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• Molecular defects in pseudohypoparathyroidism or related disorders

  Maintaining calcium levels within a narrow normal range is of critical importance for numerous different cellular functions. One of the most important regulators of blood calcium levels is parathyroid hormone (PTH), which mediates its actions through the PTH/PTHrP receptor, a Gαs-coupled receptor. Few inherited disorders are characterized by diminished blood calcium levels and elevated blood phosphate levels; some of these disorders are caused by too little PTH synthesis and/or secretion (hypoparathyroidism, HP), while others are caused by resistance towards PTH (pseudohypoparathyroidism, PHP). Only few of the inherited forms of HP (<10%) have been defined at the molecular level. In contrast, genetic mutations have been identified for several inherited forms of PHP. For example, PHP type Ia (PHP-Ia) is caused by maternally inherited mutations in those GNAS exons that encode Gαs, while autosomal dominant PHP type Ib (AD-PHP-Ib) is caused by maternal inherited deletions within or up-stream of GNAS, which are associated with abnormal GNAS methylation. However, a large number of patients with PTH-resistance and thus hypocalcemia show GNAS methylation changes, but their underlying genetic defects have not yet been defined at the DNA level. These "sporadic" patients may be affected by an autosomal recessive form of PHP-Ib (AR-PHP-Ib), which is most likely not linked to the GNAS locus. In our studies, we propose to search through exome sequence analyses for novel genetic mutations responsible for novel autosomal dominant forms of HP that are not caused by mutations in the known disease-causing genes; some of these families are large enough to perform genetic linkage studies. We furthermore propose to search for the genetic mutation(s) responsible for the autosomal recessive variant of PHP-Ib through the analysis of whole exome sequences; for these studies we focus particularly on patients, whose parents are likely to be consanguineous. The proposed efforts are expected to lead to the identification of novel genes that are involved in parathyroid development and function (HP) and genes that are involved in the establishment or maintenance of GNAS methylation (AR-PHP-Ib).

  Study phs000476

• Center for Common Disease Genomics [CCDG] - Cardiovascular: TexGen

  Cardiovascular disease (CVD), especially coronary heart disease, heart failure and cerebrovascular disease remain the leading causes of death in men and women across all race groups in the United States. Substantial evidence exists for genetic factors underlying CVD risk, and their discovery offers an opportunity to enhance understanding of disease mechanisms, to provide specific diagnostic and prognostic indicators, and to identify novel therapeutic targets. The Centers for Common Disease Genomics (CCDG) are a large-scale genome sequencing effort undertaken as a collaboration to identify rare risk and protective alleles for common chronic diseases, with a current focus on early onset heart disease, hemorrhagic stroke, and autism. In this study, whole genome sequencing (WGS) was performed in 6,146 individuals with any personal or family history of CVD from the TexGen study who were recruited from several institutions in the Texas Medical Center located in Houston, Texas. The participants included patients who were admitted with a variety of diagnoses including acute coronary syndromes, strokes, and transient ischemic attacks, or who underwent percutaneous coronary interventions or coronary artery bypass grafting (CABG) (Virani SS et al. Am J Cardiology 107:1504-1509, 2011). Patients in the TexGen cohort with a confirmed diagnosis of acute coronary syndrome (ACS) or CABG when discharged from the hospital between 2001-2008 were eligible for a follow-up study of recurrent myocardial infarction (Virani SS et al. Circulation J 76:950-956, 2012), while those presenting with ACS beginning in 2007 were recruited for an investigation of the role of depressive symptoms in the risk of major adverse coronary events (Sanner J et al. Biol Res Nurs 20:168-176, 2018). In addition, the initial criterion for enrollment in a third TexGen sub-study undertaken between 2007 and 2013 was the occurrence of premature acute myocardial infarction in men ≤ 50 years and women ≤ 55 years in order to establish a blood sample collection resource with the intention of localizing genes that contribute to disease risk. This definition was later expanded to include individuals with a clinical history of premature coronary heart disease such as CABG or percutaneous coronary interventions.

