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• Next generation sequencing of sporadic schwannomatosis samples

  Schwannomatosis (MIM #162091) is characterized by the development of multiple schwannomas without vestibular nerve involvement (which is a characteristic of neurofibromatosis type 2 - NF2). In an effort to detect novel genetic alterations predisposing to schwannomatosis, we sequenced eight tumor-blood DNA pairs from de novo schwannomatosis patients. The results of our study are present in the paper "Whole exome sequencing reveals that the majority of schwannomatosis cases remain unexplained after excluding SMARCB1 and LZTR1 germline variants" published in Acta Neuropathologica (PMID:25008767)

  Study EGAS00001000767

• Genetic landscape of relapsed DLBCL

  Diffuse large B-cell lymphoma is a heterogenous malignancy that can arise de novo or can result from histologic transformation from indolent lymphomas. Considerable sequencing effort has been placed on determining the mutations that are common at the time of diagnosis in DLBCL but little is known about the nature of relapsed disease. We have sequenced tumour and matched normal exomes of 38 rrDLBCL patients including 25 de novo DLBCLs and 13 transformed lymphomas to identify somatic mutations and copy number alterations associated with relapse.

  Study EGAS00001001553

• Genomic profiling of paediatric glioma cell lines

  Although paediatric gliomas resemble their adult counterparts in many ways, there appear to be distinct clinical and biological differences. One important factor hampering the development of new targeted therapies is the relative lack of cell lines derived from childhood glioma patients, as it is unclear whether the well-established adult lines commonly used are representative of the underlying molecular genetics of childhood tumours. We have carried out a detailed molecular profiling of paediatric glioma cell lines KNS42, SF188, UW479, RES259 and RES186.

  Study EGAS00001003006

• Multiomic profiling of pleomorphic rhabdomyosarcoma

  Rhabdomyosarcoma (RMS) describes rare soft-tissue tumors that exhibit features of skeletal muscle differentiation. The most common subtypes in children are alveolar and embryonal rhabdomyosarcoma, with the alveolar subtype characterized by PAX3/7 fusions. A lesser known and rarer subtype, pleomorphic rhabdomyosarcoma (PRMS), occurs most frequently in adults vetween the ages of 40 and 50. This pleomorphic subtype is often misdiagnosed and little is known about its molecular characterization. Here, we conducted comprehensive genomic, transcriptomic, and methylation profiling of these tumors.

  Study EGAS00001007230

• Genetic Epidemiology of Refractive Error in the KORA (Kooperative Gesundheitsforschung in der Region Augsburg) Study

  KORA ("Kooperative Gesundheitsforschung in der Region Augsburg" which translates as "Cooperative Health Research in the Region of Augsburg") is a population based study of adults randomly selected from 430,000 inhabitants living in Augsburg and 16 surrounding counties in Germany. The collection was done in 4 separate groups from 1984-2001 (S1-S4). One of the KORA groups, S3/F3, will be utilized for our GWAS because it is the only group with refractive error (RE) measurements. Consequent to informed consent, each of the surveys sampled subjects from ten strata according to age (range 25-74 years) and sex (equal ratio) with a minimum stratum size of > 400 subjects. In the KORA S3 study 4,856 subjects were studied between 1994 and 1995, and 3,006 individuals from S3 returned for follow up between 2003 and 2005 (S3/F3). For this refractive error study, we are including 1,981 subjects from S3/F3 (mean age 55.7, range 35-84). For each subject, eyeglass prescriptions were measured in addition to an evaluation by the Nikon Retinomax. Subjects with predisposing medical conditions, i.e., connective tissue disorders, and ocular conditions i.e., cataract and corneal opacities, that might predispose them to refractive error will not be included for genotyping. Whole genome association genotyping will be performed to determine common alleles that contribute to the variation of the quantitative trait of refractive error.

  Study phs000303

• Multi-Site Collaborative Study for Genotype-Phenotype Associations in Alzheimer's disease and Longitudinal follow-up of Genotype-Phenotype Associations in Alzheimer's disease and Neuroimaging component of Genotype-Phenotype Associations in Alzheimer's disease

