3334 results for "*geneti*"

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• Genetic Etiology of Heterotaxy

  To understand the genetic etiology of heterotaxy, patients with heterotaxy were consented and recruited, with blood drawn for DNA extraction and exome sequencing. Using the exome sequencing dataset obtained, rare coding sequence variants were identified.

  Study phs001691

• NHLBI TOPMed: Lung Tissue Research Consortium (LTRC)

  Chronic obstructive pulmonary disease (COPD), a disease state characterized by airflow limitation that is not fully reversible, is the third leading cause of death in the U.S. COPD is a heterogeneous syndrome, with affected individuals demonstrating marked differences in lung structure (emphysema vs. airway disease); physiology (airflow obstruction); and other clinical features (e.g., exacerbations, co-morbid illnesses). Multiple genomic regions influencing COPD susceptibility have been identified by genome-wide association studies (GWAS), and rare coding variants can also influence risk for COPD. However, only a small percentage of the estimated heritability for COPD risk can be explained by known genetic loci. Like most complex diseases, COPD is influenced by multiple genetic determinants (each with modest individual effects). Emerging evidence supports the paradigm that complex disease genetic determinants are part of a network of interacting genes and proteins; perturbations of this network can increase disease risk. To identify this network, multiple Omics data will need to be analyzed with methods to account for nonlinear relationships and interactions between key genes and proteins. Our overall hypothesis is that integrated network analysis of genetic, transcriptomic, proteomic, and epigenetic data from biospecimens ranging from lung tissue to nasal epithelial cells to blood in highly phenotyped subjects will provide insights into COPD pathogenesis and heterogeneity. We will leverage the well-phenotyped, NHLBI-funded Lung Tissue Research Consortium (LTRC) to address these questions. We will perform multi-omics analysis in 1548 lung tissue and blood samples from the LTRC. With these multi-omics data, we will utilize a systems biology approach to understand relationships between multiple genetic determinants and multiple types of Omics data. We will begin by performing single Omics analyses in COPD vs. control lung, nasal, and blood samples. Next, we will integrate single Omics data with genetic variants identified by WGS to assist in fine mapping genetic determinants of COPD. We will then perform integrated network analysis of COPD with genetic and multiple Omics data using correlation-based, gene regulatory, and Bayesian networks. Subjects were recruited from Mayo Clinic, Universities of Colorado, Michigan, and Pittsburgh, and Temple University.

  Study phs001662

• Parkinson's Disease Cognitive Genetics Consortium (PDCGC) Stage I, NeuroX Dataset

  Cognitive impairment is a common and disabling problem in Parkinson's disease (PD). Identification of genetic variants that influence the presence or severity of cognitive deficits in PD might provide a clearer understanding of the pathophysiology underlying this important nonmotor feature. We are presently undertaking a large-scale, two-stage study designed to identify genetic risk factors for cognitive impairment in PD. The study population is divided into a discovery (Stage I) and a validation (Stage II) sample of patients enrolled in the PD Cognitive Genetics Consortium (PDCGC). Each patient has undergone a detailed neurological evaluation and cognitive testing. Clinical and genetic data for the project are stored and managed at the Coordinating Center at the University of Washington and VA Puget Sound Health Care System in Seattle. Stage I of the project is now complete; 1,219 PD patients were genotyped for 249,336 variants using the NeuroX array. Participants underwent assessments of learning and memory (Hopkins Verbal Learning Test-Revised [HVLT-R]), working memory/executive function (Letter-Number Sequencing and Trail Making Test [TMT] A and B), language processing (semantic and phonemic verbal fluency), visuospatial abilities (Benton Judgment of Line Orientation [JoLO]), and global cognitive function (Montreal Cognitive Assessment). We excluded individuals who were of non-European ancestry, failed genotyping, were missing data for one or more covariates, were related to another participant in the cohort, or failed to complete at least half of the cognitive tests. After these quality control measures were implemented, 1,105 participants remained and were included in all subsequent analyses. For common variants we used linear regression to test for association between genotype and cognitive performance with adjustment for important covariates. Rare variants were analyzed using the optimal unified sequence kernel association test. The significance threshold was defined as a false discovery rate corrected P-value (PFDR) of 0.05. Eighteen common variants in 13 genomic regions exceeded the significance threshold for one of the cognitive tests. These included GBA rs2230288 (E326K; PFDR = 2.7 x 10-4) for JoLO, PARP4 rs9318600 (PFDR = 0.006) and rs9581094 (PFDR = 0.006) for HVLT-R total recall, and MTCL1 rs34877994 (PFDR = 0.01) for TMT B-A. Analysis of rare variants did not yield any significant gene regions. We have conducted the first large-scale PD cognitive genetics analysis and nominated several new putative susceptibility genes for cognitive impairment in PD. These results will require replication in independent PD cohorts, and efforts to validate the findings in PDCGC Stage II are in progress.

