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• Single-cell Kinnex sequencing of Alzheimer's disease isoform profile

  Alzheimer’s disease (AD) is the most common cause of dementia, yet its molecular causes remain incompletely understood. RNA diversity in part arising from dysregulated splicing may contribute to AD pathogenesis; however, the ability to interrogate the resulting full-length isoforms in single brain cells has been technologically limited. Here we report the use of PacBio Kinnex long-read sequencing combined with 10X Genomics single-cell preparations to identify both annotated and unannotated RNA isoforms. Eight AD and seven non-diseased post-mortem human brains yielded ~70,000 single nuclei showing diverse, differentially expressed, and switched transcripts in multiple genes. Cell-type-specific isoform expression and variants with intra-exonic junctions associated with reverse transcriptase-mediated somatic gene recombination were also detected. Novel isoforms, including CHI3L1 and SEPTIN4, were altered in AD. Kinnex sequencing of RNA isoforms from single nuclei detected vast isoform diversity amongst brain cell types, representing an under-explored element in AD and other brain disorders.

  Study EGAS50000001476

• Human islet 3D chromatin maps provide insights into type 2 diabetes

  The transcriptional output of each cell type is controlled by thousands of enhancers, many of which contain genetic risk variants for common diseases such as type 2 diabetes (T2D). To gain insight into how enhancer variation influences diabetes risk, we created promoter capture Hi-C maps in human pancreatic islets. This linked diabetes-associated islet enhancers with their target genes, often located hundreds of kilobases away. We identified hubs that show spatial and functional connections between enhancersand target genes related to islet function and diabetes. We demonstrate that genetic variants distributed across hub enhancers have a major impact on T2D heritability, and use this knowledge to identify individuals in whom islet regulatory variation has a prominent role in T2D risk. Our results demonstrate the importance of 3D chromatin architecture for molecular interpretation of T2D genetic association signals, and define genomic spaces that harbor a distinct component of the T2D polygenic burden.

  Study EGAS00001002917

• Add Health: Longitudinal Study of a Nationally Representative Sample of Adolescents in Grades 7-12 in the United States during the 1994-95 School Year, Followed into Adulthood with Five Interviews/Surveys in 1995, 1996, 2001-02, 2008, and 2016-18

  The National Longitudinal Study of Adolescent to Adult Health [Add Health] is an ongoing longitudinal study of a nationally representative U.S. cohort of more than 20,000 adolescents in grades 7-12 (aged 12-19 years) in 1994 followed into adulthood with five interviews/surveys in 1995, 1996, 2001-02, 2008, and 2016-18. Add Health was designed to understand how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. Add Health contains unprecedented environmental, behavioral, psychosocial, biological, and genetic data from early adolescence and into adulthood on a large, nationally representative cohort with unprecedented racial, ethnic, socioeconomic, and geographic diversity. Add Health has a large, multidisciplinary user base of over 50,000 researchers around the world who have published over 3,400 research articles. Add Health is housed at the Carolina Population Center of the University of North Carolina at Chapel Hill. Add Health datasets are distributed according to a tiered data disclosure plan designed to protect the data from the risk of direct and indirect disclosure of respondent identity. Add Health's large sample size, population diversity and rich longitudinal database of psychosocial, physical, and contextual data will permit investigation of an exceptionally broad range of phenotypes with known genetic variation. Prospective longitudinal measures are available to document change over time in each of these phenotypes, as well as change in the social environment and life experiences, making the Add Health sample ideal for understanding genetic linkages with health and behavior across the life course. The original design of Add Health included important features for understanding biological processes in health and developmental trajectories across the life course of young people, including an embedded genetic sample with more than 3,000 pairs of adolescents with varying biological resemblance (e.g., twins, full sibs, half sibs, and adolescents who grew up in the same household but have no biological relationship), testing of saliva and urine for sexually transmitted infections and HIV, and biomarkers of cardiovascular health, metabolic processes, immune function, renal function, and inflammation. Add Health therefore has critical objective indicators of health status and disease markers in young adulthood, well before chronic illness or its complications emerge in later adulthood. Because DNA has been collected on the full sample at Wave IV, it is possible to link genetic profiles with social, behavioral, and biological measures over time from adolescence into adulthood. Add Health sampled the multiple environments in which young people live their lives, including the family, peers, school, neighborhood, community, and relationship dyads, and provides independent and direct measurement of these environments over time. Add Health contains extensive longitudinal information on health-related behavior, including life histories of physical activity, involvement in risk behavior, substance use, sexual behavior, civic engagement, education, and multiple indicators of health status based on self-report (e.g., general health, chronic illness), direct measurement (e.g., overweight status and obesity), and biomarkers. No other data resource with this expanse of genotype and phenotype data on a large nationally representative longitudinal sample with race, ethnic, socioeconomic, and geographic diversity exists. A complete reference guide on study design and accomplishments can be found on the Add Health website: https://cdr.lib.unc.edu/concern/articles/6t053j27s.

