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• Identification of biomarkers of response to preoperative talazoparib monotherapy in treatment naïve gBRCA+ breast cancers

  Germline mutations in BRCA1 or BRCA2 exist in ~2-7% of breast cancer patients, which has led to the approval of PARP inhibitors in the advanced setting. We have previously reported a phase II neoadjuvant trial of single agent talazoparib for patients with germline BRCA pathogenic variants with a pathologic complete response (pCR) rate of 53%. As nearly half of the patients treated did not have pCR, better strategies are needed to overcome treatment resistance. To this end, we conducted multi-omic analysis of 13 treatment naïve breast cancer tumors from patients that went on to receive single-agent neoadjuvant talazoparib. We looked for biomarkers that were predictive of response (assessed by residual cancer burden) after 6 months of therapy. We found that all resistant tumors exhibited either the loss of SHLD2, expression of a hypoxia signature, or expression of a stem cell signature. These results indicate that the deep analysis of pre-treatment tumors can identify biomarkers that are predictive of response to talazoparib and potentially other PARP inhibitors, and provides a framework that will allow for better selection of patients for treatment, as well as a roadmap for the development of novel combination therapies to prevent emergence of resistance.

  Study EGAS00001005676

• Developing Allelic Imbalance Analysis from Single-Nucleus RNA-Seq Data

  Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool for understanding gene function across diverse cells. Recently, this has included the use of allele-specific expression (ASE) analysis to better understand how variation in the human genome affects RNA expression at the single-cell level. We reasoned that, because intronic reads are more prevalent in single-nucleus RNA-Seq (snRNA-Seq) and introns are under lower purifying selection, and are thus enriched for genetic variants, that snRNA-seq should facilitate single-cell analysis of ASE. Here we demonstrate how experimental and computational choices can improve the results of allelic imbalance analysis. We explore how experimental choices, such as RNA source, read length, sequencing depth, genotyping, etc., impact the power of ASE-based methods. We developed a new suite of computational tools to process and analyze scRNA-seq and snRNA-seq for ASE. As hypothesized, we extracted more ASE information from reads in intronic regions than those in exonic regions and show how read length can be set to increase power. Additionally, hybrid selection improved our power to detect allelic imbalance in genes of interest. We also explored methods to recover allele-specific isoform expression levels from both long- and short-read snRNA-seq. Overall, we provide an end-to-end experimental and computational approach for future studies.

  Study phs003749

• NHLBI TOPMed: Coronary Artery Risk Development in Young Adults (CARDIA)

  CARDIA is a study examining the etiology and natural history of cardiovascular disease beginning in young adulthood. In 1985-1986, a cohort of 5115 healthy black and white men and women, aged 18-30 years, were selected to have approximately the same number of people in subgroups of age (18-24 and 25-30), sex, race, and education (high school or less, and more than high school) within each of four US Field Centers. These same participants were asked to participate in follow-up examinations during 1987-1988 (Year 2), 1990-1991 (Year 5), 1992-1993 (Year 7), 1995-1996 (Year 10), 2000-2001 (Year 15), 2005-2006 (Year 20), 2010-2011 (Year 25) and 2015-2016 (Year 30). In addition to the follow-up examinations, participants are contacted regularly for the ascertainment of information on out-patient procedures and hospitalizations experienced between contacts. Within the past five years, 95% of the original surviving cohort has been contacted. While the specifics of each examination have differed somewhat, data have been collected on a variety of factors believed to be related to heart disease. These include conditions with clear links to heart disease, such as blood pressure, cholesterol and other lipids. Data have also been collected on physical measurements, such as weight and skinfold fat, as well as lifestyle factors such as substance use (tobacco and alcohol), dietary and exercise patterns, behavioral and psychological variables, medical and family history, and other chemistries (e.g., insulin and glucose). In addition, subclinical atherosclerosis was measured via echocardiography during Years 5, 10, and 25, computed tomography during Years 15 and 20, and carotid ultrasound during Year 20.Comprehensive phenotypic data for study participants are available through dbGaP phs000285.

  Study phs001612

• Transcriptional profiling of ovarian tumours and cell lines

  Purpose: Endogenous retroviruses (ERVs) play a role in a variety of biological processes, including embryogenesis and cancer. DNA methyltransferase inhibitors (DNMTi)-induced ERV expression triggers interferon responses in ovarian cancer cells via the viral sensing machinery. Baseline expression of ERVs also occurs in cancer cells, though this process is poorly understood and previously unexplored in epithelial ovarian cancer (EOC). Here, the prognostic and immunomodulatory consequences of baseline ERV expression was assessed in EOC. Experimental Design: ERV expression was assessed using EOC transcriptional data from TCGA and from an independent cohort (HH), as well as from untreated or DNMTi-treated EOC cell lines. LASSO logistic regression defined an ERV expression score to predict patient prognosis. Immunohistochemistry (IHC) was conducted on the HH cohort. Combination of DNMTi treatment with γδ T cells was tested in vitro, using EOC cell lines and patient-derived tumor cells. Results: ERV expression was found to define clinically relevant subsets of EOC patients. An ERV prognostic score was successfully generated in TCGA and validated in the independent cohort. In EOC patients from this cohort, a high ERV score was associated with better survival (log-rank p=0.0009) and correlated with infiltration of CD8+PD1+ T cells (r=0.46, p=0.0001). In vitro, baseline ERV expression dictates the level of ERV induction in response to DNMTi. Manipulation of ERV expression by DNMTi resulted in improved EOC cell killing by cytotoxic immune cells. Conclusions: These findings uncover the potential for baseline ERV expression to robustly inform EOC patient prognosis, influence tumor immune infiltration and affect anti-tumor immunity.

