3613 results for "*geneti*"

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• The National Institute of Neurological Disorders and Stroke (NINDS) Human Genetics Resource Center: DNA and Cell Line Repository (the NINDS Repository): Motor Neuron/Amyotrophic Lateral Sclerosis (ALS) Study

  The National Institute of Neurological Disorders and Stroke (NINDS) Human Genetics Resource Center: DNA and Cell Line Repository (the NINDS Repository), banks phenotypic data and biological samples, including from individuals with motor neuron disease, in order to facilitate gene discovery in neurological disorders. Those samples are used in a number of studies, and genotyping data from studies using this resource are encouraged to be shared via dbGaP. Many studies have already shared data in this fashion, which in turn, can be linked back to the biologicals banked at the NINDS Repository. Motor Neuron Disease is characterized by selective degeneration of the motor neurons of the spinal cord, brainstem, or motor cortex. Clinical subtypes are distinguished by the major site of degeneration. In Amyotrophic Lateral Sclerosis (ALS), there is involvement of upper, lower, and brainstem motor neurons. In progressive muscular atrophy and related syndromes, the motor neurons in the spinal cord are primarily affected. With progressive bulbar palsy, the initial degeneration occurs in the brainstem. In primary lateral sclerosis, the cortical neurons are affected in isolation (Adams et al, Principles of Neurology, 6th ed, p 1089). The Motor Neuron Disease Collection of DNA and cell lines in the NINDS Repository is largely Amyotrophic Lateral Sclerosis cases (others include progressive muscular atrophy, primary lateral sclerosis, progressive bulbar palsy, Kennedy's disease). Amyotrophic lateral sclerosis (ALS) is the most common form of motor neuron disease (MND). Although ALS is the most common MND, it is still a relatively rare disease with an incidence of around 1.6 per 100,000 in the United States. It is currently incurable and treatment is largely limited to supportive care. Family history is associated with an increased risk of ALS, and many Mendelian causes have been discovered (including SOD1). However, most forms of the disease are not obviously familial. It is suspected that the sporadic forms of neurodegenerative disorders are caused by multiple genetic variants that individually make relatively weak contributions to risk. There is also an associated Control collection (see dbGaP and Coriell). Studies in motor Neuron Disease may use cases from the NINDS repository, controls from the NINDS repository, as well as cases, and controls, from other sources. A subset of subjects from The National Institute of Neurological Disorders and Stroke (NINDS) Human Genetics Resource Center: DNA and Cell Line Repository (the NINDS Repository): Motor Neuron/Amyotrophic Lateral Sclerosis (ALS) Study was utilized in the Genome-wide genotyping in amyotrophic lateral sclerosis and neurologically normal controls: first stage analysis and public release of data study. Note: The publication Chio et al., 2009 states that "Raw sample-level genotype data from the initial GWAS study ... are available for download through the dbGAP portal (phs000006.v1.p1)". Instead, please follow this link: phs000101.v1.p1.

  Study phs000006

• Substance Use and Immunity in HIV+ Adolescents by Systems Biology

  Marijuana contains a complex variety of unique cannabinoids, including Δ9-tetrahydrocannabinol (THC) and cannabidiol (CBD), known to impact inflammatory and lymphocyte activation pathways in the lymphoid tissues and brain. While marijuana continues to be classified under United States federal law as an illegal drug, medical use of cannabis is legal in at least 35 states, including 16 states and the District of Columbia where recreational marijuana is approved for individuals over the age of 21. In many states HIV infection is the sole indication for the use of medicinal marijuana as adjuvant therapy. Cannabis is effective in the treatment of HIV-associated peripheral neuropathy, improves appetite, and enhances overall quality of life of people with HIV while the anti-inflammatory effects of cannabis may improve HIV-associated complications. However, few studies have examined the effect of recreational or medicinal cannabis use on inflammatory pathways in peripheral blood cells among individuals with HIV. The goal for this study is to assess the anti-inflammatory effect of recreational marijuana use by YWH. Using a systems biology approach, unique genetic and cellular pathways within the peripheral blood cell transcriptome in a population of virally suppressed YWH on ART who used marijuana, alone or in combination with tobacco, compared to a reference group of youth without HIV.