  Study phs001367

• Atherosclerosis Risk in Communities Study (ARIC-BioLINCC)

  Data Access NOTE:Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. At present, the ARIC sIRB has determined that ARIC data cannot be shared with for-profit entities.Related Studies Other ARIC data available include: Imaging studies (ARIC-Imaging), Genetics and genomics (ARIC, phs000280.v8.p2), Collaborative Cohort of Cohorts for COVID-19 Research (C4R): ARIC (phs002988.v1.p1), and as a component of the Sleep Heart Health Study (SHHS-BioLINCC, phs003637.v1.p1). Available Data Data available for request include ARIC v1-v8 examination cycles, collated annual follow-up communication data for contact years 2-32, and follow-up for mortality, heart disease, and stroke events through 2019. Also included are data from ancillary studies. Objectives The objectives of ARIC are to: 1) investigate associations of factors, including those not previously measured in cohort studies, with prevalence of atherosclerosis and incidence of CHD, clinical stroke and other cardiovascular diseases; and 2) measure cardiovascular disease occurrence and trends and relate these to community levels of, and changes in, risk factors, medical care and atherosclerosis. Background At the time of project initiation, the NHLBI had long recognized the need for longitudinal studies to identify the biochemical and physiological markers and specific environmental factors which place individuals at high risk for the major atherosclerosis diseases. The development of reliable ultrasound examination of peripheral arteries enhanced the expected benefit of such studies. Community surveillance planning began for ARIC in response to recommendations of the 1978 NHLBI Workshop on the Decline in CHD Mortality and has been extended in its purpose to evaluate the large geographic differences in U.S. mortality. Participants Black and white men and women, age 45-64 at entry; sample size: 15,792. Design ARIC is a large-scale, long-term prospective study that measures associations of established and suspected coronary heart disease risk factors with both atherosclerosis and new CHD events in men and women from four geographically diverse communities. The project has two components: community surveillance of morbidity and mortality; and repeated examinations of a representative cohort of men and women in each community. The community surveillance involves abstracting hospital records and death certificates and investigating out-of-hospital deaths. The representative cohorts include approximately 4,000 persons from each community. Community surveillance data includes detailed hospital record abstraction, ECG tracings, and event adjudication. Data from out-of-hospital events in the community include physician, informant, and coroner questionnaires as well as death certificate data and event adjudication. Community surveillance ended in 2014.Cohort participants were examined four times at three year intervals between 1987 and 1998, and have been continuously contacted annually to update their medical histories. Atherosclerosis was measured by carotid ultrasonography. Risk factors studied include: blood lipids, lipoprotein cholesterols, and apolipoproteins; plasma hemostatic factors; blood chemistries and hematology; sitting, supine and standing blood pressures; anthropometry; fasting blood glucose and insulin levels; ECG findings; cigarette and alcohol use; physical activity levels; dietary aspects; and family history. Clinic visits were restarted in 2011 with ARIC visit 5.

