Search Results - EGA European Genome-Phenome Archive

Confirmation of a founder effect in a Northern European population (FRL) of a new beta-globin variant: HBB:c.23_26dup (codons 8/9 (+AGAA))

Beta-thalassemia is a genetic disease caused by a defect in the production of the beta-like globin chain. More than 200 known different variants can lead to the disease and are mainly found in populations that have been exposed to malaria parasites. We recently described a duplication of 4 nucleotides in the first exon of beta-globin gene in several families of patients living in Nord-Pas-de-Calais (France). Using the genotypes at 12 microsatellite markers surrounding the beta-globin gene of four unrelated variant carriers plus an additional one recently discovered, we found that they shared a common haplotype indicating a founder effect that was estimated to have taken place 225 years ago (9 generations). In order to determine whether this variant arose in this region of Northern-Europe or was introduced by migrants from regions of the world where thalassemia is endemic, we genotyped the first 4 unrelated variant carriers and 32 controls from Nord-Pas-de-Calais for 97 European ancestry informative markers (EAIMs). Using these EAIMs and comparing with population reference panels, we demonstrated that the variant carriers were very similar to the controls and were closer to North European populations than to South European or Middle-East populations. Rare beta-thalassemia variants have already been described in patients sampled in non-endemic regions but it is the first proof of a founder effect in Northern Europe. The new genetic panel FRL is under registration in EGA.

Study EGAS00001000980

Colorectal adenomas, carcinomas and adjacent normal NKI-AvL TGO series NGS-ProToCol

Cancer is caused by changes in the genome of cells, resulting in aberrant transcripts and proteins. In order to understand why normal cells become cancer cells and how we can identify and destroy them, the CTMM-NGS-ProToCol project aimed to understand prostate and colorectal cancer through DNA and RNA molecular profiling, to further improve diagnosis, prognosis and treatment.The state-of-the-art within the field of genome sequencing makes it possible to identify all the modifications in our genome that encode for RNA and of the transcripts themselves. The latest development in RNA sequencing is that if one does not select for polyA RNA, but first removes rRNA from the total RNA and then performs ‘random’ RNA sequencing, 30-60% of the reads are intronic. Since about 40% of the genome consists of genes (and only 1.6% is exonic), deep RNA sequencing will cover not only the exons, but also a large portion of the introns and therefore much of the genome. The power of the combined sequencing of genome and transcriptome is the full view of copy number aberrations (CNA), exon mutations and the consequence and relevance of the mutations at the RNA level in the form of differential gene expression, alternative splicing, alternative promoter usage, novel transcripts, fusion transcripts, read-through transcripts and mutations. For the colorectal (tumor) tissue dataset, we applied molecular profiling to 30 colorectal adenomas, 30 colorectal carcinomas and 18 normal adjacent colon tissues.

Study EGAS00001002854

Genomic characterization of 9p- syndrome

We characterized the precise genomic breakpoints of the complex structural variant associated with 9p- syndrome in one individual.

Study phs002054

International Verapamil SR/Trandolapril [INVEST] Genes Study

INternational VErapamil SR-Trandolapril STudy (INVEST) was a prospective, multicenter, randomized, open-label, parallel-clinical trial that evaluated blood pressure response and adverse outcomes in patients randomized to either an atenolol-based or a verapamil SR-based hypertension treatment strategy in 22,576 patients with documented coronary artery disease and hypertension (PMID: 9809930,14657064). Hydrochlorothiazide and trandolapril were added as needed to achieve BP control or end organ protection in a protocol-defined manner. Briefly, the protocol required patients to be followed up at bassline, 6, 12, 18 and 24 weeks and then every 6 months thereafter until 2 years after the last patient was enrolled. At each visit, patients had BP and heart rate measured, clinical assessment performed, and additional antihypertensive medications added as needed to meet JNC VI blood pressure goals. The primary outcome was the first occurrence of all-cause death, nonfatal myocardial infarction (MI), or nonfatal stroke (clinicaltrials.gov identifier: NCT00133692). The genetic substudy of INVEST, INVEST-GENES, collected genomic DNA samples from 5,979 INVEST study participants. INVEST-GENES samples were genotyped on the Illumina OmniExpressExome GWAS chip. This data release includes 1529 samples that passed quality control including 657 whites, 537 Hispanics and 155 blacks. Two case-control subsets were created: one for the primary outcome of all-cause death, nonfatal MI or nonfatal stroke; the other one is for new-onset diabetes. Resistant hypertension was also evaluated in 1349 participants based on the medication use and blood pressure measurements at the visit prior to experiencing study outcomes or censoring (PMID:30237584).

