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• Gut metagenome associations with extensive digital health data in a volunteer-based EstMB cohort second timepoint data

  As part of the Estonian Biobank, we established the Estonian Microbiome Cohort which includes stool, oral and plasma samples from 2,509 participants and is supplemented with multi-omic measurements, questionnaires, and regular linkages to national electronic health records. Out of the 2,509 Estonian Microbiome Project participants, a sub-cohort of over 300 individuals provided an additional stool sample after a median follow-up period of 4.4 years. All participants of the EstMB cohort gave informed consent for the data and samples to be used for scientific purposes. In the second time point, the participants were instructed to send the samples by post immediately after taking the sample and time their sample collection to avoid shipping on the weekends. In the study, by utilising retrospective medication usage data from the electronic health records and the Estonian microbiome cohort shotgun metagenomics data set (n = 2,509), we systematically evaluate the long-term effects of antibiotics and human-targeted medications on the gut microbiome. We show that past usage of medications is associated with the gut microbiome. For example, the effects of antibiotics, psycholeptics, antidepressants, proton pump inhibitors, and beta-blockers are detectable several years after use. Furthermore, by analysing a subcohort (n >300 individuals) from the second time point, we show that similar changes in the gut microbiome occur after treatment initiation or discontinuation, possibly indicating causal effects.

  Study EGAS50000001181

• NHLBI TOPMed: Australian Familial Atrial Fibrillation Study

  In the Australian Familial AF Study, a cohort of probands with familial AF was recruited for genetics studies at the Victor Chang Cardiac Research Institute. Familial AF cases were identified from in-patient and out-patient populations at St. Vincent's Hospital and by referral from collaborating physicians throughout Australia. Study subjects underwent clinical evaluation with history, ECG and echocardiogram, and informed consent was obtained from all participants. 151 probands aged <66 years at the time of diagnosis were included in this analysis. The control cohort was comprised of age- and sex-matched individuals (n=151) who had no history of cardiovascular disease. In the current TOPMed study, we have performed whole genome sequencing in European Ancestry cases with early-onset atrial fibrillation (defined as atrial fibrillation onset prior to 61 years).

  Study phs001435

• The Mutational Landscape of Head and Neck Squamous Cell Carcinoma

  This study was the first-known large-scale effort to uncover the mutational spectrum of head and neck cancers. We analyzed whole-exome sequence from 92 tumor-normal pairs and retained 74 of them for significance analysis. The majority exhibited a mutational profile consistent with tobacco exposure; human papilloma virus sequence was detectable in 15% of cases. In addition to identifying previously known HNSCC genes (TP53, CDKN2A, PTEN, PIK3CA, and HRAS), the analysis revealed many genes not previously implicated in this malignancy. At least 30% of cases harbor mutations in genes (such as NOTCH1, IRF6, TP63) that regulate squamous differentiation, implicating alterations in this process as a major driver of HNSCC carcinogenesis. Altogether, the results suggest that large-scale exome sequencing may illuminate fundamental tumorigenic mechanisms with important therapeutic implications.

  Study phs000370

• HuBMAP: Single-Cell Data from Human Tissues

  The small bowel and colon are organs critical for maintaining homeostasis of the human body by mediating nutritional absorption upon the ingestion of food. Though both organs are extensive in length, there are known differences in function and cellular heterogeneity within different portions of each. Also, a cross section anywhere in the bowel reveals a complex layering of components involved in absorption and secretion, motility of gut contents, circulation, and immunity. We are mapping the complexity of the the small bowel and colon with cell-to-cell resolution in histologic sections, both along their lengths and across multiple individuals. Our molecular data consist of single cell ATAC-seq and RNA-seq. These profiles are spatially mapped to histologic sections using CO-Detection by indEXing (CODEX), a highly multiplexed system of antibody-tagged target epitopes.

  Study phs002272

• Hereditary Cancer Predisposition Syndromes and Uveal Melanoma

  Uveal melanoma (UM) is a subtype of melanoma characterized by the strong contribution of genetic rather than environmental factors in the pathogenesis of the disease, making it an ideal model disease to study the genetic basis of cancer. The long-term goal of our laboratory is to determine the genes and mechanisms responsible for hereditary cancer predisposition associated with UM. BAP1 has been identified as a candidate gene with definitive association with predisposition to UM. However, pathogenic variants in BAP1 are detected in only a small subset of UM patients even those with strong personal and family history of cancer suggesting the existence of other candidate genes. The goal of this project is to identify novel candidate genes contributing to hereditary predisposition to UM in patients with no detectable germline pathogenic variant in BAP1.

