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• Alcohol Dependence GWAS in European- and African Americans

  This study includes SSADDA (Semi Structured Assessment for Drug Dependence and Alcoholism) assessed subjects (mostly unrelated, but including some affected sibling pairs) recruited in the course of several substance dependence genetics projects. The sample includes 1889 African-American (AA) subjects and 1020 European-American (EA) subjects. Among the AAs, 1397 meet DSM-IV criteria for alcohol dependence and 491 are controls. Among the EAs, 1010 meet the criteria for alcohol dependence and 9 are controls. (One in each population meets criteria for alcohol abuse and not dependence, and is therefore counted in neither category.) Although alcohol dependence is the major focus, the sample is informative also for cocaine, nicotine, and opioid dependence.

  Study phs000425

• Coenzyme Q10 (CoQ) in Huntington's Disease (HD) (2CARE)

  This is a multi-center, randomized, double-blind, placebo-controlled trial of CoQ involving 609 ambulatory subjects with HD who are not requiring skilled care or institutionalization. Eligible subjects were randomized to receive either CoQ 2400 mg/day or matching placebo. Subjects were followed prospectively and systematically for 60 months of double-blind observation. The primary outcome variable is a combination of time to death (for subjects who die) and the change from baseline to Month 60 in Total Functional Capacity (TFC) score (for subjects who survive). The primary hypothesis of the study is that chronic treatment of early-stage HD subjects with high-dosage CoQ will slow the progressive functional decline of HD.

  Study phs001065

• Genetics of diffuse large B-cell lymphoma in Japan

  Diffuse large B-cell lymphoma (DLBCL) is a common hematological malignancy. Treatment with standard chemotherapy results in long-term remission in approximately 60% of patients. Whole-exome sequencing studies of large DLBCL cohorts revealed the biological diversity of tumors and facilitated the identification of genetic subtypes based on genetic alterations. Despite the progress facilitated by NGS, genetic classification is difficult to apply in clinical practice because of the complexity of the clustering algorithm. Furthermore, only a few reports included large Asian cohorts. Thus, a genetic overview of Japanese patients with DLBCL is still needed. Thus, in this study, we aimed to establish the clinical application of our simplified genetic classification algorithm in Japanese DLBCL.

  Study JGAS000307

• Star2xml: metadata converter into XML

  Star2xml: metadata converter into XML Welcome to the landing page for star2xml - a tool developed by the European Genome-phenome Archive (EGA) that enables users to convert metadata into XML format that is compliant with EGA's programmatic submission system. For starters, if you are not sure what metadata is in this context, you may want to explore our brief metadata introduction. . Star2xml is useful for users who have already submitted their data to the EGA and want to also submit their metadata programmatically without having to create the XML files manually. The need for these XMLs containing metadata is explained in the EGA's metadata schemas and programmatic submission guidelines. In summary, star2xml allows for users to deposit metadata in a tabular format (e.g. excel spreadsheet) and transform it into a compliant XML format. This saves time in large submissions, where the sheer size of metadata makes it difficult to manage. For smaller submissions, it is recommended to use EGA's Submitter Portal (SP) instead. The installation of the tool is straightforward, and it contains detailed documentation on how to use it in its GitHub repository . While star2xml can help users convert metadata formats, it does not validate the resulting metadata against EGA's schemas. Therefore, after creating your XMLs, you should still validate your metadata before submitting it to EGA, as described in the documentation for programmatic metadata validation.

  Documentation tools/star2xml

• EGA submission account terms

  Submission account terms Each EGA submission account has a dedicated submission box. To ensure continued service to all submitters EGA submission boxes should not exceed 8Tb in size, and cannot exceed 12Tb. Those that are near to or exceeding this value will be monitored on a weekly basis by the helpdesk team and the submitter will be contacted and guidance provided accordingly on completing their metadata registration. You will be able to register your metadata associated with the files in your submission account via EGA Submitter Portal, Webin or the EGA REST API. EGA also requests that metadata is submitted within 60 days of upload data to a submission box. When we detect files that are over 60 days old in a submission box we will notify the submitter requesting that metadata be submitted or the files removed from the submission box. It is important to note that data is not archived at the EGA until the metadata describing the files has been associated and the archival process has completed. It is only when associated metadata has been submitted that the archival process into EGA is fully triggered. EGA removes files from the submission box once they have been successfully archived, so no action is required by a submitter to remove successfully archived files. Files over 90 days old will be deleted from the submission box unless EGA Helpdesk has been contacted and confirmed an exemption with the submitter.

  Documentation submission/terms

• ICGC Oesophageal adenocarcinoma - pilot samples

  The oesophageal project will focus on adenocarcinoma which is increasing in incidence in the UK and other developed countries and has a very poor outcome. The primary aims of this project are to deeply sequence tumour and normal genomic DNA (including the precursor condition Barrett's oesophagus when material is available) to provide a comprehensive catalogue of somatic mutations. This will be achieved through a UK-wide network of hospitals involved in a research collaboration called the OCCAMS consortium. The goal of this project is to use high quality clinical material with accurately annotated clinic-pathological, treatment and outcome data.

  Study EGAS00001000559

• ESGI_Identification_of_novel_genes_and_mechanisms_leading_to_Primary_Ciliary_Dyskinesia

  Approximately 80% of clinically clearly diagnosed patients suffering from primary ciliary dyskinesia (PCD) cannot be assigned to a specific gene defect. Despite extensive research on PCD and despite the increasing number of PCD genes and knowledge about their sites of action as e.g structural component or cytoplasmic pre-assembly factor, the biology of motile cilia and the pathomechanism leading to PCD is largely unknown. The aim of this study is to identify novel PCD related genes and processes relevant for motile cilia function.We will perform exome sequencing, aiming on the analysis of family trios. In these families, the diagnosis of PCD is secured, but the underlying gene defects has so far not been identified.

  Study EGAS00001000523

• ICGC Oesophageal adenocarcinoma - Barrett's samples

  The oesophageal project will focus on adenocarcinoma which is increasing in incidence in the UK and other developed countries and has a very poor outcome. The primary aims of this project are to deeply sequence tumour and normal genomic DNA (including the precursor condition Barrett’s oesophagus when material is available) to provide a comprehensive catalogue of somatic mutations. This will be achieved through a UK-wide network of hospitals involved in a research collaboration called the OCCAMS consortium. The goal of this project is to use high quality clinical material with accurately annotated clinic-pathological, treatment and outcome data.

  Study EGAS00001000726

• Deregulation of DUX4 and ERG in acute lymphoblastic leukemia

  Chromosomal rearrangements deregulating hematopoietic transcription factors are common leukemia-initiating lesions in acute lymphoblastic leukemia (ALL). Here, we show that deregulation of the homeobox transcription factor gene DUX4 and the ETS transcription factor gene ERG are hallmarks of a subtype of B-progenitor ALL with a distinct gene expression profile that comprises up to 7% of B-ALL. DUX4 rearrangement and overexpression is present in all cases, and is accompanied by profound transcriptional deregulation of ERG, frequent ERG deletion and expression of a truncated ERG isoform, ERGalt. ERGalt utilizes a non-canonical first exon that is bound by DUX4 and induces its expression....

  Study EGAS00001001923

• Whole exome sequencing of solid tumors which received PD-1 blockade therapy

  We performed whole exome sequencing of solid tumors which received PD-1 blockade therapy to evaluate tumor mutation burden.