Study phs002319

EGA account management

How to manage your EGA account Welcome to the documentation page for creating an EGA user. The European Genome-Phenome Archive (EGA) is a platform for archiving, managing, and sharing human genomic and phenotypic data. To submit, access, and manage requests for the data hosted on the EGA platform, users are required to register for an account. This documentation page provides step-by-step instructions for creating an EGA user account, as well as information on the different types of EGA user accounts and their associated privileges. You can check the EGA data flow for a better understanding. Manage EGA account step-by-step guide Contact Information Public Keys Password Authenticator Federated Identity Sessions Request an EGA account step-by-step guide Fill in this form.You cannot use a generic email account (e.g., Gmail). Make sure you use your institutional email account.Your email is by default your username.The criteria for a strong password is: It should contain between 8 and 32 charactersIt should contain at least one uppercase letterIt should contain at least one numberIt should contain at least one special characterYou will need to wait for the Helpdesk team to check your identity. Please allow two business days for this step.After the Helpdesk validation step, you will receive an email with a link to validate your institutional email.Click the link to verify your email. It will redirect you to the EGA website.As soon as your account has been validated, you will be able to start adding more information to your EGA profile. For that, you first need to log in using your credentials from step 1. Manage EGA account step-by-step guide As a logged-in user, go to your profile by clicking on Welcome > My Profile. To modify it, click the Edit button.You will see the following options: Contact Information In this section, you can modify the personal information of your EGA account. Public Keys Adding a public key is necessary for downloading data via Live Outbox distribution. If you don’t know how to generate your key, you can follow the instructions available on How do I create a key? Password In the Password tab, you can change your password anytime to ensure the security of your account. However, if you receive an email notifying you that your password was modified and you did not initiate the change, it could be a sign that your account has been compromised. In this case, you should immediately contact our Helpdesk team to report the issue and receive assistance in restoring your account security. Authenticator You can set your two-factor authentication (2FA) system for your EGA account as an identity and access management security method that requires two forms of identification to access resources and data. To obtain your code, please follow the instructions below, also available in the Authenticator tab in your profile. Sessions The Sessions tab displays a list of all devices where you are currently logged in as an EGA user. This includes any open sessions you have on your computer, phone, or other devices. By reviewing the list of active sessions, you can monitor the devices that have access to your account and ensure that there are no unauthorised logins. If you notice any suspicious activity, you can close the sessions from this page to immediately terminate access to your account from the unauthorised device.

Documentation how-to-manage-your-account

Autosomal recessive

To define a genetic syndrome of combined immunodeficiency, severe autoimmunity, and developmental delay, 4 patients from two families who had similar syndromic features were studied. To identify disease-causing mutations, we performed whole exome sequencing for one patient and her healthy parent from Family 1 and also for one patient from Family 2. Disease segregated with novel autosomal recessive mutations in a single gene, tripeptidyl-peptidase II (TPP2) gene. The result defines a new human metabolic immunodeficiency.

Study phs000848

Exome sequencing of primary and relapse neuroblastoma

In this dataset, 16 trios- primary tumor, relapse and corresponding normals- for patients with neuroblastoma are provided. For one patient, more than one relapse was available for the analyses.

Dataset EGAD00001001607

Using genetics to identify cell types and mechanisms underlying susceptibility to primary sclerosing cholangitis

Primary sclerosing cholangitis (PSC) is a T-cell mediated, chronic inflammatory condition of the biliary tree that is strongly associated with inflammatory bowel disease. Genome-wide association studies have identified 22 non-HLA genetic risk variants associated PSC. Identifying the genes impacted by these variants has proven difficult as the majority lie in non-coding regions of the genome. Knowledge of the genes and biological pathways these non-coding variants are perturbing is vital to understanding the disease biology. One means of assessing the impact of non-coding variants within disease associated loci upon genes is via colocalisation with eQTL. Many eQTL are cell-type specific, requiring the analysis of disease relevant cell types to detect colocalisation. We have collected PSC-relevant T-cell-subtypes from the peripheral blood of PSC patients via fluorescence activated cell sorting in preparation for RNA sequencing and mapping of eQTL. Samples were collected at the Norfolk and Norwich University Hopital, for which local ethical approval has been granted. Lysed cell samples will be transferred to WTSI and DNA/RNA will be extracted from lysed cell samples by T143 before genotyping (DNA) and custom library preparation and sequencing (RNA). This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Dataset EGAD00001011815

