Search Results - EGA European Genome-Phenome Archive

Cell line data (RNAseq, ATACseq, ChIPseq)

Content: 2 GB RTK I cell lines (LN229, ZH487) in two conditions (NT control and shSOX10). RNAseq: single replicates per condition, polyA+ RNA sequencing, SE. ATACseq: biological replicates per condition, SE. ChIPseq (histone H3 modifications, LN229 only): all marks for each condition were pooled and sequenced on two lanes for each pool. ChIPseq (BRD4 and SOX10): SOX10 libraries were sequenced on single lanes. BRD4 samples were multiplexed and sequenced in two lanes. ChIPseq input samples are also included. Data type and technology: RNAseq: SE 50bp sequenced on HiSeq2000/4000. ATACseq: SE 50bp sequenced on HiSeq2000/4000. ChIPseq: SE 50bp sequenced on HiSeq2000/4000.

Dataset EGAD00001005493

COVID-19 Multiomics Atlas

We provide a single-nuclei RNA-sequencing (snRNA-seq) dataset derived from four COVID-19 patients, generated using the 10x Chromium Next GEM Single Cell v3.1 kit. For our study, these were integrated with snRNA-seq data with 12 publicly available sc/snRNA-seq datasets, comprising organ donor lung samples (n=89) and COVID-19 lung tissue samples (n=51). Additionally, we provide a spatial transcriptomic dataset characterizing different histopathological stages of diffuse alveolar damage, across a cohort of 33 COVID-19 patients. This was generated using the Nanostring Whole Transcriptome Assay (WTA) with regions of interest (ROIs) sized 400 µm² each. This integrated multi-omics analysis of snRNA-seq, histology, and spatial transcriptomics data, is available for exploration and download via our web portal: https://covid19-multiomicatlas.cellgeni.sanger.ac.uk/.

Dataset EGAD00001015404

MutWP5: CRUK Mutographs of Cancer: Lung: PD38234 (Targeted) (2020-01-29)

Sequencing of LCM-derived microbiopsies from explanted lung from pulmonary fibrosis patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Targeted sequencing will be conducted on samples to identify drivers of interest and clonality of the samples, well-performing samples will be sent for subsequent whole-genome sequencing. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2020-01-29.

Dataset EGAD00001005925

Follicular lymphoma shallow whole genome sequencing and targeted sequencing of lymphoma panel

Stage I and stage III/IV Follicular lymphoma samples, shallow whole genome sequencing for copy number analysis and targeted capture sequencing for mutation and translocation analysis.

Dataset EGAD00001008385

ExomeSeq-EGAS00001001306

Exome Sequencing. 3 μg of genomic DNA from each sample were sheared and used for the construction of a paired-end sequencing library as described in the paired-end sequencing sample preparation protocol provided by Illumina41. Enrichment of exonic sequences was then performed for each library using either the Sure Select Human All Exon 50 Mb or All Exon+UTRs v4 kits following the manufacturer’s instructions (Agilent Technologies). Exon-enriched DNA was pulled down by magnetic beads coated with streptavidin (Invitrogen), followed by washing, elution and 18 additional cycles of amplification of the captured library. Enriched libraries were sequenced (2 × 76 bp) in one lane of an Illumina GAIIx sequencer or in two lanes of a HiSeq2000 when using pools of eight samples.

Dataset EGAD00001001464

Whole exome sequencing data of tumor/normal pairs for the study "TGF-β attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells"

Tumor DNA was extracted from formalin-fixed and paraffin embedded tumors of a large cohort of bladder cancer patients before treatment with anti-PD-L1. Normal DNA was extracted from matched PBMCs. Whole exome sequencing was performed. This is a subset of patients for which RNA sequencing is also provided (with more detailed phenotypic information).

Dataset EGAD00001004218

Pilot experiment on functional genomics in osteoarthritis_RNA

The aim of this work is to apply an integrated systems approach to understand the biological underpinnings of large joint (hip and knee) osteoarthritis which culminates in the need for total joint replacement (TJR). In this pilot we will assess the feasibility of the approach in the relevant tissue. We will obtain diseased and non-diseased tissue (cartilage and endochondral bone) following TJR, coupled with a blood sample, from 12 patients. We will characterise the 12 pairs of diseased and non-diseased tissue samples in terms of transcription (RNASeq) The pilot will help assess the feasibility of isolating sufficient levels of starting material for the different approaches, and will instigate the development of analytical approaches to synthesising the resulting data.

Dataset EGAD00001001331

Axes of Biological Variation in Diffuse Large B-Cell Lymphoma

To explore the DLBCL molecular and genetic environment, we conducted genome-wide NGS sequencing on 103 DLBCL biopsy samples (named as Cornell-NCI cohort) with NGS platforms, including bulk WES, etc. The raw fastq files of the bulk WES were deposited on the EGA for user access. To obtain other genomic data from the study, please see the data links described in the paper.

Study EGAS50000001227

Genomewide Association Study of Alcohol Use and Alcohol Use Disorder in Australian Twin-Families (OZ-ALC GWAS)

The Australian twin-family study of alcohol use disorder (OZALC study) derives from telephone diagnostic interview studies of two general population volunteer cohorts of Australian twins (cohort 1, mostly born 1940-1964; cohort 2, born 1964-71) and the spouses of the former cohort - a total of over 11,000 families. Three coordinated studies, using a shared assessment protocol and with a shared goal of gene-discovery, were conducted - one funded by the National Institute on Drug Abuse, the others by the National Institute on Alcoholism and Alcohol Abuse - by investigators associated with the Midwest Alcoholism Research Center at Washington University in St. Louis, and investigators at Queensland Institute of Medical Research, Brisbane, Australia (led by Professor Nicholas Martin), using informative families identified from these cohorts. The first of these (NIDA Nicotine Addiction Genetics [NAG] project, PI Pamela Madden) identified index cases from the 3 cohorts with a history of heavy smoking (smoked 20 or more cigarettes daily, or 40 or more cigarettes on 1 or more occasions) and with additional available full siblings who were smokers, and interviewed and obtained blood samples from twins, and cooperative full siblings and parents, in order to identify families that would be informative for linkage analysis of a quantitative heaviness of smoking trait. The second identified additional families with an index case who either reported a history of alcohol dependence (DSM-IV), or scored above the 85th percentile on a quantitative measure of heaviness of alcohol use (alcohol factor score), derived from measures of frequency of heavy drinking, frequency of drinking to intoxication, and typical weekly consumption in standard drinks (all referenced to the respondent's heaviest drinking period) and of lifetime maximum 1-day alcohol consumption and maximum tolerance to alcohol (drinks before getting drunk or before feeling effects of alcohol). Interview and DNA were obtained from index cases and siblings, and DNA only from available parents. The goal of this second study (NIAAA OZ-ALCOHOL EDAC study, PI Andrew Heath) was to identify sibships including pairs who were either extreme concordant for the quantitative consumption measure (both scoring above the 85th percentile) or extreme discordant (one scoring above the 85th percentile and one scoring below the 30th percentile) that would be informative for linkage analysis. The third identified additional sibships solely on the basis of large sibship size, regardless of alcohol or tobacco use phenotypes (NIAAA OZ-BIGSIB study, PIs the late Richard Todd, Andrew Heath). From these coordinated studies a case-control series of alcohol dependent individuals and unaffected controls were constructed for a family-based Genomewide Association Study (OZALC-GWAS) of heaviness of alcohol use and alcohol dependence, funded by the National Institute of Alcoholism and Alcohol Abuse. These data are made available here for all investigators studying outcomes related to alcohol or tobacco use (including major depressive disorder).

Study phs000181

Maintenance of Brain Tumor Profile on Organotypic Brain Slice Culture (OBSC)

We used uncultured tumor resection tissue from an NF2 mutation-driven grade II meningioma (MG-II) to investigate whether tumors engrafted onto organotypic brain slice cultures (OBSCs) maintained the genetic profile of the parent tumor. We prepared three groups of samples for whole exome sequencing (WES) from the same pool of dissociated MG-II tissue. Group HT is the original uncultured human tumor tissue (n = 3). Group CL is the parent tumor tissue expanded in standard in vitro cell culture until the minimum number of cells required for WES had grown. Because of initial cell loss and subsequent clonal expansion, this required six passages over the span of approximately one month (n = 3). Group BSHT is the uncultured tumor resection tissue engrafted onto OBSCs and subsequently dissected from the OBSCs at the conclusion of our standardized assay length (4 days; n = 4). WES analysis showed that tumor tissue engrafted onto OBSCs maintained a significant genetic resemblance to the parent tumor, while tumor tissue expanded in vitro displayed a distinctly different profile. Furthermore, the mutational profiles of all four BSHT biological replicates were markedly similar, indicating that each OBSC-engrafted tumor indeed contained a representative sample of the original patient tumor. A closer look at the hallmark NF2 mutations existing within all samples revealed that while all samples from the original tumor (HT1-3) and the OBSC-engrafted tumor (BSHT1-4) maintain the frame shift deletion at V24, this mutation was lost in all samples expanded in vitro (CL1-3) and replaced by mutations in other areas. Together, this data suggests that the rapid assay design and tumor-accommodating niche of our OBSC platform enables effective maintenance of the original patient tumor profile. The BBsplit algorithm from the BBtools suite was run on all samples to eliminate rat DNA contamination in the BSHT samples as well as to account for any biases that may result as a part of that process. Only the reads that were binned to the human reference were used for subsequent analysis. Reads were then mapped to the GRCh38 version of the human genome with BWA v0.7.17 and realigned together with ABRA2 v.23. Quality control was implemented using the GATK/Picard v4.1.7.0 toolkit. Somatic variants were called for each sample using the MuTect2 algorithm v4.1.7.0. Variants were merged into a single cohort variant call file and then converted to MAF via vcf2maf v1.6.21 tool. Variants were annotated using VEP v87. To identify mutations with potentially high biological impact, multiple filtering steps were applied to somatic mutation calling. First, we selected only the somatic variants that passed all filters from the MuTect2 FilterMutectCalls algorithm and second, only high/moderate impact (change coding) variants as defined by the VEP annotation were further analyzed. Over 1900 single nucleotide variants (SNVs) were detected across all samples. Figures that summarized the results were generated using maftools.

