3246 results for "*geneti*"

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• Characterizing Disease-Causing Variants Using Personal Genomes with Large Recurrent Deletions

  Individuals with recurrent genomic deletions are known to present variable clinical phenotypes, despite the apparent identical range of the genomic segments being affected in their genomes. We propose to study the phenotypic variability and the molecular polymorphism in individuals with the recurrent 17q12 deletions or the recurrent 1q21.1 deletions, with the objective to establish causal relationship between the genotypes and the incompletely penetrant clinical phenotypes. Genome sequencing and phenotypic data from individuals with the deletions and their relatives are included in this submission.

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• Multi-Omic Investigation of Beckwith-Wiedemann Syndrome Hepatoblastoma

  Hepatoblastoma (HB) is the most common malignant liver tumor diagnosed in children under 5 years of age. One of the most common HB predisposition syndromes is Beckwith-Wiedemann Syndrome (BWS, OMIM 130650), which affects approximately 1/10,000 live births. In this study, we perform Whole Exome Sequencing (WES), DNA methylation array, messenger RNA-Sequencing (mRNA-Seq), and microRNA-Sequencing (miRNA-Seq) to examine the genomic, methylomic, and transcriptomic signature of BWS HB. We analyzed five tumor-normal paired samples, two BWS tumor only samples, and five non-BWS control samples to identify a predisposition and oncogenic signature of BWS HB development. 

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• CIDR: NINDS High Throughput Genotyping Resource Access for Structural Hindbrain Disorders

  Recessive forms for many structural brain disorders (SBDs), including cerebellar hypoplasia (CBH), corpus callosum hypoplasia (CCH), cobblestone lissencephaly (COB), classical lissencephaly (LIS), microcephaly (MIC), and pontocerebellar hypoplasia (PCH), have been described. Patients usually present to the clinic with neurodevelopmental disorders (NDDs), including autism, epilepsy, intellectual disability, and cerebral palsy. Subsequent brain MRI usually leads to the diagnosis of an SBD. While a handful of genes that cause these diseases have been identified, most patients do not have mutations in these genes, suggesting that there is still much work to be done in identifying the genetic causes of these disorders. We have recruited a cohort of families with inherited SBDs, most from families with documented parental consanguinity with more than one affected member. Current approaches utilizing exome sequencing of SBD affected members still leave most cases unsolved, in part because there are too many possible variants to consider. Linkage analysis will allow us to extract all the useful genetic information from the family, taking advantage of each genetically informative meiosis in each family. We propose to analyze up to 100 SBD families for 500 samples per year for 4 years, through the CIDR SNP Genotyping Service, in parallel with already-funded exome sequencing of affects, leveraging off an already funded Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) effort to identify new causes of SBDs. Understanding the pathogenetic mechanisms underlying recessive pediatric SBDs will lead to better diagnostic and therapeutic opportunities for patients, and may shed light on complex NDDs. Ultimately, this work will identify new genetic disease loci to provide insight into pediatric SBD, with the hope to mitigate the impact of SBD worldwide.Public Health Significance: NDDs affect approximately 4-­6% of the general population, most notably children, and are evident in disorders, such as intellectual disability, epilepsy, and autism, with estimated yearly costs of $51.2B for intellectual disability, $11.5B for cerebral palsy, and $2.5B for visual impairment, making up >5% of total health care costs. Recessive NDDs impose enormous personal, social, and economic costs because of the early onset and the lifetime of medical dependence that often ensues. Genetic testing is critical to the diagnosis and treatment of these diseases. Many of the diseases under study have no treatment or cure. Structural brain diseases (SBDs) underlie a large percentage of these diseases, and are defined loosely as any condition in which defects in the structure or volume of a key brain component. SBDs are divided into major categories based upon the anatomical brain location. The major types involve the anatomical structures of the developing neural tube, forebrain, hindbrain, cerebral cortex, and those affecting overall brain size. For the purposes of this application, we have excluded SBDs resulting from environmental causes (i.e. prematurity-­induced), those below the brainstem, or those unlikely to be due to a germline or de novo mutation (i.e. focal SBDs or simplex disease).

