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• Defining the metastasome in colorectal cancer: Implications for hypotheses on metastasis evolution and personalized therapy (HIPO-032)

  Personalized cancer therapy aims at individual genetic changes characterizing primary cancers. Still, however, metastasis is the major clinically unmet problem, also due to an incomplete understanding of its molecular evolution.This study is the first to define the metastasis-specific whole genome landscape of human colorectal primary vs. matched metastatic lesions.Protein coding, ncRNA genes and 3’UTRs harbored about a third each of single nucleotide variations (SNVs)/indels, 19% of them being metastasis-specific. We found novel mutational hills among ncRNAs and 3’UTRs, copy number changes able to explain changes in microRNA expression in metastases, and novel metastasis-specific mutations in the 3’UTRs on important cancer signalling genes. Some metastatic lesions showed targetable mutations not detected in the primaries. Analysis of mutual exclusivity patterns supported a model that has progressive alterations in important colorectal cancer genes and revealed new partners. Metastatic lesions were enriched in SNVs, specific structural variations, and alterations in genes affecting cell adhesion and extracellular matrix interaction.Furthermore, a hepatic stellate activation cascade was enriched in metastases, suggesting genetic programs for site-specific colonization. Allele frequency distribution and mutational signature analysis suggests a common ancestor clone to both the primary tumor and the metastasis, with additional mutagenesis ongoing in both sites independently. Taken together, our results significantly add to hypothesis generation on metastasis evolution, and suggest novel metastasis-specific genomic changes which would be missed by current personalized therapy concepts. (HIPO-032)

  Study EGAS00001002717

• Prevention and Early Treatment of Acute Lung Injury (PETAL) - Low Tidal Volume Universal Support Feasibility of Recruitment for Interventional Trial (LOTUS FRUIT) (PETAL-LOTUS FRUIT-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 two main goals of PETAL-LOTUS FRUIT were to conduct a prospective, observational study within all PETAL Network sites to determine the frequency of and outcomes from acute respiratory failure and the current usual care for tidal volume ventilation in patients with and without acute respiratory distress syndrome (ARDS), and to simulate the design and power of the proposed LOTUS trial. Background: A previous study demonstrated improved survival among patients with ARDS receiving tidal volume (Vt) targeted to 6 ml/kg of predicted body weight (PBW). As a result, low–tidal volume ventilation (LTVV) is now recommended for all patients with ARDS, although penetration of this evidence-based practice has been limited, especially early in mechanical ventilation. LTVV may also benefit patients without ARDS. Consequently, there has been increasing call to apply LTVV for all patients with acute respiratory failure upon initiation of mechanical ventilation. The PETAL Network considered performing a pragmatic stepped-wedge, cluster-randomized, controlled, hybrid implementation trial to examine systematic implementation of a default 6 ml/kg PBW LTVV strategy in patients with acute respiratory failure requiring intubation to improve adherence to LTVV and decrease mortality in acute respiratory failure. Trial planning may be better estimated by simulation than routine, simplistic calculations, but such simulations require detailed data of initial parameters. Participants: 2848 patients from 49 hospitals were enrolled. Enrollment varied by hospital, ranging from 4 to 100 patients, the maximum enrollment allowed per site. Design: PETAL-LOTUS FRUIT was a multicenter, prospective, observational cohort study of patients with acute respiratory failure on mechanical ventilation in the PETAL Network hospitals. For all patients, baseline demographic data, the hospital location, indication for intubation (hypoxemic or hypercapnic respiratory failure or both, altered level of consciousness, or surgery), type of intensive care unit (ICU), and Sequential Organ Failure Assessment score in the first 24 hours after intubation were collected. Baseline ventilator data immediately after intubation, arterial blood gas results and oxygen saturation as measured by pulse oximetry, and presence of ARDS was also collected for all patients. ARDS was defined as a ratio of arterial oxygen tension to fraction of inspired oxygen (FiO2) less than or equal to 300 with a chest radiograph within 24 hours of the qualifying ratio of arterial oxygen tension to FiO2 that had bilateral infiltrates unexplained by mass, collapse, or effusion. For the first 50 patients enrolled at each hospital, daily data on ventilator mode, Vt, and presence of ARDS for the first 3 days after intubation was collected. Vt indexed to PBW was calculated from the set Vt for patients on ventilator mode with volume settings. For patients on pressure ventilation modes, Vt was calculated from the ratio of minute ventilation (in ml/min) to the respiratory rate. Enrolled patients were followed until hospital discharge or 28 days for clinical outcomes including mortality, ventilator-free days, and length of stay. To determine the possible improvement in mortality that could be observed with a reduction in Vt from current usual care in the PETAL-LOTUS FRUIT cohort to 6 ml/kg PBW, mortality was estimated as a function of initial Vt. Five models based on data from three distinct patient populations were used. 500 simulations of a stepped-wedge, cluster-randomized clinical trial using the model with greatest predicted benefit for lowering the Vt to 6 ml/kg PBW in PETAL-LOTUS FRUIT sites were performed. Conclusions: Use of initial tidal volumes less than 8 ml/kg predicted body weight was common at hospitals participating in the PETAL Network. After considering the size and budgetary requirement for a cluster-randomized trial of LTVV versus usual care in acute respiratory failure, the PETAL Network deemed the proposed trial infeasible (PMID: 30407869).

