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• Tracking the evolution of Therapy-Related Myeloid Neoplasms using chemotherapy signatures

  Patients treated with cytotoxic therapies, including autologous stem cell transplantation, are at risk for developing therapy-related myeloid neoplasms (tMN). Pre-leukemic clones (i.e., clonal hematopoiesis; CH) are detectable years before the development of these aggressive malignancies, though the genomic events leading to transformation and expansion are not well-defined. Here, leveraging distinctive chemotherapy-associated mutational signatures from whole-genome sequencing data and targeted sequencing of pre-chemotherapy samples, we reconstruct the evolutionary life-history of 39 therapy-related myeloid malignancies. A dichotomy is revealed, in which neoplasms with evidence of chemotherapy-induced mutagenesis from platinum and melphalan are hypermutated and enriched for complex structural variants (i.e., chromothripsis) while neoplasms with non-mutagenic chemotherapy exposures are genomically similar to de novo acute myeloid leukemia. Using chemotherapy-associated mutational signatures as temporal barcodes linked to a discrete clinical exposure in each patient’s life, we estimate that several complex events and genomic drivers are acquired after chemotherapy is administered. For patients with prior multiple myeloma who were treated with high-dose melphalan and autologous stem cell transplantation, we demonstrate that tMN can develop from either a reinfused CH clone that escapes chemotherapy exposure and is selected following reinfusion, or from TP53-mutant CH that survives direct myeloablative conditioning and acquires melphalan-induced DNA-damage. Overall, we reveal a novel mode of tMN progression that is not reliant on direct mutagenesis or even exposure to chemotherapy. Conversely, for tMN that evolve under the influence of chemotherapy-induced mutagenesis, distinct chemotherapies not only select pre-existing CH, but also promote the acquisition of recurrent genomic drivers.

  Study EGAS00001006903

• Genetics of Antinuclear Antibodies

  Antinuclear antibodies (ANA) are antibodies that react against self-antigens in the cell. While it has been reported that 12 to 20% of the general population have a positive ANA test, the genetics of ANA positivity is unknown. We performed a genome wide-association study for positive ANA tests among individuals without an ANA related autoimmune disease in the Vanderbilt University Medical Center (VUMC) DNA biobank linked to the de-identified electronic health record (EHR) system. The study is funded by the National Institute of Arthritis and Musculoskeletal and Skin diseases (NIAMS) grant R01AR076516.

  Study phs003189

• Genome-Wide Association Study of Genetic Susceptibility for Graft-vs-Host Disease Cohort 1

  Allogeneic hematopoietic stem cell transplantation (Allo-HSCT) is the only curative therapy for many advanced hematologic malignancies. Allo-HSCT is associated with significant morbidities and mortality, mainly because of the graft-versus-host disease (GVHD) caused by donor T cells recognizing antigens present in recipient tissues, and initiating an alloimmune response resulting in damage to many organs including the skin, gastrointestinal (GI) tract, and liver in recipient. More than half of all Allo-HSCT recipients develop different degrees of GVHD (grades I-IV). About 20% of recipients develop severe GVHD (grades III-IV) that is associated with a very high morbidity and mortality. The most important factor determining the severity of GVHD is the genetic disparities between donors and recipients, as is reflected in human leukocyte antigen (HLA) haplotypes that are routinely checked for donor selection. Even when donors and recipients are HLA-identical, many recipients develop severe GVHD. As a result, non-HLA antigens are important determinants of acute GVHD. An interesting and unique aspect of GVHD is that it is the consequence of an interaction between antigens present in one individual with the immune system of another individual. As a result, genotypes of both donor and recipient, and their interactions affect the pathogenesis of GVHD. To determine the genetic risk factors for GVHD, in the first aim (discovery phase), we will conduct Genome-Wide Association Studies (GWAS) in 3,000 patients who underwent Allo-HSCT and in their respective donors (6000 DNA samples) that are provided to us by the Center for International Blood and Marrow Transplant Research (CIBMTR), a research collaboration between the NMDP and Medical College of Wisconsin. In the second aim, we will validate the association between high risk genotypes detected in the first aim and severe GVHD in 1,750 donors and 1,750 recipients of Allo-HSCT, and perform the joint analysis with the discovery samples. In the third aim, we will investigate the functional effect of SNPs detected and validated to be significantly correlated with the severity of acute GVHD in mixed lymphocyte reaction (MLR), as an ex vivo surrogate for an alloimmune response.

