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• A sequence-based genetic dissection of human immune cell types and implications for immune-related disease.

  The immune system is an intricate biological network mediating interactions with other organisms while preserving the integrity of our tissues. By mounting appropriate responses it protects us from a vast range of pathogens while inadvertent immune system attacks on self result in autoimmune diseases. The project aims to discover whether and to what extent the behaviour of the immune system is genetically regulated and to detect the relationships of diverse immune cells with autoimmunity. The project consists of the genetic analysis using up to ~8.2 Million variants, deriving from high density genotyping data and low pass whole genome sequencing, and quantitative levels of 95 cell types encompassing 272 immune traits, in a cohort of 1,629 individuals from four clustered Sardinian villages belonging to the SardiNIA/ProgeNIA study.

  Study EGAS00001000574

• dbGaP Collection: NHLBI Heart Failure Related dbGaP Data (No IRB requirement)

  The National Heart, Lung, and Blood Institute (NHLBI) Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research has concluded. The NHLBI will continue to make this collection of data available to the research community.Past information regarding the Data Collection for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research is below.The National Heart, Lung, and Blood Institute (NHLBI), part of the National Institutes of Health (NIH), is inviting novel Solutions for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research. The goal of the challenge is to foster innovation in computational analysis and machine learning approaches utilizing large-scale NHLBI-funded datasets to identify new paradigms in heart failure research. The challenge aims to address the need for new open source disease models that can define sub-categorizations of adult heart failure to serve as a springboard for new research hypotheses and tool development in areas of heart failure research from basic to clinical settings. NHLBI has a history of making considerable investments in the creation of deep data resources including: long-standing, deeply-phenotyped epidemiological cohorts, innovative clinical trials, and large-scale precision medicine efforts that have generated whole genome sequencing and "other omics" data for more than one-hundred thousand individuals. To provide challenge participants with streamlined access to data across NHLBI's numerous studies containing heart failure data, the NHLBI has created this dbGaP study collection. Data access for this collection is controlled by NHLBI's Data Access Committee. Challenge participants are required to follow the use restrictions and acknowledgement instructions from the original dataset(s). Please note that the data in this collection are not harmonized across studies or otherwise altered from the original study. The NHLBI Big Data Analysis Challenge: Heart Failure Data Collection contains all NHLBI studies currently in dbGaP that contain data that may be relevant to research on heart failure. The studies in this collection are approved for General Research Use (GRU), Health/Medical/Biomedical Use (HMB), or Disease-Specific Use (DS) that permits research on heart failure. These studies span a variety of study designs, inclusion and exclusion criteria, sample sizes, and provide a wide breadth and depth of phenotype data on study participants. The available genomic data in these studies also varies, including genotyping arrays, sequencing (targeted, exome, whole genome), and additional -omic data (e.g., RNA or metabolite profiles). Please refer to each study's individual accession page to learn more about how study data were collected. Challenge participants are reminded that in addition to dbGaP, NHLBI's Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) contains other studies that have collected data relevant to heart failure and may wish to utilize BioLINCC data in the development of their Solution. Please refer to the individual accession page for each study in this collection to learn more about the history of each study.

  Study phs001991

• Single-cell and spatial atlas of steatotic liver disease-related hepatocellular carcinoma

  This study consists of the spatial transcriptomics data generated by : 1. Visium CytAssist Spatial Gene Expression for FFPE (10x) for steatotic liver disease-associated hepatocellular carcinoma (SLD-HCC) (n=7) and non-SLD-HCC (n=5) 2. CosMxTM Human Universal Cell Characterization RNA Panel (1000-plex); NanoString, USA for n=4 SLD-HCC and n=4 non-SLD-HCC. The goal of this data is to compare SLD-HCC vs non-SLD-HCC as well as response to immunotherapy

  Study EGAS50000001034

• Next Generation Mendelian Genetics: Ehlers-Danlos Syndrome Type VIII

  The NHGRI Next Generation Mendelian Genetics project uses exome resequencing to identify variants in unsolved Mendelian diseases. Ehlers-Danlos syndrome Type VIII is a dominantly inherited connective tissue disorder that is distinguished from other forms of EDS by significant early-onset periodontal disease. Although the clinical phenotype is well delineated, the underlying molecular basis remains unknown. By studying a large family of affected and unaffected individuals with the EDS VIII by exome sequencing, we hope to identify unique regions of homology to assist in identifying the causative gene.

  Study phs000540

• The epigenetic landscape controlled by p63 in epidermal development

  Transcription factor p63 is a key regulator of epidermal keratinocyte proliferation and differentiation. Heterozygous mutations of TP63 encoding p63 cause a spectrum of developmental disorders. EEC syndrome is caused by point mutations in the p63 DNA-binding domain, and manifests ectodermal dysplasia with defects in the epidermis and epidermal related appendages, limb malformation and cleft lip/palate. Five hotspot mutations affecting amino acids, R204, R227, R279, R280 and R304, have been found in approximately 90% of the EEC population. Although the role of p63 in normal epidermal development and differentiation has been demonstrated, the molecular mechanism by which p63 mutations cause the epidermal phenotype in diseases is not yet understood. In the two related studies, we characterize p63 mutant keratinocytes (R204W, R279H and R304W) and p63 mutant iPSCs (R204W and R304W) and the molecular mechanisms underlying their differentiation defects.