  Study phs003791

• H3Africa - Genomic and Environmental Risk Factors for Cardiometabolic Disease in Africans

  The long-term vision of the AWI-Gen Collaborative Centre (CC) is to build sustainable capacity in Africa for research that leads to an understanding of the interplay between genetic, epigenetic and environmental risk factors for obesity and related cardiometabolic diseases (CMD) in sub-Saharan Africa. The CC will be consolidated under the auspices of the University of the Witwatersrand (Wits) and the International Network for the Demographic Evaluation of Populations and Their Health in Developing Countries (INDEPTH). It will capitalize on the unique strengths of existing longitudinal cohorts, including the urban Soweto and rural Agincourt studies in South Africa (Wits based), and the well established INDEPTH demographic health and surveillance centers in Kenya, Ghana, Burkina Faso and South Africa. The centers offer established infrastructure, trained fieldworkers, long-standing community engagement, and detailed longitudinal phenotypic data, focusing on obesity and cardiometabolic health. Key strengths are harmonized phenotyping across sites, building on strong existing cohorts, and representation of the geographic and social variability of African populations. We aim to: 1. Build sustainable infrastructure (biobanks and laboratories) and capabilities (well characterized population cohorts, genotyping and bioinformatics) for genomic research on the African continent; 2. Understand the genomic architecture of sub-Saharan populations from west, east and south Africa to guide genomic studies (genome sequencing and high throughput SNP and CNV arrays using unrelated individuals and family trios to improve the accuracy of haplotype analyses) and; 3. Investigate the independent and synergistic genomic contributions to body fat distribution (BMI, hip/waist circumference, subcutaneous and visceral fat) in these populations considering the relevant environmental and social contexts (rural/urban communities, quickly transitioning obesity prevalence, differential HIV, TB, and malaria infection histories). We will investigate the effect of obesity and fat distribution on the risk for CMD in the longitudinal cohorts.

  Study EGAS00001002482

• NIH RECOVER: A Multi-Site Pathology Study of Post-Acute Sequelae of SARS-CoV-2 Infection

  The RECOVER tissue pathology study is a cross-sectional study designed to define and characterize the epidemiology, natural history, clinical spectrum, and underlying mechanisms of post-acute effects of SARS-CoV-2 infection in a diverse population representative of the general COVID-19 population in the US. The autopsy study will characterize the pathology of PASC in decedents who die more than 60 days after initial onset or after hospital discharge, whether in-hospital or out-of-hospital at time of death, and who meet the working definition of PASC as defined by the recent World Health Organization publication given in Section 5.4. The autopsy study will also explore the pathology of acute SARS-CoV-2 infection in a smaller subset of decedents who died between15-60 days from symptom onset. This protocol defines the common set of clinical data elements, autopsy procedures for tissue collection, core measures, pathology protocols, shared pathology tissues, data elements, and methodology. Each investigator site is expected to perform autopsies on the decedents to address the pathophysiology of the potential long-term effects of SARS-CoV-2 infection on human health. The Consortium analysis plan aims to address research questions by incorporating: 1) tissue obtained from autopsies performed at each Phase II participant's site; and 2) tissue available from other pathology investigators/autopsy sites within the Consortium.

  Study phs003768

• Mid-pass Whole-genome Sequencing in a Malagasy Cohort Uncovers Body Composition Associations

  The majority of human genomic research studies have been conducted in European-ancestry cohorts, reducing the likelihood of detecting potentially novel and globally impactful findings. Here, we present mid-pass whole-genome sequencing data and a genome-wide association study in a cohort of 264 self-reported Malagasy individuals from three locations on the island of Madagascar. We describe genetic variation in this Malagasy cohort, providing insight into the shared and unique patterns of genetic variation across the island. We observe phenotypic variation by location, and find high rates of hypertension particularly in the Southern Highlands sampling site as well as elevated self-reported malaria prevalence in the West Coast site relative to other sites. After filtering to a subset of 214 minimally-related individuals, we find a number of genetic associations with body composition traits, including many variants that are only observed in African populations or populations with admixed African ancestry from the 1000 Genomes Project. This study highlights the importance of including diverse populations in genomic research for the potential to gain novel insights, even with small cohort sizes. This project was conducted in partnership and consultation with local stakeholders in Madagascar and serves as an example of genomic research that prioritizes community engagement and that has potential impacts on our understanding of human health and disease.

  Study EGAS50000000496

• Landscape of somatic mutations and clonal evolution in mantle cell lymphoma

  Mantle cell lymphoma (MCL) is an aggressive tumor, but a subset of patients may follow an indolent clinical course. To understand the mechanisms underlying this biological heterogeneity, we performed whole-genome and/or whole-exome sequencing on 29 MCL cases and their respective matched normal DNA, as well as 6 MCL cell lines. Recurrently mutated genes were investigated by targeted sequencing in an independent cohort of 172 MCL patients. We identified 25 significantly mutated genes, including known drivers such as ataxia-telangectasia mutated (ATM), cyclin D1 (CCND1), and the tumor suppressor TP53; mutated genes encoding the anti-apoptotic protein BIRC3 and Toll-like receptor 2 (TLR2); and the chromatin modifiers WHSC1, MLL2, and MEF2B. We also found NOTCH2 mutations as an alternative phenomenon to NOTCH1 mutations in aggressive tumors with a dismal prognosis. Analysis of two simultaneous or subsequent MCL samples by whole-genome/whole-exome (n = 8) or targeted (n = 19) sequencing revealed subclonal heterogeneity at diagnosis in samples from different topographic sites and modulation of the initial mutational profile at the progression of the disease. Some mutations were predominantly clonal or subclonal, indicating an early or late event in tumor evolution, respectively. Our study identifies molecular mechanisms contributing to MCL pathogenesis and offers potential targets for therapeutic intervention.

