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• Extreme phenotypes define epigenetic and metabolic signatures in cardiovascular diseases

  Improving the understanding of cardiometabolic syndrome pathophysiology and its relationship with thrombosis are ongoing healthcare challenges. Using plasma biomarkers analysis coupled with the transcriptional and epigenetic characterisation of cell types involved in thrombosis, obtained from two extreme phenotype groups (obese and lipodystrophy) and comparing these to lean individuals and blood donors, the present study identifies the molecular mechanisms at play, highlighting patterns of abnormal activation in innate immune phagocytic cells and shows that extreme phenotype groups could be distinguished from lean individuals, and from each other, across all data layers. The characterisation of the same obese group, six months after bariatric surgery shows the loss of the patterns of abnormal activation of innate immune cells previously observed. However, rather than reverting to the gene expression landscape of lean individuals, this occurs via the establishment of novel gene expression landscapes. Netosis and its control mechanisms emerge amongst the pathways that show an improvement after surgical intervention. Taken together, by integrating across data layers, the observed molecular and metabolic differences form a disease signature that is able to discriminate, amongst the blood donors, those individuals with a higher likelihood of having cardiometabolic syndrome, even when not presenting with the classic features.

  Dataset EGAD00001005197

• Whole-exome sequencing of hepatocellular carcinoma biopsies

  All 122 HCC biopsies and 115 non-tumoral tissues from 114 patients were subjected to whole-exome sequencing. Whole-exome capture was performed using the SureSelectXT Clinical Research Exome (Agilent Technologies) or SureSelect Human All Exon V6+COSMIC (Agilent Technologies) platforms according to the manufacturer’s guidelines. Sequencing was performed on an Illumina HiSeq 2500 at the Genomics Facility Basel according to the manufacturer’s guidelines. Paired-end 101-bp reads were generated.

  Dataset EGAD00001008182

• 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

• Exome sequencing of UK Birth Cohorts - Born in Bradford

  Birth cohort studies involve repeated surveys of large numbers of individuals from birth and throughout their lives. They collect information useful for a wide range of life course research domains, and biological samples which can be used to derive data from an increasing collection of omic technologies. This rich source of longitudinal data, when combined with genomic data, offers the scientific community valuable insights from population genetics to rare disease associations. Avon Longitudinal Study of Parents and Children (ALSPAC)recruited 14,775 babies of predominantly White ethnicity in the Avon county of south-west England between 1991 and 1992. Born in Bradford (BiB) is similarly focused on a particular local area, the city of Bradford in the north of England, and recruited 13,858 babies between 2007 and 2011, of whom ~41% self-report as white British and ~59% as other ethnicities, predominantly Pakistani. Millennium Cohort Study (MCS) is a national cohort that recruited 18,827 children born between 2000 and 2002, intentionally over-sampling areas with high child poverty, large ethnic minority populations, and smaller UK nations (Wales, Scotland and Northern Ireland) Available here is a subset of exome-sequenced parents and children from these studies (CRAMS and post-QC VCFs) as detailed in https://doi.org/10.12688/wellcomeopenres.22697 [doi.org]. Phenotypic data is also available by submitting an application to the corresponding cohort: https://borninbradford.nhs.uk/ [borninbradford.nhs.uk]

  Dataset EGAD00001015370

• Exploring the driver events of eccrine poromas and porocarcinomas: A retrospective, cross-institutional study of 90 cases

  Eccrine poroma (EP) and porocarcinoma (EPC) are rare benign and malignant adnexal neoplasms of the terminal sweat gland duct, respectively. Both can arise de novo, however, EPCs can also arise from a pre-existing EP. To-date, genetic investigation of these tumors has involved studies with small sample sizes and/or limited analyses. To comprehensively compare the driver events and mutational landscape of these tumors, we performed a retrospective multi-institutional whole-exome sequencing and RNA sequencing study on the largest cohort of EPs and EPCs to-date (n=90). We uncovered novel events and delineated different pathways of tumorigenesis underlying these tumors, with EPs driven largely by fusion genes, and EPCs driven largely by somatic mutations, with rare YAP1 and frequent PAK gene novel fusions.

