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• National Institute of Arthritis and Musculoskeletal and Skin Diseases and Istanbul Faculty of Medicine Genome-wide Association Study of Behçet's Disease (Turkish)

  IntroductionBehçet's disease (BD) is a genetically complex multisystem disease of unknown etiology, characterized by recurrent inflammatory attacks affecting orogenital mucosa, eyes, skin, joints, blood vessels, and less frequently, the central nervous system and gastrointestinal tract. Family studies suggest a genetically complex contribution to BD. With the exception of HLA-B51, which explains less than 20% of the genetic risk, the identities of alleles that are responsible for the complex inheritance of this disease have remained unclear. AimTo identify genes that contribute to BD susceptibility. MethodsA genome-wide association study was undertaken with 311,459 informative and high quality SNPs in a collection of 1215 BD patients and 1278 healthy controls from Turkey using a beadchip microarray assay (Infinium SNP genotype assay, Illumina). HLA-B types were determined with a reverse sequence-specific oligonucleotide method (One Lambda). Regions with evidence for association were fine-mapped using Sequenom iPLEX gold assays. Disease-associated SNPs were genotyped in additional ethnically matched case/control collections from diverse genetic backgrounds, including a total of 2430 cases and 2660 controls, using TaqMan SNP genotype assays. Association data were combined in a meta-analysis of all the collections. ResultsWe confirmed the known association with HLA-B51 and found evidence for a second, independent susceptibility locus in the Class I region of the MHC. In addition, we identified one SNP with genome-wide evidence for disease association (P < 5.0 x 10-8) within the gene encoding the immunoregulatory cytokine, interleukin-10 (IL10). A meta-analysis of the data from all the collections established associations with the IL10 variant (rs1518111, P = 3.54 x 10-18, odds ratio 1.45 with 95% confidence interval 1.34 to 1.58) and with a variant located between the interleukin-23 receptor (IL23R) and interleukin 12 receptor β2 (IL12RB2) genes (rs924080, P = 6.69 x 10-9, odds ratio 1.28 with 95% confidence interval 1.18 to 1.39). The disease-associated IL10 variant was associated with diminished mRNA expression and low protein production by cells obtained from healthy blood donors. ConclusionsThese data suggest that genetically encoded low production of IL-10 increases risk of BD and suggest novel interventional targets in the IL-10 and IL-23 pathways. Note: The submitted data are the genotypes of the 311,459 SNPs in 1215 cases and 1278 controls.

  Study phs000272

• Circulating Genomic Determinants of Treatment Failure in Hodgkin Lymphoma

  In this study, we show that the plasma representation of mutations exceeds the bulk tumor representation in most cases, making classic Hodgkin Lymphoma (cHL) particularly amenable to noninvasive profiling. Leveraging single-cell transcriptional profiles of cHL tumors, we demonstrate hazard ratios (HRs) circulating tumor DNA (ctDNA) shedding to be shaped by DNASE1L3, whose increased tumor microenvironment-derived expression drives high ctDNA concentrations. Using this insight, we comprehensively profile 366 patients, revealing two distinct cHL genomic subtypes with characteristic clinical and prognostic correlates, as well as distinct transcriptional and immunological profiles. Furthermore, we identify a novel class of truncating IL4R-mutations that are dependent on IL13 signaling and therapeutically targetable with IL4R blocking antibodies. Finally, we demonstrate the clinical value of pre- and on-treatment ctDNA levels for longitudinally refining cHL risk prediction, and for detection of radiographically occult minimal residual disease. Collectively, these results support the utility of noninvasive strategies for genotyping and dynamic monitoring of cHL as well as capturing molecularly distinct subtypes with diagnostic, prognostic, and therapeutic potential.Methods utilized include a) targeted genotyping of baseline plasma samples, b) whole exome sequencing (WES) of baseline plasma samples, c) epigenetic expression inference from cell-free DNA-sequencing (EPIC-Seq) to infer gene expression from cell-free DNA (cfDNA) fragmentation profiles, d) ctDNA tracking in on-treatment samples, e) RNA-Sequencing, and f) Phased variant Enrichment and Detection Sequencing (PhasED-Seq).All patients were treated at cancer centers across Europe and North America between 2011 and 2020. The following 3 cancer centers, Stanford (CA, USA), Bellinzona [Confoederatio Helvetica (CH) or Switzerland], and Leuven (Belgium), were included. The 6 clinical trial collectives included in this study are the Phase III trial AHOD1331 trial (NCT02166463) and the Phase II cHOD17 study (NCT03755804) for enrolled pediatric patients, the Phase III AHL2011 (NCT01358747), the Phase II BREACH trial (NCT02292979), a pilot study evaluating concurrent Pembrolizumab with AVD (Doxorubicin, also known as Adriamycin, Vinblastine, and Dacarbazine; NCT03331341), and a Phase II study evaluating PVAB (Prednisone, Vinblastine, Doxorubicin and Bendamustine; NCT02414568) in older patients (61 years and older). In addition, lymph node specimens from a biorepository at St. Jude Children's Research Hospital (TN, USA) were included.