  Study phs003738

• Lipid Research Clinics - Prevalence Study (LRC-PS-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: The LRC Program began in 1971 under the sponsorship of the National Heart, Lung, and Blood Institute, National Institutes of Health. Part of this program was the Lipid Research Clinics Prevalence Study, a standardized series of cross-sectional surveys of various North American populations designed to determine the prevalence of dyslipidemias and to describe the distributions of lipids and lipoproteins in major ethnic and social groups. In addition to contributing to the aggregate analysis, each independent population-based study was designed with capabilities for separate analyses of lipid and lipoprotein distributions. The participating populations were not selected to be a probability sample representative of the North American population per se, but by virtue of their size and economic and geographical diversity, they provide a useful cross-sectional group. The Family Study was the third phase of the Lipids Research Clinics North American Population Studies. The Family Study was designed to obtain knowledge of the distribution of lipids and lipoproteins among family members and of the association of familial and genetic attributes to dyslipoproteinemias. Background: An association between serum cholesterol and coronary heart disease is well established. A system was developed for classifying hyperlipoproteinemias into six types of patterns, as a basis for characterizing lipoprotein disorders. The Lipid Research Clinics was thus created to improve the detection of and clinical management of hyperlipoproteinemias. The three primary objectives were: 1) to acquire data on the prevalence of different types of hyperlipoproteinemia in various age and ethnic groups, with special emphasis on the nature and frequency of genetic forms; 2) to collect reliable data on the prevalence and incidence of atherosclerosis in different types of hyperlipoproteinemia; and 3) to conduct an intervention trial to determine if lowering plasma lipid levels would reduce the risk of CHD. Participants: There were 60,495 participants. Conclusions: Data from this study confirm findings from earlier studies in developed countries, showing age-related differences in plasma lipid levels. However, for overall distributions, the LRC data showed slightly lower cholesterol and markedly higher trigylceride values than those previously reported for North America. Some variation in plasma lipid values was evident among the clinic populations. The large number of participants within most subgroups permitted a variety of analytic and comparative studies. For example, data from the large pediatric population revealed a drop in plasma cholesterol levels in adolescent males and females. Males aged 20-50 years had higher cholesterol levels than females in the same age group, and higher trigylceride levels between ages 20-70 years. Numbers were also significient for meaningful comparisons between lipid distributions of females who were taking sex hormones and those who were not; in females taking sex hormones, cholesterol and triglyceride levels were higher for subjects younger than 45 years, but slightly lower after age 45, than lipid levels in females not taking hormones (Circulation 1979; 60(2):427-439).

  Study phs003995

• GSA bigbatch raw data

  Unfiltered genotype data for a larger batch (Batch 2) of 8,697 DDD Study participants (and 1 "Blank" sample). Samples include 2,858 mothers, 2,857 fathers and 2,982 probands, and form 2,918 trios. Most of the probands have been previously genoyped on the llumina HumanCoreExome BeadChip (EGAD00010001598) or the Illumina InfiniumCoreExome Beadchip (EGAD00010001600). All samples were genotyped on the Illumina Global Screening Array.

  Dataset EGAD00010002569

• GSA pilot raw data

  Unfiltered genotype data for a pilot study (Batch 1) of 1,140 DDD Study participants (and 12 "Empty" samples). Samples include 380 mothers, 382 fathers and 378 probands, and form 376 trios. Most of the probands have been previously genoyped on the llumina HumanCoreExome BeadChip (EGAD00010001598) or the Illumina InfiniumCoreExome Beadchip (EGAD00010001600). All samples were genotyped on the Illumina Global Screening Array.

  Dataset EGAD00010002567

• Single-nuclei ATAC sequencing of pheochromocytoma and paraganglioma arising from germline SDHB mutations

  10x genomics single-nuclei ATAC sequencing of 7 SDHB-deficient non-metastatic and metastatic pheochromocytoma and paraganglioma, and 1 normal adrenal medulla sample. snATAC-seq was conducted using the "Van Helsing" protocol (dx.doi.org/10.17504/protocols.io.bw52pg8e). Once processed, snATAC-seq libraries were sequenced on the Illumina NextSeq 500 (Illumina, USA) using 50bp paired-end sequencing. Raw sequencing data in BCL format was demultiplexed using cellranger-atac mkfastq (V2.0.0). This dataset contains sequencing reads in FASTQ format. R1/R3 files contain the forward and reverse sequencing reads, respectively, R2 contains the 10x Barcode.

  Dataset EGAD50000000503

• Tumor Normal Pair for SV mosaic

  Simulated (based on real world data) tumor normal pair designed for benchmarking and optimisation of structural variation callers. The calls are derived from 12 patients in the hartwig database requested by the EUCANCan project. Paired-end sequencing data was imputed into the normal reference data to simulate real world variation like purity as well as technical impact of sequencing technologies. The dataset contains a tumor sequenced to ±90x depth and a normal control sequenced to ±30 x depth of these imputed events. The break junctions of all detected SVs in the original cases are imputed in this data from diagnostic WGS sequencing data.

  Dataset EGAD50000000668

• SUM-seq data for Macrophage polarisation to M1 and M2 phenotypes experiment

  We stimulated iPSC-derived M0 macrophages with LPS and IFN-γ to induce M1 polarization or IL-4 to induce M2 polarization. To discern early and sustained responses at chromatin accessibility and gene expression levels, we collected samples at five time points along the two polarization trajectories; prior to stimulation (M0) and at 1-hour, 6-hour, 10-hour, and 24-hour intervals, each sampled in duplicates totaling 18 samples, and subjected them to SUM-seq library preparation. Sequenced files for both data modalities are provided as demultiplexed fastq files.

  Dataset EGAD50000001206