  Study phs001943

• RNA-seq of Glioblastoma stem cells

  Chromatin accessibility discriminates stem from mature cell populations, enabling the identification of primitive stem-like cells in primary tumors, such as Glioblastoma (GBM) where self-renewing cells driving cancer progression and recurrence are prime targets for therapeutic intervention. We show, using single-cell chromatin accessibility, that primary GBMs harbor a heterogeneous self-renewing population whose diversity is captured in patient-derived glioblastoma stem cells (GSCs). In depth characterization of chromatin accessibility in GSCs identifies three GSC states: Reactive, Constructive, and Invasive, each governed by uniquely essential transcription factors and present within GBMs in varying proportions. Orthotopic xenografts reveal that GSC states associate with survival, and identify an invasive GSC signature predictive of low patient survival. Our chromatin-driven characterization of GSC states improves prognostic precision and identifies dependencies to guide combination therapies.

  Study EGAS00001003070

• Framingham Heart Study-Cohort (FHS-Cohort) - 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. Related Studies Other Framingham data available include: Imaging studies (Framingham Heart Study-Cohort (FHS-Cohort)-Imaging, phs003593), Genetics and genomics (Framingham Cohort, phs000007), Collaborative Cohort of Cohorts for COVID-19 Research (C4R): (Framingham Heart Study, phs002911), and as a component of the Sleep Heart Health Study (SHHS-BioLINCC, phs003637). Available Data Original cohort: data now include examination data from the first 32 clinical exams, selected ancillary data, and event follow-up through 2018. Offspring/Omni1 cohort: Data available include Framingham Offspring examination data from the first 9 clinical exams and selected ancillary data and event follow-up through 2019. Also included are the first 4 exams from the OMNI 1 cohort. Third Generation/Omni2/New Offspring Cohort: Data available include Framingham Generation 3 examination data from the first 3 clinical exams, selected ancillary data and event follow-up through 2019. Also included are the OMNI 2 and New Offspring (NOS) cohorts. A genetic pedigree is not provided for the Framingham phenotype only data. Objectives The objectives of the Framingham Study are to study the incidence and prevalence of cardiovascular disease (CVD) and its risk factors, trends in CVD incidence and its risk factors over time, and familial patterns of CVD and risk factors. Other important objectives include the estimation of incidence rates of disease and description of the natural history of cardiovascular disease, including the sequence of clinical signs and systems that precede the clinically recognizable syndrome and the consequences and course of clinically manifest disease. Background Original cohort: The original cohort of the Framingham Study began in 1948 under the U.S. Public Health Service and was transferred under the direct operations of the new National Heart Institute, NIH, in 1949. Participants were sampled from Framingham, Massachusetts, including both men and women. This was the first prospective study of cardiovascular disease and identified the concept of risk factors and their joint effects. Offspring/Omni1 cohort: With the aging of the Framingham cohort and with interest in familiar aggregation and heritability, a new cohort consisting of the offspring of the original cohort was sampled. Spouses of offspring were also included. This new sample, began enrollment in 1971 and constituted a second generation of participants, permitting new assessment of risk factors and outcomes, and provided a resource for the genetic analyses which were yet to come. The Offspring participants have had repeated examinations, though at typically longer intervals than the original cohort. Third Generation/Omni2/New Offspring Cohort: Thirty-one years after enrollment began for the second generation of the Framingham Heart Study (Framingham Offspring Study), Framingham investigators began enrolling adults with at least one parent enrolled in the Offspring study into the Framingham Generation 3 cohort. The addition of the third generation was expected to facilitate investigation of secular trends in risk factors and indicators of health and disease within families, to enhance statistical power to detect genetic and environmental determinants of complex diseases, and to clarify how subclinical cardiovascular disease predicts occurrence of overt clinical events. Participants Original cohort: At entry to the study in 1948-1952, the study recruited 5,209 men and women, ages 28-62 years, living in Framingham, MA. Offspring/Omni1 cohort: 5,124 men and women, ages 5-70 years at entry consisting of offspring of the original Framingham cohort (and spouses of the offspring). In 1994, the Omni Cohort 1 enrolled 507 men and women of African-American, Hispanic, Asian, Indian, Pacific Islander and Native American origins, who at the time of enrollment were residents of Framingham and the surrounding towns. Third Generation/Omni2/New Offspring Cohort: 4095 men and women, almost all who self reported their ethnicity as white, ages 19+ years at entry, with at least one parent in the Framingham Offspring study, participated in the Gen III cohort. The New Offspring Cohort enrolled spouses of Offspring participants that were not otherwise enrolled and had at least two biological children participating in Gen III. 103 New Offspring Spouses (47 men and 56 women) participated. The OMNI 2 cohort enrolled additional ethnically diverse participants, including many individuals related to the participants of Omni Cohort 1 and also individuals unrelated to Omni Cohort 1 members for a total of 410 new participants. Design The cardiovascular disease conditions under investigation include coronary heart disease (angina pectoris, myocardial infarction, coronary insufficiency and sudden and non-sudden death), stroke, hypertension, peripheral arterial disease and congestive heart failure. Original cohort: The Framingham Study is a longitudinal investigation of constitutional and environmental factors influencing the development of CVD in men and women. Examination of participants has taken place every two years and the cohort has been followed for morbidity and mortality over that time period. Offspring/Omni1 cohort: By 1975, a sample of 5,124 men and women, consisting of offspring of the original Framingham cohort (and spouses of the offspring) had participated in the study. Additional studies of these subjects have continued under research contracts. Third Generation/Omni2/New Offspring Cohort: The children of Offspring Cohort participants were initially identified who would be 20 years of age or older by the end of the enrollment period. A higher priority for recruitment was assigned to individuals who belonged to large extended families, in order to complement phenotypic and genotypic information already obtained from prior generations. The baseline examination was begun in 2002 and completed in 2005.

