4002 results for "*geneti*"

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• Immunophenotyping in a COVID-19 Cohort (IMPACC) Transcriptomics and Genotyping Assays

  IMPACC (IMmunoPhenotyping Assessment in a COVID-19 Cohort) is a prospective longitudinal cohort study (NCT04378777) launched in May 2020 in response to the worldwide pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was funded by the National Institute of Allergy and Infectious Diseases (NIAID) of the National Institute of Health (NIH). Patient enrollment and sample analysis involved 20 hospitals associated with 15 U.S. biomedical research centers and 11 centralized Core immunoassay laboratories.The study aimed to enable the identification of potential biomarkers and inform future therapeutic interventions using a longitudinal approach encompassing the whole disease course for a comprehensive understanding of the contributions of the pathogen and host immune response in modulating the manifestations, severity, and post-acute sequelae of the infection. IMPACC enrolled close to 1200 adult symptomatic, molecularly confirmed hospitalized COVID-19 patients in the study within 48 hours of their hospital admission. Clinical data and biological samples (blood, mid-turbinate nasal swabs, and esophageal aspirant) were collected according to minimal risk guidelines at enrollment and on days 4, 7, 14, 21, and 28. Biological samples were collected at 3-month intervals up to 12 months after hospital discharge to assess functional and immunologic recovery measures. Sample collection, processing, and storage procedures were standardized across sites, and samples were transported to centralized assay-specific core laboratories (Core Labs) in batches for testing and analysis. The description of outcome severity was not limited to survival versus death but encompassed a clinical trajectory approach using 5 groups leveraging longitudinal data based on time in the hospital, disease severity by ordinal scale based on the degree of respiratory illness, and presence or absence of limitations at discharge. Disease severity was assessed based on the degree of respiratory illness using a 7-point ordinal scale adapted from the World Health Organization COVID-19 and NIAID disease ordinal severity scales. DNA for genetic analyses was collected from whole blood at a single time point. To identify any genomic determinants of severe COVID-19 disease, single-nucleotide polymorphism (SNP) genotyping and exome sequencing were conducted to assess genetic variants associated with individual susceptibility to severe disease. In addition, IMPACC included bulk transcriptomic analysis of upper airway (nasal swaps) samples, lower airway (esophageal aspirant) samples, and peripheral blood mononuclear cells (PBMCs) to evaluate dynamic changes in cellular composition and cellular response during the course of the disease. Reads were aligned to the GRCh38 human reference genome. Additional information for the IMPACC study has been submitted to The Immunology Database and Analysis Portal (ImmPort) under study accession SDY1760. Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Dr. Steven Kleinstein (steven.kleinstein@yale.edu).

  Study phs002686

• DAC_RNA-seq of murine osteosarcoma cell line genetically modified for CYR61

  Data access committee for RNA-seq of murine osteosarcoma cell line genetically modified for CYR61

  Dac EGAC50000000352

• T-bet+ CXCR3+ B cells drive hyperreactive B-T cell interactions in multiple sclerosis

  Data Access Committee means the following members of the Institute of Experimental Immunology, UZH, and investigators of the publication, to which the Data Access refers and who are responsible for making the data access decisions for the genotype and gene expression generated by UZH or respectively the epigenetic data, which had been generated at Karolinska Institute. Christian Münz, PhD; Co-Director of Institute of Experimental Immunology, University of Zurich Roland Martin, MD; Affiliated Group Leader (to Institute Münz) of Institute of Experimental Immunology Institute of Experimental Immunology Ivan Jelcic, PhD, Roche Pharma Research and Early Development (pRED), Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland Maja Jagodic, PhD, Department of Clinical Neuroscience, Karolinska Institutet, Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden

