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• Variant calling for LUNG-NSCLC2 cohort

  The goal of IMMUcan is to understand how the immune system interacts with tumors and how therapeutic interventions influence this interaction. This cohort includes patients with non-small cell lung cancer who had surgical resection. This is a subcohort of the EORTC SPECTAlung study. This dataset contains whole exome sequencing data from tumor samples processed with the Vegan pipeline. In the absence of matching germline samples, variant calling is performed using two panel of normals (one for female and one for male). It includes SNP and CNV calling.

  Dataset EGAD50000002235

• Stanford Center for Urologic Genomics: Genomic Analysis of Benign Prostatic Hyperplasia

  Benign prostatic hyperplasia (BPH) entails growth in the central regions of the prostate gland and is common among older men. BPH obstructs urinary outflow, resulting in voiding symptoms for which current treatments that target prostate physiology are only partially effective. A better understanding of BPH may suggest new treatment strategies that target its pathophysiology. The overall goal of the study is to apply next-generation sequencing-based approaches to investigate BPH, to discover new insight into BPH disease processes and new targets for precision therapy, and to determine whether the hyperplasia reflects underlying clonal expansions of prostatic cells.

  Study phs001698

• Variation in the Glucose Transporter gene SLC2A2 is associated with glycaemic response to metformin

  Metformin is the first-line antidiabetic drug with over 100 million users worldwide, yet its mechanism of action remains unclear1. Here the Metformin Genetics (MetGen) Consortium reports a three-stage genome wide association study (GWAS), consisting of 13,123 participants of different ancestries. The C-allele of rs8192675 in the intron of SLC2A2, which encodes the facilitated glucose transporter GLUT2, was associated with a 0.17% (p=6.6x10-14) greater metformin induced HbA1c reduction in 10,577 participants of European ancestry. rs8192675 is the top cis-eQTL for SLC2A2 in 1,226 human liver samples, suggesting a key role for hepatic GLUT2 in regulation of metformin action. In obese individuals C-allele homozygotes at rs8192675 had a 0.33% (3.6mmol/mol) greater absolute HbA1c reduction than T-allele homozygotes.This is about half the effect seen with the addition of a DPP-4 inhibitor, and equates to a dose difference of 550mg of metformin, suggesting rs8192675 as a potential biomarker for stratified medicine.

  Study EGAS00001001875

• EGA QuickView

  EGA QuickView Secure and Remote Access to EGA Files What is EGA QuickView? EGA QuickView is a FUSE file system that allows secure and remote access to EGA files. It is a hybrid of sshfs and crypt4ghfs, which means it uses ssh to connect to the EGA distribution servers, downloads data in Crypt4GH format, and transparently decrypts those files. It is compatible with Linux and macOS 12. Why use EGA QuickView? EGA QuickView is a highly useful and convenient tool for anyone who needs to access EGA files remotely and securely. The software offers a quick and convenient way to browse through EGA files without the need for complete downloads, thus saving bandwidth and time. Whether you are a medical professional requiring access to sensitive patient data or a research scientist working on a project that involves EGA files, EGA QuickView provides a highly useful solution. The software boasts advanced security features, ensuring that your data is safe and protected at all times. Get started with EGA QuickView To get started with EGA QuickView, visit the EGA QuickView GitHub repository for more information and installation instructions.

  Documentation access/download/visualisation/ega-quickview

• Perceptions, Prevalence, and Patterns of Cannabis Use among Cancer Patients in NCI-Designated Cancer Centers

  This study aimed to better understand the evolving landscape of cannabis use among patients undergoing cancer treatment across diverse geographic regions. It sought to characterize patterns of use, patient perceptions, and contextual influences such as legal status and provider engagement that affect cannabis use. Given the shifting legal environment, this study addresses a critical gap in the literature by providing data on how cancer patients integrate cannabis into their care. The available delivery methods of cannabis have also undergone dramatic changes and now include edibles, oils, tinctures, topicals, and inhaled forms. State-based policy changes are rapidly changing. Yet research on cannabis use by cancer patients across a variety of geographic settings remains limited. The extent of cannabis use, the perceived and real benefits and risks of use, potential interactions with cancer treatment and other medications, and impact on comorbid conditions are uncertain. Clinicians should be aware of the extent of use in order to assess potential drug-drug interactions, side effects, and contraindications; hence, an understanding of how cancer patients and clinicians engage in discussions about cannabis use is essential. Twelve NCI-designated cancer centers were awarded supplemental funding to conduct surveys assessing cannabis use among recently diagnosed cancer patients. Selected sites were in 8 states with varied legal status for medical and recreational cannabis use at the time of the survey. The 12 cancer centers independently received approval from their institutional review boards (IRB) and collected data from September 2021 to August 2023. Eligible participants were cancer patients or survivors who resided in their respective cancer center's catchment area. Cancer centers were responsible for sampling patients within their catchment area with the goal of 1,000 completed surveys. Ten out of 12 cancer centers drew probability samples of patients from patient lists defining their catchment area with some stratifying the sample in various ways including by cancer type, by sex, by race/ethnicity or by a combination of demographic variables.

