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• Genetic Epidemiology of COPD (COPDGene) Funded by the National Heart, Lung, and Blood Institute

  Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States and the only leading cause of death that is steadily increasing in frequency. This project will establish a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,000 subjects will be recruited, including control smokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 or GOLD-Unclassified). This cohort will be used for cross-sectional analysis, although long-term longitudinal follow-up will be a future goal. The primary focus of the study will be genome-wide association analysis to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The hypotheses to be studied are: 1) Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, will provide data that will enable the broad COPD syndrome to be decomposed into clinically significant subtypes. 2) Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes. 3) Distinct genetic determinants influence the development of emphysema and airway disease. The initial phase of genome-wide association analysis included 500 COPD cases and 500 control subjects (all non-Hispanic White) genotyped with the Illumina Omni-1 chip. The second phase genotyped the entire study cohort using the Illumina Omni-Express chip. Unique aspects of the study include: 1) Inclusion of large numbers of African American subjects (approximately 1/3 of the cohort); 2) Obtaining chest CT scans (including inspiratory and expiratory images); and 3) Inclusion of the full range of disease severity. The COPDGene_v6 Cohort 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" box located on the right hand side of this top-level study page phs000179 COPDGene_v6 Cohort. phs000296 ESP LungGO COPDGene phs000765 COPDGene_Geno

  Study phs000179

• The identification of genetic vulnerabilities in head and neck cancers for the development of novel treatments.

  The global cancer burden is expected to double by the year 2030 and this will disproportionately affect the Asian continent. Head and neck squamous cell carcinoma (HNSCC) is endemic in Asia. It is the sixth most common cancer worldwide and the second most common in Malaysia, with approximately 600,000 new cases per year globally. Longterm survival remains less than 50%, underscoring the need for better therapeutic strategies. In this proposal we aim to bring new technological advancements in the identification of critical genes in HNSCC and the identification of compounds for the development of new therapies in HNSCC. We propose to genomically characterise 16 unique Asian H&N cancer cell lines, to classify sub groups where identification of essential genes that can be targeted for tumor control can be applied in a more rational way. Further, we propose to use zebrafish, an established drug discovery platform to identify promising pathway-specific compounds that could be further studied using CRISPR/Cas9 lethality screens and biological models to better identify novel therapeutic strategies to combat this major health problem in Asia.

  Study EGAS00001002682

• Same-day genomic and epigenomic diagnosis of brain tumors using realtime nanopore sequencing

  Molecular classification of cancer has entered clinical routine to inform diagnosis, prognosis and treatment decisions. At the same time, new tumor entities have been identified that cannot be defined histologically. For central nervous systems tumors, the current World Health Organization classification explicitly demands molecular testing, e.g. for 1p/19q- codeletion or IDH mutations, to make an integrated histomolecular diagnosis. However, a plethora of sophisticated technologies is currently needed to assess different genomic and epigenomic alterations and turnaround times are in the range of weeks, which makes standardized and widespread implementation difficult and hinders timely decision making. Here, we explored the potential of a pocket-size nanopore sequencing device for multimodal and rapid molecular diagnostics of cancer. Low-pass whole genome sequencing was used to simultaneously generate copy number (CN) and methylation profiles from native tumor DNA in the same sequencing run. Single nucleotide variants in IDH1, IDH2, TP53, H3F3A and the TERT promoter region were identified using deep amplicon sequencing. Nanopore sequencing yielded ~0.1X genome coverage within six hours and resulting CN and epigenetic profiles correlated well with matched microarray data. Diagnostically relevant alterations, such as 1p/19q codeletion, and focal amplifications could be recapitulated. Using ad hoc random forests, we could perform supervised pan-cancer classification to distinguish gliomas, medulloblastomas and brain metastases of different primary sites. Single nucleotide variants in IDH1, IDH2 and H3F3A were identified using deep amplicon sequencing within minutes of sequencing. Detection of TP53 and TERT promoter mutations shows that sequencing of entire genes and GC-rich regions is feasible. Nanopore sequencing allows same-day detection of structural variants, point mutations and methylation profiling using a single device with negligible capital cost. It outperforms hybridization-based and current sequencing technologies with respect to time-to diagnosis and required laboratory equipment and expertise, aiming to make precision medicine possible for every cancer patient, even in resource restricted settings.

  Study EGAS00001002213

• Weighing Risks and Benefits of Laparoscopic Anti-Reflux Surgery in Patients With Idiopathic Pulmonary Fibrosis (WRAP-IPF-BioLINCC)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To determine if the reduction of abnormal gastro-esophageal reflux (GER) with laparoscopic anti-reflux surgery will slow the progression of idiopathic pulmonary fibrosis (IPF) as measured by forced vital capacity (FVC).Background: Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease of unknown cause and increasing prevalence in the United States. Aside from lung transplantation, which approximately only 1% of participants will receive, there is no FDA-approved therapy. Abnormal acid gastro-esophageal reflux (GER) has been well described in participants with IPF and is thought to play a role in the progression of the disease. The several retrospective cohort studies that have assessed the association of anti-acid therapies for GER with clinical outcomes in IPF have had inconsistent results.Participants: A total of 58 participants were enrolled.Design: The WRAP-IPF trial was a multicenter, unblinded randomized clinical trial with participants randomized to either laparoscopic anti-reflux surgery or no surgery. Participants in the no-surgery group had the option of receiving laparoscopic anti-reflux surgery from 24 weeks after randomization if their clinician deemed it medically necessary. Medications for acid GER were allowed in both groups if the clinician felt it was necessary.Participants were followed up from time of randomization to 52 weeks. All participants had study visits at baseline, 12, 24, 36, and 48 weeks, during which spirometry, 6-min walk testing, and participant-related outcome assessments were done. Participants in the surgery group had clinical visits for preoperative evaluation, laparoscopic anti-reflux surgery, and postoperative management as clinically indicated. Surgery participants additionally underwent repeat 24-hour pH testing at 24 weeks to assess the efficacy of the surgery. All participants were contacted by telephone for safety assessments at weeks 4, 8, 16, 20, 28, 32, 40, 44, and 52. All participants completed an exploratory questionnaire on reflux symptoms at baseline and 48 weeks. The primary endpoint was change in FVC from randomization (baseline) to 48 weeks. Secondary endpoints included acute exacerbation, non-elective hospitalization (both all-cause and respiratory-related), death, change in cough severity, change in dyspnea severity, change in health-related quality of life, change in 6-min walk distance, and time to selected event-driven composite endpoints of disease progression. Conclusions: In participants with IPF and abnormal acid GER, laparoscopic anti-reflux surgery is safe and well tolerated but did not significantly slow the rate of FVC decline. Further research is needed, particularly with a larger study in order to achieve sufficient statistical power, regarding the possible benefits of anti-reflux surgery in this population.Raghu G, Pellegrini CA, Yow E, et al. Laparoscopic anti-reflux surgery for the treatment of idiopathic pulmonary fibrosis (WRAP-IPF): a multicentre, randomised, controlled phase 2 trial. Reference: Raghu, et al., 2018; PMID: 30100404.

