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• An analysis of humoral and cellular immune responses following COVID-19 vaccination.

  Two dose mRNA vaccination provides excellent protection against SARS-CoV-2. However, there are few data on vaccine efficacy in elderly individuals above the age of 801. Additionally, new variants of concern (VOC) with reduced sensitivity to neutralising antibodies have raised fears for vulnerable groups. Here we assessed humoral and cellular immune responses following vaccination with mRNA vaccine BNT162b22 in elderly participants prospectively recruited from the community and younger health care workers. Median age was 72 years and 51% were females amongst 140 participants. Neutralising antibody responses after the first vaccine dose diminished with increasing age, with a steep drop in participants over 80 years old. Sera from participants below and above 80 showed significantly lower neutralisation potency against B.1.1.7, B.1.351 and P.1. variants of concern as compared to wild type. Those over 80 were more likely to lack any neutralisation against VOC compared younger participants following first dose. Binding IgG and IgA antibodies were lower in the elderly, as was the frequency of SARS-CoV-2 Spike specific B- cells. We observed a trend towards lower somatic hypermutation in participants with suboptimal neutralisation, and elderly participants demonstrated clear reduction in class switched somatic hypermutation, driven by the IgA1/2 isotype. SARS-CoV-2 Spike specific T- cell IFN?? and IL-2 responses were secreted primarily by CD4 T cells, and impaired in the older age group. We conclude that the elderly are a high risk population that warrant specific measures in order to mitigate against vaccine failure, particularly where variants of concern are circulating. Specifically, the dosing interval should not be extended in this group.

  Study EGAS00001005380

• Institut Curie Neuroblastoma Whole Genome Sequencing Diagnosis Relapse

  Neuroblastoma, a clinically heterogeneous pediatric cancer, is characterized by distinct genomic profiles but few recurrent mutations. As neuroblastoma is expected to have high degree of genetic heterogeneity, study of neuroblastoma's clonal evolution with deep coverage whole-genome sequencing of diagnosis and relapse samples will lead to a better understanding of the molecular events associated with relapse. Samples were included in this study if sufficient DNA from constitutional, diagnosis and relapse tumors was available for WGS. Whole genome sequencing was performed on trios (constitutional, diagnose and relapse DNA) from eight patients using Illumina Hi-seq2500 leading to paired-ends (PE) 90x90 for 6 of them and 100x100 for two. Expected coverage for sample NB0175 100x100bp was 30X for tumor and constitutional samples. For the seven other patients expected coverage was 80X for tumor samples with PE 100x100, 100X in the other tumor samples and 50X for all constitutional samples (see table 1). Following alignment with BWA (Li et al., Oxford J, 2009 Jul) allowing up to 4% of mismatches, bam files were cleaned up according to the Genome Analysis Toolkit (GATK) recommendations (Van der Auwera et al., Current Protocols in Bioinformatics, 2013, picard-1.45, GenomeAnalysisTK-2.2-16). Variant calling was performed in parallel using 3 variant callers: GenomeAnalysisTK-2.2-16, Samtools-0.1.18 and MuTect-1.1.4 (McKenna et al., Genome Res, 2010; Li et al., Oxford J, 2009 Aug; Cibulskis et al., Nature, 2013). Annovar-v2012-10-23 with cosmic-v64 and dbsnp-v137 were used for the annotation and RefSeq for the structural annotation. For GATK and Samtools, single nucleotide variants (SNVs) with a quality under 30, a depth of coverage under 6 or with less than 2 reads supporting the variant were filter out. MuTect with parameters following GATK and Samtools thresholds have been used to filter our irrelevant variants. .SNVs within and around exons of coding genes overlapping splice sites.. Then,variants reported in more than 1% of the population in the 1000 genomes (1000gAprl_2012) or Exome Sequencing Project (ESP6500) have been discarded in order to filter polymorphisms. Finally, synonymous variants were filtered out. MuTect focuses on somatic by filtering with constitutional sample. Mpileup comparison between constitutional and somatic DNAs allowed us to focus also on tumor specific SNVs with GATK and Samtools. Finally, every SNV called by our pipeline and also supported in any constitutional samples were filtered our in order to prevent putative constitutional DNA coverage deficiency. Then we analyzed CNVs (copy number variants) with HMMcopy-v0.1.1 (Gavin et al., Genome Res, 2012) and control-FREEC-v6.7 (Boeva et al., Bioinformatics 2011) with a respective window of 2000bp and 1000 bp, and auto-correction of normal contamination of tumor samples for Control-FREEC. Finally we explored Structural variants (SVs) including deletions, inversions, tandem duplications and translocations using DELLY-v0.5.5 with standard parameters (Rausch et al., Oxford J, 2012). In tumors, at least 10 supporting reads were required to make a call and 5 supporting reads for the sample NB0175 with a coverage of only 40X (see table 2). To predict SVs in constitutional samples for subsequent somatic filtering, only 2 supporting reads were required in order not to miss one. To identify somatic events, all the SVs in each normal sample were first flanked by 500 bp in both directions and any SVs called in a tumor sample which was in the combined flanked regions of respective normal sample was removed (see graph 1). Deletions with more than 5 genes impacted or larger than 1Mb and inversions or tandem duplications covering more than 4 genes, were removed. We focused on exonic and splicing events for deletions, inversions, and tandem duplications. For translocation, we keep all SVs that occurred in intronic, exonic, 5'UTR, upstream or splicing regions. Bioinformatics detection of variations with Deep sequencing approach Once PE reads merged and adaptors trimmed by SeqPrep with default parameters, merged reads were aligned via the BWA (Li H. and Durbin R. 2009 PMID 19451168) allowing up to 1 differences in the 22-base-long seeds and reporting only unique alignments. Only reads having a mapping quality 20 or more have been further analysed. Variant calling software was not used, since we aimed to predict variations at low frequencies, observed in less than 1% of reads. Such variants require a custom approach. Using DepthOfCoverage functions of the Genome Analysis Toolkit (GATK) v2.13.2 (McKenna A, et al., 2010 Genome Research PMID: 20644199), we focused on high quality coverage of bases A, C, G and T at the targeted variant position. Depth of coverage of each base following a mapping quality higher than 20 and a base quality higher than 10 have been taken into account in order to focus only on high quality data. Aiming to determine the background level of variability at the studied regions, 10 control samples were included in the analysis. The same approach and filtering criteria have been applied as introduced above over the entire amplicons. In order to highlight variants, for each sample the frequencies of each bases at each amplicon position were then compared to those observed in the set of controls. Statistical analyses were performed with the R statistical software (http://www.R-project.org). Fisher’s exact two-sided tests with a Bonferroni correction were performed to compare percentages of bases between the data sets, i.e. for a given base between a case and the controls. Finally, significant variations were filtered-in once (i) a significant increase in the percentage of avariant base and (ii) a significant decrease in the percentage of it's reference base following our p.values criteria was observed (p.val < 0.05).