  Study JGAS000244

• Genetic Causes of Growth Disorders

  Description of the disorder: A very common disorder presenting to pediatricians/pediatric endocrinologists is childhood growth failure. Sometimes the cause is evident, for example, growth hormone deficiency. In other children, the etiology remains unknown despite extensive evaluation, resulting in the unhelpful diagnosis of severe idiopathic short stature (SISS). These conditions are quite heterogeneous, including children with isolated growth failure and others who also have other abnormalities such as developmental delay or a constellation of congenital anomalies (syndromic short stature). Sometimes, the disorder appears to primarily affect the growth plate, which drives skeletal growth and thereby determines overall body proportions, whereas in other children, the disorder affects skeletal and non-skeletal tissues equally. Some cases of SISS have a polygenic inheritance while others appear to follow a Mendelian inheritance model, recessive, dominant or X-linked. Very recently, genome-wide analysis for copy number variants (CNVs) and whole-exome sequencing have begun to identify some of the molecular etiologies of these disorders.1 Identifying the molecular etiology of growth disorders has clinical and scientific value. Clinically, identifying a molecular cause prevents extensive further testing and may direct anticipatory care for associated medical problems. For example, we recently studied aggrecan (ACAN) gene mutations in families with autosomal dominant short stature and accelerated skeletal maturation. These mutations affect both growth plate cartilage, causing linear growth failure, and also articular cartilage, causing osteochondritis dissecans and early-onset osteoarthritis.1 Etiological classification of idiopathic growth failure allows more precise characterization of prognosis and response to treatment, which are currently highly imprecise because of the locus heterogeneity. In some cases, finding the genetic etiology points to a novel treatment approach that targets the specific molecular pathway involved. The proposed project is central to the main focus of our group, the Section on Growth and Development, NICHD. Our primary goal is to investigate cellular and molecular mechanisms governing childhood growth and to gain insight into the many human genetic disorders causing childhood growth failure. The proposed project is well suited for the intramural program because it takes advantage of Clinical Center expertise to phenotype subjects with SISS. Study subjects: We will study subjects with SISS and nuclear family members. SISS will be defined by height SDS < -2.5 for age without evident cause after routine evaluation including: growth hormone axis evaluation; thyroid function testing; celiac disease screening; urinalysis; CBC; chemistry; karyotype (girls, for Turner syndrome); and testing for single gene defects based on the clinical evaluation (for example, SHOX or Noonan-associated genes). Candidate families will include isolated growth disorders and growth disorders that are accompanied by congenital anomalies, developmental delay, or other syndromic short stature. Strong preference will be given to subjects with a severe phenotype and a pedigree that indicates a Mendelian inheritance. Multiple independent families with the same phenotype will have priority. The pool of applicants for recruitment is large, and we receive many inquiries by emails and phone consultations from pediatric endocrinologists for advice regarding diagnosis and management of unusual growth disorders, including familial disease. Often these families are seeking further evaluation and are willing to participate in a research study. From this pool, we will be selecting pedigrees with very favorable Mendelian characteristics, for example de novo dominant occurrences where two normal parents have a child with SISS, and the child grows up to be an adult who passes this phenotype on to multiple grandchildren in the next generation. Subjects and family members will be brought to the NIH Clinical Center (NIHCC) for outpatient evaluation. Participants will be evaluated by pediatric endocrinology fellows (as part of our training program) and by senior staff to establish the clinical findings and construct a pedigree. Subjects will receive additional biochemical and imaging studies at the Clinical Center to complete the phenotyping and assign affected status. The growth abnormality will be evaluated by assessing body proportions, relative organ size, and skeletal imaging as indicated. Associated clinical abnormalities beyond altered growth will be characterized with the help of other Clinical Center subspecialists. Subjects and family members will be evaluated by SNP microarray and whole-exome sequencing. We anticipate 4-5 persons for each of 16-20 families, for a total of 72-90 whole-exome sequences. Half of the families will be recruited and studied within the first year and half in the second year. We will use freshly collected peripheral blood as the DNA source for SNP array and NextGen Sequencing. Analytic approach: The candidate genes will be chosen based on 1) inheritance state consistency, 2) population frequency in the ESP and UDP databases, and 3) predictions of deleteriousness. We will use VarSifter and the B road Institute Integrated Genome Viewer to filter and visualize these data. The genetic model will be dependent on the family's pedigree. For a simple trio, we will explore variants using genetic models including autosomal recessive, de novo (dominant), compound heterozygous, deletion/point mutation recessive, and X-linked (male only). The candidate variants will be identified using Boolean logic sets in VarSifter following intramural NHGRI/UDP methods. We will also use SNP microarray data to identify copy number variations, complete/single copy deletions, duplications, non-paternity, consanguinity for homozygosity mapping, uniparental isodisomy, mosaicism, and segregation patterns (bed file generation for use in VarSifter filter work). After a list of candidate sequence variants has been generated, annotation will include using the Exome Variant Server, Polyphen-2, MutationTaster, Sift, and CADD predictions of deleteriousness. Biological laboratory data will be included to prioritize candidate variants. Our group has expertise in the molecular mechanisms regulating both skeletal growth2,3 and growth of other tissues4,5, which may be helpful in this phase of the analysis. The most promising candidate mutations will be confirmed by Sanger sequencing and studied functionally, in vitro and/or in vivo. For mutations that affect skeletal growth, we will use experimental systems related to growth plate cartilage. For in vitro studies, we have experience transfecting chondrocyte cell lines, such as ATDC5, and primary chondrocytes. We will determine whether the mutation alters protein and/or cell function. In vivo studies can be used to explore pathophysiology. We have recently successfully used a new approach, the CAS9/CRISPR system to knockout multiple loci in mice (unpublished), which can be used again in the future to create mouse models efficiently. 1J Clin Endocrinol Metab, 2014 (PMID: 24762113) 2J Mol Endocrinol, 2014 (PMID: 24740736) 3Hum Mol Genet, 2012 (PMID: 22914739) 4Proc Natl Acad Sci U S A, 2013 (PMID: 23530192) 5Endocr Rev, 2011 (PMID: 21441345)

  Study phs001617

• Fixed single-cell transcriptomic characterization of human radial glial diversity

  The human neocortex is created from diverse intermixed progenitors in the prenatal germinal zones. These progenitors have been difficult to characterize since progenitors - particularly radial glia (RG) - are rare, and are defined by a combination of intracellular markers, position and morphology. To circumvent these problems we developed a method called FRISCR (Fixed and Recovered Intact Single Cell RNA) for transcriptome profiling of individual fixed, stained and sorted cells. We developed and validated FRISCR on human embryonic stem cells. We then profiled primary human RG (96 - 132 days post conception) that constitute only 1% of the mid-gestation cortex. These RG could be classified into ventricular zone-enriched RG (vRG) that express ANXA1 and CRYAB, and outer subventricular zone-localized RG (oRG) that express HOPX. Our study identifies the first markers and molecular profiles of vRG and oRG cells, and provides an essential step for understanding molecular networks driving the lineage of human neocortical progenitors. Reprinted from Thomsen et. al. Nature Methods (2015), with permission from Nature Publishing. Human embryonic stem cell data may be obtained through NCBI's GEO database, using accession number GSE71858. Raw data from one human sample that was not consented to be released to dbGaP may be obtained directly from the authors of Thomsen et. al., 2015.