  Study EGAS00001004814

• A Genomic Atlas of Systemic Interindividual Epigenetic Variation in Humans (GTEx)

  Methylation of cytosines in CpG dinucleotides is an epigenetic mechanism with essential roles in mammalian development. To explore its functions in cellular differentiation, unbiased analysis of CpG methylation by whole genome bisulfite sequencing (WGBS) has been used to characterize epigenetic differences among different human tissues and cell types. Meanwhile, human interindividual variation in DNA methylation that is not cell-type specific has attracted relatively little attention. Systemic interindividual epigenetic variation is important, however, because like genetic variation it is a potential determinant of phenotypic variation and can be assessed in any easily obtainable DNA sample. Since systemic epigenetic variants originate in the preimplantation embryo, their establishment can be influenced by periconceptional environment, and potentially provide information about lifetime risks relevant to global health, obesity, and cancer. We elucidated systemic interindividual variation in CpG methylation in the human genome. We studied brain, heart, and thyroid tissues (representing all three germ layer lineages) from each of 10 donors in the NIH Gene-Tissue Expression (GTEx) project. We performed deep whole genome bisulfite sequencing for these 30 samples, achieving a sequencing depth of over 50x coverage per sample. We identified 9,926 correlated regions of systemic interindividual variation (CoRSIVs). These regions, comprising just 0.1% of the human genome, often correlate with one another over long genomic distances, are associated with transposable elements and subtelomeric regions, conserved across various human ethnic groups, and particularly sensitive to periconceptional environment. While genetic variation appears to influence methylation at most CoRSIVs, many show no evidence of genetic influence, suggestive of 'pure' epigenetic variation. At CoRSIVs, interindividual variation in DNA methylation in an easily biopsied tissue predicts expression in other tissues, and genes associated with these loci are implicated in a range of human disorders. In addition to charting a previously unrecognized molecular level of human individuality, this atlas of human CoRSIVs provides a resource for future population-based investigations into how interindividual epigenetic variation modulates risk of disease.Version 2 now also includes Target Capture Sequencing of CoRSIVs in 808 tissues (188 GTEx Donors). Focusing on the CoRSIVs identified by analyzing WGBS data, a Target Capture Bisulfite sequencing assay was developed. Using the genotype data of 188 GTEx donors, we assessed mQTL by capturing a 1MB region at each CoRSIV and quantifying methylation by Bisulfite-seq. The Target Capture Bisulfite sequencing data will be available to download via the AnVIL project.

  Study phs001746

• Warfarin Pharmacogenetics: Pharmacogenetic Optimization of Anticoagulant Response (POAT) and Genetic and Environmental Determinants of Warfarin Response (GEDWR)

  Although the efficacy of warfarin in the treatment and prevention of thromboembolic disorders is proven, it is vastly underutilized with difficulties in management and risk of complications being the main deterrents. Recognition of genetic regulation of warfarin response has fueled efforts to quantify this influence, but the focus has been restricted to select genes and outcomes mainly in European Americans. Race appears to influence warfarin dose requirements with African Americans requiring larger and Asians requiring lower doses compared to Europeans. This variation in dose requirement by race may at least partially be explained by genetic differences. The Genetic and Environmental Determinants of Warfarin Response (GEDWR) and the Pharmacogenetic Optimization of Anticoagulation Therapy (POAT) are prospective cohort study aimed at defining the influence of CYP2C9, VKORC1 and other genes. All patients were followed at monthly intervals from initiation of therapy. At each visit factors influencing warfarin response such as warfarin dose, INR, concurrent medications, etc. were documented. Information on concurrent medications was updated at every clinic visit by self-report and verified by medical record review. Concomitant use of drugs such as drugs that alter warfarin pharmacokinetics, including CYP2C9 inhibitors (e.g., amiodarone), and pharmacodynamics such as antiplatelet agents (e.g. aspirin). Although the a priori hypothesis focused on the candidate-gene approach, with the recognition that the candidate-gene approach is bound by the assumption that our knowledge of genetic influences on warfarin response is complete. Among African Americans known variation in candidate genes (CYP2C9 and VKORC1) explain substantially less variability in warfarin dose requirements. Therefore a genome-wide association study (GWAS) was conducted on African American patients to identify novel variants associated with warfarin dose requirements.

