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• Peripheral blood DNA transcriptomics of ustekinumab treatment response in patients with Crohn's disease

  Data pertains longitudinal transcriptomic data measured from blood obtained from patients with Crohn's disease that were starting treatment with ustekinumab. Samples were obtained prior to treatment and approximately 26 weeks into treatment during response assessment. At response assessment, patients were classified as responders (R) or non-responders (NR) based on a strict combination of endoscopic, biochemical and clinical criteria: ≥50% reduction in the endoscopic SES-CD score, corticosteroid-free clinical remission (≥3 point drop98 in HBI or HBI ≤4 and no systemic steroids) and/or biochemical response (C-reactive protein (CRP) and fecal calprotectin reduction ≥50% or ≤5 mg/L and fecal calprotectin ≤250 µg/g). Modified response was defined as a combination of corticosteroid-free clinical- (HBI ≤4) and biochemical (CRP ≤5 mg/L and/or fecal calprotectin ≤250 µg/g) remission between week 26-52 without treatment change through week 52. Transcriptomic analyses was conducted through RNA sequencing, wherein mRNA was extracted utilizing the QIAsymphony system, converted into cDNA and sequenced in a paired-end format on the Illumina NovaSeq6000 at the Amsterdam UMC Core Facility Genomics, generating a dataset comprising 40 million 150 bp-reads.

  Dataset EGAD50000000386

• COVID-19-Induced Immune Alterations in Infants

  Although previous studies have described some overlap between COVID-19-induced immune alterations in adults and children, no systematic immune profiling studies have been reported in infants. We applied a multidimensional approach to decipher the immune responses to SARS-CoV-2 infected infants (n=26; 10 mild, 11 moderate and 5 severe) and healthy matched controls (n=14). Single-cell RNA-seq profiling (scRNA-seq) of PBMCs revealed alterations in cell composition upon infection, with most cell types demonstrating an interferon-stimulated gene (ISGhi) state. Our findings shed insight into the immune responses to SARS-CoV-2 in the first year of life.

  Study phs002655

• Pre-existing immunity drives the response to neoadjuvant chemotherapy in esophageal adenocarcinoma

  Esophageal adenocarcinoma (EAC) is a highly aggressive tumor. Patients with locally advanced disease undergo neoadjuvant chemotherapy (nCT) before surgery, however fewer than 30% of treated patients achieve a pathological complete response associated with increased 5-year overall survival. We set out to elucidate the mechanisms the response to nCT by multi-dimensional profiling of pre-treatment tumor biopsies and blood samples from EAC patients. In particular we performed whole exome sequencing (WES) and RNAseq on n=26 baseline EAC tumor; two additional EAC samples underwent only WES. WES on matched peripheral blood mononuclear cells (PBMCs) were used as germline control.

  Study EGAS00001007245

• Longitudinal sampling in relapsed and refractory Hodgkin lymphoma

  Ultra-deep next-generation panel-sequencing on 59 FFPE-samples (20 LTR, 26 relapsed (rHL: 11 initial-diagnosis, 15 relapse) and 13 primary-refractory (prHL: 8 initial-diagnosis, 5 progression) from 44 cHL-patients applying a hybrid-capture approach. Data was processed as described in the publication and mark duplicated bam files were uploaded.

  Dataset EGAD50000000210

• Whole Exome Sequencing of paired gDNAs and PPGL tumor DNA from patients with cyanotic congenital heart disease

  Fastq files from Whole Exome Sequencing of 12 paired germline DNA (from blood/saliva) and 14 PPGL tumor DNA (from formalin-fixed paraffin-embedded (FFPE) blocks from surgery) from patients with cyanotic congenital heart disease (CCHD) and pheochromocytoma and paraganglioma (PPGL). Sequencing was performed using the Illumina HiSeq4000.

  Dataset EGAD50000001201

• Sensitive and robust liquid biopsy-based detection of PIK3CA mutations

  Over the last years, the treatment of hormone receptor-positive metastatic breast cancer patients has dramatically changed. Combination strategies attempting to overcome resistance to endocrine therapy such as targeting the PI3 kinase pathway are gaining importance. The phase III SOLAR-1 trial demonstrated the benefit of the addition of alpelisib to fulvestrant, thereby providing further clinical evidence of the increasing importance of PIK3CA testing. Here, we performed a comparison of liquid biopsy and tissue-based detection of PIK3CA mutations in HR-positive metastatic breast cancer patients. Plasma samples and the latest available tumor tissue from 69 patients with metastatic hormone-receptor positive breast cancer were analyzed for PIK3CA hotspot mutations. A high-resolution NGS assay (SiMSen-Seq) was used for plasma samples covering 11 recurrent PIK3CA mutations, used for stratification in SOLAR-1. Additionally, mFAST-SeqS was used to estimate the tumor fractions in the plasma samples. For tumor tissue samples, targeted Ion Torrent NGS was employed. Matched tissue and plasma samples were available from 63 patients. PIK3CA mutations were detected in 46.1% of the tissue samples and in 50.7% of the plasma samples. The variant allele frequency (VAF) ranged from 4.36% to 72.93% with a median of 28.60% in tissue samples, and from 0.28% to 49.85% with a median of 1.17% in plasma samples. The most frequent variants in tissue and plasma were H1047R, E545K, and E542K. We detected at least one of 11 PIK3CA mutations from the SOLAR-1 trial in 51/63 patients, both in tissue and plasma. In 7 patients, such mutations were found only in plasma. In 5 patients, PIK3CA mutations found in tissue were not detectable in ctDNA, 2 of which had a low tumor fraction.Together, in 33/67 plasma samples without detectable PIK3CA mutations, 18 samples had elevated tumor fraction, implicating true negative results. In the remaining 15 patients with low tumor fraction, additional tissue analysis was needed. SiMSen-Seq-based detection of PIK3CA mutations in plasma shows advantageous concordance with the tissue analyses. A combination with an untargeted, mutation-independent approach for detecting ctDNA fractions may confirm a negative PIK3CA result and thereby enhance the performance of the SiMSen-Seq test. This combinatory approach for selecting suitable patients for alpelisib treatment should be validated in larger patient cohorts.