Study phs003268

Resuscitation Outcomes Consortium Pragmatic Trial of Airway Management in out-of-Hospital Cardiac Arrest (ROC PART-BioLINCC)

Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: To determine the effect of an initial airway management strategy using laryngeal tube (LT) insertion, compared with endotracheal intubation (ETI), on survival among adults with out-of-hospital cardiac arrest (OHCA).Background: Out-of-hospital cardiopulmonary arrest (OHCA) affects more than 350,000 adults in the United States each year, with only a low percentage of patients surviving to hospital discharge. Emergency medical services (EMS) paramedics commonly perform ETI or insertion of supraglottic airways (SGAs), such as the LT, on patients with OHCA to facilitate oxygenation and protect the lungs from aspiration of vomitus. Because SGA insertion is rapid, simple, and requires less training compared to ETI, many EMS agencies have incorporated this as the primary method of ventilation during OHCA resuscitation. However, the optimal method for OHCA advanced airway management is unknown.Participants: A total of 3004 patients were included; 1505 assigned to initial LT and 1499 assigned to initial ETI.Design: PART was a multicenter cluster-crossover randomized trial. The trial included 27 EMS agencies associated with US sites of the Resuscitation Outcomes Consortium (ROC). The EMS agencies were grouped into 13 randomization clusters. Each cluster selected a crossover interval of 3 or 5 months. Within each cluster, treatment assignments for consecutive intervals were computer-randomized in blocks of 2 to ensure balanced exposure to both airway groups. Crossovers between study groups could occur more than once. Treatment assignments were initial LT insertion or initial ETI. Neuromuscular blocking agents or video laryngoscopy was permitted for initial intubation efforts. The trial did not limit the number of initial LT insertion or ETI attempts. If the initial insertion efforts were unsuccessful, EMS personnel performed rescue airway management using any available airway technique. EMS personnel followed local protocols for confirmation of airway placement and management of OHCA, including field termination of resuscitation efforts. Patients receiving bag-valve mask (BVM) ventilation only were retained in their assigned treatment group per intention-to-treat principles. The trial did not prescribe clinical care at the receiving hospitals, including use of EMS airway, targeted temperature management, percutaneous coronary intervention, or the timing of withdrawal of life-sustaining therapy.The primary outcome was 72-hour survival. Secondary outcomes included return of spontaneous circulation, survival to hospital discharge, and favorable neurological status at hospital discharge (Modified Rankin Scale score ≤3). Conclusions: Among adults with OHCA, a strategy of initial LT insertion was associated with significantly greater 72-hour survival compared with a strategy of initial ETI. These findings suggest that LT insertion may be considered as an initial airway management strategy in patients with OHCA, but limitations of the pragmatic design, practice setting, and ETI performance characteristics suggest that further research is warranted.

Study phs003902

Immunophenotyping in a COVID-19 Cohort (IMPACC) Transcriptomics and Genotyping Assays

IMPACC (IMmunoPhenotyping Assessment in a COVID-19 Cohort) is a prospective longitudinal cohort study (NCT04378777) launched in May 2020 in response to the worldwide pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was funded by the National Institute of Allergy and Infectious Diseases (NIAID) of the National Institute of Health (NIH). Patient enrollment and sample analysis involved 20 hospitals associated with 15 U.S. biomedical research centers and 11 centralized Core immunoassay laboratories.The study aimed to enable the identification of potential biomarkers and inform future therapeutic interventions using a longitudinal approach encompassing the whole disease course for a comprehensive understanding of the contributions of the pathogen and host immune response in modulating the manifestations, severity, and post-acute sequelae of the infection. IMPACC enrolled close to 1200 adult symptomatic, molecularly confirmed hospitalized COVID-19 patients in the study within 48 hours of their hospital admission. Clinical data and biological samples (blood, mid-turbinate nasal swabs, and esophageal aspirant) were collected according to minimal risk guidelines at enrollment and on days 4, 7, 14, 21, and 28. Biological samples were collected at 3-month intervals up to 12 months after hospital discharge to assess functional and immunologic recovery measures. Sample collection, processing, and storage procedures were standardized across sites, and samples were transported to centralized assay-specific core laboratories (Core Labs) in batches for testing and analysis. The description of outcome severity was not limited to survival versus death but encompassed a clinical trajectory approach using 5 groups leveraging longitudinal data based on time in the hospital, disease severity by ordinal scale based on the degree of respiratory illness, and presence or absence of limitations at discharge. Disease severity was assessed based on the degree of respiratory illness using a 7-point ordinal scale adapted from the World Health Organization COVID-19 and NIAID disease ordinal severity scales. DNA for genetic analyses was collected from whole blood at a single time point. To identify any genomic determinants of severe COVID-19 disease, single-nucleotide polymorphism (SNP) genotyping and exome sequencing were conducted to assess genetic variants associated with individual susceptibility to severe disease. In addition, IMPACC included bulk transcriptomic analysis of upper airway (nasal swaps) samples, lower airway (esophageal aspirant) samples, and peripheral blood mononuclear cells (PBMCs) to evaluate dynamic changes in cellular composition and cellular response during the course of the disease. Reads were aligned to the GRCh38 human reference genome. Additional information for the IMPACC study has been submitted to The Immunology Database and Analysis Portal (ImmPort) under study accession SDY1760. Further information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Dr. Steven Kleinstein (steven.kleinstein@yale.edu).

Study phs002686

Submitter Portal API

Submitter Portal API The metadata submission process can be difficult and time-consuming. For this reason, the EGA has developed the Submitter Portal, a tool that was created to offer a simplified and user-friendly method of registering metadata. Our portal provides features that are intended to make the input of metadata easier, ensuring that your data is registered correctly and effectively. Our page is divided into logical sections and includes a helpful video instruction to further assist you as you complete the submission process. With the Submitter Portal, you can rest assured that the submission of your data is in good hands. For those that want a more flexible and automated approach, we also provide a programmatic approach using the Submitter Portal AP in addition to the user interface of the Submitter Portal. With the help of our API, you can quickly include the submission of metadata into your own workflow for a more effective and individualised experience. Previous steps Create your EGA account To submit data you first need to create your EGA user. Then, once your account has been verified, you will have to request a submitter role and sign the EGA Data Processing Agreement (DPA). When the DPA is signed, you must send it to EGA Helpdesk for further validation. Please, note that if you already have an EGA account, or you have an ega-box (submission account), you can skip this step. Upload your files Please note that all your files must be encrypted using the Crypt4GH tool before upload them.As soon as you are assigned with a submitter role, you will be able to connect to the EGA inbox and upload your files. Understand the EGA metadata schema It's crucial to comprehend the EGA metadata schema, a set of rules that specify how data is organised, described, and shared inside the EGA, in order to get the most out of this resource. Learn all about EGA metadata schema! Register your DAC and policy There are two objects in the EGA metadata schema that are registered in a separate portal. All DACs and policy objects are registered using the DAC Portal, a tool developed by EGA to help data controllers manage their data stored at the EGA. You can find the relevant information in the DAC Portal Guide. Programmatic submission All the calls to the API need to be Authenticated. We use the OpenID Connect protocol. API Usage Flow: Click here to check the API usage flow schema Obtain Access and Refresh Token: The first step to using the API is to obtain an access and refresh token. These tokens are required for authentication and authorisation of API requests. To obtain these tokens, you need to log in using your EGA credentials. Example: curl "https://idp.ega-archive.org/realms/EGA/protocol/openid-connect/token" \ -d "grant_type=password" \ -d "client_id=sp-api" \ -d "username=your-username" \ --data-urlencode "password=your-password" Use Access Token in API Calls: Once you have obtained the access token, you must use it in all the calls to the API. The access token is valid for a limited time period. When it expires, you will need to use the refresh token to obtain a new access token. Create Submission Object: After authentication, you can start creating a submission object. This object will be used to store all the metadata objects and files related to the submission. Example: curl "https://submission.ega-archive.org/api/submissions" \ -H "Authorization: Bearer your-access-token" \ -H "Content-Type: application/json" \ -d "{ \"title\":\"My submission title\", \"description\":\"My submission description\" }" Create EGA Metadata Objects: Within the submission object, you can create other metadata objects required for the submission. These objects may include information about the submitter, study, sample, experiment, and run. Example of study creation: curl "https://submission.ega-archive.org/api/submissions/{submisison-id}/studies" \ -H "Authorization: Bearer your-access-token" \ -H "Content-Type: application/json" \ -d "{ \"title\":\"My study title\", \"description\":\"My study description\", \"study_type\":\"Metagenomics\" }" If you would like to reuse already registered objects in new submissions, bear in mind that they must have an accession which you must use to reference them. You cannot reuse objects that have not been finalised and accepted yet.For example, when creating a new run which is reusing a previously submitted experiment, instead of using experiment_provisional_id, you must use experiment_accession_id. Enums There are some fields that only accept specific values, i.e. study_type. The API provides several enumerations to list these values. You can list all the enumerations, or a specific one, for example, study_types. Obtain IDs of files You can list the files available in your inbox and filter by a prefix by adding the prefix param, i.e. &prefix=/my_folder/abc Example: curl "https://submission.ega-archive.org/api/files?status=inbox&prefix=/my_folder/abc" \ -H "Authorization: Bearer your-access-token" \ -H "Content-Type: application/json" To improve performance and manageability, we have limited the number of files that the Submitter Portal API can return in a response. If a given call exceeds this limit, user will be asked to narrow down the search by using the query parameters already available in this endpoint. Finalise Submission: Once all the metadata objects are created and linked to the submission, you can finalise the submission. Finalising the submission sends it to the Helpdesk team for review. Please, note that all files linked to the submission must be ingested, and all objects created in a submission must be linked before you can finalise the submission. API Reference: For a full API reference, please check our specification documentation.