Metagenomic Analysis of the Structure and Function of the Human Gut Microbiota in Crohn's Disease

Inflammatory bowel diseases (IBD), such as Crohn's disease, are chronic, immunologically mediated disorders that have severe medical consequences. The current hypothesis is that these diseases are due to an overly aggressive immune response to a subset of commensal enteric bacteria. Studies to date on IBD have suggested that the disorder may be caused by a combination of bacteria and host susceptibility; however the etiologies of these diseases remain an enigma. In this application, we propose to develop and demonstrate the ability to profile Crohn's disease at an unprecedented molecular level by elucidation of specific biomarkers (bacterial strains, genes, or proteins) that correlate to disease symptoms. To achieve this goal, we will employ a multidisciplinary approach based on metagenomic and metaproteomic molecular tools to elucidate the composition of the commensal microbiota in monozygotic twins that are either healthy or exhibit Crohn's disease (for concordant, both are diseased; for discordant, one is healthy and one is diseased). The central hypotheses of this proposal are (1) that specific members and/or functional activities of the gastrointestinal (GI) microbiota differ in patients with Crohn's disease as compared to healthy individuals, and (2) that it will be possible to elucidate microbial signatures which correlate with the occurrence and progression of this disease by integration of data obtained from 16S rRNA-based molecular fingerprinting, metagenomics, and metaproteomics approaches. To address these hypotheses, three specific aims are proposed: 1) Obtain data on community gene content (metagenome) in a subset of healthy twins and twins with Crohn's Disease to assess potential differences in the metabolic capabilities of the gut microbiota associated with CD, 2) Obtain data on community protein content (metaproteome) in a subset of healthy twins and twins with Crohn's Disease to assess the state of expressed proteins associated with CD, 3) Apply various statistical clustering and classification methods to correlate/associate microbial community composition, gene and protein content with patient metadata, including metabolite profiles and clinical phenotype. The ultimate goal of these efforts is to identify novel biomarkers for non-invasive diagnostics of CD and to eventually identify drug targets (i.e. bacterial strains) for cure or suppression of disease symptoms. PUBLIC HEALTH RELEVANCE: This study aims to unravel the contribution of the bacteria that normally inhabit the human gastrointestinal tract to Crohn's disease by using a multidisciplinary approach to study changes in the structure and function of gut microbial communities in three sets of patient cohorts who have Crohn's disease. These results will be compared with those obtained from the study of healthy individuals and have the potential to identify new biomarkers of disease severity, location, and progression.

Study phs000257

DCM-cases

DCM-cases (149 human DCM samples) human heart biopsies from 149 patients with dilated cardiomyopathy (DCM) were subjected to RNA sequencing in order to assess transcriptome variation. We used Illumina HiSeq2000 technology. Each sample-dataset contains the output from tophat-1.4.1 (one *.bam file with the aligned reads and two *.fq files one with the not aligned forward read and one with the revers unaligned reads). We reveal extensive differences of gene expression and splicing between dilated cardiomyopathy patients and controls.

Dataset EGAD00001003390

DCM-controls

DCM-controls (113 human non-DCM samples) human heart biopsies from 113 non-diseased controls were subjected to RNA sequencing in order to assess transcriptome variation. We used Illumina HiSeq2000 technology. Each sample-dataset contains the output from tophat-1.4.1 (one *.bam file with the aligned reads and two *.fq files one with the not aligned forward read and one with the revers unaligned reads). We reveal extensive differences of gene expression and splicing between dilated cardiomyopathy patients and controls.