  Study phs003010

• NHLBI GO-ESP: Early-Onset Myocardial Infarction (Broad EOMI)

  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. In the Grand Opportunities Exome Sequencing Program Early MI Project (GO ESP - EOMI), we are sequencing cases with extremely early-onset MI drawn from 8 cohorts. These cohorts include five hospital or community-based studies that ascertained individuals based on MI status. These include PennCATH, Cleveland Clinic Genebank, Massachusetts General Hospital Premature Coronary Artery Disease Study (MGH-PCAD), Heart Attack Risk in Puget Sound (HARPS), and Translational Research Investigating Underlying Disparities in Myocardial Infarction Patients' Health Status (TRIUMPH). Cases were selected based on MI occurring in men aged ≤50 years and women aged ≤60 years. In addition, early-MI cases are being drawn from three population-cohort studies including the Framingham Heart Study, the Women's Health Initiative, and the Atherosclerosis Risk in Communities Study. MI-free controls are being drawn from five population-based cohort studies including the Framingham Heart Study, the Women's Health Initiative, Atherosclerosis Risk in Communities Study, Cardiovascular Health Study, and the Jackson Heart Study. Controls were selected based on two factors: (1) highest predicted risk for MI based on Framingham risk score; and (2) absence of prevalent or incident MI despite a high predicted risk.

  Study phs000279

• NIDDK IBD Genetics Consortium Crohn's Disease Genome-Wide Association Study

  This dataset contains data from a genome-wide association study performed with 968 Inflammatory Bowel Disease (IBD) affected cases and 995 unrelated controls using the Illumina HumanHap300 Genotyping BeadChip. Cases were selected to have Crohn's disease with ileal involvement, and controls were matched to cases based on sex and year of birth. Subjects were drawn from two cohorts: (1) persons with non-Jewish, European ancestry (561 cases and 563 controls), and (2) persons with Jewish ancestry (407 cases and 432 controls). Genotyping was performed at the Feinstein Institute for Medical Research. Seven-hundred fifty-four of the samples (468 cases and 286 controls) were taken from the NIDDK IBD Genetics Consortium cell line repository. These samples are identified in the IBD_Sample file. The subject IDs for these individuals may be used to request corresponding samples for follow-up research through the repository. In addition, complete phenotype data for these individuals are available, together with the Consortium's phenotyping manual and the forms used to collect the data. The remaining 1,209 samples were obtained from pre-existing collections ascertained through Cedars-Sinai Medical Center, Johns Hopkins University, University of Chicago, University of Montreal, University of Pittsburgh, University of Toronto, and the New York Health project (controls only). For these samples, only sex, cohort (Jewish vs. non-Jewish), and age at diagnosis (cases only) are available. Two-hundred three individuals from among the pre-existing samples did not provide consent to release their genotype data (designated as consent group 2 in the file IBD_Subject). Thus, individual genotype data are only provided for 1,760 samples. To compensate for this, we have provided summary results for each SNP. These are based on a stratified analysis testing case/control association. Fifty-one samples had a call rate less than 93% and were therefore excluded from this analysis, leaving an overall sample size of 1,963 - 51 = 1,912. X Chromosome Heterozygosity Nine samples have X chromosome heterozygosity that is neither consistent nor inconsistent with their phenotypic sex. One of these samples was found to have Turner Syndrome. The remaining 8 samples have heterozygosity ranging from 35-76%.

