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• Chronic Renal Insufficiency Cohort (CRIC) - GWAS

  The Chronic Renal Insufficiency Cohort (CRIC study) was established in 2001 by the National Institute of Diabetes, Digestive, and Kidney Diseases (NIDDK) to improve the understanding of the relationship between chronic kidney disease and cardiovascular disease. The goals of the CRIC Study are to examine risk factors for progression of chronic kidney disease and cardiovascular disease among patients with chronic kidney disease and to develop predictive models to identify high-risk subgroups, informing future treatment trials and increasing application of available preventive therapies. Data available at dbGaP include genotype data for 3527 participants released in version 1. Plasma metabolomics and plasma proteomics data will be available at dbGaP in "Chronic Renal Insufficiency Cohort (CRIC) Study Metabolomics and Proteomics". Additional phenotypic, clinical, and outcomes data are available at the NIDDK Central Repository and can be linked to data available at dbGaP. More than 330 manuscripts have been published, reporting on the effects of a broad range of risk factors (from molecular biomarkers of disease pathways to clinical, demographic, and behavioral characteristics) on the progression of CKD and other health consequences. The full CRIC bibliography can be found at http://cristudy.org/Chronic-Kidney-Disease/Chronic-Renal-Insufficiency-Cohort-Study/bibliography-2024-2023.

  Study phs000524

• Exome sequencing of a novel cervical cancer cell line

  Human cancer cell lines are largely used in the searching for new antineoplastic agents. However, due to the artifacts of a long-term in culture, cell lines do not always represent the realistic tumor cell behavior. This has motivated the development of models that better mimetics the tumor tissue, among them, the establishment of primary cell cultures. In this work, we establish and characterized a low-passage cervix cancer cell line from a Brazilian patient with squamous cell carcinoma. The phenotype confirms the epithelial and tumor origin, through cytokeratins, EpCAM, and p16 staining. Whole exome sequencing showed relevant somatic mutations in several genes including BRCA2, TGFBR1, and IRX2 genes. CNV analysis by nanostring and WGS revealed amplification in genes related mainly with kinases proteins, involved in proliferation, migration and cell differentiation, such as EGFR, PIK3CA, and MAPK7. Overexpression of EGFR was confirmed by phospho RTK-array and western blot analysis. Furthermore, the cell was sensitivity to cisplatin, with IC50 13 times lower than SiHa cell line. In conclusion, this cervical cancer cell line presents molecular alterations that are an important tool for leading pre-clinical studies of new drugs that target one or more of the altered pathways.