  Study phs002090

• The Electronic Medical Records and GEnomics Network Genomic Risk Assessment (eMERGE IV)

  The eMERGE (electronic MEdical Records and GEnomics) network enrolled ~25,000 individuals not typically involved in research in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report along with recommended actions. The GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports and was returned to participants, their providers, and their EHR. The network is examining the uptake of care recommendations after return of results.Children's Hospital of Philadelphia (CHOP)The Center for Applied Genomics (CAG) is a specialized Center of Emphasis at the Children's Hospital of Philadelphia (CHOP) with the primary goal of translating basic research findings to medical innovations. The mission of CAG is to develop new and better ways to diagnose and treat children affected by rare and complex medical disorders. We aim to discover genetic causes for the most prevalent diseases of childhood including ADHD, asthma, autism, diabetes, epilepsy, obesity, schizophrenia, pediatric cancer, and a range of rare diseases. Ultimately, our objective is to generate new diagnostic tests and to guide physicians to the most appropriate therapies. Our participants are recruited from the CHOP Health Care Network, which includes over 50 sites throughout Pennsylvania and New Jersey, 100% of which use Epic EMR system. This constitutes the country's largest pediatric integrated delivery system, supporting >1.1 million visits/year within the primary and specialty care networks, community-based inpatient pediatric and neonatal programs, a rehabilitation hospital, and a home care service. It provides acute- and well-care to patients in urban, rural, and suburban settings.Cincinnati Children's Hospital Medical Center (CCHMC)CCHMC has proposed ambitious initiatives for eMERGE IV. The major goals are to generate, return as appropriate along with clinical recommendations, individualized genomic risk assessments that include polygenic risk scores for 2500 minority participants ascertained on dyads (mother/child) and extended to families (dyad + biologic father, siblings). The informatics initiatives include integration of electronic medical records and development, implementation and evaluation of clinical decision support at two different hospital systems, one pediatric and one adult. Participant preferences, education needs, and ethical and social implications will be studied throughout the 5 year period. Columbia UniversityColumbia University in partnership with the New York-Presbyterian hospital has a long and strong tradition of patient-centered research and community engagement in the urban, medically underserved communities of Washington Heights and Harlem in Northern Manhattan, and has established Precision Medicine as a major university-wide initiative (PMI), of which eMERGE is a vital program. We possess broad and deep expertise in clinical genetics, genomics, informatics, EHR phenotyping, systems biology, public health, and ELSI, including return of genetic results and secondary findings to diverse patients. Columbia will share lessons learned in linking EHR and sequence data for genomic decision support, developing scalable genomic education methods and assessing the impact of returning genetic results on patients, families, and clinicians. We are poised to contribute novel comprehensive risk prediction and management solutions for diverse patients as part of eMERGE IV efforts.Icahn School of Medicine at Mt. Sinai (Mt. Sinai)Mt. Sinai investigators have been at the center of many NHGRI-led genomic research (GSP, PAGE) and genomic medicine (eMERGE, CSER, IGNITE) consortia. Building on our decade-long track record in genomic research, clinical trials, and genomic medicine in diverse, underserved patients from New York City, we propose to develop new frameworks to bring genomic risk into clinical care to promote health equity. In addition to genomic discovery and risk prediction, we are creating analytical and data resources, and digital health applications tailored to diverse populations, as part of the eMERGE IV Network. The Mt. Sinai team is composed of clinicians and scientists who work closely with community members and industry partners to develop flexible and innovative strategies to bring leading-edge research into clinical care. Having recently announced a large institutional investment to scale the integration of genomics and artificial intelligence into patient care, Mt. Sinai is poised to contribute to eMERGE IV's mission to implement and learn from genomic risk assessment in clinical care. Mt. Sinai's team will contribute to progress in multiple areas across eMERGE, including developing and deploying electronic phenotypes; discovering new genotype-phenotype associations; and facilitating the communication of genomic results to patients and their healthcare providers.Mass General BrighamThe eMERGE IV Clinical Center at Mass General Brigham leverages a large biobank, clinical data in the electronic health records (EHR) for >6 million patients from the largest integrated health care provider in New England, advanced bioinformatics expertise, prior leadership in PRS development, established expertise in returning genomics results, and experience using information technology to transform clinical processes and assess medical, behavioral and economic outcomes. We have developed highly specific machine learning algorithms for e-phenotypes and implemented eMERGE algorithms for multiple phenotypes and have considerable experience in developing decision support tools and analyzing