  Dac EGAC50000000464

• Cryptococcosis in Previously Healthy Adults

  Cryptococcus is a fungus that causes infections most commonly in immunocompromised patients, such as those with AIDS and solid organ transplant recipients and is currently responsible for an estimated 15% of all AIDS-related deaths globally. However, in developed countries, approximately one-third of cases fall outside these groups such that cryptococcal meningoencephalitis (CM) has become the most common cause of non-viral meningitis in the U.S. Within the U.S., approximately 15-20% have no readily identifiable immune defect and cryptococcal infection in these hosts has a mortality rate of 30-50% despite optimal antifungal therapy. NIH Clinical Study Protocol 93-I-0106 (NCT00001352). The objectives of this protocol can be broadly categorized as: 1) Characterize the immunologic and genetic mechanisms predisposing to disease acquisition; 2) Understand the post-infectious inflammatory response and distinguish its consequences from those directly due to fungal growth; and 3) Management of post-infectious neuro-inflammatory syndromes associated with cryptococcal meningitis (CM). This protocol recruits patients who have microbiological evidence of cryptococcal neurologic or non-CNS disease (typically pulmonary or bone). Cerebrospinal fluid (CSF) and blood samples collected during clinical care are used to measure serum and CNS cellular and soluble cytokines as well as to perform in-situ immunohistochemistry. CSF and blood samples are also collected to measure transcriptional (gene expression), proteomic (protein), and lipidomic (lipids) changes that occur throughout disease and treatment. Observational data detailing audiological, ophthalmological and neurocognitive deficits in these patients is also recorded. We have recently described a post-infectious inflammatory syndrome (PIIRS) associated with cryptococcal meningoencephalitis (CM) which can be best described as a neuro-inflammatory state during which CM patients present with altered mental status (Montreal Cognitive Assessment Score As part of the protocol, we treat patients for either microbiological failure or neuroinflammatory sequelae by conventional therapies utilizing FDA-approved pharmaceuticals at FDA-approved doses. To understand and identify the predominant biological pathways responsible for PIIRS neuroinflammation, we examined patient CSF at baseline (at time of PIIRS diagnosis) and post-treatment with different FDA-approved pharmaceuticals at FDA-approved doses compared to CSF from non-PIIRS donors. Upstream pathway analysis of differentially expressed genes in the CSF of PIIRS patients revealed a prominent role for the JAK/STAT pathway in the pathogenesis of PIIRS and support the use of the JAK inhibitor, ruxolinib, as a pathway-instructed therapy to treat PIIRS patients. Data available through dbGaP: single cell RNA sequencing (scRNA-seq) data from CSF cells of a patient with PIIRS at the time of diagnosis and following treatment with steroids (1g solumedrol/day) and NanoString transcriptional data from CSF cells of patients with PIIRS at the time of diagnosis compared to CSF cells from non-PIIRS donors.

  Study phs003871

• Circulating, Cell-Free DNA Methylation Patterns Indicate Cellular Sources of Allograft Injury after Liver Transplant

  Post-transplant complications reduce allograft and recipient survival. Current approaches for detecting allograft injury non-invasively are limited and do not differentiate between cellular mechanisms. Here, we monitor cellular damages after liver transplants from cell-free DNA (cfDNA) fragments released from dying cells into the circulation. We analyzed longitudinal blood samples collected from patients at different time points after transplant. Sequence-based methylation of cfDNA fragments were mapped to an atlas of cell-type-specific DNA methylation patterns derived from 476 methylomes of purified cells. For liver cell types, DNA methylation patterns and multi-omic data integration show distinct enrichment in open chromatin and regulatory regions functionally important for the respective cell types. We find that multi-tissue cellular damage post-transplant recovers in patients without allograft injury during the first post-operative week. However, sustained elevation of hepatocyte and biliary epithelial cfDNA within the first month indicates early-onset allograft injury. Further, cfDNA composition differentiates amongst causes of allograft injury indicating the potential for non-invasive monitoring and timely intervention.

  Study phs003610

• Next Generation Sequencing to Predict Risk of Events from Coronary Artery Disease

  Coronary artery disease (CAD) and myocardial infarction (MI) remain the leading cause of death worldwide and in the US. In recent years, clinical studies that considered intermediate phenotypes (phenotypic or genomic data isolated between DNA and the main disease phenotype) have greatly enhanced our understanding of complex traits like CAD by enabling inference of biological networks from the combination of genetic and genomic datasets isolated from disease-relevant tissue(s). The NGS-PREDICT study used whole transcriptome sequence data generated from primary macrophages derived in vitro from venous blood that was obtained from CAD cases and non-CAD controls. This study provided a valuable resource for the validation of biomarkers identified in STARNET NGS data from macrophages obtained from patients with and without CAD. It also can be used as a reference dataset for the study of metabolic syndrome as well as other systemic inflammatory diseases.