  Study phs003594

• California Pacific Medical Center Research Breast Health Cohort

  Description of Cohort: The California Pacific Medical Center (CPMC) Breast Health Cohort is a cohort study based at CPMC and is linked to the San Francisco Mammography Registry, one of the sites of the NCI-funded Breast Cancer Screening Consortium (U01CA063740). CPMC is a community hospital in San Francisco, which has one of the highest volumes for mammography in San Francisco. Between September 2004 and June 2007, >90,000 mammograms were performed at CPMC. The CPMC breast health cohort collects demographic and risk factor data on women receiving mammography through participation in the San Francisco Mammography Registry, as part of the Breast Cancer Screening Consortium (U01CA063740). The SFMR database collects information from all sources, including a questionnaire on demographic and risk factor information, the clinical results of the breast examination, the measures of breast density by Dr. John Shepherd and the women who agreed to donate a blood sample. By merging these various sources of information we have very efficiently developed a large sample of women who have donated blood and have had a measure of mamographic density. Blood Collection: Dr. Steve Cummings is leading an effort to collect and archive blood samples from women who are receiving mammography screening. All women who are sent for a screening mammogram at CPMC are considered eligible. Since the cohort began collecting blood samples in July 2004 until June 2007, samples have been collected from over 11,000 women. Measurement of Breast Density: Dr. John Shepherd is currently measuring breast density in a large fraction of the cohort using an automated approach with single X-ray absorptiometry. Dr. Shepherd has established a link with the CPMC mammography center that allows him to collect routine digital mammography information. Using the data from the mammogram, Dr. Shepherd and his group have developed the single X-ray absorptiometry (SXA) technique for measuring density which is described in more detail below. The table demonstrates the distribution of demographic variables and some breast cancer risk factors of women who donated blood and had a breast density measurement in the CPMC breast health cohort. Nearly 80% of the participants are Caucasian and most of the women are post-menopausal with a median age of ~52. Since it will be difficult to accrue a large enough sample from each ethnic group, our study will focus only on Caucasian women. Table: Demographic variables, reproductive history and family history of breast cancer among 2962 women participating in the CPMC cohort study who contributed blood samples between 1994-1997. Variable Median/Percentage Age (Median/IQR) 52 (46-59) Ethnicity Caucasian/White 0.76 Asian/Pacific Islander 0.141 Hispanic 0.029 Mixed Race/Ethnicity 0.039 African American/Black 0.022 American Indian 0.001 Other 0.009 First degree relative with breast cancer 0.17 Age at first birth Nulliparous 0.39 Age<20 0.043 Age>40 0.032 Age<30, ≥20 0.251 Age>30, ≤40 0.282 Measurement of Breast Density in Cohort: Measurement of breast density is accomplished using an automated technique for all mammograms obtained by Dr. Shepherd using Single X-Ray absorptiometry (SXA). SXA measurement of breast density is done on approximately 30% of all screening mammograms. Below we describe the method for measurement of breast density by SXA by Dr. Shepherd's group and its validation and association with breast cancer. As we demonstrate below, breast density, as measured by SXA, is an automated, highly reproducible measure of the density of breast tissue and is associated with breast cancer risk. SXA for Quantifying Breast Density: Single x-ray absorptiometry (SXA) was initially developed for measuring bone density. SXA can determine the fraction of each of two densities simultaneously using the fact the sample is a constant thickness, the thickness in known, and the total attenuation is known. In applying this technique to breast density, we assume a two compartment model: fat and non-fatty (fibroglandular tissue). We use a reference material composed of various concentrations of two materials: one which is the same density as fat and another which is the same density as fibroglandular tissue. The reference material (phantom) is placed in the X-ray field with each mammogram. We have been able to implement this in a way that is unintrusive to the patient and technologist at CPMC. Assuming this two-compartment model and a constant known breast thickness, we can then calculate the percent density at any region of the breast based on the assumption that % pixel grey-scale is proportion to the mass fractions of breast fat and lean tissue. If reference materials (a phantom) of fat and fibroglandular tissue are imaged with the patient's breast and the reference materials have the same thickness as the patient's breast, then the breast's grey-scale values can be converted to fat/fibroglandular mass fractions by interpolating between those two references. The total percent density is found by averaging the volume fraction over all breast pixels. The phantom being used for breast density assessment at CPMC began to be used in September 2004. The phantom does not have to be manipulated by the technologist and stays attached on the mammography device during standard craniocaudal (CC) views. Thus it creates minimal to no interference with the clinical mammogram. Reproducibility of breast density measures: Traditional measures of mammographic density require some human interpretation. A human reader outlines the area perceived to be dense and a computer then calculates the percent area outlined as a percent of the entire image. Thus, while traditional mammographic density is associated with breast cancer risk, it has some limitations. In a study by Drs. Shepherd, Kerlikowske, et al., the correlation coefficient (Pearson's R) between different readers was 0.8-0.9. In contrast to the traditional mammographic density measurement, the SXA measurement is fully automated and, therefore, the reproducibility of the measurement is higher. Dr. Shepherd and colleagues have performed a replication study of SXA as a measurement of breast density. They have estimated the correlation coefficient of the SXA measurement of breast density to be >0.98. Thus, as expected for an automated measure, SXA is a highly reproducible measure of mammographic breast density. Drs. Shepherd and Kerlikowske have recently analyzed the association between breast cancer risk and breast density as measured by SXA (Shepherd et al., Cancer Epi Biomarkers and Prev, 2011, PMID: 21610220). They found that women in the highest quintile of % volumetric density had an odds ratio of 4.1 (95% CI: 2.3 - 7.2) for breast cancer risk compared to women in the lowest quintile of volumetric density. Thus volumetric density appears to be a highly reproducible, automated measure of breast cancer.

