4052 results for "*geneti*"

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• Genomic Answers for Kids (GA4K)

  Identification of complex genetic variants including defects in gene regulatory circuits and uncharacterized genes present challenges for rare disease diagnosis. In Genomic Answers for Kids program we apply the joint interpretation of patient genome sequence with genomic endophenotypes to expand the clinically actionable genome among pediatric cases of suspected genetic disease. Our objective is to examine the role of novel and under-interpreted sequence variation by combining complete DNA sequences, personal epigenetic variations and massively parallel functional screens. To achieve this we perform augmented whole genome sequence (WGS) interpretation including reanalysis of clinical exomes as well as generating WGS for patients with negative exome results all be subject to family-based semi-automated recall pipeline to discover missed diagnostic variation. We use linked-read and long-read sequencing technologies to focus on putative structural variants missed in short-read genome and exome analysis by the optimized integration of linked and long read technologies that also improve identification of transmission patterns of all variants, as well as resolving genomic regions resistant to standard alignment. We also include tissue DNA sequencing to investigate somatic mosaicism. To further assist with WGS interpretation for uncommon variation we capture snapshots of patient transcriptomes and epigenomes in individual cells using single-cell RNA (scRNA) and sc open chromatin (scATAC) as well as bulk whole genome bisulphite genome sequencing for methylome interpretation. Alternative splicing is functionally assessed in available patient tissues using RNA-seq, including full length cDNA sequences by IsoSeq (PacBio) methodology. Our overarching goal is an increase rate of diagnostic genomic findings up to two-fold among rare disease, resulting in the majority (>50%) of patient cases resolved by the integrated system developed in our program.

  Study phs002206

• Brain Cell Type-Specific Enhancer-Promoter Connectivity Maps and Disease Risk Association

  These studies map the epigenetic landscape of microglia, neurons, astrocytes and oligodendrocytes. The initial study compared acutely isolated microglia to cultured microglia from the same donors, to identify changes that occur when microglia are removed from the brain microenvironment. In collaboration with the Rady Children's Hospital, we obtained brain tissue samples from pediatric patients representing putative normal tissue resected to gain access to brain tumors as well as tissue resected to remove epileptic foci. We assayed microglia isolated from these samples using RNA-seq, ATAC-seq and ChIP-seq for PU.1, H3K4me2, and H3K27ac. For patients from whom a sufficient cell number was obtained, we additionally cultured their microglia for up to 7 days and subjected these to the same suite of assays. In a follow-up study, we obtained brain tissue from a comparable cohort of pediatric epilepsy patients from Rady Children's Hospital. We isolated nuclei from microglia, neurons, astrocytes and oligodendrocytes, and assayed for ATAC-seq, ChIP-seq for H3K4me3, and H3K27ac, and PLAC-seq (Proximity Ligated ChIP-seq). We isolated microglia from human fetal and postnatal sample and assayed for bulk RNA-seq, bulk ATAC-seq, bulk H3K27ac ChIP-seq, single-cell RNA-seq (scRNA-seq) and single-cell ATAC-seq. For these studies, human microglia are defined by signature genes/proteins, such as P2RY12, SALL1, and CX3CR1.

  Study phs001373

• Genomic Basis of Phenotypic Variability of Complex Disorders

  The 520-kbp deletion on chromosome 16p12.1 is associated with multiple neurodevelopmental outcomes, including intellectual disability/developmental delay (ID/DD), schizophrenia, autism, and epilepsy. This variant is inherited in >95% of cases from carrier parents manifesting neuropsychiatric features, while affected children with the deletion were more likely to carry another large Copy Number Variation (CNV) or rare deleterious mutation elsewhere in the genome, or "second-hits", compared to carrier parents. Thus, while the 16p12.1 deletion confers significant risk for a range of disorders, the ultimate phenotypic trajectory is determined by "second-hit" variants in the genetic background. However, outstanding questions remain about the genetic background in these disorders, including the functional effects of "second-hit" variants towards gene expression or developmental phenotypes, the full spectrum of "second-hit" variants, and the mechanisms driving accumulation of these variants.In version 1, we performed deep clinical phenotyping, whole-genome sequencing (WGS), SNP microarray analysis, and RNA-sequencing of lymphoblastoid cell lines of 32 individuals in five large families with the 16p12.1 deletion. We found that specific classes of rare single-nucleotide and structural variants in coding and non-coding regions contributed towards expression changes in affected children based on their inheritance patterns, including a subset of variants that acted synergistically with the deletion to alter expression. We further found that rare variant-mediated expression changes contribute to specific developmental phenotypes in the carrier children, suggesting a potential genetic mechanism for variable expressivity of the deletion.In version 2, we additionally analyzed genetic and phenotypic data from individuals with 16p12.1 deletion and their spouses to assess the role of assortative mating modulating phenotypic outcomes of the 16p12.1 deletion. We identified significant within- and cross- disorder phenotypic correlations between spouses, but observed no significant genetic correlations between spouses, in line with expectations.

