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• Colon adenomas and adenocarcinomas and matched mucosae

  Whole exome sequencing in sporadic colorectal cancers (CRC) and advanced adenomas (Ad-As), and their paired healthy mucosa, for a deeper understanding of the biology of this cancer.

  Study EGAS00001007255

• A Machine Learning Tool Integrating Circulating Cell-Free DNA Methylation with Clinical Variables for Non-Invasive Diagnosis of Liver Graft Pathology

  Liver Transplant Recipients (LTRs) with elevated liver enzymes can develop graft injury due to various etiologies, such as T-cell mediated rejection (TCMR) and NASH (NASH-LT). While liver biopsy is the gold standard method for diagnosis of graft pathology, it is invasive and is associated with risks. The goal of our study was to develop a Machine Learning (ML) tool integrating clinical variables with methylation patterns on circulating DNA in plasma as a non-invasive diagnostic tool of graft injury. We generated methylation profiles of circulating DNA in a pilot study of 43 LTRs (11 NASH-LT, 19 TCMR, and 13 Control-LT), and developed an L2 multinomial logistic regression ML approach across 101 bootstrapped models to distinguish between the graft conditions. NASH was associated with distinctive methylation patterns on genes involved in fatty acid metabolism, while methylation of platelet-derived growth factors was identified in patients with TCMR. Our ML model achieved a mean multi-classification accuracy of 0.91, with mean specificity and sensitivity of 0.94 and 0.91, respectively. The model was found to be particularly adept at detecting TCMR and Control-LT, with true positive rates (TPRs) of 95% and 90%, and areas under the curve (AUROC) of 0.992 and 0.985, respectively. For NASH-LT, the models achieved a performance with a TPR of 82% and an AUROC of 0.991. These preliminary results suggest that our newly developed ML tool, leveraging cell-free DNA methylation and clinical variables, is a promising non-invasive classifier of graft pathology.

  Study EGAS00001007171

• AIDS Linked to the Intravenous Experience (ALIVE) Cohort

  The AIDS Linked to the Intravenous Experience (ALIVE) Study is a long-standing community based research effort that includes past and current injection drug users (IDUs). ALIVE has been ongoing since 1988 and is one of the longest-running community-based cohorts of IDUs in existence. The primary objectives when the study started were to characterize the incidence and natural history of HIV among injection drug users (IDUs). At each study visit, participants undergo a series of questionnaires that elicit information about substance use (including drugs used and route of administration) and a blood draw. A subsample of 1200 subjects was selected for genotyping for the NIDA Smokescreen effort who report heroin injection and have existing peripheral blood samples (isolated buffy coat). In addition to injected heroin, ALIVE subjects are assessed on lifetime and previous six months use of marijuana (76.3%), crack (55.5%), snorted cocaine (48.3%), injected cocaine (89.9%), injected speedball (87.0%), and smoking heroin (9.0%). The sample is 33.4% female, ~85% African-American and assessed through a mean maximum age of 49.9 years old. Importantly, subjects are not assessed to meet DSM criteria, but all subjects report having injected drugs. We provide demographic data (age at assessment, sex, self-reported race) and drug use data (lifetime "use" ever endorsed) for each drug class/route described above for each subject

  Study phs001494

• National Heart, Lung, and Blood Institute (NHLBI) Bench to Bassinet Program: The Pediatric Cardiac Genetics Consortium (PCGC) Study

  Multi-center, prospective observational cohort study of individuals with congenital heart defects (CHD). Phenotypic data and source DNA derived from 10,000 probands, parents, and families of interest are being collected to investigate relationships between genetic factors and phenotypic and clinical outcomes in patients with CHD. Phenotype data will be stored at dbGaP, while molecular and sequence data will be stored at BioData Catalyst. The PCGC Cohort is utilized in the following dbGaP substudies. Please click on the following substudies below or in the "Substudies" section of this top-level study page phs001194 PCGC Cohort. phs000571 PCGC: whole exome sequences, whole genome sequences, targeted sequences, MIP sequences, and SNP array data phs001843 PCGC-CMG Collaboration: whole genome sequences The Gabriella Miller Kids First Pediatric Research Program (Kids First) subset of the PCGC project (phs001194) is now accessible through a separate dbGaP study accession: phs001138. To access this dataset, please submit a Data Access Request (DAR) for phs001138. Approval of this DAR will be expedited for approved users of phs001194. To learn about other Kids First datasets visit https://kidsfirstdrc.org/.NHLBI's TOPMed program has provided additional Whole Genome Sequencing for PCGC participants - that data is accessible through a separate dbGaP sudy accession: phs001735. Access to this data set should be requested through a Data Access Request (DAR) for phs001735.