outcomes that can be leveraged to study the integration of PRS data into clinical practice. We will test the hypothesis that PRS will allow us to stratify eMERGE participants based on genetic risk for common complex traits. We will focus on coronary artery disease, atrial fibrillation, type 2 diabetes, colorectal cancer and depression in GWAS populations and validate multi-ethnic PRS in the Mass General Brigham Biobank and eMERGE III dataset. We will conduct an analysis of the effect of disclosing results to high risk participants to determine how personalized results changed patient outcomes in laboratory values, risk reduction behaviors, or health care utilization.Mayo Clinic (Mayo)The goal of Mayo eMERGE investigators is to leverage the electronic health record (EHR) for genomic discovery and to implement genomic medicine to improve health care outcomes, working closely with other eMERGE sites and the Mayo Center for Individualized Medicine. In eMERGE I we used genotype data and electronic phenotyping algorithms for genomic discovery. In eMERGE II we conducted a clinical trial of disclosing a polygenic risk score (PRS) for coronary heart disease (CHD) and placed pharmacogenomic variants in the EHR with linkage to clinical decision support (CDS). In eMERGE III, we returned actionable findings from targeted sequencing of 68 genes and collaborated with a Federally Qualified Health Center (FQHC) to bring genomic medicine to an under-represented population. In eMERGE IV, as part of the Genomic Risk Assessment & Management Network, we will test the hypothesis that individuals at high polygenic risk for common diseases will have a higher uptake of risk reduction measures than those at lower risk. We will build on our prior work in genomic discovery, EHR integration and return of results (RoR) to develop and validate PRS and combine these with clinical risk scores and family history to compute comprehensive risk profiles for 2500 individuals. Our prior work in disclosing a PRS for CHD to research participants as part of a comprehensive risk profile enables us to efficiently expand the approach to other common diseases that pose a significant public health burden. To assess the utility of PRSs, we will recruit 1800 adults and 200 adolescents from Rochester MN and 500 adults from Phoenix AZ. DNA will be sent for CLIA-certified genomic testing and we will calculate ancestry specific PRSs for each participant. Individualized risk estimates will be reported to participants and health care providers (HCPs) and placed in the EHR with linkage to CDS that includes guideline-based risk-management information. For participants who are at significantly higher polygenic risk of developing at least 1 of the diseases, results will be disclosed in-person by a HCP followed by assessment of outcomes including new tests ordered, risk reduction measures, and changes in modifiable risk factors. We will examine the economic, behavioral and psychosocial implications of returning PRS. Our focus on PRS for common cardiovascular diseases brings genomic medicine to the population. We will continue our partnership with Mountain Park Health Center, a FQHC serving low-income, minority communities in Phoenix AZ, to address concerns about health disparities in the context of genomic medicine.Northwestern University (NU)Northwestern University is dedicated to translational genomics, with a strong focus on unified, interdisciplinary research bridging the informatics, clinical, basic science, and bioethics domains. Over the phases of eMERGE, Northwestern has applied this interdisciplinary approach to study the feasibility, utility, outcomes, and effectiveness of EHR-linked genomic information as a member of the network. Particular areas of focus include: novel informatics approaches to integrate genomic results into EHR systems; development of open-source, EHR-based phenotyping algorithms to empower translational research across a variety of clinical domains; and studies of participant, patient, and provider interaction with EHR-based genomic results. In phase IV of eMERGE, Northwestern is building on this expertise to develop, deploy, and evaluate systems of EHR-based, genomics-guided clinical risk assessment and management tools across a variety of common, impactful conditions. Northwestern's cross-disciplinary approach to this work is empowered by an innovative smartphone app to consolidate outreach, enrollment, engagement, return of results, and dissemination of health education materials surrounding genetic risk and risk management. Focusing recruitment on community-based clinics, Northwestern aims to engage participants from communities that, though not traditionally included in academic research settings, could benefit significantly from these risk management approaches. By combining expertise in informatics and EHR integration with innovative return-of-results strategies rooted in behavior theory, Northwestern aims to provide valuable data on accuracy, utility, and uptake of genetic risk assessment as the field moves towards integrating genetic risk scores into clinical practice.University of Alabama at Birmingham (UAB)Our eMERGE team aims to bring our experience and expertise in research with medically underserved (>75%) populations to identify genomic signatures of common diseases, conduct genomic risk assessments within the clinical workflow and where appropriate, pre-treat at-risk patients with common diseases including diabetes, chronic obstructive pulmonary disease, obesity, coronary artery disease and prostate cancer. Our aims will also allow us to develop genomic risk assessments, and