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• Whole Genome Sequencing of Bilateral Cleft Lip and Palate Families from Africa: CIDR

  The focus of this study is to identify and test both common and rare genetic variants that elevate risk for CL/P, and to identify genetic variants associated with specific orofacial cleft (OFC) phenotypes in the population that has accumulated the greatest genetic variation in the human race. We hypothesize that bilateral complete cleft lip and palate (BCLP), the most clinically severe form of OFC, is associated with a higher mutation load than less severe forms (cleft lip only and unilateral cleft lip and palate) and focusing on BCLP will facilitate the discovery of novel risk variants.

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• The Spatio-Temporal Evolution of Multiple Myeloma from Baseline to Relapse-Refractory States

  In multiple myeloma, the spatio-temporal evolution patterns of cancer cells in the bone marrow remain largely unknown. Here, we applied spatial-longitudinal sequencing, including a total of 179 samples collected from 25 patients during a follow-up of up to 14 years. Our study highlights focal bone lesions (FL) as hotspots of tumor evolution and provides possible explanations for their negative prognostic impact. We show a close phylogenetic relationship between baseline FL and relapse clones. In patients with ≥3 FDG-PET-positive FL at diagnosis, relapse was driven by multiple distinct sub-clones, whereas in other patients, a single-cell expansion was typically seen (p<0.01). Applying imaging-guided sampling, we identified a novel evolutionary pattern with unique treatment-resistant sub-clones at distinct locations. We observed multiple selective clonal sweeps, resistant clones that can be hidden over years, and epigenetic modifier mutations as a new class of relapse aberrations. Here we show that imaging can enhance tumor evolution studies and response assessment. The sophisticated evolution mechanisms in myeloma and presence of single cells that can drive relapse even after 10 years of remission suggest that a prerequisite for curative therapies would be to overcome not only tumor heterogeneity but also dormancy.

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• Kids First: The Genomic Basis of Structural Birth Defects Associated with Chromosome 18 Copy Number Changes

  Chromosome abnormalities are a common cause of structural birth defects. 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.However, because these genomic copy number changes involve multiple genes and because most of these conditions are individually rare, defining the specific causative genes behind specific phenotypes has been a challenge. We met that challenge by spending the last 28 years enrolling and evaluating anyone with a chromosome 18 abnormality. The cohort now includes over 700 individuals with a wide variety of chromosome 18 copy number changes (CNV), as well as their parents. Because the vast majority of these participants have individually unique CNVs, we have been able to perform extensive genotype-phenotype correlations resulting in 58 publications. Of the 263 genes on chromosome 18, 28 are linked to specific hemizygous phenotypes. However, most have low penetrance. Genomic sequence data could identify variants in the extant allele that are hypermorphic and compensate for hemizygosity, or are hypomorphic and exacerbate hemizygosity. Additionally, there are phenotypes within this cohort that are rare, or an extreme version of one of the more common phenotypes. Genomic sequence data could help discover new biallelic conditions by revealing functional sequence variants of the extant allele. In both of these cases, there could also be variants in other genes on other chromosomes that may be associated with the phenotype that confer susceptibility or resilience. Inclusion of this unique cohort in the Gabriella Miller Kids First Pediatric Research Program can advance the goals of the program in several ways. First, by adding known susceptibility loci to the existing Kids First cohorts for the structural birth defects that are also found in our cohort. Second, for those structural birth defects known to be polygenetic, this cohort has a single defined risk factor which can simplify the search for secondary factors. Third, these studies can also bring clarity to people with chromosome 18 conditions and help to make the genotype more accurately predict phenotype. This approach could be a model for understanding the many other rare chromosome abnormalities which collectively are a common cause of structural birth defects.

