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• Sequencing to Guide Cancer Care (CanSeq)

  The overall goal of the CanSeq U01 project is to study the impact of whole-exome sequencing (WES) on the clinical care of cancer patients and oncology provider practices. The aims of Project 1 are to implement and establish the feasibility of germline and somatic WES in patients with advanced solid tumors (lung and colon); to develop a framework for interpreting and reporting for exome sequencing data; to determine the proportion of patients with "actionable items" compared to existing technologies; and to report on the percentage of patients in whom unique WES findings led to a clinical action. The aims of Project 2 are to implement a production-scale platform for WES from archival (FFPE) material; to identify biologically relevant somatic and germline alterations existing in tumor/normal DNA from individual patients; to produce an evidence-based list of clinically "actionable" genetic alterations; and to develop inferential models that predict the utility of tumor genomic data within the larger clinical context. The goals of Project 3 are to describe the impact of information derived through WES on cancer patients; to test the hypothesis that patients will want to receive information about all potentially informative somatic and germline variants; to study patients' understanding of disclosed genomic information; and to describe the experiences of oncology providers as they implement WES into cancer care delivery.

  Study phs001075

• Molecular Determinants of Tumor Behavior in Early Lung Adenocarcinoma

  Lung adenocarcinoma is the leading cause of cancer death worldwide and a heterogeneous disease with poor survival in the advanced stage. Given that the frequency of early diagnosis is increasing, the investigation of the molecular determinants of disease progression is paramount. Prediction of whether the tumor is indolent or aggressive has been the subject of recent investigations. Yet, the molecular underpinnings explaining the difference in tumor behavior remains largely unknown and is directly relevant to the efficacy and cost-effectiveness of lung cancer screening, including the risks of over-diagnosis and overtreatment. To gain insights into the molecular pathogenesis and the underlying molecular determinants of clinical behavior of early adenocarcinoma, we investigated genetic alterations in 102 surgically resected early adenocarcinomas. We hypothesized that the behavior of early adenocarcinoma can be predicted based on genomic underpinnings. To identify the type of genomic alterations associated with resected indolent and aggressive early lung ADC, the DNA samples from 21 adenocarcinoma in situ (AIS), 27 minimally invasive adenocarcinoma (MIA) and 54 fully invasive adenocarcinoma were collected and subjected to a deep next generation sequencing, targeting a custom 347 cancer gene panel. Our study provides new insights into cancer genomic evolution, helps to elucidate the interplay of somatic mutation and the adaptation of clones, and brings new insights into the key distinction between indolent and aggressive tumor behavior.

  Study phs001811

• Human CD4 Memory T Cell Activation Time Course

  We performed a high-resolution time course RNA-seq experiment on CD4+ memory T cells during activation with anti-CD3/CD28 beads. We performed this in 24 adult individuals of European ancestry with no autoimmune diseases. We used 1 million cells as starting material, per time point (up to 8 time points per individual from 0 to 72 hours). We identified widespread dynamic allele-specific expression (dynASE) across the genome, i.e. ASE that changes with time after activation, which reflects cell state-dependent genetic regulatory effects. DynASE events were enriched in risk loci for multiple autoimmune diseases. This highlights the importance of studying multiple cellular states in order to elucidate the mechanisms of autoimmune disease. It also provides a successful framework to do it in other cellular systems relevant for other traits. We also showed an unprecedented amount of regulatory variation for HLA genes. HLA-DQB1 has 3 distinct regulatory haplotypes with expression profiles that could come from 3 different genes. We performed ATAC-seq in replicate for CD4+ memory T cells stimulated for 72 hours from another healthy individual. These data, together with genetic fine-mapping, CRISPR editing, EMSA and luciferase assays, helped us find a SNP in the promoter of HLA-DQB1 that causes at least part of the large cell state-dependent change in expression, at the RNA and protein levels.

  Study phs002259

• NHLBI TOPMed: Genome-Wide Association Study of Adiposity in Samoans

  The individuals sequenced here represent a small subset of the parent study (described below) and were carefully selected for the purpose of creating a Samoan-specific reference panel for imputation back into the parent study. The INFOSTIP algorithm of Gusev et. al. (2012) (PMID: 22135348) was used to optimally choose the individuals for sequencing. The research goal of the parent study (dbGaP ID phs000914) is to identify genetic variation that increases susceptibility to obesity and cardiometabolic phenotypes among adult Samoans using genome-wide association (GWAS) methods. DNA from peripheral blood and phenotypic information were collected from 3,119 adult Samoans, 23 to 70 years of age. The participants reside throughout the independent nation of Samoa, which is experiencing economic development and the nutrition transition. Genotyping was performed with the Affymetrix Genome-Wide Human SNP 6.0 Array using a panel of approximately 900,000 SNPs. Anthropometric, fasting blood biomarkers and detailed dietary, physical activity, health and socio-demographic variables were collected. We are replicating the GWAS findings in an independent sample of 2,500 Samoans from earlier studies. After replication of genomic regions and informative SNPs in those regions, we will determine sequences of the important genes, and determine the specific genetic variants in the sequenced genes that are associated with adiposity and related cardiometabolic conditions. We will also identify gene by environment interactions, focusing on dietary intake patterns and nutrients.

