3311 results for "*geneti*"

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• Genetic Effects on miRNA Expression During Mid-Gestation Neocortical Development

  In this study we aimed to find common genetic variants that influence miRNA expression during mid-gestation neocortical development. Small RNA-sequencing from 212 fetal cortical tissue samples between 14 and 21 weeks gestation were used to profile miRNA expression. Combined with donor genotypes, we were able to find miRNA-eQTLs during neocortical development. The dataset provided here includes 212 Small RNA-sequencing files in FASTQ format from cortical wall samples. Also provided here are 212 donor genotypes in PLINK format (hg19).

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• Role of Genetic Factors in the Pathogenesis of Lung Disease

  Three individuals with lymphangioleiomyomatosis (LAM) underwent evaluation for Tuberous Sclerosis Complex (TSC)-associated mucocutaneous and internal findings. Next-generation sequencing (NGS) of cutaneous findings was used to confirm clinical suspicion for mosaic TSC in individuals with LAM. Mosaic mutations in TSC2 were found in these three individuals.

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• Genetics of Male Infertility Initiative (GEMINI)

  The Genetics of Male Infertility Initiative (GEMINI) project is a multi-center study designed to discover and characterize genetic variants conferring risk for male infertility. Patients enrolled in GEMINI have been clinically diagnosed with male infertility. Patients are recruited from multiple medical centers and are primarily of European ancestry. DNA from each patient is extracted from peripheral blood or saliva and used for exome sequencing. Genetic data generated by the GEMINI project has contributed to the discovery of over a dozen genes involved in human infertility. A VCF file of genetic data from GEMINI patients that have been appropriately consented will be available through dbGaP.

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• Genetic Epidemiology of Ovarian Cancer Histotypes

  Epithelial ovarian cancer is a highly fatal malignancy with known genetic etiology; however, it is estimated that a substantial portion of narrow sense heritability remains to be discovered. The goal of this research was to use genetic information from distantly related ovarian cancer cases to identify regions of the genome that may harbor rare risk variants for epithelial ovarian cancer. The study was conducted in the setting of the Utah Population Database, a statewide data resource in which extensive ancestry data are linked to Utah Cancer Registry records. Focusing on families with a statistically significant excess risk of epithelial ovarian cancer, we used the Infinium Global Screening Array v.3.0 to generate germline genotyping data for distantly related cases. We then applied Shared Genomic Segment Analysis to each set of related cases to identify genomic regions that may harbor ovarian cancer risk variants. Eleven regions were identified. Genotype data are available through dbGaP for one case from each pedigree. Genotype data from other ovarian cancer cases within the high-risk pedigrees as well as the pedigrees' corresponding structures can be requested and made available with approval from the Utah Resource for Genetic and Epidemiologic Research (RGE).

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• 3/7 Psychiatric Genomics Consortium: Finding Actionable Variation

  The goal of this study was to generate new therapeutic hypotheses by targeted sequencing of 161 genes most likely to harbor schizophrenia (SCZ) causal variants in multi-ancestry schizophrenia case-control cohorts. The gene panel was intended to contain putative SCZ risk genes, from within which, the majority of new discoveries from additional WES/WGS would come. To this end, we integrated current knowledge of the genetic architecture of SCZ (results from The Schizophrenia Exome Sequencing Meta-Analysis Consortium, or SCHEMA) and gene membership in gene sets that have been implicated in SCZ using a Bayesian framework. A total of 23,352 individuals selected to be non-overlapping with SCHEMA, as well as other previous and ongoing sequencing efforts in the field, were identified from over 20 individual study sites. Sequencing of the exonic regions of 161 prioritized genes was performed on the Ion Torrent platform in between June 2018 and April 2019. Sequencing plates were matched with respect to ancestry and case/control composition whenever possible. The average sequencing depth across all samples was 224x. Single sample calling was performed using Torrent Variant Caller v5.8.0, which is specially optimized to exploit the underlying flow signal information generated by the Ion Torrent sequencing. The schizophrenia case-control status was obtained from each original study site.

  Study phs003138

• Genetic Progression of Head and Neck Squamous Cell Carcinoma

  These data are tumor/normal-matched exome sequencing results on 45 participants (median age of 58.6 years) treated for squamous cell carcinoma of the oropharynx at Mass Eye and Ear (MEE; Boston, MA, USA). Some tumors had two portions sequenced separately. All research complied with all relevant ethical regulations. Human subject research on patients at MEE was approved by the MEE Human Studies Committee under protocol HSC 11-024H, with informed consent obtained from participants. Participants were not compensated. Clinical data, including HPV status, were abstracted from patient records. Sequencing and clinical data were combined with TCGA data on 486 cases of head and neck squamous cell carcinoma (HNSCC). The PhylogicNDT suite of genomic analysis tools was used to infer the relative timing of genetic events during tumor progression for major molecularly defined classes of HNSCC: HNSCC negative for human papillomavirus (HPV), HPV-associated HNSCC, and HPV-negative HNSCC involving mutations in CASP8, NSD1, and NOTCH1. The timing of the development of whole-genome somatic events leading to tetraploidy or triploidy and to increased measures of intratumor genetic heterogeneity was determined. Associations of heterogeneity measures with clinical outcomes were assessed. The analysis identified genes with early mutations that likely play roles in HPV-tumor initiation (FBXW7, NOTCH1, CASP8, FAT1, NSD1, HRAS, EP300, CREBBP, KMT2D). Genes with mutations at later median relative timing (PK3CA, NFE2L2, HLA-A, SPEN, and KMT2C) were more likely to be important for progressing to later stages of the disease. Gain of chromosome arm 3q and loss of arm 11q were found to occur more frequent in HPV+ HNSCC cases. A high prevalence of 3p and 17p loss were also observed in HPV+ HNSCC cases.