  Study phs001194

• Transcriptome human nasal epithelium

  1. Odors are detected, firstly, by olfactory sensory neurons (OSNs) in the olfactory epithelium of the nose. This neurons then project directly to the olfactory bulb in the brain. Olfaction depends on cellular regeneration of the OE, olfactory bulb and hippocampus, and on their continual re-wiring. The olfactory neural pathway includes regions of the frontal, temporal and limbic brain, which in turn overlap with brain areas involved in brain disorders. OSNs are the only aspect of the human brain exposed to the external environment. This not only makes them vulnerable to environmental changes, but also accessible for biomedical studies. We have already sequenced and developed a protocol for analyzing the transcriptome of mouse main olfactory epithelium and single OSNs. We propose here to perform a similar study for samples from the human olfactory epithelium. We have developed a minimally invasive method for obtaining human OSNs, among other cells from the nasal epithelium. In this experiment, we have obtained cell samples from the olfactory epithelium, including OSN, from healthy volunteers. We would like to further characterize them by RNA sequencing. This will give us valuable insight into human olfaction. It will also provide a first step into a new avenue to study, and find biomarkers for, brain diseases though the analysis of these easily available neurons. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001002226

• The Environmental Determinants of Diabetes in the Young Study (TEDDY)

  Study Overview The Environmental Determinants of Diabetes in the Young (TEDDY) Study is a longitudinal study that investigates genetic and genetic-environmental interactions, including gestational events, childhood infections, dietary exposures, and other environmental factors after birth, in relation to the development of islet autoimmunity and type 1 diabetes (T1D). A consortium of six clinical centers assembled to participate in the development and implementation of the study to identify environmental triggers for the development of islet autoimmunity and T1D in genetically susceptible individuals. Beginning in 2004, the TEDDY study screened over 400,000 newborns for high-risk HLA-DR, DQ genotypes from both the general population and families already affected by T1D. The TEDDY study enrolled around 8,676 participants across six clinical centers worldwide (Finland, Germany, Sweden and three in the United States) in the 15-year prospective follow-up. Participants are followed every three months for islet autoantibody (IA) measurements with blood sampling until four years of age and then at least every six months until the age of 15. After the age of four, autoantibody positive participants continue to be followed at three month intervals and autoantibody negative participants are followed at six-month intervals. In addition to the analysis of autoantibodies, additional data and sample collection are performed at each visit. Parents collect monthly stool samples in early childhood. The parents also fill out questionnaires at regular intervals in connection with study visits and record information about diet and health status in the child's TEDDY Book between visits. Continued long-term follow-up of the currently active TEDDY participants will provide important scientific information on early childhood diet, reported and measured infections, vaccinations, and psychosocial stressors that may contribute to the development of type 1 diabetes and islet autoimmunity. Additional information on the TEDDY study is available in the following articles: Rewers et al., 2008, PMID: 19120261 and Hagopian et al., 2006, PMID: 17130573. Details of the TEDDY protocol can be found in Hagopian et al., 2011, PMID: 21564455. TEDDY data currently available in dbGaP include: gene expression, SNPs, exome, microbiome (gut, nasal, and plasma), RNA sequencing, and whole genome sequencing. For more information on TEDDY Study version history please refer to TEDDY Study dbGaP README File. ImmunoChip SNP DNA from whole blood samples on study participants and their family members (mothers, fathers, and siblings) was obtained and used for SNP genotyping. Genotyping was performed by the Center for Public Health Genomics at the University of Virginia using the Illumina ImmunoChip SNP array, which contains around 196,000 SNPs from 186 regions associated with 12 autoimmune diseases (Hadley et al., 2015, PMID: 26010309). Data