  Study phs004046

• Whole exome sequencing of germline DNA was performed and subsequent polymorphisms in genes known and putatively involved in the innate immune response to fungi were identified

  Disease can be conceptualized as the result of interactions between infecting microbe and holobiont, the combination of a host and its microbial communities. It is likely that genomic variation in the host, infecting microbe, and commensal microbiota are key determinants of infectious disease clinical outcomes. However, until recently, simultaneous, multiomic investigation of infecting microbe and holobiont components has rarely been explored. Herein, we characterized the infecting microbe, host, micro- and mycobiomes leading up to infection onset in a leukemia patient that developed invasive mucormycosis. We discovered that the patient was infected with a strain of the recently described Mucor velutinosus species which we determined was hypervirulent in a Drosophila challenge model and has a predisposition for skin dissemination. After completing the infecting M. velutinosus genome and genomes from four other Mucor species, comparative pathogenomics was performed and assisted in identifying 66 M. velutinosus-specific putatively secreted proteins, including multiple novel secreted aspartyl proteinases which may contribute to the unique clinical presentation of skin dissemination. Whole exome sequencing of the patient revealed multiple non-synonymous polymorphisms in genes critical to control of fungal proliferation, such as TLR6 and PTX3. Moreover, the patient had a non-synonymous polymorphism in the NOD2 gene and a missense mutation in FUT2, which have been linked to microbial dysbiosis and microbiome diversity maintenance during physiologic stress, respectively. In concert with host genetic polymorphism data, the micro- and mycobiome analyses revealed that the infection developed amid a dysbiotic microbiome with low α-diversity, dominated by staphylococci. Additionally, longitudinal mycobiome data showed that M. velutinosus DNA was detectable in oral samples preceding disease onset. Our genome-level study of the host-infecting microbe-commensal triad extends the concept of personalized genomic medicine to the holobiont-infecting microbe interface thereby offering novel opportunities for using synergistic genetic methods to increase understanding of infectious diseases pathogenesis and clinical outcomes.

  Study EGAS00001001542

• Mayo Clinic - Fecal Microbiota and Adenomas

  Background: Adenomatous polyps are the most common precursor to colorectal cancer (CRC), the second leading cause of cancer death in the United States. We sought to learn more about early events of carcinogenesis by investigating shifts in the gut microbiota of patients with adenomas. Methods: We analyzed 16S rRNA gene sequences from the fecal microbiota of patients with adenomas (n=233) and without (n=547). Results: Multiple taxa were significantly more abundant in patients with adenomas, including Bilophila, Desulfovibrio, pro-inflammatory bacteria in the genus Mogibacterium, and multiple Bacteroidetes species. Patients without adenomas had greater abundances of Veillonella, Firmicutes (Order Clostridia), and Actinobacteria (family Bifidobacteriales). Many of our findings were consistent with previously reported shifts in the gut microbiota of CRC patients. Importantly, the altered adenoma profile is predicted to increase primary and secondary bile acid production, as well as starch, sucrose, lipid, and phenylpropanoid metabolism. Conclusions: These data suggest that diets rich in refined sugar, protein, and lipids may lead to increased bile acid production, creating a colonic environment that promotes the growth of bile-tolerant microbes such as Bilophilia and Desulfovibrio. In turn, these microbes may produce genotoxic or inflammatory metabolites such as H2S and secondary bile acids, catalyzing adenoma development and eventually CRC. Impact: This study suggests a plausible biological mechanism to explain the links between diet, shifts in the microbiota, and CRC. This represents a first step toward resolving the complex interactions that shape the adenoma-carcinoma sequence of CRC and may facilitate personalized therapeutics focused on the microbiota.