Dataset EGAD00001003391

MP2PRT: Comprehensive Genomic Profiling to Identify Alterations Associated with Relapse for NCI Standard Risk (SR) B-Lineage ALL and NCI High Risk (HR) B-Lineage ALL with Favorable Genetic Features

The Molecular Profiling to Predict Response to Treatment (MP2PRT) program is part of the NCI's Cancer Moonshot Initiative. The aim of this program is the retrospective characterization and analysis of biospecimens collected from completed NCI-sponsored trials of the National Clinical Trials Network and the NCI Community Oncology Research Program. This study, titled "Comprehensive Genomic Profiling to Identify Alterations Associated with Relapse for NCI Standard Risk (SR) B-Lineage ALL and NCI High Risk (HR) B-Lineage ALL with Favorable Genetic Features," is one of the selected studies under this program. For this study, genomic characterization (WGS 30X, WXS, Total RNAseq) was performed on NCI Standard Risk B-lineage ALL patients who relapse and subsets of NCI High Risk B-lineage ALL patients who relapse as well as two non-relapse control cases for each relapse case. It was hypothesized that the comprehensive characterization of these sample sets will allow the identification of somatic genetic features that will facilitate early intervention to improve cure rates for those enrolled on future trials. Data were generated and genetic subtype was integrated with clinical variables, including age, presenting white blood cell count, sex, race, and levels of minimal residual disease at the end of induction. Additional secondary alterations were identified and included if they occurred in more than 10 patients. The study has been completed and a manuscript has been prepared.

Study phs002005

Molecular Characterization of Hemimegalencephaly

Somatic mutations, in which a fraction of the cells in the body have a deleterious mutation, are well recognized in cancer but only recently appreciated in neurological disease. Given a somatic mutation in a population of progenitor cells, all daughter cells inherit the mutation and are able to express the resultant phenotype as a function of the differentiation program. We recently identified the first de novo somatic mutations in the developing brain in the condition hemimegalencephaly (HME), a catastrophic focal epilepsy condition associated with a malformation of cerebral cortical development (MCD). HME is one of the most severe MCD syndromes, characterized by massive hamartomatous overgrowth of either of the two cerebral hemispheres. Cerebral hemispherectomy is a frequent treatment for refractory epilepsy, allowing the sampling of diseased tissue. By comparing DNA from a diseased brain with DNA from blood/saliva, we identified de novo somatic mutations in PIK3CA, AKT3 or MTOR, part of the mTOR pathway. Mutations were present in 8-40% of sequenced alleles in various brain regions sampled during surgery and in some codons known to activate proteins.• Population informationPatient samples were collected from multiple centers. The population is Caucasian and Hispanic• Molecular technologies employedWhole-exome sequencing• Principal findings of the studyWe were the first to describe mTOR-related and non-mTOR mutations causing hemimegalencephaly, and we described two-hit mutational models to explain the genetic pathogenesis of hemimegalencephaly

Study phs002156

Nanopore sequencing enables allelic phasing of FLG loss-of-function variants, intragenic copy number variation and methylation status in atopic dermatitis and ichthyosis vulgaris

Loss-of-function (LoF) variants in the FLG gene are associated with ichthyosis vulgaris (IV) and atopic dermatitis (AD). IV and AD patients with two FLG LoF variants are reported to have a more severe disease course. However, subsets of compound heterozygous patients display phenotypic heterogeneity despite a prediction of a severe phenotype from their genotype. The underlying genetic mechanism of this phenotypic variability is unknown. One possibility is that two LoF FLG variants could be located in cis (on the same allele), thus altering the predicted gene dosage. To investigate the allelic contribution of compound heterozygous FLG LoF mutations to IV phenotypic variability, we employ long reads from Oxford Nanopore Technologies, utilising two methodologies to phase the entire coding region of FLG into parental alleles: an amplicon-sequencing approach and an adaptive-sampling strategy. We investigated the allelic phasing of FLG LoF variants and intragenic-repeat copy-number variations (CNV) of 21 subjects with known compound heterozygous genotypes and mixed IV severity. Our results suggest that IV severity is not linked to the presence of cis variants in our IV patient cohort. Nanopore reads enabled detection and accurate phasing of CNVs and LoF variants into parental alleles, providing a framework for future in-depth genetic analysis. These results highlight the usefulness of utilising long reads for interrogating the FLG gene and other highly repetitive genes for genetic stratification related to clinical phenotypes.