Documentation submission/metadata/submission/sequencing-phenotype/submitter-portal-api

Providing access to COVID-19 data: one year later

response efforts On 11 March 2020 the World Health Organization declared the novel coronavirus outbreak a global pandemic. Four months later, the European Genome-phenome Archive (EGA) released its first COVID-19 dataset. This dataset – single cell RNA and VDJ sequencing of B cells from 60 COVID-19 patients – showed that neutralizing antibodies could be identified by high-throughput sequencing in response to SARS-CoV-2 infection. That was one year ago. Today, the EGA provides access to fifteen COVID-19 datasets from researchers across seven countries in Asia, Europe, and North America. These studies represent almost 17,000 individuals and have resulted in at least sixteen publications and preprints. Researchers deposit controlled access COVID-19 data at EGA The global research community has come together rapidly to investigate the SARS-CoV-2 coronavirus and better understand the related disease, COVID-19. These research efforts generate valuable genetic and phenotypic data from patients and research participants that can be shared with approved researchers. The EGA enables sharing of this research data by providing a service for archiving and controlled distribution of sensitive data. Over the past year, the EGA has worked with researchers to archive and distribute COVID-19 data from high-throughput sequencing experiments, genotyping studies, and phenotypic information. These datasets investigate the immune system, blood, and cells and tissues of the lung, which are relevant for studying a contagious respiratory illness caused by a viral infection. *Study Spotlight. In January 2021, Ancestry.com demonstrated the utility of deep phenotyping based on self-reported outcomes from a large population of mild and asymptomatic COVID-19 cases. They identified genetic associations with eight COVID-19 phenotypes and showed distinct patterns of association, most notably related to the chr3/SLC6A20/LZTFL1 and chr9/ABO regions. The supporting data is available at the EGA to approved researchers and includes both genotype and phenotype data for 15,000 individuals. EGA collaborates with global COVID-19 community Since the coronavirus outbreak, the EGA has collaborated with other life science resources to support discovery and access to COVID-19 datasets. COVID-19 Host Genetics Initiative. With the NHGRI’s Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) platform, the EGA enables sharing of individual-level genetic and phenotypic data from the COVID-19 Host Genetics Initiative (HGI). This initiative aims to generate, share, and analyze data from COVID-19 host genetics research projects to better understand the genetic determinants of COVID-19 susceptibility, severity, and outcomes. In response to COVID-19, the EGA actively supports COVID-19 data submissions and integration of data access and flow into the COVID-19-HGI analysis platform. *Study Spotlight. The COVID-19 HGI has combined individual-level data for 13,868 COVID-19 positive patients (N=7,167 hospitalized) from 17 cohorts in nine countries. The data were used to assess the association of the major common COVID-19 genetic risk factor (chromosome 3 locus tagged by rs10490770) with mortality, COVID-19-related complications, and laboratory values. The genotype and phenotype data for 10 of these cohorts is available at the EGA to approved researchers under accession EGAS00001005304. Fig 1: EGA COVID-19 studies are searchable in the European COVID-19 Data Portal alongside other COVID-19 and SARS-CoV-2 public datasets. European COVID-19 Data Portal. EGA-archived COVID-19 data are discoverable via the European COVID-19 Data Portal (Fig. 1), which brings together public and controlled access data to accelerate coronavirus research for the international community. By indexing all COVID-19-related data in one place, researchers can more easily discover relevant datasets of interest, thus increasing the “FAIRness” (Findability, Accessibility, Interoperability, Reusability) of this valuable data. Fig 2: SARS-CoV-2 viral sequences are imported from ENA and analysed in Galaxy to detect variants. Results are accessible to researchers through the COVID-19 Viral Beacon. COVID-19 Viral Beacon. The COVID-19 Viral Beacon tool was developed in collaboration with the European Nucleotide Archive and Galaxy to enable near real-time browsing of SARS-CoV-2 variability at genomic, amino acid, and motif levels (Fig. 2). The COVID-19 Viral Beacon allows researchers to (i) perform detailed searches about genomic variants, (ii) filter queries and find unique cases, (iii) filter data based on strain-specific variants, and (iv) explore associated metadata. It uses the Global Alliance for Genomics and Health (GA4GH) Beacon standard including new Beacon v2 features. With this tool, researchers can study intra-host mutations on genomic regions of interest, or trace any variant frequency over time using raw read data. More than 200,000 SARS-CoV-2 analysed genomic data files are now available to researchers for further exploration. Ongoing COVID-19 efforts at EGA Addressing the COVID-19 pandemic is a global effort. Federated resources are necessary to support transnational deposition, access, and analysis of sensitive COVID-19 host genetics and other related data. At the same time, many countries now have emerging personalized medicine programmes which are generating data from national or regional healthcare initiatives. These data are subject to more stringent information governance than research data and often must comply with national data protection legislation. To address this need, the Federated EGA was established to serve as the primary global resource for discovery and access of sensitive human omics and associated data consented for secondary use. The Federated EGA will comprise a network of national human data repositories and will implement community standards and common interfaces. Launching Federated EGA promises to accelerate not only global research efforts to understand, diagnose, and treat COVID-19, but also to foster data reuse, enable reproducibility, and accelerate biomedical and disease research to ultimately improve human health.

Blog providing-access-to-covid-19

The Haemgen RBC study

Anaemia is a major determinant of global ill-health. To refine our understanding of the genetic factors influencing red blood cell formation and function, we carried out a meta-analysis of genome-wide association studies (GWAS) for six red blood cell traits: haemoglobin (HB), mean cell haemoglobin (MCH), mean cell haemoglobin concentration (MCHC), mean cell volume (MCV), packed cell volume (PCV) and red blood cell count (RBC). We provide genome-wide association results for 62,553 people of European ancestry using up to 2,644,161 autosomal SNPs. Participants with extreme measurements (>+/-3SD from mean) were excluded on a per phenotype basis. Imputation was done using haplotypes from HapMap Phase 2. SNP associations with each phenotype were tested by linear regression using an additive genetic model. Associations were tested separately in each cohort, with principal components and other study specific factors as covariates to account of population substructure. We then carried out meta-analysis of results from the individual cohorts using z-scores weighted by square root of sample size. SNPs with MAF<1% (weighted average across cohorts) were removed, as were SNPs with weight <50% of phenotype sample size. Anaemia is a major determinant of global ill-health. To refine our understanding of the genetic factors influencing red blood cell formation and function, we carried out a meta-analysis of genome-wide association studies (GWAS) for six red blood cell traits: haemoglobin (HB), mean cell haemoglobin (MCH), mean cell haemoglobin concentration (MCHC), mean cell volume (MCV), packed cell volume (PCV) and red blood cell count (RBC). We provide genome-wide association results for 62,553 people of European ancestry using up to 2,644,161 autosomal SNPs. Participants with extreme measurements (>+/-3SD from mean) were excluded on a per phenotype basis. Imputation was done using haplotypes from HapMap Phase 2. SNP associations with each phenotype were tested by linear regression using an additive genetic model. Associations were tested separately in each cohort, with principal components and other study specific factors as covariates to account of population substructure. We then carried out meta-analysis of results from the individual cohorts using z-scores weighted by square root of sample size. SNPs with MAF<1% (weighted average across cohorts) were removed, as were SNPs with weight <50% of phenotype sample size.

Study EGAS00000000132

National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (ARIC)

The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study, the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis. Together, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African-American, Caucasian, Asian, and Hispanic ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000398 contains the Atherosclerosis Risk in Communities (ARIC) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

Study phs000398

Foregut Microbiome in Development of Esophageal Adenocarcinoma

The distal esophagus is an important anatomical area where gastric acid reflux can cause reflux esophagitis (RE), Barrett's esophagus (BE) (intestinal metaplasia), and esophageal adenocarcinoma (EA). The incidence of EA has increased 6-fold in the U.S. since the 1970s, parallel to a significant increase in the prevalence of gastroesophageal reflux diseases (GERD). Although specific host factors might predispose one to disease risk, such a rapid increase in incidence must be predominantly environmental. The cause remains unknown. Our hypothesis is that changes in the foregut microbiome are associated with EA and its precursors, RE and BE in the GERD sequence. We will conduct a case control study to characterize the microbiome in every stage of the GERD sequence as well as analyze the trend in changes in the microbiome along disease progression toward EA. Specific Aim 1. To conduct a comprehensive population survey of the foregut microbiome and demonstrate its association with GERD sequence, by a 16S rRNA gene survey. We will analyze samples of the foregut microbiome at three anatomic loci: mouth, distal esophagus, and gastric corpus. Changes of the microbiota in the distal esophagus will be correlated with the phenotypes. Spatial relationship between the esophageal microbiota and upstream (mouth) and downstream (stomach) foregut microbiotas as well as temporal stability of the microbiome-disease association will also be examined. Specific Aim 2. To define distal esophageal metagenome and demonstrate its association with GERD sequence, by shotgun metagenomic analysis. We will first classify samples of the metagenome into metagenotypes by between-sample k-mer distance and correlate the metagenotypes with the four phenotypes. Subsequent detailed analyses will include pathway-disease and gene-disease associations. DNA viruses and fungi, if identified, also will be correlated with the phenotypes. A significant association between the foregut microbiome composition and GERD sequence, if demonstrated, will be the first step for eventually testing the causal hypothesis that an abnormal microbiome is required for the development of the sequence of phenotypic changes toward EA. If EA and its precursors represent a microbial ecological disease, treating the cause of GERD might become possible, for example, by normalizing the microbiome through use of antibiotics, probiotics, or prebiotics. Causative therapy for GERD could prevent its progression and reverse the current trend of increasing incidence of EA.