  Study phs001016

• OMRF SLEGEN GWAS Data from European-American Women with Lupus

  "Systemic lupus erythematosus (SLE) is a common systemic autoimmune disease with complex etiology but strong clustering in families (lambda(S) = approximately 30). We performed a genome-wide association scan using 317,501 SNPs in 720 women of European ancestry with SLE and in 2,337 controls, and we genotyped consistently associated SNPs in two additional independent sample sets totaling 1,846 affected women and 1,825 controls. Aside from the expected strong association between SLE and the HLA region on chromosome 6p21 and the previously confirmed non-HLA locus IRF5 on chromosome 7q32, we found evidence of association with replication (1.1 x 10-7 < P(overall) < 1.6 x 10-23; odds ratio = 0.82-1.62) in four regions: 16p11.2 (ITGAM), 11p15.5 (KIAA1542), 3p14.3 (PXK) and 1q25.1 (rs10798269). We also found evidence for association (P < 1 x 10-5) at FCGR2A, PTPN22 and STAT4, regions previously associated with SLE and other autoimmune diseases, as well as at > or =9 other loci (P < 2 x 10-7). Our results show that numerous genes, some with known immune-related functions, predispose to SLE." Reprinted from Nature Genetics, 2008 Feb; 40(2):204-10, PMID:18204446, with permission from Nature Publishing Group. Data submitted to dbGaP includes 297 samples from Oklahoma. (Please see also Study Accession: phs000216.v1.p1)

  Study phs000202

• Sequencing to Guide Cancer Care (CanSeq)

  The overall goal of the CanSeq U01 project is to study the impact of whole-exome sequencing (WES) on the clinical care of cancer patients and oncology provider practices. The aims of Project 1 are to implement and establish the feasibility of germline and somatic WES in patients with advanced solid tumors (lung and colon); to develop a framework for interpreting and reporting for exome sequencing data; to determine the proportion of patients with "actionable items" compared to existing technologies; and to report on the percentage of patients in whom unique WES findings led to a clinical action. The aims of Project 2 are to implement a production-scale platform for WES from archival (FFPE) material; to identify biologically relevant somatic and germline alterations existing in tumor/normal DNA from individual patients; to produce an evidence-based list of clinically "actionable" genetic alterations; and to develop inferential models that predict the utility of tumor genomic data within the larger clinical context. The goals of Project 3 are to describe the impact of information derived through WES on cancer patients; to test the hypothesis that patients will want to receive information about all potentially informative somatic and germline variants; to study patients' understanding of disclosed genomic information; and to describe the experiences of oncology providers as they implement WES into cancer care delivery.

  Study phs001075

• A Genome-Wide Association Study of Peripheral Arterial Disease

  The Electronic Medical Record Phenotypes and Community-engaged Genomic Association Study aims to identify genetic variants mediating susceptibility to peripheral arterial disease (PAD). The study leverages a biorepository of blood samples of 1688 PAD cases and 1649 controls, and the electronic medical record (EMR) to annotate the biorepository. PAD cases were identified from the vascular laboratory database as having an ankle brachial index (ABI) <0.9 at rest or after exercise or having non-compressible vessels. Controls were without prior history of atherosclerotic vascular disease and when tested, no evidence of ischemia on a stress test. Phenotypes and environmental exposures including age, ethnicity, demographic and anthropometric data are derived from the Mayo Electronic Medical Record (EMR). Comorbidities were determined using algorithms for diabetes and hypertension based on ICD-9 codes and medication use. Relevant laboratory data, including lipid levels, fasting blood sugar and serum creatinine at index date or within a 1-year window of the index date were extracted. Medication classes at index date were identified using Mayo's Natural Language Processing-based system with RxNorm codification and NDF-RT terminologies mapping. Smoking status was confirmed by natural language processing of clinical notes. Genotyping of ~600,000 SNPs across the genome is being conducted at the Broad Institute using the Illumina 660W platform. Statistical analyses will be conducted to identify genetic variants associated with susceptibility to PAD.

  Study phs000203

• Stressors and Health Study

  ObjectivesThe objectives of the Stressors and Health Study were to: (1) examine the prevalence of stressors and health outcomes and (2) assess differences in the associations between multi-level stressors and health outcomes, and (3) explore the protective and adaptive factors in the associations between multi-level stressors and health outcomes. Background Stressors have been posited to explain disparities in health. However, no surveys to our knowledge have simultaneously collected multiple stressors at various levels and the coping strategies used to deal with these stressors. Measuring these factors can provide a better understanding of the stressors experienced by specific groups and the impact that these experiences have on their health and health practices. In addition, exploring the various resilience and coping strategies employed to deal with stressors can help design appropriate interventions to reduce health disparities. Participants Participants included 1000 White, 1000 Black or African American, 1000 Latino or Hispanic, 1000 Asian, 500 American Indian or Alaska Native, 500 Native Hawaiian or Pacific Islander, and 500 mixed or multi-race adults (≥18 years) across the United States. Design The Stressors and Health Study is a cross-sectional online survey of adults across the US. A sampling frame (target population) of US residents based on the American Community Survey (ACS) was constructed using a rigorous two-step sampling matching approach to establish national representation.

  Study phs004019

• Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Coronary Artery Risk Development in Young Adults Study (CARDIA)

  Cohort Description The Coronary Artery Risk Development in Young Adults (CARDIA) study is a study examining the development and determinants of clinical and subclinical cardiovascular disease and their risk factors. It began in 1985-6 with a group of 5115 black and white men and women aged 18-30 years. The participants were selected so that there would be approximately the same number of people in subgroups of race, gender, education (high school or less and more than high school), and age (18-24 and 25-30 years) in each of 4 centers: Birmingham, AL; Chicago, IL; Minneapolis, MN; and Oakland, CA. These same participants were asked to participate in follow-up examinations during 1987-1988 (Year 2), 1990-1991 (Year 5), 1992-1993 (Year 7), 1995-1996 (Year 10), 2000-2001 (Year 15), 2005-2006 (Year 20), 2010-2011 (Year 25), 2015-2016 (Year 30), and 2021-2022 (Year 35). Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 2434 CARDIA participants in C4RWave 2 questionnaire data includes 448 variables for up to 1901 CARDIA participants in C4RDried Blood Spot/Serosurvey data includes 7 variables for up to 1332 CARDIA participants in C4RDerived data includes 43 variables for up to 2723 CARDIA participants in C4RPhenotype data includes 113 variables for up to 2723 CARDIA participants in C4R

  Study phs003045

• In vitro reconstitution of epigenetic reprogramming in the human germ line

  Epigenetic reprogramming resets parental epigenetic memories and differentiates primordial germ cells (PGCs) into mitotic pro-spermatogonia or oogonia, ensuring sexually dimorphic germ-cell development for totipotency. In vitro reconstitution of epigenetic reprogramming in humans remains a fundamental challenge. Here, we establish a robust strategy for inducing epigenetic reprogramming and differentiation of pluripotent stem cell (PSC)-derived human PGC-like cells (hPGCLCs) into mitotic pro-spermatogonia or oogonia, coupled with their extensive amplification (~>1010-fold). Strikingly, bone morphogenetic protein (BMP) signalling is a key driver of these processes: BMP-driven hPGCLC differentiation involves an attenuation of the mitogen-activated protein kinase/extracellular-regulated kinase (MAPK/ERK) pathway and both de novo and maintenance DNA methyltransferase (DNMT) activities, likely promoting replication-coupled, passive DNA demethylation. On the other hand, hPGCLCs deficient in tens-eleven translocation (TET) 1, an active DNA demethylase abundant in human germ cells, differentiate into extraembryonic cells, including amnion, with de-repression of key genes bearing bivalent promoters; these cells fail to fully activate genes vital for spermatogenesis and oogenesis, with their promoters remaining methylated. Our study elucidates the framework of epigenetic reprogramming in humans, making a fundamental advance in human biology, and through the generation of abundant mitotic pro-spermatogonia and oogonia-like cells, represents a milestone for human in vitro gametogenesis (IVG) research and its potential translation into reproductive medicine.