address challenges involved in bringing genomic medicine into routine medical care. Working with the eMERGE network, we will select the eleven diseases of public health impact and select polygenic risk scores for clinical implementation. We will conduct an ethical legal social implications (ELSI) study, to explore patient perspectives on the use of family history and polygenic risk scores for estimating disease risk among Alabama Genomic Health Initiative (a statewide cohort) participants. The results will inform the development of consent, educational materials, and a communication strategy to enhance recruitment and retention of eMERGE participants. Recruiting over 75% of patients from medically underserved communities, we will incorporate genomic risk, family history, and clinical data to identify high-risk patients, recommending risk reduction recommendations in concordance with practice guidelines. For high-risk patients, we will deploy clinical decision support and present the genomic risk assessments and risk reduction recommendations. We will assess three outcomes: uptake of recommendations (implementation outcome), adherence to clinic visits (engagement outcome), and surrogates of disease/control (clinical outcome; e.g. blood sugar, cholesterol). We bring our expertise and experience to collaborate with the eMERGE investigative team to leverage the power of genomics to prevent disease.University of Washington (UW)The eMERGE IV Northwest partnership includes clinicians, scientists, and professionals in other fields from University of Washington (UW) Medicine, UW Health Sciences, the Fred Hutchinson Cancer Research Center, and the Brotman Baty Institute for Precision Medicine. The eMERGE IV Northwest partnership aims to evaluate the use of genomic information in the health care of diverse participants at the University of UW. Our site is expected to lead work on the prediction of colon cancer, glaucoma, and cardiovascular disease; other conditions expected to be studied include diabetes, liver disease, high cholesterol, and osteoporosis. Working with our eMERGE colleagues, we will aggregate, into a single score that informs about the risk of a disease, a participant's polygenic test information, which looks at variants from across the genome, as well as other known risk factors, such as personal and family medical history, environmental and social determinants, and physical and lab results. This score would let clinicians know which patients might benefit from screenings or other interventions to reduce the risk of disease or make an early diagnosis. In addition to experts specializing in each of the medical conditions that are the focus of the Northwest site, leaders in health economics, and in the ethical and societal aspects of genomics and health care will also be part of the research team. Medical, as well as economic, outcomes will be measured. Stakeholder engagement will be encouraged to obtain comments from participants and their families.Vanderbilt University Medical Center (VUMC)Vanderbilt University Medical Center has embraced Personalized Health and Healthcare as a key pillar of our Research Strategic Plan. This institutional commitment has taken multiple forms including the development of key infrastructure resources (the institutional Biobank (BioVU); the program in preemptive pharmacogenetic testing; the genotyping and sequencing core) and support of faculty in key disciplines such as genomics, informatics, ethics, privacy science, and clinical pharmacology. VUMC's team has contributed importantly to progress in multiple areas across eMERGE, including developing and deploying phenotype algorithms; developing and managing the genotype quality control pipeline for the network (eMERGE I); discovering new genotype-phenotype relations in VUMC and cross-network datasets; actively participating in the PGx clinical implementation project, community consultation, and return of results initiatives; developing methods to resolve tensions between data access and individual privacy; developing sampling methodology for the CERC survey; and developing new software tools for the field, including for developing and validating phenotypes, de-identification and for the phenome-wide association study paradigm (“PheWAS”)eMERGE Network Coordinating Center (CC)Vanderbilt University Medical Center has been the coordinating center of the eMERGE Network since inception. During this phase of eMERGE we have partnered with the Broad Institute to to add expertise in large-scale genotyping, cloud computing, and genomic data analysis and management, and with Duke University to leverage its proficiency in the implementation of patient-oriented family history tools and delivery of risk assessments. To meet the needs of the Network, the CC continues to serve NHGRI, the Network, and its members in all coordination, communication, and collaboration functions while providing a nationally visible home for eMERGE authored tools and scientific productivity. The CC is also assisting the Network with selecting and validating polygenic risk scores (PRS) for approximately eleven complex diseases and developing genomic risk assessments (GRAs) which combine the PRS with other clinical risks, family history, and monogenic risks. Finally, The CC will coordinate a prospective study for 25,000 participants which calculates clinical and genomic risks for participants and their providers. In addition to providing the genotyping and PRS reporting services, we will develop with the Network scalable EHR-based methods to assess uptake of risk-reduction recommendations and clinical impact.