  Study phs000972

• NHLBI TOPMed: Novel Risk Factors for the Development of Atrial Fibrillation in Women

  The Women's Genome Health Study (WGHS) is a prospective cohort comprised of over 25,000 initially healthy female health professionals enrolled in the Women's Health Study, which began in 1992-1994. All participants in WGHS provided baseline blood samples and extensive survey data. Women who reported atrial fibrillation during the course of the study were asked to report diagnoses of AF at baseline, 48 months, and then annually thereafter. Participants enrolled in the continued observational follow-up who reported an incident AF event on at least one yearly questionnaire were sent an additional questionnaire to confirm the episode and to collect additional information. They were also asked for permission to review their medical records, particularly available ECGs, rhythm strips, 24-hour ECGs, and information on cardiac structure and function. For all deceased participants who reported AF during the trial and extended follow-up period, family members were contacted to obtain consent and additional relevant information. An end-point committee of physicians reviewed medical records for reported events according to predefined criteria. An incident AF event was confirmed if there was ECG evidence of AF or if a medical report clearly indicated a personal history of AF. The earliest date in the medical records when documentation was believed to have occurred was set as the date of onset of AF.

  Study phs001040

• Identification of Cancer Predisposition Genes in Breast Cancer Families

  Breast cancer has a significant genetic component. The strongest epidemiologic risk factor is family history of the disease. Familial studies have identified a number of genes contributing to increased risk. Of these, the highly penetrant BRCA1 and BRCA2 genes account for the majority of families in whom disease-causal mutations have been identified. However, mutations in other genes have been associated with predisposition to breast or breast and ovarian cancer including (CHEK2, ATM, PALB2, RAD51C, RAD51D). Together these genes account for less than 20% of excess familial breast cancer risk and do not explain ~50% of high-risk families referred for genetic testing. This significant gap in our understanding of the genetic basis of breast cancer poses a significant barrier to our ability to identify women at increased risk, who would benefit greatly from appropriate clinical management. To identify additional breast cancer predisposition genes whole exome sequencing of familial high-risk breast cancer patients was undertaken. DNA samples from 50 pairs of breast cancer patients from high-risk breast cancer families with no pathogenic mutations in the BRCA1 or BRCA2 breast cancer predisposition genes were subjected to whole exome sequencing. The goal was to select candidate predisposition genes for further validation studies based on sharing of putative protein inactivating mutations among both members of each family and/or the frequency of inactivating mutations among the 50 families.

  Study phs000480

• MAESTRO-Pool Enables Highly Parallel and Specific Mutation-Enrichment Sequencing for Minimal Residual Disease Detection in Cohort Studies

  MAESTRO-Pool builds upon the technology MAESTRO (Minor Allele Enriched Sequencing Through Recognition Oligonucleotides) by pooling tumor-specific MAESTRO probes from multiple patients and applying these to all samples from all patients. In this study, MAESTRO-Pool was applied to a cohort of 9 melanoma patients where 98 plasma samples were screened for 22,333 mutations. Additionally, a new dynamic minimal residual disease (MRD) caller was used to estimate the likelihood of MRD detection based on the number mutations and cell-free DNA molecules interrogated which allowed each bespoke MRD test to be properly calibrated against false detection. These developments led to sensitive detection in patient-matched samples down to 0.78 parts per million (ppm) while limiting false detection in negative controls to 1/784 (tumor fraction=2.7 ppm). MAESTRO-Pool and the dynamic MRD caller enable a unique blend of sensitivity, specificity, and efficiency, which will improve the ability to detect MRD.The data contained in this repository consists of:Tumor and normal whole genome sequencing data used to call patient-specific tumor mutations and design the MRD Tracker and MAESTRO-Pool fingerprintsMAESTRO-Pool data (enriched duplex sequencing via hybrid capture) of tumor gDNA, normal gDNA and cfDNA MRD Tracker data (duplex sequencing via hybrid capture) of tumor gDNA, normal gDNA and cfDNA