  GenADA is a multi-site collaborative study, involving GlaxoSmithKline Inc and nine medical centres in Canada, to develop a dataset containing 1000 Alzheimer's disease patients and 1000 ethnically-matched controls in order to associate DNA sequence (allelic) variations in candidate genes with Alzheimer's disease phenotypes. The study consists of both retrospective and prospective components, that is, patients with an existing diagnosis of Alzheimer's disease as well as newly diagnosed patients were enrolled in the study. Thus, clinical data was retrospectively or prospectively obtained on Day 1 of entry into GenADA. Where possible, biological relatives with Alzheimer's (up to third degree relationship such as cousins) and unaffected siblings of AD cases were also recruited. Note that recruitment numbers for biological relatives were lower than expected and genotypic data has not been submitted to dbGap for these subjects. The purpose of this study is: To identify DNA sequence variations (genotype) in candidate genes that are associated with the clinical symptoms and behavioural features of Alzheimer's disease (phenotype), which differ between study participants with and without the disease. To identify other genotype-phenotype associations in cognitively impaired study participants such as age of onset, family history, rate of cognitive decline, patterns of behavioural/psychiatric non-cognitive symptoms factors, response to treatment co-morbid conditions, and risks/exposure. The final subject recruitment for this study included 875 Alzheimer's disease patients, 850 ethnically-matched controls, and 37 family members. GenADA LONG is a longitudinal assessment to the original GenADA study. Eligible subjects were recruited from five of the nine memory clinics that participated in the GenADA study. Mild to moderate AD participants, a matched subset of controls, and biological related siblings (both affected and unaffected) or other blood relatives affected with AD, were initially examined a minimum of 12 months from recruitment into the original GenADA study, then at two further intervals of 12 and 18 months after time of entry into GenADA LONG. This enables an evaluation of the disease progression in AD patients and a determination of whether controls show evidence of cognitive decline. The overall goal of this extension study is to identify genetic differences and environmental influences that modulate the age of onset of the disease, the course of the disease, and/or biomarkers for neurodegenerative processes. Three of the five memory clinics that participated in the GenADA LONG study recruited eligible patients into GenADA Imaging. A concurrent neuroimaging sub-study was conducted at three of the five memory clinics participating in GenADA LONG. Eligible AD cases with mild to moderate AD, who were recruited into the original GenADA study and participated in the GenADA LONG extension study, were enrolled. Additionally, controls that showed signs of cognitive decline, as part of the assessment in GenADA LONG, were imaged at baseline, 12 and 18 month scanning intervals. The objective of this study is to find genes that: affect changes in AD brain volume measure by magnetic resonance in order to investigate how well change in brain volume predicts other key clinical measures in AD, such as neurodegenerative scales; that correlate changes in brain volume for other genotype-phenotype associations in cognitively impaired study participants; and that correlate with other clinically applicable magnetic resonance measures of pathology that can be conducted at the same time as structural volume measures, and are complementary to the volume measures. The ultimate aim of this research is to obtain a better understanding and definition of Alzheimer's Disease in order to develop new improved medicines.

  Study phs000219

• LCLF1.0 Data

  In this study, we investigated ad libitum food intake of 20 healthy adult volunteers who each completed a 4-week stay at the National Institutes of Health (NIH). During their stay, they consumed a low-carbohydrate, high-fat (LCHF) diet and a low-fat, high-carbohydrate (LFHC) diet for 2 weeks each, in random order. We collected information about energy intake and metabolic changes in response to the two test diets. The test diets were presented to subjects in amounts exceeding their daily energy requirements, and subjects were instructed to eat as much or as little of each diet as desired. This study implemented 7-day rotating menus for each test diet. The diets were matched for presented calories and protein, but the LCHF diet was low in carbohydrate (~10% of calories) and high in fat (~75% of calories) whereas the LFHC diet was high in carbohydrates (~75% of calories) and low in fat (~10% of calories). The two test diets had a common foundation of vegetables with low amounts of digestible carbohydrates such as lettuce, spinach, kale, cabbage, cauliflower, zucchini, tomato, asparagus, broccoli, peppers, brussels sprouts, and green beans. The LCHF diet included meat, poultry, fish, eggs, dairy, and nuts. The LFHC diet included legumes, rice, root vegetables, soy products, corn, lentils, peas, whole grains, bread, and fruit. The test diets were designed using a standard computerized nutrition database, and blood samples were collected from the subjects.

  Study phs003187

• UK10K NEURO FSZNK

  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. This Finnish schizophrenia sample set has been collected from a population cohort using national registers. The entire sample collection consists of 2756 individuals from 458 families of whom 931 are diagnosed with schizophrenia spectrum disorder. Families outside Kuusamo (n=288) all had at least two affected siblings. All diagnoses are based on DSM-IV and for a large fraction of cases there is cognitive data.For further details/descriptions with regard to this data set please contact Tiina Paunio (tiina.paunio@thl.fi)

  Study EGAS00001000119

• Bulgarian Trio Sequencing Study to Identify de Novo Mutations in Schizophrenia

  The primary aim of this study is to whole exome sequence complete Bulgarian trios to identify de novo mutations in schizophrenic probands. We are investigating the rate of de novo mutations in probands as well as looking for enrichment among previously implicated genes and synaptic gene sets.