  Study EGAS00001003343

• Hepatocellular Carcinoma Spatial transcriptomics Data Access Committee

  This is the DAC for study ST HCC

  Dac EGAC50000000635

• Genetic Basis of Early Onset Bicuspid Aortic Valve Disease

  The study protocol was approved by the Committee for the Protection of Human Subjects at the University of Texas Health Science Center at Houston (HSC-MS-11-0185). Study recruitment began on July 1, 2017, and concluded on March 30, 2022. After written informed consent, we enrolled probands with early onset BAV disease (EBAV), which we defined as individuals with BAV who were under the age of 30 at the time of first clinical event. Clinical events were defined as aortic replacement, aortic valve surgery, aortic dissection, moderate or severe aortic stenosis or aortic regurgitation, large aneurysm (Z > 4.5), or intervention for BAV-related conditions. Those with hypoplastic left heart, known genetic mutations, genetic syndromes, or complex congenital heart disease were excluded. Samples were collected and genotyped as previously reported. For comparison, we analyzed a cohort of older individuals of European ancestry with sporadic BAV disease selected from the International BAV Consortium (BAVGWAS). Phenotypes were derived from record review with confirmation of image data whenever possible [25-26]. The computational pipeline for CNV analysis of Illumina single nucleotide polymorphism (SNP) array data included three independent CNV detection algorithms.GenomeStudio was used to exclude samples with indeterminate sex or more than 5% missing genotypes, and single nucleotide polymorphisms (SNPs) with GenTrain = 0. Principal component analysis was used to remove outliers that did not cluster with European ancestry. Prior to CNV analysis, each dataset was trimmed by selecting a common set of 650,000 SNPs that were genotyped on each of the microarrays used in this study.Three independent algorithms (PennCNV, cnvPartition, and QuantiSNP) were used to generate CNV calls and sample-level quality statistics from SNP intensity data. PennCNV and QuantiSNP were run on Unix clusters and cnvPartition data were exported from GenomeStudio. The analysis was run using default configurations. PennCNV was used to generate QC data and remove CNV calls that intersect with polymorphic genomic regions. Samples that met any of the following criteria were excluded, standard deviation of the LogR ratio (obtained from PennCNV) > 0.35 or number of CNVs > 2 standard deviations above the mean for each data set. CNV calls less than 20 Kilobases in length and/or spanned by fewer than 6 probes were excluded. The overlap function for rare CNVs in PLINK was used to construct CNV regions (CNVRs) after adjacent regions were merged using PennCNV. LogR ratio (LRR) and B allele frequency (BAF) data at CNVRs and calls of interest were visualized in GenomeStudio for validation. For segregation analysis, GenomeStudio was used to determine the presence of CNVs in relatives.A total of 22,014 unselected control Illumina Genotypes obtained from the Database of Genotypes and Phenotypes were analyzed using identical methods (S1 Table). The Wisconsin Longitudinal Study (WLS) includes data on a cohort of 10,300 individuals who graduated from Wisconsin high schools in 1957. The Health and Retirement Study (HRS) includes data on 37,000 individuals aged 50 above from 23,000 households across the United States. Principal component analysis was used to select European ancestry genotypes from these datasets for analysis. Datasets were paired for case-control analysis based on the concordance of log-transformed sample-level quality control statistics (number of CNV calls and standard deviation of logR ratios). Chi-squared or Fisher exact tests were used to compare CNV frequencies in cases and controls.Rare CNV functions in PLINK (v1.7) were used to perform permutation-based burden tests or gene set-based enrichment tests. Case control burden tests were restricted to CNVs that were longer than 110 Kb and less than 0.1% in frequency. CNV overlap functions in PLINK were used to identify rare CNVs that intersect between datasets or involve specific BAV or CHD genes . The list of candidate genes included 190 CHD genes that have strong cumulative evidence to cause BAV or related congenital malformations from human or animal model data. Genome Reference Consortium Human Build 37 was used for CNV annotation [34].

  Study phs003705

• Whole-Genome Sequencing of a Healthy Aging Cohort.

  Studies of long-lived individuals have revealed few genetic mechanisms for protection against age-associated disease. Therefore, we pursued genome sequencing of a related phenotype-healthy aging-to understand the genetics of disease-free aging without medical intervention. In contrast with studies of exceptional longevity, usually focused on centenarians, healthy aging is not associated with known longevity variants, but is associated with reduced genetic susceptibility to Alzheimer and coronary artery disease. Additionally, healthy aging is not associated with a decreased rate of rare pathogenic variants, potentially indicating the presence of disease-resistance factors. In keeping with this possibility, we identify suggestive common and rare variant genetic associations implying that protection against cognitive decline is a genetic component of healthy aging. These findings, based on a relatively small cohort, require independent replication. Overall, our results suggest healthy aging is an overlapping but distinct phenotype from exceptional longevity that may be enriched with disease-protective genetic factors.

  Study EGAS00001002306

• Fastq files used for searching for variants associated with endometriosis at 9p21 region

  We performed target re-sequencing for 1.29 Mb interval of chromosome 9 (chr9:21299764–22590271, hg19). NimbleGen SeqCap EZ choice system was used as a target enrichment method (Roche Diagnostics). A DNA probe set complementary to the target region was designed by NimbleDesign. The libraries were sequenced on the Illumina MiSeq platform with 2×150-bp paired-end module (Illumina). Fastq files for 48 Japanese patients with endometriosis are deposited.

  Dataset EGAD00001001942

• Development of actionable molecular targets and/or biomarkers for prognostication and patient stratification in gynecological cancer based on whole-exome sequencing and epigenomic analysis

  We collected 92 endometrial hyperplasia lesions (48 non-atypical from 30 cases and 44 atypical from 24 cases) and matched normal tissues/whole blood. The purpose of this study is to develop actionable molecular targets and/or biomarkers for prognostication and patient stratification.

