12452 results for ""non-traditional+communal+storytelling+approach"+novel+segment+noted+in+critical+commentary"

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• National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK): Identification of VUR genes by exome sequencing

  Primary vesicoureteric reflux (PVUR), or non-syndromic VUR, is the most common type of congenital anomaly of the kidney and the urinary tract (CAKUT). PVUR is the single most important risk factor for pyelonephritis and renal parenchymal scarring in the pediatric age group. Renal parenchymal scarring due to PVUR is referred to as reflux nephropathy and is a major cause of end stage kidney disease requiring dialysis and kidney transplantation in children. PVUR shows familial aggregation; however, the specific genetic cause(s) of PVUR is unknown despite a number of linkage studies. Reasons for this include: variable expression of the disease, difficulty with case ascertainment, genetic heterogeneity and lack of large pedigrees that can facilitate locus identification. We have ascertained a large 97 member PVUR kindred spanning five generations. We performed a genome-wide linkage study (GWLS) on this family and obtained a significant genome-wide LOD score of 3.3 on chromosome 6p. We performed exome sequencing on affected individuals in the family and identified mutations in tenascin XB (TNXB) as a cause of familial VUR. The proposed studies have the following specific objectives: a) to define the role of tenascin genes in the etiology of PVUR, and b) to identify new PVUR causative genes. Our specific aims are (1) To perform mutation analysis in TNXB and other tenascins in a cohort of 200 individuals with familial and sporadic PVUR and define genotype/phenotype correlations. (2) To perform sequential genome wide linkage studies (GWLS) and whole exome/targeted sequencing in families with PVUR. Impact on public health: Identification of PVUR genes may provide a novel non-invasive diagnostic tool for a subset of children with PVUR. Furthermore, this research will provide insights into the pathogenesis of PVUR and further elucidate the pathways involved in the development of the kidney and genitourinary tract. Future studies will define the role of the genes in the etiology of other malformations of the kidney and urinary tract and also seek to unravel the mechanisms by which the identified gene causes PVUR and other malformations of the kidney and the urinary tract.

  Study phs000778

• The Cancer Dependency Map (DepMap)

  The Cancer Dependency Map (DepMap) aims to accelerate precision cancer medicine by creating a comprehensive map of tumor vulnerabilities. The DepMap project genomically profiles a wide range of cancer models and characterizes them for their sensitivity to genetic and compound perturbations. The data is computationally analyzed to create a systematic overview of the genetic dependencies and compound sensitivities of cancer types and the predictive biomarkers that point to patient populations most likely to benefit from targeting of these vulnerabilities. The DepMap public portal has become a comprehensive resource to identify cancer vulnerabilities by providing datasets at scale, cutting-edge computational tools, and sophisticated visualization tools that together have accelerated the discovery of novel targets and biomarkers. Please visit Depmap.org to access the public portal.

  Study phs003444

• RNAseq data of polyA+ RNA from Leukocytes from 624 individuals of the SardiNIA cohort.

  We sequenced the polyA+ of the RNA of the leukocytes from 624 sardinian individuals with RNAseq (Illumina 2000, an average of round 60M reads per sample, 51 + 51 nt). Combining the genotype information of the same individuals (already available from the ProgeNIA project) with the transcriptome data we identified 21,183 independent expression quantitative trait loci (eQTLs) and 6,768 independent splicing quantitative trait loci (sQTLs), including 619 novel QTLs that exhibit population-specific trait associations. Using family relationships, we identified 809 segregating expression outliers and provide a new approach to study large effect regulatory variants and their relevance to traits. Our results provide insight into the effects of regulatory variants and their relationship to population history and individual genetic risk.