  Study phs002450

• Germline Mutations and Developmental Mosaicism Underlying EGFR-Mutant Lung Cancer

  We designed this study to examine the etiology of multiple lung tumors in EGFR-mutant non-small cell lung cancer patients who undergo surgical resection. Participants were 52-85 years old never or former smokers, who had at least 2 surgical lung tumor pathology specimens available in the Massachusetts General Hospital biobank, at least one of which had an EGFR mutation by routine clinical genotyping. 10 patients were selected, along with two patients from a family with an inherited EGFR-T790M mutation leading to multiple lung tumors. These patient tumor samples and matched normal lung samples were microdissected to collect DNA.In addition to obtaining clinical histories, we performed whole exome sequencing to evaluate the genetic profile of matched tumor and normal samples. The WES data are available on dbGaP. Our data showed increasing mutational burden and copy number alteration with increasing invasiveness, as compared to normal tissues, for the subset of samples that were assessed for tumor invasiveness. We also observed a range of numbers of shared mutations between tumors in a single patient, indicating different degrees of relatedness between lung tumors. We hope that this resource will help researchers understand non-small cell lung cancer presentations with multiple lung tumors. These data may aid in clinical decision making for such patients.

  Study phs003379

• Integrative Analysis for Multi-Omics Data in Non-Small-Cell Lung Cancer

  We conducted epigenetic and transcriptomic mapping of primary non-small cell lung tumors and non-neoplastic tissues. 20 non-neoplastic lung tissues and 18 non-small cell lung tumors were obtained from Biorepository and Tissue Technology Shared Resource at Moores Cancer Center, UC San Diego. All tumor samples were in pathological stages I and II. 8 pairs of samples were "matched", meaning that the tumor and normal tissues came from the same patient. Microfluidic oscillatory washing–based chromatin immunoprecipitation followed by sequencing (MOWChIP-seq) was used to profile the binding of H3K4me1, H3K4me3, H3K9me3, H3K27ac and H3K27me3. SmartSeq-2 was used to map mRNA expression. We identified a large number of differentially modified regions for both epigenetic and transcriptomic markers between tumors and normal tissues. Deep learning model showed extensive transcription factor network rewiring. Raw sequencing data of the ChIP-seq and RNA-seq libraries are available through this dbGaP submission.

  Study phs003113

• BIRC5 Upregulation Enhances DNMT3A-Mutant T-ALL Cell Survival and Pathogenesis

  The goal of this study was to determine how patients with T-ALL who have DNA methyltransferase 3 alpha (DNMT3A) mutations develop resistance to therapy. Since DNMT3A is a methyltransferase, we examined the effect of those mutations on epigenetic regulation using whole genome bisulfite sequencing (WGBS). We also assessed any changes in gene expression using RNA-sequencing. We found that T-ALL patients with DNMT3A mutations are resistant to apoptosis and some chemotherapies. WGBS showed that DNMT3A mutated patients clustered together by their epigenetic profile, which was associated with hypomethylation at TERT and HOX genes. RNA sequencing identified differences in JAK/STAT signaling.

  Study phs003623

• Single-Cell DNA Methylation Profiling with sciMETv2

  In this study we developed a high-throughput single-cell DNA methylation analysis technology, sciMETv2. This technique is rapid, cost-effective, and robust, enabling large-scale single-cell methylome dataset generation. We demonstrate this technology on human middle frontal gyrus, where we identified major cell types. We additionally performed target enrichment using sciMET-cap to enable a reduction in sequencing costs per cell while achieving comparable cell type identification.

