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• Whole_Genome_sequencing_of_individuals_from_Carlantino__Italy

  This study includes whole-genome sequencing data (at 4x depth) of 100 individuals from an Italian genetic isolate population (Carlantino, abbreviated CARL) of the Italian Network of Genetic Isolates (INGI). The INGI-CARL_SEQ project aims to combine available extensive genetic and phenotypic data to the latest high-throughput genome sequencing technology and ad hoc statistical analysis to identify new rare genetic variants underlying complex traits.

  Study EGAS00001000460

• Pooled Genome-Wide Analysis of Kidney Cancer Risk (KIDRISK)

  Incidence rates of renal cell carcinoma (RCC) are rising and the latest estimates show that it accounts for over 300,000 cases and 120,000 deaths worldwide each year. Mechanisms underlying RCC occurrence are not fully understood and a large part of the disease heritability remains unexplained. The study aimed at augmenting the size of available RCC genome-wide association studies to increase the statistical power to detect genetic variants associated with the disease. The study includes genome-wide genotyping data from RCC cases (n=2,781) and controls (n=2,526) recruited in Western Europe, Central and Eastern Europe, and Australia.

  Study phs001271

• Ribo-depleted RNA-sequencing of II.3, III.1, and III.3

  This datasets contains the Ribo-depleted RNA-sequencing of patients II.3, III.1, and III.3. Libraries were sequenced to a minimum depth of 195 million read pairs (2x75nts) on an Illumina NextSeq500 Midoutput FC.

  Dataset EGAD50000002364

• NHLBI Family Heart Study (FamHS-Visit1 and FamHS-Visit2)

  The Family Heart Study (FamHS) was funded by the National Heart, Lung, and Blood Institute (NHLBI). It was begun in 1992 with the ascertainment of 1,200 families, half randomly sampled, and half selected because of an excess of coronary heart disease (CHD) or risk factor abnormalities as compared with age- and sex-specific population rates (Higgins et al. 1996). The families, with approximately 6,000 individuals, were sampled on the basis of information on probands from four population-based parent studies: the Framingham Heart Study, the Utah Family Tree Study, and two Atherosclerosis Risk in Communities (ARIC) centers (Minneapolis, and Forsyth County, NC). A broad range of phenotypes were assessed at a clinic examination in broad domains of CHD, atherosclerosis, cardiac and vascular function, inflammation and hemostasis, lipids and lipoproteins, blood pressure, diabetes and insulin resistance, pulmonary function, and anthropometry (FamHS Visit 1). Approximately 8 years later, study participants belonging to the largest pedigrees were invited for a second clinical exam (FamHS Visit 2). A total of 2,756 Caucasian subjects in 508 extended families were examined. A two-phase design was adopted for the genome wide association (GWA) study. In phase-1, 1007 subjects were chosen, equally distributed between the upper and lower quartile of age- and sex-adjusted values for coronary artery calcification, assessed by CT scan in Visit 2. These subjects were chosen to be largely unrelated; 34% of the subjects were from unique families, while 200 other subjects had 1 or more siblings selected into the sample, yielding a sample of 465 unrelated subjects. The remaining family members (N=1749) were genotyped in the phase-2 for replication of the top hits from the phase-1. The results presented here represent those for the analysis of the phase-1 case-control sample for variables assessed in FamHS Visit 1 (from 1992 to 1995) and for the variables assessed in FamHS Visit 2 (from 2002 to 2003). All subjects were typed on the Illumina HumMap 550 chip (Phase 1 genotype). Of these, 33 (3.3%) were excluded due to technical errors, call rates below 98%, and discrepancies between reported sex and sex-diagnostic markers. The final sample of 974 subjects have Visit 2 phenotypes, approximately 100 of these do not have Visit 1 phenotypes. There was no significant plate-to-plate variation in allele frequencies. The covariate adjustments were performed separately by sex using cubic polynomial age and clinical centers, and retaining the terms in the stepwise regression analysis that were significant at the 5% level. Extreme outliers (>4 SD from the mean) were set aside, temporarily, for the adjustments. The final phenotypes were computed for all individuals using the best mean regression models and standardizing to 0 mean and unit variance. The FamHS has contributed GWA results in many phenotype domains (antropometric and adiposity, atherosclerosis and coronary heart disease, lipid profile, diabetes and glicemic traits, metabolic syndrome etc) to meta-analyses and various consortia, including Heard-Costa et al. 2009, Köttgen et al. 2010, Teslovich et al. 2010, Nettleton et al. 2010, Lango et al. 2010, Heid et al. 2010, Speliotes et al. 2010, Dupuis et al. 2010, Kraja et al. 2011.

  Study phs000221

• Cancer Biomarkers team at The ICR DAC

  DAC for Cancer Biomarkers

  Dac EGAC50000000200

• Whole_Genome_sequencing_of_individuals_from_Val_Borbera__Italy

  This study includes Phase 2 whole-genome sequencing data (at 4x depth)of 100 individuals from an Italian genetic isolate population (Val Borbera, abbreviated VBI) of the Italian Network of Genetic Isolates (INGI). The INGI-VBI_SEQ2 project aims to combine available extensive genetic and phenotypic data to the latest high-throughput genome sequencing technology and ad hoc statistical analysis to identify new rare genetic variants underlying complex traits.

  Study EGAS00001000458

• ATAC-seq

  ATAC-seq data for 26 CLL samples (7 controls, 19 tumor) of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005967

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: kidney (2019-03-26)

  This dataset contains all the data available for this study on 2019-03-26.

  Dataset EGAD00001004867

• Detection of cancers three years prior to diagnosis using plasma cell-free DNA

  A major goal of early cancer detection is to identify subclinical disease when the tumor burden is low, so that treatments are more effective. But how early can cancers be detected prior to clinical signs or symptoms? This question can be answered only through the evaluation of participants whose clinical course has not been altered by the study itself. We here describe such an evaluation, performed on prospectively collected plasma samples from the Atherosclerosis Risk in Communities (ARIC) study, including 26 participants diagnosed with cancer and 26 matched controls. At the index time point, eight of these 52 participants scored positively with a multicancer early detection (MCED) blood test. All eight of these participants were diagnosed with cancer within 4 months after blood collection. In six of these 8 participants, we were able to assess an earlier plasma sample collected 3.1 to 3.5 years prior to clinical diagnosis. In four of these six participants, the same mutations detected by the MCED test could be identified, but at 8.6 to 79-fold lower levels. These results demonstrate that it is possible to detect circulating tumor DNA (ctDNA) more than three years prior to clinical diagnosis, and provide benchmark sensitivities required for the success of ctDNA-based tests for this purpose.

  Study EGAS00001008068

• Variables of diversity, clonality, V and J usage and main COVID-19-reactive GLIPH2 frequencies.

  Main results of the T cell repertorie analysis of a cohort of 61 patients. For each patient, repertorie diversity and clonality metrics, V an J alelle frequency and COVID-19-reactive sequencies have been calculated using open.source code. For more information about the study, please visit DOI: 10.1186/s40246-024-00654-0

  Study EGAS50000000587