  Study phs003435

• Molecular_characterization_of_invasive_lobular_carcinoma

  Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer accounting for 10-15% of cases. ILC differs from invasive ductal carcinoma (IDC)with respect to epidemiology, histology, and clinical presentation. Moreover, ILC is lesssensitive to chemotherapy, more frequently bilateral, and more prone to form gastrointestinal, peritoneal, and ovarian metastases than IDCs. In contrast to IDC, the prognostic value ofhistological grade (HG) in ILC is controversial. One of the three major components of histological grading (tubule formation) is missing in ILC which hinders the process of gradingin this histological subtype and results in the classification of approximately two thirds of ILC as HG 2.Over the last decade, a number of gene expression signatures have shed light onto breast cancer classification, allowing breast cancer care to become more personalized. Withrespect to the management of estrogen receptor (ER)-positive breast cancer, several gene expression signatures provide prognostic and/or predictive information beyond what is possible with current classical clinico-pathological parameters alone. Nevertheless, most studies using gene expression signature have not considered different histologic subtypesseparately. Recently, a comprehensive research program has elucidated some of the biological underpinnings of invasive lobular carcinoma. Genetic material extracted from 200 ILC tumor samples were studied using gene expression profiling and identified ILCmolecular subtypes. These proliferation-driven gene signatures of ILC appear to have prognostic significance. In particular, the Genomic Grade (GG) gene signature improved upon HG in ILC and added prognostic value to classic clinico-pathologic factors. In addition this study demonstrated that most ILC are molecularly characterized as luminal-A (~75%)followed by luminal-B (~20%) and HER2-positve tumors (~5%). Moreover, we investigated the prognostic value of known gene signatures/ gene modules in the same cohort of ILC. As a second step within the scope of this project, we aim to investigate the interactionsbetween somatic ILC tumor mutations to observed transcriptome findings. To this end, we aim to perform somatic mutation analysis for the ILC tumors for which Affymetrix gene expression profiling is available. To this end, we will use a gene screen assay, which specifically interrogates the mutational status of a few hundreds of cancer genes. We believe that this pioneering effort will be fundamental for a tailored treatment of ILC withimprovement in patients' outcome.

  Study EGAS00001000292

• Genome_Diversity_in_Africa_Project__Benin

  Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene–disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region.The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group).Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformaticsThis data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001001688