  Study EGAS00001000510

• PyEGA3 download client

  PyEGA3 Checks prior to download - Is the dataset available for download? Most datasets are available using the PyEGA3 Download client, except for specific legacy datasets. For these ones, refer to Live Outbox distribution, an alternative way to download these datasets.If the dataset you've been granted access to begins with the ID EGAD5XXXXXXX, please refer to the Live Outbox distribution. If the dataset you have been granted access to contains encrypted data (filename ending in .gpg), contact EGA Helpdesk for detailed information on how to download these files.General Information The PyEGA3 download client is available at its GitHub repository. In its README you will find a step by step guide on how to use it to download files you have been granted access to. PyEGA3 implements the GA4GH-compliant HTSGET protocol supporting requests over genomic ranges. This enables the download of specific regions of interest rather than the entire file. HTSGET is not possible for all the files held by EGA: if the dataset does not contain index files (e.g. filename ending in *.crai), then genomic range requests cannot be performed. The maximum number of connections allowed is 30. If more than 30 connections are used, the download client will encounter 500 errors. The recommended number of connections for maximum output is one. Check out our video tutorial! Frequently Asked Questions General questions How do I download the datasets to which I have been granted access? After setting up your EGA download account, you can proceed to download using the EGA download client – PyEGA3. The pyEGA3 download client is a python-based tool for viewing and downloading files from authorised EGA datasets. This download client is continuously being developed for more user-friendly download experiences. Can I download the dataset’s metadata via the download client? No, the download client cannot be used to download metadata. Registered EGA users can download metadata of an authorised dataset by logging into the EGA webpage and navigating to the dataset of choice. Approximately two thirds down the page you will find the option to download the metadata as a zip file. How do I download large datasets as quickly as possible? The main EGA download client is pyEGA3 download client, a python-based tool for viewing and downloading files from authorised EGA datasets.We could exceptionally consider the option of an Aspera download for users experiencing very slow download rates or facing particular issues.Contact the EGA Helpdesk for further information. Pre-requirement and Installation What are the major requirements for the PyEGA3 download client installation and usage? The PyEGA3 client is compatible with any OS with Python 3.6+ installed. The client requires a connection to the internet, sufficient space on the destination drive, and the EGA download account credentials. Where can I find the PyEGA3 download client installation and download instructions? We strongly recommend checking our video tutorial demonstrating the usage of PyEGA3 from installation to file download. More detailed information is available at PyEGA3 GitHub. What ports are required for the PyEGA3 download client to function? PyEGA3 makes HTTPS calls to the EGA Data API (https://ega.ebi.ac.uk:8443). This port 8443 must be reachable from the location where PyEGA3 is executed to avoid timeouts. PyEGA3 download client How to update the PyEGA3 download client to be on the latest version? Updating the client to the latest version can be achieved by running the following command: pip3 install pyega3 --upgrade I do not have an active EGA account. Can I test the download with the PyEGA3 download client? An EGA download test account (ega-test-data@ebi.ac.uk) has been created for troubleshooting and training purposes. The test account does not require an EGA username and password because it contains publicly accessible files from the 1000 Genomes Project. More information about the use of this account and log in details are available at pyEGA3. I lost my connection while the download was in progress. Does this mean that I have to download the file again from the start? The PyEGA3 download client supports automatic resumption of downloads. To enable quicker download speeds, the API breaks files into up to four segments and downloads them in parallel. With the resume feature, downloads will automatically resume if you encounter any errors or if the connection is interrupted. How can I improve the overall download speed of the PyEGA3 download client? Download speeds can be optimised using the --connections parameter which will parallelise download at the file level. If the --connections parameter is provided, all files >100Mb will be downloaded using the specified number of parallel connections. It is important to note that files are still downloaded sequentially, so using multiple connections does not mean downloading multiple files in parallel. The maximum number of connections allowed is 30. If more than 30 connections are used, the download client will encounter 500 errors. The recommended number of connections for maximum output is one. Why is my file taking a long time to be saved? Please note that when a file is being saved, it goes through two processes. First, the downloaded file "chunks" are pieced back together to reconstruct the original file. Secondly, PyEGA3 calculates the checksum of the file to confirm that the file was downloaded successfully. Larger files will take more time to reconstruct and validate the checksum. Why is the HTSGET protocol not working with my dataset of interest? PyEGA3 implements the GA4GH-compliant htsget protocol for supporting requests over genomic ranges. This exciting new feature means that for data files with accompanying index files (e.g. .crai for CRAM files) users can download specific regions of interest rather than the entire file, saving both time and storage space. Please note that in order for the genomic range requests to work for a BAM, CRAM or VCF file there must be an associated BAI, CRAI or TBI file, respectively. If the dataset does not contain these index files then genomic range requests cannot be performed. After download Do I need to decrypt data files downloaded through the pyEGA3 download client? Files are transferred over secure HTTPS connections and received unencrypted, thus there is no need for decryption after data download. What is the purpose of an MD5 file? After the download completes, file integrity is verified using checksums. The PyEGA3 download client automatically verifies each file’s unencrypted md5 after download to ensure that the file was downloaded correctly from the EGA. Errors Why do I get a “400 Client Error” while trying to access the download client? Ensure that your credentials are formatted correctly. Please contact the EGA Helpdesk if you are unsure about your account’s username (i.e. your email address). Why do I get a “500 Server Error”? It is important to note that files are still downloaded sequentially, so using multiple connections does not mean downloading multiple files in parallel. The maximum number of connections allowed is 30. If more than 30 connections are used, the download client will encounter 500 errors. The recommended number of connections for maximum output is one. Otherwise, 500 server errors are internal server errors from EGA’s end. Retry after some time and, if the 500 error persists: check our homepage or Twitter for any outage information or report it to EGA Helpdesk. Why do I get a “slice error”? This type of error occurs when one slice download was prematurely interrupted. Please re-start the same download. The download client will pick up any partial download and download any missing slices. Why do I get the error “Dataset' EGADXXXXXXXXXXX' is not in the list of your authorised datasets”? Please note that the data access was given to the email (username) provided to the Data Access Committee (DAC) in your official request. Therefore, you shall check that the account that you are using is the same one that you sent to the DAC. Why do I get “ERROR:root:Failed to obtain IP address”? This might mean that the connection ports are blocked. Check that the port 8443 is reachable.In case the port is reachable and the error persists, please try to modify the file pyega3.py on line 44 in the python module installation: Replace endpoint = 'https://ipinfo.io/json' with endpoint = 'https://api.myip.com' Why do I get the error “Invalid username, password or secret key - please check and retry”? Make sure that you are using the correct credentials (username and password) and there is no typo. Contact EGA Helpdesk if the problem persists.