  Dataset EGAD00001015376

• Exploring the driver events of eccrine poromas and porocarcinomas: A retrospective, cross-institutional study of 90 cases

  Eccrine poroma (EP) and porocarcinoma (EPC) are rare benign and malignant adnexal neoplasms of the terminal sweat gland duct, respectively. Both can arise de novo, however, EPCs can also arise from a pre-existing EP. To-date, genetic investigation of these tumors has involved studies with small sample sizes and/or limited analyses. To comprehensively compare the driver events and mutational landscape of these tumors, we performed a retrospective multi-institutional whole-exome sequencing and RNA sequencing study on the largest cohort of EPs and EPCs to-date (n=90). We uncovered novel events and delineated different pathways of tumorigenesis underlying these tumors, with EPs driven largely by fusion genes, and EPCs driven largely by somatic mutations, with rare YAP1 and frequent PAK gene novel fusions.

  Dataset EGAD00001015377

• MethylScan data of plasma samples

  10ng from each cfDNA sample was used as the input material. For gDNA samples, 1.5-2ug each was first sonicated by Covaris R230 system (Woburn, MA). Next, size-selection with 0.8x-1.5x two-step Ampure XP beads was performed to enrich the 150-200bp fragments. 200ng of the size-selected gDNA was used as input material. The pre-capture library construction was performed with NEB UltraII DNA library prep kit for Illumina (Ipswich, MA) and the adapter was the methylated EM-seq adapter. Before the first PCR amplification, the gDNA samples were subjected to bisulfite conversion by QIAGEN Epitect kit, and cfDNA samples were subjected to enzymatic conversion by NEBNext enzymatic methyl-seq kit if the hybrid capture panel designed for converted DNA was used downstream. Twist panel hybrid capture was performed with their standard protocol (Twist Bioscience, South San Francisco, CA). The concentration of the post-capture library after the second PCR amplification was measured by Qubit 1xdsDNA HS kit (ThermoFisher, Waltham, MA). Their quality was examined by TBE-UREA PAGE and Bioanalyzer before sequencing. Libraries were then sequenced with 150bp paired-end reads on Illumina machines by Genewiz, Inc. (South Plainfield, NJ, USA). This dataset contains MethylScan data of the plasma samples from 248 noncancer individuals and 27 cancer patients (17 liver and 10 GI-tract cancers).

  Dataset EGAD00001015815

• Data generated by the Drier Lab at HUJI

  This Data Access Committee is responsible to all data generated by and deposited by the Drier Lab at the Faculty of Medicine of the Hebrew University of Jerusalem (http://yotamdrier.ekmd.huji.ac.il/)

  Dac EGAC50000000060

• Data Access Committee for Translational analyses from a phase II study of pembrolizumab and epigenetic modification with azacitidine in platinum-resistant epithelial ovarian cancer

  This DAC is responsible for request review and handling related to the study above.

  Dac EGAC50000000697

• Haukeland University Hospital Data Access Committee for STRAT-PARK datasets archived in Federated EGA Norway

  This is the Data Access Committee mandated by Haukeland University Hospital for the STRAT-PARK cohort: an initiative to stratify Parkinson's disease.

  Dac EGAC50000000428

• Picuris Pueblo Genomic Project – Modern Dataset

  Please refer to the Supplemental Materials of the paper for more information.

  Dataset EGAD50000001245

• WES

  Whole Exome Sequencing data from Lauss et al Nat Comm 2024. Molecular patterns of resistance to immune checkpoint blockade in melanoma.

  Dataset EGAD50000000380

• TCRseq

  TCRseq data from Lauss et al Nat Comm 2024: Molecular patterns of resistance to immune checkpoint blockade in melanoma.

  Dataset EGAD50000000379

• MalariaGEN_Gambia-HLA_typing

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations: Gambian trio HLA typing

  Dataset EGAD00010001818

• MalariaGEN_GWAS-2.5M_b37_aligned_phased

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations: phased genotypes

  Dataset EGAD00010001748

• Tanzania_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:Tanzania

  Dataset EGAD00010001743

• Kenya_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:Kenya

  Dataset EGAD00010001742

• Malawi_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:Malawi

  Dataset EGAD00010001741

• Cameroon_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:Cameroon

  Dataset EGAD00010001740

• BurkinaFaso_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:BurkinaFaso

  Dataset EGAD00010001739

• Gambia_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:Gambia

  Dataset EGAD00010001738

• Mali_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:Mali

  Dataset EGAD00010001737

• Nigeria_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:Nigeria

  Dataset EGAD00010001736

• PNG_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:PNG

  Dataset EGAD00010001735

• Ghana_GWAS-2.5M_b37_2019

  EGAS00001001311: Genome-wide study of resistance to severe malaria in eleven worldwide populations:Ghana

  Dataset EGAD00010001734