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• Predicting the Prevalence of Complex Genetic Diseases from Individual Genotype Profiles Using Capsule Networks

  Diseases with a complex genetic architecture, such as amyotrophic lateral sclerosis (ALS) as a most prominent example, are hard to disentangle. "Human mind-friendly" methods, such as linear approaches used in genome wide association studies (GWAS), remain blind to many genetic variants that matter. On the other hand, methods that are sufficiently sophisticated to entirely capture the characteristic interplay of genetic variants remain black boxes for the human mind. Here, we give this a decided, and as we argue, a very promising try. We present DiseaseCapsule, a capsule network-based approach that enables us to predict prevalence/occurrence of a genetically complex disease from individual genotype profiles. Importantly, capsule networks are considerably easier to decompose into their components than ordinary deep neural networks, which promotes the interpretability of their results. The data we used are from Project MinE, a large-scale study that aims to reveal the genetic and epigenetic mechanisms that underlie ALS in the framework of a globally concerted collaboration. Specifically, we used data from the Dutch cohort of the project, which contains 7213 healthy ('control') individuals and 3192 individuals affected with ALS. The cohort includes 5208 females and 5197 males. All participants of the study were genotyped using an Illumina 2.5M SNP array.

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• International Cancer Proteogenomics Consortium (ICPC): Proteogenomics of East-Asian Breast Cancer

  The incidence of invasive breast cancer is rapidly increasing in East Asia, enriching in younger patients and luminal disease. We presented a deep proteogenomic landscape of a prospectively enrolled early-stage cohort in Taiwan to uncover the etiology, age-related subtype and oncogenic vulnerabilities underlying the heterogeneous disease. Multilayer proteogenomic architecture revealed distinct endogenous and environmental carcinogen-associated mutagenesis, linking APOBEC (apolipoprotein-B mRNA editing enzyme, catalytic polypeptide-like) cytidine deaminase and DBAC (dibenz[a,j] acridine) signatures to significantly elevated hormone biosynthesis and chemical carcinogenesis in younger patients, and identifying a novel subset of high mutation burden and immune escape potentially beneficial from combined epigenetic therapy and immunotherapy. A proteomics-informed classification resolves luminal heterogeneity, defines high-risk recurrent luminal disease and nominates biomarkers and actionable druggable pathways. Furthermore, proteogenomics profile distinguished a young luminal population susceptible to exogenous carcinogen and having DNA repair deficiency. This study illuminates the age-related molecular subtypes and oncogenic vulnerabilities, providing a proteogenomics-transformative guide for patient stratification and precision therapeutics beyond clinical staging.

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• Genetics of Glucose Regulation in Gestation and Growth (Gen3G) Cohort - Placenta Transcriptomics RNA Sequencing

  The overarching goals of Genetics of Glucose regulation in Gestation and Growth (Gen3G) are to increase our understanding of biological, environmental, and genetic determinants of glucose regulation during pregnancy and their impact on fetal/child development. Gen3G is a prospective cohort study: we initially recruited 1,024 pregnant women between 2010-2013 at Blood Sampling in Pregnancy Clinic during the first trimester of pregnancy (median 9 weeks of gestation) in Sherbrooke, Québec, Canada. We assessed 898 pregnant women at second trimester (median 26 weeks of gestation), when participants completed a 75g oral glucose tolerance test (OGTT) as clinically indicated for screening of gestational diabetes mellitus (GDM). We collected data for 854 mother-child dyads at delivery (from medical records), in addition to placenta and/or cord blood samples in majority of newborns.The overall goal of the grant that supported data that is included in this dbGaP submission was to discover novel placental factors that regulate glucose metabolism in pregnancy and predict GDM by conducting genome-wide transcriptomics (RNA and miRNA) in carefully collected placenta samples from Gen3G.

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• Enhancing Open Data Sharing for Functional Genomics Experiments: Measures to Quantify Genomic Information Leakage and File Formats for Privacy Preservation

  This study was designed to develop methods that address the privacy risk associated with genetic variants obtained from genomic sequencing experiments. The preponderance of readily available genetic sequencing experiments has enabled the generation of datasets whose target purposes range from the genotyping of individuals for medical and forensic analyses, to the acquisition of molecular information for biological model development. However, by virtue of the experimental procedure, the raw sequences are tagged with small bits of patients' private variant information. In addition, depending on the protocol, these experiments may identify sequences from exogenous species. Raw human and microbial sequences can be analyzed as a whole to learn both general facts about biology, but can also be used to determine sensitive information about an individual. This presents a privacy conundrum for data sharing.To address privacy concerns, we have developed several mathematical and computational approaches to quantify the risk of disclosure of sensitive information from genetic sequence data, and to sanitize the associated reads in a manner that optimally maintains the utility of the data. In addition, we have generated environmental samples containing genetic information from consented individuals to evaluate the risk posed by such data. These samples were then used to assess the efficacy of the computational methods. Human-derived and -associated samples that are damaged or obscured by environmental factors represent the scope of samples used for experimentation in this study. Samples include, but were not limited to, swabs of contacted objects and glass slides coated in saliva from consented individuals. Blood samples were also acquired from the same consented individuals to create gold-standard comparison datasets.

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