  Study phs003883

• ATAC-seq in KMS11 vs TKO cells

  ATAC-seq to determine chromatin accessibility in t(4;14) Myeloma cell line KMS11 and KMS11 cells with knock-out of the translocated NSD2 allele.

  Study EGAS50000000076

• ChIP-seq in KMS11 and TKO cells

  Histone chIP-seq in t(4;14) Myeloma cell line KMS11 and KMS11 cells with knock-out of translocated NSD2 allele (KMS11 TKO).

  Study EGAS50000000077

• MicroC in KMS11 and TKO cells

  MicroC to show high resolution chromatin interactions in t(4;14) Myeloma cell line KMS11 and KMS11 cells with knock-out of translocated NSD2 allele (KMS11 TKO).

  Study EGAS50000000078

• Timing and trajectory of BCR-ABL1 driven chronic myeloid leukaemia

  Mutation of some genes provide fitness advantages that drive uncontrolled cell proliferation, leading to clinical manifestations of cancer. The discovery of the Philadelphia chromosome in chronic myeloid leukaemia (CML) provided the very first such genetic link to cancer and the hypothesis that this lesion provided an abnormal growth advantage to cells. However, little is known about the trajectory to CML, the rate of BCR::ABL1 driven clonal expansion, and how this impacts on disease presentation. Here, using whole-genome sequencing of 1013 single-cell-derived colonies from patients with CML, we reconstruct phylogenetic trees of haematopoiesis in 9 patients aged 22 to 81 years at diagnosis. The expected intronic breaks in BCR and ABL1 were not always observed, and out-of-frame exonic breakpoints in BCR, requiring exon skipping to derive BCR::ABL1 fusion transcripts, were noted in several patients. Apart from ASXL1 and RUNX1 mutations, additional somatic mutations in myeloid genes were generally present only in wild-type cells and did not contribute to the CML clone. Using phylogenetic analysis, we infer sustained explosive growth attributed to BCR::ABL1 fusion, with clonal expansions beginning 3-14 years (Cl 2-16 years) before diagnosis and annual growth rates exceeding 70,000% per year in some young patients with the most recent and rapid clonal expansions. Mutation rate was higher in BCR::ABL1-positive cells than in wild-type counterparts, together with markedly shorter telomere lengths, reflecting their excessive cell division history. Clonal expansion rates inferred from phylogenetic trees were in line with mutational signature patterns and telomere attrition, and inversely correlated with the time to diagnosis. Whole genome sequencing of advanced phase CML was characterised by genomic evolution within BCR::ABL1-positive cells. Our findings highlight the oncogenic potency of a single BCR::ABL1 fusion and its capacity to drive fast clonal outgrowth to cancer. These data contrast with the early-in-life, slow, and sequential clonal trajectories typical of most cancers, such as Philadelphia-negative myeloproliferative neoplasms, solid organ malignancies, and patterns of clonal expansion in healthy tissue ageing.

  Dataset EGAD00001015473

• Whole Genome Sequencing Consortium on Frontotemporal Dementia With Underlying TDP-43 Pathology

  Frontotemporal lobar degeneration (FTLD) is one of the leading causes of dementia in individuals younger than 65 years. The FTLD symptoms of most patients are not yet explained by mutations in the known FTLD genes (C9orf72, GRN, MAPT). Identifying genetic risk associated with the disease is key for developing disease models and new therapeutic avenues. We performed short-read whole-genome sequencing (WGS) on 19 neuropathologically normal individuals and 560 patients with FTLD, including 171 pathologically confirmed FTLD patients, 352 clinically diagnosed FTLD patients, and 37 autosomal dominant FTLD patients. Pathologically confirmed FTLD patients include FTLD with TDP43 inclusions (FTLD-TDP) and FTLD with FUS inclusions (FTLD-FUS), autosomal dominant FTLD patients include GRN (FTLD-TDP GRN) and C9ORF72 (FTLD-TDP C9ORF72) mutation carriers, clinically diagnosed patients include behavioral variant of frontotemporal dementia (bvFTD), frontotemporal dementia with amyotrophic lateral sclerosis (FTD-ALS), frontotemporal dementia with corticobasal syndrome (FTD-CBS), semantic variant of primary progressive aphasia (svPPA), and non-fluent variant of primary progressive aphasia (nfvPPA).