  Study phs003447

• NHLBI TOPMed: Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE)

  ECLIPSE was a longitudinal observational study of 2164 COPD subjects and a smaller number of smoking controls (337) and nonsmoking controls (245) followed regularly for three years, with three chest CT scans (at baseline, one year, and three years) (Vestbo et al., 2008, PMID: 18216052). Subjects were enrolled at clinical centers in the US, Canada, Europe, and New Zealand. Inclusion criteria included subjects ages 40-75, at least 10 pack-years of smoking, and spirometry in GOLD grades 2-4 (COPD cases) or normal spirometry with post-bronchodilator FEV1 >85% (predicted) and FEV1/FVC>0.7 (controls). Study visits were performed at enrollment, three months, and every six months thereafter with spirometry, questionnaires, and other clinical evaluations. The ECLIPSE CT scans have been analyzed with the VIDA software for emphysema and airway phenotypes. ECLIPSE has provided key insights into the clinical epidemiology of COPD, including COPD exacerbations (Hurst, et. al., 2010, PMID: 20843247) and lung function decline in COPD (Vestbo, et. al., 2011, PMID: 21991892). ECLIPSE has been used in a number of genetic studies of COPD susceptibility and protein biomarkers (Faner, et. al., 2014, PMID: 24310110). Genome-wide gene expression microarray data are available in 147 induced sputum samples from COPD subjects and 248 peripheral blood samples from COPD and control subjects. Phenotype data for ECLIPSE subjects is available through dbGaP phs001252.

  Study phs001472

• Brain Cell Type-Specific Enhancer-Promoter Connectivity Maps and Disease Risk Association

  These studies map the epigenetic landscape of microglia, neurons, astrocytes and oligodendrocytes. The initial study compared acutely isolated microglia to cultured microglia from the same donors, to identify changes that occur when microglia are removed from the brain microenvironment. In collaboration with the Rady Children's Hospital, we obtained brain tissue samples from pediatric patients representing putative normal tissue resected to gain access to brain tumors as well as tissue resected to remove epileptic foci. We assayed microglia isolated from these samples using RNA-seq, ATAC-seq and ChIP-seq for PU.1, H3K4me2, and H3K27ac. For patients from whom a sufficient cell number was obtained, we additionally cultured their microglia for up to 7 days and subjected these to the same suite of assays. In a follow-up study, we obtained brain tissue from a comparable cohort of pediatric epilepsy patients from Rady Children's Hospital. We isolated nuclei from microglia, neurons, astrocytes and oligodendrocytes, and assayed for ATAC-seq, ChIP-seq for H3K4me3, and H3K27ac, and PLAC-seq (Proximity Ligated ChIP-seq). We isolated microglia from human fetal and postnatal sample and assayed for bulk RNA-seq, bulk ATAC-seq, bulk H3K27ac ChIP-seq, single-cell RNA-seq (scRNA-seq) and single-cell ATAC-seq. For these studies, human microglia are defined by signature genes/proteins, such as P2RY12, SALL1, and CX3CR1.

  Study phs001373

• NIH Division of Intramural Research Multiomic Monogenic Disease Study

  This cross-sectional, observational study utilized high-dimensional approaches, including transcriptomic analysis, serum protein profiling, and peripheral blood frequency assessments, to compare 228 adult and pediatric patients diagnosed with 22 monogenic immune-mediated conditions impacting various key immunological pathways, with 42 age- and sex-matched healthy controls. Participants were enrolled in clinical protocols at the National Institutes of Health in Bethesda, Maryland, USA. The primary objectives of the study were twofold: first, to identify disease-specific and shared "pan-disease" signatures using the collected data, and second, to develop a Random Forest classifier integrating these datasets to differentiate between age- and sex-matched healthy individuals and monogenic patients. This classifier produced a metric known as the "Immune Health Metric" (IHM). Subsequent analysis demonstrated that the IHM effectively distinguished healthy subjects from individuals with multiple polygenic autoimmune and inflammatory diseases in independent datasets. Moreover, it exhibited correlations with healthy aging and tracked disease activities and treatment responses across both immunological and non-immunological conditions. Additionally, the IHM accurately predicted age-dependent antibody responses to various vaccines, including influenza, Hepatitis A/B, Yellow Fever, Varicella Zoster, and Meningococcal vaccines.The microarray-based transcriptomic data, aptamer-based serum protein concentrations (Somalogic platform), peripheral blood frequency data, and clinical information will be made accessible through the database of Genotypes and Phenotypes (dbGaP).

  Study phs002732