  Documentation access/download/files/pyega3

• Cancer Moonshot Biobank

  The National Cancer Institute initiated the Cancer Moonshot Biobank to accelerate research through the collection and distribution of biospecimens for key research efforts. The Biobank will engage with over one thousand cancer patients, being treated with standard-of-care therapies, for longitudinal biospecimen and data collection. Cancer patients will be enrolled into the study from a diverse participant population engaged at medical institutions throughout the U.S. The biospecimens will be distributed to qualified scientists to accelerate research progress. The Biobank program, working closely with Leidos Biomedical, Inc. (LBR), will partner with community hospitals and other medical institutions, designated as Biospecimen Source Sites (BSS), to engage and consent eligible participants and collect biospecimens and associated clinical data; work with a central Biospecimen Core Resource (BCR) to support biospecimen collection, processing and storage activities and perform pathology quality control; work with LBR's Molecular Characterization (MoCha) lab to perform clinical tumor molecular characterization assays and return results to patients and their physicians; and make the biospecimens and associated data available to researchers to accelerate cancer research progress. Return of clinical results, a dedicated Patient and Provider Engagement (PPE) website, electronic informed consent, local participant engagement projects, and an embedded ethical, legal and social issues sub-study will together support patient and provider engagement in the program. Cancer Moonshot Biobank imaging data is being made available in The Cancer Imaging Archive (TCIA) on a release schedule that is coordinated with the program releases of data to dbGaP. The imaging data can be found at the following link: Cancer Moonshot Biobank Imaging

  Study phs002192

• Colon Cancer Family Registry (Colon CFR)

  The Colon Cancer Family Registry Cohort (CCFRC www.coloncfr.org) is a cohort of families recruited through six study sites located in the USA, Canada, Australia, and New Zealand. The CCFRC was formed as a resource to support studies on the etiology, prevention, and clinical management of colorectal cancer. Recruitment protocols fall broadly into two main categories: population-based and clinic-based ascertainment. Between 1998 and 2013, the CCFR recruited and interviewed probands who were either recently diagnosed with colorectal cancer that was reported to state or regional population cancer registries in the United States (Washington, California, Arizona, Minnesota, Colorado, New Hampshire, North Carolina, and Hawaii), Australia (Victoria), and Canada (Ontario) or were from multiple-case families referred to family-cancer clinics in the United States (Mayo Clinic in Rochester, Minnesota, and Cleveland Clinic in Cleveland, Ohio), Australia (Melbourne, Adelaide, Perth, Brisbane, and Sydney), New Zealand (Auckland), and Canada. Cases with known familial adenomatous polyposis were excluded. Once recruited, probands were asked for permission to contact their relatives for recruitment. Collectively, we have enrolled 42,49874 participants in 15,048 families who participated in standardized protocols used to collect information regarding family cancer history and colorectal cancer risk factors and biospecimens. All participants of population-based case families (excluding control-families) and clinic-based families are asked to provide updates on their personal and family history of cancer as well as their history of surgery, cancer screening, and some risk factors every 4-5 years either by telephone interview or by self-completed questionnaire via mail or online (PMID: 17982118).

  Study phs002733

• A unidirectional histone code in bidirectional promoters across cell types

  Recent studies indicate that thousands of genes are expressed from bidirectional promoters (BDPs). Gene regulation at BDPs is poorly understood, in particular how the cell is able to regulate them differently. Here we investigate the effect of histone Modifications in BDP regulation. In this study, we model the gene activity using different gene expression assays, such as RNA-Seq, GRO-cap, and CAGE around the BDP transcription start sites (TSSs) using different histone modifications in various cell types. We develop a new statistical approach that links histone modifications to gene expression at BDPs. It improves over previous methods, because it is able to capture spatial dependencies of histone modifications along a promoter and leads to more interpretable results. We predict a general histone code that is independent of transcript orientation, cell type, and promoter configuration. The histone code at BDPs reveals that promoters are regulated unidirectionally, such that the majority of histone marks associated with gene expression occur downstream of the gene's TSS. By contrasting associations of histone marks with steady-state levels of capped RNAs in CAGE and nascent capped RNAs in GRO-cap, we show which histone marks have a preference for initiating polymerases and actively elongating polymerases. Using single-cell data we show that the bidirectional histone signal of activating marks is often due averaging of a heterogeneous cell population. Our results have implications for other experiments where the relationship between histone modification and gene initiation or gene elongation is investigated on a genome-wide scale.

  Study EGAS00001001656

• Cryptococcosis in Previously Healthy Adults

  Cryptococcus is a fungus that causes infections most commonly in immunocompromised patients, such as those with AIDS and solid organ transplant recipients and is currently responsible for an estimated 15% of all AIDS-related deaths globally. However, in developed countries, approximately one-third of cases fall outside these groups such that cryptococcal meningoencephalitis (CM) has become the most common cause of non-viral meningitis in the U.S. Within the U.S., approximately 15-20% have no readily identifiable immune defect and cryptococcal infection in these hosts has a mortality rate of 30-50% despite optimal antifungal therapy. NIH Clinical Study Protocol 93-I-0106 (NCT00001352). The objectives of this protocol can be broadly categorized as: 1) Characterize the immunologic and genetic mechanisms predisposing to disease acquisition; 2) Understand the post-infectious inflammatory response and distinguish its consequences from those directly due to fungal growth; and 3) Management of post-infectious neuro-inflammatory syndromes associated with cryptococcal meningitis (CM). This protocol recruits patients who have microbiological evidence of cryptococcal neurologic or non-CNS disease (typically pulmonary or bone). Cerebrospinal fluid (CSF) and blood samples collected during clinical care are used to measure serum and CNS cellular and soluble cytokines as well as to perform in-situ immunohistochemistry. CSF and blood samples are also collected to measure transcriptional (gene expression), proteomic (protein), and lipidomic (lipids) changes that occur throughout disease and treatment. Observational data detailing audiological, ophthalmological and neurocognitive deficits in these patients is also recorded. We have recently described a post-infectious inflammatory syndrome (PIIRS) associated with cryptococcal meningoencephalitis (CM) which can be best described as a neuro-inflammatory state during which CM patients present with altered mental status (Montreal Cognitive Assessment Score As part of the protocol, we treat patients for either microbiological failure or neuroinflammatory sequelae by conventional therapies utilizing FDA-approved pharmaceuticals at FDA-approved doses. To understand and identify the predominant biological pathways responsible for PIIRS neuroinflammation, we examined patient CSF at baseline (at time of PIIRS diagnosis) and post-treatment with different FDA-approved pharmaceuticals at FDA-approved doses compared to CSF from non-PIIRS donors. Upstream pathway analysis of differentially expressed genes in the CSF of PIIRS patients revealed a prominent role for the JAK/STAT pathway in the pathogenesis of PIIRS and support the use of the JAK inhibitor, ruxolinib, as a pathway-instructed therapy to treat PIIRS patients. Data available through dbGaP: single cell RNA sequencing (scRNA-seq) data from CSF cells of a patient with PIIRS at the time of diagnosis and following treatment with steroids (1g solumedrol/day) and NanoString transcriptional data from CSF cells of patients with PIIRS at the time of diagnosis compared to CSF cells from non-PIIRS donors.