  Study EGAS00001002105

• Expression profiling of a human endocrine pancreas iPSC model

  Directed differentiation of stem cells offers a scalable solution to the need for human cell models recapitulating islet biology and T2D pathogenesis. We profiled mRNA expression at six stages of an induced pluripotent stem cell (iPSC) model of endocrine pancreas development from two donors, and characterized the distinct transcriptomic profiles associated with each stage. Established regulators of endodermal lineage commitment, such as SOX17 (log2 fold change [FC] compared to iPSCs=14.2, p-value=4.9x10-5) and the pancreatic agenesis gene GATA6 (log2 FC=12.1, p-value=8.6x10-5), showed transcriptional variation consistent with their known developmental roles. However, these analyses highlighted many other genes with stage-specific expression patterns, some of which may be novel drivers or markers of islet development. For example, the leptin receptor gene, LEPR, was most highly expressed in published data from in vivo-matured cells compared to the endocrine pancreas-like cells (log2 FC=5.5, p-value=2.0x10-12), suggesting a role for the leptin pathway in the maturation process. Endocrine pancreas-like cells showed significant stage-selective expression of adult islet genes, including INS, ABCC8, and GLP1R, and enrichment of relevant GO-terms (e.g. “insulin secretion”; odds ratio=4.2, p-value=1.9x10-3): however, principal component analysis indicated that in vitro-differentiated cells were more immature than adult islets. Integration of the stage-specific expression information with genetic data from T2D genome-wide association studies revealed that 46 of 82 T2D-associated loci harbor genes present in at least one developmental stage, facilitating refinement of potential effector transcripts. Together, these data show that expression profiling in an iPSC islet development model can further understanding of islet biology and T2D pathogenesis.

  Dataset EGAD00001002148

• DNA Methylation Analysis of Prostate Cancer Cell Lines and Tissues Using Next Generation Sequencing

  Aberrant DNA methylation changes are known to occur during prostate cancer progression beginning with precursor lesions. Utilizing fifty nanograms of genomic DNA in Methylplex-Next Generation Sequencing (M-NGS) we mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2). Peaks were located from mapped reads obtained in each sequencing run using a Hidden Markov Model (HMM)-based algorithm previously used for Chip-Seq data analysis(http://www.sph.umich.edu/csg/qin/HPeak). The total methylation events in intergenic/intronic regions between benign adjacent and cancer tissues were comparable. Promoter CGI methylation gradually increased from -12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues and approximately 20% of all CpG islands (CGIs) (68,508) were methylated in tissues. We observed distinct patterns in promoter methylation around transcription start sites, where methylation occurred directly on the CGIs, flanking regions and on CGI sparse promoters. Among the 6,691 methylated promoters in prostate tissues, 2481 differentially methylated regions (DMRs) are cancer specific and several previously studied targets were among them. A novel cancer specific DMR in WFDC2 promoter showed 77% methylation in cancer (17/22), 100% methylation in transformed prostate cell lines (6/6), none in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested a role for DNA methylation in alternate transcription start site utilization. While methylated promoters containing CGIs had mutually exclusive H3K4me3 modification, the histone mark was absent in CGI sparse promoters. Finally, we observed difference in methylation of LINE-1 elements between transcription factor ERG positive and negative cancers. The comprehensive methylome map presented here will further our understanding of epigenetic regulation of the prostate cancer genome. Overall Design: We mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2) from fifty nanograms of genomic DNA using Methylplex-Next Generation Sequencing (M-NGS). For replicate analysis in cell lines, a total of 4 runs were completed for PrEC prostate normal cell line, and 5 runs were completed for LNCaP prostate cancer cell line. For tissue samples, 2 benign prostate samples were sequenced twice on Illumina next generation sequencing platform to access overall repeatability of M-NGS.

  Study phs000597

• A novel subset of human CD33+ haematopoietic stem cells characterized at single-cell resolution

  Elucidation of the identity and diversity of mechanisms that sustain long-term human blood cell production remains an important challenge. Previous studies indicate that, in adult mice, this property is ultimately vested in cells uniquely identified by their ability to clonally regenerate detectable levels of mature blood cells in serially transplanted recipients. We now present a combined multi-parameter analysis of the molecular features of very primitive human cord blood cells that display different cell output activities in vitro and in vivo. These analyses identified a new, prospectively separable, but still functionally heterogeneous, subset of long-term human blood-forming cells. Single-cell measurements of their transcriptional, DNA methylation and 40-protein content and of closely related phenotypes revealed numerous subtle, but consistent differences both within and between each subset analyzed. These results suggest that multiple regulatory mechanisms underlie the functional heterogeneity exhibited by clonally tracked human blood cell precursors with long-term output abilities.

