3455 results for "*geneti*"

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• VA APOLLO Project - Research for Precision Oncology (RePOP)

  The Research for Precision Oncology Program (RePOP) is a research activity that establishes a cohort of Veterans diagnosed with cancer and who have had genomic analyses performed on their tumor tissue as part of standard of care. All data relevant to a patient's cancer and cancer care will be collected under RePOP, including patient demographics, co-morbidities, genomic analysis, treatments, medications, lab values, imaging studies, and outcomes. All RePOP participants will have signed/verbal informed consent and signed HIPAA authorization to have their data stored and shared from RePOP's Precision Oncology Program Data Repository (PODR). The Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) network is a collaboration between NCI, the Department of Defense (DoD), and the Department of Veterans Affairs (VA) to incorporate proteogenomics into patient care as a way of looking beyond the genome, to the activity and expression of the proteins that the genome encodes. The emerging field of proteogenomics aims to better predict how patients will respond to therapy by screening their tumors for both genetic abnormalities and protein information, an approach that has been made possible in recent years due to advances in proteomic technology.

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• GMKF: Kids First Pediatric Research Program on Congenital Cranial Dysinnervation Disorders and Related Birth Defects

  The Gabriella Miller Kids First Pediatric Research Program (Gabriella Miller Kids First Pediatric Research Program) (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). Both, childhood cancers and structural birth defects are critical and costly conditions associated with substantial morbidity and mortality. Elucidating the underlying genetic etiology of these diseases has the potential to profoundly improve preventative measures, diagnostics, and therapeutic interventions. Whole Genome Sequence (WGS) and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. Goals of this ongoing study are to identify novel "congenital cranial dysinnervation disorder" (CCDD) genes and define the role of the wildtype and mutant genes in normal and aberrant development. The umbrella term (CCDD) refers to congenital birth defects with malformation of one or more cranial nerves, typically resulting in limitations of eye and/or face movement. Examples of CCDDs include congenital fibrosis of the extraocular muscles (CFEOM), congenital ptosis, Duane retraction syndrome (DRS), horizontal gaze palsy with progressive scoliosis (HGPPS), congenital 3rd, 4th or 6th nerve palsies, Moebius syndrome (MBS), and hereditary congenital facial paresis (HCFP). In some cases, anosmia, and disorders of hearing, sucking, chewing, swallowing, and breathing may also be classified as CCDDs. CCDDs can be accompanied by additional birth defects such as intellectual and social disabilities, developmental delays, limb anomalies, and cardiac, GI, and GU disorders. The genetic basis of multiple CCDDs has been determined, and the gene mutations typically alter cranial motor neuron identity or function, or perturb axon growth and guidance. Despite these successes, the genetic etiologies of many inherited CCDDs remain unidentified.

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• Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Follow-Up Study: BioMe Biobank Program

  The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: Type 2 Diabetes Genetic Exploration by Next-generation sequencing in Multi-Ethnic Samples (T2D-GENES) Genetics of Type 2 Diabetes (GoT2D) Exome Sequencing Project (ESP) Slim Initiative in Genomic Medicine for the Americas (SIGMA) Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP) Progress in Diabetes Genetics in Youth (ProDIGY) This data generated from the BioMe Biobank cohort was part of the T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. The T2D-GENES Project is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGAP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGAP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 502 527 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 532 African American ESP Exome Sequencing Project (ESP) US 467 1374 African American T2D-GENES Follow-Up Study BioMe Biobank Program (BioMe) US 1294 1254 East Asian T2D-GENES Project 1 Korea Association Research Project Korea 526 561 East Asian T2D-GENES Project 1 and Follow-Up Study Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 1486 1568 East Asian T2D-GENES Follow-Up Study Korea SNUH South Korea 450 475 East Asian T2D-GENES Follow-Up Study Research Studies in Hong Kong (Hong Kong) Hong Kong 493 485 European T2D-GENES Project 1 Ashkenazi US, Israel 506 355 European T2D-GENES Project 1 Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European GoT2D Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European GoT2D Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European GoT2D UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European GoT2D Malmö-Botnia Study Finland, Sweden 478 443 European LuCamp Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) Denmark 997 997 European ESP Exome Sequencing Project (ESP) US 390 2843 European T2D-GENES Follow-Up Study Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) Scotland, UK 960 966 European T2D-GENES Follow-Up Study Framingham Heart Study (FHS) US 396 596 Hispanic T2D-GENES Project 1 San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 218 Hispanic T2D-GENES Project 1 and SIGMA v2 Starr County, Texas US 1762 1738 Hispanic SIGMA v1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMA v1 and SIGMA v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMA v1 and SIGMA v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMA v1 and SIGMA v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multiethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multiethnic ProDIGY SEARCH for Diabetes in Youth (SEARCH) US 553 0 South Asian T2D-GENES Project 1 London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 531 538 South Asian T2D-GENES Project 1 and Follow-Up Study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow-Up Study Pakistan Genomic Resource (PGR) Pakistan 914 932 The BioMe Biobank study contributed 1294 cases and 1254 controls to T2D-GENES Follow-Up Study.