Study EGAS50000000166

Whole genome study of Hurthle cell thyroid carcinoma

Oncocytic thyroid carcinoma, also known as Hürthle cell thyroid carcinoma, accounts for only a small percentage of all thyroid cancers. However, this malignancy often presents at an advanced stage and poses unique challenges to patients and clinicians. Surgical resection of the tumor accompanied in some cases by radioactive iodine treatment, radiation and chemotherapy are the established modes of therapy. Knowledge of the perturbed oncogenic pathways can provide better understanding of the mechanism of disease and thus opportunities for more effective clinical management. Initially, two oncocytic thyroid carcinomas and their matched normal tissues were profiled using whole genome sequencing. Subsequently, 72 oncocytic thyroid carcinomas, one cell line and 5 Hürthle cell adenomas were examined by targeted sequencing for the presence of mutations in multiple endocrine neoplasia I (MEN1) gene. We report the identification of MEN1 loss-of-function mutations in approximately 7% of patients diagnosed with oncocytic thyroid carcinoma. Whole genome sequence data also revealed large regions of copy number variation encompassing nearly the entire genomes of these tumours. Menin, a ubiquitously expressed nuclear protein, is a well-characterized tumor suppressor whose loss is the cause of multiple endocrine neoplasia type 1 syndrome. Menin is involved in several major cellular pathways such as regulation of transcription, control of cell cycle, apoptosis and DNA damage repair pathways. Mutations of this gene in a subset of Hürthle cell tumors point to a potential role for this protein and its associated pathways in thyroid tumorigenesis.

Study EGAS00001000940

Genome-wide association study identifies common variants associated with breast cancer in South African Black women

Genome-wide association studies (GWAS) have characterized the contribution of common variants to the development of breast cancer (BC) in populations of European descent, however no GWAS have been reported in resident African populations. This GWAS included 2,485 resident African BC cases and 1,101 population matched controls. Two risk loci were identified, one on chromosome 15, located between UNC13C and RAB27A (rs7181788, p = 1.01x10-08) and a second in an intron of USP22 on chromosome 17 (rs899342, p = 4.62x10-08). RAB27A is a member of the RAS oncogene family associated with invasive growth and metastasis, and UNC13C is involved in tumor progression. The rs899342 SNP is an eQTL for expression of USP22 in a wide range of tissues. Several genome-wide significant signals were detected in a hormone receptor subtype analysis. Comparison of a meta-analysis of other African ancestry BC GWAS datasets predominantly of West African ancestry with our South African data showed limited evidence of shared risk loci, suggesting potential heterogeneity in genetic risk factors for breast cancer in different African populations. A European ancestry derived polygenic risk model for BC was applied to our data, explaining only 0.79% of variance, with an area under the curve of 0.56. This study identified genetic risk factors for BC in a resident African population, but larger studies in this and other African populations are needed to further define the contribution of common variants to BC risk.

Study EGAS00001008032

National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS)

NIAGADS is an NIH controlled-access data repository that collaborates with researchers around the world to facilitate data access and sharing for genomic and associated omics data related to Alzheimer's Disease (AD), Alzheimer's Disease Related Dementias (ADRD), as well as healthy aging. Serving as the data coordinating center for the Alzheimer's Disease Sequencing Project (ADSP), NIAGADS hosts all ADSP-generated whole-exome, whole-genome and associated phenotypes. Other data types hosted by NIAGADS include genotype SNP arrays, functional omics, fluid biomarkers, aggregated imaging data (such as volumetric data for brain regions of interest), and summary statistics. In adherence with NIH security best practices and genome data sharing policies, NIAGADS supports data access requests through review by an NIH-appointed and registered Data Access Committee. Data stored within NIAGADS cannot be requested via dbGaP. Data requests must go through the NIAGADS Data Sharing Service (DSS) via the following NIAGADS url: https://dss.niagads.org/. Questions related to the request of data should be directed to the NIAGADS admin team at: niagads@pennmedicine.upenn.edu. DSS is a FISMA certified platform built by a team of data scientists at the University of Pennsylvania to support the request and access of AD/ADRD data by qualified researchers internationally. Questions related to the use of data hosted in the DSS should be directed to the Portal admin team at: help@niagads.org.