  Study phs001737

• Epi4K: Gene Discovery in 4,000 Epilepsy Genomes

  The Epi4K project began in 2011 as an international, multi-center study that seeks to identify and characterize the genetic bases of complex epilepsies. The Center without Walls Epi4K project includes three cores and four scientific projects, as well as a steering committee comprised of the primary study investigators and representatives from the National Institute of Neurological Disorders and Stroke (NINDS). The three cores include: (1) The Administrative Core which handles the overall coordination of Epi4K activities; (2) The Sequencing, Biostatistics and Bioinformatics Core which is responsible for generating the next-generation sequence data, inferring the genetic variation in each of the study participants, and performing the primary analyses to identify epilepsy genes; and (3) The Phenotyping and Clinical Informatics Core which verifies and archives all the phenotypic data from each study participant. The proposed number of patients to be sequenced and analyzed in the scientific projects is a minimum of 4,000; thus the Center was named "Epi4K: Gene Discovery in 4,000 Genomes". Project 1 addresses the genetics of rare and severe childhood epilepsies, including epileptic encephalopathies (infantile spasms and Lennox-Gastaut syndrome), and malformations of cortical development (periventricular nodular heterotopia and polymicrogyria). Exome and genome sequence data generated from DNA collected from patients will be screened for mutations (single nucleotide substitutions, small insertion-deletions, and copy number variations) that cause or contribute to the diseases. Project 2 is focused on genetic discovery in multiplex families. This study will use next-generation sequencing to identify genomic variation that influences risk for common subtypes of epilepsy including idiopathic generalized epilepsy and nonlesional focal epilepsy. Project 3 seeks to identify genetic determinants of prognosis in patients with a range of epilepsy disorders. This study will study established epilepsy cohorts with well-characterized data on seizure outcome to look for relationships between genetic variation and pharmacological control of seizures. Project 4 will use next-generation sequencing data (exome and genome) to screen for epilepsy-associated copy number variation across all Epi4K projects using novel computational algorithms.

  Study phs000653

• Exome Sequencing of Gastric Cancer

  GASTRIC cancer (GC) is a heterogeneous disease with multiple environmental etiologies and alternative pathways of carcinogenesis. Beyond mutations in TP53, alterations in other genes or pathways account only for small subsets of the disease. We performed exome sequencing of 22 GCs and identified mutated genes and pathway alterations previously unreported: genes involved in chromatin modification were commonly mutated. A downstream validation study confirmed frequent inactivating mutations and/or protein deficiency of the SWI/SNF chromatin remodeling complex gene ARID1A in 83% of GCs with microsatellite instability, 73% of GCs with Epstein-Barr virus (EBV) infection, and 11% of non-EBV microsatellite stable GCs. The mutation spectrum of ARID1A differs between molecular subtypes and the mutation prevalence is negatively associated with mutations in TP53. Clinically, ARID1A alterations were associated with better prognosis in a stage-independent manner. These results revealed the genomic landscape and highlighted the importance of chromatin remodeling in the molecular taxonomy of GCs.

  Study EGAS00001000153

• Single_cell_analysis_of_cytokine_induced_T_cell_states

  We isolated T cells from healthy platelet donors and cultured them in resting and stimulated conditions with addition of a range of cytokines. We performed scRNA sequencing to assess the variability of polarization in different cytokines treated cells. Cytokines affect T cell responses by polarising them to different phenotypes. Given that the inflammation and and autoimmune tissue distruction is driven by the local production of cytokines, we investigated cytokine induced changes in T cells by using a combination of immunological and genomics approaches. To characterize, the efficacy of cytokine induced porization, here we stimulated naive and memory CD4+ T cells in the presence of cytokine polarizing coctails and profiled single cell transcriptome five days following polarization. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001003215

• Genomic analysis of primary plasma cell leukemia reveals complex structural alterations and high risk mutational patterns

  Primary plasma cell leukemia (pPCL) is a rare and aggressive form of multiple myeloma (MM) that is characterized by poor overall survival despite advances in anti-MM therapy. The disease biology as well as molecular mechanisms that distinguish pPCL from non-pPCL MM remain poorly understood. In an attempt to identify key biological mechanisms that result in the aggressive pPCL phenotype we performed whole exome sequencing in 23 patients with newly diagnosed pPCL. The results reveal an enrichment of complex structural changes and high risk mutational patterns in pPCL that explain, at least in part, the aggressive nature of the disease. In particular pPCL patients with traditional low risk features such as translocation t(11;14) or hyperdiploidy accumulated adverse risk genetic events that could account for the poor outcome in this group.

  Study phs002022

• Mutational Landscape of MCPyV-Positive and MCPyV-Negative Merkel Cell Carcinomas

  Merkel cell carcinoma (MCC) is an aggressive neuroendocrine carcinoma of the skin most commonly found on the sun-exposed skin of older Caucasian adults. Roughly one-third of patients with MCCs die of the disease; therefore, MCC is the most lethal skin cancer on a case-by-case basis. 49 cases were studied, and putative cancer driver gene mutations and tumor antigens in both MCPyV-negative and MCPyV-positive MCCs were identified.

  Study phs002515