  Study phs003968

• Robust methylation-based classification of brain tumours using nanopore sequencing

  Background: DNA methylation-based classification of cancer provides a comprehensive molecular approach to diagnose tumours. In fact, DNA methylation profiling of human brain tumours already profoundly impacts clinical neuro-oncology. However, current implementations using hybridization microarrays are time-consuming and costly. We recently reported on shallow nanopore whole-genome sequencing for rapid and cost-effective generation of genome-wide 5-methylcytosine profiles as input to supervised classification. Here, we demonstrate that this approach allows to discriminate a wide spectrum of primary brain tumours. Results: Using public reference data of 82 distinct tumour entities, we performed nanopore genome sequencing on N=382 tissue samples covering 46 brain tumour (sub)types. Using bootstrap sampling in a cohort of N = 56 cases, we find that a minimum set of 1,000 random CpG features is sufficient for high-confidence classification by ad hoc random forests. We implemented score recalibration as confidence measure for interpretation in a clinical context and empirically determined a platform-specific threshold in a randomly sampled discovery cohort (N = 185). Applying this cut-off to an independent validation series (N = 184) yielded 148 classifiable cases (sensitivity 80.4%) and demonstrated 100 % specificity. Cross-lab validation demonstrated robustness with concordant results across four laboratories in 10/11 (90.9%) cases. In a prospective benchmarking (N = 15), median time to results was 21.1 hours. Conclusions: In conclusion, nanopore sequencing allows robust and rapid methylation-based classification across the full spectrum of brain tumours. Platform-specific confidence scores facilitate clinical implementation for which prospective evaluation is warranted and ongoing.

  Study EGAS00001006540

• IL7-receptor expression is frequent in T-cell acute lymphoblastic leukemia and predicts sensitivity to JAK-inhibition

  T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy with a dismal prognosis related to refractory/relapsing diseases, raising the need for new targeted-therapies. Activating mutations of the IL7-receptor pathway genes (IL7Rp) play a proven leukemia-supportive role in T-ALL. JAK-inhibitors such as ruxolitinib have recently demonstrated preclinical efficacy. However, prediction markers for sensitivity to JAK-inhibitors are still lacking. Herein, we show that IL7R (CD127) expression is more frequent (~70%) than IL7Rp-mutations in T-ALL (~30%). We compared the so-called non-expressers (no IL7R-expression/IL7Rp-mutation), expressers (IL7R-expression without IL7Rp-mutation) and mutants (IL7Rp-mutations). Integrative multi-omics analysis outlined IL7R-deregulation in virtually all T-ALL subtypes, at the epigenetic-level in non-expressers, genetic-level in mutants, and post-transcriptional level in expressers. Ex-vivo data using primary-derived xenografts support that IL7Rp is functional whenever the IL7R is expressed, regardless of the IL7Rp mutational status. Consequently, ruxolitinib impaired T-ALL survival in both expressers and mutants. Interestingly, we show that expressers displayed ectopic IL7R-expression and IL7Rp-addiction conferring a deeper sensitivity to ruxolitinib. Conversely, mutants were more sensitive to venetoclax than expressers. Overall, combination of ruxolitinib and venetoclax resulted in synergistic effects in both groups. We illustrate the clinical relevance of this association by reporting achievement of complete remission in two patients with refractory/relapsed-T-ALL. This provides proof of concept for translation of this strategy into clinics as bridge to transplant. Altogether, IL7R-expression can be used as a biomarker for sensitivity to JAK-inhibition, thereby expanding the fraction of T-ALL patients eligible to ruxolitinib up to nearly ~70% of T-ALL.

  Study EGAS00001007144

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Autism - Simons Simplex Collection (SSC)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of New York Genome Center (NYGC). WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs001676

• Resuscitation Outcomes Consortium Trial of Continuous Compressions Versus Standard CPR in Patients With out-of-Hospital Cardiac Arrest (ROC CCC-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: To compare the rate of survival to hospital discharge after continuous chest compressions versus standard American Heart Association recommended cardiopulmonary resuscitation with interrupted chest compressions in patients with out-of-hospital cardiac arrest.Background: Standard cardiopulmonary resuscitation (CPR) consists of manual chest compressions to maintain blood flow and positive-pressure ventilation to maintain oxygenation until spontaneous circulation is restored. Chest compressions during standard CPR are interrupted frequently by ventilations. These interruptions reduce blood flow and potentially reduce the effectiveness of CPR. In animals with cardiac arrest, the interruption of chest compressions has been associated with decreased survival. Observational studies involving humans with out-of-hospital cardiac arrest of presumed cardiac cause have suggested that continuous compressions are associated with higher rates of survival than interrupted compressions.Participants: Of 35,904 patients with out-of-hospital cardiac arrest who were screened, 26,148 were eligible for participation in the trial and were enrolled in the trial during either the run-in phase or the active-enrollment phase. The active-enrollment phase included 23,711 patients, of whom 12,653 were assigned to the intervention group and 11,058 to the control group.Design: There were 114 participating EMS agencies across the eight participating Resuscitation Outcomes Consortium (ROC) sites, which were grouped into 47 clusters. Clusters of agencies were randomly assigned, in a 1:1 ratio, to perform continuous chest compressions or interrupted chest compressions during all the out-of-hospital cardiac arrests to which they responded. Each cluster was required to begin enrolling patients in a run-in phase to demonstrate adherence to the protocol before entering the active-enrollment phase of the trial. Twice per year, each cluster was crossed over to the other resuscitation strategy.Patients assigned to the group that received continuous chest compressions (intervention group) were to receive continuous chest compressions at a rate of 100 compressions per minute, with asynchronous positive-pressure ventilations delivered at a rate of 10 ventilations per minute. Patients assigned to the group that received interrupted chest compressions (control group) were to receive compressions that were interrupted for ventilations at a ratio of 30 compressions to two ventilations; ventilations were to be given with positive pressure during a pause in compressions of less than 5 seconds in duration. The primary outcome was the rate of survival to hospital discharge. Secondary outcomes included neurologic function at discharge, which was measured with the use of the modified Rankin scale, and adverse events. Conclusions: During the active-enrollment phase, 1129 of 12,613 patients in the continuous chest compression group and 1072 of 11,035 patients in the interrupted chest compressions group survived to hospital discharge.In patients with out-of-hospital cardiac arrest, continuous chest compressions during CPR performed by EMS providers did not result in significantly higher rates of survival or favorable neurologic function than did interrupted chest compressions.

  Study phs003901

• Germline mutations in the transcription factor IKZF5 cause thrombocytopenia.

  To identify novel causes of hereditary thrombocytopenia, we performed a genetic association analysis of whole-genome sequencing data from 13,037 individuals enrolled in the NIHR BioResource, including 233 cases with isolated thrombocytopenia. We found an association between rare variants in the transcription factor encoding gene IKZF5 and thrombocytopenia. We report five causal missense variants in or near IKZF5 zinc fingers (Znfs), of which two occurred de novo and three co-segregated in three pedigrees. A canonical DNA-Znf binding model predicts that three of the variants alter DNA recognition. Expression studies showed that chromatin binding was disrupted in mutant compared to wild-type (WT) IKZF5 and electron microscopy revealed a reduced quantity of alpha granules in normally sized platelets. Proplatelet formation (PPF) was reduced in megakaryocytes (MKs) from seven cases relative to six controls. Comparison of RNA-seq data from platelets, monocytes, neutrophils and CD4 T-cells from three cases and 14 healthy controls showed 1,194 differentially expressed genes in platelets but only four DEGs in each of the other blood cell types. In conclusion, IKZF5 is a novel transcriptional regulator of megakaryopoiesis and the eighth transcription factor associated with dominant thrombocytopenia in humans.