  Study JGAS000690

• A thymic ILC1-like progenitor with differentiation potential towards KIR+NKG2A- NK cells

  KIR+NKG2A- Natural Killer (NK) cells have the unique ability to detect downregulation of single HLA-I allotypes, frequently occurring in malignantly-transformed and virus-infected cells in order to escape T cell recognition. We have recently shown that circulating Innate Lymphoid Cells 1 (cILC1) have the potential to generate such KIR+NKG2A- NK cells but their developmental origin was unknown. Here we demonstrate that the development of cILC1 is thymus-dependent and identify a putative progenitor of cILC1s in the thymus, called thyILC1. Single-cell RNAseq analysis revealed a close relationship of thyILC1s to CD34+ double-negative (DN) thymocytes, but in contrast to DNs, thyILC1s had lost T cell differentiation potential. However, like cILC1s they could be efficiently differentiated into KIR+NKG2A- NK cells. thyILC1s strongly expressed RAG1/2, PTCRA (preTCR, and NOTCH1/3, but lacked expression of TCR chains, suggesting that they failed to pass the -selection checkpoint of thymocyte development. Finally, analyses of patients with FOXN1het deficiency, showing thymic hypoplasia due to lack of mature thymic epithelial cells, exhibited a profound deficiency of cILC1s but not cILC2s and cILC3s, demonstrating thymus dependency of cILC1s. Together, the data suggest that thyILC1s are the source of a novel thymus-dependent NK cell differentiation pathway that promotes generation of KIR+NKG2A- NK cells.

  Study EGAS50000000760

• A thymic ILC1-like progenitor with differentiation potential towards KIR+NKG2A- NK cells - sc

  KIR+NKG2A- Natural Killer (NK) cells have the unique ability to detect downregulation of single HLA-I allotypes, frequently occurring in malignantly-transformed and virus-infected cells in order to escape T cell recognition. We have recently shown that circulating Innate Lymphoid Cells 1 (cILC1) have the potential to generate such KIR+NKG2A- NK cells but their developmental origin was unknown. Here we demonstrate that the development of cILC1 is thymus-dependent and identify a putative progenitor of cILC1s in the thymus, called thyILC1. Single-cell RNAseq analysis revealed a close relationship of thyILC1s to CD34+ double-negative (DN) thymocytes, but in contrast to DNs, thyILC1s had lost T cell differentiation potential. However, like cILC1s they could be efficiently differentiated into KIR+NKG2A- NK cells. thyILC1s strongly expressed RAG1/2, PTCRA (preTCR, and NOTCH1/3, but lacked expression of TCR chains, suggesting that they failed to pass the -selection checkpoint of thymocyte development. Finally, analyses of patients with FOXN1het deficiency, showing thymic hypoplasia due to lack of mature thymic epithelial cells, exhibited a profound deficiency of cILC1s but not cILC2s and cILC3s, demonstrating thymus dependency of cILC1s. Together, the data suggest that thyILC1s are the source of a novel thymus-dependent NK cell differentiation pathway that promotes generation of KIR+NKG2A- NK cells.

  Study EGAS50000000790

• Transcriptional regulatory networks of tumor-associated macrophages that drive malignancy in mesenchymal glioblastoma

  Background: Glioblastoma (GBM) is a complex disease with extensive molecular and transcriptional heterogeneity. GBM can be subcategorized into four distinct subtypes; tumors that shift towards the mesenchymal phenotype upon recurrence are generally associated with treatment resistance, unfavorable prognosis, and the infiltration of pro-tumorigenic macrophages. Results: We explore the transcriptional regulatory networks of mesenchymal-associated tumor-associated macrophages (MA-TAMs), which drive the malignant phenotypic state of GBM, and identify macrophage receptor with collagenous structure (MARCO) as the most highly differentially expressed gene. MARCOhigh TAMs induce a phenotypic shift towards mesenchymal cellular state of glioma stem cells, promoting both invasive and proliferative activities, as well as therapeutic resistance to irradiation. MARCOhigh TAMs also significantly accelerate tumor engraftment and growth in vivo. Moreover, both MA-TAM master regulators and their target genes are significantly correlated with poor clinical outcomes, and are often associated with genomic aberrations in neurofibromin 1 (NF1) and phosphoinositide 3-kinases/mammalian target of rapamycin/Akt pathway (PI3K-mTOR-AKT)-related genes. We further demonstrate origination of MA-TAMs from peripheral blood, as well as their potential association with tumor-induced polarization states and immunosuppressive environments. Conclusions: Collectively, our study characterizes the global transcriptional profile of TAMs driving mesenchymal GBM pathogenesis, providing potential therapeutic targets for improving the effectiveness of GBM immunotherapy.

  Study EGAS00001002443

• Enrichment of oral-derived bacteria in inflamed colorectal tumors and distinct associations of Fusobacterium in the mesenchymal subtype

  The association between colorectal cancer (CRC) clinical variables and Fusobacterium, but not other intra-tumoral bacteria, has been extensively studied. Here we leveraged whole-transcriptome sequencing from 807 CRC tumor samples from the AVANT phase III trial to dually characterize tumor gene expression and intra-tumoral bacteria. After stringent filtering, 74 high-confidence taxa were identified. 17 of these species, including 4 Fusobacterium spp., were classified as orally-derived and had a robust signal within right-sided, MSI-H, and BRAF mutant tumors. Across consensus molecular subtypes (CMS), integration of Fusobacterium animalis presence and tumor gene expression revealed that F. animalis had the greatest number of associations in mesenchymal CMS4 tumors, despite an overall lower prevalence than in immune CMS1 tumors. Pathway analysis within CMS4 revealed that F. animalis, but not other highly prevalent species, was uniquely associated with pathways for collagen degradation and formation as well as IL-6 and IL-1 cytokine signaling. These associations could explain in part why Fusobacterium has been previously associated with reduced survival in mesenchymal populations. Overall, this study identified oral-derived bacteria, including Fusobacterium, as broadly more prevalent in inflamed CRC tumors compared to the other subtypes, and the association of intra-tumoral bacteria on tumor gene expression is context- and species-specific.

  Study EGAS00001006757

• Genetic insights into the biological mechanisms governing human ovarian ageing

  Reproductive longevity is critical for fertility and impacts healthy ageing in women, yet insights into the underlying biological mechanisms and treatments to preserve it are limited. Here, we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in ~200,000 women of European ancestry. These common alleles influence clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations. Identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increase fertility and extend reproductive life in mice. Causal inference analyses using the identified genetic variants indicates that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases risks of hormone-sensitive cancers. These findings provide insight into the mechanisms governing ovarian ageing, when they act across the life-course, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.

  Study EGAS00001004947

• Machine Learning Signal Enrichment for Ultrasensitive Plasma Tumor Burden Monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007451

• Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

  In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

  Study EGAS00001007545

• GoDARTS T2D-GENES Exome Sequencing Study is a subset of the ~52,000 Type 2 diabetes exome sequencing project.

  The GoDARTS T2D-GENES Exome sequencing study is a subset of a larger Type 2 Diabetes Exome Sequencing project. This effort is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date and includes samples from: T2D-GENES, GoT2D, ESP, SIGMA T2D, LuCAMP, and ProDIGY. This data generated from the Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) cohort was part of the T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for T2D through multiethnic sequencing studies. Sequencing for the GoDARTS study was performed at the Broad Institute using Illumina Rapid Capture on Illumina HiSeq machines.