  Study phs002185

• Genome-wide prediction of human embryos

  BACKGROUND: Preimplantation genetic diagnosis (PGD) enables profiling of embryos for genetic disorders prior to implantation. The majority of PGD testing is restricted in the scope of variants assayed or by the availability of extended family members. While recent advances in single cell sequencing show promise, they remain limited by bias in DNA amplification and the rapid turnaround time (<36 h) required for fresh embryo transfer. Here, we describe and validate a method for inferring the inherited whole genome sequence of an embryo for preimplantation genetic diagnosis (PGD). METHODS: We combine haplotype-resolved, parental genome sequencing with rapid embryo genotyping to predict the whole genome sequence of a day-5 human embryo in a couple at risk of transmitting alpha-thalassemia. RESULTS: Inheritance was predicted at approximately 3 million paternally and/or maternally heterozygous sites with greater than 99% accuracy. Furthermore, we successfully phase and predict the transmission of an HBA1/HBA2 deletion from each parent. CONCLUSIONS: Our results suggest that preimplantation whole genome prediction may facilitate the comprehensive diagnosis of diseases with a known genetic basis in embryos.

  Study EGAS00001001020

• The Genomic Landscape of Mongolian Hepatocellular Carcinoma

  Background and Hypotheses: Mongolia has the highest reported incidence of - and mortality from - hepatocellular carcinoma (HCC) in the world, which is between three and seven times higher than that observed in other high-incidence populations, such as South Korea, Thailand, and China. Although its causative factors and underlying tumor biology remain unknown, risk factors such as chronic hepatitis B virus and/or hepatitis C virus infection are highly prevalent. Moreover, Mongolia has an extraordinarily high prevalence of hepatitis delta virus (HDV), more than ten times above the global estimate, which we hypothesize as a major driver of Mongolian hepatocarcinogenesis. By performing a comprehensive and integrative genomic characterization, we aimed to identify robust molecular subclasses and driver features informative of the etiology and progression of the disease. This study, the first one of this nature ever to be conducted on a Mongolian cohort, identifies similarities to previous studies performed on other populations (which reflect general characteristics of liver carcinogenesis) as well as unique features of Mongolian HCC. Study Design and Methods: Clinical information and paired tumor/non-tumor liver tissue samples were obtained from 76 HCC patients undergoing surgery at the National Cancer Center of Mongolia. Transcriptome sequencing and whole exome sequencing were performed on all tumor and non-tumor samples, followed by bioinformatics processing and quality control. Consensus clustering and regularized Cox regression analyses were performed on transcriptome data. Driver mutations and mutational signatures were assessed. These results were compared to those from 373 HCC patients of different races and ethnicities and diverse etiologies. Furthermore, molecular subclass gene signatures from multiple previous studies were assessed for validation. Results and Conclusions: Using a transcriptomics-based unsupervised approach, we identified four molecular subclasses among Mongolian HCC cases, which were associated with different patient survival outcomes. These molecular subclasses were mapped to signatures reported in other HCC cohorts, showing significant associations consistent with survival outcomes. A supervised analysis determined risk scores strongly associated with survival, consistent with the four molecular subclasses. Mutational signature analysis using recently published COSMIC and Environmental Agents Compendia identified signatures with distinct prevalence among HDV+ and HVD- groups. Signatures differentially associated with HDV+ include mutational patterns linked to alkylating agents (such as temozolomide), tobacco chewing and exposures to 1,8-Dinitropyrene and furan, whereas HDV- appeared differentially associated with aristolochic acid II. In addition to common driver mutations (TP53, CTNNB1) frequently found in pan-cancer analysis, Mongolian HCC exhibits several unique drivers (most notably GTF2IRD2B, PNRC2, and SPTA1), the latter of which may be linked to HDV infection. These results suggest the existence of new molecular mechanisms at play in Mongolian hepatocarcinogenesis.

  Study phs002000

• The whole blood of female volunteers and sperm from the male volunteer were used to extract genomic DNA to do whole genome sequencing. Distinguished SNPs between parental genomes were retained to analyze parental allele-specific DNA methylation and chromatin accessibility in scCOOL-seq data.

