric Cancers The establishment of these datasets represents a significant step towards achieving the broader objectives of the FEGA; to facilitate the sharing of high-quality human genomic and phenotypic data across borders. “The value for users is twofold: it becomes easier to make data available securely compared to storing data locally, and data becomes easier to find for other researchers. The possibility of reuse improves the chances of both verifying scientific discoveries and reaching groundbreaking conclusions, of benefit to the research community and later also patients,” said Anna Hagwall, project manager and head of human data at FEGA Sweden, NBIS. About Federated EGA FEGA was launched in 2022 as a network to store and lawfully share sensitive human omics data safely. It relies on the technology originally developed by the EGA and support from ongoing collaborations with ELIXIR - a European life sciences infrastructure. FEGA has contributed to and benefitted from the implementation of community standards for sensitive data management including those developed by the Global Alliance for Genomics and Health (GA4GH). “The FEGA concept and the development of the Nordic FEGA nodes have been made possible thanks to several projects coordinated by NeIC,” said Kjell Petersen, FEGA Norway technical lead. Managing human omics data is challenging due to its sheer size and privacy concerns, often resulting in restrictions on how and where sensitive data can be shared. The FEGA network follows a federated data access model whereby sensitive data is stored securely within a local or national jurisdiction, while discovery across the network for data of interest is enabled via a central portal. As of February 2024, the FEGA network comprises seven European national nodes with tens of additional national partners working towards establishing a FEGA node. As the FEGA network continues to onboard nodes from around the world, populated with more and more data, we move closer to a vision of a truly global resource for discovery of and access to sensitive human omics data to accelerate disease research and improve human health. "The Federated EGA network is entering a key phase where the first research datasets are now available across the network. In coming years, we look forward to expanding these datasets to cover key areas such as cancer and rare diseases for the benefit of patients" said Thomas Keane, Group Leader at EMBL-EBI.

  Blog first-datasets-available-in-Federated-EGA

• GCAT | Genomes for life: cohort study of the genomes of Catalonia

  The GCAT Study have recruited 20 000 participants aged 40–65 years. Participants who agreed to take part in the study completed a self-administered computer-driven questionnaire, and underwent blood pressure, cardiac frequency and anthropometry measurements. For each participant, blood plasma, blood serum and white blood cells are collected at baseline. A total of 5459 genomic profiles have been characterised by comprehensive genotyping. Genome-wide genotypes have been generated using Illumina Infinium SNP-bead array technology. We chose the Multi-Ethnic Global (MEGAEX, V.2) consortium array, a multipurpose, multiethnic genotyping array with two million selected markers (including previously described germline mutations, insertions-deletions (InDels) and SNPs).We have strictly followed the standard manufacturer recommended automated protocol for the Infinium HTS Assay scanned with a HiScan confocal scanner (Illumina, San Diego, California, USA). Genome Studio V.2011.1 has been used for raw data analysis. Genotyping was performed at the Genomics and Bioinformatics Unit of the PMPPC Institute for Health Science Research Germans Trias i Pujol, in Badalona, Spain. Future plans The first follow-up study started in December 2017 and will end by March 2018. Residences of all subjects will be geocoded during the following year. Several genomic analyses are ongoing, and metabolomic and genomic integrations will be performed to identify underlying genetic variants, as well as environmental factors that influence metabolites. http://dx.doi.org/10.1136/bmjopen-2017-018324

  Study EGAS00001003018

• SNP Genotype Data: Subpopulations of Filipino, Malaysian, and Papua New Guinea

  In the context of the study 'Exploring Adaptive Phenotypes for the Human Calcium-Sensing Receptor Polymorphism R990G,' this repository contains 11 VCF files. Each file includes genetic data from 22 autosomes, representing distinct subpopulations. The subpopulations are as follows: Malaysian: Aeta (15 samples) Agta (11 samples) Batak (10 samples) Mamanwa (6 samples) Filipino: Jehai (13 samples) Kintaq (6 samples) Temiar (5 samples) Papua New Guinea: Highlands (2 samples) Koinambe (10 samples) Kosipe (10 samples) Sepik (2 samples) The numbers in parentheses indicate the sample size for each respective subpopulation.

  Study EGAS50000000044

• Genomic Sequencing of Lung Adenocarcinoma

  Lung carcinoma is the leading cause of cancer death in the United States and world-wide; lung adenocarcinoma is the most common cause of lung cancer. Pilot studies of lung adenocarcinoma with hybrid-capture based whole exome sequencing will enable us to identify new targets for therapy and improve diagnosis. We will analyze a blend of whole exome and whole genome sequencing data as well as copy number and somatic mutation calls for 200 tumor and matched normal controls. When completed this study will represent the most comprehensive lung adenocarcinoma genome dataset to date.