  Study EGAS00001002826

• NHGRI GREGoR Consortium: Genomics Research to Elucidate the Genetics of Rare Disease

  The NHGRI GREGoR (Genomics Research to Elucidate the Genetics of Rare Disease) Consortium was established in June 2021 with the goal of developing novel tools and approaches to advance the discovery of the genetic basis of rare conditions. Numerous types of molecular data are generated in GREGoR and available on the AnVIL cloud platform via dbGaP application, including short- and long-read genome and exome sequencing, transcriptomics, metabolomics, methylomics, and proteomics. De-identified clinical and demographic data is obtained, with a focus on standardized ontologies.Visit the GREGoR Consortium data webpage for summary information about the GREGoR Dataset, including numbers of participants and data types, methods documentation, and Release Notes. The Consortium comprises five Research Centers (RCs - see below), a Data Coordinating Center (DCC), and various partner members and external collaborators.Baylor College of Medicine Research Center (BCM-GREGoR) The Baylor College of Medicine GREGoR program, which is part of the GREGoR consortium, enrolls individuals, families, and cohorts with suspected rare disease across a range of syndromic and non-syndromic phenotypes. Subjects are enrolled from national and international collaborating physician referrals. Subjects provide written informed consent for future re-contact. Data generated and shared include family structure, detailed phenotypes, exome or short-read genome data, and in some cases long-read genome or RNA-sequencing, and these are shared upon completion of standard quality control checks and annotation. Broad Institute (Broad) The Broad Center for Mendelian Genomics, part of the GREGoR consortium uses next-generation sequencing (exome, genome, transcriptome, and long read sequencing), computational approaches, and functional studies to discover the variants and genes that underlie Mendelian conditions with a particularly focus on neuromuscular, neurodevelopmental, and syndromic phenotypes. Samples come from collaborators and direct enrollment through the Rare Genomes Project and we are committed to rapid data sharing without an embargo period. University of California, Irvine (UCI-GREGoR) To accelerate the pace of Mendelian disease gene discovery and clinical implementation, we propose a Mendelian Genomics Research Center, part of the GREGoR Consortium, leveraging the broad pediatric and adult clinical and research expertise at Children's National Hospital and University of California, Irvine. Our goal is to develop best practices to increase the diagnostic yield of rare diseases, engage the community to reduce health disparities for complex diagnoses, while creating a dataset accessible to all. Our Center will unite world class experts combining basic and translational research with innovative approaches to phenotyping, variant identification and functional investigation of both coding and non-coding sequence changes with the goals of discovering novel Mendelian gene variations and identifying variants not detected on current sequencing pipelines, disambiguating uncertain variants into disease-causing versus benign categorizations, and sharing information by working collaboratively with the GREGoR community.GREGoR Stanford Site (GSS) The goal of the GREGoR Stanford Site (GSS) is to provide a platform for functional genomics research and validation to improve diagnosis in Mendelian disease. Participants included individuals with undiagnosed suspected Mendelian disease who had non-diagnostic exome sequencing and their immediate family members. Participants and their family members provided written, informed consent and biological samples from which DNA, RNA, plasma, fibroblasts, PBMCs and other cell types were generated and stored. Samples from research participants and their immediate family members may have undergone short and long-read genome sequencing, transcriptome sequencing, metabolomics and/or lipidomics profiling, methyl-capture-sequencing and ATAC-sequencing. De-identified clinical data extracted from participant medical records are linked to the samples. University of Washington Center for Rare Disease Research (UW-CRDR) The goals of the University of Washington Center for Rare Disease Research are to: (1) maximize novel gene discovery for Mendelian conditions by recruitment, short- and long-read whole genome sequencing, transcriptome sequencing and analysis of families with rare conditions for which the gene is either unknown or the gene is known but no pathogenic variant can be identified via clinical testing; (2) develop new strategies for gene discovery for Mendelian conditions caused by variants that are difficult to detect using conventional testing strategies, variants of unknown function effect (e.g., regulatory, structural variants) or have unusual modes of inheritance; and (3) implement high-throughput screening and targeted follow-up functional studies to prioritize and validate candidate non-coding variants. De-identified data and phenotypic information are shared via MyGene2, ClinVar, and AnVIL.

