93 results for ""A3+problem+solving"+"high+reliability"+"Swiss+cheese"+"simulation"+"boot+camp"+healthcare"

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• A study of resistance to novel coronavirus infection in health care workers

  There have been cases of what appear to be nosocomial infections among healthcare workers at several hospitals. The infected healthcare workers were assumed to have contracted the disease through close contact with infected patients. However, we confirmed at each medical institution that there were many healthcare workers who had apparently had closer contact with infected patients than with infected patients, but had not contracted the disease. Thus, the purpose of this study was to clarify the internal factors that make individuals less susceptible to novel coronavirus infection and their stress tolerance, and to establish a system that contributes to the appropriate allocation of healthcare workers and the creation of a system that can more safely deal with this disease in the future.

  Study JGAS000562

• Whole Genome sequencing of Angolan and Mozambican individuals

  To support the continued discovery and cataloguing of genomic variation in human populations and to further our understanding of the Bantu Expansion, we sequenced the genomes of 291 individuals from Cabinda, a northern exclave of Angola, and 49 individuals from Maputo, the capital of Mozambique. Utilising the power and flexibility of these whole-genome sequencing datasets, we discover rare variation, fine-scale population structure, and perform analyses using haplotype-based inference tools and our own model-based simulation framework to reconstruct complex dispersals of Bantu speak-ing populations across sub-Saharan Africa.

  Study EGAS00001007458

• Exome-wide mutation analysis of cell-free DNA to simultaneously monitor the full spectrum of cancer treatment outcomes

  Purpose: Cell-free DNA (cfDNA) offers a non-invasive approach to monitor cancer. Here we develop a method using whole-exome sequencing (WES) of cfDNA for simultaneously monitoring the full spectrum of cancer treatment outcomes, including MRD, recurrence, evolution, and second primary cancers. Experimental Design: Three simulation datasets were generated from 26 cancer patients to benchmark the detection performance of MRD/recurrence and second primary cancers. For further validation, cfDNA samples (n=76) from cancer patients (n=35) with six different cancer types were used for performance validation during various treatments.Results: We present a cfDNA-based cancer monitoring method, named cfTrack. Taking advantage of the broad genome coverage of WES data, cfTrack can sensitively detect MRD and cancer recurrence by integrating signals across known clonal tumor mutations of a patient. In addition, cfTrack detects tumor evolution and second primary cancers by de novo identifying emerging tumor mutations. A series of machine learning and statistical denoising techniques are applied to enhance the detection power. On the simulation data, cfTrack achieved an average AUC of 99% on the validation dataset and 100% on the independent dataset in detecting recurrence in samples with tumor fraction ≥0.05%. In addition, cfTrack yielded an average AUC of 88% in detecting second primary cancers in samples with tumor fraction ≥0.2%. On real data, cfTrack accurately monitors tumor evolution during treatment, which cannot be accomplished by previous methods.Conclusion: Our results demonstrated that cfTrack can sensitively and specifically monitor the full spectrum of cancer treatment outcomes using exome-wide mutation analysis of cfDNA.

  Study EGAS00001005906

• Veterans Administration (VA) Million Veteran Program (MVP) Summary Results from Omics Studies

  MVP is an ongoing prospective cohort study and mega-biobank in the Department of Veterans Affairs Healthcare System designed to study genetic influences on health and disease among veterans.

  Study phs001672

• NHLBI TOPMed: Partners HealthCare Biobank

  The Atrial Fibrillation Genetics Consortium (AFGen) was organized to identify common and rare genetic variation associated with atrial fibrillation risk. In the current study, we have performed whole genome sequencing in cases with early-onset atrial fibrillation. Samples in this study were enrolled as a part of the Partners HealthCare Biobank. Cases with early-onset atrial fibrillation were identified from the Biobank (defined as atrial fibrillation onset prior to 61 years and in the absence of structural heart disease).

  Study phs001024

• NHLBI TOPMed - NHGRI CCDG: Intermountain INSPIRE Registry

  The INtermountain Healthcare Biological Samples Collection Project and Investigational REgistry for the On-going Study of Disease Origin, Progression and Treatment (Intermountain INSPIRE Registry) purpose is to collect biological samples, clinical information and laboratory data from Intermountain Healthcare patients. The registry originally collected samples in patients undergoing a coronary angiography as part of the Intermountain Heart Collaborative Study. It has been expanded to collect samples in patients diagnosed with all types of medical conditions, and patients from the general population including those who have not been diagnosed with health related issues. Just over 25,000 individuals have provided samples as part of this registry. The registry enables researchers to develop a comprehensive collection of information that may help in disease management, including determining best medical practices for predicting, preventing and treating medical conditions.