  Study phs000488

• Performance Characteristics of Selective Targeted Enrichment in Genetic Diagnostic Testing

  The Nex-StoCT and ACMG recommend that validation of an NGS-based diagnostic test include performance test characteristics for assay accuracy, analytical sensitivity and specificity, reproducibility and repeatability. To measure these parameters for the GEDi capture and sequencing test, 4 samples (three randomly selected patient samples and the NA12878 HapMap sample) were prepared and sequenced in triplicate on each of three separate days. We also performed WES and SNP array genotyping analyses of these 4 samples using Agilent V4+UTR whole exome enrichment kit and Illumina Omni 2.5 SNP arrays, respectively.

  Study phs000798

• Transcriptome and TCR Sequencing of T Cells from Metastectomies

  T cells were sorted from metastatic tumors (colon, rectal, breast, anal, melanoma primary histologies) following tumor dissociation and single-cell sequencing was performed (RNAseq and TCRseq). For samples from tumors that had been previously studied, cells were analyzed comparing known neoantigen-reactive TCR-expressing cells to other T cells. For samples without previously identified neoantigen reactivity, TCRs were predicted on the basis of T cell transcriptomic states. To determine candidate neoantigen screening, exome and RNA sequencing were performed on fragments of matched tumors from which T cells were sequenced   

  Study phs002748

• The Vaginal Microbiome in Reproductive Age Women

  The focus of this cross-sectional study was to characterize the vaginal microbiota of asymptomatic, sexually-active, and reproductive-age women representing four self-reported ethnic groups (White, Black, Asian, and Hispanic). Each woman self-collected two mid-vaginal swabs. The first swab was used to prepare a vaginal smear for Nugent gram stain analysis. The second swab was used for DNA extraction, 16S rRNA gene amplicon sequencing, and detection of Candida albicans. In addition, participants measured vaginal pH and completed a detailed questionnaire on sexual health and behaviors.

  Study phs001909

• Identification of Putative Neoantigens in Stage III Melanoma

  This study of three metastatic melanoma patients utilized exome sequencing and RNA sequencing to help identify putative neoantigen peptides that could be further validated by standard immunological assays before design of a personalized vaccine. For each set of neoantigens identified and verified by standard assays, we designed GMP peptides that correspond to the top neoantigens, then used these to condition dendritic cell isolates from each patient. The conditioned dendritic cells were used as the vaccine in three rounds of vaccination, followed by monitoring for T cell memory response to each of the neoantigens.

  Study phs001005

• Fetal Chorioamniotic Membranes Show Molecular Changes in Placenta Previa and Placenta Accreta Spectrum

  Placenta previa and the placenta accreta spectrum (PAS) are understudied pregnancy disorders with serious consequences for both mother and infant. To better understand the molecular and cellular etiologies of these diseases, we performed 3SEQ of formalin-fixed paraffin-embedded (FFPE) fetal chorioamniotic membrane samples from PAS, previa, and gestationally age-matched spontaneous pre-term birth samples to identify molecule signatures of these diseases. These samples were subsequently validated using a second validation cohort of previa, PAS, and control patients. FFPE archival samples provide opportunities for retrospective molecular investigation of many diseases.

  Study phs002075

• Patient Microbiome and Surgical Site Infection in Spine Surgery

  Single center, prospective cohort study on the contribution of the preoperative patient microbiome and resistome to surgical site infection (SSI) and resistance to surgical antibiotic prophylaxis in spine surgery. The samples in this entry comprise a subset of patients for whom paired preoperative microbiome samples and postoperative wound culture isolates were obtained. These samples were analyzed by Illumina-based sequencing of metagenomic libraries enriched for the SSI pathogen of interest using the GenCap-Seq methodology (PMID: 36121157) to identify instances of endogenous infection with strains present in the preoperative microbiome.

  Study phs003358

• Long read mRNA sequencing of human neural retinal samples - Usher syndrome transcript landscape

  Long-read (PacBio) RNA sequencing dataset of three neural retinal samples. Three PacBio libraries were prepared according the 'standard workflow' optimized for sequencing transcripts centered around 2kb. Additionally one Library (input HNR_S2) was prepared according an optimized 'long workflow' to enrich for larger transcripts up to >10kb. To further enhance the capture of full-length transcripts for USH2A and ADGRV1 (USH2C) genes, we also employed a targeted enrichment approach using the Samplix Xdrop System, followed by PacBio long-read sequencing. USH2A and ADGRV1 enrichment was performed by targeting '5- mid and 3' targets of the respective genes. Finally, we also added ONT (Oxford Nanopore technology) long-read mRNA sequencing of three independent neural retina samples. These data were used for the validation of events observed from the Iso-Seq and Samplix data. The ONT datasets contain sequencing data of the Usher-associated genes. Files are raw BAM, and CRAM format files generated by a Sequel II machine. Additionally, the ccs3 BAM format files are included.

