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• Copy number profiling of putative cancer stem from pleural effusion aspirates from breast cancer patients

  A common symptom during late stage breast cancer disease is pleural effusion, which is related to poor prognosis. In pleural effusions malignant cells can be detected, which indicates a metastatic spread from the primary tumor site. Beside the usefulness for investigation of the metastatic process, it has been a source to isolate cells with putative cancer stem cell (CSC) properties. For this study, pleural effusion aspirate from 25 metastatic breast cancer patients were processed to establish in vitro culture. Patient-derived aspirates were cultured under sphere forming conditions and isolated primary cultures were sorted for cancer stem cell populations ALDH1+ and CD44+CD24-/low and sphere forming efficiency of CSC and non-CSC subpopulation was determined. Unsorted cells had a higher potential to form spheres compared to CSC subpopulations. Subsequently, DNA was isolated from pleural effusions before and after cell sorting, to compare their copy number profiles generated by low-coverage whole genome sequencing to DNA from FFPE primary tumors or bone metastasis. Unbalanced profiles could be detected in four pleural samples before sorting, in two ALDH1+ sorted samples, in one CD44+CD24-/low and in all control samples. Additionally, spheroid culture from one pleural sample could be passaged on and was characterized. Therefore, pleural effusions are an appropriate media for enrichment of putative CSC. However, low-coverage sequencing is difficult due to low quantities of abnormal cells compared to normal cells.

  Study EGAS00001002343

• Genome-wide analysis of genetic risk factors for rheumatic heart disease in Aboriginal Australians provides support for pathogenic molecular mimicry

  Background. Rheumatic heart disease (RHD) following Group A Streptococcus (GAS) infections is heritable and prevalent in Indigenous populations. Molecular mimicry between human and GAS proteins triggers pro-inflammatory cardiac valve-reactive T-cells. Methods. Genome-wide genetic analysis was undertaken in 1263 Aboriginal Australians (398 RHD cases; 865 controls). Single nucleotide polymorphisms (SNPs) were genotyped using Illumina HumanCoreExome BeadChips. Direct typing and imputation was used to fine-map the human leukocyte antigen (HLA) region. Epitope binding affinities were mapped for human cross-reactive GAS proteins, including M5 and M6. Results. The strongest genetic association was intronic to HLA-DQA1 (rs9272622; P=1.86x10-7). Conditional analyses showed rs9272622 and/or DQA1*AA16 account for the HLA signal. HLA-DQA1*0101_DQB1*0503 (OR 1.44, 95%CI 1.09-1.90, P=9.56x10-3) and HLA-DQA1*0103_DQB1*0601 (OR 1.27, 95%CI 1.07-1.52, P=7.15x10-3) were risk haplotypes; HLA_DQA1*0301-DQB1*0402 (OR 0.30, 95%CI 0.14-0.65, P=2.36x10-3) was protective. Human myosin cross-reactive N-terminal and B repeat epitopes of GAS M5/M6 bind with higher affinity to DQA1/DQB1 alpha/beta dimers for the two risk haplotypes than the protective haplotype. Conclusions. Variation at HLA_DQA1-DQB1 is the major genetic risk factor for RHD in Aboriginal Australians studied here. Cross-reactive epitopes bind with higher affinity to alpha/beta dimers formed by risk haplotypes, supporting molecular mimicry as the key mechanism of RHD pathogenesis.

  Study EGAS00001002678

• Targeted sequencing of candidate regions on chromosome 22q predisposing to multiple schwannomas

  Constitutional LZTR1 or SMARCB1 pathogenic variants have been found in ~86% of familial and ~40% of sporadic schwannomatosis cases. Hence, we performed massively parallel sequencing of the entire LZTR1, SMARCB1 and NF2 genomic loci in 35 individuals with schwannomas negative for constitutional first-hit pathogenic variants in the LZTR1/SMARCB1/NF2 coding sequences, however with 22q deletion and/or a different NF2 pathogenic variant in each tumor, including six cases with only one tumor available. Furthermore, we verified whether any other LZTR1/SMARCB1/NF2 (likely) pathogenic variant(s) could be found in 16 cases carrying a SMARCB1 constitutional variant in the 3’ untranslated region (3’-UTR) c.*17C>T, c.*70C>T or c.*82C>T. As no additional variants were found, functional studies were performed to clarify the effect of these 3’-UTR variants on the transcript. The 3’-UTR variants c.*17C>T and c.*82C>T showed pathogenicity by negatively affecting SMARCB1 transcript level. Two novel deep intronic SMARCB1 variants, c.500+883T>G and c.500+887G>A, resulting in out-of-frame missplicing of intron 4, were identified in two unrelated individuals. Further resequencing of the entire repeat - masked genomics sequences of chromosome 22q in individuals negative for pathogenic variants in the SMARCB1/LZTR1/NF2 coding- and non-coding regions revealed five potential schwannomatosis-predisposing candidate genes, i.e. MYO18B, NEFH, SGSM1, SGSM3 and SBF1, pending further verification.