Study phs000260

(Epi)genetic Risk Architectures of Opioid-Dependent Brain

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

Study phs002724

Genomic Characterization of Head and Neck Squamous Cell Carcinoma Cell Lines

Head and neck squamous cell carcinoma (HNSCC) is the sixth leading cancer by incidence worldwide(1). Various chemical carcinogens (tobacco, alcohol and betel nut), human papillomavirus (HPV) infection, and genetic predisposition contribute to the etiology of HNSCC, and to the complex genetic alterations in tumor subsets that differ in prognosis and response to therapies (2). Recently, a comprehensive landscape of genomic and transcriptomic alterations in HNSCC tumors has emerged from The Cancer Genome Atlas (TCGA) Network (3). TCGA revealed novel and previously recognized gene and chromosomal region copy number alterations (CNAs), mutations, and expression clusters, and defined their frequency, co-occurrence, and relationship to common and rare subtypes of HPV(-) and (+) tumors that vary in prognosis. To identify cell line models for determining the functional role and therapeutic importance of these alterations, we are performing whole exome and RNA sequencing and bioinformatic analysis of an expanded panel of 15 HPV(-) and 11 HPV(+) HNSCC cell lines and primary oral keratinocytes. We find that the recurrent genomic alterations in cell lines are remarkably consistent with those found in more aggressive tumors, from which cell lines have traditionally been most readily adapted to culture (4). Genome-wide correlation of CN (copy number) with expression identified a suite of potential drivers or modifier genes that differ by HPV status, and are of potential biologic and therapeutic relevance. Further, our findings elucidate and validate genomic alterations underpinning numerous discoveries made with these widely-used and recently derived HNSCC lines, and provide a roadmap for their potential use as models for future studies of tumor subtypes with worse prognosis. References Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin. 2015;65(2):87-108. Van Waes C, Musbahi O. Genomics and advances towards precision medicine for head and neck squamous cell carcinoma. Laryngoscope Investig Otolaryngol. 2017;2(5):310-9. Cancer Genome Atlas N. Comprehensive genomic characterization of head and neck squamous cell carcinomas. Nature. 2015;517(7536):576-82. White JS, Weissfeld JL, Ragin CC, Rossie KM, Martin CL, Shuster M, et al. The influence of clinical and demographic risk factors on the establishment of head and neck squamous cell carcinoma cell lines. Oral Oncol. 2007;43(7):701-12.

Study phs001581

Genetic Modifiers of Huntington's Disease

Huntington's disease (HD) is a neurodegenerative disorder typically diagnosed in mid-life that is caused by expansion of an otherwise polymorphic CAG trinucleotide repeat. The mutation causes a gain-of-function of the huntingtin protein to trigger a pathogenic process that produces detectable phenotypic differences many years before the traditional diagnosis, which is based upon characteristic motor symptoms. The prediagnosis phase of pathogenesis is now the subject of intense scrutiny by an NINDS-funded longitudinal study, PREDICT-HD, in which undiagnosed gene carriers are followed longitudinally and subjected to detailed phenotyping (PREDICT-HD Huntington Disease Study -- dbGaP Study Accession: phs000222). This powerful approach, which offers the potential for moving the focus of therapeutic development to the decades prior to neurological disease diagnosis, is enabled by the fact that all individuals with HD have the same type of mutation, which can be determined at any time in life by a single HD CAG repeat PCR amplification assay. The precise length of the HD CAG repeat differs between individuals. There is a strong negative correlation between the number of CAG repeats and the age at onset of diagnostic neurological abnormalities in HD, such that the CAG repeat accounts for ~50% of the variation in age at diagnosis. Analysis of the remaining variance not explained by the length of the CAG repeat has shown that it is highly heritable, being due to genetic variation, elsewhere in the genome. The intent of the Genetic Modifiers of Huntington's Disease study is to identify genetic modifiers of HD pathogenesis by using genomewide association techniques in diagnosed HD individuals to identify genetic factors associated with the residual variance in age at onset not explained by the CAG repeat, and to extend these analyses to pre-diagnosis phenotypes, for example, those defined in the PREDICT-HD study. Identification of modifier genes is a top priority for HD research (and an example of an approach that can be applied in other late-onset genetic disorders), as it could provide clues to developing rational treatments that delay or prevent the pathogenic process from causing the ravages of the disease that ensue in the ~15 years of inexorable decline to ultimate death that now follows clinical diagnosis. To further that goal, the release of study version 2 makes available whole exome sequencing data of n=221 study participants.

Study phs000371

National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (FHS)

The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study, the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis. Together, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African-American, Caucasian, Asian, and Hispanic ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000401 contains the Framingham Heart Study (FHS) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

Study phs000401

Region-specific Transcriptome Analysis of the Human Retina and Retinal Pigment Epithelium (RPE)/Choroid

Proper spatial differentiation of retinal cell types is necessary for normal human vision. Many retinal diseases, such as Best disease and male germ cell associated kinase (MAK)-associated retinitis pigmentosa, preferentially affect distinct topographic regions of the retina. While much is known about the distribution of cell types in the retina, the distribution of molecular components across the posterior pole of the eye has not been well-studied. To investigate regional difference in molecular composition of ocular tissues, we assessed differential gene expression across the temporal, macular, and nasal retina and retinal pigment epithelium (RPE)/choroid of human eyes using RNA-Seq. RNA from temporal, macular, and nasal retina and RPE/choroid from four human donor eyes was extracted, poly-A selected, fragmented, and sequenced as 100 bp read pairs. Digital read files were mapped to the human genome and analyzed for differential expression using the Tuxedo software suite. Retina and RPE/choroid samples were clearly distinguishable at the transcriptome level. Numerous transcription factors were differentially expressed between regions of the retina and RPE/choroid. Photoreceptor-specific genes were enriched in the peripheral samples, while ganglion cell and amacrine cell genes were enriched in the macula. Within the RPE/choroid, RPE-specific genes were upregulated at the periphery while endothelium associated genes were upregulated in the macula. Consistent with previous studies, BEST1 expression was lower in macular than extramacular regions. The MAK gene was expressed at lower levels in macula than in extramacular regions, but did not exhibit a significant difference between nasal and temporal retina. The regional molecular distinction is greatest between macula and periphery and decreases between different peripheral regions within a tissue. Datasets such as these can be used to prioritize candidate genes for possible involvement in retinal diseases with regional phenotypes. Reprinted from Whitmore, S.S., Wagner, A.H., DeLuca, A.P., Drack, A.V., Stone, E.M., Tucker, B.A., Zeng, S., Braun, T.A., Mullins, R.F., Scheetz, T.E., 2014. Transcriptomic analysis across nasal, temporal, and macular regions of human neural retina and RPE/choroid by RNA-Seq. Experimental Eye Research. Used under Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported license. Additional RNA sequencing was performed on temporal, macular, nasal, inferior, and superior retina from a fifth subject and is included in this dataset. See original publication for details.

Study phs001151

National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (JHS)

The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study, the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis. Together, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African-American, Caucasian, Asian, and Hispanic ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000402 contains the Jackson Heart Study (JHS) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

Study phs000402

National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (CHS)

The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study, the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis. Together, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African-American, Caucasian, Asian, and Hispanic ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000400 contains the Cardiovascular Health Study (CHS) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

Study phs000400

Rare Genetic Steroid Disease Consortium (GSD) Apparent Mineralocorticoid Excess (AME) Syndrome Natural History Clinical Protocol

The objective of this project is to observe the natural history of apparent mineralocorticoid excess (AME). AME is a rare monogenic hypertensive disease first described by the Principal Investigator, Dr. Maria I. New, in 1977 [1], for which the first mutation in the causative HSD11B2 gene was reported by her group in 1995. [2] Little is known about the progression of this rare hypertensive disorder, which is defined by the presence of hypertension in conjunction with low renin, low to absent levels of the mineralocorticoid aldosterone, elevated urinary cortisol/cortisone metabolite ratio 5β-tetrahydrocortisol (THF) + allo-THF/ tetrahydrocortisone (THE) (i.e., THF+αTHF/THE) and the presence of mutations in the HSD11B2 gene on both alleles. The range of symptoms reflecting progressive end-organ damage is wide in the small number of affected individuals studied to date. It is important to develop accurate information on the longitudinal pattern of progression (natural history) of AME not only because it may improve the care of affected individuals, but also because it may serve as a platform for understanding the role of mineralocorticoid excess in other forms of low-renin hypertension, which constitute 40% of all forms of hypertension. In this study, we will recruit as widely as possible through the Rare Diseases Clinical Research Network (RDCRN) to identify individuals with the triad of low renin, low aldosterone, and elevated urinary THF+αTHF/THE and confirm their disorder as AME by molecular genetic testing of the HSD11B2 gene. We will gather clinical and biochemical data yearly for the duration of the grant. We will describe phenotype and genotype at diagnosis and follow the progression or regression of symptoms over time under standard treatment, with rigorous review of end organs potentially damaged by chronic hypertension. Finally, we will study the natural history of the carriers of HSD11B2 mutations, i.e., the heterozygote relatives of the probands, in order to ascertain evidence of existing or developing hypertension and resulting end-organ damage. This will be the first rigorous study of AME heterozygotes. The participant accrual for AME-affected patients and the carriers of HSD11B2 mutations will be at least two years, but as long as seven years.

Study phs000603

National Institute of Arthritis and Musculoskeletal and Skin Diseases and Istanbul Faculty of Medicine Genome-wide Association Study of Behçet's Disease (Turkish)

IntroductionBehçet's disease (BD) is a genetically complex multisystem disease of unknown etiology, characterized by recurrent inflammatory attacks affecting orogenital mucosa, eyes, skin, joints, blood vessels, and less frequently, the central nervous system and gastrointestinal tract. Family studies suggest a genetically complex contribution to BD. With the exception of HLA-B51, which explains less than 20% of the genetic risk, the identities of alleles that are responsible for the complex inheritance of this disease have remained unclear. AimTo identify genes that contribute to BD susceptibility. MethodsA genome-wide association study was undertaken with 311,459 informative and high quality SNPs in a collection of 1215 BD patients and 1278 healthy controls from Turkey using a beadchip microarray assay (Infinium SNP genotype assay, Illumina). HLA-B types were determined with a reverse sequence-specific oligonucleotide method (One Lambda). Regions with evidence for association were fine-mapped using Sequenom iPLEX gold assays. Disease-associated SNPs were genotyped in additional ethnically matched case/control collections from diverse genetic backgrounds, including a total of 2430 cases and 2660 controls, using TaqMan SNP genotype assays. Association data were combined in a meta-analysis of all the collections. ResultsWe confirmed the known association with HLA-B51 and found evidence for a second, independent susceptibility locus in the Class I region of the MHC. In addition, we identified one SNP with genome-wide evidence for disease association (P < 5.0 x 10-8) within the gene encoding the immunoregulatory cytokine, interleukin-10 (IL10). A meta-analysis of the data from all the collections established associations with the IL10 variant (rs1518111, P = 3.54 x 10-18, odds ratio 1.45 with 95% confidence interval 1.34 to 1.58) and with a variant located between the interleukin-23 receptor (IL23R) and interleukin 12 receptor β2 (IL12RB2) genes (rs924080, P = 6.69 x 10-9, odds ratio 1.28 with 95% confidence interval 1.18 to 1.39). The disease-associated IL10 variant was associated with diminished mRNA expression and low protein production by cells obtained from healthy blood donors. ConclusionsThese data suggest that genetically encoded low production of IL-10 increases risk of BD and suggest novel interventional targets in the IL-10 and IL-23 pathways. Note: The submitted data are the genotypes of the 311,459 SNPs in 1215 cases and 1278 controls.