  Study phs001204

• Probabilistic cell type assignment of single-cell transcriptomic data reveals spatiotemporal microenvironment dynamics in human cancers

  Single-cell RNA sequencing (scRNA-seq) has transformed biomedical research, enabling decomposition of complex tissues into disaggregated, functionally distinct cell types. For many applications, investigators wish to identify cell types with known marker genes. Typically, such cell type assignments are performed through unsupervised clustering followed by manual annotation based on these marker genes, or via "mapping" procedures to existing data. However, the manual interpretation required in the former case scales poorly to large datasets, which are also often prone to batch effects, while existing data for purified cell types must be available for the latter. Furthermore, unsupervised clustering can be error-prone, leading to under- and over- clustering of the cell types of interest. To overcome these issues we present CellAssign, a probabilistic model that leverages prior knowledge of cell type marker genes to annotate scRNA-seq data into pre-defined and de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while simultaneously controlling for batch and patient effects. We demonstrate the analytical advantages of CellAssign through extensive simulations and exemplify real-world utility to profile the spatial dynamics of high-grade serous ovarian cancer and the temporal dynamics of follicular lymphoma. Our analysis reveals subclonal malignant phenotypes and points towards an evolutionary interplay between immune and cancer cell populations with cancer cells escaping immune recognition.

  Study EGAS00001003452

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Epilepsy: Epi25 Consortium

  Epilepsy genetics research is at an exciting stage where it is now feasible, with the power of a large cohort, to understand the more complex genetic components of epilepsy. The driving principle behind the Epi25 Consortium is collaboration and synergy - it is only possible to achieve this type of research by working together. The Epi25 Consortium was formed by the unification of various consortia, including Epi4K, EPIGEN, EuroEPINOMICS, the Epilepsy Phenome/Genome Project, EpiPGX, SANAD, and EpiCURE, and individual epilepsy investigators. The consortium's sample collection is the best resource in the world for this disease, both in terms of numbers of patients and quality of phenotypic information. As part of the NHGRI Centers for Common Disease Genomics (2016-2020), we aggregated a global sample collection from the various repositories for whole genome genotyping and whole exome sequencing (WES) at the Broad Institute (Cambridge, MA), initiating the largest and most ethnically diverse genetic study of epilepsy to date. The primary epilepsy phenotypes for Epi25 are based on strict standards agreed upon by the epilepsy community. The epilepsy cases contributed by Epi25 sites can be broadly defined as genetic generalized epilepsy (GGE), non-acquired focal epilepsy (NAFE), epileptic encephalopathies (EE), and lesional focal epilepsies. More information about eligibility criteria and phenotyping forms for Epi25, as well as the contributing centers, can be found here: epi-25.org The genomic data will be analyzed iteratively to identify genes and variants that explain these types of epilepsy. Summary clinical data compiled in the Epi25 clinical database will allow retrospective phenotypic analyses of groups of subjects with common genomic variant(s).

  Study phs001489

• Prematurity and Respiratory Outcome Program: Clinical Research Center Study of Functional and Lymphocytic Markers of Respiratory Morbidity in Hyperoxic Preemies

  Approximately 550,000 babies born prematurely each year in the United States suffer from birth at a time in development when the respiratory tract and immune system would normally be protected and maintained in a naïve state. This project is a component of the NIH Prematurity and Respiratory Outcomes Program (PROP) whose goals are the identification of disease mechanisms and biomarkers to stratify premature infants, at the time of discharge, for their risk of subsequent pulmonary morbidity. This Clinical Research Center (CRC) project will investigate prematurity-dependent alterations in cellular innate and adaptive immune systems resulting in increased susceptibility to respiratory infections and environmental irritants, and leading to respiratory morbidity in the first year of life. Prior studies have established developmental (maturity) and disease-related changes in circulating and pulmonary lymphocyte populations, but a comprehensive assessment of their relationship to disease risk/outcome has not been undertaken. We hypothesize that cellular and molecular immuno-maturity is altered due to intrinsic and extrinsic factors presented by premature birth in such a way as to reduce resistance to viral infections and to promote cytotoxic damage to the lung. We will evaluate immunologic maturity by comprehensively phenotyping lymphocyte populations in peripheral blood sampled at premature delivery, at the time of discharge from the hospital and at twelve months corrected age. The lymphocytic phenotype will be analyzed particularly in the context of gestational age and maternal-fetal stressors capable of modulating oxidative stress (oxygen exposure, infection and environmental tobacco smoke exposure). Additionally, we will assess changes in the molecular phenotype of isolated CD8 lymphocytes, a cell type preferentially recruited to the lungs of premature infants and capable of contributing to disease pathogenesis, by genome-wide expression profiling, in order to uncover novel disease pathways and define a gene expression signature associated with disease risk. We propose to build a statistical model, using cellular and molecular phenotypes and additional clinical variables, for stratifying risk of lung morbidity within the first year of life. Finally, we will assess the development of the gut microbiome in the preterm subjects to correlate with the observation of development of the adaptive immune system.

  Study phs001297