  Study EGAS00001003736

• A Population Genomics Study Using a Disease-Targeted Cell model: Integration of

  The common genetic variants associated with complex traits typically lie in non-coding DNA and may alter gene regulation in a cell type-specific manner. Consequently, the choice of tissue or cell model in the dissection of disease associations is important. We carried out an expression quantitative trait loci (eQTL) study of primary human osteoblasts (HOb) derived from 95 unrelated donors of Swedish origin, each represented by two independently derived primary lines to provide biological replication. We combined our data with publicly available information from a genome-wide association study (GWAS) of bone mineral density (BMD). The top 2000 BMD-associated SNPs were tested for cis-association of gene expression in HObs and in lymphoblastoid cell lines (LCLs) using publicly available data and showed that HObs have a significantly greater enrichment (threefold) of converging cis-eQTLs as compared to LCLs. The top 10 BMD loci with SNPs showing strong cis-effects on gene expression in HObs were selected for further validation using a staged design in two cohorts of Caucasian male subjects. All 10 variants were tested in the Swedish MrOS Cohort (n = 3014), providing evidence for two novel BMD loci (SRR and MSH3). These variants were then tested in the Rotterdam Study (n = 2090), yielding converging evidence for BMD association at the 17p13.3 SRR locus. The cis-regulatory effect was further fine-mapped to the proximal promoter of the SRR gene (rs3744270). Our results suggest that primary cells relevant to disease phenotypes complement traditional approaches for prioritization and validation of GWAS hits for follow-up studies. Reprinted from Grundberg E, Kwan T, Ge B et al., Genome Res Nov 2009, with permission from Genome Research, Cold Spring Harbor Press, PMID:19654370.

  Study phs000225

• INdiana GENomics: Implementing an Opportunity for the Under Served (INGENIOUS)

  The INGenious trial planed to enroll a total of 6,000 patients, with 2,000 patients assigned to a pharmacogenetic testing arm and 4,000 to a control arm who will be followed, but not tested. It is randomized between an intervention arm and one that receives no intervention in order that the genotyped group can be compared with one in which undisturbed, routine clinical care is carried out in patients taking the same drugs. Both arms will be followed for a year after being prescribed a targeted medication. Patients randomized into the intervention arm that are prescribed one or more of the 27 targeted index medication will receive pharmacogenomic testing using a custom micro-array measuring 43 Single nucleotide polymorphisms in 14 genes. The study is being conducted by the Indiana University School of Medicine and the Indiana University Institute of Personalized Medicine in collaboration with the Eskenazi and Indiana University Health Systems and will evaluate the economic and clinical outcomes associated with embedding a pharmacogenomics program in a system that serves as the primary health care safety-net in Indianapolis, Indiana. By successfully implementing a pharmacogenomics program and integrating it with the Electronic Health Record and Clinical Decision Support system, physicians will be able to optimize patient care by delivering tailored therapeutic decisions based on the patient's individual genetics.

  Study phs001701

• Identification of cis- and trans-regulatory variation modulating microRNA expression levels in human fibroblasts

  MicroRNAs (miRNAs) are regulatory noncoding RNAs that affect the production of a significant fraction of human mRNAs via post-transcriptional regulation. Interindividual variation of the miRNA expression levels is likely to influence the expression of miRNA target genes and may therefore contribute to phenotypic differences in humans, including susceptibility to common disorders. The extent to which miRNA levels are genetically controlled is largely unknown. In this report, we assayed the expression levels of miRNAs in primary fibroblasts from 180 European newborns of the GenCord project and performed association analysis to identify eQTLs (expression quantitative traits loci). We detected robust expression for 121 miRNAs out of 365 interrogated. We have identified significant cis- (10%) and trans- (11%) eQTLs. Furthermore, we detected one genomic locus (rs1522653) that influences the expression levels of five miRNAs, thus unraveling a novel mechanism for coregulation of miRNA expression