  Study phs001545

• Whole-genome sequencing of rare disease patients in a national healthcare system

  Most patients with rare diseases do not receive a molecular diagnosis and the aetiologicalvariants and mediating genes for more than half such disorders remain to be discovered. Weimplemented whole-genome sequencing (WGS) in a national healthcare system to streamlinediagnosis and to discover unknown aetiological variants, in the coding and non-coding regionsof the genome. In a pilot study for the 100,000 Genomes Project, we generated WGS data for13,037 participants, of whom 9,802 had a rare disease, and provided a genetic diagnosis to1,138 of the 7,065 patients with detailed phenotypic data. We identified 95 Mendelianassociations between genes and rare diseases, of which 11 have been discovered since 2015and at least 79 are confirmed aetiological. Using WGS of UK Biobank1, we showed that rarealleles can explain the presence of some individuals in the tails of a quantitative red blood cell(RBC) trait. Finally, we reported 4 novel non-coding variants which cause disease through thedisruption of transcription of ARPC1B, GATA1, LRBA and MPL. Our study demonstrates asynergy by using WGS for diagnosis and aetiological discovery in routine healthcare.

  Study EGAS00001004364

• Homopolymer switches mediate adaptive mutability in mismatch repair-deficient colorectal cancer

  Mismatch repair (MMR) deficient cancer evolves through the continuous erosion of coding homopolymers in target genes. Curiously, the MMR genes MSH6 and MSH3 also contain coding homopolymers and these are frequent mutational targets in MMR-deficient cancers. The impact of incremental MMR mutations on MMR-deficient colorectal cancer evolution is unknown. We show that microsatellite instability modulates DNA repair by toggling hypermutable mononucleotide homopolymer runs in MSH6 and MSH3 through stochastic frameshift switching. Spontaneous mutation and reversion modulates subclonal mutation rate, mutation bias, and clonal HLA and neoantigen diversity. Patient-derived organoids corroborate these observations and show that in the absence of immune selection MMR homopolymer sequences drift back into reading frame, suggesting a fitness cost of elevated mutation rates. Combined experimental and simulation studies demonstrate that subclonal immune selection favours incremental MMR mutations. Overall, our data demonstrate that MMR-deficient colorectal cancers fuel intratumour heterogeneity by adapting subclonal mutation rate and diversity to immune selection.

  Study EGAS50000000297

• Systematic comparative analysis of single-nucleotide variants detection methods from single-cell RNA sequencing data

  Systematic interrogation of single nucleotide variations (SNVs) is one of the most promising approaches to delineate the cellular heterogeneity and phylogenetic relationships at the single cell level. While SNV detection from abundant single cell RNA sequencing (scRNA-seq) data is applicable and cost-effective in identifying expressed variants, inferring sub-clones, and deciphering genotype-phenotype linkages, there is a lack of computational methods specifically developed for SNV calling in scRNA-seq. Although variant callers for bulk RNA-seq have been sporadically used in scRNA-seq, the performances of different tools have not been assessed. Here, we performed a systematic comparison of seven tools including SAMtools, the GATK pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, using both simulation and scRNA-seq datasets, and identified multiple elements influencing their performance. Our study provided the first benchmarking to evaluate the performances of different SNV detection tools for scRNA-seq data.

  Study EGAS00001003883

• eMERGE Phase III Clinical Center at Partners HealthCare

  The Partners HealthCare Biobank is a large research data and sample repository working within the framework of Partners Personalized Medicine. It provides researchers access to high quality, consented samples to help foster research, advance understanding of the causes of common diseases, and advance the practice of medicine. The Partners Biobank provides banked samples (plasma, serum and DNA) collected from consented patients. These samples are available for distribution to Partners HealthCare investigators with appropriate approval from the Partners Institutional Review board (IRB). They are linked to clinical data that originates in the Electronic Medical Record (EMR), as well as additional health information collected in a self-reported survey. The Partners Biobank will be genotyping 25,000 subjects with the Illumina Multiethnic Beadchip 1.6 million SNPs with exome and custom content (> 60,000 LoFs). Of the participants genotyped so far, 4929 of 4962 (99.3%) individuals have genotype data that passed the default quality thresholds for the Infinium array (call rate >= 0.99). We are submitting the genotype data to dbGaP for 4929 subjects with 12 phenotypes (based on icd9 codes). We will do annual releases until we reach the full 25,000 genotyped subjects.

  Study phs000944

• Whole-genome sequencing of rare disease patients in a national healthcare system

  Most patients with rare diseases do not receive a molecular diagnosis and the aetiological variants and mediating genes for more than half such disorders remain to be discovered. We implemented whole-genome sequencing (WGS) in a national healthcare system to streamline diagnosis and to discover unknown aetiological variants, in the coding and non-coding regions of the genome. In a pilot study for the 100,000 Genomes Project, we generated WGS data for 13,037 participants, of whom 9,802 had a rare disease, and provided a genetic diagnosis to 1,138 of the 7,065 patients with detailed phenotypic data. We identified 95 Mendelian associations between genes and rare diseases, of which 11 have been discovered since 2015 and at least 79 are confirmed aetiological. Using WGS of UK Biobank1, we showed that rare alleles can explain the presence of some individuals in the tails of a quantitative red blood cell (RBC) trait. Finally, we reported 4 novel non-coding variants which cause disease through the disruption of transcription of ARPC1B, GATA1, LRBA and MPL. Our study demonstrates a synergy by using WGS for diagnosis and aetiological discovery in routine healthcare.