  Study phs000687

• Drug development for pediatric cancers: the importance of patient' s genomic data re-use

  Cancer in children is uncommon and the overall prognosis for most pediatric cancers is good. However, while the combined survival rates have improved over the last decades, certain childhood malignancies, such as high-grade gliomas or metastatic sarcomas, still remain incurable in most patients. New strategies for targeting those devastating diseases are imperative, and patient genomic data can become a key asset in the process [1]. The Pediatric Cancer Genome Project’s datasets At EGA, we store over 500 datasets with sequencing data from pediatric cancer patients. A remarkable case is the datasets belonging to the Pediatric Cancer Genome Project (PCGP) from St. Jude Children’s Research Hospital–Washington University (Table 1 - EGAS list). PCGP is an ambitious effort to identify the mutations that drive childhood cancer and find new cures. Those datasets include 600 patients with complete tumor and normal genomes from 15 different tumor types. PCGP datasets have been an important resource for various studies that pooled genomic data from different public and in-house datasets to perform extensive genomic characterizations and publish comprehensive pan-cancer pediatric studies [2],[3]. Other interesting pediatric cancer datasets are from the Pediatric Brain Tumor Consortium, Sickkids or ICGC PedBrain project. How data reuse impacts drug development for pediatric cancers Recently, in October 2024, Nature Communications published a work led by the University of Michigan where authors used data from EGA (PCGP) check the table below as part of their strategy to pursue the identification of new tumor vulnerabilities susceptible to becoming novel therapeutic targets in diffuse midline glioma. Diffuse midline gliomas (DMG) are treatment-resistant and uniformly fatal pediatric brain tumors. The prognosis of this brainstem tumor is dismal with a median overall survival of 9–12 months from diagnosis. In this study, the authors first developed a lab model of the disease and reanalyzed data from the EGA to identify genes potentially linked to tumor severity. This approach revealed involvement of specific metabolic pathways, suggesting new possibilities for therapeutic intervention. In mice, the study shows that the use of statins can improve survival. For a brief overview of the underlying science, diffuse midline gliomas present intratumor heterogeneity with subpopulations of less-differentiated oligodendrocyte precursors and more differentiated astrocytes. Authors established in vitro models to recapitulate both phenotypes and identify metabolic programs in both subpopulations. To determine the clinical relevance, the authors re-used gene expression data from 76 DMG patients identifying a gene signature predicting decreased overall survival. After extensive metabolic characterization of subpopulations, authors defined strategies to target specific metabolic vulnerabilities. Pre-clinical experiments in mice using OXPHOS inhibitors and statins showed a reduction in tumor burden and increased overall survival [4]. In this scenario, the re-use of high-quality patient’s sequencing data appeared as an advantageous strategy to support the clinical relevance of in-vitro and pre-clinical findings. On the other hand, in rare conditions such as childhood cancer, the availability of public datasets and the possibility of pooling data from different sources can be the only way to obtain impactful results that lead to improvements for patients. References Davidoff, A. M. Pediatric Oncology. Seminars in pediatric surgery 19, 225–233 (2010). Gröbner, S. N. et al. The landscape of genomic alterations across childhood cancers. Nature 555, 321–327 (2018). Venu Thatikonda et al. Comprehensive analysis of mutational signatures reveals distinct patterns and molecular processes across 27 pediatric cancers. Nature Cancer 4, 276–289 (2023). Mbah, N. E. et al. Therapeutic targeting of differentiation-state dependent metabolic vulnerabilities in diffuse midline glioma. Nature Communications 15, (2024). Datasets and Studies ID Title Access Policy Year EGAD00001000134 Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma McGill-DKFZ Pediatric Brain Tumour Consortium 2016 EGAS0000100192 Somatic Histone H3 Mutations in Diffuse Intrinsic Pontine Gliomas and Non-Brainstem Paediatric Glioblastomas St. Jude Children's Research Hospital - Washington University Pediatric Cancer Genome Project 2017 EGAS00001000575 Whole genome sequencing and whole exome sequencing of DIPG tumors and matched normal tissue The hospital for sick children ("SickKids") 2016 EGAD00001000792 Exome sequencing reads of paediatric glioblastoma McGill-DKFZ Pediatric Brain Tumour Consortium 2016 EGAD00001002006 Whole genome sequencing of paediatric glioblastoma in the ICGC PedBrain project ICGC PedBrain project 2016

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