  Study EGAS00000000056

• Submission FAQ

  Submission FAQ Before Submission Is the EGA the right archive for my data? The most suitable archive for your data is dependent on the type of data you are wishing to submit and whether the data require public or controlled access. Public access is defined as complete and open access to all submitted data. On the contrary, controlled access, exerted by the EGA, requires formal applications to be made to access the submitted data files and metadata. EGA only accepts human-derived data subject to controlled access. If your submission contains other types of data, please choose the appropriate repository for it (see image below): ENA, EVA, ArrayExpress, BioSD and GWAS catalog.  Should your submission be subjected to controlled access? Data access conditions are normally defined in the original informed consent agreements signed by the participants involved in your study. All data submitted to the EGA is subject to controlled access. These consents prevent the derived data files, potentially identifiable, from being dispersed by open and public access. Controlled access data often refers to human data derived from medical research and consortium projects. If in doubt, consult the informed consent agreements that apply to your study The EGA enables you to hold a submission before publication. What data types can be submitted to the EGA? Data types accepted by the EGA can be split into three categories: Sequences: both in generic and platform-specific formats. Array-based: from raw signal files to processed matrices. Phenotypes: all possible phenotype formats are accepted. All manufacturer-specific raw data formats derived from major next generation sequencing platforms are accepted. Also generic sequence formats: flat reads in a FASTQ file, aligned sequences (BAM or CRAM files) as well as sequence variation files in VCF format. All array-based technologies are accepted, including raw data, intensity and analysis files, without any restriction on data formats accepted. We also accept and distribute phenotype data (associated to the samples) in almost any format: from an image to a README file. How long does a submission take? Submissions to EGA come in a variety of formats and sizes, thus it is difficult for us to exactly predict how long a submission will take. We, therefore, advise all of our submitters to allow as much time as possible to make a submission. Based on previous records, we anticipate that the submission process may take at least one month. The submitter’s familiarity with the procedures, possible technical issues that may arise during submission and the amount of data that is being submitted are the main factors that will affect the length of the submission process. However, each step of a regular submission should be considered when estimating the time it would take: Encryption of the files Upload of the files Metadata submission Archival of the files Release of the study and datasets to EGA webpage For example, the upload of the files depends on the submission size, while metadata submission mainly relies on each submitter’s expertise. Further, some steps (e.g. answering to inquiries) depend on the EGA Helpdesk team, which may take some days to be processed during busy times Is data deposited in the EGA secure? The EGA set-up consists of a secure computing facility for data processing, a shared EBI set-up for data submissions and distribution of data via data requests made through the EGA website. Data is also copied in the Barcelona Supercomputing Center (BSC) infrastructure, where all stored and distributed data is encrypted Data is encrypted along the submission process and stored securely, granting its access to authorised users exclusively. During the download process, through our Python Client or Aspera, all requested data is downloaded over secure https connections. All data at the EGA is encrypted, and only accessible (for log-in and download) through secure protocols. For further information please, visit our security overview. What documentation do I need to provide? All submissions require policy’s documentation: 'Data Access Agreement (DAA)', 'Data Processing Agreement (DPA)' and 'Authorized Submitters Formulary'. The data processors (EGA) and the data owners will also sign the DPA. Will all metadata be public? Among the submitted metadata we need to make the distinction between identifiable and unidentifiable metadata: (1) the former may allow the identification of the human the sample derived from (e.g. detailed geographical providence, personal name, family ancestry…); (2) while the latter can be used to interpret the data without compromising the anonymity of the patients. The majority of the metadata submitted to the EGA corresponds to the unidentifiable category (e.g. sequencer's model). This type of metadata is publicly available on the EGA website and other EBI resources/partners’ websites. On the other hand, some parts samples’ metadata are subject to being identifiable, and thus only accessible by authorized data requesters, with the exception of: 5 submitter-defined attributes of the sample: alias, title, subject_id, gender and phenotype. It is the submitter’s responsibility not to submit sensitive metadata in these public fields. 3 anonymised fields that pinpoint the sample record in archivals: sample’s EGA stable ID (EGAN…), BioSample ID (SAMEA…) and submitter’s center name. During Submission Are there any sample specific requirements for EGA? All samples submitted to the EGA must include the attributes of biological sex, subject ID (anonymised individual identifier) and phenotype information. These are critical for data findability and its analysis, and we highly recommend using controlled ontology terms where applicable. For example: defining tumour and non-tumour samples and/or defining disease state. The EGA recommends using the Experimental Factor Ontology Database to find ontologized terms that describe your sample phenotypes. How do I get an accession number to use in my publication? You will receive your study accession number (EGAS…) upon complete your submission, either: Programmatically. As soon as the metadata is submitted and validated your study will be assigned an accession number that will be given in the submission’s response. Manually registering your study and relevant metadata using the online metadata submission tool: the EGA submitter Portal. How are files uploaded to the EGA? Data files are uploaded into private submission drop boxes (i.e. environments to which you are granted access and where you can transfer your files) using INBOX or FTP. These spaces are provided as part of the submission procedure. Before uploading any file, you must encrypt your files, . Only encrypted files shall be uploaded to the drop boxes. Why does data need to to encrypted for my submitted files? It is one of the security steps the EGA has implemented. In case of a security breach, people without the proper encryption key will not be able to read or use the information that could have been leaked. This measure is essential when working with sensitive data, such as controlled access human data. All submitters must use crypt4gh to create EGA compliant files prior to uploading them. This encryption is GPG-based, using EGA’s public key. Why are my files not available if I see them in the INBOX? There exists a time window between the data upload and the availability of such files via the Submitter Portal. For this reason, some metadata (run and analysis objects) cannot be registered until at least 24 hours after the files have been uploaded to your box. Why are MD5 sum values generated for my submitted files? We require pre- and post- encryption MD5 (message-digest) checksum values to be provided for all submitted files. These 128-bit values are computed using the content of each file, creating unique sequences that allow us to ensure that file integrity has been maintained during the transfer process. In other words, if the MD5 checksums we generate and those you generated match, we infer that the content of the transferred files is correct (i.e. files are not corrupted or truncated). MD5 checksums are computed automatically using the crypt4gh tool provided. Your submission will not be accepted and may be significantly delayed if you do not provide MD5 checksum values for all data files in the required format. How can I check if my files are correctly uploaded to the inbox? It is important to check the status pf your file so you know whether your files are in the inbox, being processed, or if there is any issue with one of them. In order to check this, you should: Look for the file locally. Drag and drop it to the file table. Then bars will appear on the table, which means that we are processing it. Green: The files checksum are correct and your file will move to “ingested files”. No further actions are needed from your end.. Red: The files checksum does not match and your file needs to be re-uploaded. Please re-upload relevant files to your inbox using the same path. How can I add my dataset to the cBioPortal instance? In order to link your data to the cBioPortal, you must register it as a normal dataset in the Submitter Portal. For more information, please refer to the cBioPortal documentation. After Submission How do I use my accession number in my publication? We suggest the use of the below template, using your study accession ID (EGAS…) : Data has been deposited at the European Genome-phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGASXXXXXXXXXXX. Further information about EGA can be found at https://ega-archive.org and "The European Genome-phenome Archive of human data consented for biomedical research" Your study ID will be the one that groups your whole submission, and thus its usage is recommended as such. Nevertheless, all metadata submitted to EGA hold a unique and persistent identifier (starting with EGA…) that can be used to identify specific records. For example, you could reference a specific dataset (EGAD…) or sample (EGAN…) in your publications (see full list of identifiers). How do I make my data searchable? Once you have finalized your submission, you can schedule the data release. Please take into account that the release process needs time for the files to be archived in our system, and for the Helpdesk team to validate your submission. Can I withdraw (meta)data from the EGA? We have methods in place for the secure removal of deposited (meta)data. Contact EGA-helpdesk for further details. EGA complies with FAIRness of (meta)data, and thus, even when the data is removed we keep an entry for their identifiers in our system. In other words, we execute a soft delete on canceled objects (e.g. a study): metadata is still stored in our systems, but it loses all links, cannot be queried and data files cannot be retrieved anymore. The reason behind this behaviour is so that queries using withdrawn data properly respond back (see example of a canceled study). What happens to the data once it has been submitted to the EGA? When the data is submitted, the submitter can choose either keep their data private or schedule the release of their data.

  Documentation submission/metadata/submission/FAQ

• Single-cell RNA-seq of bronchoalveolar lavage (BAL) fluid of late stage severe COVID-19 patients

  COVID-19-induced ‘acute respiratory distress syndrome’ (ARDS) is associated with prolonged respiratory failure and high mortality, but the mechanistic basis of lung injury remains incompletely understood. Here, we analyzed pulmonary immune responses and lung pathology in two cohorts of patients with COVID-19 ARDS using functional single cell genomics, immunohistology and electron microscopy. We describe an accumulation of CD163-expressing monocyte-derived macrophages, that acquired a profibrotic transcriptional phenotype during COVID-19 ARDS. Gene set enrichment and computational data integration revealed a significant similarity between COVID-19-associated macrophages and profibrotic macrophage populations identified in idiopathic pulmonary fibrosis. COVID-19 ARDS was associated with clinical, radiographic, histopathological, and ultrastructural hallmarks of pulmonary fibrosis. Exposure of human monocytes to SARS-CoV-2, but not Influenza A virus or viral RNA analogs, was sufficient to induce a similar profibrotic phenotype in vitro. In conclusion, we demonstrate that SARS-CoV-2 triggers profibrotic macrophage responses and pronounced fibroproliferative ARDS.

  Study EGAS00001005634

• Addictions: Genotypes, Polymorphisms, and Function/Human Genetic Correlates of Addictive Diseases

  Drug addiction continues to be a major medical and social problem. It is estimated that one million or more persons in the United States are currently addicted to heroin or prescription opioids, with millions more worldwide. Cocaine addiction and alcohol dependence are frequent comorbid conditions in persons with heroin/opioid dependence in addition to being major primary addictions. Many studies over the past thirty years have shown that these drugs disrupt physiologic systems, and that these disruptions may contribute to drug addiction and alcohol dependence and to relapse to drug or alcohol abuse following withdrawal and abstinence. Clinical observations suggest that individuals differ in their response to heroin, cocaine, and alcohol; however, little is known about specific underlying hereditary genetic factors which might influence individual susceptibility to the addictive properties of these substances. Studies also suggest that both common and distinct heritable factors account for the genetic variance in the susceptibility to the separate addictive diseases. We hypothesize that there is a heritable as well as environmental basis for the acquisition and persistence of, and relapse to, specific addictive diseases. Using samples from individuals without and with opioid and other specific drug dependence diagnoses and psychiatric comorbidities, genetic analyses will be used to determine association and linkage. All study subjects will be extensively characterized with respect to the addictive diseases, medical history, family medical addictive disease history; psychiatric comorbidity, and psychological profile, as well as ethnic/cultural background. A better understanding of the consequences of genetic contributions with respect to protection from, or susceptibility to, heroin/opioid addiction and related codependencies and comorbid conditions, could have enormous importance in both prevention and treatment of this problem.