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• Genetic Study of Northern Kenya Pastoral Populations

  Human populations in Africa are the most genetically diverse in the world, having a rich history, and yet are severely understudied. The purpose of this study is to understand the population history of four ethnolinguistic groups in northern Kenya - the Turkana, Samburu, Rendille, and Borana. This study aims to measure the extent of variation among several genetic systems in these populations, with the goal to better understand the broader population history in northern Kenya and to add to the current knowledge of population genetics in Africa.

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• Whole Exome Sequencing in Alopecia Areata Identifies Rare Mutations in KRT82

  Alopecia areata (AA) is an autoimmune disorder, in which the body's own immune cells attack hair follicels resulting in hair loss. It is a complex genetic disease with 14 associated loci previously identified in our genome-wide association study (GWAS). In the study, we performed the whole-exome sequencing (WES) on 849 AA patients with the aim to identify the novel rare variants in genes contributing to AA susceptibility. We performed gene-collapsing analyses and identified keratin 82 (KRT82 Gene ID: 3888) as the highest associated AA gene in the three rare damaging collapsing models with p<6.7E-07 in one of the models. The KRT82 gene is a hair-specific type II keratin expressed in the hair shaft cuticle during the anagen phase of the hair cycle. We reported the lower expression of KRT82 in AA hair follicles, compared to controls, and the KRT82 expression is absent from the bulb region, the site of AA immune attack. This study emphasizes the significance of using WES and gene collapsing analyses to identify rare variation in a functionally relevant risk gene using a moderate sample size.  

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• CIDR: The Role of Rare Coding Variation in Prostate Cancer in Men of African Ancestry - RESPOND Project 2