• Multi-omics data of 1000 Inflammatory Bowel Disease patients

  Portal available at https://1000ibd.org Inflammatory bowel disease (IBD) is a chronic complex disease of the gastrointestinal (GI) tract. Patients with IBD can experience a wide range of symptoms, but the pathophysiological mechanisms that cause these individual differences in clinical presentation remain largely unknown. In consequence, IBD is currently classified into subtypes using clinical characteristics. If we are to develop a more targeted treatment approach, molecular subtypes of IBD need to be discovered that can be used as new drug targets. To achieve this, we need multiple layers of molecular data are generated from the same IBD patients.We initiated the 1000IBD project to prospectively follow more than 1000 IBD patients from the Northern provinces of the Netherlands. For these patients, we have collected a uniquely large number of phenotypes and generated multi-omics profiles. To date, 1,215 participants have been enrolled in the project and enrolment is on-going, with 609 patients being present in the first data release. Phenotype data collected for these participants includes information on dietary and environmental factors, drug responses, and adverse drug events. Genome information has been generated using genotyping (ImmunoChip, Global Screening Array and HumanExomeChip) and sequencing (whole exome sequencing and targeted resequencing of IBD susceptibility loci), transcriptome information generated using RNA-sequencing of intestinal biopsies and microbiome information generated using both sequencing of the 16S rRNA gene and whole genome shotgun metagenomic sequencing.All molecular data generated within the 1000IBD project will be shared in multiple data on the European Genome-Phenome Archive (www.ega-archive.org). The first data release, will contain basic phenotypes for 609 participants, genotypes of 314 participants, gut microbiome data generated by tag sequencing the 16S gene of feces from 315 participants and intestinal biopsies from 107 participants, and gut microbiome metagenomic sequencing of feces of 355 participants . Future releases will comprise many more additional phenotypes and -omics data layers. 1000IBD data can be used by other researchers as a replication cohort, a dataset to test new software tools, or a dataset for applying new statistical models.

  Study EGAS00001002702

• RNA_Seq_in_Patients_with_Primordial_Dwarfism

  Transcriptome studies in patients with rare genetic diseases can potentially aid in theinterpretation of likely causal genetic variation through identification of altered transcriptabundance and/or structure. RNA-Seq is the most sensitive assay for both investigatingtranscript structure and abundanceThe primary aim of this pilot project is to investigate to what degree integrating exome-Seqand RNA-Seq data on the same individual can accelerate the identification of causal allelesfor rare genetic diseases. There are two main strands to this: (i) identifying which variantsdiscovered in exome-seq appear to be having a functional impact on transcripts, and (ii)identifying transcript outliers, especially among known causal genes, that may not necessarilyhave a causal variant identified from exome sequencing. The latter may identify the presenceof causal variants that lie far from coding regions (e.g. the formation of cryptic splice sitesdeep within introns, or loss of long range regulatory elements), which can be confirmed withfurther targeted genetic assays. Just over 50% of all disease-causing variants recorded in theHuman Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g.nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs).This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients withprimordial dwarfism syndromes, for 10 of these samples we have previously generate exomedata as part of our collaboration with the group of Prof Andrew Jackson. The two remainingsamples are positive controls where the causal mutation is known, and is known to affecttranscript structure and/or abundance.Primordial dwarfism is a prime candidate for these RNA-seq studies because all knowncausal mutations to date have key roles in DNA replication and thus, unsurprisingly, theproducts of the causal genes are typically ubiquitously expressed.Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) persample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001000283

• Exploring high-throughput drug sensitivity testing in neuroblastoma cell lines and patient-derived tumor organoids in the era of precision medicine

  Despite druggable events in 80% of neuroblastoma patients within the Princess Máxima Center precision medicine program 'iTHER', clinical uptake of treatment recommendations has been low, and the clinical impact for individual patients remains hard to predict. This stresses the need for a method integrating genomics and transcriptomics with functional approaches into therapeutic decision making. We aimed to launch an online repository integrating genomics and transcriptomics with high-throughput drug screening (HTS) of nineteen commonly used neuroblastoma cell lines and fourteen generated neuroblastoma patient-derived organoids (NBL-PDOs) to improve identification of molecularly matched therapies and support clinical uptake. Cell lines, NBL-PDOs and their parental tumors were characterized utilizing (lc)WGS, WES and RNAseq. Cells were exposed to a ~200 compound library, and viability was assessed using CellTiterGlo or MTT. Molecular and HTS results were transferred to the R2 platform (http://r2platform.com/pmc_nb_drugs/), in which a comprehensive suite of visualizations and analysis options were implemented. As a result, a powerful reference set of cell lines is available, reflecting distinct known pharmacologic vulnerabilities, including resistance of TP53-inactivated lines to MDM2 inhibitor idasanutlin; ALK-inhibitor sensitivity in ALK-activated lines, and sensitivity of an ATM-deleted cell line to PARP- and CHEK1-inhibitors. Novel established NBL-PDOs retained molecular features of their parental tumor and again reflected established drug sensitivities. However, HTS also identified additional therapeutic vulnerabilities in vitro, such as a striking correlation between a positive mesenchymal signature and sensitivity to BCL2-inhibitor venetoclax. Finally, we explored personalized drug sensitivities within iTHER, demonstrating HTS can support genomic and transcriptomic results, thereby strengthening the rationale for clinical uptake. Furthermore, in vitro insensitivity may avoid ineffective treatments. Lastly, novel treatment options may be identified, as indicated by sensitivity to ponatinib correlating with overexpression of RET or KIT. In conclusion, we established a dynamic publicly available dataset with detailed genomic, transcriptomic, and pharmacological annotation of classical neuroblastoma cell lines as well as NBL-PDOs, representing the heterogeneous landscape of neuroblastoma. We anticipate that in vitro drug screening will be complementary to genomic-guided precision medicine by supporting clinical decision making, thereby improving prognosis for all neuroblastoma patients in the future.