  Study phs001109

• 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

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

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

  Study phs002501

• Infiltrative and drug-resistant slow-cycling cells support metabolic heterogeneity in glioblastoma

  Metabolic reprogramming has been described in rapidly growing tumors, which are thought to mostly contain fast-cycling cells (FCCs) that have impaired mitochondrial function and rely on aerobic glycolysis. Here, we characterize the metabolic landscape of glioblastoma (GBM) and explore metabolic specificities as targetable vulnerabilities. Our studies highlight the metabolic heterogeneity in GBM, in which FCCs harness aerobic glycolysis, and slow-cycling cells (SCCs) preferentially utilize mitochondrial oxidative phosphorylation for their functions. SCCs display enhanced invasion and chemoresistance, suggesting their important role in tumor recurrence. SCCs also demonstrate increased lipid contents that are specifically metabolized under glucose-deprived conditions. Increased fatty acid transport in SCCs is targetable by pharmacological inhibition or genomic deletion of FABP7, both of which sensitize SCCs to metabolic stress. Furthermore, FABP7 inhibition, whether alone or in combination with glycolysis inhibition, leads to overall increased survival. Our studies reveal the existence of GBM cell subpopulations with distinct metabolic requirements and suggest that FABP7 is central to lipid metabolism in SCCs and that targeting FABP7-related metabolic pathways is a viable therapeutic strategy.

  Study EGAS00001003251

• Molecular subtypes of malignant peritoneal mesothelioma

  Malignant Peritoneal Mesothelioma (PeM) is a rare but frequently fatal cancer that originates from the peritoneal lining of the abdomen. Standard treatment of PeM is limited to cytoreductive surgery and/or chemotherapy, and no targeted therapies for PeM yet exist. This study performs comprehensive integrative analysis of genome, transcriptome, and proteome of treatment-naive PeM tumors with the aim of identifying mesothelioma-related molecular alterations and potentially identifying novel treatment strategies.

  Study EGAS00001002820

• NextGen Consortium: The iPSCORE (iPSC Collection for Omic Research) Resource for Studying the Impact of Genetic Variation on Molecular Phenotypes

  The iPSC Collection for Omic Research (iPSCORE) Resource was created as part of the Next-Gen Consortium funded by NHLBI. The overarching purpose of the resource is to provide a large collection of human induced pluripotent stem cells (iPSCs) for use in studying the impact of genetic variation on molecular and physiological phenotypes. The resource has been used in a number of studies in the Dr. Kelly A. Frazer's Lab examining both the characteristics of human iPSCs and a variety of iPSC-derived cell types including cardiovascular progenitor cells (iPSC-CVPCs), pancreatic precursor cells (iPSC-PPCs), and retina pigment epithelium cells (iPSC-RPEs). We have shown that the iPSCs, CVPCs, and PPCs are suitable surrogate models to identify genetic factors active in early developmental processes because they exhibit fetal-like molecular properties. A total of 273 individuals have participated in the study, of which 222 have had iPSCs generated from fibroblasts. Of the 273 individuals, 181 are part of 55 families that include 24 monozygotic twin pairs and 5 dizygotic twin pairs, allowing for the incorporation of familial relationships into genetic analyses. Germline DNA has been sequenced from blood or fibroblast samples for all 273 individuals (available through dbGaP phs001325) and other genomic data (RNA-seq, DNA methylation, genotype arrays, ATAC-seq, H3K27ac ChIP-seq, HiC-seq) have been generated from the 222 iPSCs as well as derived cell types (available through dbGaP phs000924). QTL analyses were conducted for multiple omics data types and summary statistics are available through dbGaP phs0001325. Important note: Of the 273 individuals, 268 are consented for general research use and 5 are consented for cardiac research only. For detailed information about iPSCORE Collection including samples, methods used to generate the data, and how to access the datasets visit the Frazer lab website.The 222 well characterized iPSC lines that constitute the iPSCORE resource are available, please contact Dr. Kelly A. Frazer (kafrazer@health.ucsd.edu) if you are interested in obtaining the collection.

  Study phs000924

• 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

• Developmental Mechanisms of Human Congenital Heart Disease in Subjects with 22q11.2 Deletion Syndrome (DiGeorge Syndrome/Velocardiofacial Syndrome)

  The study is designed to identify genetic modifiers of cardiovascular defects in subjects with 22q11.2 deletion syndrome (22q11.2DS), also known as DiGeorge syndrome or velo-cardio-facial syndrome. Affymetrix 6.0 arrays were processed on 1,480 subjects with known cardiovascular anomalies or with normal structures, all with 22q11.2DS. One sample is a duplicate so it was removed. There are 1,472 samples total of unrelated, de-identified, probands. Over 90% have the same sized 3 million base pair deletion flanked by low copy repeats (LCR22) A and D, while approximately 6% have nested A to B deletions. The rest have other nested deletions, that include a deletion in the vicinity of TBX1 (between LCR22 A and B). A subset of the data was used to identify copy number variations serving as modifiers. Some data were previously published by Dr. Emanuel's team at Children's Hospital of Philadelphia in PA, USA (PMID:26742502; PMID:4896312; PMID:25892112; PMID:4570279). The de-identified DNA data from unrelated subjects come from multiple research sites in the US and Europe as part of the International 22q11.2 Consortium and the International 22q11.2 Brain and Behavior Consortium.

  Study phs001339

• Laser Capture Microscopy (LCM)-RNAseq for Topological Mapping of Synovial Pathology during Rheumatoid Arthritis

  Synovial tissue from the hip or knee was collected from rheumatoid arthritis (RA) and osteoarthritis (OA) patients at the time of joint replacement surgery. Samples were analyzed using laser capture microdissection (LCM) followed by RNA-seq to evaluate the transcriptome in distinct synovial compartments. Results indicated that synovial compartments have both shared and distinct transcriptional signatures that correspond to key pathways relevant to RA pathogenesis.

  Study phs003587

• Genomic Characterization CS-MATCH-0007 Arm P

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm P is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with PTEN loss by IHC are treated with the drug GSK2636771. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002152

• Phylogenetic Analyses of Melanoma Reveal Complex Patterns of Metastatic Dissemination

  Subpopulations of cells in a primary melanoma can disseminate and establish metastases. Still, the precise ancestral relationship between primary tumors and their metastases is not well understood. Using whole-exome sequencing (for discovery) and targeted sequencing (for validation), we analyzed mutation patterns of primary melanomas and two or more metastases in each of 8 patients to determine their phylogenetic relationships, profiling a total of 31 total tumors. The resulting data show that in 6 of 8 cases, genetically unique cell populations in the primary metastasized in parallel to distinct anatomic sites, rather than sequentially. These data also indicate that individual metastases were sometimes founded by multiple cell populations of the primary that were genetically distinct.