  Study phs003309

• Multiplexed scRNA-Seq Reveals Cellular and Genetic Correlates of SLE

  Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease. Knowledge of circulating immune cell types and cell states associated with SLE remains incomplete. We profiled over 1.2 million PBMCs (160 cases, 98 controls) with multiplexed single-cell RNA-seq (mux-seq). Cases exhibited prominent expression of type-1 interferon-stimulated genes (ISG) in monocytes, reduction of naïve CD4+ T cells that correlated with monocyte ISG expression, and expansion of repertoire-restricted cytotoxic GZMH+ CD8+ T cells. Cell-type-specific expression features accurately predicted case-control status and stratified patients into two molecular subtypes. We integrated dense genotyping data, mapping cell-type-specific cis-eQTLs and linked known and novel SLE-associated variants to cell-type-specific gene expression. These results demonstrate mux-seq as a systematic approach to characterize cellular composition, identify transcriptional signatures, and annotate genetic variants associated with SLE.

  Study phs002812

• Kids First: Whole Genome Sequencing Studies of Multiplex Nonsyndromic Cleft Lip/Palate Families

  Nonsyndromic cleft lip with or without cleft palate (NSCLP) is a common birth defect that affects approximately 135,000 newborns worldwide, and imposes significant medical, psychosocial and financial burdens to affected individuals and their families. Genetic variation in numerous genes has been associated with NSCLP, however the exact mechanisms by which they contribute to the condition remain largely unknown. Here, we will use whole genome sequencing and robust analytical approaches to systematically evaluate the causes of NSCLP in 923 individuals from large multigenerational families.

  Study phs002626

• Single Cell and Spatial Transcriptomics Studies of Fibrosis in Prospective Registry in IBD Study at MGH and GI Disease and Endoscopy Registry

  Stricturing disease or fibrosis is a common complication of inflammatory bowel disease (IBD), often requiring surgical intervention. This process is caused by the abnormal deposition of extracellular matrix in the context of inflammation, and thus involves crosstalk between multiple cell types including fibroblasts and immune cells. To understand the cellular interactions involved in fibrosis, we performed single cell and spatial transcriptomic analyses of biopsy or resection samples from IBD patients, diverticulitis patients or controls.For single cell analyses, intestinal samples were processed within three hours of collection by first stripping the epithelial layer with EDTA and then enzymatically digesting the underlying tissue. Cells from both the epithelial and tissue fractions were separately loaded in two channels on a 10x Chromium controller and libraries were generated with the 3'v3 Chemistry pipeline before sequencing on an Illumina sequencer. The resulting sequence data was demultiplexed and analyzed with the CellRanger pipeline to generate raw fastq files and processed gene-count matrices for each sample.For spatial transcriptomic analyses, intestinal resection samples were snap frozen in OCT (optimal cutting temperature embedding medium). Blocks were cut into 10μm sections in a cryostat and transferred to a 10x Genomics Visium slide v1. Spatially barcoded libraries were prepared according to manufacturer's instructions and sequencing on an Illumina sequencer. The resulting sequence data was processed with the SpaceRanger pipeline to generate fastq files and processed barcode-count matrices. Using the samples deposited here, we defined 68 fine-grained cell types across the ileum and colon of control and fibrotic intestinal tissues. We show that intestinal strictures were characterized by increased immune cells - including IgG+ plasma cells and CCR7hiCD4+ T cells - and inflammatory fibroblasts. We also define the transcriptional differences associated with fibrosis, with inflammatory fibroblasts in particular showing broad changes in gene expression. Spatial transcriptomics showed that key subsets colocalize within diseased tissues and identified additional populations such as interstitial cells of Cajal and enteric neurons. Further, we mapped gene expression onto intestinal biogeography, finding that known genetic risk loci are enriched within discrete spatial modules, defined by the presence of inflammatory fibroblasts and lymphoid follicles. Altogether, our datasets chart the key transcriptomic and cellular networks in stricturing CD and highlight the spatial organization of multicellular genetic risk factors.