  In RESPOND Project 2, we seek to identify rare genetic factors that are associated with prostate cancer (PCa) risk and aggressiveness in men of African ancestry (AA). We will conduct exome sequencing of 15,000 prostate cancer cases and 5,000 controls from the RESPOND cohort and the African Ancestry Prostate Cancer Consortium (AAPC) with cases selected based on risk categories: high-risk (stage T3/T4 or Gleason 8+ or PSA>20 ng/ml), intermediate-risk (stage T2b/T2c or Gleason 7 or PSA 10-20 ng/ml) and low-risk disease (stage T1/T2a and Gleason ≤ 6 and PSA<10 ng/ml). We expect the findings from this Project to significantly advance knowledge of susceptibility to aggressive PCa and racial/ethnic disparities in PCa risk, and to guide the development of future preventive, early detection and prognostic measures for AA men. The first phase of the study will include exome sequence data for approximately 7,500 cases and 5,000 controls from AAPC. The second phase of the study will include exome data for 5,000 cases from RESPOND and AAPC.ACKNOWLEDGMENTS and CONTRIBUTING SITES Multiethnic Cohort (MEC): The MEC and the genotyping in this study were supported by National Institutes of Health (NIH) grants CA63464, CA54281, CA1326792, CA148085, and HG004726. Cancer incidence data for the MEC and Los Angeles Study of Aggressive Prostate Cancer (LAAPC) studies have been collected by the Los Angeles Cancer Surveillance Program of the University of Southern California with federal funds from the National Cancer Institute (NCI)/NIH/Department of Health and Human Services (DHHS) under Contract No. N01-PC-35139, and the California Department of Health Services as part of the state-wide cancer reporting program mandated by California Health and Safety Code Section 103885, and grant 1U58DP000807-3 from the Centers for Disease Control and Prevention (CDC). Ghana Prostate Study (GPS): The Ghana Prostate Study was funded by the Intramural Program of the NCI/NIH/DHHS under Contract No. HHSN261200800001E. Men of African Descent and Carcinoma of the Prostate (MADCaP): We thank all MADCaP study participants. This work is a product of the MADCaP network. This work was supported by NCI/NIH grant U01CA184374 to Timothy Rebbeck and National Institute of General Medical Sciences (NIGMS) MIRA grant R35GM133727 to Joseph Lachance. Additional funding includes a seed grant from the Integrated Cancer Research Center at Georgia Institute of Technology. UGANDA: The UGANDA study was supported by NIH grant R01CA165862. Southern Community Cohort (SCCS) is funded by NIH grant CA092447. SCCS sample preparation was conducted at the Epidemiology Biospecimen Core Lab that is supported in part by the Vanderbilt Ingram Cancer Center (CA68485). Data on SCCS cancer cases were provided by Alabama Statewide Cancer Registry, Kentucky Cancer Registry, Office of Cancer Surveillance at Tennessee Department of Health, Florida Cancer Data System, Central Cancer Registry at North Carolina Division of Public Health, Georgia Comprehensive Cancer Registry, Louisiana Tumor Registry, Mississippi Cancer Registry, South Carolina Central Cancer Registry, Virginia Cancer Registry at Virginia Department of Health, and Cancer Registry at Arkansas Department of Health. The Arkansas Central Cancer Registry is fully funded by a grant from National Program of Cancer Registries (NPCR)/Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the Mississippi Cancer Registry which participates in the NPCR/CDC. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry. Karuprostate: The Karuprostate study was supported by the French National Health Directorate and by the Association pour la Recherche sur les Tumeurs de la Prostate. Séverine Ferdinand, Marc Romana. The North Carolina - Louisiana Prostate Cancer Project (PCaP) is carried out as a collaborative study supported by the Department of Defense contract DAMD 17-03-2-0052. The authors thank the staff, advisory committees and research subjects participating in the PCaP study for their important contributions. We would also like to acknowledge the UNC BioSpecimen Facility and the LSUHSC Pathology Lab for our DNA extractions, blood processing, storage and sample disbursement (https://genome.unc.edu/bsp). Gene-Environment Interaction in Prostate Study (GECAP) was supported by NIH grant ES011126. King County Prostate Cancer Study (KCPCS) was supported by NIH grants CA056678, CA082664, and CA092579, with additional support from the Fred Hutchinson Cancer Research Center. We thank the participants in these studies, and Ms. Suzanne Kolb for help with study management. The Los Angeles Study of Aggressive Prostate Cancer (LAAPC) was funded by grant 99-00524V-10258 from the Cancer Research Fund, under Interagency Agreement #97-12013 (University of California contract #98-00924V) with the Department of Health Services Cancer Research Program. Cancer incidence data for the MEC and LAAPC studies have been collected by the Los Angeles Cancer Surveillance Program of the University of Southern California with Federal funds from the NCI/NIH/DHHS under Contract No. N01-PC-35139, and the California Department of Health Services as part of the state-wide cancer reporting program mandated by California Health and Safety Code Section 103885, and grant 1U58DP000807-3 from the CDC. Prostate Cancer Studies at MD Anderson (MDA) was supported by grants CA68578, ES007784, DAMD W81XWH-07-1-0645, and CA140388.

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• Precision Medicine for Dilated Cardiomyopathy in European and African Ancestry

  The DCM Precision Medicine Study is a multi-site consortium-based cross-sectional study of families with an embedded open-label randomized controlled trial. The aims of the study are to test the hypothesis that dilated cardiomyopathy (DCM) has a substantial genetic basis and to evaluate the effectiveness of a family communication intervention in improving the uptake of preventive screening and surveillance in at-risk first-degree relatives. The Study goal was to recruit 1,300 individuals (600 non-Hispanic African ancestry, 600 non-Hispanic European ancestry, and 100 Hispanic; 50% female) meeting rigorous diagnostic criteria for idiopathic DCM (probands) and 2,600 of their relatives. The probands were inpatients or outpatients identified by heart failure and cardiac transplant cardiovascular physicians and clinical research personnel in heart failure/heart transplant programs at sites in the DCM Consortium. The DCM phenotype was selected for this study because of its prevalence and its prior inclusion in the development of virtually all pharmacotherapy for non-ischemic heart failure from reduced ejection fraction. Study procedures included obtaining family history, cardiac history, medical record review, surveys, and blood sample collection. Exome data from 1219 idiopathic DCM probands and 127 idiopathic DCM relatives are included in dbGaP.