  Study phs000941

• Profiling RNA Translation in Pediatric Medulloblastoma

  This study provides RNA-sequencing and ribosome profiling data for patient-derived cell lines and patient tissue samples for children with medulloblastoma. Ribosome profiling is a variant protocol of RNA-sequencing that directly sequences ribosome-bound RNA fragments only. Associated RNA-seq and Ribo-seq data obtained separately for some cancer cell lines can be found on the NCBI SRA as PRJNA957428. Samples were processed for poly-A mRNA sequencing using the Roche Kapa Kit. Ribosome profiling was performed as described in the manuscript referenced below (Hofman et al.) and based on the article by McGlincy et al., Methods (2017). Ribo-seq data were analyzed for sample quality using RiboseQC (Calviello, Nat Struct Mol Biol, 2020). These data were used to quantify P-sites of open reading frames. RNAseq and ribo-seq data were integrated and compared to determine translational efficiency values using TPM (Ribo-seq) over TPM (RNA-seq) as the metric. Ribo-seq data on 14 samples and RNAseq data on 21 samples derived from 16 fresh-frozen surgical samples for medulloblastoma and 5 autopsy samples are available through dbGaP. A second cohort of 4 medulloblastoma samples (RNAseq, Ribo-seq) related to this study can be found on the EGA at EGAS00001007426.

  Study phs003446

• Coding and regulatory somatic profiling of triple-negative breast cancer in Sub-Saharan African patients

  The burden of triple-negative breast cancer (TNBC) may be shaped by genetic factors, particularly inherited and somatic mutation profiles. However, data on this topic remain limited, especially for the African continent, where a higher TNBC incidence is observed. In the age of precision medicine, cataloguing TNBC diversity in African patients becomes imperative. We performed whole exome sequencing, including untranslated regions, on 30 samples from Angola and Cape Verde, which allowed to ascertain on potential regulatory mutations in TNBC for the first time. A high somatic burden was observed for the African cohort, with 86% of variants being so far unreported. Recurring to predictive functional algorithms, 17% of the somatic single nucleotide variants were predicted to be deleterious at the protein level, and 20% overlapped with candidate cis-regulatory elements controlling gene expression. Several of these somatic functionally-impactful mutations and copy number variation (mainly in 1q, 8q, 6 and 10p) occur in known BC- and all cancer-driver genes, enriched for several cancer mechanisms, including response to radiation and related DNA repair mechanisms. TP53 is the top of these known BC-driver genes, but our results identified possible novel TNBC driver genes that may play a main role in the African context, as TTN, CEACAM7, DEFB132, COPZ2 and GAS1. These findings emphasize the need to expand cancer omics screenings across the African continent, the region of the globe with highest genomic diversity, accelerating the discovery of new somatic mutations and cancer-related pathways.

  Study EGAS50000001013

• Resuscitation Outcomes Consortium (ROC) Cardiac Epidemiologic Registry (Cardiac Epistry) Version 3 (ROC-Cardiac Epistry 3-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Available Data The ROC Cardiac Epistry version 3 include all cardiac arrest cases entered into the ROC database from April 1, 2011 to June 30, 2015. This is separate from versions 1 and 2 because of the major changes in how and which data were collected. Version 3 represents the following major changes to the structure and data collection: separate ED Arrival and Hospital Admits forms, mandatory ED and Hospital elements and a revamped CPR Process form. For ROC traumatic injury Epistry data please see: ROC-Trauma Epistry Objectives To build a prospective population-based registry of participants with out-of-hospital cardiac arrest responded to by Emergency Medical Services (EMS). Specific aims included: to establish whether the results of Resuscitation Outcomes Consortium (ROC) trials can be generalized to the larger population of participants that experience cardiac arrest; to more fully establish the burden of cardiac arrest; and to examine the relationships between variation in EMS structure and process, regional and periodic factors, and participant outcomes. Background Cardiac arrest is a common, serious, debilitating and costly public health problem. Although there has been a steady decline in morbidity and mortality from most cardiovascular diseases, high mortality rates for out-of-hospital cardiac arrests continue to pose a challenge for healthcare providers and a significant public health burden. The Resuscitation Outcomes Consortium (ROC) was established in 2004 to conduct clinical research in the areas of cardiopulmonary arrest and life-threatening traumatic injury with the overall goal of improving resuscitation outcomes. Participant and care characteristics can predict favorable outcomes in cardiac arrests, but there is still a wide variation in outcomes that is not well understood. EMS factors such as service level, number of responding providers, use of procedures or drugs in the field, training, quality assurance/feedback, and response time intervals also vary significantly by region. Variations in geographic, socioeconomic and periodic factors may also be associated with differences in outcomes. Prior to ROC Cardiac Epistry, there were no North American population-based registries for out-of-hospital cardiac arrests. Therefore there was a need for standardized data collection of out-of-hospital cardiac arrests in diverse geographic locations in order to identify the independent effects of prognostic or treatment factors accounting for variations in survival. Participants There were 120,306 participants. Design ROC Epistry collected standardized data regarding episode-specific factors, participant demographics, clinical information, pre-hospital interventions and disposition, hospital information, and participant outcome for all out-of-hospital cardiac arrests in the ROC regions. Each ROC site had to ensure capture of all eligible cases within the EMS service areas. Out-of-hospital data were extracted from existing databases whenever possible and augmented with targeted review of EMS reports. Hospital data were abstracted directly from the hospital file in most cases. Alternative methods included linkage to death registries and obituaries if the death occurred within 30 days. Sites submitted data using a web-based interface or batch uploads. Participants were not contacted directly.

  Study phs003726

• NHLBI GO-ESP: Family Studies (Mendelian Lipid Disorders)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. In this study, we seek to identify the genetic cause of two monogenic lipid disorders-severe hypercholesterolemia and familial hypoalphalipoproteinemia. Monogenic severe hypercholesterolemia is clinically characterized by elevated total and low-density lipoprotein (LDL) cholesterol levels in plasma. Elevated LDL-cholesterol levels lead to excessive deposition of cholesterol in arterial walls, which eventually results in accelerated atherosclerosis and premature cardiovascular disease (CVD). Monogenic hypercholesterolemia has a prevalence of approximately one in 500 individuals, making it one of the most common inherited disorders. To date, mutations in the LDL receptor (LDLR) ligand-binding domains of APOB and PCSK9 have been shown to cause hypercholesterolemia. While mutations in these genes can explain a large percentage of clinically diagnosed patients, the underlying molecular determinant in a substantial fraction of patients remains unknown. Familial hypoalphalipoproteinemia (low HDL-C) is defined by an HDL-C below the age- and sex- specific 10th percentile. ABCA1, LCAT, and APOA1 are known to cause familial hypoalphalipoproteinemia. We hypothesize that: (1) additional novel genes responsible for Mendelian forms of low HDL-C exist; and (2) the causal gene and mutation(s) in each family may be discovered with exome analysis of just a few affected individuals in each pedigree.