  Dataset EGAD00001006065

• Million Veteran Program (MVP) Summary Results from Non-Sensitive Omics Studies

  MVP is an ongoing prospective cohort study and mega‐biobank in the Department of Veterans Affairs Healthcare System designed to study genetic influences on health and disease among veterans. This is the accession to hold publicly available results. Results from sensitive phenotypes or MVP population subsets can be found at accession phs001672 and will require an application for access.

  Study phs002453

• EXCEED Study

  EXCEED is a longitudinal population-based cohort which facilitates investigation of genetic, environmental and lifestyle-related determinants of a broad range of diseases and of multiple morbidity through data collected at baseline and via electronic healthcare record linkage. Recruitment has taken place in Leicester, Leicestershire and Rutland since 2013 and is ongoing, with approximately 10,000 participants aged 30-69 to date. The population of Leicester is diverse and additional recruitment from the local South Asian community is ongoing.

  Study EGAS00001003499

• Emirati Phased Diploid Trio-Assemblies

  This study, conducted under the Emirati Genome Project, aims to build a foundational pangenome reference to enable precision medicine in the United Arab Emirates. We generated phased diploid genome assemblies for 27 Emirati nationals using deep PacBio HiFi sequencing and a trio-based assembly procedure. In total, this produced 54 haplotype-resolved assemblies representing maternal and paternal genomes for each participant. The resulting high-quality reference captures population-specific genetic diversity and will accelerate translational research, variant interpretation, and genome-informed healthcare in the region.

  Study EGAS50000001234

• Normative Aging Study (NAS)

  The Normative Aging Study (NAS) is a longitudinal study established by the United States Department of Veterans Affairs in 1963. Participants were male residents and free of chronic disease at the time of recruitment. Participants were invited to undergo an in-person examination every 3-5 years. Participants provided information on medical history, lifestyle and demographic factors and underwent a physical examination and laboratory tests, at each visit. Participants provided written informed consent at each visit, and the VA Boston Healthcare System Institutional Review Board approved the study.

  Study phs000853

• Single-cell analysis of upper airway cells reveals host-viral dynamics in influenza infected adults

  This observational study was designed to determine the cellular tropism of Influenza A and B Viruses (IAV, IBV) from samples taken from the upper respiratory tract collected during routine nasal washes during the 2017-2018 season. Using single-cell RNA sequencing (scRNA-seq) we sought to determine which cell types could be infected, what the cellular response was to infection in both infected and bystander cells, and to compare the intra/inter-host variability of IAV and IBV during a single season at a single healthcare provider location.

  Study phs002039

• ABHD11 Autoimmunity Study DAC

  This DAC oversees controlled access to human RNA-seq data generated as part of the project “ABHD11 inhibition and T cell function in autoimmunity” at Swansea University. The DAC will evaluate and approve access requests based on scientific merit and alignment with participant consent. Data requests will be considered from academic researchers and healthcare professionals working on immunology or autoimmunity.

  Dac EGAC50000000750

• Genetic Markers of Caries Risk in Diverse Underserved Children: CIDR

  The study Predicting Caries Risk In Underserved Children, From Toddlers To The School-age Years In Primary Healthcare Settings, is a renewal of an initial project designed to develop a dental caries risk tool for use in primary medical and dental healthcare settings to identify high dental caries risk children, expanding from the toddler (1-4 years old, referred to as Stage 1 grant) to the school-age years (6-9 years old, referred to as Stage 2 grant); and to determine the relationships between dental caries risk profiles and dental caries disease patterns. 1326 children, 12 +/- 3 months of age, and their primary caregivers, were enrolled in the study. This cohort represents a diverse population, including ethnic and racial minorities and low socio-economic status groups. There are a total of six in-person visits (at child age 1, 2.5, 4, 6.5, 8 and 9.5 years), and at each one the primary caregiver (PCG) completes a dental caries risk questionnaire, and the child receives a detailed dental caries examination. Saliva samples were collected during the age 8 visit (2019-2020) from 1,059 racially and ethnically diverse individuals (543 children and 516 PCGs) for the purposes of human genetic testing, to study the genetics of dental caries experience of children and their primary caregivers.

  Study phs003280

• The Federated EGA network

  In the last 10 years, most human omics data has been generated in the context of research consortia while recently there has been an emergence of large cohorts of human data generated by healthcare initiatives. Many countries in Europe now have nascent personalised medicine programmes. Thus, human genomics is shifting from being predominantly research-driven to being funded through healthcare systems. Genetic data generated in a healthcare context is subject to more stringent information governance than research data and nonetheless all data must adhere to national data protections laws. In this context, EGA identified the need for the development of a federated network to enable secure sharing of data whilst enabling genetic data to remain within the jurisdiction in which it was generated. The Federated EGA is designed to support national data management requirements for genomic and clinical data collected from citizens as part of healthcare or biomedical research projects. It includes a secure authorised access mechanism to support research use of these data across Europe and worldwide. We have engaged with over 14 ELIXIR countries to develop the federation model. The EGA federated configuration is composed of Central EGA, Federated EGA nodes and Community EGA nodes: Central EGA offers international submissions and helpdesk support, currently EGA co-managed by EMBL-EBI and CRG, Federated EGA nodes offer EGA services to researchers within their national jurisdiction, Community EGA nodes are individual institutions or initiatives with human genetic data intended to be shared with the research community. Key services available in the Federated EGA structure are: Central EGA Federated EGA node Community EGA nodes Data submission Offers international submissions service Offers submission service in a particular jurisdiction Does not offer an external submissions service Helpdesk support Provides external international helpdesk Provides helpdesk support for submitters in its jurisdiction and for approved users of data managed at its facilities Provides helpdesk support only for approved users of data managed at its facilities Data distribution Manages worldwide distribution for data hosted at Central EGA Manages worldwide distribution for data hosted at Federated EGA node Distribution for data hosted at Community EGA node EMBL-EBI and CRG have prepared a series of documents describing the overall governance and coordination framework. These describe the Federated EGA structure, the rights and responsibilities of the different parties and governing committees, and node operation guidelines. The federation governance proposal is under review by the first countries invited to join as Federated nodes, with further interested countries likely to join in the coming years. The Central EGA team has been working closely with many ELIXIR partners, including ELIXIR Finland, Luxembourg, Germany, Norway, Spain and Sweden.