Study phs004180

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

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

Study phs002637

A Single-Cell and Spatial Atlas of Early Human Olfactory Development

The human nasal region is a complex structure derived from neural crest and placodal lineages, but its development remains poorly understood due to limited fetal tissue access and its intricate architecture. To address this, we created a single-nucleus and spatial transcriptomic atlas of the human fetal nasal region using tissue from 10 fetuses between 7 and 12 post-conceptional weeks. Single-nucleus RNA sequencing (snRNA-seq) revealed 34 distinct cell types, including epithelial, cartilaginous, immune, neuronal, glial, muscular, and vascular cells. By integrating snRNA-seq with multiplexed error-robust fluorescence in situ hybridization (MERFISH), we tracked dynamic changes in cell composition and gene expression over time in the olfactory epithelium (OE) and surrounding nasal regions. We identified novel markers of olfactory sensory neuron development and key pathways regulating epithelial patterning and OE morphogenesis. Notably, we observed early molecular signatures consistent with the "one neuron-one receptor" model, with spatially organized expression of 171 olfactory receptor genes. Together, this study presents the first integrated molecular and spatial framework of early human nasal development. It offers an unprecedented molecular blueprint of olfactory system formation and serves as a foundational resource for embryologists and developmental biologists studying sensory neurogenesis, epithelial patterning, and congenital disorders.

Dataset EGAD50000001712

Host Genetic Determinants of the Outcome of Staphylococcus Aureus Bacteremia by Whole Exome Sequencing

In this case-control study, Complicated Staphylococcus aureus (case) is defined as bacteremia plus endocarditis or bone/joint infection, and Uncomplicated Staphylococcus aureus (control) has no such complications and was cured at follow-up. We used whole exome sequencing to examine the cumulative effect of coding variants in each gene on risk of complicated SAB in a discovery sample of 168 SAB cases (84 Complicated SAB and 84 Uncomplicated SAB, frequency matched by age, sex and bacterial clonal complex). Then we evaluated the 334 most significantly associated genes and 8 biological candidate genes in a replication sample of 240 SAB cases (122 complicated and 118 uncomplicated, frequency matched by age, sex and bacterial clonal complex). All participants were white, non-Hispanic of European descent. In the discovery sample, gene-based analysis using SKAT-O identified 334 genes associated with complicated SAB at p<3.5 x 10-3;. Gene-based analysis of the 342 genes in the replication sample using SKATO identified one gene, GLS2 (GeneID: 27165), significantly associated with complicated SAB (p=1.2 x10-4;) after Bonferroni correction. GLS2 is an interesting candidate gene for complicated SAB due to its role in regulating glutamine metabolism, a key factor in white blood cell proliferation and activation.

Study phs001505

PIEZO1 Loss of Function Compound Heterozygous Mutation in the Rare Congenital Human Disorder Prune Belly Syndrome

Prune Belly Syndrome (PBS) is a rare congenital myopathy that is incompletely understood genetically. In this IRB approved study, one white Non-Hispanic 35 year-old male PBS proband was prospectively enrolled and phenotyped. Blood lymphocyte DNA from the proband underwent paired-end Whole Exome Sequencing using the Illumina SureSelect kit and HiSeq2500 sequencer with data pipeline analysis. We aligned the subject's sequence against the GRCh38/hg19 assembly and variant calling was performed using data training sets from the 1000 Genomes Project, Omni 2.5 M SNP microarray, and HapMap phase 3.3. These variants were filtered for rare minor allele frequency ( 0.9, CADD score > 20, GERP > 4, MutationTaster = “DC”, Mutation Assessor = “M” or “NE”, and Vest > 3.00. Rare and novel candidate functional variants were screened in the ClinVar database for prior association with smooth muscle myopathy (SMM). Only variants that met these criteria were included for further analysis. Confirmed variants had inheritance analysis performed on available samples. Our WES analysis identified novel compound heterozygous variants in the PIEZO1 gene. We conducted an extensive functional analysis of the PIEZO1 PBS variants that revealed loss-of-function characteristics. Thus, PIEZO1 mutations may be causal for PBS. Our WES data will be available through dbGaP.