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• Single Suture Craniosynostosis: Gene and Pathway Discovery

  Craniosynostosis is the premature fusion of one or more of the calvarial sutures. In this work, we used genomics and network modeling to reveal genetic and developmental pathways which, when disrupted, result in premature calvarial fusion. Calvarial bone explants were obtained from children undergoing surgery for single suture craniosynostosis. Primary osteoblast cell lines were established from calvarial explants and used as an RNA source.  The data available includes subject sex, affected suture, RNA sequence variants and counts.

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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) 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 and mid-turbinate nasal swabs) 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 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 was 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 and peripheral blood mononuclear cells (PBMCs) to evaluate both dynamic changes in cellular composition and cellular response during the course of the disease. Reads were aligned to the GRCh38 human reference genome.The data submitted here represents an initially analyzed cohort of about 500 participants. 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).

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• A Multimodal Atlas of Human Brain Cell Types 2021 Data

  Human neocortical neurons display diverse morphology, physiology and gene expression profiles. We use a method called Patch-seq, where these three data modalities are assayed simultaneously from the same neuron, to understand how the genetic profile of human neocortical neuron types corresponds to their morphological and electrophysiological phenotypes. This dataset consists of transcriptome samples collected during Patch-seq recordings from layer 5 pyramidal neurons in the human middle temporal gyrus.

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• Identification of Structural Variants Relevant to Autism by Pacific Biosciences HiFi Whole-Genome Sequencing

  The purpose of this research study was to perform long-read whole-genome sequencing on a family with autism. This family had no known genetic cause based on clinical array and whole-exome sequencing analysis. Utilizing PacBio HiFi long-read whole-genome sequencing, we identified a relevant missense variant in the KCNC2 gene. This variant was likely to be a germline mosaic in the paternal germline.

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• The National Myelodysplastic Syndromes (MDS) Study

  Myelodysplastic syndromes (MDS) are the most common cause of adult bone marrow failure in the US and occur predominantly in people over the age of 60. Much of the morbidity and mortality for MDS is due to complications from low blood counts (e.g., infections and bleeding). MDS is caused by acquired DNA mutations that occur in a patient's blood cells as they grow older. Accumulating evidence suggests that MDS patients may traverse through a series of antecedent hematopoietic conditions defined by, i) clonal hematopoiesis (i.e., detectable somatic mutations in a person's blood cells) without low blood counts, a condition that affects up to 10% of individuals 70 years old and is termed Clonal Hematopoiesis of Indeterminate Potential (CHIP), or ii) clonal hematopoiesis with low blood counts (i.e., cytopenias) but no evidence of bone marrow dysplasia, termed Clonal Cytopenia of Undetermined Significance (CCUS). Nearly all CCUS patients will develop MDS over a ten year period, highlighting the prognostic importance of this disease. A better understanding of the genetic mutations, including non-coding and structural variants (SVs), occurring in CCUS and MDS could provide valuable insight into the natural history of MDS development. The NHLBI is conducting a longitudinal, observational study to create a standardized clinical dataset linked to a prospectively collected, consistently processed, and well-characterized biospecimen repository derived from approximately 1750 participants with suspected or newly diagnosed MDS or MDS/myeloproliferative neoplasm (MPN) overlap. These volunteers will donate biological specimens (like bone marrow and blood) and medical information, including details of their symptoms, how they perceive their quality of life, the treatments they receive, and what their doctor says about the severity of their illness over time. This information will be collected at pre-determined time points for the duration of the study. Study participants may be followed for life.