  Study EGAS00001001184

• Age-specific nasal epithelial responses to SARS-CoV-2 infection : GEX

  In this study, we investigate differences in the cellular landscape and functionality of ex vivo cultured nasal epithelial cells in response to SARS-CoV-2 infection across different age groups: paediatric (<12y), adult (30-50y), and older adults (>70y). We unravel, that while ciliated cells serve as primary sites for viral replication consistently across all age groups, a distinctive goblet inflammatory subtype emerges in infected paediatric cultures, characterized by heightened expression of interferon-stimulated genes and incomplete viral replication. Conversely, older adult cultures infected with SARS-CoV-2 exhibit a proportional surge in basaloid-like cells, which not only facilitate viral dissemination but also demonstrate associations with altered epithelial repair pathways.

  Dataset EGAD00001015345

• GoT2D: Genetics of Type 2 Diabetes, a study of the the genetic architecture of type 2 diabetes

  The GoT2D study includes ~2800 samples, half T2D cases and half T2D controls, of Northern European ancestry sequenced over 3 three technologies: deep whole exome sequencing, low-pass (4x) whole genome sequencing, and OMNI 2.5M genotyping. Samples were ascertained to be phenotypically "extreme" (e.g. leaner, younger cases and older, more obese controls). Genotypes (SNVs, INDELs, and SVs) were called separately for each technology and then integrated via genotype refinement into a single phased reference panel; samples and variants were then excluded based on QC procedures described in Fuchsberger et al. Please note that 2 of the samples in the GoT2D vcf do not have phenotype data.

  Dataset EGAD00001002247

• MorphoITH: A Framework for Deconvolving Intra-Tumor Heterogeneity Using Tissue Morphology

  The ccRCC-ITH study WES dataset is derived from a morphology guided multi-regional sequencing dataset used to study the relationship between morphology and genetic evolution. It contains whole exome sequencing data of 18 tumor and 2 adjacent normal samples from 2 UTSW patients, who have consented to depositing their genomic data to public repository. Tumor samples come from different tumor sites, including primary tumor, thrombus and metastases. WES was performed using 75bp paired-end fragments at an average read depth > 50x on a NovaSeq 6000 platform (Illumina, San Diego, CA, USA). The raw data is in fastq format.