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• Search for Susceptibility Genes for Diabetic Nephropathy in Type 1 Diabetes (GoKinD study participants), GAIN

  Genetics of Kidneys in Diabetes (GoKinD) study is an initiative aimed at identifying susceptibility genes for diabetic nephropathy in type 1 diabetes. A large number of individuals with type 1 diabetes were screened to identify two subsets, one with clear-cut kidney disease and another with normal renal status despite long-term diabetes. Those who met additional entry criteria and consented to participate were enrolled. When possible, both parents were also enrolled to form family trios. Altogether, GoKinD includes 3043 participants comprising 931 cases, 944 singletons, 268 pairs of parents of cases, and 316 pairs of parents of control. Accessible as a GAIN database are 905 of the cases, 890 of the controls, 10 pairs of parents of cases and 10 pairs of parents of controls. The other parents and the remaining cases and controls are available by a separate application process through NIDDK (dbGaP phs000088 Search for Susceptibility Genes for Diabetic Nephropathy in Type 1 Diabetes (GoKinD study participants and parents), NIDDK). Interested investigators may request the DNA collection and corresponding clinical data for GoKinD participants using the instructions and application form available at Juvenile Diabetes Research Foundation. Consent groups and participant set Diabetic complications only (DCO): 1825 (904 cases, 881 controls, 40 others)

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• NHLBI TOPMed - NHGRI CCDG: Groningen Genetics of Atrial Fibrillation (GGAF) Study

  Atrial fibrillation (also called AFib or AF) is a quivering or irregular heartbeat (arrhythmia) that can lead to blood clots, stroke, heart failure and other heart-related complications. The Groningen Genetics of Atrial Fibrillation (GGAF) cohort is a cohort composed from 5 different sources of individuals with atrial fibrillation (AF) and age and sex-matched controls. Written informed consent was provided from all participating individuals, and all 5 studies were approved by the ethical committee at the University Medical Center (www.atrialfibrillationresearch.nl) and Maastricht University. All samples selected for TOPMed WGS are from individuals with atrial fibrillation.

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• Epigenetic Biomarkers of Aging

  The aim of the study was to discover new epigenetic biomarkers of aging. We used a genome-wide screen for genetic loci showing consistent changes of DNA methylation with progressive aging. Blood DNA samples from 19 apparently healthy individuals aged 22-80 years obtained from the NINDS repositories were analyzed for DNA methylation using Reduced Representation Bisulfite Sequencing. We followed the New England Biolabs (NEB) protocol for methylated adaptors as described previously. Briefly, 1 microgram of genomic DNA was spiked with 100 picograms of lambda phage DNA as the unmethylated standard and digested with MspI endonuclease at C’CGG sites. Ends of restriction fragments were filled in, 3’-dA tailed and methylated adaptors were ligated to the ends of restriction fragments. Bisulfite treatment using the Epitect kit (Qiagen) followed. Bisulfite-converted libraries were amplified using EpiMark Taq DNA polymerase (NEB) and primers with dual barcode indices. The libraries were pooled and sequenced on Illumina HiSeqX instrument using paired end reads of 150 bases. We used Bismark v0.23.1 to align the sequences to hg19 human genome assembly. We used methylKit v1.22.0 to analyze differential methylation in individuals of different ages.