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• Genetics of Hypertension Associated Treatment (GenHAT) Study, Genomic Background of Blood Pressure Response to Treatment in African Americans

  The GenHAT study is an ancillary pharmacogenomics study to the Antihypertensive and Lipid Lowering Treatment to Prevent Heart Attack Trial (ALLHAT). ALLHAT was a randomized, double-blind, multi-center trial that enrolled 42,418 participants ≥55 years of age with hypertension and at least one additional risk factor for cardiovascular disease (CVD). Participants were randomized to treatment with one of four primary antihypertensive drugs: chlorthalidone (thiazide-like diuretic), amlodipine (CCB), lisinopril (ACE-i), or doxazosin (alpha-adrenergic blocker) in a ratio of 1.7:1:1:1, respectively. Participants were followed for treatment response and CVD outcomes. The original GenHAT study (N=39,114) evaluated the association of candidate hypertensive genetic variants with CVD outcomes for participants consenting to genetic research. The current GWAS study focuses on a subset of African American GenHAT participants (n=6908).  

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• Genetics of Prostate Cancer in Africa

  African Americans (AA) suffer from the highest rates of Prostate Cancer (CaP) in the world, but while men of African descent around the world suffer disproportionately from CaP compared to men of other races or ethnicities, our understanding of the reasons for these disparities remains incomplete. To date, few exposure, lifestyle, or environmental influences have been identified in CaP etiology. In contrast, CaP is among the most heritable of common cancers, and over 290 susceptibility loci have been identified. However, many of these loci have not been replicated in AA, in part because of limited African descent sample sizes, incomplete capture of African alleles, and a limited understanding of African genomic architecture. To better understand the etiology of CaP in African descent men, we established a large, multicenter consortium known as “Men of African Descent and Carcinoma of the Prostate” (MADCaP). Using resources of this consortium, we have undertaken a multicenter study of CaP in Sub-Saharan Africa, enrolling CaP cases from 7 institutions in 4 countries in Africa (Nigeria, Senegal, Ghana, and South Africa) and age matched controls from the same institutions. We designed a novel genotyping array, in partnership with Thermo Fisher Scientific, leveraging its Applied BiosystemTM AxiomTM Genotyping solution, to provide good coverage of African genomic variation, as well as incorporating cancer loci, with the goal of being able to fine-map existing prostate cancer loci, as well as mapping novel loci. The data available encompasses genotyping our Africa cohort on this array.

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• Discovery and Characterization of Genetic Risk Loci in Sjogren's Syndrome

  The Sjögren's Genetics Network (SGENE) is an international collaboration focused on identifying and understanding the genetic variations that influence Sjögren’s pathology. Collectively, SGENE collaborators from 26 different sites (5 in the United States; 21 in foreign countries) have recruited a large cohort of geographically diverse participants of European ancestry. Recruitment, sample collection, and genotyping were performed at unique SGENE sites in compliance with local institutional review board approval. High-density SNP genotyping data were collated by the Oklahoma Medical Research Foundation (OMRF) and used to perform a GWAS of Sjögren's of European ancestry. Participants underwent extensive medical assessment for Sjögren's Syndrome using internationally accepted American-European Consensus Group (AECG) classification criteria or the American College of Rheumatology/European League Against Rheumatism classification criteria. Data quality control, GWAS imputation using the Haplotype Reference Consortium, panel version 1.1, and dbGaP preparation/posting were performed at the OMRF. To facilitate research focused on understanding the genetics of Sjögren's syndrome, the Genomic Summary Results from this GWAS are being made available herein using a total of n=3232 Sjögren's cases and n=17,481 controls. A total of n=8962 controls were obtained from our SGENE collaborators or from our previous study (Lessard, et al. Nature Genetics 2013. PMID: 24097067). To achieve adequate case-to-control ratios for the GWAS analyses, population-based control GWAS data were also obtained from dbGaP (phs000428.v2.p2; phs000672.v1.p1; phs000196.v3.p1; phs000187.v1.p1). In accordance with IRB approval, subject consents, and data sharing restrictions, we are also making available the individual-level genotyping data for a subset of Sjögren's cases (n=1,199) that were genotyped at the OMRF.