  Study phs000130

• DNA-Sequencing of Baseline Plasma From the Phase III Alliance A031201 Trial

  Liquid biopsy assays tailored for metastatic castration-resistant prostate cancer (mCRPC) patients are needed to identify molecular alterations and predict survival in the context of androgen receptor (AR) inhibitors. We developed a novel plasma cell-free DNA (cfDNA) sequencing assay to detect circulating tumor DNA (ctDNA) and alterations in key mCRPC driver genes, and tested associations with clinical features and survival outcomes in a phase III trial. cfDNA was isolated from evaluable baseline plasma specimens of untreated mCRPC patients (n=790) enrolled in the Alliance A031201 randomized phase III trial (NCT01949337) prior to enzalutamide therapy with or without abiraterone acetate and prednisone. A customized targeted cfDNA sequencing assay was used to detect AR and non-AR alterations in mCRPC. For this, DNA-seq libraries were constructed from cfDNA using Takara ThruPLEX Tag-Seq or Plasma-Seq kits, and subjected to hybridization enrichment using a custom-designed Agilent SureSelect bait panel. Post-capture DNA-seq libraries were pooled and sequenced on an Illumina HiSeq 2500 using 2x150 bp settings. ctDNA positivity was defined as >20% ctDNA using an aneuploidy-based estimate derived from ichorCNA (Group 1) or a novel definition of ≤20% ctDNA, but with detection of any alteration in AR, or gain of MYC and/or MYCN (Group 2). cfDNA sequencing data was obtained from 776 patients. There were 480/776 (62%) ctDNA-positive patients, with 324 (42%) in Group 1 and an additional 156 (20%) in Group 2 with AR or MYC/MYCN alterations detected. ctDNA-positive patients in Groups 1 and 2 had similarly poor median overall survival (OS) of 25.4 months (95% CI: 21.8-29.0) and 29.7 months (95% CI: 27.3-35.5), respectively, as compared to ctDNA-negative patients who had a median OS of 49.1 months (95% CI: 42.3-53.5). Relative to ctDNA-negative patients, OS was inferior in ctDNA-positive patients in Group 1 (HR 2.3, 95% CI: 1.9-2.9, P AR inhibitors in a contemporary phase III trial.

  Study phs003325

• Diabetic Retinopathy Genomics Study (DRGen) - Genetic Biomarkers of Diabetic Retinopathy

  Using a well-defined, clinically supported phenotypic strategy, we seek to better understand the role of common and rare genetic variants in the progression of diabetic retinopathy (DR). Whole exome/whole genome sequencing (WES/WGS) was used to systematically search the human genome to detect DR susceptibility genes or genes that protect people from developing advanced DR. Clinical data and bio specimens were obtained from clinically defined DR phenotypes such as, (i) No/Mild NPDR (non-proliferative DR) with a subset of extreme phenotype, ii) Diabetic macular edema (DME) alone and iii) Proliferative diabetic retinopathy (PDR) alone. In this ongoing comprehensive genomic study, we wish to i) Identify potential common and rare variants that may influence the phenotypic differentiation of DR into DME or PDR, ii) Define genetic variants stratified based on the "extreme phenotype," and iii) Characterize genetic factors that determine the differential response to anti-VEGF drugs in DME patients. Definition of Diabetic Retinopathy and classification of groups Study 1. Proliferative diabetic retinopathy (PDR). Anybody showing evidence of retinal neovascularization on the disc (NVD) or elsewhere (NVE) with or without pre-retinal and vitreous hemorrhage will be considered PDR. We will include only those "active" PDR patients. The total number of consented subjects in this study is 182. Study 2. Isolated Phenotype: Varied response with anti-VEGF treatment is a significant limiting factor for better clinical outcomes. We quantify the response to anti-VEGF treatment based on visual acuity changes and anatomic features of DME assessed by optical coherence tomography (OCT). Depending on the response at one month following three monthly intravitreal anti-VEGF injections, we have observed two phenotypes: 1) Good responders: Participants were considered "good responders" if the anatomical outcome to anti-VEGF treatment resulted in a significant reduction of baseline central retinal thickness (CRT) > 25% after three anti-VEGF injections. 2) Poor Responders: Participants were classified as "poor responders" if the outcome of anti-VEGF treatment resulted in a reduction of CRT < 20% or in any increase in CRT after three monthly injections. The total number of consented subjects in this study is 17.

  Study phs002501

• Gabriella Miller Kids First Pediatric Research Program in Pediatric T-Cell Acute Lymphoblastic Leukemia