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• GEnomics and Transcriptomics of Human INsulinoma (GETHIN)

  The Genomics and Transcriptomics of Human Insulinoma (GETHIN) The common forms of diabetes - Types 1 and 2 - ultimately result from a deficiency of insulin-producing pancreatic beta cells. The Genomics and Transcriptomics of Human Insulinoma (GETHIN) study was performed in order to identify novel approaches to inducing human pancreatic beta cells to replicate and regenerate. As a corollary, developing drugs that are able to expand human beta cell mass in people with diabetes should reverse diabetes. Unfortunately, identifying druggable pathways that can enhance human beta cell replication has been a major challenge. In 2017, there is only one class of drugs - the harmine analogues - that can induce human beta cells to replicate, and in this case, higher replication rates are desirable. Thus, identifying additional drugs and druggable pathways is a priority in diabetes research. Insulinomas are rare, benign adenomas of the pancreatic beta cell that cause excess insulin production and hypoglycemia: exactly the opposite of Types 1 and 2 diabetes. Beta cell proliferation rates in insulinomas are abnormally high. Thus, the premise for The Genomics and Transcriptomics of Human Insulinoma study is that benign human insulinomas hold the genomic and transcriptomic "recipe", and the repertoire of druggable pathways, that can be exploited to induce regeneration or replication of human beta cells in diabetes. Because, insulinomas are so rare, are almost always benign (non-malignant), and are easily resected by laparoscopic surgery, little attention has been paid to understanding the genomics or transcriptomics of insulinoma. There are at present only three published studies employing next-gen sequencing in insulinoma (PMID:24326773; PMID:25787250; and PMID:25763608). These studies contained 10, 7 and 8 insulinomas, respectively, and highlighted likely mutations in YY1 and MEN1. Our goal was to markedly expand the database and to add RNAseq to these earlier studies. The GETHIN study reports next-gen sequencing on 38 insulinomas, by far the largest series of human insulinomas subjected to next-gen sequencing (see the Selected publications section for reference). This includes paired (genomic plus tumor) whole exome sequencing on 26 human insulinomas (22 sequenced at Mount Sinai, 4 downloaded from Cao et al, PMID:24326773), and 25 sets of RNAseq from insulinomas, some of which also had paired whole exome sequencing, and some of which did not. The insulinoma RNAseq was compared to RNAseq from 22 sets of FACS-sorted normal human beta cells. Since insulinomas are so rare, the 38 insulinomas were collected by several investigators at several institutions over several decades, but most (22 whole exome sets, and all RNAseq) were sequenced at the Icahn School of Medicine at Mount Sinai in New York. The current dataset contains whole exome sequencing and RNAseq on the 11 insulinomas harvested at Mount Sinai. The four from Cao et al can be retrieved from Cao et al PMID:24326773. Fastq files from the remaining 23 insulinomas will be added as the local IRBs and Institutional Certifications are acquired. Complete patient data are provided in our Nature Communications report. Going forward, our intention is to expand this series, with the goal of sequencing 100 human insulinomas. These will be added to dbGaP as they accrue. Paired-end whole exome sequencing (mean usable sequencing depth 79X and 105X for blood and insulinoma, respectively) was performed using an Illumina HiSeq 2500. Insulinoma and sorted normal beta cell RNAseq was performed on Ribozero and polyA paired end libraries using the Illumina HiSeq 2500. Complete sequencing and bioinformatic details are provided in our Nature Communications report. The principal findings from the study are that although each insulinoma has a different set of presumptive driver mutations, the majority converge on genes that are members of the Polycomb Complex, Trithorax Complex and other epigenetic modifying enzymes. In addition, 20% of insulinomas have copy number loss or loss of heterozygosity of all or most of chromosome 11, and the majority display abnormalities in CpG methylation and imprinting control on the imprinted Chr 11 p15.5-15.4 region that contains INS, IGF2, CDKN1C, KCNQ1, and other genes involved in beta cell specification and proliferation.