  Study phs001664

• Genomics of Kidney Transplantation

  We have an established consortium consisting of 5 clinical centers which do a total of >800 kidney transplants/year. We have developed a quality-controlled multicenter database with high quality data, and obtained DNA samples and clinical data on 962 recipients and 442 donors. Using our developed infrastructure, we propose to study whether genetic variants are, in part, responsible for the differing outcomes of transplant recipients treated with contemporary immunosuppressive protocols. Our central hypotheses are that the genetic variation is associated with a) kidney transplant outcome, and b) immunosuppressive drug disposition and toxicity. Our long-term goals are to determine whether it is possible to individualize immunosuppressive therapy, based on genetics. At the same time, our studies may elicit new information on pathways important in the immune response or in immunosuppressive drug efficacy, disposition, and toxicity.Our application consists of 3 cores (Genetics Core, Clinical Core, and Administrative Core). We will do a genome wide association study (GWAS). Significant single nucleotide polymorphisms (SNPs) will be identified using the GWAS.Project 1 has 2 specific aims.Aim 1: To identify recipient SNPs that are associated with kidney allograft outcomes, including acute rejection, chronic graft dysfunction, and graft failure. Aim 2: To identify living donor SNPs that are associated with kidney allograft outcomes. Project 2 has 4 specific aims. Aim 1: To identify SNPs that are associated with tacrolimus blood levels.Aim 2: To identify SNPs that are associated with early tacrolimus-related nephrotoxicity and immune suppressant-related new onset diabetes.Aim 3: To identify SNPs that are associated with mycophenolate-related toxicity. Aim 4: To establish the relationships between candidate recipient SNPs, enzyme activity and mRNA expression of the pharmacologic targets of mycophenolate and calcineurin inhibitors. The projects use the genotyping data, which were provided by the Genetics Core, and clinical information, which were collected and entered into the multicenter database by the Clinical Core. Further, biostatistical support (Clinical Core) and administrative oversight and support (Administrative Core) will facilitate data collection, data entry, and data analyses for both projects. The Administrative Core will also facilitate interaction between Sites, Cores, and Projects.Technical note: Regarding to the study design, all transplant recipients should be unrelated. Given the nature of transplantation, some donors may be related to recipients. The donor-recipient relationships are reported in the demographic file under the "related" column. As we did not collect full pedigree information for the related donor-recipient pairs, we have included a IBD file (calculated using PLINK) with the genotype data.

  Study phs001667

• Veterans Administration (VA) Million Veteran Program (MVP) Summary Results from Omics Studies

  MVP is an ongoing prospective cohort study and mega-biobank in the Department of Veterans Affairs Healthcare System designed to study genetic influences on health and disease among veterans.

  Study phs001672

• ADAGESIII: Contribution of genotype to glaucoma phenotype in African Americans

  Glaucoma results in vision loss due to damage of the optic nerve that is irreversible if undetected or untreated. The most common form of glaucoma is primary open angle glaucoma (POAG). While glaucoma affects all races, persons of African descent are disproportionately affected; studies show African-Americans (AAs) are about four to five times more likely than Caucasian Americans to develop the disease. Glaucoma is the leading cause of irreversible blindness in Americans of African descent, and the second leading cause in all Americans. The lack of understanding about the etiology of POAG impedes our ability to identify and treat it early in its development. Evidence of genetic contribution in the pathogenesis of POAG is well established. Since POAG tends to run in families, it is critical to identify the genetic basis of the disease in order to develop effective therapies for early intervention. While genome wide association studies (GWAS) for glaucoma have been completed for Caucasian populations, evidence from other studies suggests that a GWAS of glaucoma specific genes to the African-American population will yield unique and important findings for both this population and for glaucoma in general. A better understanding of the relationship among the stage of disease, the rate of change, ancestry, and other important risk factors being tracked in the ongoing African Descent and Glaucoma Study (ADAGES) will allow us to evaluate the relationship between genetics, visual loss and structural damage in this high-risk cohort. The scientific plan for this new study focuses on glaucoma in ∼2058 African-Americans by detailed phenotyping of new subjects, acquisition of samples from both new and established previously phenotyped study subjects for a repository, establishment of a data coordinating center, and genome wide association studies. The recruitment, enrollment, and phenotyping of both established and new subjects occurs at five clinical centers, University of California (UCSD), New York Eye and Ear Infirmary (Mt Sinai) and Columbia University Medical Center, a private practice in the Atlanta area, the University of Alabama at Birmingham, and the Robert Cizik Eye Clinic in Houston, TX. UCSD is also the location for the Data Coordinating Center and the Repository with Robert N. Weinreb as Principal Investigator. LA BioMed at Harbor-UCLA did the genotyping with a GWAS panel of ∼1 million single nucleotide polymorphisms (SNPs) using the Illumina MEGA array under the direction of Jerome Rotter, Ida Chen, and Kent Taylor.