  Study phs000587

• Population Architecture using Genomics and Epidemiology (PAGE): Multiethnic Cohort (MEC)

  The Multiethnic Cohort (MEC) has established a large biorepository of blood and urine (N=67,000) and cryopreserved lymphocytes (N=15,000) linked to extensive, prospectively collected risk factors (e.g., diet, smoking, physical activity), biomarkers and clinical data for five racial/ethnic groups. This cohort study of over 215,000 men and women in Hawaii and California is unique in that it is population-based and includes large representations of older adults (45-75 yrs at baseline) for five US racial/ethnic groups (Japanese Americans, African Americans, European Americans, Latinos and Native Hawaiians) at varying risks of chronic diseases. Within the PAGE investigation, the MEC proposes to study: 1) diseases for which we have DNA available for large numbers of cases and controls (breast, prostate, and colorectal cancer, diabetes, and obesity); 2) important cancers that are less common (e.g., lung, pancreas, endometrial cancers, NHL) but for which we propose to pool our data with other funded groups; 3) common traits that are risk factors for these diseases (e.g., body mass index/weight, waist-to-hip ratio, height) and 4) relevant disease-associated biomarkers (e.g., fasting insulin and lipids, steroid hormones). The specific aims are: 1) To determine the population-based epidemiologic profile (allele frequency, main effect, heterogeneity by disease characteristics) of putative causal variants in the five racial/ethnic groups in the MEC; 2) for variants displaying effect heterogeneity across ethnic/racial groups, we will utilize differences in LD to identify a more complete spectrum of associated variants at these loci; 3) investigate gene x gene and gene x environment interactions to identify modifiers; 4) examine the associations of putative causal variants with already measured intermediate phenotypes (e.g., plasma insulin, lipids, steroid hormones); and 5) for variants that do not fall within known genes, start to investigate their relationships with gene expression and epigenetic patterns in small genomic studies. This study is part of the Population Architecture using Genomics and Epidemiology (PAGE) study phs000356.

  Study phs000220

• Single cell sequencing data of PBMC and CSF from a cohort of Multiple Sclerosis patients and other neurological disease controls

  Neuroinflammation is often characterised by immune cell infiltrates in the cerebrospinal fluid (CSF). Here we apply single-cell RNA sequencing to explore the functional characteristics of these cells in patients with various inflammatory, infectious and non-inflammatory neurological disorders. We show that CSF is distinct from the peripheral blood in terms of both cellular composition and gene expression. We report that the cellular and transcriptional landscape of CSF is altered in neuroinflammation, but is strikingly similar across different neuroinflammatory disorders. We find clonal expansion of CSF B and T cells in all disorders but most pronounced in inflammatory diseases, and we functionally characterise the transcriptional features of these cells. Finally, we explore the genetic control of gene expression in CSF lymphocytes. Our results highlight the common features of immune cells in the CSF compartment across diverse neurological diseases and may help to identify new targets for drug development or repurposing in Multiple Sclerosis.

  Study EGAS50000000739

• RNA isoform repertoire of neuropsychiatric risk genes in human brain

  Neuropsychiatric disorders are highly complex conditions and the risk of developing a disorder has been tied to hundreds of genomic variants that alter the expression and/or products (isoforms) made by risk genes. However, how these genes contribute to disease risk and onset through altered expression and RNA splicing is not well understood. Here we show our current understanding of gene isoforms is far from complete and reveal the precise splicing profiles of neuropsychiatric disorder risk genes. Combining our new bioinformatic pipeline IsoLamp with nanopore long-read amplicon sequencing, we deeply profiled the RNA isoform repertoire of 31 high-confidence neuropsychiatric disorder risk genes in human brain. We show most risk genes are more complex than previously reported, identifying 443 novel isoforms and 28 novel exons, including isoforms which alter protein domains, and genes such as ATG13 and GATAD2A where most expression was from previously undiscovered isoforms. The greatest isoform diversity was present in the schizophrenia risk gene ITIH4. Mass spectrometry of brain protein isolates confirmed translation of a novel exon skipping event in ITIH4, suggesting a new regulatory mechanism for this gene in brain. Our results emphasize the widespread presence of previously undetected RNA and protein isoforms in brain and provide an effective approach to address this knowledge gap. Uncovering the isoform repertoire of neuropsychiatric risk genes will underpin future analyses of the functional impact these isoforms have on neuropsychiatric disorders, enabling the translation of genomic findings into a pathophysiological understanding of disease.

  Study EGAS00001007744

• Genomic Characterization CS-MATCH-0007 Arm B

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing, RNA sequencing and if possible, whole-genome, methylation and miRNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH clinical trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm B is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with HER2- activating mutations are treated with Afatinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002028

• Genomic Characterization CS-MATCH-0007 Arm Z1I

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm Z1I is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with BRCA1, BRCA2 mutations are treated with AZD1775. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002058

• Genomic Characterization CS-MATCH-0007 Arm Z1A

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm Z1A is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with NRAS mutations are treated with Binimetinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs001973

• Genomic Characterization CS-MATCH-0007 Arm W

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm W is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with FGFR fusions, mutations, amplifications are treated with AZD4547. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including tumor tissue and whole blood.

  Study phs001948

• Genomic Characterization CS-MATCH-0007 Arm S2

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm S2 is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with GNAQ or GNA11 mutations are treated with Trametinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002178

• Genomic Characterization CS-MATCH-0007 Arm R

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm R is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with BRAF fusions, non-V600K or non-V600E mutations, are treated with Trametinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002029

• Genomic Characterization CS-MATCH-0007 Arm S1

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm S1 is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with NF1 mutations are treated with Trametinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002153

• Genomic Characterization CS-MATCH-0007 Arm I

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm I is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with PIK3CA mutations (without KRAS Mutation or PTEN Loss) are treated with Taselisib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002181

• Genomic Characterization CS-MATCH-0007 Arm U

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm U is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with NF2 loss are treated with Defactinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002179

• Genomic Characterization CS-MATCH-0007 Arm C1

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm C1 is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with MET amplification are treated with Crizotinib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002177

• Genomic Characterization CS-MATCH-0007 Arm Z1B

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm Z1B is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with CCND1, CCND2, and/or CCND3 amplifications are treated with Palbociclib. This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood.

  Study phs002180

• Genomic Characterization CS-MATCH-0007 Arm Q

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm Q is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with HER2 amplification are treated with Kadcyla® (ado-trastuzumab emtansine). This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including tumor tissue and whole blood.

  Study phs001926

• The University of Hong Kong Colon Cancer GCV Study

  Background: Ganciclovir (GCV) is widely used in solid organ and hematopoietic stem cell transplant patients for prophylaxis and treatment of cytomegalovirus. It has long been considered a mutagen and carcinogen. However, the contribution of GCV to cancer incidence and other factors that influence its mutagenicity remains unknown. Methods: This retrospective cohort study analysed genomics data for 121,771 patients who had undergone targeted sequencing compiled by the Genomics Evidence Neoplasia Information Exchange (GENIE) or Foundation Medicine (FM). A statistical approach was developed to identify patients with GCV-associated mutational signature (GCVsig) from targeted sequenced data of tumour samples. Cell line exposure models were further used to quantify mutation burden and DNA damage caused by GCV and other antiviral and immunosuppressive drugs. Results: Mutational profiles from 22 of 121,771 patient samples in the GENIE and FM cohorts showed evidence of GCVsig. A diverse range of cancers was represented. All patients with detailed clinical history available had previously undergone solid organ transplantation and received GCV and mycophenolate treatment. RAS hotspot mutations associated with GCVsig¬¬ were present in 9 of the 22 samples, with all samples harbouring multiple GCV-associated protein-altering mutations in cancer driver genes. In vitro testing in cell lines showed that elevated DNA damage response and GCV¬sig are uniquely associated with GCV but not acyclovir, a structurally similar antiviral. Combination treatment of GCV with the immunosuppressant, mycophenolate mofetil (MMF), increased the misincorporation of GCV in genomic DNA and mutations attributed to GCVsig in cell lines and organoids. Conclusions: In summary, GCV can cause a diverse range of cancers. Its mutagenicity may be potentiated by other therapies, such as mycophenolate, commonly co-prescribed with GCV for post-transplant patients. Further investigation of the optimal use of these drugs could help reduce GCV-associated mutagenesis in post-transplant patients.