  Study phs003905

• RNA Transcriptomic and DNA Methylation Landscape in FTLD-TDP and Controls

  Frontotemporal lobar degeneration (FTLD) is one of the leading causes of dementia in individuals younger than 65 years, with the aggregation of TDP-43 as one of the most common forms of FTLD. FTLD-TDP is clinically, genetically and pathologically heterogeneous, with GRN and C9orf72 as the most common genetic forms (although more than 50% of the cases are genetically unexplained), and A, B and C as the most common pathological subtypes. To investigate the molecular differences between the different forms of FTLD-TDP, we performed bulk RNA sequencing (RNAseq) and reduced representation bisulfite sequencing (RRBS) from different brain regions of FTLD-TDP patients and controls. The RNAseq dataset includes samples from the frontal cortex of 149 individuals, comprising 127 FTLD-TDP cases (genetically unexplained types A (27), B (20) and C (22), 24 GRN mutation carriers, and 34 C9orf72 expansion carriers) and 22 controls. The RRBS dataset includes samples from the frontal cortex of 158 individuals —119 FTLD-TDP cases (genetically unexplained types A (25), B (24), and C (25), 20 GRN mutation carriers, and 25 C9orf72 expansion carriers) and 39 controls; and from the cerebellum of 151 individuals —113 FTLD-TDP cases (genetically unexplained types A (24), B (21), and C (23), 20 GRN mutation carriers, and 25 C9orf72 expansion carriers) and 38 controls. In total, the study consists of data from 183 unique individuals, with some overlap across the different datasets.

  Study phs004075

• Genetic Testing to Understand and Address Renal Disease Disparities across the United States (GUARDD-US)

  GUARDD-US is a prospective, multicenter, unblinded, two arm randomized pragmatic clinical trial. Participants will be randomized in a 1:1 ratio to immediate APOL1 gene testing and return of results (ROR) to participant and provider (Intervention arm) versus delayed APOL1 gene testing and ROR to participant and provider (Control arm). The main study will compare outcomes between APOL1 positive participants in the Intervention arm (i.e., early knowledge of APOL1 status) to APOL1 positive participants in the Control arm (i.e., delayed knowledge of APOL1 status). Participants that are APOL1 negative in the Intervention and Control groups will not be included in the main study analyses.Approximately 6,750 participants of African ancestry, age 18-70, with hypertension that either: 1) do not have diabetes and do not have CKD, or 2) have CKD (with or without diabetes) were randomized for the GUARDD-US study. GUARDD-US also includes a substudy to determine the effect of knowledge of genetic test results that predict efficacy of various antihypertensive medications on change in SBP from baseline to 3 months in APOL1 negative individuals at participating sites. The population for the PGx substudy were participants from main study (above) who were randomized to Intervention and who test negative for APOL1. Only participants from PGx substudy participating sites were included in this population.