  Study phs003047

• Glial Cell Line-Derived Neurotrophic Factor (GDNF) Polymorphisms and Anxiety, Depression

  GDNF gene variants were studied as possible risk factors of depression or anxiety on a young sample. The association study involved eight (rs1981844, rs3812047, rs3096140, rs2973041, rs2910702, rs1549250, rs2973050 and rs11111) GDNF single nucleotide polymorphisms and anxiety and depression scores measured by the Hospital Anxiety and Depression Scale (HADS) on 708 Caucasian young adults with no psychiatric history. Results provided significant effects of two single nucleotide polymorphisms on anxiety scores following the Bonferroni correction for multiple testing (p=0.00070 and p=0.00138 for rs3812047 and rs3096140, respectively). Haplotype analysis confirmed the role of these SNPs (p=0.00029). A significant sex-gene interaction was also observed since the effect of the rs3812047 A allele as a risk factor of anxiety was more pronounced in males. This is the first demonstration of a significant association between the GDNF gene and mood characteristics demonstrated by the association of two SNPs of the GDNF gene (rs3812047 and rs3096140) and individual variability of anxiety using self-report data from a non-clinical sample. Reprinted from Kotyuk et. al., 2013 (Kotyuk, E., Keszler, G., Nemeth, N., Ronai, Z., Sasvari-Szekely, M., and Szekely, A. (2013). Glial Cell Line-Derived Neurotrophic Factor (GDNF) as a Novel Candidate Gene of Anxiety. PLoS One,8, (12) PMID: 24324616), with permission from Publisher (All content of articles published in PLOS journals is open access. You can read about our open access license here: http://www.plos.org/about/open-access/. To summarize, this license allows you to download, reuse, reprint, modify, distribute, and/or copy articles or images in PLOS journals, so long as the original creators are credited (e.g., including the article's citation and/or the image credit); Laura Perry; Staff EO;PLOS ONE)

  Study phs000713

• Blood Transcriptome Profiling Following Seizures

  The retrospective diagnosis or confirmation of a seizure, after the event, is very challenging. Many times clinicians can only use a patient's self-reported history. To further complicate the diagnosis, it is known that 20-30% of patients reporting a seizure actually suffer from psychogenic non-epileptic seizure (PNES). The patient has the behavior of a seizure, but does not suffer from brain seizure activity. Considerable time and resources are used to monitor PNES, and many patients undergo unnecessary therapy with anti-epileptic drugs. These resources could be more effectively used if we could confirm a seizure after the event (retrospective diagnosis). Here we propose a novel approach to distinguish seizures from PNES after the seizure event has happened.We have developed an accurate blood biomarker technology to diagnose acute brain injury, and assess chronic progression following brain injury. Previous studies support the premise that seizures affect blood RNA expression; here we assess temporal RNA expression pattern changes following seizure. We present preliminary preclinical data showing the discrimination of electric-stimulation evoked animal seizures. Here, we validate this maturing technology to assist with the discrimination of epileptic seizures from psychogenic non-epileptic seizures. We will analyze blood samples from patients undergoing video EEG monitoring in an epilepsy monitoring unit (Emory University Hospital, Atlanta GA). We expect 20% of these patients will have PNES. Once a patient has an EEG verified seizure, we will collect blood at various time points and identify biomarker RNA molecules in the blood. Blood samples will be collected from patients with non-verified seizures as control. These RNA expression values will be used to develop a predictive test for the occurrence of seizures. A biomarker gene panel will be developed from this exploratory project for validation in a larger patient population.

  Study phs003460

• Gene Environment Association Studies (GENEVA): Genetics of Early Onset Stroke (GEOS) Study

  The Genetics of Early Onset Stroke (GEOS) Study is a population-based case-control study designed to identify genes associated with early-onset ischemic stroke and to characterize interactions of identified stroke genes and/or SNPs with environmental risk factors such as smoking and oral contraceptive use. The GEOS study consists of 921 ischemic stroke cases with age of first stroke 16-50 years and a similar number of controls, identified from the Baltimore-Washington area. Cases and controls were recruited in 3 different time periods: Stroke Prevention in Young Women-1 (SPYW-1) conducted from 1992-1996, Stroke Prevention in Young Women-2 (SPYW-2) conducted from 2001-2003, and Stroke Prevention in Young Men (SPYM) conducted from 2003-2007. The overall GEOS sample includes 477 cases who self-reported their race as "white" and 396 cases who self-reported their race as "African American." Traditional stroke risk factors and other study variables, including age, ethnicity, and history of hypertension, diabetes, myocardial infarction (MI), current smoking status, and current oral contraceptive use (both defined as use within one month prior to event for cases and at a comparable reference time for controls), were also collected during standardized interview and were included as covariates in our analyses. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to early-onset ischemic stroke through large-scale genome-wide association studies of cases and controls of European and African descent from the Baltimore-Washington area. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000292