cleaning and validation included the removal of subjects with a low call rate (< 5% SNPs missing) and differences in reported sex and prior genotyping at the TEDDY HLA laboratory. Additionally, SNPs with a low call rate or Hardy-Weinberg equilibrium P value < 10-6, except for chromosome 6 due to HLA eligibility requirements, were removed from the final dataset (Törn et al., 2015, PMID: 25422107).TEDDY-T1DExome ArrayDNA from whole blood samples on study participants and their family members (mothers, fathers, and siblings) was obtained and used for genotyping. Genotyping was performed by the University of Virginia using the Illumina TEDDY-T1DExome array. The TEDDY-T1DExome array is a custom chip that contains 550,601 markers from the Infinium CoreExome-24 v1.1 BeadChip and an additional 90,214 tagSNPs specifically selected by the TEDDY investigators based on their associations with nutrients, vitamins, type 2 diabetes, autoimmune diseases, body-mass index, or other exposures and phenotypes measured by TEDDY study.The Illumina GenTrain2 algorithm was used for genotype calling. Sample quality control metrics included sample call rate, heterozygosity rate and concordance of gender between the information reported and genotyped. Gene Expression The TEDDY study collected peripheral blood for the extraction of total RNA from enrolled children starting at 3 months of age, and then at 3 month intervals up to 48 months and then biannually. Total RNA was extracted using a high throughput (96-well format) extraction protocol using magnetic (MagMax) beads technology at the TEDDY RNA Laboratory, Jinfiniti Biosciences in Augusta, GA. Purified RNA (200 ng) was further used for cRNA amplification and labeling with biotin using Target Amp cDNA synthesis kit (Epicenter catalog no. TAB1R6924). Labeled cRNA was hybridized to the Illumina HumanHT-12 Expression BeadChips based on the manufacturer's instructions. The HumanHT-12 Expression BeadChip provides coverage for more than 47,000 transcripts and known splice variants across the human transcriptome. Microbiome The TEDDY microbiome study aimed to characterize the longitudinal development of the microbiome, including bacteria, viruses and other microorganisms in the gut, plasma, and nasal cavity of prediabetic and diabetic subjects compared to autoantibody negative non-diabetic subjects. Stool samples used were collected monthly from 3 to 48 months, after which stool samples were collected every 3 months. Nasal swab samples were collected every 3 months starting at 9 months of age until 48 months, after which nasal swabs were collected every 6 months. Plasma samples were collected every 3 months starting at 3 months of age until 48 months, after which plasma samples were collected every 6 months. If the subject was autoantibody positive at 48 months then they remained on the 3 month collection interval for nasal swab and plasma samples. Samples underwent 16s rRNA gene sequencing, DNA and viral RNA metagenomics shotgun sequencing, and sequencing of the internal transcribed spacer (ITS) regions. Additional information on the TEDDY microbiome data is available in the following articles: Vatanen et al., 2018, PMID: 30356183, Stewart et al., 2018, PMID: 30356187, and Vehik et al., 2020, PMID: 31792456. RNA Sequencing The TEDDY study aimed to characterize the transcriptome in subjects with islet autoimmunity and type 1 diabetes compared to matched control subjects. Peripheral blood was collected to extract total RNA from enrolled children starting at 3 months of age, and then at 3 month intervals up to 48 months and then biannually. Total RNA was extracted using a high throughput (96-well format) extraction protocol using magnetic (MagMax) beads technology at the TEDDY RNA Laboratory, Jinfiniti Biosciences in Augusta, GA. Purified RNA was then sent to the Broad Institute for the generation of the TEDDY RNA sequencing (RNA-Seq) data. The RNA samples were prepped using Superscript III reverse transcriptase and Illumina's TruSeq Stranded mRNA Sample Prep Kit. The TruSeq libraries were run on the Illumina HiSeq2500 platform. Whole Genome Sequencing The TEDDY study aimed to conduct deep whole genome sequencing and examine the genomic variations in subjects with islet autoimmunity and type 1 diabetes compared to matched autoantibody negative and non-diabetic children. DNA from whole blood was obtained from TEDDY children for whole genome sequencing. The WGS data were generated on the Illumina HiSeq X Ten system.