  Study EGAS00001002937

• Virtual Growing Child 5-Dimensional Functional Models for Treating Respiratory Anomalies (dMRI-VGC)

  Objectives We are sharing a database of dynamic magnetic resonance imaging (dMRI) scans of normal children, which can serve as a reference standard to quantify regional respiratory abnormalities in young patients with various respiratory conditions and facilitate treatment planning and response assessment. The database can also be useful to advance future AI-based research on image-based object segmentation and analysis. Background In pediatric patients with respiratory abnormalities, it is important to understand the alterations in regional dynamics of the lungs and other thoracoabdominal components, which in turn requires a quantitative understanding of what is considered as normal in healthy children. Currently, such a normative database of regional respiratory structure and function in healthy children does not exist. Participants 200 normal children (ages 6-18 years) participated in our research study related to this dataset. DesignThe shared open-source normative database is from our ongoing virtual growing child (VGC) project, which includes 4D dMRI images representing one breathing cycle for each normal child and also segmentations of 10 objects at end expiration (EE) and end inspiration (EI) phases of the respiratory cycle in the 4D image. The lung volumes at EE and EI as well as the excursion volumes of chest wall and diaphragm from EE to EI, left and right sides separately, are also reported. The database has thus 4,000 3D segmentations from 200 normal children in total. The database is unique and provides dMRI images, object segmentations, and quantitative regional respiratory measurement parameters of volumes for normal children. All dMRI scans are acquired from normal children during free-breathing. The dMRI acquisition protocol was as follows: 3T MRI scanner (Verio, Siemens, Erlangen, Germany), true-FISP bright-blood sequence, TR=3.82 ms, TE=1.91 ms, voxel size ~1×1×6 mm3, 320×320 matrix, bandwidth 258 Hz, and flip angle 76o. With recent advances, for each sagittal location across the thorax and abdomen, we acquired 40 2D slices over several tidal breathing cycles at ~480 ms/slice. On average, 35 sagittal locations are imaged, yielding a total of ~1400 2D MRI slices, with a resulting total scan time of 11-13 minutes for any particular study participant.The collected dMRI scan data then went through the procedure of 4D image construction, image processing, object segmentation, and volumetric measurements from segmentations. 4D image construction: For the acquired dMRI scans, we utilized an automated 4D image construction approach to form one 4D image over one breathing cycle (consisting of typically 5-8 respiratory phases) from each acquired dMRI scan to represent the whole dynamic thoraco-abdominal body region. The algorithm selects 175-280 slices (35 sagittal locations × 5-8 respiratory phases) from the 1400 acquired slices in an optimal manner using an optical flux method. Image processing: Intensity standardization is performed on every time point/3D volume of the 4D image so that image values have the same tissue-specific meaning across all subjects. Object segmentation: For each subject, there are 10 objects segmented at both EE and EI time points in this database. They include the thoracoabdominal skin outer boundary, left and right lungs, liver, spleen, left and right kidneys, diaphragm, and left and right hemi-diaphragms. All dMRI scans utilize large field of view images, which include the full thorax and abdomen to the inferior aspect of the kidneys in the sagittal plane. We used a pretrained U-Net based deep learning network to first segment all objects, and then all auto-segmentation results were visually checked and manually refined as needed, under the supervision of a radiologist with over 25 years of expertise in MRI and thoracoabdominal radiology. Manual segmentations have been performed for all objects in all datasets. Volumetric measurements based on object segmentations for lung volumes (left and right separately) at EE and EI, as well as for chest wall and diaphragm excursion volumes (left and right separately) are reported. ConclusionsThe provided database is unique and provides dMRI images, object segmentations, and quantitative regional respiratory measurement parameters of volumes for normal children. The database has 4,000 3D segmentations from 200 normal children, which to our knowledge is the largest and only such dMRI dataset to date. All images and object segmentations are saved in DICOM. All DICOM files (176,574 in total) have been anonymized, and PHI has been removed. The database can be used as a reference standard to quantify regional respiratory abnormalities in young patients with various respiratory conditions and facilitate treatment planning and response assessment. The large amount of object segmentations can potentially benefit AI-based research on image-based object segmentation and analysis.

  Study phs004002

• COLO-829/COLO-829BL

  COLO-829 is a publicly available immortal cancer cell line and COLO-829BL is a lymphoblastoid cell line derived from the same patient

  Dataset EGAD00000000055

• UNC Tumor Donation Program Set 2021

  The goal of this study is to study gene expression patterns in primary, metastatic tumors, and normal tissues.

  Study phs002429

• Stage-1 GWAS

  Summary statistics from Stage-1 GWAS for blood pressure phenotypes

  Dataset EGAD00010001569

• lebanon-U-1

  Lebanon_Genotyping

  Dataset EGAD00010001870

• HumanCytoSNP12-2-1

  HumanCytoSNP-12 v2.1 on tissue DNA

  Dataset EGAD00010002091

• Center for Craniofacial and Dental Genetics: Study of Dental Caries and Cleft Lip/Palate in Guatemala

  This study provides an opportunity to investigate the genetics of both dental caries and orofacial clefts (OFCs) in one set of families ascertained in Guatemala. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org), which was developed through the trans-NIH Genes, Environment, and Health Initiative (GEI). Furthermore this study brings together multiple research priorities of the University of Pittsburgh Center for Craniofacial and Dental Genetics (www.ccdg.pitt.edu). A genome-wide panel of 610,000 SNPs was genotyped at the Broad Institute to be comparable to our other pertinent GENEVA studies that are also part of dbGaP (dbGaP accession number phs000095, "Dental Caries: Whole Genome Association and Gene x Environment Studies" and dbGaP accession number phs000094, "International Consortium to Identify Genes and Interactions Controlling Oral Clefts"). The goal of this study is to investigate genetic determinants to dental caries and to OFCs in a novel study population. To date, most genetic studies of dental caries have been conducted in Caucasians, and of OFCs in Caucasians and Asians. The Guatemalan population under study is rural and ethnically mixed with a high proportion of Native-South-Americans. Thirty-six Guatemalans from this dataset were also part of the recent GWAS studies of cleft lip and cleft palate (Beaty et al., 2010 and 2011, dbGaP Study Accession: phs000094, "International Consortium to Identify Genes and Interactions Controlling Oral Clefts"). In addition to the families ascertained in Guatemala, some subjects were genotyped with this cohort to augment the data in the parent GENEVA study (Dental Caries: Whole Genome Association and Gene x Environment Studies, dbGaP accession number phs000095), in particular individuals from the IOWA and PITT GENEVA study sites. Their data are available with the parent study. Dental caries (also known as tooth decay) remains the most common chronic disease of childhood, five times more common than asthma and seven times more common than environmental allergies, with more than 40% of children exhibiting caries when they enter kindergarten. In 2005, it was estimated that dental health care costs were approximately $84 billion, of which 60% or about $50 billion were related to treatment of dental caries. The etiology of dental caries has been studied for many years. Multiple factors contribute to a person's risk for caries, including: 1) environmental factors such as diet, oral hygiene, fluoride exposure and the level of colonization of cariogenic bacteria and 2) host factors such as salivary flow, salivary buffering capacity, position of teeth relative to each other, surface characteristics of tooth enamel and depth of occlusal fissures on posterior teeth. In spite of all that is known about this disease, there are still individuals who appear to be more susceptible to caries and those who are extremely resistant, regardless of the environmental risk factors to which they are exposed, implying that genetic factors also play an important role in caries etiology. This conclusion is supported by studies in both humans and animals, with the most compelling evidence coming from studies of twins reared apart in which investigators found significant resemblance within monozygotic (MZ) but not dizygotic (DZ) twin pairs for percentage of teeth and surfaces restored or carious and estimated the genetic contribution to caries as 40%. Other recent studies of twins reared together estimated the heritability for caries, adjusted for age and gender, as ranging from 45-64%. In our study populations of families, we also estimated caries heritability as approximately 54%-70% of variation in primary dentition caries scores and 35%-55% in the permanent dentition (Wang et al., 2010). Orofacial clefts (OFCs), particularly cleft lip with or without cleft palate (CL/P) and isolated cleft palate (CP) are a major public health problem, affecting one in every 500-1000 births worldwide thus representing the most common facial birth defect and one of the most common of all congenital anomalies. CL/P is a major structural birth defect that is notable for significant lifelong morbidity and complex etiology. The extensive psychological, surgical, speech and dental involvement emphasize the importance of understanding the underlying causes of CL/P. Therefore, many research groups have attempted to elucidate the etiology of CL/P, with some recent success by our research group and others (see Beaty et al., 2010, 2011; Dixon et al., 2011). It is clear that CL/P can occur as part of Mendelian syndromes, that certain chromosomal abnormalities include CL/P in the phenotype, and that certain teratogens can increase the risk of having an offspring with CL/P. However, phenotypes of known etiology comprise only a small portion of all individuals with a CL/P or CP, and the major focus of research into OFCs is to develop an understanding of the etiology of nonsyndromic (NS) forms of clefting. A major focus of the University of Pittsburgh CCDG has been to study additional phenotypes within nonsyndromic OFC families in order to identify sub-clinical expressions of OFC risk genes or risk variants, e.g. SNPs (see Weinberg et al., 2006). A detailed oral exam is conducted as part of these extended phenotypic studies, including a dental caries exam. Note that although there are some reports in the literature of higher caries experience in individuals with clefts, the most recent meta-analysis of those literature reports concluded that individuals born with these defects do not have a higher frequency of caries (Hasslöf and Twetman, 2007). Notably, we investigated the association of CL/P and caries in three of our study populations (including part of the Guatemalan population in this GWAS study) and also found no increase in caries rates of CL/P cases versus controls (Jindal et al., 2011). This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org), which was developed through the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to dental caries and oral clefts through large-scale genome-wide association studies of well-characterized Guatemalan families and individuals. Genotyping was performed at the Broad Institute of MIT and Harvard. The study was supported by the National Institute of Dental and Craniofacial Research (NIDCR, U01-DE018903). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000440