  Blog the-federated-ega-network

• NanoSring of PBMC from bladder cancer and RCC patients

  PBMCs from patients were isolated using 50 mL Leucosep™ tubes (Greiner Bio-One International, Germany) and Ficoll-Paque™ PLUS (GE Healthcare, Sweden). Whole blood drawn into sodium heparin blood collection tubes were diluted 3x with phosphate-buffered saline (PBS) without calcium or magnesium (Lonza, Walkersville, MD). Diluted cell suspensions were carefully layered on Leucosep tubes and centrifuged for 15 minutes at 800 x g at room temperature (RT). Interphase containing PBMCs were harvested and washed with PBS and subsequently centrifuged for 10 minutes at 250 x g at RT before further processing.

  Study EGAS00001004229

• Single cell exome sequencing of lung adenocarcinoma

  Single cell exome sequencing was performed on 200 single cells isolated from a lung adenocarcinoma, female, non-smoker patient. The cells were derived from two distant tumour sectors and a far normal sector. The single cells were amplified on the Fluidigm C1 machine using the GE Healthcare illustra GenomiPhi V2 DNA Amplification Kit prior to sequencing library preparation. In addition, bulk exome sequencing was also conducted for each tumour sectors. For this study, somatic variations were detected from the single cells and phylogenetic clustering was conducted to elucidate the evolutionary trajectory of lung cancer.

  Study EGAS00001002972

• CSER: Evaluating Utility and Improving Implementation of Genomic Sequencing for Pediatric Cancer Patients in the Diverse Population and Healthcare Settings of Texas: The KidsCanSeq Study

  Through this Clinical Sequencing Evidence-Generating Research (CSER) with Enhanced Diversity project we are completing a clinical study (The Texas KidsCanSeq Study) comparing the results of targeted cancer panel sequencing versus genome-scale testing in pediatric cancer patients across diverse clinical settings. We will compare the targeted pediatric cancer panel to germline whole exome sequencing (WES) of unselected childhood cancer patients. We will also compare an RNA/DNA targeted pediatric cancer panel versus WES, transcriptome sequencing and copy number array of FFPE tumor samples for the subset of patients with high-risk tumors. Exome sequencing is performed from a blood or saliva sample of the pediatric age (0-18) patient. We are building on our success completing the CSER program BASIC3 exome sequencing trial (which included 60% Hispanic and African-American patients from a single large academic center) in this large multi-institutional study of an even more diverse patient population from six pediatric oncology healthcare settings across Texas. Data from the Texas KidsCanSeq study will be submitted through the CSER Data Coordinating Center for access in NIH-supported databases.

  Study phs002378

• Noninvasive prenatal molecular karyotyping from maternal plasma

  Fetal DNA is present in the plasma of pregnant women. Massively parallel sequencing of maternal plasma DNA has been used to detect fetal trisomies 21, 18, 13 and selected sex chromosomal aneuploidies noninvasively. Case reports describing the detection of fetal microdeletions from maternal plasma using massively parallel sequencing have been reported. However, these previous reports were either polymorphism-dependent or used statistical analyses which were confined to one or a small number of selected parts of the genome. In this report, we reported a procedure for performing noninvasive prenatal karyotyping at 3 Mb resolution across the whole genome through the massively parallel sequencing of maternal plasma DNA. This method has been used to analyze the plasma obtained from 6 cases. In 5 cases, fetal microduplications or microdeletions have been detected successfully from maternal plasma. The two cases with fetal microduplications represented the first noninvasive prenatal detection of such changes from maternal plasma. In the remaining case, the plasma DNA sequencing result was consistent with the pregnant mother being a carrier of a microduplication. Simulation analyses were performed for determining the number of plasma DNA molecules that would need to be sequenced and aligned for enhancing the diagnostic resolution of noninvasive prenatal karyotyping to 2 Mb and 1 Mb. In conclusion, noninvasive prenatal molecular karyotyping from maternal plasma by massively parallel sequencing is feasible and would enhance the diagnostic spectrum of noninvasive prenatal testing.

