3613 results for "*geneti*"

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• NHLBI TOPMed: Determining the Association of Chromosomal Variants with Non-PV Triggers and Ablation-Outcome in AF (DECAF)

  The DECAF trial was conducted at the Texas Cardiac Arrhythmia Institute (TCAI) in 2013 in collaboration with the University of Texas at Austin. Four hundred consecutive AF patients undergoing catheter ablation were enrolled. All participants provided voluntary informed consents. Blood samples were collected before the ablation procedure and labeled with anonymous patient identifier. The researchers at UT Austin responsible for DNA extraction and genetic analysis were blinded about the clinical characteristics and identification of the study participants. AF cases included adults >18 years of age from both sex and all AF types.

  Study phs001546

• NHLBI TOPMed - NHGRI CCDG: Genes-Environments and Admixture in Latino Asthmatics (GALA II)

  This is a case-only pharmacogenetic study of bronchodilator drug response among racially admixed Latino children with asthma. Each participant had two spirometry measurements using the KoKo PFT System. With the first spirometry test, participant was administered with 4 puffs of HFA Albuterol. The second albuterol measurement was based on age, for participants under 16 years of age, additional 2 puffs were administered and for those over 16 years of age, additional 4 puffs were administered. The overall goal is to identify genetic factors which are predictive of drug response in children with asthma. The principal tools include a questionnaire and biological specimen collection. Participants are 8-21 years old at time of recruitment. Children with asthma have physician-diagnosed asthma, symptoms and medications. Comprehensive phenotypic data for GALAII study participants are available through dbGaP phs001180.

  Study phs000920

• 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 the Common Fund in 2023. The National Institute of Neurological Disorders and Stroke (NINDS) oversees 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), clinical sites, core laboratories, 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

• NHLBI TOPMed: Genetic Causes of Complex Pediatric Disorders - Asthma (GCPD-A)

  The Center for Applied Genomics (CAG) at the Children's Hospital of Philadelphia (CHOP) is focused on addressing the roles of both single nucleotide variants and structural copy number variants, and their functional impact, together with gene-environment interactions and their influence on asthma drug response.

  Study phs001661

• 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

• NHLBI TOPMed: Outcome Modifying Genes in Sickle Cell Disease (OMG)

  Sickle cell disease (SCD) is caused by homozygosity for a single mutation of the beta hemoglobin gene. Despite the constancy of this genetic abnormality, the clinical course of patients with SCD is remarkably variable. SCD can affect the function and cause the failure of multiple organ systems through the pathophysiologic processes of vaso-occlusion and hemolysis. These pathophysiological processes are complex and expected to impact multiple organ systems in a variety of ways. This study, therefore, was designed to identify genetic factors that predispose SCD patients to develop specific end-organ complications and to experience more or less severe clinical courses. We enrolled > 700 patients with Hb SS, Hb S-beta0 thalassemia and HbSC being followed primarily at three southeastern U.S. regional institutions (Duke University Medical Center, University of North Carolina Medical Center, and Emory University Medical Center). Medical information obtained included the presence or absence of specific targeted outcomes (overall disease severity as well as specific types of end organ damage). Clinical data include medical status (history, physical, examination, and laboratory results) and information regarding potentially confounding environmental factors. Limited plasma samples are available for correlative studies (e.g. of cytokine levels, coagulation activation). Targeted SNP for candidate gene analysis as well as GWAS has been performed on most samples. Whole genome sequencing has been conducted through the TOPMed Consortium. The subjects in this analysis were collected as part of a larger study, "Outcome Modifying Genes in Sickle Cell Disease" (OMG-SCD) aimed at identifying genetic modifiers for sickle cell disease. More information about the study can be found in Elmariah et al. (2014), PMID: 24478166. Clinical and genetic data have been used to identify genetic characteristics predisposing patients with SCD to a more or less severe overall clinical course as well as to individual organ-specific complications. It is anticipated that identification of such genetic factors will reveal new therapeutic targets individualized to specific complications of SCD, leading to improved outcomes and increased life expectancy for patients with SCD.

  Study phs001608

• 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

• Characterization of Prostate Cancer Organoids

  Using models from the LuCaP series as well as those generated at the National Cancer Institute, we have established organoids for in vitro mechanistic testing, including drug screening and genetic manipulation. The major findings from these continuing studies is the durability of organoids for maintaining complex subpopulation and intratumoral heterogeneity, studying metastasis in vivo, and the parallels between in vitro testing and patient outcomes. Existing data from prior releases includes whole-genome sequencing, whole-exome sequencing, single-cell and bulk RNA-seq, single-cell ATAC-seq, ChIP-seq, and SNP array. New data in this release is single-cell sequencing from two models, long-read sequencing from one model, and updated whole-genome/whole-transcriptome sequencing.

  Study phs001587

• 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

• Kids First: Pediatric Research Project on the Genomic Analysis of Congenital Diaphragmatic Hernia

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). Both, childhood cancers and structural birth defects are critical and costly conditions associated with substantial morbidity and mortality. Elucidating the underlying genetic etiology of these diseases has the potential to profoundly improve preventative measures, diagnostics, and therapeutic interventions. WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. In collaboration with the University of Utah, DNA from four families were selected for high-depth WGS (60X) including diaphragm and skin tissue to identify mosaicism. In collaboration with the Broad Institute, DNA from four families underwent linked long read sequencing using 10X Genomics technology. Probands with congenital diaphragmatic hernia/defects and both biological parents enrolled as part of the DHREAMS study.

  Study phs001110