• Contextual and Health Behavior Effects on Epigenetic Aging Among Africans in the Family and Community Health Studies

  The Family and Community Health Studies (FACHS) is a longitudinal examination of health and health related behaviors in African American families. The original study cohort consisted of 867 African American parent-child dyads from Georgia and Iowa who were ascertained in cooperation with local school districts. The key inclusion criteria for participating in the study were the presence of an adolescent in the 5th grade (approximately 10-11 years old) who self-identified as African American (i.e., the Target) and the participation of a primary caretaker (PC) for the Target. The clinical and biological data included in this collection are from the Target (i.e., FACHS-T) portion of these studies of these African American parent-child dyads. The initial wave of behavioral assessments of the FACHS-T subjects was conducted in 1997-98 (Wave 1), with seven subsequent ascertainments, Wave 2 (1999–2000), Wave 3 (2002–2003), Wave 4 (2005–2006), Wave 5 (2007–2009), Wave 6 (2010–2011), Wave 7 (2014–2016) and Wave 8 (2019-2021). Full interviews were obtained at each wave of the study with the exact content of the wave varying as a function of developmental age. These interviews of the FACHS-T subjects collected a wide variety of data including the following: perceived discrimination; socioeconomic status; substance use exposure; common internalizing and externalizing disorders such as depression, substance use, and conduct disorder; school efficacy; peer support and perceived parenting practices. Biological sampling of the FACHS-T subjects was conducted at three time points. Saliva DNA was collected at Wave 5 while full phlebotomy was conducted at Waves 7 and 8. The genome wide methylation data listed below is derived from the whole blood DNA samples collected at Wave 8 and Wave 9. The genome wide genotyping data was determined using DNA from the Wave 7 samples. The clinical and biological data available herein are those from 309 FACHS-T subjects who participated in both Wave 7 and Wave 8, and who consented for deposition of their data in dbGAP.

  Study phs003723

• METSIM (METabolic Syndrome In Men) Study

  The METSIM Study includes 10,197 men, aged from 45 to 73 years, randomly selected from the population register of the town of Kuopio, Eastern Finland, and examined in 2005-2010. The aim of the study is to investigate genetic and non-genetic factors associated with the risk of type 2 diabetes (T2D), cardiovascular disease (CVD), and insulin resistance-related traits in a cross-sectional and longitudinal setting. Study protocol includes collection of data on CVD risk factors (smoking, exercise, diet, history of chronic diseases including coronary heart disease, stroke, cardiac failure, medication, history of diabetes or early onset coronary heart disease in the family), questionnaire on the FINDRISC Score, measurement of height, weight, waist, hip, blood pressure, and bioimpedance for the evaluation of fat percentage. July 2016 - The first study release (v1) included phenotype and whole exome sequencing (WES) data of n=982 participants in substudy: Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Project 1: Metabolic Syndrome in Men Study (METSIM) - phs001100.v2.p1. The second study release (v2) included phenotype data for the entire METSIM cohort and made two additional substudies available, phs000919.v1.p1 and phs000752.v1.p1. The third study release (v3) made three subcutaneous adipose biopsy substudies available, phs003385.v1.p1, phs003386.v1.p1, and phs003387.v1.p1.The fourth study release (v4) added phenotype data for the subcutaneous adipose biopsies, made two additional substudies available, phs01579.v1.p1 and phs004033.v1.p1, and is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" section of this top-level study page phs000743 METSIM Study. phs000752 METSIM FinMetSeq Exome Sequencing phs000919 METSIM GWAS and Exome Chip phs001100 METSIM T2D-GENES Exome Sequencingphs001579 METSIM CCDG Whole Genome Sequencingphs003385 METSIM Subcutaneous Adipose Needle Biopsy RNA-Seq phs003386 METSIM Subcutaneous Adipose Needle Biopsy ATAC-Seq phs003387 METSIM Subcutaneous Adipose Surgical Biopsy RNA-Seqphs004033 METSIM Metabolomics

  Study phs000743

• 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

• 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

• Evolution and clinical impact of genetic epistasis within EGFR-mutant lung cancers

  The current understanding of tumorigenesis is largely centered on a monogenic driver oncogene model. This paradigm is incompatible with the prevailing clinical experience in most solid malignancies: monotherapy with a drug directed against an individual oncogenic driver typically results in incomplete clinical responses and eventual tumor progression1-7. By profiling the somatic genetic alterations present in over 2,000 cases of lung cancer, the leading cause of cancer mortality worldwide, we show that combinations of functional genetic alterations, i.e. genetic collectives dominate the landscape of advanced-stage disease. We highlight this polygenic landscape and evolution of advanced-stage non-small cell lung cancer (NSCLC) through the spatial-temporal genomic profiling of 7 distinct tumor biopsy specimens and 6 plasma specimens obtained from an EGFR-mutant NSCLC patient at (1) initial diagnosis of early-stage disease, (2) metastatic progression, (3) sequential treatment and resistance to 2 EGFR inhibitors, (4) death. The comprehensive genomic analysis of this case, coupled with circulating free (cf) tumor DNA profiling of additional advanced-stage EGFR-mutant NSCLC clinical cohorts with associated treatment responses uncovered features of evolutionary selection for multiple concurrent gene alterations: including the presence of EGFR inhibitor-sensitive (EGFRL858R;EGFRexon19del) or inhibitor-resistant (EGFRT790M;EGFRC797S) forms of oncogenic EGFR along with cell cycle gene alterations (e.g. in CDK4/6, CCNE1, RB1) and activating alterations in WNT/β-catenin and PI3K pathway genes, which our data suggest can cooperatively impart non-redundant functions to limit EGFR targeted therapy response and/or promote tumor progression. Moreover, evidence of an unanticipated parallel evolution of both EGFR T790M and two distinct forms of oncogenic PIK3CA was observed. Our study provides a large-scale clinical and genetic dataset of advanced-stage EGFR-mutant NSCLC, a rationale for specific polytherapy strategies such as EGFR and CDK4/6 inhibitor co-treatment to potentially enhance clinical outcomes, and prompts a re-evaluation of the prevailing paradigm of monogenic-based molecular stratification for targeted therapy. Instead, our findings highlight an alternative model of genetic collectives that operate through epistasis to drive lung cancer progression and therapy resistance.