  Study phs003091

• Genetic Investigations of Attention-Deficit/Hyperactivity Disorder

  Design and Aims:We conducted whole-exome DNA sequencing on 152 parent-child trios (456 individuals total) that included a child meeting DSM-IV or DSM-5 criteria for ADHD along with both biological parents to identify rare de novo damaging DNA variants associated with ADHD risk. Mutation rates were compared between 147 ADHD trios and 780 unaffected control trios. We aimed to identify specific ADHD risk genes by combining the de novo trio data with rare variant data from an independent case-control cohort.Population Information:ADHD trios were collected from four sites. The 780 control trios were unaffected siblings from the Simons Simplex Collection who scored in the normal range on the Child Behavior Checklist (CBCL) or Adult Behavior Checklist (ABCL) ADHD subscale.Molecular Technologies:Whole-exome DNA sequencing was performed on the ADHD trios using the IDT xGen V1 or Agilent SureSelect All Exon V7 capture and the Illumina NovaSeq6000 sequencer. Control trios were previously sequenced with the NimbleGen SeqCap EzExomeV2 capture and Illumina HiSeq 2000 sequencer. Joint variant calling was performed for all trios. Rare de novo variants with allele frequency Principal Findings:We found a 1.67-fold enrichment of rare de novo damaging variants and a 1.93-fold enrichment of ultra-rare de novo damaging variants in ADHD cases vs controls. By integrating the de novo data with an independent case-control cohort, KDM5B was identified as a high-confidence ADHD risk gene (FDR=0.04). Three potential risk genes were also identified. Twenty-three genes with ultra-rare damaging de novo variants in ADHD overlapped with previously reported risk genes for other neuropsychiatric conditions. Exploratory analyses showed enrichment of these genes in early neurodevelopmental pathways.

  Study phs003647

• Tumor detection by analysis of both symmetric- and hemi-methylation of plasma cell-free DNA

  Aberrant DNA methylation plays a critical role in tumorigenesis. While DNA methylation has been used for cancer detection and classification, DNA hemi-methylation, a novel epigenetic mark has not been analyzed extensively in cancer epigenomes. Here we report a strand-specific (ss) sequencing method (MeDIP-Seq) for plasma cell free (cf) DNA (sscf-MeDIP-Seq), which can analyze both symmetrically methylated DNA regions (DMRs) as well as hemi-methylated regions (DHMRs). Using the sscf-MeDIP-Seq method, we analyzed plasma cfDNA methylomes of 271 samples from subjects with liver cancer and brain cancer and from individuals without cancer (controls). Among them, 215 samples were chosen as the discovery cohort for the identification of DMRs and DHMRs specific in each subject group and for the training of machine learning models of multi-cancer detection (MCD) using DMRs, DHMRs and DMRs+DHMRs as inputs. These models were then used to predict the 56 samples in the validation cohort. We found that models trained with DMRs+DHMRs as inputs in general outperformed models trained with DMRs or DHMRs alone, with AUROC being 0.971, 0.981, and 0.99 in predicting control, liver and brain cancer samples in the validation cohort, respectively, by the DMR+DHMR-trained models.

  Study phs003462

• NHLBI TOPMed: The Genetic Epidemiology of Asthma in Costa Rica

  This administrative supplement to the project, "The Genetic Epidemiology of Asthma in Costa Rica" (R37 HL066289) is in response to NOT-HL-14-029 to perform whole genome sequencing (WGS) on existing NHLBI populations. We focus on asthma because of its public health significance. Asthma affects 26 million U.S. children and adults, remains a major cause of morbidity (one-half million hospitalizations a year) and is the most common cause of school and work days lost. Asthma-related costs are estimated to be over $12.7 billion annually. The Asthma Probands for both the extended pedigrees and the trios utilized in this study were selected on the basis of a physician diagnosis of asthma; a history of recurrent asthma attacks or at least 2 respiratory symptoms; and either airway hyperresponsiveness to methacholine or significant response to bronchodilator (Albuterol) administration. These criteria are identical to the criteria used in the Childhood Asthma Management Program (CAMP). The three primary goals of this project are to: (1) identify common and rare genetic variants that determine asthma and its associated phenotypes (height, weight, IgE level, lung function, bronchodilator response, steroid treatment response) through whole genome sequencing (WGS); (2) perform novel family based association analysis of our WGS data to identify novel genes for asthma; and (3) integrate epigenomic and transcriptomic data with our WGS data and determine the epistatic interactions present using systems genomics approaches. Identification of the molecular determinants of asthma remains an important priority in translational science. Genome-wide association studies (GWAS) have been successful in this regard, identifying at least 10 novel susceptibility genes for asthma. However, as with most complex traits, the variants identified by GWAS explain only a fraction of the estimated heritability of this disorder. Herein, we propose a novel family-based study design and state-of-the-art genome sequencing techniques to map a set of sequence variants for asthma and its associated phenotypes and assess the interrelationships of the identified genes and variants using systems genomics methods. We have assembled a team of investigators highly-skilled and expert in whole genome sequencing (Drs. Michael Cho and Benjamin Raby), genetic association analysis (Drs. Scott T. Weiss, Jessica Lasky-Su and Christoph Lange), integrative genomics (Drs. Raby, Kelan Tantisira, Augusto Litonjua and Dawn DeMeo), and systems genomics (Drs. Weiss, Amitabh Sharma, Lange and Raby) to address this important problem with both a novel study design and data set.

  Study phs000988