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• Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Genetic Epidemiology of COPD Study (COPDGene)

  Cohort Description The Genetic Epidemiology of COPD (COPDGene) study is a non-interventional, multicenter, longitudinal, case-control study at 21 US sites of smokers with a ≥10 pack-year history of smoking, with and without COPD, and healthy never smokers. The initial goal was to characterize disease-related phenotypes and explore associations with susceptibility genes. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 3683 COPDGene participants in C4R. Wave 2 questionnaire data includes 447 variables for up to 2191 COPDGene participants in C4R. Dried Blood Spot/Serosurvey data includes 7 variables for up to 1692 COPDGene participants in C4R. Derived data includes 43 variables for up to 4082 COPDGene participants in C4R. Phenotype data includes 113 variables for up to 4082 COPDGene participants in C4R.

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• (Epi)genetic Risk Architectures of Opioid-Dependent Brain

  With nearly 20,000 overdose deaths in 2014 alone, opioid addiction (OA) has emerged as one of the most pressing public health crises in recent US history. One-fifth of individuals who try heroin develop an addiction to opioids. Genetics is a major contributor to OA with an estimated 60% heritability, only somewhat less than schizophrenia (80%) which has recently seen substantial gains in identified underlying genetics. Yet, studies to date have failed to uncover most of the genes that predispose individuals to OA, leaving the overwhelming fraction of OA heritability unexplained. The proposed study takes a novel, integrated "omics-based" strategy to investigate the molecular basis of OA and uncover both genetic and epigenetic factors associated with opioid addiction. The premise for our approach is founded on studies from our labs, and others, implicating regulatory variation in common traits and diseases, including those associated with complex brain phenotypes like addiction. We have collected the largest known cohort of postmortem brains from addicts who overdosed on opioids, along with matched control brains from non-users. From both cases and control specimens, we will isolate cells from 2 regions of the brain closely implicated in the addiction phenotype: the Prefrontal Cortex (PFC) and the Nucleus Accumbens (NAc). In Aim 1, we propose ChIP-seq studies to identify regulatory elements that distinguish cases from controls and define the opioid addiction phenotype. The regulatory differences will be connected to their gene targets through high resolution in situ Hi-C. In Aim 2, we propose QTL-based approaches to identify genetic variants that underlie the regulatory differences (hmQTLs). We also propose eQTL analyses to identify genetic variants that underlie differences in transcript levels between cases and controls. Aim 3 leverages the largest heroin addiction GWAS meta-analysis to date to test the hypothesis that SNPs in regions associated with chromatin and expression differences between cases and controls define novel loci for predisposition to OA. Each Aim has the potential for discovery independent of the others (differential HM, RNAexp, QTLs, and variant-phenotype associations) but their synergy is the most powerful component of the proposed study: identifying regulatory pathways that generate, not only phenotype associations, but hypothesized mechanisms for those associations which can be the focus of new opioid addiction prevention and treatment development.

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• Center for Common Disease Genomics [CCDG] - Cardiovascular: ENGAGE Atrial Fibrillation-TIMI 48

  This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1. Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules.Source: https://ccdg.rutgers.edu/sites/default/files/CCDG_CVD_EOAF_FINAL_w_link.pdfFor this study, The Broad Institute of MIT and Harvard generated genetic data for 13,667 individuals from the ENGAGE AF-TIMI 48 clinical trial run by Brigham and Women's Hospital TIMI study group using whole exome sequencing and whole genome genotyping (Infinium Global Screening Array); all cases with atrial fibrillation.