  Study phs004045

• Virginia PrIMeD Study

  The goal of this study was to determine whether screening children (2-16 yrs) in pediatric waiting rooms for genetic risk of type 1 diabetes (T1D) could be applied to diverse (by geography, genetic ancestry) communities, and for those at "high genetic risk," if barriers prevent subsequent screening for presence of islet autoantibodies. A total of 3,818 children were recruited from eight general pediatric and specialty clinics across Virginia. Clinical Research Coordinators were stationed at each clinic and obtained informed consent/assent, a brief medical history, and a saliva sample for DNA extraction and determination of their genetic risk using a T1D Genetic Risk Score (T1D GRS). Children were present in the clinic for a "healthy" visit, although children with and without a history of T1D were recruited into the study. Age, sex, self-reported ancestry/race, T1D history, and other medical history information was obtained. DNA was extracted from the saliva samples and genotyping with a T1D-focused array using 74 SNPs (including 26 SNPs in the HLA region) provided data to generate a T1D GRS for each individual. Of the 3,818 children recruited, there was a slight excess of males (1,959, 51.3%), a majority of white and Hispanic/Latino ancestry (82.8%), and 91 (2.4%) with prevalent T1D. A total of 542 (14.2%) had "high T1D genetic risk" (T1D GRS > 5). Although the T1D GRS included non-HLA genetic variants, 80% of those with "high genetic risk" would have been classified using only those SNPs in the HLA region alone. Of children with "high genetic risk" and without pre-existing T1D (n=494), 7.0% (34/494) consented for islet autoantibody screening. Among children with pre-existing T1D (n=91), 52% (n=48) also had a "high genetic risk." The HLA-focused T1D GRS was not significantly associated with age at onset of T1D. Of those at high genetic risk that consented for autoantibody testing (n=34) and completed the blood collection (n=28), two (2/28, 7.1%) tested positive for multiple autoantibodies and were at significant risk of developing T1D. Follow up of 55% of parents/guardians identified 2 (of 2,096, 0.095%) participants who developed T1D, one at "high genetic risk" and one with a first-degree relative with T1D. A major factor in obtaining islet autoantibody testing was concern over SARS-Cov-2 exposure and an independent non-scheduled blood collection.Individual-level data at each SNP (genotyped and imputed) for T1D genetic risk and affiliated data are provided in dbGaP.

  Study phs003609

• Prevention and Early Treatment of Acute Lung Injury (PETAL) Network - Functional, Imaging, and Respiratory Evaluation in CORAL (PETAL FIRE CORAL-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from PETAL FIRE CORAL include plasma and whole blood. Please note that use of biospecimens in genetic research is subject to a tiered consent and biospecimens may not be used to produce commercial products.Objectives: To examine the recovery from COVID-19 disease following acute hospitalization with an emphasis on functional, imaging, and respiratory evaluation, and assess the feasibility of conducting a larger study to evaluate variables associated with differential recovery.Background: The BLUE CORAL study, dbGaP phs003419, was intended to address the knowledge gaps and provide critical data to help guide clinical care, public health, and scientific efforts regarding SARS-CoV-2 (COVID-19) recovery. The understanding and treatment of long-term sequelae of COVID-19, referred to variously as post-acute sequelae of COVID-19 (PASC), post-acute COVID, long COVID, or long-haul COVID, is fundamental to patient recovery. These long-term consequences are common and increasingly recognized, although heterogeneous in manifestation, and can result in a failure to return to baseline level of health. At the time of the FIRE CORAL study, there were limited studies that collected objective assessments following hospital discharge for a wide spectrum of patients surviving COVID-19.Participants: FIRE CORAL enrolled adult participants as a subset of those enrolled in the BLUE CORAL study with a recent COVID-19 hospitalization and that completed the 1- or 3-month post-hospital telephone long-term outcomes assessment. The target enrollment for this pilot study cohort was 80 participants.Design: FIRE CORAL was a multicenter prospective cohort study of participants recovering from COVID-19 disease with in-person follow-up, as an extension of the BLUE CORAL study. The study consisted of a battery of assessments objectively measuring pulmonary function, abnormalities on lung imaging, and functional status. Participants were to attend and perform initial in-person testing at 3 to 9 months after hospital discharge. Participants with abnormal findings on pulmonary function testing or chest imaging during their initial assessment or those with persistent respiratory symptoms were eligible to repeat study procedures 3 months later with a subsequent visit at 12 months. All participants were invited to return for in-person follow up at 12 months after hospital discharge. Assessments included high-resolution chest CT scan without contrast, spirometry, lung volume assessment, diffusing capacity measured by single breath measurement, Six Minute Walk Test, Short Physical Performance Battery, St. George's Respiratory Questionnaire, and Functional Assessment of Chronic Illness Therapy-Fatigue scale. Demographic and hospitalization data are available as part of the BLUE CORAL study.The primary aim of the FIRE CORAL study was to examine the feasibility of conducting rigorous in-person follow-up testing of participants discharged from the hospital following COVID-19 illness to assist with planning for a larger study to evaluate variables associated with differential recovery. The secondary aim was to describe the pulmonary, imaging, and functional recovery following COVID-19 hospitalization in a diverse population of patients.