Study phs003475

Center for Common Disease Genomics [CCDG] Neuropsychiatric: Autism Spectrum Disorder (ASD) – Whole Exomes

The National Human Genome Research Institute (NHGRI) has funded a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Called the Centers for Common Disease Genomics (CCDG), this initiative will explore a range of diseases with the ultimate goal of 1) undertaking variant discovery for enough different examples of disease architectures and study designs to better understand the general principles of the genomic architecture underlying common, complex inherited diseases, 2) understanding how best to design rare variant studies for common disease, and 3) developing resources, informatics tools, and innovative approaches and technologies for multiple disease research communities and the wider biomedical research community. The initial focus of the CCDGs will be in cardiovascular disease (early-onset coronary artery disease, atrial fibrillation, hemorrhagic stroke), neuropsychiatric disease (epilepsy, autism), and autoimmune/inflammatory disease (type 1 diabetes, inflammatory bowel disease). The Broad Institute is one of four selected CCDG project centers. The goal of the Autism Spectrum Disorder (ASD) program is to work together to utilize dramatic new advances in DNA sequencing technology to reveal the genetic architecture of autism through comprehensive examination of the exotic sequence of all genes.

Study phs002502

Comparison of EGF and PDGF driven glioblastomas.

Glioblastoma multiforme (GBM) is the most common and aggressive type of primary brain tumor. Epidermal growth-factor (EGF) and platelet-derived growth-factor (PDGF) receptors are frequently amplified and/or possess gain-of-function mutations in these tumors. Despite years of research into tyrosine-kinase inhibitors, clinical trials have shown disappointing efficacy. One of the underlying reasons is intra-tumor heterogeneity. To assess the effect of intra-tumor heterogeneity on gene expression, we derived a general approach to map single-cell expression profiles to sequentially-acquired mutations identified from exome sequencing. Using 288 single cells, we constructed high-resolution phylogenies of EGF-driven and PDGF-driven GBMs, modeling transcriptional kinetics during tumor evolution. A deletion in a PDGF-receptor domain involved in dimerization correlated to an up-regulation of the PI3K/AKT pathway in a proneural GBM, and ectopic expression of this mutant PDGFRA in vitro enhanced proliferation and invasiveness. Descending the phylogenetic tree of the PDGFR-driven tumor corresponded to a progressive induction of an oligodendrocyte progenitor-like cell type that expresses growth and angiogenic factors. In contrast, phylogenetic analysis of an EGFR-amplified tumor showed a gradual up-regulation of pro-invasive genes.

Study EGAS00001001900

Developmental_Dysplasia_of_the_Hip__DDH_

The National Joint Registry for England and Wales (NJR) has become established as one of the largest repositories of clinical information about patients undergoing hip and knee replacement. The primary aim of this proposal is to examine the feasibility of adding value to that clinical information by partnering it with a DNA dataset to allow its use to be extended to the study of the underlying pathogenesis of diseases of the hip and knee, and the complications of their treatment. We will do this 1) by establishing a mechanism for accessing and linking pseudo-anonymised demographic and phenotype data between the NJR database and the proposed DNA Biobank; 2) by validating the collection of postal DNA samples from consenting NJR patients; and 3) by genotyping genome-wide 900 patients with the condition developmental dysplasia of the hip (DDH) to find variants that play a role in this heritable condition. The successful demonstration that the NJR can be used to establish a DNA Biobank will provide a powerful platform to examine the genetic basis for a wide range of joint diseases, and the complications of their treatment. This proposal is to carry out the genotyping portion of this project on the current CoreExome array

Study EGAS00001000916

CancerLocator: Non-Invasive Cancer Diagnosis and Tissue-of-Origin Prediction Using Methylation Profiles of Cell-Free DNA

Background: The detection and characterization of cell-free DNA in plasma is one of the most promising new areas in cancer diagnosis. Liquid biopsy, unlike traditional tissue biopsy, has the potential to diagnose a variety of different malignancies. Results: Here we propose a probabilistic method, CancerLocator, which exploits the diagnostic potential of cell-free DNA by determining not only the presence but also the location of tumors. CancerLocator simultaneously infers the proportions and the tissue-of-origin of tumor-derived cell-free DNA in a blood sample using genome-wide DNA methylation data. We comprehensively evaluate CancerLocator with simulations and real data, and compare its performance with that of two established multi-class classification methods. We show that the predicted tumor burdens are highly consistent with the true values. In addition, when the proportion of tumor-derived DNAs in the cell-free DNAs is low, the two popular machine learning methods completely fail for cancer diagnosis, while CancerLocator successfully overcomes the challenge. CancerLocator also achieves promising results on patient plasma samples, despite the fact that the DNA methylation data from these samples has very low sequencing coverage. Conclusions: CfDNA methylation may be developed as an important approach for non-invasive early cancer diagnosis.

Study EGAS00001002211

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