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• eMERGE Genome-Wide Association Studies of Obesity (Metabochip)

  The Geisinger eMERGE Genome Wide Association Studies of Obesity (Metabochip) Project is a genetic study of a cohort of primarily Caucasian patients with extreme obesity who have undergone bariatric surgery. Roux-en-Y gastric bypass (RYGB) surgery, in which intestinal anatomy is altered, dramatically ameliorates and/or eliminates Type 2 diabetes mellitus (T2D) in 50-80% of patients within hours to days following surgery, well before significant weight loss, in contrast to other types of bariatric surgeries, such as gastric banding, that attenuate insulin resistance as a result of substantial weight loss that occurs over months to years. The molecular mechanism by which RYGB exerts this clinical phenomenon is not known. The goal of this project was to conduct a genome wide association study (GWAS) to identify genetic variants associated with amelioration in T2D defined by medication independence. Identifying genetic variants that influence the dramatic resolution of T2D from RYGB may identify novel targets for pharmacological T2D therapies and/or identify patients in whom RYGB may not be effective.

  Study phs000380

• eMERGE Genome-Wide Association Studies of Obesity

  The Geisinger eMERGE Genome-Wide Association Studies of Obesity Project is a genetic study of a cohort of primarily Caucasian patients with extreme obesity who have undergone bariatric surgery. Roux-en-Y gastric bypass (RYGB) surgery, in which intestinal anatomy is altered, dramatically ameliorates and/or eliminates Type 2 diabetes mellitus (T2D) in 50-80% of patients within hours to days following surgery, well before significant weight loss, in contrast to other types of bariatric surgeries, such as gastric banding, that attenuate insulin resistance as a result of substantial weight loss that occurs over months to years. The molecular mechanism by which RYGB exerts this clinical phenomenon occurs is not known. The goal of this project was to conduct a genome-wide association study (GWAS) to identify genetic variants associated with amelioration in T2D defined by medication independence. Identifying genetic variants that influence the dramatic resolution of T2D from RYGB may identify novel targets for pharmacological T2D therapies and/or identify patients in whom RYGB may not be effective.

  Study phs000408

• Synthetic - FEGA Sweden Heilsa synthetic dataset December 2023

  Synthetic - This submission contains a subset of a synthetic dataset derived from the project Heilsa Tryggvedottir - a Nordic collaboration on sharing sensitive human data. Heilsa Tryggvedottir is funded by the Nordic e-Infrastructure Collaboration (NeIC), the ELIXIR nodes of Finland, Norway, and Sweden, Computerome in Denmark, and the Estonian Scientific Computing Infrastructure (ETAIS). In the synthetic data creation process, it was attempted to strike a fine balance between the usability of the datasets (e.g. technical FEGA development, testing, user training, and basic bioinformatics) and compliance with GDPR. File names and file content (e.g. headers in fastq) are anonymized. Moreover, the X, Y, and mitochondrial sequences have been discarded from the original data since these data can be used for maternal, paternal, or ethnic origin tracing. The dataset does not follow natural haplotype distribution (inherent to imputation panels). The only inputs derived from real sequence data are variant distribution density per chromosome and learning sequencing error models. The synthetic dataset consists of two fastq files, a cram file, a vcf file, and two index files.

  Study EGAS50000000086

• H3Africa H3AChipDesign Phenotype

  Basic phenotypic data (country, ethnicity and sex) for 348 samples of the H3Africa Chip Design Study. Divided into 8 datasets of 41 samples from Zambia, 24 samples from Cameroon, 50 samples from Mali, 26 samples from Cameroon, 49 samples from Nigeria, 48 samples from Botswana, 50 samples from Benin, 60 samples from Burkina Faso and Ghana.

  Dataset EGAD00001005310

• Whole-exome/genome sequencing of childhood acute leukemia in Iraq

  This dataset contains 26 whole-genome sequencing (13 paired tumor and normal), 106 whole-exome sequencing (53 paired tumor and normal), and 43 targeted sequencing data. Sequencing was performed using an Illumina platform. The data are BAM files aligned to the hg19 reference genome.

  Dataset EGAD00001007873

• Emirati Genome Project Population Variome (MAF Table)

  The Emirati Genome Project (EGP) Variome comprises allele frequency data derived from 43,608 individuals sequenced as part of the national genome program in the United Arab Emirates. Samples were processed at the M42 EGP Facility and sequenced to a minimum of 30x coverage using Illumina NovaSeq 6000 short-read technology. Variant calling and alignment were performed using the DRAGEN pipeline (v3.9) against the GRCh38 reference genome. This dataset contains a total of 421,605,069 short variants (SNVs and indels), stored in VCF format. Each variant is annotated with population-level metrics in the INFO field, including: AC (alternate allele count) AF (alternate allele frequency) RC (reference allele count) RF (reference allele frequency) For convenience, VCF files are split by chromosome (chr1–22, X, Y), compressed and indexed using bgzip and tabix.