  Study phs003871

• eMERGE Network Genome-Wide Association Study of Red Cell Indices, White Blood Count (WBC) Differential, Diabetic Retinopathy, Height, Serum Lipid Levels, Specifically Total Cholesterol, HDL (High Density Lipoprotein), LDL (Low Density Lipoprotein), and Triglycerides, and Autoimmune Hypothyroidism.

  The electronic Medical Records and Genomics (eMERGE) Network is a consortium of five participating sites (Group Health Seattle, Marshfield Clinic, Mayo Clinic, Northwestern University, and Vanderbilt University) funded by the NHGRI to investigate the use of electronic medical record systems for genomic research. The goal of eMERGE is to conduct genome-wide association studies in approximately 19,000 individuals using EMR-derived phenotypes and DNA from linked Biorepositories. Using electronic phenotyping methods, the consortium used DNA samples from all participating sites to explore the genetic determinants of red cell indices, white blood count (WBC) differential, diabetic retinopathy, height, serum lipid levels, specifically total cholesterol, HDL (high density lipoprotein), LDL (low density lipoprotein), and triglycerides, and autoimmune hypothyroidism as well as using the phenome-wide association study (PheWAS) paradigm to replicate and discover relationships between targeted genotypes with multiple phenotypes. eMERGE led studies for which original genotyping was performed and are included in this merged set: Genome-Wide Association Study on Cataract and HDL in the Personalized Medicine Research Project Cohort, phs000170 Development and Use of Network Infrastructure for High-Throughput GWA Studies, phs000234 Vanderbilt Genome-Electronic Records (VGER) Project: QRS Duration, phs000188 Northwestern NUgene Project: Type 2 Diabetes, phs000237 A Genome-Wide Association Study of Peripheral Arterial Disease, phs000203 Sites and participants include: Vanderbilt University: BioVU, Vanderbilt's DNA databank, is an enabling resource for exploration of the relationships among genetic variation, disease susceptibility, and variable drug responses, and represents a key first step in moving the emerging sciences of genomics and pharmacogenomics from research tools to clinical practice. BioVU acquires DNA from discarded blood samples collected from routine patient care. The biobank is linked to de-identified clinical data extracted from Vanderbilt's EMR, which forms the basis for phenotype definitions used in genotype-phenotype correlations. Marshfield Clinic: The Marshfield Clinic Personalized Medicine Research Project is a population-based biobank in central Wisconsin with more than 20,000 adult subjects who provided written, informed consent to access their medical records and provided a blood sample from which DNA was extracted and plasma and serum stored. In addition to an average of 30 years of medical history data, a questionnaire about environmental exposures, including a detailed food frequency questionnaire, is available to facilitate gene/environment studies. Northwestern University: The NUgene Project is a repository with longitudinal medical information from participating patients at affiliated hospitals and outpatient clinics from the Northwestern University Medical Center. Participants' DNA samples are coupled with data from a self-reported questionnaire and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 2 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators. Group Health(GH)/University of Washington (UW): Aging and Dementia eMERGE study biorepository leverages rich population-based longitudinal data from both electronic medical records and in-depth research data to explore genome wide associations. Participants include Seattle-area members of GH (a large integrated health care system in Washington State) consented and enrolled in 1) the UW Alzheimer's Disease Patient Registry (ADPR) and 2) the Adult Changes in Thought (ACT) study. The ADPR (PI: Eric B. Larson; NIH/NIA U01 AG 006781) is a population-based registry of incident dementia cases designed to identify all new Alzheimer's Disease cases within GH from 1987 to 1996. Medical history, physical, laboratory testing, and neuropsychological testing were performed on all consenting potential cases for determination of dementia status by a consensus conference. The study base of the ADPR population was stable with an attrition rate of less than 1%/year. The ACT study (PI: Eric B. Larson; NIH/NIA U01 AG 006781) is an ongoing community-based cohort study of aging and dementia. The original cohort of 2,581 randomly selected dementia-free members age 65 and older was enrolled in 1994-1996 and expanded by 811 in 2000-2002. Continuous enrollment to maintain a cohort of 2,000 dementia free persons began in 2005. Participants receive biennial assessment including cognitive status determination. The ACT sub-sample is stable; for the original cohort, median enrollment in GH was 19 years prior to joining the ACT study, and 85% of the cohort has ≥10 years of GH enrollment. DNA for the ADPR participants were obtained through a companion study, Genetic Differences in Cases and Controls (PI: Walter Kukull; NIH/NIA R01 AG007584). DNA obtained through both studies were extracted from blood using Gentra Systems Puregene methods. DNA concentration is determined by UV optical density. All samples are checked for quality by 260/280 ratio. For long-term storage, samples are aliquoted and stored at -70°C. Mayo Clinic: The Mayo biobank is a disease-specific biobank for vascular diseases including peripheral arterial disease (PAD). PAD patients were identified from individuals referred to the non-invasive vascular laboratory for lower extremity arterial evaluation. Since 1997, laboratory findings have been recorded into an electronic database employing an in-house software package for data archiving and retrieval; this data becomes part of the Mayo EMR. Patients referred to the center with suspected PAD undergo a comprehensive non-invasive evaluation including the ankle-brachial index (ABI) - the ratio of blood pressure measured in the upper arms divided by blood pressure measured at the ankles. Controls subjects are identified from patients referred to the Cardiovascular Health Clinic for stress ECG. The prevalence of PAD in patients with normal exercise capacity who do not have inducible ischemia on the stress ECG, was <1%. Data regarding risk factors for atherosclerosis such as diabetes, dyslipidemia, hypertension, and smoking are ascertained from the EMR.