  Study JGAS000642

• Integrating Genomic and Transcriptomic Data to Identify Breast Cancer Susceptibility Genes

  Genetic factors play an important role in the etiology of both sporadic and familial breast cancer. Since 2007, common genetic variants in ~200 loci have been identified in genome-wide association studies (GWAS) in relation to breast cancer risk. However, it is often difficult to translate GWAS findings to disease prevention and treatment since causal genes in the large majority of GWAS-identified loci are unknown. Furthermore, a large fraction of breast cancer heritability remains unexplained. Recent studies suggest that nearly 80% of disease heritability can be explained by genetic variants regulating gene expression. Herein, we propose three well-powered transcriptome-wide association studies (TWAS) to systematically investigate the association of breast cancer risk with gene expression across the transcriptome of African, Asian and European descendants. In Aim 1, we will perform RNA sequencing and high-density genotyping assays using normal breast tissue samples, and build race-specific gene expression prediction models using data from 1000 women of African, Asian and European descent. These models will be applied to the GWAS data generated from approximately 320,000 breast cancer patients and controls to impute gene expression for association analyses of predicted gene expression with risk of breast cancer overall, and by estrogen receptor and HER2 status. In Aim 2, we will select the top 50 genes identified in Aim 1 for in vitro functional assays to assess their influence on major cell functions related to cancer biology. In Aim 3, we will evaluate whether TWAS-identified genes may express differently in normal breast tissues and breast cancer tissues collected from African, Asian, and European descendants to assess whether these genes may contribute to racial differences in breast cancer risk by molecular subtypes. With strong methodology and a large sample size, we believe that this proposed study should be able to identify and characterize a large number of novel genes related to breast cancer risk. Uncovering breast cancer susceptibility genes will greatly improve the understanding of the genetic and biological basis for breast cancer and accelerate the translation of genetic findings to disease prevention and patient care.

  Study phs003535

• ctDNA quantification in Ewing sarcoma patients

  Background. Treatment stratification and response assessment in pediatric sarcomas has relied on imaging studies and surgical/histopathological evidence of vital tumor cells. Such studies and evidence collection processes often involve radiation and/or general anesthesia in children. Cell-free circulating tumor DNA (ctDNA) detection in blood plasma is one available method of so-called liquid biopsies that has been shown to correlate qualitatively and quantitatively to some extent with the existence of vital tumor cells in the body. Our clinical observational study focused on the utility and feasibility of ctDNA detection in pediatric Ewing sarcoma (EWS) as a marker of minimal residual disease (MRD). Patients and Methods. We performed whole genome sequencing to identify the exact breakpoints in tumors known to carry the EWS-FLI1 fusion gene. Patient-specific fusion breakpoints were tracked in peripheral blood plasma using digital droplet PCR (ddPCR) before, during, and after therapy in six consecutive children and young adults with EWS. Presence and levels of fusion breakpoints were correlated with clinical disease courses. The genetic changes in the tumors were defined, and inter- and intra-individual changes in the tumor DNA copy loads were observed over time. Results. We show that the detection of ctDNA in the peripheral blood of EWS patients i) is feasible in the clinical routine and ii) allows for the longitudinal real-time monitoring of MRD activity in children and young adults. Although changing ctDNA levels correlated well with clinical outcome within patients, between patients, a high variability was observed (inter-individually) for the six patients described here. Conclusions. ctDNA detection by ddPCR is a highly sensitive, specific, feasible, and highly accurate method that can be applied in EWS for follow-up assessments as an additional surrogate parameter for clinical MRD monitoring and, potentially, also for treatment stratification in the near future.

  Study EGAS00001006433

• Synergy study: "Tissue resident CD8+ T cell clonal expansion in advanced triple negative breast cancer is associated with response to chemoimmunotherapy"

  Dataset of the study "Synergy study: "Tissue resident CD8+ T cell clonal expansion in advanced triple negative breast cancer is associated with response to chemoimmunotherapy". This dataset contains the cellranger's gene-expression matrices for the 5 prime single-cell RNA sequencing experiments

  Dataset EGAD50000000748