  Study EGAS00001000439

• Rapid Acceleration of Diagnostics - Digital Health Technologies (RADx-DHT): COVID-19 Experience Study (C19EX) Survey

  This was conducted virtually through the Achievement studies platform during the current COVID-19 pandemic. Participants were asked to complete a survey every day to capture information about whether they had experienced symptoms corresponding to respiratory, ILI, and COVID-19 infections within the previous 24 hour period, their experiences with the healthcare system, treatments, diagnostic testing, and their behaviors and potential risk factors. Participants were also asked to share their wearable activity tracker data. The purpose of this study was to better understand the geographic spread of diseases, impacts on daily life, and behavioral and physiological functioning in relation to recent self-reported respiratory disease, influenza-like-illness (ILI), and coronavirus disease (COVID-19) events.DOI: https://rapids.ll.mit.edu/10.57895/6m5z-je42

  Study phs002537

• IGNITE: Implementing GeNomics In practice: Genomic Medicine Implementation - The Personalized Medicine Program

  IGNITE is an NIH-funded network dedicated to supporting the implementation of genomics in healthcare. IGNITE was created to enhance the use of genomic medicine by supporting the development of methods for incorporating genomic information into clinical care and exploration of the methods for effective implementation, diffusion and sustainability in diverse clinical settings. As part of the IGNITE network, the University of Florida Health Personalized Medicine Program partners with health professionals and patients at UF Health and across the state to develop, implement, study and refine methods that allow genetic information to be used as a routine part of patient care. The program's initial focus is on pharmacogenetics. We also aimed to develop and implement innovative genomic medicine educational programs for health-care providers, health professions students, patients.

  Study phs001978

• Synthetic data - Genome in a Bottle

  In May, the National Institute of Standards and Technology (NIST) released its first genome in a bottle, a reference sample of DNA for validating human genome sequences. This so-called truth sequence comes from a decades-old sample donated by a Utah woman for (other) research purposes (NA12878 cell line), which, over the years, has been one of the most studied, and hence best-characterized, human samples. Seeing genomic medicine moving toward mainstream healthcare, researchers at NIST recognized the need for a reference human genome and assembled a private-public consortium in 2012 to create one. As detailed in a 2014 Nature Biotechnology paper (Nat. Biotechnol.32, 246–251, 2014), the group integrated and arbitrated among sequences from 14 data sets, five sequencing technologies, seven read mappers and three variant callers.

  Study EGAS00001005591

• eMERGE III: Columbia GENIE (Genomic Integration with EHR)

  The Columbia GENIE study contributes and shares phenotype and genotype data for individuals who were treated with our healthcare facilities and consented to share their data with dbGaP for scientific discovery. Some of these individuals have kidney or neurological problems and some are healthy volunteers from the Washington Height patient community. The purpose of this NOMAS study is to obtain information about physical features of the brain, carotid arteries, and heart. Some of our patients are pediatric patients with cardiac conditions. The study sample consists of four patient cohorts: Northern Manhattan Study (NOMAS), N=1072 Pediatric Cardiac Genomic Consortium (PCGC), n=374 Caribbean Hispanics with Familial and Sporadic Late Onset Alzheimer's disease (Caribbean Hispanics/AD), n=330 Alzheimer's Disease Sequencing Project (ADSP, n=44) Genetics of Chronic Kidney Disease Study, n=1256

  Study phs000961

• CSER: Incorporating Genomics into the Clinical Care of Diverse NYC Children (NYCKidSeq)

  The NYCKidSeq program will significantly advance the implementation of genomic medicine, particularly for children, young adults and their families in Harlem and the Bronx. The study will assess the clinical utility of genomic medicine in three broad areas of pediatric disorders, while engaging a range of providers and community advisors to overcome the well-documented barriers to inclusion of underserved and underrepresented populations in genomic research. The study will also include testing, analyzing, and implementing a novel communication tool, Genomic Understanding, Information and Awareness (GUÍA), to facilitate the return of genomic test results. The use of GUÍA will enhance the understanding of these genomic testing results by families, patients, and care providers at all levels of expertise, in two health systems. Healthcare system leadership will be engaged to provide insights into their readiness for genomic implementation. Overall, the NYCKidSeq program will inform the genomics and clinical communities about how to implement genomic medicine in a diverse population in a clinically useful, technologically savvy, culturally sensitive, and ethically sound manner.

  Study phs002337

• A Study of the Genetic Causes of Complex Pediatric Disorders

  The Center for Applied Genomics (CAG) at the Children's Hospital of Philadelphia (CHOP) is a high-throughput, highly automated genotyping and sequencing facility equipped with state-of-the-art genotyping and sequencing platforms. Children who are treated at the Children's Hospital Healthcare Network and their parents may be eligible to take part in a major initiative to collect more than 100,000 blood samples, covering a wide range of pediatric diseases. A large majority of participants consenting to prospective genomic analyses also consent to analysis of their de-identified electronic medical records (EMRs). EMRs are longitudinal, with a mean duration of 6.5 years. CAG has committed to releasing genotype and phenotype data for 4000 individuals diagnosed with asthma, ADHD, atopic dermatitis, GERD (1000 for each), and 1000 individuals on the upper and lower ranges of Low-Density Lipoprotein (LDL) levels to dbGaP. We will also release genotype/phenotype of 3000 controls. Relevant phenotype data includes primary diagnoses (ICD9 codes), secondary diagnoses (ICD9 codes), medical procedures/tests conducted in relation to the phenotype, and a listing of relevant medications. Further details of CAG's research programs and capacity are available at: http://www.caglab.org