  The outcome for patients with relapsed T-ALL is dismal with 3-year event free survival of AALL0434 was a Children's Oncology Group-initiated phase 3 randomized clinical trial comparing Capizzi-style escalating methotrexate plus pegaspargase (CMTX) vs. high dose methotrexate (HDMTX), with/without six 5-day courses of nelarabine. Survival on this study was superior to any prior trial for de novo T-ALL, changing the standard of care. Yet, a substantial minority (~15%) of patients had relapsed or refractory (r/r) disease. Through the TARGET initiative, RNA sequencing (RNA-Seq), DNA copy number analysis, and whole-exome sequencing (WES) were performed on 264 T-ALL patients treated on AALL0434, demonstrating recurrent alterations could be grouped into 10 different potentially targetable functional pathways. This analysis was not powered to examine associations between genetic lesions with outcome, because too few patients with r/r disease were included. This project is dedicated to testing the hypothesis that comprehensive genomic profiling of the entire AALL0434 cohort will identify recurrent genetic alterations that can be segregated into biologically relevant deregulated pathways that can be combined with MRD to identify patients at risk for poor outcomes before they relapse and provide rationale for treatment with alternative therapies. In addition, a number of small recent studies demonstrated that many of the biologically relevant alterations in T-ALL occur in non-coding regions of the genome, but no large studies have performed whole genome sequencing (WGS) in T-ALL. This project also tests the hypothesis that WGS of a large cohort of patients with T-ALL will identify novel lesions in coding and non-coding regions that will be highly impactful in the understanding of T-ALL pathogenesis.These hypotheses are tested by performing comprehensive genomic profiling (WGS, WES, RNA-Seq, and copy number analysis) of the entire AALL0434 cohort with available samples with the following specific aims: (1) identify recurrent genetic alterations that predict poor outcome in T-ALL; (2) identify novel alterations, including non-coding alterations in T-ALL; and (3) identify germline genetic variants that predispose to T-ALL and to increased toxicity to chemotherapy.

  Study phs002276

• UK10K NEURO GURLING

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. This sample set consists of DNA from multiply affected schizophrenia families. The families have been diagnosed using the SADS-L clinical instrument which gives diagnoses at the probable level of the research diagnostic criteria (RDC). In addition all diagnoses are available using DSMIIIR criteria. These criteria are widely accepted as being valid and reliable for the diagnosis of schizophrenia. All families have been collected to ensure that they are uni-lineal for transmission of schizophrenia, i.e. they have only one affected parent with schizophrenia, or a relative of only one transmitting or obligate carrier parent with schizophrenia. Families with bi-lineal transmission of schizophrenia (i.e. with both parents being affected) were not sampled for this study. All families have multiple cases of schizophrenia and related disorders. The families have been selected to ensure there are no cases of bipolar disorder within them and that they do not contain bipolar disorder in any relatives on either side of the family.For further information on this cohort please contact Hugh Gurling (h.gurling@ucl.ac.uk).

  Study EGAS00001000225

• Gene expression-based prediction of pazopanib efficacy in sarcoma (HIPO, H021)

  The multi-receptor tyrosine kinase (RTK) inhibitor pazopanib is approved for the treatment of advanced non-adipocytic soft-tissue sarcoma and has also shown activity in other sarcoma subtypes. However, its clinical efficacy is highly variable, and no reliable predictors exist to date to select patients who are most likely to benefit from this drug. We analyzed the molecular profiles and clinical outcomes of pazopanib-treated sarcoma patients enrolled in a prospective observational study by the German Cancer Consortium, DKTK MASTER, that employs whole-genome/exome sequencing (WGS/WES) and transcriptome sequencing to inform the care of adults with advanced cancer across histologies who are younger than 51 and patients with rare tumors, including rare subtypes of more common entities, regardless of age.​ Among a total of 109 patients with available WGS/WES data, there was no correlation between clinical parameters, specific genetic alterations, or mutational signatures and clinical outcome. In contrast, analysis of a subcohort of 62 patients who underwent molecular analysis before pazopanib treatment and had transcriptome sequencing data available showed that mRNA levels of NTRK3 (hazard ratio [HR]=0.53, p=0.021), IGF1R (HR=1.82, p=0.027), and KDR (HR=0.50, p=0.011) were independently associated with progression-free survival (PFS). Based on the expression of these RTK genes, i.e., the features NTRK3-high, IGF1R-low, and KDR-high, we developed a pazopanib efficacy predictor (PEP) that stratified patients into three groups with significantly different PFS (p<0.0001). Application of the PEP to an independent cohort of pazopanib-treated sarcoma patients from DKTK MASTER (n=43) confirmed its potential to separate patient groups with significantly different PFS (p=0.02), whereas no such association was observed in sarcoma patients from DKTK MASTER (n=77) or The Cancer Genome Atlas sarcoma cohort (n=256) who were not treated with pazopanib. A score based on the combined expression of NTRK3, IGF1R, and KDR allows identification of sarcoma patients with good, intermediate, and poor outcome following pazopanib therapy and warrants investigation as a predictive tool in prospective studies to optimize the use of this drug in the clinic.