  DNA methylation, chromatin states, and their interrelationships represent critical epigenetic information, but those are largely unknown in human early embryos. Here, we apply scCOOL-seq (Chromatin Overall Omic-scale Landscape Sequencing) to generate a genome-wide map of DNA methylation and chromatin accessibility at single-cell resolution during human preimplantation development. Unlike in mice, the chromatin of paternal genome is already more open than that of maternal genome at the mid-zygote stage in humans, and this state is maintained until the 4-cell stage. After fertilization, genes with high variations in DNA methylation and those with high variations in chromatin accessibility tend to be two different sets. Furthermore, 1,797 (35%) out of 5,155 widely open chromatin regions in promoters closed when transcription activity was inhibited, indicating a feedback mechanism between transcription and open chromatin maintenance. Our work paves the way for dissecting the complex, yet highly coordinated, epigenetic reprogramming during human preimplantation development.

  Study EGAS00001002987

• All you need to know about the new Submitter Portal

  In September we launched new services for all EGA users, including a new version of the former Submitter Portal. Our main objective with this Portal is to transform the metadata submission in a simplified and user-friendly method. Although it is possible to find documentation about the Submitter Portal on our website, we wanted to highlight the new features in this article. Enjoy! Credentials: who needs to create a new user to access the Submitter Portal and who doesn't? Users with an old submission account (ega-box) can already access the new Submitter Portal. If it is the first time that you want to access, it is time to request a submitter role linked to the EGA User. In the form, it is mandatory to explain which type of data you want to deposit, the size of your submission, add any comment you’d like us to read, and manage the EGA Data Processing Agreement (DPA) document. This document should be checked by the legal department of your institution and signed by a person with authority to sign contracts on behalf of the institution. Note that we provide a DPA template for new Users; it can be found and downloaded in the Submitter Request section. With the DPA signed and the Submitter Request sent, it is time to wait for our Helpdesk team to validate the request. Metadata submission now can be collaborative It is possible to add collaborator(s) to your submissions. Only registered EGA Users will appear on the search bar. When adding a collaborator, it is mandatory to define the permission granted: Read only: collaborators with this permission can check if the information of the submission is correct but cannot modify anything. Read & write: collaborators with this label can register new objects and modify the registered ones. We wanted to save time for submitters that usually rely on the same collaborators. For that, we have implemented the possibility of adding the same collaborators from previous submissions; all you need to do is to search the submission, and the exact set of EGA users will have access to your submission. You can check the collaborators and their permissions at any point of the submission by going to the collaborators section. Even adding more people to complete the submission is allowed by following the same steps: looking for the EGA User and defining the permission granted (please, note that during the submission it is not possible to add collaborators from previous submissions). Use external links to complement the study information When filling the information about the study we recommend users to enrich the submission with complementary fields such as PubMeds IDs, custom tags and external links. External links are used to connect a study to an external repository. We have implemented an external link to Euro-Bioimaging for a European Project (EuCanImage). Now, we are looking forward to keeping increasing the list of external repositories! Choose the expected release date for your metadata to be searchable on our website Once all the metadata objects are registered it is time to finalise the submission so that the Helpdesk team can approve it. In the new version of the Submitter Portal users can choose the expected release date for the metadata to be searchable on the EGA website. Please, note that the selected date will have a minimum of one week margin from the day of finalisation. This time is necessary for your files to be archived and for the submission to be validated by the Helpdesk Team. Are you looking for the Array submission within the Submitter Portal? Our Submitter Portal does not support array submissions. The submission of Array-based metadata must be done using the EGA programmatic submission. You will find our Array-based format template and all the necessary information on our website, and you can find all the steps in our submission quickguide! More information about the submission process at the EGA Our Team has developed an extended documentation related to metadata submission. A good first step is to take a closer look at the Submission FAQ. To have a general overview of all the metadata submission process we recommend taking a glimpse of our take-the-tour or watching the tutorial available on our YouTube Channel. Don't miss our section on EGA Schemas, to learn more about how the EGA is built. It can be useful to fully ensure that your submissions comply with the EGA's standards and contribute to a valuable and accessible genomic resource.