  Study phs000360

• One-step generation of tumor models by base editor multiplexing in adult stem cell-derived organoids

  Recent optimization of CRISPR/Cas9-mediated genome engineering has resulted in the development of base editors that can efficiently mediate C>T and A>G transitions. Combining these genome engineering tools with human adult stem cell (ASC)-derived organoid technology holds promise for disease modeling. Here, we demonstrate the application of base editors for the generation of complex tumor models in human ASC-derived hepatocyte, endometrial and intestinal organoids. First, using conventional and evolved Cas9-variants, we show efficacy of both cytosine and adenine base editors and use them to model four hot-spot point mutations in CTNNB1 in hepatocyte organoids. Next, we apply C>T base editors in endometrial organoids to insert nonsense mutations in PTEN and demonstrate tumorigenicity even in the heterozygous state. Furthermore, we use cytosine base editors for simultaneous oncogene activation (PIK3CA) and tumor-suppressor inactivation (APC and TP53). To increase the flexibility of base editor multiplexing, we then combine SpCas9 and SaCas9 base editors for simultaneous C>T and A>G editing at individual target sites. Finally, we show the power of base editor multiplexing by modeling colorectal tumorigenesis in a single step by simultaneously transfecting sgRNA’s targeting four cancer genes. Seven clonal organoid lines and one bulk wild-type control sample were paired-end whole-genome sequenced using the Illumina Novaseq 6000 system. We sequenced four clonal intestinal organoid lines harbouring engineered TP53 and FBXW7 mutations as well as three lines targeted for oncogenic APC/TP53/PIK3CA/SMAD4 mutations. This WGS showed, as previously reported, a genome-wide increase in C>T mutations due to C>T base editor off-target activity, which is not enriched in predicted off-target regions based on the sgRNA sequences. Furthermore, we confirmed the absence of editing-induced driver mutations and lack of off-target mutational hotspots created by the genomic engineering.

  Study EGAS00001006886

• 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

• University of Illinois at Chicago (UIC) Autism Centers of Excellence (ACE) Exome Sequencing Analysis

  Autism spectrum disorder (ASD) is highly heritable with recent sibling recurrence risk estimates of 19% overall and 26% in males. The heritable phenotype of hyperserotonemia, or elevated levels of platelet serotonin (5HT), in ~35% of people with ASD is a well-established biomarker. The efficacy of drugs like risperidone and potent serotonin transporter inhibitors at treating behaviors related to Insistence on Sameness, along with evidence of the contribution of hyperserotonemia to autism susceptibility collectively support the hypothesis that dysfunction in the 5HT system is a significant etiological target for investigation of the genetic component to autism. ASD genetic architecture is complex; common variants of large effect do not contribute substantially to overall ASD risk, but there are clearly common variants with small effects and rare genetic/genomic variation of larger effect among ASD genetic risk factors. The NIH ARRA Autism Sequencing Consortium, including Dr. Sutcliffe and Dr. Cook among others, has initiated exome sequencing studies to identify more of the rare variants contributing to ASD. Data from our group and others reveal numerous rare de novo and inherited sequence mutations, and the number of de novo and other functional mutations that are found to affect molecules encoding 5HT signaling and its regulation further reinforces our hypothesis that regulation of serotonin levels is important in autism genetic susceptibility. Integrin receptor signaling pathways were prominently featured among identified de novo mutations, thus defining a set of interrelated gene networks that control 5HT signaling. We propose to extend our findings to date by conducting exome sequencing on ACE subjects, for whom we also have 5HT biochemical data, to identify rare variants (including CNVs) in 5HT-related gene networks. In total we propose to have exome sequencing completed on 523 samples. The purpose of the proposed research is two-fold: 1) we will conduct more extensive investigations to determine the support for the hypothesis that genetic variation at genes regulating platelet serotonin levels affect susceptibility to ASD and 2) we will combine the exome sequence data from these studies with sequence data for autism being accumulated in a variety of other research projects to further the goal of identifying and characterizing the genetic component to ASD.

  Study phs000712

• ICGC Prostate Cancer Whole Genome Sequencing

  To characterize the subclonal genomic architecture of androgen-deprived metastatic prostate cancer, we performed whole-genome sequencing (WGS) of 51 tumours from 10 patients to an average sequencing depth of 55x, including multiple metastases from different anatomic sites in each patient and, in five cases, the prostate tumour. Noncancerous DNA from blood or other tissue is used as reference comparison for each patient. The patients are part of PELICAN (Project to ELIminate Lethal Cancer) rapid autopsy study led by G. Steven Bova at Johns Hopkins University (USA) and Tampere University (Finland). As of September 2020, some of the studies using these data include: Gundem et al, Nature 2015 (PMID: 25830880). Additional EGAD00001000891 sample metadata is contained in Supplementary Information in this report.Tubio et al, Science 2014 (PMID: 25082706) Behjati et al, Nature Comm 2015 (PMID: 27615322) Wedge et al, Nature Genetics 2018 (PMID: 29662167)Pan-Cancer Analysis of Whole Genomes, Nature 2020 (PMID: 32025007)Rodriguez-Martin et al, Nature Genetics 2020 (PMID: 32024998)Woodcock et al, Nature Comm 2020 (In Press)