  Study EGAS00001005680

• Genetic variability in exon 1 of the glucocorticoid receptor gene NR3C1 is associated with postoperative complications

  Patients having major surgery experience inflammation post-operatively, which may contribute to post-operative morbidity. Endogenous glucocorticoids (GCs) are an essential part of the stress response, but this response varies between individuals, which may in turn affect clinical outcome in general, and post-operative inflammation, specifically. Exon 1 of the NR3C1 gene, encoding the glucocorticoid receptor, contains an established region of differential regulation. DNA methylation patterns in this region have been found to differ between individuals. We investigated the methylation status and genotype in the Cytosine-phosphate-Guanine (CpG) island in exon 1 of NR3C1 in 24 patients who underwent major abdominal surgery and correlated it with post-operative complications. DNA was extracted from peripheral blood leukocytes and underwent targeted bisulfite sequencing of the CpG island. Complications were graded according to the Clavien-Dindo classification and 14 out of 24 had post-operative complications. Multifactorial and partial least square methods were used to analyse the data. A homogenous demethylated pattern was observed in all patients and no single CpG methylation was associated with post-operative complications. Four single nucleotide polymorphisms (SNPs) were significantly correlated with higher Clavien-Dindo scores. Genetic variability in the chr5:143,402,505-143,405,805 region of exon 1 of the glucocorticoid receptor gene NR3C1, but not DNA methylation, was associated with more severe post-operative complications in patients having major abdominal surgery. This indicates that the response to GCs may be of clinical importance for inflammatory conditions.

  Study EGAS00001005737

• H3.3G34R/V-transformed interneuron progenitors co-opt PDGFRA for gliomagenesis

  Histone H3.3 glycine 34 to arginine/valine (H3.3G34R/V) mutations occur in deadly hemispheric high-grade gliomas. These tumors show exquisite regional and temporal specificity, suggesting a developmental context permissive to the effects of G34R/V mutations. Here we present the molecular landscape of G34R/V gliomas (n=85) and show that 50% bear activating mutations in PDGFRA, with strong selection pressure for PDGFRAMUT clones at recurrence. We show that G34R/V tumors arise in interneuron progenitors of the foetal ventral forebrain expressing GSX2 and the DLX family of homeobox transcription factors, where terminal neuronal differentiation is impaired through aberrant G34R/V-mediated H3K27me3. Frequent co-occurrence of G34R/V & PDGFRAMUT is facilitated in this interneuron lineage-of-origin as PDGFRA forms an aberrant chromatin loop with the adjacent GSX2, hijacking its active chromatin conformation. At the single-cell level, G34R/V tumours entirely lack oligodendroglial transcriptional programs prominent in other glioma entities, and instead harbour dual neuronal and astroglial compartments. CRISPR-removal of H3.3G34R/V does not impact tumorigenicity suggesting this mutation becomes dispensable, while PDGFRAMUT are potently oncogenic regardless of G34 mutation. Collectively, our results suggest that G34R/V gliomas arise in foetal interneuron progenitors unable to undergo terminal differentiation, enabling co-option of PDGFRA through inappropriate expression and activating mutations to promote gliogenesis and oncogenicity. Reliance on PDGFRA for oncogenesis may be of therapeutic opportunity in G34R/V glioma.

  Study EGAS00001004301

• ICU_transcriptomics__Assessing_the_role_of_the_host_immune_response_in_patients_with_ventilator_associated_pneumonia

  The aim of the proposed project is to provide transcriptomic sequencing data analysis of cells isolated from bronchioalveolar lavage and blood samples from critically ill patients with pneumonia on an intensive care unit in order to investigate the host contribution to disease. The lung microbiome of these patients will be analysed in parallel by deep sequencing and 16S sequencing. These data will provide important information to the development of strategies aimed at improving patient outcomes, reducing the development of antimicrobial resistance and facilitating infection control measures in hospital. Specifically, the proposed work will be a proof of principle study of 100 patients. We will use transcriptomic data to define the host contribution to the symptoms of these critically ill patients diagnosed with pneumonia. The data will be correlated with cytokine/chemokine concentrations, routine microbiology analysis and pathogen genomic data from the same samples to determine the ecology of the lungs of these patients. We will look for associations between clinical features, host response and pathogen genomics in order to identify new diagnostic markers. This study should provide important information to improve the speed and accuracy of diagnosis - resulting in more targeted and successful treatment of critically ill patients in the ICU. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001003074