  Study phs003943

• Sequencing of 3D Organoids Derived From Colorectal Cancer Patients

  This study focuses on the whole-exome sequencing (WES) of patient-derived organoids (PDOs) established from colorectal cancer (CRC) tumors collected at Columbia University. CRC remains a major cause of cancer-related mortality due to its metastatic progression and resistance to therapy. To model CRC at the patient level, we generated 3D organoid cultures from primary and metastatic tumors, preserving their genetic and phenotypic characteristics. The study cohort consists of 9 CRC patients with microsatellite-stable adenocarcinomas from the ascending, transverse, and descending colon, as well as the rectum, with differentiation statuses ranging from well to moderate and moderate-poor. Notably, for one patient, we generated organoids from both the primary tumor and matched liver metastases, allowing for a comparative analysis of tumor evolution. PDOs were derived from these tumors and subjected to WES at early passage to profile somatic mutations, copy number variations, and other genomic alterations to identify mutational signatures. Mutations identified in the PDOs were cross-referenced and confirmed with mutational data from the Columbia Solid Tumor Panel, which was conducted on all tumor tissues prior to organoid establishment. Molecular technologies employed include next-generation sequencing (NGS) for WES, enabling high-resolution characterization of the genomic landscape of CRC PDOs. WES of PDOs allowed us to classify tumor samples based on oncogenic mutations and mutation types, with a specific focus on PIK3CA. Notably, the efficacy of PI3Kα-specific pharmacologic inhibitors in suppressing organoid growth was dependent on the mutational status of KRAS and PIK3CA, underscoring the importance of genomic context in therapeutic response. The dataset available through dbGaP includes raw WES data from CRC PDOs.

  Study phs003965

• Childhood Cancer Data Initiative (CCDI): Comprehensive Genomic Sequencing of Pediatric Cancer Cases (CMRI/KUCC)

  This study provides paired tumor normal genomic sequencing data from ~ 200 children with cancer, including both solid tumors and leukemias, done by the Children's Mercy Research Institute (CMRI) and University of Kansas Cancer Center (KUCC). These data include whole genome sequencing (generally, ~20x), whole exome sequencing (generally, ~300x), bulk RNA sequencing (generally, ~80 million reads), and single-cell RNA and ATAC sequencing (>50,000 reads/cell). Additional phenotypic, pathologic, and genetic data, gathered clinically for these samples, are also provided.

  Study phs002529

• Genomic Changes in Breast Cancer Among Chinese Women in Hong Kong

  Recently, tumor sequencing and profiling analyses have improved molecular classification and refined existing breast cancer subtypes. However, epidemiologic data are absent in most somatic profiling studies even in extensively studied Western populations. The expansion of genomic studies to understudied populations with the integration of etiologic factors will allow the capture of a much wider range of genetic structure and mutagenic exposures associated with breast cancer risk. We therefore conducted a detailed molecular characterization of paired breast tumor/normal tissues using fresh frozen tissues collected from breast cancer cases in an ongoing breast cancer case-control study in Hong Kong. These analyses included whole genome (WGS)/exome sequencing (WES), targeted DNA panel sequencing, RNA sequencing (RNA-Seq), and genome-wide methylation profiling analyses.

  Study phs001870

• Neurodevelopment_Nantes_hospital

  The neurodevelopmental team in the genetics unit of Nantes hospital focus on the identification on new genes causing neurodevelopmental disorders through whole-genome and transcriptomics sequencing.