Study phs000272

Circulating Genomic Determinants of Treatment Failure in Hodgkin Lymphoma

In this study, we show that the plasma representation of mutations exceeds the bulk tumor representation in most cases, making classic Hodgkin Lymphoma (cHL) particularly amenable to noninvasive profiling. Leveraging single-cell transcriptional profiles of cHL tumors, we demonstrate hazard ratios (HRs) circulating tumor DNA (ctDNA) shedding to be shaped by DNASE1L3, whose increased tumor microenvironment-derived expression drives high ctDNA concentrations. Using this insight, we comprehensively profile 366 patients, revealing two distinct cHL genomic subtypes with characteristic clinical and prognostic correlates, as well as distinct transcriptional and immunological profiles. Furthermore, we identify a novel class of truncating IL4R-mutations that are dependent on IL13 signaling and therapeutically targetable with IL4R blocking antibodies. Finally, we demonstrate the clinical value of pre- and on-treatment ctDNA levels for longitudinally refining cHL risk prediction, and for detection of radiographically occult minimal residual disease. Collectively, these results support the utility of noninvasive strategies for genotyping and dynamic monitoring of cHL as well as capturing molecularly distinct subtypes with diagnostic, prognostic, and therapeutic potential.Methods utilized include a) targeted genotyping of baseline plasma samples, b) whole exome sequencing (WES) of baseline plasma samples, c) epigenetic expression inference from cell-free DNA-sequencing (EPIC-Seq) to infer gene expression from cell-free DNA (cfDNA) fragmentation profiles, d) ctDNA tracking in on-treatment samples, e) RNA-Sequencing, and f) Phased variant Enrichment and Detection Sequencing (PhasED-Seq).All patients were treated at cancer centers across Europe and North America between 2011 and 2020. The following 3 cancer centers, Stanford (CA, USA), Bellinzona [Confoederatio Helvetica (CH) or Switzerland], and Leuven (Belgium), were included. The 6 clinical trial collectives included in this study are the Phase III trial AHOD1331 trial (NCT02166463) and the Phase II cHOD17 study (NCT03755804) for enrolled pediatric patients, the Phase III AHL2011 (NCT01358747), the Phase II BREACH trial (NCT02292979), a pilot study evaluating concurrent Pembrolizumab with AVD (Doxorubicin, also known as Adriamycin, Vinblastine, and Dacarbazine; NCT03331341), and a Phase II study evaluating PVAB (Prednisone, Vinblastine, Doxorubicin and Bendamustine; NCT02414568) in older patients (61 years and older). In addition, lymph node specimens from a biorepository at St. Jude Children's Research Hospital (TN, USA) were included.

Study phs003435

CRCbiome: Gut metagenome of Norwegian screening participants using FIT sampling

The study aims to characterize the gut metagenome of Norwegian screening participants and assess the ability of the gut metagenome to identify those at need for colonoscopy. Background: Colorectal cancer (CRC) screening reduces CRC incidence and mortality. However, current screening methods are either hampered by invasiveness or suboptimal performance, limiting their effectiveness as primary screening methods. To aid in the development of a non-invasive screening test with improved sensitivity and specificity, we have initiated a prospective biomarker study (CRCbiome), nested within a large randomized CRC screening trial in Norway. We aim to develop a microbiome-based classification algorithm to identify advanced colorectal lesions in screening participants testing positive for an immunochemical fecal occult blood test (FIT). We will also examine interactions with host factors, diet, lifestyle and prescription drugs. The prospective nature of the study also enables the analysis of changes in the gut microbiome following the removal of precancerous lesions. Methods: The CRCbiome study recruits participants enrolled in the Bowel Cancer Screening in Norway (BCSN) study, a randomized trial initiated in 2012 comparing once-only sigmoidoscopy to repeated biennial FIT, where women and men aged 50–74 years at study entry are invited to participate. Since 2017, participants randomized to FIT screening with a positive test result have been invited to join the CRCbiome study. Self-reported diet, lifestyle and demographic data are collected prior to colonoscopy after the positive FIT-test (baseline). Screening data, including colonoscopy findings are obtained from the BCSN database. Fecal samples for gut microbiome analyses are collected both before and 2 and 12 months after colonoscopy. Samples are analyzed using metagenome sequencing, with taxonomy profiles, and gene and pathway content as primary measures. CRCbiome data will also be linked to national registries to obtain information on prescription histories and cancer relevant outcomes occurring during the 10 year follow-up period. Discussion: The CRCbiome study will increase our understanding of how the gut microbiome, in combination with lifestyle and environmental factors, influences the early stages of colorectal carcinogenesis. This knowledge will be crucial to develop microbiome-based screening tools for CRC. By evaluating biomarker performance in a screening setting, using samples from the target population, the generalizability of the findings to future screening cohorts is likely to be high.

Study EGAS50000000170

Molecular_characterization_of_invasive_lobular_carcinoma

Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer accounting for 10-15% of cases. ILC differs from invasive ductal carcinoma (IDC)with respect to epidemiology, histology, and clinical presentation. Moreover, ILC is lesssensitive to chemotherapy, more frequently bilateral, and more prone to form gastrointestinal, peritoneal, and ovarian metastases than IDCs. In contrast to IDC, the prognostic value ofhistological grade (HG) in ILC is controversial. One of the three major components of histological grading (tubule formation) is missing in ILC which hinders the process of gradingin this histological subtype and results in the classification of approximately two thirds of ILC as HG 2.Over the last decade, a number of gene expression signatures have shed light onto breast cancer classification, allowing breast cancer care to become more personalized. Withrespect to the management of estrogen receptor (ER)-positive breast cancer, several gene expression signatures provide prognostic and/or predictive information beyond what is possible with current classical clinico-pathological parameters alone. Nevertheless, most studies using gene expression signature have not considered different histologic subtypesseparately. Recently, a comprehensive research program has elucidated some of the biological underpinnings of invasive lobular carcinoma. Genetic material extracted from 200 ILC tumor samples were studied using gene expression profiling and identified ILCmolecular subtypes. These proliferation-driven gene signatures of ILC appear to have prognostic significance. In particular, the Genomic Grade (GG) gene signature improved upon HG in ILC and added prognostic value to classic clinico-pathologic factors. In addition this study demonstrated that most ILC are molecularly characterized as luminal-A (~75%)followed by luminal-B (~20%) and HER2-positve tumors (~5%). Moreover, we investigated the prognostic value of known gene signatures/ gene modules in the same cohort of ILC. As a second step within the scope of this project, we aim to investigate the interactionsbetween somatic ILC tumor mutations to observed transcriptome findings. To this end, we aim to perform somatic mutation analysis for the ILC tumors for which Affymetrix gene expression profiling is available. To this end, we will use a gene screen assay, which specifically interrogates the mutational status of a few hundreds of cancer genes. We believe that this pioneering effort will be fundamental for a tailored treatment of ILC withimprovement in patients' outcome.

Study EGAS00001000292

Genome_Diversity_in_Africa_Project__Benin

Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene–disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region.The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group).Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformaticsThis 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/

Study EGAS00001001688

Multi-omics data of 1000 Inflammatory Bowel Disease patients

Portal available at https://1000ibd.org Inflammatory bowel disease (IBD) is a chronic complex disease of the gastrointestinal (GI) tract. Patients with IBD can experience a wide range of symptoms, but the pathophysiological mechanisms that cause these individual differences in clinical presentation remain largely unknown. In consequence, IBD is currently classified into subtypes using clinical characteristics. If we are to develop a more targeted treatment approach, molecular subtypes of IBD need to be discovered that can be used as new drug targets. To achieve this, we need multiple layers of molecular data are generated from the same IBD patients.We initiated the 1000IBD project to prospectively follow more than 1000 IBD patients from the Northern provinces of the Netherlands. For these patients, we have collected a uniquely large number of phenotypes and generated multi-omics profiles. To date, 1,215 participants have been enrolled in the project and enrolment is on-going, with 609 patients being present in the first data release. Phenotype data collected for these participants includes information on dietary and environmental factors, drug responses, and adverse drug events. Genome information has been generated using genotyping (ImmunoChip, Global Screening Array and HumanExomeChip) and sequencing (whole exome sequencing and targeted resequencing of IBD susceptibility loci), transcriptome information generated using RNA-sequencing of intestinal biopsies and microbiome information generated using both sequencing of the 16S rRNA gene and whole genome shotgun metagenomic sequencing.All molecular data generated within the 1000IBD project will be shared in multiple data on the European Genome-Phenome Archive (www.ega-archive.org). The first data release, will contain basic phenotypes for 609 participants, genotypes of 314 participants, gut microbiome data generated by tag sequencing the 16S gene of feces from 315 participants and intestinal biopsies from 107 participants, and gut microbiome metagenomic sequencing of feces of 355 participants . Future releases will comprise many more additional phenotypes and -omics data layers. 1000IBD data can be used by other researchers as a replication cohort, a dataset to test new software tools, or a dataset for applying new statistical models.