  Study phs000490

• NHLBI Recipient Epidemiology Donor Evaluation Study (REDS)-III - Brazil Sickle Cell Disease Cohort (REDS-BSCDC)

  The Recipient Epidemiology and Donor Evaluation Study (REDS)-III program established a Brazilian Sickle Cell Disease (SCD) Cohort to identify molecular determinants of response to transfusions, alloimmunization and risk factors associated with HIV infection. The Brazil population presents a complex admixture of African, European, Asian and Indigenous heritage and will provide insights into genetic, demographic, social, and healthcare system determinates of SCD outcomes. The REDS-III Brazil SCD cohort began in the Fall of 2013 and aimed to: Establish a cohort of SCD patients with a comprehensive centralized electronic database of detailed clinical, laboratory and transfusion information, as well as establish a repository of blood samples to support biological studies relevant to SCD pathogenesis and transfusion complications; Characterize changes in markers of inflammation in response to transfusion by analyzing chemokine/cytokine panels in serial post transfusion specimens; Identify single nucleotide polymorphisms (SNPs) that contribute to the risk of red blood cell alloimmunization in SCD by performing a genome-wide association (GWA) study in transfused SCD patients; Characterize risk of HIV and HIV outcomes in the Brazilian SCD population and compare SCD outcomes among HIV sero-positive and sero-negative SCD patients.

  Study phs001972

• CSER: Exome Sequencing in Diverse Populations in Colorado and Oregon/CHARM Cancer Health Assessments Reaching Many

  The CHARM (Cancer Health Assessment Reaching Many) study, part of the Clinical Sequencing Evidence-Generating Research (CS.ER2) effort, aimed to assess the utility of clinical exome sequencing and how it affects care in diverse populations. The study population included adults at risk for hereditary cancer syndromes. The primary objective was the implementation of a hereditary cancer risk assessment program in healthy 18-49 year-olds in primary care settings within a vertically integrated health delivery system (Kaiser Permanente) and a federal qualified health center (Denver Health). The investigators aimed to assess clinical exome sequencing implementation and interpretation, as well as tailored interactions for low health literacy including a contextualized consent process, and a modified approach to results disclosure and genetic counseling. The investigators were also assessing the clinical utility (healthcare utilization and adherence to recommended care) and personal utility of primary and additional results from clinical exome sequencing, and evaluate the ethical and policy implications of considering personal utility of genomic information decisions for health care coverage.Sequencing and analysis for CHARM was conducted at the Northwest Clinical Genomics Laboratory, University of Washington, Seattle (https://nwgc.gs.washington.edu/).

  Study phs002111

• H3Africa - Deciphering Developmental Disorders in Africa

  Developmental disorders are typically rare conditions, causing an impairment in physical, learning, language, or behavioural areas. Genetic heterogeneity and highly variable clinical manifestations make diagnosing developmental disorders particularly challenging. Developmental disorders are increasing in prevalence in low- and middle-income countries, partly due to effective prevention and treatment of infectious diseases leading to a decrease in childhood mortality. New sequencing technologies are used effectively in the diagnosis of rare diseases and results can impact clinical practice significantly. Despite this international trend, very little implementation of these new approaches has taken place in low-resource settings, especially in Africa. The Deciphering Developmental Disorders in Africa (DDD-Africa) study aims to take advantage of an unbiased genotype-driven approach to improve healthcare services for patients. The study aims to recruit and perform detailed clinical phenotyping and exome sequencing (ES) on 500 African patients with a developmental disorder in whom a genetic diagnosis has not been confirmed. Where available, parents are also included in sequencing efforts. The project has two active research sites in Johannesburg (South Africa) and Kinshasa (Democratic Republic of Congo) representing diversity in geography, clinical, socio-economic, genetic and environmental factors.

  Study EGAS00001008319

• Count Me In (CMI): The Metastatic Prostate Cancer (MPC) Project (CMI-MPCproject)

  Count Me In - The Metastatic Prostate Cancer Project: A Patient-Driven Research Initiative to Accelerate Metastatic Prostate Cancer Research The Metastatic Prostate Cancer Project (MPCproject; http://mpcproject.org/) is a research study that empowers men with metastatic and advanced prostate cancer to partner directly with researchers by sharing their samples and clinical information, with the ultimate goal of accelerating scientific discoveries that have clinical impact. The MPCproject enables any man with metastatic or advanced prostate cancer in the US and Canada to participate in cutting-edge genomic and molecular research, regardless of where they live. Metastatic or advanced prostate cancer patients visit the project website and complete an online questionnaire of basic information about themselves and their cancer. Enrolled patients are mailed saliva and blood draw kits, which can be used to extract germline DNA and cell-free DNA (cfDNA), respectively. The study team contacts participants' healthcare institutions to obtain medical records and a portion of archived tumor samples. Whole exome sequencing is performed on tumor DNA, germline DNA, and cfDNA, and transcriptome sequencing is performed on tumor RNA. De-identified data, including linked genomic, clinical, and patient-reported data, are shared via public databases on a recurring pre-publication basis. Participants are regularly provided with updates on the study.