  Study EGAS00001007160

• CRCbiome: Gut metagenome of Norwegian screening participants using FIT sampling

  The study aims to characterize the gut metagenome of Norwegian screening participants and assess the ability of the gut metagenome to identify those at need for colonoscopy. Background: Colorectal cancer (CRC) screening reduces CRC incidence and mortality. However, current screening methods are either hampered by invasiveness or suboptimal performance, limiting their effectiveness as primary screening methods. To aid in the development of a non-invasive screening test with improved sensitivity and specificity, we have initiated a prospective biomarker study (CRCbiome), nested within a large randomized CRC screening trial in Norway. We aim to develop a microbiome-based classification algorithm to identify advanced colorectal lesions in screening participants testing positive for an immunochemical fecal occult blood test (FIT). We will also examine interactions with host factors, diet, lifestyle and prescription drugs. The prospective nature of the study also enables the analysis of changes in the gut microbiome following the removal of precancerous lesions. Methods: The CRCbiome study recruits participants enrolled in the Bowel Cancer Screening in Norway (BCSN) study, a randomized trial initiated in 2012 comparing once-only sigmoidoscopy to repeated biennial FIT, where women and men aged 50–74 years at study entry are invited to participate. Since 2017, participants randomized to FIT screening with a positive test result have been invited to join the CRCbiome study. Self-reported diet, lifestyle and demographic data are collected prior to colonoscopy after the positive FIT-test (baseline). Screening data, including colonoscopy findings are obtained from the BCSN database. Fecal samples for gut microbiome analyses are collected both before and 2 and 12 months after colonoscopy. Samples are analyzed using metagenome sequencing, with taxonomy profiles, and gene and pathway content as primary measures. CRCbiome data will also be linked to national registries to obtain information on prescription histories and cancer relevant outcomes occurring during the 10 year follow-up period. Discussion: The CRCbiome study will increase our understanding of how the gut microbiome, in combination with lifestyle and environmental factors, influences the early stages of colorectal carcinogenesis. This knowledge will be crucial to develop microbiome-based screening tools for CRC. By evaluating biomarker performance in a screening setting, using samples from the target population, the generalizability of the findings to future screening cohorts is likely to be high.

  Study EGAS50000000170

• HLA-A*3101 and Carbamazepine-Induced Hypersensitivity Reactions in Europeans

  Based on the prior knowledge of involvement of the human leukocyte antigen locus in Han Chinese patients with carbamazepine-induced Stevens-Johnson syndrome, we imputed the HLA types for each case and control subject from the array of SNPs in the Human610-Quad GWAS platform (NCBI Build 36.1). We then performed a genome-wide association test which included the imputed HLA alleles as markers.

  Study EGAS00000000036

• Identification of Recurrent SMO and BRAF Mutations in Ameloblastomas

  RNA-seq data from two cases of ameloblastoma was analyzed for candidate gene fusions and point mutations. Recurrent point mutations identified in the RNA-seq data, as well as mutations identified with limited panel targeted deep sequencing, were validated as somatic. Expanding to a larger cohort of 28, one of two activating mutations was found in 80% of cases. No recurrent gene fusions events were identified.

  Study phs000739