Study EGAS00001002702

RNA_Seq_in_Patients_with_Primordial_Dwarfism

Transcriptome studies in patients with rare genetic diseases can potentially aid in theinterpretation of likely causal genetic variation through identification of altered transcriptabundance and/or structure. RNA-Seq is the most sensitive assay for both investigatingtranscript structure and abundanceThe primary aim of this pilot project is to investigate to what degree integrating exome-Seqand RNA-Seq data on the same individual can accelerate the identification of causal allelesfor rare genetic diseases. There are two main strands to this: (i) identifying which variantsdiscovered in exome-seq appear to be having a functional impact on transcripts, and (ii)identifying transcript outliers, especially among known causal genes, that may not necessarilyhave a causal variant identified from exome sequencing. The latter may identify the presenceof causal variants that lie far from coding regions (e.g. the formation of cryptic splice sitesdeep within introns, or loss of long range regulatory elements), which can be confirmed withfurther targeted genetic assays. Just over 50% of all disease-causing variants recorded in theHuman Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g.nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs).This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients withprimordial dwarfism syndromes, for 10 of these samples we have previously generate exomedata as part of our collaboration with the group of Prof Andrew Jackson. The two remainingsamples are positive controls where the causal mutation is known, and is known to affecttranscript structure and/or abundance.Primordial dwarfism is a prime candidate for these RNA-seq studies because all knowncausal mutations to date have key roles in DNA replication and thus, unsurprisingly, theproducts of the causal genes are typically ubiquitously expressed.Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) persample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity.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/

Study EGAS00001000283

Exploring high-throughput drug sensitivity testing in neuroblastoma cell lines and patient-derived tumor organoids in the era of precision medicine

Despite druggable events in 80% of neuroblastoma patients within the Princess Máxima Center precision medicine program 'iTHER', clinical uptake of treatment recommendations has been low, and the clinical impact for individual patients remains hard to predict. This stresses the need for a method integrating genomics and transcriptomics with functional approaches into therapeutic decision making. We aimed to launch an online repository integrating genomics and transcriptomics with high-throughput drug screening (HTS) of nineteen commonly used neuroblastoma cell lines and fourteen generated neuroblastoma patient-derived organoids (NBL-PDOs) to improve identification of molecularly matched therapies and support clinical uptake. Cell lines, NBL-PDOs and their parental tumors were characterized utilizing (lc)WGS, WES and RNAseq. Cells were exposed to a ~200 compound library, and viability was assessed using CellTiterGlo or MTT. Molecular and HTS results were transferred to the R2 platform (http://r2platform.com/pmc_nb_drugs/), in which a comprehensive suite of visualizations and analysis options were implemented. As a result, a powerful reference set of cell lines is available, reflecting distinct known pharmacologic vulnerabilities, including resistance of TP53-inactivated lines to MDM2 inhibitor idasanutlin; ALK-inhibitor sensitivity in ALK-activated lines, and sensitivity of an ATM-deleted cell line to PARP- and CHEK1-inhibitors. Novel established NBL-PDOs retained molecular features of their parental tumor and again reflected established drug sensitivities. However, HTS also identified additional therapeutic vulnerabilities in vitro, such as a striking correlation between a positive mesenchymal signature and sensitivity to BCL2-inhibitor venetoclax. Finally, we explored personalized drug sensitivities within iTHER, demonstrating HTS can support genomic and transcriptomic results, thereby strengthening the rationale for clinical uptake. Furthermore, in vitro insensitivity may avoid ineffective treatments. Lastly, novel treatment options may be identified, as indicated by sensitivity to ponatinib correlating with overexpression of RET or KIT. In conclusion, we established a dynamic publicly available dataset with detailed genomic, transcriptomic, and pharmacological annotation of classical neuroblastoma cell lines as well as NBL-PDOs, representing the heterogeneous landscape of neuroblastoma. We anticipate that in vitro drug screening will be complementary to genomic-guided precision medicine by supporting clinical decision making, thereby improving prognosis for all neuroblastoma patients in the future.

Study EGAS00001007160

Whole_genome_sequencing_of_100_DDD_trios_with_suspected_noncoding_causal_mutations

We would like to whole-genome sequence 100 trios (300 individuals) from the DDD project in which we suspect the proband has a pathogenic noncoding mutation, to 30X coverage. These have been carefully selected to maximise the chances of finding pathogenic noncoding mutations. Specifically, we have selected probands who have no likely causal mutation within the coding region but who have a heterozygous loss-of-function mutation inherited from one parent in a known recessive developmental disorder gene, and whose phenotype is a good match for the typical phenotype caused by recessive variants in that gene. We suspect that these probands may have a heterozygous noncoding mutation on the other allele which reduces expression of the gene so that, together, these two mutations are effectively equivalent to a homozygous loss-of-function mutation. About a quarter of the probands have affected siblings and, if those siblings have been exome sequenced, we have checked that they are identical-by-descent in the region of the gene. We propose to search in the promoter region, intronic and annotated regulatory regions around these genes of interest for rare variants inherited from the other parent (i.e. not the one who transmitted the loss-of-function variant), or de novo variants. If we find such variants, and demonstrate an enrichment of this compound heterozygous LoF noncoding mechanism above that expected by chance, we intend to follow up specific candidates by RNAseq and potentially CRISPR/Cas9 experiments. 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 please see http://www.sanger.ac.uk/datasharing/

Study EGAS00001002452

Bladder Cancer Organoids as a Functional System to Model Different Disease Stages and Therapy Response

The study 'Bladder Cancer Organoids as a Functional System to Model Different Disease Stages and Therapy Response' reports the genomic characterization at the single allele level upon Whole Exome Sequencing of Bladder Cancer (BLCa) Patient Tumor (PT) samples obtained from 18 patients and corresponding Patient Derived Organoids (PDOs), implementing the SPICE pipeline (Ciani Y et al). Our cohort included 21 PTs and 22 PDOs. In this study, we generated a unique biobank resource of BLCa organoids that encompasses a broad spectrum of disease stages. We demonstrated that PDOs retain cancer heterogeneity and mutational burden. Furthermore, we observed that BLCa PDO can have different morphologies which may reflect tumor-specific features. Indeed, a solid morphology may be associated with more advanced tumors, as supported by the high PDO genomic burden and high primary tumor stage. Moreover, with our drug screening pipeline, we demonstrated the clinical relevance and feasibility of using a BLCa PDO-based drug assay for comparing the standard of care (SOC) drugs with compounds not currently in use for BLCa. Response to SOC was highly heterogeneous with approximately 50% of non-muscle invasive bladder cancer and 33% of muscle invasive bladder cancer PDOs showing no or minimal response. The most effective targeted therapy was lapatinib. We used an integrative analysis of drug response profiles with matched PDO genomic analysis to determine enrichment thresholds for candidate markers of therapy resistance and sensitivity. Importantly, by assessing the clinical history of longitudinally sampled cases, the clonal evolution of the disease could be determined and matched with PDO drug response profiles.

Study phs003149

NHLBI GO-ESP Family Studies: Pulmonary Arterial Hypertension

The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. Pulmonary arterial hypertension (PAH) is a progressive disease characterized by widespread occlusion of the smallest arteries of the lungs. Pulmonary vascular obstruction leads to increased pulmonary vascular resistance, which subsequently causes heart failure with mean survival of 3 years. PAH occurs at all ages and affects women more than twice as frequently as men. Sporadic Idiopathic pulmonary arterial hypertension (IPAH), comprises 94% of what was formerly known as primary pulmonary hypertension, and is clinically and pathologically indistinguishable from familial PAH (FPAH). Most FPAH is due to mutation in BMPR2, including more than 120 families in the US. Our goal here is to find other genes that are a basis for FPAH, so we selected for exome sequencing 5 families among 40 who do not have mutation in BMPR2, or other known genes (ACVRL1, SMAD8, ENG) that rarely are the basis for FPAH.

Study phs000354

Genetics of Neuropsychiatric and Neurodevelopmental Disorders

Although schizophrenia is a highly heritable disease, relatively little progress had been made in securely identifying the genetic causes of this disorder, and most instances of schizophrenia in the general population remain unexplained. One avenue of explanation for the genetic basis of schizophrenia, however, has been effectively closed by recent research. Genome-wide association studies (GWAS) have now shown that common variation makes at most a modest contribution to the risk of schizophrenia. At the same time that the role of common variation has been circumscribed by GWAS, however, the analysis of copy number variants that are detectable on a genome-wide scale has revealed and replicated a number of very rare variants that associate with schizophrenia. These rare copy number variants that have been implicated in schizophrenia, however, have one striking feature in common: they are all risk factors for other brain related disorders beyond schizophrenia such as mental retardation, autism and epilepsy. These findings argue that genetic risk factors may confer a highly penetrant vulnerability to neuropsychiatric disorder, which is then further modified by interacting genetic or environmental factors to determine the ultimate manifestation. Most schizophrenia collections that are being studied today, however, have been selected precisely for their homogeneity: including only schizophrenia patients with no comorbidities, or schizophrenia patients with relatives who have schizophrenia but no other neuropsychiatric conditions. These selection criteria are inconsistent with what we now know about the bulk of the genetic differences that have been associated with disease. The central hypothesis of this project is that there are rare genetic variants that strongly elevate the risk of various neuropsychiatric diseases, and that these risk factors can be identified most readily in families segregating multiple neuropsychiatric conditions.

Study phs000682

Genomic Evolution of Low- and High-Grade Glioma

Malignant transformation (MT) of IDH-mutant low-grade glioma (LGG) to aggressive high-grade tumors is an event of major clinical significance, eventually leading to death in the majority of LGG patients. While patients with primary glioblastoma (GBM) have benefited from increased overall survival due to treatment with the alkylating chemotherapy temozolomide (TMZ), the benefit of TMZ for patients with diffuse low-grade gliomas (LGG) remains unknown. To further explore the relationships among TMZ treatment, hypermutation and malignant progression, we studied tumor evolution in an expanded cohort of untreated and TMZ-treated patients by exome-sequencing of paired IDH1/2-mutant LGGs and their post-TMZ recurrences. Together, these findings further our understanding of the molecular features and clinical behavior of hypermutated clones. The heterogeneity present in individual tumors, i.e. intratumoral heterogeneity (ITH), is thought to be a major reason why targeted treatments eventually fail. However, we know little about ITH in most human tumors because studies typically analyze one biopsy per tumor without knowledge of where in the tumor the sample was taken. Understanding how malignant and non-malignant cellular populations are distributed in 3D tumor space is foundational knowledge for resolving how human tumors grow, with translational implications for identifying representative biopsy specimens and predicting the impact of targeted therapy. Diffuse gliomas are incurable brain tumors with variably aggressive molecular subtypes. To determine the extent of ITH and its 3D organization in diffuse glioma, we prospectively collected a median of 10 spatially mapped samples from newly diagnosed and recurrent patient tumors, including aggressive canonical IDH1/IDH2 wild-type (IDH-wtc) glioblastoma, slower-growing IDH1/IDH2 mutant (IDHmut) glioma and a noncanonical IDH-wt glioblastoma (IDH-wtnc) lacking the TERT promoter mutation typical of canonical Glioblastoma.