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• Genome-Wide Pleiotropy Scan Across Multiple Cancers

  A whole-exome sequencing (WES) study was conducted in 3,233 cases diagnosed with multiple primary cancers and 3,229 matched cancer-free controls (90% non-Hispanic white, 3% African-American, 3% East Asian, and 4% Latino) selected from individuals in the Kaiser Permanente Research Bank (KPRB) who were members of the Kaiser Permanente Northern California (KPNC) health plan. Cancer-free controls were matched to cases on age at specimen collection (within 2 years), sex, genotyping array (which matched on self-reported race/ethnicity), closest distance using the first two principal components for genetic ancestry, and reagent kit. Cases and controls were drawn from two prospective KPRB cohorts: the Research Program on Genes, Environment and Health (RPGEH) and the ProHealth study. Participants were sequenced by the Regeneron Genetics Center using the Illumina NovaSeq 6000 platform, and sample preparation and quality control were performed using a high-throughput, fully-automated system [PMID: 33087929]. Reads were aligned to the GRCh38 reference genome, and variants were called using WeCall [PMID: 33087929]. Participants with sex discordance, 20x coverage at less than 80% of targeted sites, and/or contamination greater than 5% were excluded. After quality control, we retained n = 6,247 (3,111 cases, 3,136 controls) individuals for downstream analyses. Among participants selected for this WES study, n = 5,432 (2,299 cases; 3,133 controls) consented to deposition of data to the National Institutes of Health (NIH).Further quality control was applied to filter low quality variants. Genotype calls with low depth of coverage (DP) were updated to missing (DP < 7 for SNPs and DP < 10 for indels), after which sites with low allele balance (AB) - variants without at least one sample having AB ≥ 15% for SNPs or AB ≥ 20% for indels - were removed. Lastly, variants with missingness > 10% and Hardy-Weinberg equilibrium p-value < 10-15 were excluded. Further description of quality control and downstream single-variant and gene-based analyses is available in Cavazos et al, 2022 [medRxiv].

  Study phs002809

• Genetic Analysis of Latin American Cervical Cancer

  HPV16 is the most oncogenic type of human papillomaviruses (HPV). Integration of HPV into the human genome is an important mechanism of carcinogenesis but is absent in at least 30% of HPV16+ tumors. We applied long-read whole-genome sequencing (WGS) to cervical cancer cell lines and tumors to characterize HPV16 carcinogenesis in the absence of integration. WGS of HPV16+ cervical tumor samples from Latin America revealed that 11/20 tumors with only episomal HPV (EP) had intact monomer episomes. The remaining 9 EP tumors had multimer and rearranged HPV genomes. The majority (80%) of the HPV rearrangements and deletions disrupted the E1 and E2 genes, and EP tumors overexpressed the E6 and E7 viral oncogenes, a similar profile to tumors with HPV integration. Tumors with putative multimer HPV integrations display HPV multimers and concatemers of human and viral sequences. Our data uncovered a novel mechanism for HPV16 to cause cancer without integration through aberrant episomal replication, and forming rearranged, mutated, and multimer episomes.

  Study phs002810

• Center for Common Disease Genomics [CCDG] - Cardiovascular: The Genetics of Atrial Fibrillation

  This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1 . Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules.Source: https://ccdg.rutgers.edu/sites/default/files/CCDG_CVD_EOAF_FINAL_w_link.pdfFor this study, The Broad Institute of MIT and Harvard generated genetic data for UWO Genetic Investigation of Supraventricular Tachycardias.Patients confirmed to possess a supraventricular tachycardia and/or an accessory pathway at the time of invasive electrophysiology study at the London Health Sciences Centre, London, Ontario, Canada were eligible for enrollment. Potential supraventricular tachycardias included atrioventricular nodal reentrant tachycardia (AVNRT), atrioventricular reentrant tachycardia (AVRT), atrial tachycardia, junctional tachycardia, atriofascicular tachycardia, nodofascicular tachycardia, and nodoventricular tachycardia. Patients that did not have inducible supraventricular tachycardia, but had an accessory pathway that conducted antegrade, retrograde, or both, were also eligible for enrollment. All patients additionally underwent, at minimum, a clinical history, physical examination, 12-lead ECG, and echocardiogram. Study participants provided informed written consent under a protocol approved by the research ethics board of Western University.Raw sequencing data, metadata, vcf and phenotype data at individual level are available at https://anvilproject.org/data For questions about availability contact help@lists.anvilproject.org.

  Study phs002811

• 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