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• CIDR Whole Exome Sequencing in Joubert Syndrome

  The purpose of this study is to identify new genetic causes of neurodevelopmental diseases (NDDs) in the Joubert syndrome (JS) spectrum. Joubert syndrome is a recessive disease characterized by cerebellar vermis hypoplasia. Our currently funded NINDS award entitled "Molecular characterization of Joubert syndrome" seeks to identify new genetic causes through a variety of molecular strategies. Although our previous strategies involved whole genome SNP-scans, followed by candidate gene sequencing to arrive at identification of new JS causes, we have recently moved to Whole Exome Sequencing (WES) as a highly efficient methodology that is optimized for recessive disease. In this pilot project, CIDR has sequenced DNA on probands from 20 inbred families with JS spectrum disorders in which known causes have been excluded, that have not previously undergone genome-wide SNP scans. These paired end reads will be subject to our established bioinformatics pipeline including HOMOZGYOSITY, SNP and INDEL callers in our lab to identify potentially deleterious sequence changes (PDSC). This is followed by analysis to include testing each PDSC for segregation in the whole pedigree, for occurrence in a ethnically-matched cohort, as well as a defined patient cohort patients, in order to validate new NDD genes.

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• Pharmacogenetics of Efavirenz Discontinuation for Reported Central Nervous System Symptoms Appears to Differ by Race

  This is an evaluation of genetic associations with efavirenz (EFV) discontinuation for central nervous system (CNS) symptoms within 12 months of treatment. Patients were treated at an HIV primary care clinic in Nashville TN from 1998 to 2012. Previously known SNPs in CYP2B6 and CYP2A6 were used to define metabolizer genotypes (extensive, intermediate, slow metabolizer). Over 500,000 SNPs from genome-wide genotyping were used to define MDS (Multidimensional Scaling) coordinates to account for population stratification. Patients were defined as cases if they discontinued EFV for CNS symptoms within 12 months, otherwise they were defined as controls if they did not stop treatment. Among 563 evaluable participants, the hazard ratio for EFV discontinuation for CNS symptoms was 4.9 (95% C.I. 1.9 TO 12.4, p=0.001) in slow metabolizers compared to extensive metabolizers. This association was very significant in Whites 6.5 (95% CI: 2.3 to 18.8; p = 0.001), but not in Blacks 2.6 (95% C.I. 0.5 to 14.1; p = 0.27). The reason for this difference by race is not clear and warrants further investigation.

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• Host Genetic Determinants of the Outcome of Staphylococcus Aureus Bacteremia by Whole Exome Sequencing

  In this case-control study, Complicated Staphylococcus aureus (case) is defined as bacteremia plus endocarditis or bone/joint infection, and Uncomplicated Staphylococcus aureus (control) has no such complications and was cured at follow-up. We used whole exome sequencing to examine the cumulative effect of coding variants in each gene on risk of complicated SAB in a discovery sample of 168 SAB cases (84 Complicated SAB and 84 Uncomplicated SAB, frequency matched by age, sex and bacterial clonal complex). Then we evaluated the 334 most significantly associated genes and 8 biological candidate genes in a replication sample of 240 SAB cases (122 complicated and 118 uncomplicated, frequency matched by age, sex and bacterial clonal complex). All participants were white, non-Hispanic of European descent. In the discovery sample, gene-based analysis using SKAT-O identified 334 genes associated with complicated SAB at p<3.5 x 10-3;. Gene-based analysis of the 342 genes in the replication sample using SKATO identified one gene, GLS2 (GeneID: 27165), significantly associated with complicated SAB (p=1.2 x10-4;) after Bonferroni correction. GLS2 is an interesting candidate gene for complicated SAB due to its role in regulating glutamine metabolism, a key factor in white blood cell proliferation and activation.

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