  Study EGAS00001002604

• High-resolution testing of ctDNA dynamics predicts survival in metastatic NSCLC

  One of the great challenges of therapeutic oncology is determining who might achieve survival benefit from a particular therapy. Circulating tumor DNA (ctDNA) provides real-time assessments of patient prognosis and response to treatment using a simple blood draw. While ctDNA positivity is established as a poor prognostic factor, studies on longitudinal ctDNA dynamics have been small and non-randomized, with ctDNA assessments done at disparate time points. To address this, we performed high-sensitivity longitudinal ctDNA testing in 466 patients across 5 time points (1,954 samples total) in a randomized phase III study comparing different chemotherapy-immunotherapy combinations. We leverage machine learning to jointly model multiple ctDNA metrics to predict overall survival in a training/testing framework. _ . Treatment initiation correlated with reductions in ctDNA levels, and training of our machine learning model suggests that assessment of ctDNA dynamics at C3D1 (cycle 3 day 1) of chemo-IO treatment may be optimal to predict OS. The model performs well in the hold-back test data, enabling stratification of patients with Stable Disease (SD) into high-risk vs low-intermediate-risk (HR = 3.2 [2.0-5.3], p <0.001; median 7.1 versus 22.3 months respectively); similarly, the model stratifies patients with a Partial Response (PR) (HR =3.3 [1.7-6.4], p <0.001; median 8.8 versus 28.6 months). Importantly, the model validates well in an external cohort of patients in a different treatment setting and assayed with a different ctDNA technology, in which model predictions similarly identified high-risk patients (OS HR=3.73 [1.83-7.60], logrank p=0.00012). Simulations of clinical trial scenarios employing our ctDNA model further suggest that early ctDNA testing outperforms early radiographic imaging for predicting trial outcomes (increasing the rate of ‘True Go’ decisions by 5.2 - 22.8% depending on the drug combination). Overall, we show that measuring ctDNA dynamics during the course of therapy dramatically improves patient risk stratification, and may provide a means to differentiate between competing therapies at an early time point during clinical trials.

  Study EGAS00001006703

• Influence of Genomic Landscape on Cancer Immunotherapy for Newly Diagnosed Ovarian Cancer: Biomarker Analyses from the IMagyn050 Randomized Clinical Trial

  The IMagyn050 trial (NCT03038100), which evaluated the efficacy of Atezo vs placebo (Pla) with carboplatin, paclitaxel and bevacizumab (CPB) in front line ovarian cancer patient (pts), did not meet its co-primary endpoints of PFS in ITT or PD-L1+ (Moore et al. JCO 2021). The aim of this exploratory study was to evaluate whether patients with BRCA1/2-mutated or homologous recombination-deficient (HRD) ovarian cancers benefitted from atezolizumab in the phase III IMagyn050 (NCT03038100) trial. Methods: Patients with newly diagnosed ovarian cancer were randomized to either atezolizumab or placebo with standard chemotherapy and bevacizumab. PD-L1 status of tumor-infiltrating immune cells was determined centrally (VENTANA SP142 assay). Genomic alterations, including deleterious BRCA1/2 alterations, genomic loss of heterozygosity (gLOH), tumor mutation burden (TMB), and microsatellite instability (MSI), were evaluated using the FoundationOne assay. HRD was defined as gLOH ≥16%, regardless of BRCA1/2 mutation status. Potential associations between progression-free survival (PFS) and genomic biomarkers were evaluated using standard correlation analyses and log-rank of Kaplan-Meier estimates. Results Among biomarker-evaluable samples, 22% (234/1050) harbored BRCA1/2 mutations and 46% (446/980) were HRD. Median TMB was low irrespective of BRCA1/2 or HRD. Only 3% (29/1024) had TMB ≥10 mut/Mb and 0.3% (3/1022) were MSI-high. PFS was better in BRCA2-mutated versus BRCA2-non-mutated tumors and in HRD versus proficient tumors. PD-L1 positivity (≥1% expression on immune cells) was associated with HRD but not BRCA1/2 mutations. PFS was not improved by adding atezolizumab in BRCA2-mutated or HRD tumors; there was a trend toward enhanced PFS with atezolizumab in BRCA1-mutated tumors. Conclusion Most ovarian tumors have low TMB despite BRCA1/2 mutations or HRD. Neither BRCA1/2 mutation nor HRD predicted enhanced benefit from atezolizumab. This is the first randomized double-blind trial in ovarian cancer demonstrating that genomic instability triggered by BRCA1/2 mutation or HRD is not associated with improved sensitivity to immune checkpoint inhibitors.