  Dac EGAC50000000542

• Heterogeneity in Lysosomal Storage Disorders

  Gaucher disease (GD) is an inherited lysosomal storage disorder caused by biallelic pathogenic variants in GBA1, which encodes glucocerebrosidase. Additionally, GBA1 variants are a well-established genetic risk factor for Parkinson's disease (PD), leading some PD research centers to incorporate GBA1 screening to identify patients who may benefit from targeted therapeutics. However, detecting GBA1 variants remains challenging due to the gene's high sequence homology with its pseudogene, which can give rise to complex recombinant alleles. This study evaluates the performance of Gauchian, a recently developed software tool for identifying GBA1 variants from whole genome sequencing (WGS) data. The assessment was conducted in a cohort of 90 individuals with GD and five GBA1 heterozygotes, all previously characterized through Sanger sequencing. While Gauchian successfully identified the most common genotypes, it demonstrated limitations in detecting rare or de novo variants due to its restricted internal database and heavy reliance on intergenic structural variants. These limitations led to misclassified homozygosity, incomplete genotyping, and undetected recombination events, ultimately reducing the tool's utility for comprehensive variant screening and precluding its application in diagnostic settings. The study dataset includes WGS from the 90 individuals used in the Gauchian pipeline. This data will be available through dbGaP to facilitate further research on GBA1 variant detection, genotype-phenotype correlations in GD and PD, and the development of improved bioinformatics tools for complex variant identification.

  Study phs003459

• Whole Exome Sequencing of Diffuse Large B-Cell Lymphoma

  We performed massively parallel whole exome sequencing of 55 primary tumor samples from patients with diffuse large B cell lymphoma (DLBCL) and matched normal tissue. We identified recurrent mutations in genes that are well known to be functionally relevant in DLBCL, as well as in genes for which a functional role in DLBCL has not been previously suspected. Significantly mutated genes include MYD88, CARD11, EZH2, CREBBP, as well as MEF2B, MLL2, BTG1, GNA13, ACTB, P2RY8, PCLO and TNFRSF14. Analysis of somatic mutations in patients with DLBCL also revealed that BCL2 mutations commonly occur in patients with BCL2/IgH rearrangements as a result of somatic hypermutation normally occurring at the IgH locus. The BCL2 point mutations are primarily synonymous, likely caused by activation-induced cytidine deaminase (AID)-mediated somatic hypermutation, and those non-synonymous mutations that are observed tend to be found outside of the functionally important BH domains of the protein, suggesting that strong negative selection against BCL2 loss-of-function mutations is at play. We further identified genes with mutations that are likely to be functionally relevant despite being mutated at a low rate. These genes include KRAS, BRAF and NOTCH1 as likely drivers of DLBCL pathogenesis in some patients.In order to facilitate additional in vitro and in vivo analyses of the discrete molecular clusters and associated targeted therapies in preclinical models, we also performed our subtyping analysis on 28 Diffuse Large B-Cell Lymphoma (DLBCL) cell lines. We performed whole exome sequencing (WES) on these cell lines to capture structural variants (SVs), from which we obtained full genetic characterization and segregation of these cell lines into our previously defined molecular clusters by DLBclass assignment. These analyses are available in an interactive DLBclass portal available to the public. Our data provide an unbiased view of the landscape of mutations in DLBCL. These data may point towards new targets for the treatment of DLBCL.

  Study phs000450

• UCSF Database for the Advancement of JMML - Integration of Metadata with Omic Data

  Juvenile myelomonocytic leukemia (JMML) is a rare and frequently fatal myeloproliferative/myelodysplastic disorder of early childhood with an estimated incidence of 1.2 cases per million. It is associated with a spectrum of diverse outcomes ranging from spontaneous resolution in rare patients to transformation to acute myeloid leukemia in others. The overwhelming majority of JMML patients (~95%) will harbor mutations in canonical Ras pathway genes, including NF1, NRAS, KRAS, PTPN11, and CBL. As Ras proteins are mutated in more than 30% of human cancers, the information gleaned from the study of JMML has provided insights into Ras signaling in cancer as well as a group of congenital diseases with tumor predispositions known as the “Rasopathies”. While oncogenic Ras is one of the most common mutations in human cancer, it remains one of the most vexing targets for efficacious therapy. To better understand this disease, a JMML tissue bank was established at UCSF that allows for consenting of subjects, biobanking of tissue and collection of follow up data from patients both locally and at other institutions. Through the collection and analysis of specimens, knowledge about the genetic, epigenetic, and biochemical basis of JMML has been gained. This integrated database will enable future JMML research, and importantly, additional Ras/MAPK pathway research by depositing linked, processed data to well annotated anonymized patients in an easily accessible online database

  Study phs002504

• National Heart, Lung, and Blood Institute (NHLBI) Bench to Bassinet Program: The Pediatric Cardiac Genetics Consortium (PCGC) Study