  Study phs000395

• Cell-type eQTLs for single-cell Mendelian Randomisation

  The following study mapped eQTLs in the post-mortem human brain from snRNA-seq generated on 391 individuals. Following eQTL discovery and identification of state-specific eQTLs (dynamic associations interacting with disease), colocalisation and MR was performed integrating GWAS from 42 traits, for the identification of putatively causal genes with cell-type specific context. This study contains raw sequencing data and genotype for two datasets used in this work; - The MRC 60 dataset, which contains snRNA-seq generated on post-mortem brain from 60 control individuals (104 samples total, split across prefrontal cortex and hippocampus). Samples were pooled into 27 distinct pools, each of which was split across 4 lanes. Following sequencing and mapping using cellranger, demultiplexing was done using Demuxlet using the pool-specific genotype data (which contain sample IDs). - The Roche PD dataset, which is 10X multiome data generated on on 70 PD and 22 control individuals.

  Study EGAS50000000687

• Trans-ethnic genome-wide association study identifies 12 genetic loci influencing blood pressure and implicates a role for DNA methylation

  We carried out a trans-ethnic genome-wide association and replication study of blood pressure phenotypes amongst up to 320,251 individuals of East Asian, European and South Asian ancestry. We find genetic variants at 12 novel loci to be associated with blood pressure (P=3.9x10-11 to P=5.0x10-21). The sentinel blood pressure SNPs are enriched for association with DNA methylation at multiple nearby CpG sites, suggesting that at some of the loci identified DNA methylation may lie on the regulatory pathway linking sequence variation to blood pressure. The sentinel SNPs at the 12 novel loci point to genes involved in vascular smooth muscle (IGFBP3, KCNK3, PDE3A and PRDM6) and renal (ARHGAP24, OSR1, SLC22A7, TBX2) function. The novel and known genetic variants predict increased left ventricular mass, circulating levels of NT-proBNP, cardiovascular and all-cause mortality (P=0.04 to 8.6x10-6). Our results provide new evidence for the role of DNA methylation in blood pressure regulation.

  Study EGAS00001001427