  Study phs001673

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Autism - Simons Simplex Collection (SSC)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of New York Genome Center (NYGC). WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs001676

• Adolescent Idiopathic Scoliosis (AIS) 1000 Exomes Study

  Adolescent idiopathic scoliosis (AIS) is the most common pediatric spinal deformity. Although the Bracing in AIS Trial (BrAIST) recently demonstrated the effectiveness of bracing for preventing scoliosis progression in some patients, more than 20,000 children undergo major spinal fusion surgery at an annual cost of $3 billion. Spinal fusion surgery is a major operation with considerable risks and complications. Accurate methods of predicting curve progression are needed to develop personalized prevention strategies for those at high risk and to eliminate screening and treatment of those at low risk of progression. Previously identified risk factors for scoliosis curve progression include sex, age of onset, curve type, and presence of an underlying disorder. However, currently available algorithms for predicting AIS curve progression are inaccurate, possibly because the role of genetic factors has been largely unexplored. Because there is little a priori knowledge of the genetic variants involved in AIS pathology, an unbiased genome-wide approach is likely to provide the best opportunity to comprehensively identify disease-associated genes. This is a multicenter exome sequencing study of extreme cases with severe scoliosis.

  Study phs001677

• Defining T cell States Associated with Response to Checkpoint Immunotherapy in Melanoma

  Checkpoint blockade therapy using antibodies targeting CTLA4, PD1 or PDL1 have changed the way cancer patients with advanced disease are being treated, as evident by their FDA approval in a wide variety of malignancies, and their ability to induce high response rates when compared to conventional therapies (e.g. chemotherapy). However, even in melanoma, despite the high response rate, most patients are refractory to therapy or acquire resistance in 10-12 months. To identify key immunological elements coupled with response or resistance to checkpoint immunotherapy, we performed an unbiased analysis on 16,291 CD45+ immune cells from 32 patients (48 samples) treated with checkpoint therapy (anti-PD1=37; anti-PD1/CTLA4=11), using single cell transcriptomics. Initial unsupervised clustering of all CD45+ cells identified 11 clusters. When examining the association of these clusters with clinical outcome, we found that two clusters (B-cells, p=0.005; memory T-cells, p=0.03) were significantly enriched in responder lesions while 4 clusters (monocytes/macrophages, p=0.003; dendritic cells, p=0.015; exhausted CD8+ T-cells, p=0.005; and exhausted/cell-cycle lymphocytes, 1.3x10-5) are enriched in non-responder lesions. Next, by leveraging our unbiased single cell approach, we identified not only clusters but also specific markers associated with either responder lesions (PLAC8, LTB, LY9, SELL, TCF7, IGKC and CCR7) or non-responder ones (CCL3, CD38, HAVCR2, ENTPD1 and WARS), many of which were not previously reported to be associated with clinical outcome to checkpoint therapy. Due to the importance of CD8+ T-cells in controlling tumors, the significant association of T-cell states with clinical outcome, and their high abundance in melanoma tumors, we next focused our analysis on CD8+ T-cells and identified 2 main clusters CD8_G (with increased expression of genes linked to memory) and CD8_B (enriched for genes linked to cell dysfunction), that were significantly enriched in responder (CD8_G, p=1.4x10-6) and non-responder (CD8_B, p=0.005) lesions, respectively. Since cells with both states coexist in each of the responder and non-responder lesions, we decided to calculate the ratio between the number of cells in these 2 clusters and observed a significant separation between responders (CD8_G/CD8_B>1) and non-responders (CD8_G/CD8_B<1) when looking at all samples, baseline or post samples separately. Similar results were detected when looking at the expression of a single transcription factor, TCF7, in CD8 T-cells in an independent cohort (n=43) using a simple immunofluorescence assay. Additionally, we validated the identity and function of some of the newly identified cell states as well as their epigenetic landscape, and found that cells expressing the inhibitory molecules CD39 and TIM3, on top of being enriched in non-responder lesions, are likely to play a crucial role in T-cell exhaustion in melanoma. Collectively, our study provides extensive unbiased data in human tumors for discovery of predictors and therapeutic targets to checkpoint immunotherapy.

  Study phs001680

• Prediction of DNA Repair Inhibitor Response in Short Term Patient-Derived Ovarian Cancer Organoids

  In this study, 34 ovarian tumor organoids generated from 23 patients underwent paired DNA damage repair defect functional analyses and whole exome sequencing analysis to compare genetic mutational status to DNA repair functional capacity. 22 of the patients had high grade serous cancer and 1 of the patients had low grade serous cancer. A normal control, fresh parent tumor, and cells from the organoid culture generated from the parent tumor underwent whole exome sequencing analysis and the data from the sequencing analysis is provided here.

  Study phs001685