  Study phs001939

• Extreme phenotypes define epigenetic and metabolic signatures in cardiovascular diseases.

  Improving the understanding of cardiometabolic syndrome pathophysiology and its relationship with thrombosis are ongoing healthcare challenges. Using plasma biomarkers analysis coupled with the transcriptional and epigenetic characterisation of cell types involved in thrombosis, obtained from two extreme phenotype groups (obese and lipodystrophy) and comparing these to lean individuals and blood donors, the present study identifies the molecular mechanisms at play, highlighting patterns of abnormal activation in innate immune phagocytic cells and shows that extreme phenotype groups could be distinguished from lean individuals, and from each other, across all data layers. The characterisation of the same obese group, six months after bariatric surgery shows the loss of the patterns of abnormal activation of innate immune cells previously observed. However, rather than reverting to the gene expression landscape of lean individuals, this occurs via the establishment of novel gene expression landscapes. Netosis and its control mechanisms emerge amongst the pathways that show an improvement after surgical intervention. Taken together, by integrating across data layers, the observed molecular and metabolic differences form a disease signature that is able to discriminate, amongst the blood donors, those individuals with a higher likelihood of having cardiometabolic syndrome, even when not presenting with the classic features.

  Study EGAS00001003780

• Characterization of Structural Variants in Acute Myeloid Leukemia Patients

  Acute myeloid leukemia (AML) is the most common form of acute leukemia in adults and is expected to increase in frequency as the population ages. Most subtypes of AML are difficult to treat, in part due to a lack of understanding of possible molecular targets. Furthermore, the peak incidence of AML is in the sixth decade, and patients over the age of 65 do not tolerate chemotherapeutic regimens well. Moreover, AML has been highly studied as a model for other cancers. An RNA Biology Program is established aiming to develop comprehensive datasets through the profiling of all different classes of RNA expression, RNA editing, alternative splicing, and non-coding RNAs in CD34+ normal hematopoietic stem cells (HSC), their differentiated progeny, and AML clinical samples that could be utilized to understand leukemia. These datasets will allow us to computationally identify and characterize various RNA species and processes to enable the development of effective therapeutics to AML, leukemia and other types of cancers. Epigenetic factors such as methylation and histone modifications will also be characterized from these clinical samples allowing for integrated dataset analysis to look at the cross-talk between RNA and DNA/epigenomics in leukemia. The following is a subsidiary study of the above study description where whole genome sequencing was performed on two collected AML patients' samples using Illumina and Oxford Nanopore sequencing technologies. The aim is to characterize the roles of structural variants (SV) in RNA biology which are potentially important for AML development using our own established long-read SV characterization tool, NanoVar. The advent of Oxford Nanopore sequencing technologies has opened a new avenue for better SV characterization by having longer sequencing reads. NanoVar is an accurate and rapid SV characterization tool that utilizes low-depth Nanopore sequencing data. NanoVar makes use of split-reads and hard-clipped reads for SV discovery and employs a simulation-trained neural network classifier for true positive enrichment. NanoVar exhibited higher accuracy and faster computational speed amongst other long-read SV detection tools in simulated data. In AML patient data, NanoVar displayed excellent accuracy in SV characterization (16/16 SVs validated in two patients) by using only 4x depth sequencing data. In summary, NanoVar improves the accuracy and speed of SV characterization at a lower sequencing cost, an approach compatible with clinical studies.

  Study phs001847

• NHLBI TOPMed: Pharmacogenomics of Hydroxyurea in Sickle Cell Disease (PharmHU)

  Sickle cell disease (SCD) is characterized by the presence of sickle hemoglobin (HbS) within circulating erythrocytes resulting in hemolytic anemia, vascular occlusion, and end organ damage due to alterations in the shape and deformability of the cell membrane. The disease is inherited in an autosomal recessive pattern, and is most commonly caused by a single nucleotide substitution in the hemoglobin subunit beta (HBB) gene located on chromosome 11. Participants in this study include children with SCD treated with hydroxyurea to pharmacologically increase fetal hemoglobin (HbF) levels and reduce disease severity. Therefore, the primary phenotype of interest in this study is the change in HbF levels in response to hydroxyurea treatment. Genetic factors have been shown to influence inter-individual variation in drug response, and identification of novel genes and variants associated with clinical outcomes in SCD will be achieved through collaboration between Baylor College of Medicine, Augusta University, Columbia University Medical Center, Emory University School of Medicine and Children's Healthcare of Atlanta, and St. Jude Children's Research Hospital. The NHLBI TOPMed Program is designed to generate scientific resources to enhance understanding of fundamental biological processes that underlie heart, lung, blood and sleep disorders (HLBS). It is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment.

