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• Associations between APOE status and cognitive ability across the lifecourse

  The association between APOE genotype and cognitive function suggests a positive role for the e2 allele and a negative role for the e4 allele. Both alleles have relatively low frequencies in the general population, hence meta-analyses have been based on many small, heterogeneous studies. Here we report the APOE-cognition associations in the largest single analysis to date. APOE status and cognitive ability were measured in 18,337 participants from the Generation Scotland study between 2006 and 2011. The age range was 18-94 years with a mean of 47 (SD 15). Four cognitive domains were assessed: verbal declarative memory (paragraph recall), processing speed (digit symbol substitution), verbal fluency (phonemic verbal fluency), and vocabulary (Mill Hill synonyms). Linear regression was used to assess the associations between APOE genetic status and cognition. Possession of the e4 allele was associated with lower scores on the measures of memory and processing speed in subjects aged >60. Across all age ranges, the e4 allele was linked to better verbal fluency scores. In younger subjects (≤60 years) the e4 allele was linked to higher vocabulary scores. There were no associations between the e2 allele and cognitive ability. As seen in previous meta-analyses, the APOE e4 allele is linked to poorer cognitive performance in the domains of memory and processing speed. By contrast, positive associations were seen between the e4 allele and measures of verbal fluency and vocabulary. All associations were relatively small and, in many cases, nominally significant despite the very large sample size.

  Study EGAS00001001235

• Multi-Omic Investigation of Beckwith-Wiedemann Syndrome Wilms Tumor

  Wilms’ Tumor (WT), also known as nephroblastoma, is one of the most common malignant kidney tumors diagnosed in children. One of the most common WT predisposition syndromes is Beckwith-Wiedemann Syndrome (BWS, OMIM: 130650), which affects approximately 1/10,000 live births. In this study, we perform Whole Exome Sequencing (WES), DNA methylation array, and messenger RNA-Sequencing (mRNA-Seq), to examine the genomic, methylomic, and transcriptomic signature of BWS WT. We analyzed six tumor-normal paired samples, three BWS tumor only samples, and four non-BWS control samples to identify BWS WT drivers.

  Study phs002769

• Whole genome, whole exome and transcriptome sequencing of 10 ccRCC with Von Hippel-Lindau disease

  The aim of this study is to investigate genetic and transcriptomic profiles of inherited ccRCC with Von Hippel-Lindau disease.

  Study JGAS000544

• 16S rRNA Rectal Mucus

  16S rRNA sequencing of rectal mucus samples from patients suspected to have colorectal cancer. This is 1 of 4 sequencing experiments on the same sample type.

  Study EGAS50000001262

• Enzymatic Methyl-Seq Rectal Mucus

  Enzymatic methyl sequencing of rectal mucus samples from patients suspected to have colorectal cancer. This is 1 of 4 sequencing experiments on the same sample type.

  Study EGAS50000001314

• HiChIP data and analysis in OCI-AML3

  Data and analysis of HiChIP assay of shZNF143 and shControl in OCI-AML3. CTCF was the ChIP antibody. Data files are paired-end reads in FASTQ format from the Illumina NovaSeq 6000 sequencer. Analysis files are paired-end bed files produced by FitHiChIP.

  Dataset EGAD50000001376

• Multiomics characterisation of the response to stimulation in Long Covid patients

  We generated 10X, droplet-based paired snRNAseq+snATACseq (Multiome) of the response to P. Aeruginosa or RPMI in patients suffering from Long Covid. In total, we included 15 patients. Single nuclei libraries are genetically multiplexed across donors, genotype files are available to enable demultiplexing. Phenotype sheets provide information of pools/donors as well as donor phenotype.

  Dataset EGAD50000000203

• RNA-Seq of GM adipose tissue samples

  This dataset contains 210 fastq files (RNA sequencing was performed in two centers) from 105 individuals (106 files in subcutaneous tissue and 104 files in visceral tissue). Of the 210 fastq files, 129 files are in PEx100 mode (appeared in a single fastq file) and 81 files are in PEx49bp mode (appeared in two separate fastq files). Sequencing was done on the Illumina HiSeq2000 platform.

  Dataset EGAD00001010253

• UK10K NEURO UKSCZ

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. These samples have been collected from throughout the UK and Ireland. The samples fall into two main categories, approximately 500 have a full diagnostic work up. A proportion of these are cases with a positive family history of schizophrenia, either collected as sib-pairs or from multiplex kindred's. The second group consist mainly of >300 samples that have been systematically collected within South Wales and in addition to full diagnostic work up have undergone detailed cognitive testing. All samples have obtained a DSM IV diagnosis of schizophrenia or schizoaffective disorder.For further information on this cohort please contact Michael Owen (OwenMJ@cardiff.ac.uk).

  Study EGAS00001000123

• Blood Somatic Mutations in TCGA Donors Suffering from Solid Tumors

  Blood somatic mutations identified across 8,530 solid tumor patients in TCGA cohort. We reasoned that low-coverage whole-genome sequencing of blood samples routinely carried out in cancer genomics projects may be repurposed to detect clonal hematopoiesis (CH). Thus, inspired by a previous approach to identify early mutations in the development of the hematopoietic system, we implemented a pipeline to systematically carry out this "reverse" somatic mutation calling on the paired blood/tumor samples. Blood somatic mutations were called using a 'reverse' approach, in which the tumor sample taken from each patient was used as control of their germline genome. Blood somatic mutations are thus detected as variants in the blood (with respect to the human reference genome) that are absent in the tumor sample. The variant calling was carried out in our in house cluster on downloaded blood/tumor BAM files. The matched blood and tumoral BAM files -- masked and deduplicated using GATK -- of 8,530 whole-exome patients were obtained as described above. The variant calling was carried out using Strelka2 (employing default parameters) with the blood sample as the tumoral input and the tumor sample as control (reverse calling). All variants with two or more supporting reads matching the caller PASS filter and with VAF<0.5 were kept. Mutations in lowly mappable regions as defined by the DUST algorithm (k=30) and UMAP68 (36-kmers) were excluded. Contiguous variants were merged into double-base substitutions. Variants with greater frequency across the cohorts than the DNMT3A R882H or JAK2 V617F hotspot in a cohort-specific Panel of Normals and in gnomAD v2.1 were removed. This was equivalent to discarding variants present in these datasets with an allele frequency greater than 0.008 in PoN TCGA and 0.0003 in gnomAD v2.1. Additionally, common SNPs as defined by the dbSNP 151 Common UCSC track and dbSNP were excluded. Mutations within segmental duplications, simple repeats and masked regions as defined in UCSC tracks were also removed. Finally, samples with the mutation count above the 97.5 percentile of the mutation burden across the cohort were deemed unreliable and excluded for further analyses. We call the set of variants obtained after the application of these filters the full set. A more conservative subset of somatic mutations was generated from the full set of blood somatic mutations. To this end, we applied MosaicForecast, a software designed to phase mutations to polymorphisms with the aim of identifying somatic mutations in a small number of cells and also predict mosaicism for the unphased ones with a random forest classifier. As a result, we obtained a subset of mosaic-phased mutations, and a subset of mutations likely to be somatic (mosaic set).In order to obtain access to this study, please first obtain access to TCGA study (phs000178).

  Study phs002867