  Study phs004130

• HudsonAlpha Long Read Sequencing Data of Individuals with Rare Suspected Genetic Conditions

  The data included in this project were generated from several IRB projects focused on the identification of the underlying genetic cause of undiagnosed rare conditions in infants, children and adults enrolled across the southeastern United States. Long read genome sequencing was performed on DNA samples collected as part of an IRB-approved study and findings from this testing was returned to enrolled study participants and the clinical team providing care. Proband participants in these studies were enrolled in both inpatient (neonatal intensive care units) and outpatient settings. When possible, biological relatives (including both biological parents) were also enrolled to help clarify inheritance of variants identified. Sequencing and analysis for SouthSeq is conducted at the HudsonAlpha Institute for Biotechnology in Huntsville, Alabama (https://www.hudsonalpha.org/). Results of testing are disclosed to participants by genetic counselors or trained non-genetics providers who also facilitate sharing of results with the participants' medical care teams when appropriate. Further, participant families may choose to opt-into return of secondary findings identified in the proband, which focus on pathogenic and likely pathogenic variation identified within the current ACMG gene list.

  Study phs003537

• Germline Sequence Variation in Cancer Genes Among Rwandan Breast and Prostate Cancer Cases

  Inherited genetic information can reduce cancer risk and mortality using protocols for patient ascertainment, testing, counseling, prevention, and treatment. For example, carriers of germline BRCA1/BRCA2 or Lynch Syndrome mutations are at increased risk of breast, ovarian, prostate, endometrial, colorectal, and other cancers. Genetic testing is of clinical value because many mutations are actionable in reducing risk or determining appropriate treatment regimens. There is growing evidence that inherited genetic mutations represent a large proportion of cancer cases in sub-Saharan Africa (SSA). It is also well known that most cancer genetic testing data does not represent the racial and ethnic diversity of the US or global population. Despite the high proportion of cancer cases diagnosed at an early age and late stage, as well as the potential for interventions to reduce cancer risk and death by using genetic tools, genetic testing, counseling, and clinical management protocols have largely not been widely developed in SSA. In order to develop and evaluate the potential for genetic testing in SSA, we propose to undertake a proof of concept feasibility study of hereditary cancer that will contribute data on the prevalence of hereditary cancer mutations in SSA and inform the development of SSA-specific guidelines for cancer genetic testing. In this study, we undertook a pilot evaluation of research genetic testing and counseling in breast and prostate cancer cases in Rwanda that involved genetic testing of breast and prostate cancer cases.

  Study phs003927

• National Cancer Institute Multi-Ancestry Genome-Wide Association Study of Kidney Cancer (NCI-3)

  The National Cancer Institute (NCI) multi-ancestral genome-wide association study (GWAS) of kidney cancer ("NCI-3") was performed by NCI to further investigate common genetic variants associated with risk of kidney cancer and its two major subtypes across individuals of different ancestries (European, African, East Asian, Latin American). The NCI-3 GWAS includes 12,315 cases and 73,091 controls from 25 centers in North America, South America and Europe, genotyped using the Illumina Global Screening Array v2.0. SNP-level results from this GWAS were combined by meta-analysis with results from two earlier NCI European-ancestry GWAS (RCC; phs000351: 1,311 cases and 3,424 controls and phs001736: 2,417 cases and 4,391 controls), a NCI GWAS of African Americans (phs000863; 255 cases and 375 controls), GWAS conducted at other institutions [International Agency for Research on Cancer (scan 1: 2,438 cases and 5,071 controls; scan 2: 2,781 cases and 2,940 controls), The University of Texas MD Anderson Cancer Center (scan 1: 893 cases and 556 controls, scan 2: 1,241 cases and 1,712 controls) and the Institute for Cancer Research, UK (944 cases and 4,024 controls)] and GWAS analyses of data from three large biobanks (Biobank Japan: 523 cases and 86,306 controls; FinnGen: 2,095 cases and 304,956 controls; UK Biobank: 1,807 cases and 348,824 controls). Only individual-level data from NCI-3 and the two MD Anderson Cancer Center scans are included in this dbGaP submission. All study-specific and meta-analysis summary statistics are included.

  Study phs003505