  Study phs001466

• Whole blood RNA-sequencing of covid-19 patients and healthy controls

  This dataset contains whole blood transcriptome data generated from 93 patients with COVID-19 across a range of severities and 23 healthy controls. All patients were PCR positive for SARS-CoV-2 and disease severity ranged from asymptomatic to severe disease requiring ventilation. Individuals without symptoms, or with mild symptoms, were recruited from routine screening of healthcare workers, while COVID-19 patients were recruited at or soon after admission to Addenbrooke’s or Royal Papworth hospitals. Blood samples were taken at recruitment and then again four weeks later. Further details of the cohort and the generation of the RNA-Sequencing data can be obtained from Bergamaschi, L. et al. Longitudinal analysis reveals that delayed bystander CD8+ T cell activation and early immune pathology distinguish severe COVID-19 from mild disease. Immunity 54, 1257-1275 e8 (2021).

  Dataset EGAD00001007776

• Center for Common Disease Genomics (CCDG) Neuropsychiatric: Multimodal Developmental Neurogenetics of Females

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants, both in coding and noncoding regions, will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases, pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002043

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Genomics of Autism Spectrum Disorder (GASD)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants, both in coding and noncoding regions, will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of New York Genome Center (NYGC). WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal.An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases, pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002509

• Center for Common Disease Genomics (CCDG) Neuropsychiatric: Homozygosity Mapping Consortium for Autism (HMCA)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants, both in coding and noncoding regions, will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases, pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs001894

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Simons Searchlight

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants, both in coding and noncoding regions, will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of New York Genome Center (NYGC). WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal.An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases, pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002512

• Center for Common Disease Genomics (CCDG) Neuropsychiatric: Autism Center of Excellence (ACE II)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants, both in coding and noncoding regions, will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases, pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002042

• Center for Common Disease Genomics (CCDG) Neuropsychiatric: Study of Autism Genetics Exploration (SAGE)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs001740

• Center for Common Disease Genomics (CCDG)-Neuropsychiatric: A Study of the Genetic Causes of Complex Pediatric Disorders (CAG)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002004

• Center for Common Disease Genomics (CCDG) Neuropsychiatric: Autism Genetic Resource Exchange

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs001766

• Center for Common Disease Genomics (CCDG) Neuropsychiatric: The Autism Simplex Collection (TASC)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs001741

• GCAT | Genomes for life

  The GCAT project is a prospective cohort study that was designed to recruit the general population of Catalonia, the north-east region of Spain. This study is a long-term genomic, environmental and lifestyle cohort project that aims to evaluate and track multiple pathologies as well as biologically related traits. By the end of 2017, the GCAT Study had recruited a total of 20 000 participants aged 40–65 years. Participants who agreed to take part in the study completed a self-administered computer-driven questionnaire, and underwent blood pressure, cardiac frequency and anthropometry measurements. For each participant, blood plasma, blood serum and white blood cells are collected at baseline. The GCAT Study has access to the electronic health records of the Catalan Public Healthcare System. Participants are followed biannually for/during, at least, 20 years after recruitment. Therefore, the GCAT Study offers a unique opportunity to integrate diverse data to allow the identification of novel relations among different biomarkers and conditions. Results may lead to the development of new genetic, genomic, epigenomic and proteomic diagnoses and screening tests, as well as new public health recommendations. The only currently available population-based prospective cohort study in Spain to the date, including more than 4899 genotyped participants and 800 whole genome sequences is now stored in the EGA archive under accession id EGAS00001003018.

  Blog gcat-genomes-for-life

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Autism - Simons Simplex Collection (SSC)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of New York Genome Center (NYGC). WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs001676

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: SPARK Simons Foundation Powering Autism Research for Knowledge

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants, both in coding and noncoding regions, will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of New York Genome Center (NYGC). WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal.An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases, pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002511

• Count Me In (CMI): The Angiosarcoma (ASC) Project (CMI-ASCproject)

  Count Me In - The Angiosarcoma Project: A Patient-Partnered Research Initiative to Accelerate Research in a Rare Sarcoma The Angiosarcoma Project (ASCproject) is a research study that directly engages angiosarcoma patients online and empowers them to accelerate cancer research by sharing medical information and clinical samples. Angiosarcoma is an exceedingly rare soft tissue sarcoma with an incidence of ~300 newly diagnosed cases per year in the United States. This low incidence has impeded large-scale research efforts in this disease that are strongly needed to catalyze research and improve clinical outcomes. The Angiosarcoma Project, launched in March 2017, has demonstrated the feasibility of directly engaging geographically dispersed patients to democratize research and establish a large patient cohort to characterize the genomic and clinical landscape of a rare disease. Angiosarcoma patients living in the US or Canada can access the study and consent online through an online portal (ASCproject.org). Enrolled patients are mailed saliva and blood draw kits, which can be used to extract germline DNA and cell-free DNA (cfDNA), respectively. The study team contacts participants' healthcare institutions to obtain medical records and a portion of archived tumor samples. All received tumor samples are subjected to centralized histological re-review by an expert pathologist to confirm a diagnosis of angiosarcoma. Whole exome sequencing is performed on tumor DNA, germline DNA, and cfDNA; transcriptome sequencing is performed on tumor RNA. De-identified data, including linked genomic, clinical, and patient-reported data, are shared via public databases on a recurring pre-publication basis. Participants are regularly provided updates on the study.

  Study phs001931