  Dataset EGAD50000001550

• RNA004 DRS METTL5 variant of patient sample

  This dataset contains RNA004 DRS data for a single patient sample with heterozygous inactivating SNPs for the methyltransferase METTL5. We provide 1) all reads in a GRCh38 aligned bam file + unaligned reads and 2) filtered reads just for the relevant part of chrR. Both bam files have been called with dorado 0.7.2 to contain the neccessary m6A methylation information. Companion datasets are 1) EGAS50000001201 for DRS of a healthy control with intact METTL5 and 2) PRJEB74238 for IVT 18S rRNA vector data as unmodified control. Please note, that both the companion datasets contain pod5 data, to faciliate re-basecalling.

  Dataset EGAD50000001882

• Single-cell RNA-sequencing of CD19 Chimeric Antigen Receptor (CAR) T-cells (CD19 CAR T-cells) from a Phase I clinical study in paediatric ALL: CARPALL

  Chimeric antigen receptor (CAR)-modified T-cells have become established as an effective treatment of haematological cancers. In the context of relapsed and refractory childhood pre-B cell acute lymphoblastic leukaemia (B ALL), CD19 targeting CAR T-cells often induce durable remissions. Previously, we generated a novel low-affinity CAR incorporating a CD19-specific single-chain variable fragment (scFV) called CAT, displaying a faster off-rate of interaction than the FMC63 CD19 binder used in prior clinical studies. Here, we systematically analysed CD19 CAR T-cells of ten children with relapsed or refractory B ALL enrolled in the CARPALL trial (NCT02443831). To characterize persisting CD19 CAR T-cells, we performed high throughput single-cell gene expression and T-cell receptor (TCR) sequencing of infusion products and serial blood and bone marrow samples up to five years post-infusion. We isolated CAR T-cells from peripheral blood or bone marrow by flow cytometry for CD3 and CAR expression, prior to single cell sequencing (Chromium 10X) platform.

  Dataset EGAD00001010018

• WGS and RNA-Seq data from a GBM patient PT-GJ3716

  WGS and RNA-Seq data from a GBM patient PT-GJ3716

  Dataset EGAD00001004240

• Genome-wide association study of response to warfarin in a UK prospective cohort

  Genome-wide association study of Warfarin dosing in 714 British, recruited in Liverpool and Birmingham. Three phenotypes were investigated: warfarin mean dose, warfarin mean stable dose, and INR over 4 during first week of treatment. Stability was defined by at least three INR measurements within target in a three week period. The samples were genotyped on the Illumina 610K chip and imputed using Impute v2.1, with a combined filtered set composed of HapMap 3 release 2 and 1000 genomes pilot 1 CEU.

  Study EGAS00001001130

• Correlative Studies for Protocol #14-C-0059: T Cells Expressing an Anti-GD2 Chimeric Antigen Receptor in Patients with GD2+ Solid Tumors, a Collaboration with CIMAC-CIDC

  This study is a retrospective correlative analysis of immune cell phenotypes in samples from a Phase I clinical trial (NCT02107963) of GD2 CAR-T cells (GD2-CAR.OX40.28.z.iC9) in children and young adults with osteosarcoma and neuroblastoma. The study was a 3+3 dose-escalation study with four dose levels (1 x 10(5) transduced T cells/kg; 1 x 106 transduced T cells/kg; 3 x 106 transduced T cells/kg; and 1 x 107 transduced T cells/kg). Apheresis and final manufactured GD2 CAR-T product samples were analyzed by bulk RNA sequencing and ATAC sequencing. The patients were stratified into good CAR-T expanders (peak CAR-T expansion >1000 GD2 CAR copies/100ng DNA) and poor CAR-T expansion (peak CAR-T expansion Increased naïve T cell subsets in baseline apheresis are associated with patients who experienced good CAR T cell expansion A T cell exhaustion signature was observed in the manufactured GD2 CAR-T product and may have contributed to lack of efficacy observed in this trial Increased myeloid-derived suppressor cell (MDSC) signatures were observed in patients with poor CAR-T expansion CAR-T product in good expanders displayed increased AP-1 factor transcription factor motifs, such as BATF, JUN, and FOS Data provided in dbGaP for this study include: Bulk RNA-Seq data for 11 pre-treatment peripheral blood and 11 GD2 CAR-T product from 14 patients. ATAC sequencing of 22 peripheral blood samples and 5 GD2 CAR-T products from 14 patients.

  Study phs003455