  Study EGAS00001004940

• Whole blood RNAseq from a large ALS case-control study at Univ of Michigan

  This dataset consists of 694 bulk RNA-seq data (sorted aligned BAM files) from whole blood of ALS participants meeting the Gold Coast definition of ALS during their clinical visit (n=422) and healthy controls (n=272) at the University of Michigan (UM). Samples were collected as part of the UM Pranger ALS Clinic between 2011-2021, and prepared either using poly-A selection of rRNA depletion (see Experiments). RNAseq was performed on the NovSeq 6000 S4 at the UM Advanced Genomics Core, resulting in 150bp paired-end reads. Raw reads were trimmed using Cutadapt (v2.3) and aligned to hg38 using STAR (v2.5.3a). Age provided is the age at blood sample collection date.

  Dataset EGAD50000001488

• 10x Genomics raw data of intestinal plasma cells

  The dataset contains raw fastq files (fastq.gz) for Chromium Single Cell 5’ gene expression (GEX), human B cell VDJ and feature barcode (CSP) sequencing from transglutaminase 2-specific and other small intestinal plasma cells isolated from four untreated celiac disease patients. Single cell 5’ gene expression, V(D)J-enriched and cell surface protein libraries were generated using Chromium single cell kits, and barcoded cDNA from a total of 5,000-10,000 cells per sample was generated using the 10x Genomics Chromium Controller. The libraries were pooled prior to sequencing on a NovaSeq 6000 instrument (Illumina) using the following configuration: read 1: 26 cycles, read 2: 89 cycles, index read 1: 8 cycles.

  Dataset EGAD50000000342

• Finnish_population_cohort_genotyping_B

  The FINRISK cohorts comprise the respondents of representative, cross-sectional populationsurveys that are carried out every 5 years since 1972, to assess the risk factors of chronicdiseases (e.g. CVD, diabetes, obesity, cancer) and health behavior in the working agepopulation, in 3-5 large study areas of Finland. DNA samples were collected in the followingsurvey years: 1987, 1992, 1997, 2002, 2007, and 2012. The MONICA and EHES (EU)procedures were applied in phenotype collection (cf. MORGAM) and a wide spectrum oflaboratory tests was carried out from serum and plasma samples. Background information onsocioeconomic status, medical history, diet, exercise, measured anthropometric measures,etc. was collected by questionnaires and during a clinical visit. Plasma/serum samples arestill available for the 2002-2012 cohorts. The cohort sizes are 6000-8800 per survey. Thecohorts have been followed up by linking them to the national hospital discharge register,causes-of-death register and cancer register.This project is an extension to previous efforts to build a catalogue of Finnish genome widedata on population-based Finsrisk samples with rich phenotypic characterisations and healthregistry link-up. These samples will extend the current Sequencing Initiative Suomi (SISu)samples with a combination of genotyping using Illumina HumanCoreExome array and SISu-based imputation. This will lead to high confidence common and low frequency variantcatalogue. The project will be funded by Aarno Palotie’s remaining faculty fundscomplemented by Finnish funding from FIMM.

  Study EGAS00001001047

• Center for Common Disease Genomics [CCDG] - Cardiovascular: Cardiology Biobanking for Biomarker Discovery

  This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1. Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules.Source: https://ccdg.rutgers.edu/sites/default/files/CCDG_CVD_EOAF_FINAL_w_link.pdfThe BioHEART study is a multi-center, prospective, observational cohort study to identify new biomarkers in stable coronary artery disease (CAD) and acute myocardial infarction (MI) (ACTRN12618001322224). Participants are recruited at time of clinically indicated computed tomography (CT) coronary angiogram (CTCA). 1,950 of 5,000 planned participants have been recruited and serum/plasma/erythrocytes/monocytes stored, with follow-up ongoing. CTCA imaging studies provides volumetric quantification of total calcified and non-calcified plaque, which is assessed using established and novel scoring systems. Comprehensive molecular phenotyping is performed on blood samples using state-of-the-art genomic, transcriptomic, proteomics, metabolomic, lipidomic, and immunophenotyping. Outcome data will be used to build improved risk models for CAD.Reference: http://www.anzctr.org.au/ - ACTRN12618001322224

  Study phs002726