  Study phs000708

• LifeLines-DEEP population multi-omix cohort from the noth of the Netherlands.

  The LifeLines-DEEP cohort is a sub-cohort of the LifeLines cohort (167,729 participants) that employs a broad range of investigative procedures to assess the biomedical, socio-demographic, behavioral, physical and psychological factors that contribute to health and disease in the general Dutch population, (Scholtens 2015). A subset of approximately 1,500 participants also took part in LifeLines-DEEP. For these participants, additional biological materials were collected, including analysis of the gut microbiome composition. The phenotyping and processing of LifeLines-DEEP has been described in Tigchelaar (2015).

  Study EGAS00001001704

• Elevated somatic mutation burdens in normal human cells due to defective DNA polymerases

  Mutation accumulation over time in normal somatic cells contributes to cancer development and is proposed as a cause of ageing. DNA polymerases POLE and POLD1 replicate DNA with high fidelity during normal cell divisions. However, in some cancers defective proofreading due to acquired mutations in the exonuclease domains of POLE or POLD1 causes markedly elevated somatic mutation burdens with distinctive mutational signatures. POLE and POLD1 exonuclease domain mutations also cause familial cancer predisposition when inherited through the germline. Here, we sequenced normal tissue DNA from individuals with germline POLE or POLD1 exonuclease domain mutations. Increased mutation burdens with characteristic mutational signatures were found to varying extents in all normal adult somatic cell types examined, during early embryogenesis and in sperm. Mutation burdens were further markedly elevated in neoplasms from these individuals. Thus human physiology is able to tolerate ubiquitously elevated mutation burdens. Indeed, with the exception of early onset cancer, individuals with germline POLE and POLD1 exonuclease domain mutations are not reported to show abnormal phenotypic features, including those of premature ageing. The results, therefore, do not support a simple model in which all features of ageing are attributable to widespread cell malfunction directly resulting from somatic mutation burdens accrued during life.

  Dataset EGAD00001006212

• Molecular defects in pseudohypoparathyroidism or related disorders

  Maintaining calcium levels within a narrow normal range is of critical importance for numerous different cellular functions. One of the most important regulators of blood calcium levels is parathyroid hormone (PTH), which mediates its actions through the PTH/PTHrP receptor, a Gαs-coupled receptor. Few inherited disorders are characterized by diminished blood calcium levels and elevated blood phosphate levels; some of these disorders are caused by too little PTH synthesis and/or secretion (hypoparathyroidism, HP), while others are caused by resistance towards PTH (pseudohypoparathyroidism, PHP). Only few of the inherited forms of HP (<10%) have been defined at the molecular level. In contrast, genetic mutations have been identified for several inherited forms of PHP. For example, PHP type Ia (PHP-Ia) is caused by maternally inherited mutations in those GNAS exons that encode Gαs, while autosomal dominant PHP type Ib (AD-PHP-Ib) is caused by maternal inherited deletions within or up-stream of GNAS, which are associated with abnormal GNAS methylation. However, a large number of patients with PTH-resistance and thus hypocalcemia show GNAS methylation changes, but their underlying genetic defects have not yet been defined at the DNA level. These "sporadic" patients may be affected by an autosomal recessive form of PHP-Ib (AR-PHP-Ib), which is most likely not linked to the GNAS locus. In our studies, we propose to search through exome sequence analyses for novel genetic mutations responsible for novel autosomal dominant forms of HP that are not caused by mutations in the known disease-causing genes; some of these families are large enough to perform genetic linkage studies. We furthermore propose to search for the genetic mutation(s) responsible for the autosomal recessive variant of PHP-Ib through the analysis of whole exome sequences; for these studies we focus particularly on patients, whose parents are likely to be consanguineous. The proposed efforts are expected to lead to the identification of novel genes that are involved in parathyroid development and function (HP) and genes that are involved in the establishment or maintenance of GNAS methylation (AR-PHP-Ib).

  Study phs000476

• 13K T2D-GENES analysis files

  This data set includes the following summary level data files used for the 13k analysis of T2D-GENES data: wes.variants.list: list of variants to keep for any analysis of the exomes data wes.assoc.samples.list: list of samples to keep for association analysis wes.assoc.variants.list: list of variants to keep for association analysis wes.sv.assoc.txt: single variant association analysis results wes.gene.ptv.variants.list.txt: list of protein truncating variants to use in gene-level analysis wes.gene.ptv.assoc.txt: results from gene-level tests of protein truncating variants wes.gene.nsstrict.variants.list.txt: list of NSstrict variants to use in gene-level analysis wes.gene.nsstrict.assoc.txt: results from gene-level tests of NSstrict variants wes.gene.nsbroad.variants.list.txt: list of NSbroad variants to use in gene-level analysis wes.gene.nsbroad.assoc.txt: results from gene-level tests of NSbroad variants wes.gene.ns.variants.list.txt: list of non synonymous variants to use in gene-level analysis wes.gene.ns.assoc.txt: results from gene-level tests of non synonymous variants

  Dataset EGAD00010001188