• Small variants in mtDNA Canary Islands - WES Illumina (ITER)

  The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

  Study EGAS00001005678

• Small variants in mtDNA Canary Islands - WGS Illumina (ITER)

  The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

  Study EGAS00001005679

• Small variants in mtDNA Canary Islands - WGS Oxford Nanopore Technologies (ITER)

  The mitochondrial genome (mtDNA) is of interest for a range of fields including evolutionary, forensic, and medical genetics. Human mitogenomes can be classified into evolutionary related haplogroups that provide ancestral information and pedigree relationships. Because of this and the advent of high-throughput sequencing (HTS) technology, there is a diversity of bioinformatic tools for haplogroup classification. We present a benchmarking of the 11 most salient tools for human mtDNA classification using empirical whole-genome (WGS) and whole-exome (WES) short-read sequencing data from 36 unrelated donors. Besides, because of its relevance, we also assess the best performing tool in third-generation long noisy read WGS data obtained with nanopore technology for a subset of the donors. We found that, for short-read WGS, most of the tools exhibit high accuracy for haplogroup classification irrespective of the input file used for the analysis. However, for short- read WES, Haplocheck and MixEmt were the most accurate tools. Based on the performance shown for WGS and WES, and the accompanying qualitative assessment, Haplocheck stands out as the most complete tool. For third-generation HTS data, we also showed that Haplocheck was able to accurately retrieve mtDNA haplogroups for all samples assessed, although only after following assembly-based approaches (either based on a referenced-based assembly or a hybrid de novo assembly). Taken together, our results provide guidance for researchers to select the most suitable tool to conduct the mtDNA analyses from HTS data.

  Study EGAS00001005677

• dbGaP Collection: NHLBI Heart Failure Related dbGaP Data (No IRB requirement)

  The National Heart, Lung, and Blood Institute (NHLBI) Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research has concluded. The NHLBI will continue to make this collection of data available to the research community.Past information regarding the Data Collection for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research is below.The National Heart, Lung, and Blood Institute (NHLBI), part of the National Institutes of Health (NIH), is inviting novel Solutions for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research. The goal of the challenge is to foster innovation in computational analysis and machine learning approaches utilizing large-scale NHLBI-funded datasets to identify new paradigms in heart failure research. The challenge aims to address the need for new open source disease models that can define sub-categorizations of adult heart failure to serve as a springboard for new research hypotheses and tool development in areas of heart failure research from basic to clinical settings. NHLBI has a history of making considerable investments in the creation of deep data resources including: long-standing, deeply-phenotyped epidemiological cohorts, innovative clinical trials, and large-scale precision medicine efforts that have generated whole genome sequencing and "other omics" data for more than one-hundred thousand individuals. To provide challenge participants with streamlined access to data across NHLBI's numerous studies containing heart failure data, the NHLBI has created this dbGaP study collection. Data access for this collection is controlled by NHLBI's Data Access Committee. Challenge participants are required to follow the use restrictions and acknowledgement instructions from the original dataset(s). Please note that the data in this collection are not harmonized across studies or otherwise altered from the original study. The NHLBI Big Data Analysis Challenge: Heart Failure Data Collection contains all NHLBI studies currently in dbGaP that contain data that may be relevant to research on heart failure. The studies in this collection are approved for General Research Use (GRU), Health/Medical/Biomedical Use (HMB), or Disease-Specific Use (DS) that permits research on heart failure. These studies span a variety of study designs, inclusion and exclusion criteria, sample sizes, and provide a wide breadth and depth of phenotype data on study participants. The available genomic data in these studies also varies, including genotyping arrays, sequencing (targeted, exome, whole genome), and additional -omic data (e.g., RNA or metabolite profiles). Please refer to each study's individual accession page to learn more about how study data were collected. Challenge participants are reminded that in addition to dbGaP, NHLBI's Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) contains other studies that have collected data relevant to heart failure and may wish to utilize BioLINCC data in the development of their Solution. Please refer to the individual accession page for each study in this collection to learn more about the history of each study.

  Study phs001991