  Study EGAS00001006707

• Convergent evolution towards CD38 biallelic loss is a recurrent mechanism of resistance to anti-CD38 antibodies in multiple myeloma.

  Monoclonal antibodies directed against CD38 are a therapeutic mainstay in multiple myeloma (MM). While they have contributed to improved outcomes, most patients will still experience disease relapse. Despite their ubiquity, little is known about tumor-intrinsic mechanisms of resistance to these drugs. Antigen escape, whereby tumor cells alter expression of cell surface immunotherapy targets, has been proposed as a potential avenue, and has been seen with other immunotherapies in MM. Yet, it is unknown whether MM cells can develop permanent resistance to anti-CD38 antibodies by acquiring genomic events leading to biallelic disruption of the CD38 gene locus. Here, by using whole genome and whole exome sequencing data from 701 newly diagnosed patients, 72 patients at relapse with naivety to anti-CD38 antibodies, and 52 patients collected at relapse following anti-CD38 antibodies, we report biallelic inactivation of CD38 as a recurrent mechanism of resistance in 6% of patients, often via convergent evolution where distinct subclones are advantaged towards the same selective endpoint within the same patient. Monoallelic loss of the CD38 locus was seen in another 14% post-CD38-directed therapy. Three of the cases with biallelic events on CD38 presented with missense mutations and retained CD38 expression. Functional work demonstrated that two of these mutations decreased binding affinity and antibody-dependent cellular cytotoxicity of commercial antibodies Daratumumab and Isatuximab. However, the third mutation (R140G) provided relative resistance only towards one commercial product. Given that patients are often rechallenged with CD38 antibodies following disease progression, these data support the need for next generation sequencing to guide treatment selection.

  Study EGAS50000000709

• DNA from colon cancer samples and matched normal samples was hybridized on Human 660W-Quad SNP arrays and sequenced in Illumina HiScanSQ.

  DNA from colon cancer samples and matched normal samples was hybridized on Human 660W-Quad SNP arrays and sequenced in Illumina HiScanSQ. The objective of the study was to introduce methodology for the detection of genomic copy number alterations (CNAs) using high-throughput sequencing data. The samples in this study allow the comparison of the results from the seqCNA R package with those from other methods that detect copy number alterations (CNAs) in tumoural samples, either using SNP-array data or high-throughput sequencing data.

  Study EGAS00001000558

• Kids First: Whole Genome Sequencing in Recessive Structural Brain Defects

  Almost 5% of all live births in the US (1:20 births) display an inborn defect, including both structural and functional/metabolic abnormalities. These are among the most common causes of Infant mortality in the developed world and underlie nearly half of hospitalizations in the first 3 years of life. Of the 35 major defects observable at birth from the International Clearinghouse for Birth Defects Surveillance Program (www.icbdsr.org, external link), about half involve the nervous system. Many of these result in lifelong neurodevelopmental disorders. Structural Brain Defects (SBDs) result from errors in development of the central nervous system, including defects in the forebrain, midbrain and hindbrain. Many SBDs arise as the consequence of a single gene bi-allelic mutation, and for this reason, occur more commonly in populations or communities with elevated consanguinity.Our lab has identified dozens of novel SBD genes using WES/WGS in consanguineous SBD families. Importantly, the genes that we and others have identified in these unique families are then used to advance diagnosis in pediatric SBDs around the world. We have built an enormous cohort of SBD families, including newly recruited families not yet studied genetically, and previous families that were negative for cause following WES analysis. Here we propose to collaborate with the Gabriella Miller Kids First Pediatric Research Program (X01) to have sequencing performed in individuals from a total of 200 families with genetically undiagnosed SBDs. The Gleeson Lab team of researchers is dedicated to the field of SBDs, with an outstanding track record of high-impact science, and a collaborative approach to discovery. We have 150 newly recruited families that we propose to study by WES by sequencing blood-derived DNA from two affected patients, or the parents and one affected patient. We also have 50 families in which WES was negative, which we propose to study in a multi-omics approach combining WGS from blood-derived DNA. We anticipate that this study will lead to the identification of many new molecular causes of SBDs, as well as uncover new genotype-phenotype correlations and new disease mechanisms, paving the way for future breakthroughs in detection, treatment and prevention.

  Study phs002590

• Idiopathic Multicentric Castleman Disease Whole Genome Sequencing Project

  Multicentric Castleman disease (MCD) is a rare lymphoproliferative disorder driven by excessive production of inflammatory cytokines. Patients can exhibit a wide range of clinical features from mild flu-like symptoms to multiple organ failure and death. Human herpesvirus-8 (HHV-8) is a well-established cause of MCD in individuals who are immunosuppressed due to human immunodeficiency virus infection or other causes. On the other hand, it is not known what causes MCD in otherwise healthy individuals with no evidence of exposure to HHV-8 (idiopathic MCD or iMCD). Although iMCD is most common in 40-60 years old adults, it affects people of all ages and early-onset (childhood or young adulthood) cases have been reported. Germline mutations may underlie iMCD in such cases. Patients with early-onset iMCD and their family members were enrolled in the study. To identify germline mutations that may underlie iMCD, whole-genome sequencing was performed in patients and their biological parents from whom DNA samples were available.

  Study phs001706

• Evolution of DNA repair defects during malignant progression of low-grade gliomas after temozolomide treatment.

  Temozolomide (TMZ) increases the overall survival of patients with glioblastoma (GBM), but its role in the clinical management of diffuse low-grade gliomas (LGG) is still being defined. DNA hypermethylation of the O 6 -methylguanine-DNA methyltransferase (MGMT) promoter is associated with an improved response to TMZ treatment, while inactivation of the DNA mismatch repair (MMR) pathway is associated with therapeutic resistance and TMZ-induced mutagenesis. We previously demonstrated that TMZ treatment of LGG induces driver mutations in the RB and AKT-mTOR pathways, which may drive malignant progression to secondary GBM. To better understand the mechanisms underlying TMZ-induced mutagenesis and malignant progression, we explored the evolution of MGMT methylation and genetic alterations affecting MMR genes in a cohort of 34 treatment-naïve LGGs and their recurrences. Recurrences with TMZ-associated hypermutation had increased MGMT methylation compared to their untreated initial tumors and higher overall MGMT methylation compared to TMZ-treated non-hypermutated recurrences. A TMZ-associated mutation in one or more MMR genes was observed in five out of six TMZ-treated hypermutated recurrences. In two cases, pre-existing heterozygous deletions encompassing MGMT, or an MMR gene, were followed by TMZ-associated mutations in one of the genes of interest. These results suggest that tumor cells with methylated MGMT may undergo positive selection during TMZ treatment in the context of MMR deficiency.

  Study EGAS00001001179