Study phs002034

Analysis of Donor Pancreata Defines the Transcriptomic Signature and Microenvironment of Early Neoplastic Pancreatic Lesions

The adult healthy human pancreas has been poorly studied given lack of indication to obtain tissue from the pancreas in the absence of disease and rapid postmortem degradation. We obtained pancreata from brain dead donors thus avoiding any warm ischemia time. We found that neoplastic lesions occur frequently in healthy organs, in donors as young as in their 3rd decade of life. Using the 10X Genomics Platform, we performed single cell RNA sequencing on 7 donor pancreata, 6 of which we separately sequenced tissue from the pancreas head and tail, for a total of 11 sequencing runs. Of note, because one of our runs (containing sequencing from pancreas head and tail) did not pass qc, our final analysis in our study utilized 6 donor pancreata, 5 of which contained pancreas head and tail sequenced separately. This is a robust single-cell dataset of healthy, nonpathologic pancreas tissue and includes acinar, ductal, and non-epithelial cells (myeloid cells, fibroblasts, endothelial cells, lymphocytes).Briefly, the donor pancreas was dissected by a clinically-trained pancreatobiliary surgeon. The organ was dissected into head, body, and tail, with portions of each placed into DMEM media with 1% BSA/10µM Y27632. Tissue was minced into 1mm3 pieces, then digested with 1 mg/mL collagenase P for 20-30 min at 37°C with gentle agitation. Digested tissue was rinsed three times with DMEM/1% BSA/10µM Y27632, then filtered through a 40µm mesh. Resulting cells were submitted to the University of Michigan Advanced Genomics Core for single cell sequencing using the 10x Genomics Platform. FASTQ files of all sequencing runs along with clinical annotation of donors is available through this dbGaP submission.

Study phs003229

Ecological Stressors, PTSD, and Drug Use in Detroit: The Detroit Neighborhood Health Study (DNHS)

The Detroit Neighborhood Health Study (DNHS) is a prospective, representative longitudinal cohort study of predominantly African American adults living in Detroit, Michigan. The overall goal of the DNHS is to identify how genetic variation, lifetime experience of stressful and traumatic events, and features of the neighborhood environment predict psychopathology and behavior. Cohort participants were selected with a dual-frame probability design, using telephone numbers obtained from the U.S. Postal Service Delivery Sequence Files as well as a listed-assisted random-digit-dial frame. Individuals without listed landlines or telephones and individuals with only a cell phone listed were invited to participate through a postal mail effort. Participants completed a 40 minute, structured telephone interview annually between 2008-2012 to assess perceptions of participants' neighborhoods, mental and physical health status, social support, exposure to traumatic events, and alcohol and tobacco use; each participant was compensated $25USD. All survey participants were offered the opportunity to provide a specimen (venipuncture, blood spot, or saliva) for immune and inflammatory marker testing as well as genetic testing of DNA. Participants received an additional $25USD if they elected to give a sample. Informed consent was obtained at the beginning of each interview and again at specimen collection. The Institutional Review Board of the University of Michigan reviewed and approved the study protocol. The DNHS submission to dbGaP includes phenotype data from all five survey waves (n=856), all available GWAS data for participants who completed wave 4 (n=507), and methylation data for wave 1, wave 2, wave 4, and wave 5 participants (n = 456).

Study phs000560

Exome Sequencing to Identify Medically Relevant Associations in Finnish Sub-Isolate Samples from the FINRISK Cohort

We propose to undertake, at the McDonnell Genome Institute of Washington University, a collaborative exome sequencing project of ~10,000 samples from a large Finnish population cohort, FINRISK, a participating component of the Sequencing Initiative Suomi (SISu) consortium. Together these sequenced samples will provide a unique resource for identification of infrequent or rare variants with a large impact on cardiovascular and metabolic disorders as well as on a wide range of heritable, disease-related quantitative phenotypes. Our collaborative group has already shown, in exome sequencing studies of smaller Finnish samples, that numerous loss of function variants are dramatically more frequent in Finland compared to other European populations, and that such variants demonstrate strong associations to several disease-related traits. Finland is the largest population isolate in Europe and the enrichment of these variants reflects its rapid growth from a severe population bottleneck about 100 generations ago. Northern and Eastern parts of Finland experienced additional, more recent bottlenecks, and therefore the enrichment of particular high-impact variants in these regions is even more extreme (Stoll et al., 2013, PMID: 23912948). We therefore propose to focus exome sequencing efforts on about 10,000 members of FINRISK who are specifically drawn from these sub-isolate regions. As a very wide range of phenotypes are available from this cohort (including cardiovascular and metabolic disease outcomes obtained from national registries) we hypothesize that the proposed exome sequencing will identify numerous new disease-related associations. Within the National Biobanks of Finland (www.nationalbiobanks.fi) we have DNA and tissue samples from over 200,000 individuals of whom 50,000 have GWAS data; these samples provide an exceptional resource for both imputation from the sequencing studies proposed here, as well as for replication of associations.

Study phs000756

Diabetes Control and Complications Trial (DCCT) and Epidemiology of Diabetes Interventions and Complications Study (EDIC)

The Diabetes Control and Complications Trial (DCCT, 1982-93) and the Epidemiology of Diabetes Interventions and Complications follow-up study (EDIC, 1994-2016) have been ongoing for more than twenty years. After a mean follow-up of approximately 16 years, the DCCT-EDIC cohort of 1,441 Type 1 diabetics had remained remarkably complete with more than 90% of the original cohort being actively followed. Taken together, the DCCT clinical trial and subsequent EDIC longitudinal follow-up provide a uniquely rich source of information on the impact of intensive therapy on glycemia and the its long-term complications for persons with Type 1 diabetes. The DCCT was a multicenter, randomized clinical trial (1, 2) designed to compare intensive with conventional diabetes therapy with regard to their effects on the development and progression of the early complications of Type 1 diabetes. The DCCT trial found that "intensive therapy effectively delays the onset and slows the progression of diabetic retinopathy, nephropathy, and neuropathy" in patients with Type 1 diabetes (1). The goal of the EDIC follow-up was to examine the longer term effects of the original DCCT interventions, especially as they apply to late-occurring complications, such as cardiovascular disease and more advanced stages of retinal and renal disease (3). The EDIC study has been remarkably fruitful in discovering the long term "imprinting" effects (metabolic memory) of the previous intensive therapy, and in delineating the interactions among risk factors with regard to microvascular complications (4-6). In addition, EDIC established, for the first time, the role of intensive therapy and chronic glycemia on atherosclerosis (7-9). Note: This study description has been prepared using materials authored by the DCCT-EDIC Data Coordinating Center. DETAILED DESCRIPTION OF STUDY

Study phs000086

NHLBI: Genetic modifiers of sickle cell anemia severity and fetal hemoglobin expression in the Cooperative Study of Sickle Cell Disease (CSSCD)

Phenotypic heterogeneity is characteristic of sickle cell anemia, a Mendelian disorder caused by homozygosity for the sickle HBB gene (glu6val). Patients have different rates of hemolysis/vasculopathy and viscosity/vasoocclusion-related complications. These complications account for a substantial reduction in life expectancy. In 1994, the median life expectancy for men and women with sickle cell anemia was 42 and 48 years, respectively, and despite many advances in care, the annual mortality still approaches 4%. Fetal hemoglobin (HbF) is one of the most studied markers of severity of sickle cell anemia, and detailed longitudinal measurements were taken on subjects enrolled in the Cooperative Study of Sickle Cell Disease (CSSCD). Cubic root transformation of the median values from follow-up in 848 African American subjects is the phenotype data used in the GWAS of fetal hemoglobin. The analysis was adjusted by sex. Details are in Solovieff et al., Blood 2010 [PMID: 20018918]. To integrate individual disease complications into a comprehensive measure of severity, we developed a model of the associations among clinical and laboratory variables that scored disease severity as the risk of death within 5 years. This network was developed using data obtained from more than 3,400 subjects from the CSSCD, and its accuracy was validated in two unrelated sets of sickle cell patients. Recently, the network was also validated in a small European cohort of patients with sickle cell anemia. We used extreme values of disease severity as cases and control in the GWAS of severity of sickle cell anemia. We conducted the GWAS in 1,265 patients with either "severe" (177) or "mild" disease (1088) based on a network model of disease severity. Details are in Sebastiani et al. Am J Hematol, 2010 [PMID: 20029952].

Study phs000366

AC-ICAM: An Atlas and Compass of Immune-CAncer-Microbiome Interactions in Colon Cancer

Fresh frozen tumor samples and matched normal colon specimens from chemotherapy naïve, consecutive patients with a histological diagnosis of colon adenocarcinoma at Leiden University Medical Center (LUMC) were subjected to multi-omics profiling at Sidra Integrated Genomics Services, part of Sidra Medicine, Doha, Qatar. This resulted in a high-quality dataset of samples collected between 2001 and 2015. Multi-step QC was performed, including assessment of the quality of the nucleic acid extraction, sequencing, and genetic concordance between DNA/RNA sequences from the same patient. After QC, this resulted in RNA sequencing on 348 tumor samples, whole exome sequencing (WES) on 281 tumor-normal sample pairs (n=562 samples), TCR sequencing of the TCR β locus (TRB) for 114 tumor and 10 matched normal samples, and 16S rDNA sequencing on 246 tumor-normal sample pairs (n=492 samples) and 42 tumor only samples, and 167 WGS non human-aligned reads of the tumor samples. Extensive clinicopathological and survival data of the cohort are available. The median follow-up time for this cohort is 4.6 years, and the distribution of gender and pathological stage are within expected ranges for this patient population with a mean age of 68. We refer to this resource as the Sidra-LUMC (SILU) colon adenocarcinoma (COAD) Atlas and Compass of Immune-Colon cancer-Microbiome interactions (AC-ICAM)."Reprinted from Nature Medicine,Roelands, J., Kuppen, P.J.K., Ahmed, E.I. et al. An integrated tumor, immune and microbiome atlas of colon cancer. Nat Med (2023). https://doi.org/10.1038/s41591-023-02324-5, with permission from Nature."