  Dataset EGAD00001000891

• BLUEPRINT: Epigenetic programming during monocyte to macrophage differentiation and trained innate immunity

  Monocyte differentiation into macrophages represents a cornerstone process for host defense. Concomitantly, immunological imprinting of either tolerance or trained immunity determines the functional fate of macrophages and susceptibility to secondary infections. Transcriptomes (RNA-Seq) and epigenomes (ChIP-Seq H3K4me1,H3K4me3,H3K27ac) in four primary cell types: monocytes, in vitro differentiated naive, tolerized and trained macrophages were characterized. Inflammatory and metabolic pathways were modulated in macrophages, including decreased inflammasome activation, and pathways functionally implicated in trained immunity were identified. Strikingly, B-glucan training elicits an exclusive epigenetic signature, revealing a complex network of enhancers and promoters. Analysis of transcription factor motifs in DNase I hypersensitive sites at cell-type specific epigenetic loci unveiled differentiation and treatment specific repertoires. Altogether, this study provides a resource to understand the epigenetic changes that underlie innate immunity in humans.

  Dataset EGAD00001001011

• Dental Caries: Whole Genome Association and Gene x Environment Studies

  Dental caries (also known as tooth decay) remains the most common chronic disease of childhood, five times more common than asthma and seven times more common than environmental allergies, with more than 40% of children exhibiting caries when they enter kindergarten. In 2005, it was estimated that dental health care costs were approximately $84 billion, of which 60% or about $50 billion were related to treatment of dental caries. Although overall caries prevalence has declined over the last 40 years, dental caries in the primary dentition and mean caries rates in children ages 2-11 has increased markedly over the past 12 years. Childhood caries is a serious public health issue because of associated health problems and because disparities in oral health have led to substantially higher average disease prevalence among children in poverty and in under-served racial and ethnic groups. These issues are of such concern that in 2005, the American Academy of Pediatrics made children's oral health one of their top areas of focus, as it is for the majority of the NIDCR "Disparities Centers". The etiology of dental caries has been studied for many years. Multiple factors contribute to a person's risk for caries, including: 1) environmental factors such as diet, oral hygiene, fluoride exposure and the level of colonization of cariogenic bacteria and 2) host factors such as salivary flow, salivary buffering capacity, position of teeth relative to each other, surface characteristics of tooth enamel and depth of occlusal fissures on posterior teeth. In spite of all that is known about this disease, there are still individuals who appear to be more susceptible to caries and those who are extremely resistant, regardless of the environmental risk factors to which they are exposed, implying that genetic factors also play an important role in caries etiology. This conclusion is supported by studies in both humans and animals, with the most compelling evidence coming from studies of twins reared apart in which investigators found significant resemblance within monozygotic (MZ) but not dizygotic (DZ) twin pairs for percentage of teeth and surfaces restored or carious and estimated the genetic contribution to caries as 40%. Other recent studies of twins reared together estimated the heritability for caries, adjusted for age and gender, as ranging from 45-64%. Despite the strong evidence of a genetic component to risk for dental caries, there have been only a few studies of candidate genes in caries, and no published genome-wide scans. A comprehensive genome wide search is the only approach that will allow us to identify those genetic regions likely to harbor genes increasing the risk for dental caries, and eventually to identify the etiologic genes and to explore the interaction of those genes with microbiological, dietary, fluoride, and behavioral factors that are known to be associated with caries risk and progression. Therefore, the goal of this study is to perform genome-wide association (GWA) studies of dental caries with a large panel of SNP's (610,000) in families and individuals ascertained through multiple US sites (University of Pittsburgh and University of Iowa). The v2 release of this study includes 96 additional individuals who were genotyped with the CCDG: Dental Caries and CL/P in Guatemala project (dbGaP accession number phs000440) to augment the data initially presented here. These subjects were genotyped on the Illumina 610 platform to make their data comparable. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org), which was developed through the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to dental caries through large-scale genome-wide association studies of well-characterized families and individuals at multiple sites in the U.S. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). The study was supported by the National Institute of Dental and Craniofacial Research (NIDCR, U01-DE018903). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington. Samples of some participants in this study were selected for further genomic analysis. These results will be available in the dbGaP CIDR study: Center for Oral Health Research in Appalachia (COHRA) Genomic Studies of Oral Health and Disease (phs001591).

  Study phs000095

• Single cell and whole tissue transcriptomes investigating Barrett's oesophagus

  Data consists of 4,640 RNA-sequencing sample libraries. These libraries were sequenced from four sites of the upper gastro-intestinal tract (Barrett’s oesophagus, proximal normal oesophagus, proximal normal stomach, and duodenum) in two experiments. 4,587 libraries were produced in the first experiment in which whole transcriptomes were isolated single cells dissociated from endoscopic biopsy tissue obtained from the four previously mentioned tissues. The other 53 libraries were produced in the second experiment in which whole transcriptomes were isolated from whole tissue from endoscopic biopsies of the four previously mentioned tissues. The data found here are stored in the raw fastq file format from paired end sequencing.

  Dataset EGAD00001004344

• Influence of the Microbiome on Epigenetic Mechanisms in IBD

  Live CD4 T cells were sorted from inflamed and non-inflamed tissue samples of IBD patients or from healthy and IBD blood samples. ATAC-Seq libraries were generated from live CD4 T cells sorted from i) inflamed and non-inflamed tissue samples, ii) healthy and IBD blood samples, or from iii) CD4 T cell subsets polarised from healthy blood samples. After isolating crude nuclei, live CD4+ T cells were treated with Tagment DNA buffer and Tagment DNA Enzyme (Nextera DNA Library Prep Kit, Illumina), and then the DNA was purified by MinElute PCR Purification Kit (Qiagen). Transposed DNA fragments were amplified using specific adapters followed by purification with MinElute PCR Purification Kit (Qiagen). Fragments from 240-360pb were selected in the PippinHT system (Sage Science). The quality of the library and its DNA concentration were assessed by Bioanalyzer instruments (Agilent Technologies) and ultimately submitted for sequencing using Illumina HiSeq 2500 sequencer, V4 chemistry. On the other hand, single cell RNA-Seq libraries were generated exclusively from inflamed and non-inflamed tissue samples of Crohn’s disease patients. Briefly, live CD4 T cells were captured and encapsulated before cDNA amplification using the 10X Genomics Chromium Platform. Samples were prepared as outlined by 10x genomics Single Cell 3’ Reagent Kits v2 user guide. Samples were sequenced on a HiSeq 2500 with the following run parameters: Read 1 – 26 cycles, read 2 – 98 cycles, index 1 – 8 cycles.