  Study EGAS00001005836

• EGA metadata schema

  EGA Schemas In this page, you will find information on how the European Genome-phenome Archive (EGA) manages its metadata standards using both XML Schema Definition (XSD) and JavaScript Object Notation (JSON) formats. If you are not sure what this means, you may want to explore our brief metadata introduction. This information may be of your interest if you are planning to learn more about how the EGA is built and how to wrap around it for other processes. Nevertheless, if you are a common user (e.g. submitter or requester), you would not have to worry about these schemas nor their format, since they are implemented in user-friendly ways for you. Metadata standards are rules that define how to format and structure data of metadata objects (i.e. entities), like EGA's samples or experiments in a consistent manner. These objects are the nodes of the metadata model of the EGA (Figure 1). Figure 1. Diagram of EGA's metadata model. The model's building blocks are objects (e.g. sample), which can reference each other (e.g. an experiment referencing the used samples). Once your files are uploaded, they can also be referenced by Runs and Analyses. The submission object is an object itself that compiles many others. At EGA, we inherit our metadata schemas from the European Nucleotide Archive (ENA), and we have expanded them to include bespoke objects such as "Policy", "Dataset", and "DAC" (Data Access Committee) for our specific use-case: handling sensitive human data. See below a list of all our metadata objects and some context for each. Metadata Object EGA accession Description Examples of metadata fields Study EGAS… Information about the study Study type, study title, study abstract… Sample EGAN… Information about the used samples in the experiment or analysis Taxon ID, scientific name, biological sex, phenotype… Experiment EGAX… Information about the performed experiment Used libraries, sequencing platform, reference to the used samples… Analysis EGAZ… Contains information about the analysis Type of analysis, used assembly, reference sequence… Run EGAR… The run holds information about the files containing the raw reads generated in a run of sequencing Platform, spot descriptor, raw file references… DAC EGAC… Contains information about the Data Access Committee (DAC) DAC contacts, contact emails… Policy EGAP… Contains the Data Access Agreement (DAA) and policy which its usage complies with Policy text, data use ontologies (DUO) codes… Dataset EGAD… Contains the collection of runs/analysis to be subject to controlled access Dataset type, compilation of Run's and Analysis' IDs There are two different sets of schemas, based on their formats, in which the EGA accepts metadata: XSDs (for XML files) and JSON Schemas (for JSON files). EGA's XML Schema Definition . When programmatic submissions are pushed through the European Bioinformatics Institute (EBI) system, XML format is used. The schemas that are applied for this format are defined in XML Schema Definition (XSD) files, which can be found at ENA's GitHub repository. You can find more information on how to validate and submit your data programmatically in our programmatic submission documentation. Furthermore, see at our GitHub repository some XML examples with either made-up values (similar to what you would submit) or descriptive values for each field (just for documentation). EGA's JSON Metadata Schemas . When programmatic submissions are pushed through the Centre for Genomic Regulation (CRG) system, JSON format specifications are used instead. See the full JSON specifications for further details. In conclusion, the EGA metadata schemas are crucial for maintaining the quality and consistency of submitted data. By understanding and following the rules outlined in these schemas, you can ensure that your submissions comply with the EGA's standards and contribute to a valuable and accessible genomic resource. Sample checklists Besides the standards in our schemas, we have another layer called Sample checklists. These are another system that the EGA inherits from ENA, and specifies what attributes are required or allowed for a sample object. The EGA uses these checklists to enforce that, for example, a sample object has the three mandatory attributes: subject ID, sex and phenotype of the individual the sample was taken from. When you submit to EGA, our checklist is automatically selected by default.

  Documentation submission/metadata/ega-schema