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• NIDDK⁄CIDR Inflammatory Bowel Disease Genetics Consortium (IBDGC) Genome Wide Association Study in Familial Crohn's Disease

  The National Institute of Diabetes and Digestive and Kidney Diseases Inflammatory Bowel Disease Genetics Consortium (NIDDK - IBDGC) conducted a genome wide association study (GWAS) using the Human Omni2.5-Quad beadchip from Illumina to identify disease variants associated with familial Crohn's disease. This study includes a subset of individuals from an original cohort of affected subjects and affected/unaffected relatives from a previous linkage scan which showed increased linkage evidence at three novel risk loci. A total of 708 samples were selected based on various criteria for inclusion from the 6 Genetic Research Centers (GRC) in North America that participate in the IBDGC. This project was supported by an ancillary R01 grant from the NIDDK with resources made available through the IBDGC.

  Study phs000367

• Oesophageal adenocarcinoma RNAseq from LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19)

  This dataset contains bulk transcriptomes from the inoperable cohorts of the LUD2015-005 study (NCT02735239, EudraCT 2015-005298-19). Transcriptomes were prepared from pre-treatment oesophageal tumour biopsies using a ribodepletion approach in order to assess both previously reported (e.g. PD-L1 expression) and novel predictive expression-based biomarkers for immunochemotherapy treatment in this setting. On-treatment and post-treatment biopsies were generated as well to characterize response to therapy, and samples were also prepared from paired normal GI tissues for a subset of patients. scRNA-seq based deconvolution was also applied to bulk transcriptomes in this study to estimate the cell composition of tumour biopsies and assess the link between the presence of specific cell types with immunochemotherapy outcomes.

  Dataset EGAD00001009399

• Plasma MicroRNA Signatures of Aging

  Background. MicroRNAs are small non-coding RNAs that regulate gene expression post-transcriptionally and show differential expression in various tissues with aging phenotypes. Detectable in circulation, extracellular microRNAs reflect (patho)physiological processes and hold promise as biomarkers for healthy aging and age-related diseases. This study aimed to explore plasma extracellular microRNAs as biological aging indicator and their associations with health outcomes using population-level data. Methods. We quantified plasma expression levels of 2,083 extracellular microRNAs using targeted RNA-sequencing in 2,684 participants from the population-based Rotterdam Study cohort. The training and test sets included 1,930 participants from the advanced-aged initial and second subcohort (RS-I/RS-II; median age: 70.6), while the validation set comprised 754 participants from the middle-aged fourth subcohort (RS-IV; median age: 53.5). Based on 591 microRNAs well-expressed in plasma, we examined differential expression of microRNAs with chronological age, PhenoAge –a composite score of age and nine multi-system blood biomarkers–, the frailty index, and mortality. Next, elastic net models were employed to construct composite microRNA-based aging biomarkers predicting chronological age (mirAge), PhenoAge (mirPA), frailty index (mirFI), and mortality (mirMort). The association of these aging biomarkers with different age-related health outcomes was assessed using Cox Proportional Hazard, linear regression, and logistic regression models in the test and validation sets. Results. We identified 188 microRNAs differentially expressed with chronological age within the RS-I/RS-II advanced-aged population (ntraining=1158, ntest=772), of which 177 microRNAs (94.1%) were replicated in the middle-aged RS-IV subcohort (nvalidation=754). Moreover, 227 miRNAs showed robust associations with PhenoAge, 61 with FI, and 16 with ten-year mortality independent of chronological age. Subsequently, we constructed four plasma microRNA-based aging biomarkers: mirAge with 108, mirPA with 153, mirFI with 81, and mirMort with 50 miRNAs. Elevated scores on these microRNA-based aging biomarkers were associated with unfavorable health outcomes, including lower subjective physical functioning and self-reported health and increased mortality and frailty risk, but not with first- or multi-morbidity. Overall, larger effect estimates were observed for mirPA, mirFI, and mirMort compared to mirAge. Conclusions. This study describes distinct plasma microRNA-aging signatures and introduces four microRNA-based aging biomarkers with potential to identify accelerated aging and age-related decline, providing insights into the intricate process of human aging.

  Study EGAS00001008117

• Exome data: Histone mutations in human Pre-Leukemic HSC and AML

  Exome sequencing was performed on samples from patients 064, 105, and 8760, including the remission sample for 105. Exomes were captured using the Agilent SureSelect All Exon kit v5 kit and libraries sequenced on HiSeq 2000 or 2500 or 4000.

  Dataset EGAD00001004436

• WGBS for T-Cell and B-Cell, control and tumor

  WGBS data for 75 paired fastq, spread over 31 samples (4 healthy T-cell, 7 healthy B-cell, 20 B-cell CLL tumors) of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005970

• Sanger sequencing of catalytic-domain encoding exons of tyrosine kinase genes from human endometrial tumor DNAs

  The purpose of the original study was to search for somatic mutations in the tyrosine kinome of serous and clear cell endometrial carcinomas (human). The study was conducted in two phases. Phase 1: A mutation discovery screen, in which ~577 exons encoding the catalytic domains of 86 tyrosine kinases were PCR-amplified and bidirectionally Sanger sequenced from 24 serous, 11 clear cell, and 5 mixed histology endometrial tumors. This was followed by alignment of sequence reads to the human reference sequence and subsequent nucleotide variant calling to identify potential somatic (tumor-specific) mutations. Potential somatic mutations were confirmed by re-amplification and sequencing of the relevant tumor DNA as well as matched non-tumor ("normal") DNA from the same case. Phase 2: A mutation prevalence screen, in which the non-catalytic regions two tyrosine kinase genes, TNK2 and DDR1, were PCR-amplified and sequenced from the 40 discovery screen tumors, and all coding exons of TNK2 and DDR1 were PCR-amplified and sequenced from another 10 clear cell, 21 serous, and 41 endometrioid endometrial tumors, in an effort to identify additional somatic mutations in each gene. Exons encoding the exonuclease domain of POLE were also sequenced to document somatic mutations.

  Study phs000841

• High-throughput single-cell DNA sequencing of acute myeloid leukemia tumors with droplet microfluidics

  We developed a novel microfluidic platform to automatically barcode genomic DNA from individual cancer cells. Using this approach, we sequenced acute myeloid leukemia (AML) tumors targeting up to 62 loci relevant for the disease from thousands of cells. We predict that our platform will enable analysis of heterogeneity in AML and improve stratification and therapy selection.

  Study phs001627

• Pre-neoplastic somatic mutations including MYD88L265P in lymphoplasmacytic lymphoma

  Normal-cell counterparts of solid and myeloid tumors accumulate mutations years before disease onset; whether this occurs in B-lymphocytes prior to lymphoma remains uncertain. In this study, we sequenced multiple stages of the B-lineage in elderly individuals and patients with lymphoplasmacytic lymphoma, a singular disease for studying lymphomagenesis because of high-prevalence of mutated MYD88.

  Study EGAS00001005656

• A Pilot Study Using Next Generation Sequencing in Advanced Cancers: Feasibility and Challenges

  In this study, we used NGS to identify somatic events in advanced stage cancer patients to demonstrate the feasibility for using this approach to improve patient treatment.

  Study phs000657

• Data files for PCGP SJACT WES

  This dataset contains WES files for the SJACT cohort associated with the paper "Genetic landscape of pediatric Adrenocortical Tumor". In this paper, we analyse 37 adrenocortical tumours (ACTs) by whole-genome, whole-exome and/or transcriptome sequencing.

  Dataset EGAD00001002679