  Study phs001442

• PAGE: The Charles Bronfman Institute for Personalized Medicine (IPM) BioMe BioBank

  The Institute for Personalized Medicine (IPM) BioMe Biobank is a consented, EMR-linked medical care setting biorepository of the Mount Sinai Medical Center (MSMC) drawing from a population of over 70,000 inpatients and 800,000 outpatient visits annually. MSMC serves diverse local communities of upper Manhattan, including Central Harlem (86% African American), East Harlem (88% Hispanic Latino), and Upper East Side (88% Caucasian/white) with broad health disparities. IPM BioMe Biobank populations include 28% African American, 38% Hispanic Latino predominantly of Caribbean origin, 23% Caucasian/White. IPM BioMe Biobank disease burden is reflective of health disparities with broad public health impact. Biobank operations are fully integrated in clinical care processes, including direct recruitment from clinical sites waiting areas and phlebotomy stations by dedicated Biobank recruiters independent of clinical care providers, prior to or following a clinician standard of care visit. Recruitment currently occurs at a broad spectrum of over 30 clinical care sites. This study is part of the Population Architecture using Genomics and Epidemiology (PAGE) study (phs000356).

  Study phs000925

• RNAseq data to study PRPF6 regulated splice forms in colon cancer cell lines

  Alternative splicing plays critical roles in differentiation, development, and cancer (Pettigrew et al., 2008; Chen and Manley, 2009). The recent identification of specific spliceosome inhibitors has generated interest in the therapeutic potential of targeting this cellular process (van Alphen et al., 2009). Using an integrated genomic approach, we have identified PRPF6, an RNA binding component of the pre-mRNA spliceosome, as an essential driver of oncogenesis in colon cancer. Importantly, PRPF6 is both amplified and overexpressed in colon cancer, and only colon cancer cells with high PRPF6 levels are sensitive to its loss. Our data clearly point to an important role for PRPF6 in colon cancer growth and suggest that a better understanding of its role in alternative splicing in colon cancer is warranted. To determine the specific alternative splice forms that PRPF6 regulates in colon cancer, we plan three experiments: 1. The first involves knocking down expression of PRPF6 in two different cancer cell lines with 3 different siRNAs, and then completing RNA-seq to determine the gene expression changes that occur relative to a non-targeting control siRNA. Because of the role for PRPF6 in pre-mRNA splicing, we especially want to quantify the changes in splice-specific forms of all genes genome-wide to identify genes whose splicing is altered upon PRPF6 knockdown. 2. The second involves immunoprecipitating PRPF6 from two different cancer cell lines and isolating any RNA that is bound to PRPF6, since PRPF6 is an RNA-binding protein. We then want to carry out RNA-seq to identify which RNA molecules co-immunoprecipitated with PRPF6. This will help us determine possible functions for PRPF6 in regulating colon cancer growth. 3. The third involves overexpressing PRPF6 in cell lines and then carrying out RNA-seq to identify any changes in splice-specific gene expression. This will allow us to determine whether increased PRPF6 expression is sufficient to drive alternative splicing changes.

  Dataset EGAD00001000817

• Understanding the Biology of Language Impairment through Whole Genome Sequencing

  This study involves the whole genome sequencing of a cohort of 390 individuals assessed for language ability, IQ, and behavior as schoolchildren. The primary goal of the study is to identify genes, regulatory elements, and pathways which may underlie variation in language ability within an average population. 

  Study phs002255

• Genome-Wide Association Study on Calcific Aortic Valve Stenosis in Quebec (QUEBEC-CAVS)

  Calcific aortic valve stenosis (CAVS) is a common and life-threatening heart disease with no drug that can stop or delay its progression. A genome-wide association study (GWAS) on 1,009 cases and 1,017 ethnically-matched controls was performed to identify susceptibility genes for CAVS.

  Study phs001492