  Blog new-submitter-portal

• Genome-wide Association Study of Myasthenia Gravis

  The purpose of this project was to conduct a genome-wide associate study to search for the genetic factors that predispose to myasthenia gravis. The rationale for this study lies in the fact that, although the immunological and physiological processes affecting the neuromuscular junctions of myasthenia gravis patients are well understood, the spectrum of genetic factors that predispose to myasthenia gravis and influence its disease manifestations are not well known. Identification of the myasthenia gravis-related genes will shed light on the fundamental cellular events underlying myasthenia gravis, and will provide focus for research aimed at developing therapies that alter the natural course of the disease. A consortium of fourteen institutions in North America collected DNA samples from 1028 people diagnosed with autoimmune myasthenia gravis. Relevant clinical data have been collected for each patient, including age of onset, severity of disease, response to drug therapy, personal and family history of other autoimmune diseases. Genotyping of the case cohort was performed in the Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD. Genotyping of the case cohort was performed using the HumanOmniExpress-12v1_C SNP array manufactured by Illumina Inc. For the control cohort, we downloaded genotype data from dbGAP (accession phs000196.v2.p1) for 1,998 US neurologically normal individuals. The control cohort had been previously genotyped at the Center for Inherited Disease Research at Johns Hopkins University on HumanOmni1-Quad version 1.0B beadchips (Illumina) as part of the NeuroGenetics Research Consortium GWAS of Parkinson's disease. Analyses were confined to the 677,673 autosomal SNPs that were common to both chips. Of the 1028 samples which were genotyped, 21 samples were excluded due to mismatched genders, 9 were excluded due to low genotype call rate, 5 samples were excluded as duplicates, and 25 samples were excluded as ethnic outliers. The remaining 972 samples were used in analysis.

  Study phs000726

• Brain Arteriovenous Malformation Genetics Study

  The Predictors of Spontaneous Cerebral AVM Hemorrhage study was designed to identify genetic markers that predict adverse outcomes in brain arteriovenous malformation (BAVM) patients, examine race-ethnicity influences on BAVM hemorrhage risk, and use genome-wide association analysis to identify novel genetic predictors of AVM and hemorrhage using the Affymetrix GeneChip. We performed the first genome-wide association study (GWAS) (PMID: 26818729) of sporadic BAVM to investigate association of common single nucleotide polymorphisms (SNPs) with risk of sporadic BAVM in the international, multicenter Genetics of Arteriovenous Malformation (GEN-AVM) consortium. The study included a Caucasian discovery cohort of 515 BAVM cases and 1,191 controls genotyped using Affymetrix genome-wide SNP arrays. The Phase 1 discovery cohort comprised of 338 BAVM cases (154 male) and 504 controls genotyped using the Affymetrix Genome-Wide Human SNP Array 6.0. The molecular data (individual genetic data) for the Phase 1 discovery cohort 338 BAVM cases (self-reported Caucasian) recruited at University of California, San Francisco, or Kaiser Permanente of Northern California (KPNC) are included in the dbGaP Study Report: Brain Arteriovenous Malformation Genetics Study, with the additional BAVM case phenotypic and sample attribute characteristics: sex, race, age at BAVM diagnosis, hemorrhagic presentation, BAVM size. Written informed consent was obtained from all participants and the study was approved by the respective Institutional Review Boards. The molecular dataset for this study in dbGaP is based on the genotypes obtained for the initial set of 906,600 SNPs for cases and controls called together using Birdseed v2 algorithm in Affymetrix Genotyping Console Software. The final QC'd dataset includes 717,335 markers as SNPs with MAF<0.01 or deviating from Hardy-Weinberg equilibrium (P<0.00001) in controls were excluded. After QC, the average genotyping call rate was 99%. The discovery phase GWAS identified 57 top BAVM-associated SNPs which were tested in a replication cohort including 608 BAVM cases and 744 controls. The molecular dataset for these 338 BAVM cases was also included in a report investigating common and rare genome-wide copy number variation for association with BAVM (PMID: 24098321), which included a total sample size of 371 sporadic Caucasian BAVM cases and 563 Caucasian controls. This study identified a CNV region on 1p36.13 (NBPF1 locus) that was significantly enriched with duplications in BAVM cases compared to controls, although this association did not replicate in an independent cohort of 184 sporadic BAVM cases and 182 controls. This resource will help researchers to better understand the genetic risk factors for BAVM and/or hemorrhage. These data may be applied to examine the genetic contributions to arteriovenous malformation, stroke, and related vascular disorders and may help generate hypotheses regarding the genetics of cerebrovascular disease.