  Multi-center, prospective observational cohort study of individuals with congenital heart defects (CHD). Phenotypic data and source DNA derived from 10,000 probands, parents, and families of interest are being collected to investigate relationships between genetic factors and phenotypic and clinical outcomes in patients with CHD. Phenotype data will be stored at dbGaP, while molecular and sequence data will be stored at BioData Catalyst. The PCGC Cohort is utilized in the following dbGaP substudies. Please click on the following substudies below or in the "Substudies" section of this top-level study page phs001194 PCGC Cohort. phs000571 PCGC: whole exome sequences, whole genome sequences, targeted sequences, MIP sequences, and SNP array data phs001843 PCGC-CMG Collaboration: whole genome sequences The Gabriella Miller Kids First Pediatric Research Program (Kids First) subset of the PCGC project (phs001194) is now accessible through a separate dbGaP study accession: phs001138. To access this dataset, please submit a Data Access Request (DAR) for phs001138. Approval of this DAR will be expedited for approved users of phs001194. To learn about other Kids First datasets visit https://kidsfirstdrc.org/.NHLBI's TOPMed program has provided additional Whole Genome Sequencing for PCGC participants - that data is accessible through a separate dbGaP sudy accession: phs001735. Access to this data set should be requested through a Data Access Request (DAR) for phs001735.

  Study phs001194

• Clinical and Genetic Evaluation of Individuals with Undiagnosed Disorders through the Undiagnosed Diseases Network (UDN)

  The National Human Genome Research Institute and the NIH Clinical Center established the intramural Undiagnosed Diseases Program (UDP) in 2008 to make progress in uncovering, understanding, and treating rare disorders. Based on the success of the UDP, the NIH Common Fund established the Undiagnosed Diseases Network (UDN) in FY 2013 (Phase I, 9/16/2015-8/31/2018) to achieve this type of cross-disciplinary approach to disease diagnosis in academic medical centers around the United States. The NIH Common Fund expanded the network in 2018 (Phase II, 9/1/2018-6/20/2023) to increase the availability of diagnostic services, foster opportunities for collaboration between laboratory and clinical investigators, provide resulting data and protocols to the broader community, and assess development of a sustainable national resource after Common Fund support ends. The UDN transitioned from Common Fund in 2023. The National Institute of Neurological Disorders and Stroke (NINDS) will oversee the Network in Phase III, which launched in July 2023, with help from 17 different NIH Institutes and Centers along with the NIH Office of the Director. With help from patients, family members, patient advocacy groups, a Data Management and Coordinating Center (DMCC), several Clinical Sites, and other stakeholders, the NIH envisions the UDN evolving into a larger, diverse, and self-sustained network that fosters scientific discovery and provides expert diagnostic services for undiagnosed patients across the nation. The overarching goals of the UDN in Phase III include: Continuing the proven success of the UDN in improving the clinical evaluation of difficult-to-diagnose patients using a collaborative team approach and investigating and validating promising new diagnostic technologies. Facilitating research into the etiology of undiagnosed diseases by collecting and sharing standardized, high-quality clinical and laboratory data including genotyping, phenotyping, and documentation of environmental exposures. Promoting a broader integrated and collaborative community across multiple Clinical Sites and among laboratory and clinical investigators prepared to investigate the genetic, pathophysiologic, cell biologic, and molecular mechanisms underpinning these difficult-to-diagnose conditions.

  Study phs001232

• IDH mutant Glioma methylation analysis and prognostic signatures

  Study EGAS00001006961

• Multi-Omics Study of Lung Cancer in Smokers From EAGLE

  EAGLE (Environment And Genetics in Lung cancer Etiology) is a population-based case-control study examining the full spectrum of lung cancer etiology from smoking initiation, smoking dependency to lung cancer development and outcome. It combines a traditional molecular epidemiology design with more integrative approaches by examining epidemiological, molecular, and clinical data together. To comprehensively investigate the effect of tobacco smoking behaviors on genomic or epigenomic alterations, we performed a multi-omics study including whole-genomic, transcriptomic, and epigenomic profiles in a total of 221 individuals from the EAGLE study.

  Study phs002992