Study phs002978

Microvascular Permeability, Inflammation, and Lesion Physiology in Endometriosis: A Microphysiological Systems Approach

The goal of the study is to identify novel molecular pathways involved in the etiology of endometriosis and to develop in vitro model systems to enable the study of the mechanisms regulating reproductive function. Using a physiomimetic modeling approach, primary tissue samples of the human endometrium derived from patients diagnosed with and without endometriosis and/or endometriotic diseases (e.g. adenomyosis) were used for secondary analysis using multi-omic systems biology analysis and to build tissue engineered models. We performed single cell RNA sequencing (scRNA-Seq, N=6)) to study the cellular and transcriptomic composition of the endometrial tissue microenvironment and proteomics (LC-MS/MS) to study protein-level signaling pathways and the matrisome of the native endometrium. Systems biology analysis of these datasets helped identified a putative dysregulated inflammatory signaling pathway in endometriosis patients compared to controls. Moreover, subsets from these scRNA-Seq and proteomic datasets were used to aid the design of a synthetic extracellular matrix hydrogel as an in vitro platform for the culture of endometrial cells. Tissue-engineered synthetic PEG hydrogel enables the simultaneous co-culture of endometrial epithelial organoids and stromal fibroblasts in a fully defined, 3D, and tunable environment. We demonstrated that the in vitro co-culture model recapitulates key phenotypic processes observed across the human menstrual cycle in response to sex hormone stimulation through both biochemical and transcriptomic (bulk RNA-sequencing) analysis. This model will enable future mechanistic studies that examine origins of endometriotic disease phenotypes. The transcriptomic data generated for this study including the scRNA-Seq data from primary human endometrial tissues and the bulk RNA-Seq datasets from the experimental co-culture models is available through dbGAP.

Study phs003326

Genetic Investigations of Attention-Deficit/Hyperactivity Disorder

Design and Aims:We conducted whole-exome DNA sequencing on 152 parent-child trios (456 individuals total) that included a child meeting DSM-IV or DSM-5 criteria for ADHD along with both biological parents to identify rare de novo damaging DNA variants associated with ADHD risk. Mutation rates were compared between 147 ADHD trios and 780 unaffected control trios. We aimed to identify specific ADHD risk genes by combining the de novo trio data with rare variant data from an independent case-control cohort.Population Information:ADHD trios were collected from four sites. The 780 control trios were unaffected siblings from the Simons Simplex Collection who scored in the normal range on the Child Behavior Checklist (CBCL) or Adult Behavior Checklist (ABCL) ADHD subscale.Molecular Technologies:Whole-exome DNA sequencing was performed on the ADHD trios using the IDT xGen V1 or Agilent SureSelect All Exon V7 capture and the Illumina NovaSeq6000 sequencer. Control trios were previously sequenced with the NimbleGen SeqCap EzExomeV2 capture and Illumina HiSeq 2000 sequencer. Joint variant calling was performed for all trios. Rare de novo variants with allele frequency Principal Findings:We found a 1.67-fold enrichment of rare de novo damaging variants and a 1.93-fold enrichment of ultra-rare de novo damaging variants in ADHD cases vs controls. By integrating the de novo data with an independent case-control cohort, KDM5B was identified as a high-confidence ADHD risk gene (FDR=0.04). Three potential risk genes were also identified. Twenty-three genes with ultra-rare damaging de novo variants in ADHD overlapped with previously reported risk genes for other neuropsychiatric conditions. Exploratory analyses showed enrichment of these genes in early neurodevelopmental pathways.

Study phs003647

A Personalized Neoantigen Vaccine Generates Anti-Tumor Immunity in High-Risk Renal Cell Carcinoma

Personalized cancer vaccines (PCVs) can generate circulating immune responses against predicted neoantigens. However, whether such responses can target cancer driver mutations, lead to immune recognition of a patient's tumor, and result in clinical activity are largely unknown, particularly in patients with lower mutation burden tumors. We conducted a phase I trial testing a neoantigen-targeting PCV in patients with high-risk, fully resected clear cell renal cell carcinoma (RCC; stage III or IV), with or without ipilimumab administered adjacent to the vaccine. At a median follow-up of 40.2 months from surgery, none of the 9 initial participants experienced a recurrence of RCC. No dose-limiting toxicities were observed. All patients generated T cell immune responses against PCV antigens, including RCC driver mutations in VHL, PBRM1, BAP1, KDM5C, and PIK3CA. Following vaccination, there was a durable expansion of peripheral T cell clones, and T cell reactivity against autologous tumor was detected in 7 of the 9 patients. Our results demonstrate that neoantigen-targeting PCVs in high-risk RCC are highly immunogenic, capable of targeting key driver mutations, and induce anti-tumor immunity. These observations, in conjunction with the absence of recurrence in all 9 vaccinated patients, highlights the promise of PCV as effective adjuvant therapy in RCC. We are submitting WES data from whole blood samples and tumor FFPE samples, and RNA-Seq data from tumor FFPE samples. We are also submitting RNA-Seq data from purified tumor samples. scRNA-seq data will be submitted for skin samples (vaccine site biopsies at Weeks 0, 4, and 13), tumor samples (including resected metastatic tumor samples for two patients), and normal kidney samples. Bulk TCR-seq data will be submitted for blood samples.

Study phs003710

Sequencing of 3D Organoids Derived From Colorectal Cancer Patients

This study focuses on the whole-exome sequencing (WES) of patient-derived organoids (PDOs) established from colorectal cancer (CRC) tumors collected at Columbia University. CRC remains a major cause of cancer-related mortality due to its metastatic progression and resistance to therapy. To model CRC at the patient level, we generated 3D organoid cultures from primary and metastatic tumors, preserving their genetic and phenotypic characteristics. The study cohort consists of 9 CRC patients with microsatellite-stable adenocarcinomas from the ascending, transverse, and descending colon, as well as the rectum, with differentiation statuses ranging from well to moderate and moderate-poor. Notably, for one patient, we generated organoids from both the primary tumor and matched liver metastases, allowing for a comparative analysis of tumor evolution. PDOs were derived from these tumors and subjected to WES at early passage to profile somatic mutations, copy number variations, and other genomic alterations to identify mutational signatures. Mutations identified in the PDOs were cross-referenced and confirmed with mutational data from the Columbia Solid Tumor Panel, which was conducted on all tumor tissues prior to organoid establishment. Molecular technologies employed include next-generation sequencing (NGS) for WES, enabling high-resolution characterization of the genomic landscape of CRC PDOs. WES of PDOs allowed us to classify tumor samples based on oncogenic mutations and mutation types, with a specific focus on PIK3CA. Notably, the efficacy of PI3Kα-specific pharmacologic inhibitors in suppressing organoid growth was dependent on the mutational status of KRAS and PIK3CA, underscoring the importance of genomic context in therapeutic response. The dataset available through dbGaP includes raw WES data from CRC PDOs.

Study phs003965

Field Studies of Human Immunity to Amebiasis in Bangladesh

Amebiasis is a common cause of diarrhea and is associated with malnutrition in grade-school aged children in an urban slum of Dhaka, Bangladesh. Field Studies of Human Immunity to Amebiasis in Bangladesh was designed to determine the contribution of amebiasis to illness in the first 2 years of life when most deaths due to diarrhea occur, and understand the immunologic and genetic factors that protect children from amebiasis. The hypothesis underlying the study is that susceptibility to amebiasis is determined by host innate and acquired immune responses that vary between individuals in part due to: human genetic polymorphisms; environmental influences including malnutrition and concurrent geohelminth infection; and virulence differences among Entamoeba histolytica genotypes. Specific aims proposed in the design of the study were to: a) Measure the incidence of amebiasis and correlate it with human and parasite genetic polymorphisms, immune responses, and environmental factors such as geohelminth infection and malnutrition; b) Test the hypothesis that protective immunity is mediated both by innate immune responses initiated via TLR stimulation as well as by mucosal IgA against the Gal/GalNAc lectin and systemic IFN-γ; c) Test for the association of common genetic polymorphisms in host innate and acquired immune genes with incidence of amebiasis. 629 newborn babies were enrolled and followed regularly through bi-weekly surveillance for diarrheal episodes, anthropometry at 3-month interval until 60 months of age. The infants that were consented for GWAS analysis were genotyped in 3 separate batches at different times, on 3 different arrays. Quality control was performed on the 3 separate data sets and then jointly after merging. Genetic data available on 447 infants together with their phenotype data is made available in this submission.

Study phs001476

Mortality and risk of progression to adult T-cell leukemia/lymphoma in patients with HTLV-1-associated myelopathy/tropical spastic paraparesis

Human T-cell leukemia virus (HTLV)-1 causes the functionally debilitating disease HTLV-1-associated myelopathy/ tropical spastic paraparesis (HAM/TSP) as well as adult T-cell leukemia lymphoma (ATLL). Although there were concerns that the mortality of HAM/TSP could be affected by the development of ATLL, prospective evidence was lacking in this area. In this 5-year prospective cohort study, we determined the mortality, prevalence, and incidence of ATLL in 527 HAM/TSP patients. The standard mortality ratio of HAM/TSP patients was 2.25, and ATLL was one of the major causes of death (5/33 deaths). ATLL prevalence and incidence in these patients were 3.0% and 3.81 per 1,000 person-years, respectively. To identify patients at a high risk of developing ATLL, flow cytometry, Southern blotting, and targeted sequencing data were analyzed in a separate cohort of 218 HAM/TSP patients. In 17% of the HAM/TSP patients, we identified an increase in T-cells positive for cell adhesion molecule 1 (CADM1), a marker for ATLL and HTLV-1 infected cells. Genomic analysis of these patients revealed that somatic mutations of HTLV-1 infected cells were seen in 90% of the cases and 11% of them had dominant clone and developed ATLL in the longitudinal observation. In this study, we were able to demonstrate for the first time that the increased mortality in patients with HAM/TSP and a significant effect of ATLL on their prognosis. Having dominant clonal expansion of HTLV-1- infected cells with ATLL-associated somatic mutations may be important characteristics of patients with HAM/TSP who are at an increased risk of developing ATLL.

Study JGAS000226

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