  Study EGAS00001006838

• pacbio dataset 3

  This dataset consists of 1 sample

  Dataset EGAD00001008747

• California Pacific Medical Center Research Breast Health Cohort

  Description of Cohort: The California Pacific Medical Center (CPMC) Breast Health Cohort is a cohort study based at CPMC and is linked to the San Francisco Mammography Registry, one of the sites of the NCI-funded Breast Cancer Screening Consortium (U01CA063740). CPMC is a community hospital in San Francisco, which has one of the highest volumes for mammography in San Francisco. Between September 2004 and June 2007, >90,000 mammograms were performed at CPMC. The CPMC breast health cohort collects demographic and risk factor data on women receiving mammography through participation in the San Francisco Mammography Registry, as part of the Breast Cancer Screening Consortium (U01CA063740). The SFMR database collects information from all sources, including a questionnaire on demographic and risk factor information, the clinical results of the breast examination, the measures of breast density by Dr. John Shepherd and the women who agreed to donate a blood sample. By merging these various sources of information we have very efficiently developed a large sample of women who have donated blood and have had a measure of mamographic density. Blood Collection: Dr. Steve Cummings is leading an effort to collect and archive blood samples from women who are receiving mammography screening. All women who are sent for a screening mammogram at CPMC are considered eligible. Since the cohort began collecting blood samples in July 2004 until June 2007, samples have been collected from over 11,000 women. Measurement of Breast Density: Dr. John Shepherd is currently measuring breast density in a large fraction of the cohort using an automated approach with single X-ray absorptiometry. Dr. Shepherd has established a link with the CPMC mammography center that allows him to collect routine digital mammography information. Using the data from the mammogram, Dr. Shepherd and his group have developed the single X-ray absorptiometry (SXA) technique for measuring density which is described in more detail below. The table demonstrates the distribution of demographic variables and some breast cancer risk factors of women who donated blood and had a breast density measurement in the CPMC breast health cohort. Nearly 80% of the participants are Caucasian and most of the women are post-menopausal with a median age of ~52. Since it will be difficult to accrue a large enough sample from each ethnic group, our study will focus only on Caucasian women. Table: Demographic variables, reproductive history and family history of breast cancer among 2962 women participating in the CPMC cohort study who contributed blood samples between 1994-1997. Variable Median/Percentage Age (Median/IQR) 52 (46-59) Ethnicity Caucasian/White 0.76 Asian/Pacific Islander 0.141 Hispanic 0.029 Mixed Race/Ethnicity 0.039 African American/Black 0.022 American Indian 0.001 Other 0.009 First degree relative with breast cancer 0.17 Age at first birth Nulliparous 0.39 Age<20 0.043 Age>40 0.032 Age<30, ≥20 0.251 Age>30, ≤40 0.282 Measurement of Breast Density in Cohort: Measurement of breast density is accomplished using an automated technique for all mammograms obtained by Dr. Shepherd using Single X-Ray absorptiometry (SXA). SXA measurement of breast density is done on approximately 30% of all screening mammograms. Below we describe the method for measurement of breast density by SXA by Dr. Shepherd's group and its validation and association with breast cancer. As we demonstrate below, breast density, as measured by SXA, is an automated, highly reproducible measure of the density of breast tissue and is associated with breast cancer risk. SXA for Quantifying Breast Density: Single x-ray absorptiometry (SXA) was initially developed for measuring bone density. SXA can determine the fraction of each of two densities simultaneously using the fact the sample is a constant thickness, the thickness in known, and the total attenuation is known. In applying this technique to breast density, we assume a two compartment model: fat and non-fatty (fibroglandular tissue). We use a reference material composed of various concentrations of two materials: one which is the same density as fat and another which is the same density as fibroglandular tissue. The reference material (phantom) is placed in the X-ray field with each mammogram. We have been able to implement this in a way that is unintrusive to the patient and technologist at CPMC. Assuming this two-compartment model and a constant known breast thickness, we can then calculate the percent density at any region of the breast based on the assumption that % pixel grey-scale is proportion to the mass fractions of breast fat and lean tissue. If reference materials (a phantom) of fat and fibroglandular tissue are imaged with the patient's breast and the reference materials have the same thickness as the patient's breast, then the breast's grey-scale values can be converted to fat/fibroglandular mass fractions by interpolating between those two references. The total percent density is found by averaging the volume fraction over all breast pixels. The phantom being used for breast density assessment at CPMC began to be used in September 2004. The phantom does not have to be manipulated by the technologist and stays attached on the mammography device during standard craniocaudal (CC) views. Thus it creates minimal to no interference with the clinical mammogram. Reproducibility of breast density measures: Traditional measures of mammographic density require some human interpretation. A human reader outlines the area perceived to be dense and a computer then calculates the percent area outlined as a percent of the entire image. Thus, while traditional mammographic density is associated with breast cancer risk, it has some limitations. In a study by Drs. Shepherd, Kerlikowske, et al., the correlation coefficient (Pearson's R) between different readers was 0.8-0.9. In contrast to the traditional mammographic density measurement, the SXA measurement is fully automated and, therefore, the reproducibility of the measurement is higher. Dr. Shepherd and colleagues have performed a replication study of SXA as a measurement of breast density. They have estimated the correlation coefficient of the SXA measurement of breast density to be >0.98. Thus, as expected for an automated measure, SXA is a highly reproducible measure of mammographic breast density. Drs. Shepherd and Kerlikowske have recently analyzed the association between breast cancer risk and breast density as measured by SXA (Shepherd et al., Cancer Epi Biomarkers and Prev, 2011, PMID: 21610220). They found that women in the highest quintile of % volumetric density had an odds ratio of 4.1 (95% CI: 2.3 - 7.2) for breast cancer risk compared to women in the lowest quintile of volumetric density. Thus volumetric density appears to be a highly reproducible, automated measure of breast cancer.

  Study phs000395

• Genomic sequencing of Ewing's Sarcoma

  The Ewing sarcoma family of tumors (EFT) is a group of malignant small round blue cell tumors that arise in bone or soft tissue. Ewing sarcoma (ES) is the second most common type of primary bone tumor to affect children and adolescents and accounts for 2.9% of all childhood cancers. This data set reports whole-genome sequencing of 6 primary Ewing's Sarcoma samples and matching germline samples.

  Study phs000768

• Dana-Farber Cancer Institute (DFCI) Brown Lab CLL Sequencing Study

  Chronic Lymphocytic Leukemia (CLL) is a hematological malignancy characterized by accumulation of CD5+CD19+ B cells in peripheral lymphoid organs, bone marrow and blood. In this study we analyze matched whole genome sequencing and RNA-seq data from CLL patients to characterize the mutational processes operative throughout tumor evolution. Source of tumor and normal DNA used is patient PBMC or B cells and saliva respectively.

  Study phs000879

• Clinical and Genetic Analysis of Retinopathy of Prematurity (ROP)

  Retinopathy of prematurity (ROP) is a leading cause of childhood blindness worldwide and is treated based on the presence of symptoms of "plus disease", a dilation and tortuosity of retinal vessels. This project aims to identify the genetic and clinical underpinnings of the disease by comparing the germline variants of ~1,400 premature babies. 100 samples have been selected for WES and all have been genotyped.

  Study phs002047

• CLDN14 mutation identifed from Japanese sensorineural hearing loss patient.

  The CLDN14 gene, encoding claudin 14, is reported to be one of the rare causes of non-syndromic autosomal dominant sensorineural hearing loss. The detailed clinical characteristics of CLDN14 associated hearing loss is still remain unclear. In the present study, we performed CLDN14 mutation analysis using massively parallel DNA sequencing (MPS) to reveal the clinical characteristics of CLDN14-related hearing loss in a large hearing loss population.

  Study JGAS000191

• Benchmarking V(D)J Repertoire Reconstruction: Bulk RNA-Seq vs PCR-Based RepSeq Validated by SMRT Sequencing

  The aim of this study is to benchmark methods for immunoglobulin repertoire profiling using human B-cell samples. We compare targeted VDJ mRNA sequencing and repertoire reconstruction from bulk RNA-seq data to PCR-independent full-length transcript sequencing using Single-Molecule Real-Time technology. The objective is to assess methodological biases and establish a robust reference framework for immunoglobulin repertoire analysis.

  Study EGAS50000001541

• ATAC_SEQ_MAIN___PHASE_1

  This is a study to test ATAC-seq protocols. CD4+ and CD8+ cells have been obtained from three different anatomical compartments. We aim to assay open-chromatin regions across these cells and perform comparative analyses.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 EGAS00001000947

• Spontaneous mutations in the single TTN gene represent high tumor mutation burden

  Tumor mutation burden (TMB) is an emerging biomarker, whose calculation requires targeted sequencing of many genes. We investigated if the measurement of mutation counts within a single gene is representative of TMB. Whole exome sequencing (WES) data from the pan-cancer cohort (n=10,224) of TCGA, and targeted sequencing (tNGS) and TTN gene sequencing from 24 colorectal cancer samples (AMC cohort) were analyzed.

  Study EGAS00001004009

• The Landscape of Genetic Alterations in Hepatocellular Carcinoma, 88 matched HCC tumour/normal pairs WGS belongs to ICGC LICA-CN project

  Hepatocellular carcinoma (HCC) is the most common malignancy of the liver. Genomic analysis is conducted to identify genetic alterations in driver genes which are all druggable targets for cancer therapy. Whole genome shotgun sequencing (WGS) and the landscaple of somatic mutations in 88 paired samples from HCC patients including tumors and matched adjacent normal tissues using Illumina HiSeq 2000 platform were performed.

  Study EGAS00001002218