  Dataset EGAD00001011066

• Using NGS to Sequence Whole Genomes to Identify Genes Underlying ALS

  Our ALS Consortium - a partnership of clinicians, basic scientists, geneticists, and computational biologists from 48 institutions (4 of which are industry partners) across 5 countries - establishes a framework to apply whole genome sequencing (WGS) and functional genomics to the study of amyotrophic lateral sclerosis (ALS). Because ALS-causing mutations tend to be of moderate impact and are relatively rare in the population (reviewed in Al-Chalabi et al., 2017, PMID: 27982040), identification of new mutations require several thousand samples, which need to be obtained from multiple sites (even the busiest ALS clinics see only 200-400 patients per year). ALS Consortium is using genomics technologies to study the causes and mechanisms underlying neurodegenerative disease, and the contribution of various cell types within the brain and spinal cord. Much of this work is done and continues to be done in collaboration with the members of the NYGC ALS Consortium.

  Study phs003067

• The chromatin accessibility signature of human immune aging stems from CD8+ T cells

  Aging is linked to deficiencies in immune responses and increased systemic inflammation. To unravel the regulatory programsbehind these changes, we applied systems immunology approaches and profiled chromatin accessibility and the transcriptomein PBMCs, purified monocytes, and B and T cells. Analysis of samples from 77 young and elderly donors revealed a novel androbust aging signature in PBMCs, with simultaneous systematic chromatin closing at promoters and enhancers associated withT cell signaling and a potentially stochastic chromatin opening mostly found at quiescent and repressed sites. Combined analysesof chromatin accessibility and the transcriptome uncovered immune molecules activated/inactivated with aging andidentified the silencing of the IL7R gene and the IL-7 signaling pathway genes as potential biomarkers. This signature is borneby memory CD8+ T cells, which exhibited an aging-related loss in binding of NF-κB and STAT factors. Thus, our study providesa unique and comprehensive approach to identifying candidate biomarkers and provides mechanistic insights into aging-associatedimmunodeficiency.

  Study EGAS00001002605

• High-grade B-cell lymphoma, not otherwise specified: an LLMPP study

  Molecular characterization of high-grade B-cell lymphoma, not otherwise specified (HGBCL-NOS), is hindered by its rarity, evolving definition, and poor diagnostic reproducibility. To address this challenge, we analyzed 92 HGBCL-NOS tumors collected across Lymphoma/Leukemia Molecular Profiling Project sites. These tumors were profiled using whole-genome sequencing (WGS) or whole-exome sequencing (WES) to identify somatic mutations, WGS or low-pass WGS to detect copy number alterations, targeted capture sequencing to assess MYC and BCL2 structural variants, and RNA sequencing. The genetic features of HGBCL-NOS were compared to those of diffuse large B-cell lymphoma (DLBCL-NOS) and EBV-negative adult Burkitt lymphoma (BL). DLBCL-NOS tumors underwent targeted capture sequencing using a panel of 125 genes recurrently mutated in aggressive B-cell lymphomas. BL biopsies were drawn from the Burkitt Lymphoma Genome Sequencing Project and had available WGS (dbGaP Study Accession: phs000527.v18.p6).

  Study EGAS50000000932

• Transcriptional mechanisms of resistance to anti-PD-1 therapy

  Purpose: To explore factors associated with response and resistance to anti-PD-1 therapy, we analyzed multiple disease sites at autopsy in a patient with widely metastatic melanoma who had a heterogeneous response.Materials and Methods: Twenty-six melanoma specimens (four pre-mortem, 22 post-mortem) were subjected to whole-exome sequencing. Candidate immunologic markers and gene expression were assessed in ten cutaneous metastases showing response or progression during therapy.Results: The melanoma was driven by biallelic inactivation of NF1. All lesions had highly concordant mutational profiles and copy number alterations, indicating linear clonal evolution. Expression of candidate immunologic markers was similar in responding and progressing lesions. However, progressing cutaneous metastases were associated with over-expression of genes associated with extracellular matrix and neutrophil function.Conclusions: Although mutational and immunologic differences have been proposed as the primary determinants of heterogeneous response/resistance to targeted therapies and immunotherapies, respectively, differential lesional gene expression profiles may also dictate anti-PD-1 outcomes.

  Study EGAS00001002195

• Swarm Learning to identify COVID-19, tuberculosis and leukemia patients based on blood transcriptomes

  Identification of patients with life-threatening diseases including leukemias or infections such as tuberculosis or COVID-19 is an important goal of modern precision medicine. However, there is an increasing divide between what is technically possible and what is allowed because of privacy legislation. We have recently illustrated that classical machine learning can identify leukemia patients based on their blood transcriptomes. To facilitate integration of any omics data from any data owner world-wide without violating privacy laws, we here introduce Swarm Learning (SL), a decentralized machine learning approach uniting edge computing, artificial intelligence (AI), blockchain and privacy protection without the need for a central coordinator thereby going beyond federated learning. To illustrate its feasibility, using more than 12,000 transcriptomes from peripheral blood mononuclear cells and more than 2,000 peripheral blood transcriptomes we demonstrate that SL of omics data distributed across different individual sites leads to disease classifiers that outperform those developed at individual sites. Yet, SL completely protects local privacy regulations by design. We propose this approach to noticeably accelerate the introduction of precision medicine.

  Dataset EGAD00001006231