  Dataset EGAD50000000720

• NHLBI TOPMed: Women's Health Initiative (WHI)

  This is Whole Genome Sequencing data from the TOPMed participation of the Women's Health Initiative. Approximately 11,100 subjects were involved in this study: approximately 1,100 cases of VTE, 4,000 cases of ischemic stroke, 900 cases of hemorrhagic stroke, and 5,100 controls. Summary level phenotypes for the WHI Cohort study participants can be viewed at the top-level study page phs000200 WHI Cohort. Individual level phenotype data and molecular data for all WHI top-level study and substudies are available by requesting Authorized Access to the WHI Cohort study phs000200.

  Study phs001237

• A Comprehensive Genomic Study of Pediatric Malignancy

  Malignancy remains the leading cause of disease-related death in children. DNA sequencing studies have shown a paucity of actionable genomic alterations and a low mutation burden across pediatric cancers at diagnosis. We perform a comprehensive genomic and epigenomic analysis of pediatric tumor and normal tissues using next-generation sequencing to identify molecular fingerprints and targets for diagnosis, prognosis, and development of novel therapeutic methods. This study also represents one of the largest of its type to date and provides a rich genomic dataset for the pediatric cancer research community.

  Study phs001928

• Arcagen - Extra-pulmonary neuroendocrine tumour or cancer grade 3 (NET / NEC G3) domain

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here were are submitting the dataset that contains NGS files from patients with extra-pulmonary neuroendocrine tumour or cancer grade 3 (NET / NEC G3) (n=85).

  Study EGAS50000000644

• scRNA-seq of human follicular lymphoma and lymph node

  Cryopreserved cells from human nodal follicular lymphoma and lymph node samples were thawed and processed for scRNA-seq analysis. CD3+ CD19− 7-AAD− live T cells (six FL samples from the Original cohort) or 7-AAD− whole live hematopoietic cells (five lymph node and nine FL samples from Validation cohort 1) were sorted using a FACS Aria II or III instrument (BD Biosciences). To generate single-cell emulsions, 6,000–10,000 live cells were loaded into the 10X Genomics Chromium Controller for single-cell partitioning, along with the reverse transcriptase reagent mixture and 3' or 5' gel beads. Sorted T or whole hematopoietic cells were converted to barcoded scRNA-seq libraries using 10X Genomics Chromium single cell 3' reagent kits (v3) for the Validation cohort 1, 5' reagent kits (v1) for the Original cohort, according to the manufacturer’s instructions. The libraries were sequenced on an Illumina HiSeq X Ten or NovaSeq X Plus system, mapped to the human genome (build GRCh38), and demultiplexed using CellRanger pipelines (v3.1.0, 10x Genomics).

  Dataset EGAD50000001143

• Single-cell targeted DNA-sequencing and protein sequencing

  We performed single-cell targeted DNA sequencing (MissionBio) on 13 high hyperdiploid B-ALL patients at diagnosis to study the genetic heterogeneity. For a number of patients single-cell surface protein antibody sequencing was added (DAB-seq) to better characterize the different cell types. Furthermore, additional samples during treatment were collected and analysed for some patients. In this way we want to study the clonal heterogeneity of these B-ALL samples, based both on mutations and CNVs, and identify resistant clones that could be targeted after relapse.

  Study EGAS50000000580

• Sequencing of in vitro generated macrophages and T cells

  Monocyte derived macrophages were polarised into M1 or M2 using IFNg+ ILP or IL-4 respectively (n =4) . Pan T cells were cultured with or without IL-2 for 4 days (n=4 - 6). Pan T cells were co-cultured with THP1 tumour cells for 20 hours in the presence or absence of ImmTAC molecules and in the presence or absence of M2 macrophages. Sorted T cells and macrophage populations prior and post co-culture were analysed by bulk RNA sequencing (60 million reads per sample) using the Illumina NovaSeq system.

  Study EGAS50000000837

• FEGA Sweden Helpdesk

  FEGA Sweden is an archive for storing and sharing all kinds of data resulting from biomedical research projects. As a national node of the Federated European Genome-phenome Archive (FEGA), we enable researchers to store their data in Sweden in a way that meets the requirements of the General Data Protection Regulation (GDPR). Any data submitted to the archive is subject to controlled access, meaning access to the data only will be granted after a formal application procedure. Using FEGA Sweden for storing and sharing data is free of charge for academic users affiliated with a Swedish university. However, the university must have a signed Data Processing Agreement (DPA) with Uppsala University. The current list of universities with a signed DPA can be found here: https://fega.nbis.se/submission/complying-with-gdpr.html. FEGA Sweden is hosted by the National Bioinformatics Infrastructure Sweden (NBIS), which legally is part of Uppsala University. NBIS forms the bioinformatics platform at SciLifeLab and constitutes the Swedish node of the European organisation ELIXIR. Contact the FEGA Sweden Helpdesk at fega-sweden@nbis.se for further questions.

  Dac EGAC50000000077