  Dataset EGAD50000001558

• Whole genome sequencing data of paediatric ETV6-RUNX1 acute lymphoblastic leukemia

  Whole genome sequencing data from paediatric (<18-y) ETV6-RUNX1 fusion positive acute lymphoblastic leukemias. Dataset includes fastq and BAM files from diagnostic and remission (control) samples of 33 patients. Dataset consists of two experiments depending on sequencing instrument; "Experiment 1" sequenced by using Illumina Hiseq X Ten instrument, and "Experiment 2" Illumina Novaseq 6000, respectively.

  Dataset EGAD00001010128

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 17)

  The dataset contains whole genome sequencing data of 26 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 86 samples are either fresh frozen tumour samples or blood samples. The files provided are paired fastq files.

  Dataset EGAD50000002409

• MUSIC: Long-TerM OUtcomes after the Multisystem Inflammatory Syndrome In Children

  This study is an observational cohort study that will use routinely-collected clinical and cardiac (EKG, echocardiogram, CMR, exercise testing) data to assess the association between MIS-C (multisystem inflammatory syndrome in children) and cardiac outcomes within the first year after hospital discharge. Research funding will be available for EKGs, echocardiograms and MRIs in protocol windows that are not ordered by primary caregivers. Our principal goal is to determine the spectrum and early time course of coronary artery involvement, LV systolic function, and arrhythmias or conduction system abnormalities, and, using these data, to define associated clinical and laboratory factors. We will include all eligible patients, including retrospective cases beginning January 1, 2020, with follow-up (in-person or telehealth) up to one year and annual medical history forms until up to 5 years have elapsed since illness onset. Because many patients will have been identified by retrospective review, we will obtain consent at different times in their illness course. For this reason, it may be hard to reach some patients and their families. Waiver of consent will be obtained after three attempts have been made to locate the patient and family without success, as well as for the rare child who dies before informed consent can be obtained. We will include a HIPAA-compliant cryptographic algorithm to create a sharable “hashed” identifier from patient information. If blood work for research purposes is added to usual clinically-indicated blood work during follow-up visits, this will be covered by other informed consent forms. Our primary outcomes are the largest proximal Left Anterior Descending Coronary Artery (LAD) or Right Coronary Artery (RCA) z score and lowest Left Ventricular Ejection Fraction (LVEF).

  Study phs002770

• Whole genome and transcriptome analysis of a sporadic and recurring parathyroid carcinoma

  Parathyroid carcinoma is an extremely rare endocrine malignancy with an estimated incidence of less than 1 per million population. Excessive secretion of parathyroid hormone, extremely high serum calcium level and the deleterious effects of hypercalcemia are the clinical manifestations of the disease. Up to 60% of patients develop multiple disease recurrences and although long-term survival is possible with palliative surgery, permanent remission is rarely achieved. Molecular drivers of sporadic parathyroid carcinoma have remained largely unknown. Previous studies, mostly based on familial cases of the disease, suggested a potential role for the tumor suppressor MEN1 and proto-oncogene RET in benign parathyroid tumorigenesis while the tumor suppressor HRPT2 and proto-oncogene CCND1 may also act as drivers in parathyroid cancer. Here, we report the complete genomic analysis of a sporadic and recurring parathyroid carcinoma. Mutational landscapes of the primary and recurrent tumor specimens were analyzed using high throughput sequencing technologies. Such molecular profiling allowed for identification of somatic mutations never previously identified in this malignancy. These included single nucleotide point mutations in well characterized cancer genes such as mTOR, MLL2, CDKN2C and PIK3CA. Comparison of acquired mutations in patient-matched primary and recurrent tumors revealed loss of PIK3CA activating mutation during the evolution of the tumor from the primary to the recurrence. Structural variations leading to gene fusions and regions of copy loss and gain were identified at a single-base resolution. Loss of short arm of chromosome 1 along with somatic mis-sense and truncating mutations in CDKN2C and THRAP3, respectively, provide new evidence for the potential role of these genes as tumor suppressors in parathyroid cancer. The key somatic mutations indentified in this study can serve as novel diagnostic markers as well as therapeutic targets.

  Study EGAS00001000484