  Study phs002069

• Single cell RNAseq of stenotic, inflamed and non-inflamed transmural lesions from patients with Crohn's disease

  This dataset contains a gene-cell matrix derived from single-cell RNA sequencing (scRNA-seq) data of ileal tissue from Crohn's disease (CD) patients and colorectal cancer (CRC) patients. It includes: Crohn's Disease Patients: A trio of transmural lesions (stenotic, inflamed, and non-inflamed) from each patient. Colorectal Cancer Patients: Unaffected ileal tissue used as external non-inflamed control. Cell Level Metadata: The dataset includes relevant cell-level metadata such as cell type annotations used in the study. Experimental Details: Platform: 10x Genomics Chromium Single Cell 3' GEX Sequencing: Illumina NovaSeq Processing: Data processed with Cell Ranger software. Resulting count matrices were merged for downstream analysis, including integration and dimensionality reduction. Dataset Composition: Crohn's Disease Patients: 10 patients with 3 samples each (non-inflamed, inflamed, stenotic), totaling 30 samples. Colorectal Cancer Patients: 5 patients with 1 sample each of unaffected tissue, totaling 5 samples. Data Provided: Merged Raw Count Matrix: The final merged raw count matrix used for downstream analysis. Cell Metadata File: Contains details of sample, tissue, and patient for each cell in the count matrix. Barcodes File: Indicate each cell barcode which also encodes the sample, tissue, and patient details for each cell. CD.S_Inf: Stenotic Corhn's disease inflamed samples CD.S_Sten: Stenotic CD patient stenosis sample CD.S_Prox: Stenotic CD Patient - proximal non-inflamed sample CC.C_Prox: CRC Patient proximal unaffected sample eg: A barcode 'CC.C_1_Prox_AAGTCGTAGACCCTTA' indicates CRC Patient unaffected proximal sampe from CRC Patient no.1 and the nucleic acid sequence indicate a unique cell from this sample. Total Samples: Crohn's Disease (CD) Patients: 30 samples Colorectal Cancer (CRC) Patients: 5 samples Patient_no Sample Sample_type 1 CC.C_1 CC.C_1_Prox CC.C_Prox 2 CD.S_1 CD.S_1_Prox CD.S_Prox 3 CD.S_1 CD.S_1_Infl CD.S_Infl 4 CD.S_1 CD.S_1_Sten CD.S_Sten 5 CC.C_2 CC.C_2_Prox CC.C_Prox 6 CD.S_2 CD.S_2_Prox CD.S_Prox 7 CD.S_2 CD.S_2_Infl CD.S_Infl 8 CD.S_2 CD.S_2_Sten CD.S_Sten 9 CC.C_3 CC.C_3_Prox CC.C_Prox 10 CC.C_4 CC.C_4_Prox CC.C_Prox 11 CD.S_3 CD.S_3_Prox CD.S_Prox 12 CD.S_3 CD.S_3_Infl CD.S_Infl 13 CD.S_3 CD.S_3_Sten CD.S_Sten 14 CD.S_4 CD.S_4_Prox CD.S_Prox 15 CD.S_4 CD.S_4_Infl CD.S_Infl 16 CD.S_4 CD.S_4_Sten CD.S_Sten 17 CC.C_5 CC.C_5_Prox CC.C_Prox 18 CD.S_5 CD.S_5_Prox CD.S_Prox 19 CD.S_5 CD.S_5_Infl CD.S_Infl 20 CD.S_5 CD.S_5_Sten CD.S_Sten 21 CD.S_6 CD.S_6_Prox CD.S_Prox 22 CD.S_6 CD.S_6_Infl CD.S_Infl 23 CD.S_6 CD.S_6_Sten CD.S_Sten 24 CD.S_7 CD.S_7_Prox CD.S_Prox 25 CD.S_7 CD.S_7_Infl CD.S_Infl 26 CD.S_7 CD.S_7_Sten CD.S_Sten 27 CD.S_8 CD.S_8_Prox CD.S_Prox 28 CD.S_8 CD.S_8_Infl CD.S_Infl 29 CD.S_8 CD.S_8_Sten CD.S_Sten 30 CD.S_9 CD.S_9_Prox CD.S_Prox 31 CD.S_9 CD.S_9_Infl CD.S_Infl 32 CD.S_9 CD.S_9_Sten CD.S_Sten 33 CD.S_10 CD.S_10_Prox CD.S_Prox 34 CD.S_10 CD.S_10_Infl CD.S_Infl 35 CD.S_10 CD.S_10_Sten CD.S_Sten

  Dataset EGAD50000000559