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• Non Dystrophic Myotonias: Genotype-Phenotype Correlation and Longitudinal

  NMD are rare ion channel disorders. The optimal management and treatment of these disorders are not known. This multi-center proposal will allow the prospective collection of standardized data from a critical number of patients to help better define the clinical features of NDM. The data will also be used to establish clinically relevant endpoints for use in therapeutic trials. The identification and genetic characterization of patients will facilitate recruitment of participants for future therapeutic trials. Ultimately, the information gained will lead to the improvements in the treatment and management of NMD with an associated reduction in morbidity and improvement in patient quality of life.

  Study phs000578

• Single-cell atlas of penile cancer reveals TP53 mutations as driver for an aggressive phenotype, irrespective of HPV status, and provides clues for treatment personalization

  Our aim was to identify molecular differences in the microenvironment of penile squamous cell carcinoma (PSCC) stratified by TP53 loss-of-function (TP53LOF) mutations and HPV-status. Hence, we present a first single-cell transcriptomic atlas of PSCC. Stratification based on TP53 and HPV-status uncovered differences in CSS and underlying molecular pathways. Our data indicate that TP53LOF tumors are characterized by worse biological behavior regardless of HPV-status. These findings and further research are essential for trial design in PSCC, allowing us to move away from the current one-size-fits-all approach.

  Study EGAS50000000217

• Healthspan and lifespan extension by fecal microbiota transplantation in progeroid mice

  The gut microbiome is emerging as a key regulator of several metabolic, immune and neuroendocrine pathways. Gut microbiome deregulation has been implicated in major conditions such as obesity, type 2 diabetes, cardiovascular disease, non-alcoholic fatty acid liver disease or cancer, but its precise role in aging remains to be elucidated. Here, we characterize the gut microbiome profile of accelerated aging and show that its external modulation is sufficient to extend healthspan and lifespan. We found that two different mouse models of progeria present with intestinal dysbiosis, which is characterized, among other alterations, by an increment in proteobacteria, cyanobacteria and a loss in verrucomicrobia, whereas long-lived humans (i.e., centenarians) exhibit a remarkable increase in verrucomicrobia and a reduction in proteobacteria. Fecal microbiota transplantation proved to be effective to enhance healthspan and lifespan in both progeroid mouse models and, more importantly, the solely transplantation with the verrucomicrobia Akkermansia muciniphila was sufficient to exert beneficial effects. Our results demonstrate that intestinal dysbiosis is a phenotype associated with accelerated aging and its correction provides health benefits. Moreover, metabolomic analysis of ileal content points to the restoration of secondary bile acids as a possible mechanism for the beneficial outcome of reestablishing a healthy microbiome. Our results suggest the existence of a link between gut aging and the microbiota, and can help to gain insight into the rationale for microbiome-based interventions against age-related diseases. Mouse sequence data have been deposited in ENA (https://www.ebi.ac.uk/ena) under accession number PRJEB34214

  Study EGAS00001003656

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

  The NIH Researching COVID to Enhance Recovery (RECOVER) initiative comprises a set of three combined retrospective and prospective, longitudinal, observational meta-cohort studies with nested case-control studies designed to define and characterize the epidemiology, natural history, clinical spectrum, and underlying mechanisms of post-acute effects of SARS-CoV-2 infection (PASC or Post-COVID syndrome) in a diverse study population representative of the general COVID-19 population in the US. Enrolled patients with and without known SARS-CoV-2 infection will be observed for clinical signs and symptoms of PASC and will be assessed for risk and resiliency factors and potential mediating factors associated with the severity and progression of PASC. The objective of the RECOVER initiative is to enhance knowledge of recovery from SARS-CoV-2 infections in order to support development of novel diagnostic and therapeutic interventions. Overarching scientific objectives are as follows: Characterize the incidence and prevalence of sequelae of SARS-CoV-2 infection. Characterize the spectrum of clinical symptoms, subclinical organ dysfunction, natural history, and distinct phenotypes identified as sequelae of SARS-CoV-2 infection.Define the biological mechanisms underlying pathogenesis of the sequelae of SARS-CoV-2 infection. The RECOVER observational studies comprise three cohorts across the lifespan (adult, pediatric, and tissue pathology (autopsy)). The data collection and data analysis plans for each cohort have been harmonized to use common data elements where feasible. Brief descriptions of each cohort are provided in the following paragraphs:1) NIH RECOVER: A Multi-site Observational Study of Post-Acute Sequelae of SARS-CoV-2 Infection in Adults (this study)The RECOVER adult cohort study is a combined retrospective and prospective, longitudinal, observational meta-cohort of individuals who will enter the cohort with and without SARS-CoV-2 infection and at varying stages before and after infection. Individuals with and without SARS-CoV-2 infection and with or without PASC symptoms will be followed to identify risk factors and occurrence of PASC. This study will be conducted in the United States and subjects will be recruited through inpatient, outpatient, and community-based settings. Study data including age, demographics, social determinants of health, medical history, vaccination history, details of acute SARS-CoV-2 infection, overall health and physical function, and PASC symptom screen will be reported by subjects or collected from the electronic health record using a case report form at specified intervals. Biologic specimens will be collected at specified intervals, with some tests performed in local clinical laboratories and others performed by centralized research centers or banked in the Biospecimen Repository. Advanced clinical examinations and radiologic examinations will be performed at local study sites with cross-site standardization. A summary of information available by request in the RECOVER Adult Cohort (this study) can be reviewed via the "Adult Cohort Dataset Release Notes" and the "REDCap Codebook for the Adult Cohort" documents.2) The RECOVER Post Acute Sequelae of SARS-CoV-2 (PASC) Pediatric Cohort Study: A Multi-Center Observational Study (data not yet released)The RECOVER pediatric study is a combined retrospective and prospective, longitudinal, observational meta-cohort of individuals ages newborn-25 years who will enter the cohort with and without SARS-CoV-2 infection at varying stages before and after infection. Individuals with and without SARS-CoV-2 infection and with or without PASC symptoms will be followed to identify risk factors and occurrence of PASC. This study recruit participants inpatient, outpatient, and community-based settings in the United States. Study data including age, demographics, social determinants of health, medical history, vaccination history, details of acute SARS-CoV-2 infection, overall health and physical function, and PASC symptoms will be reported by participants or collected from the electronic health record using a case report form at specified intervals. Biologic specimens will be collected at specified intervals, with some tests performed in local clinical laboratories and others performed by centralized research centers or banked in the Biospecimen Repository. Advanced clinical and radiologic examinations will be performed at local study sites with cross-site standardization.3) NIH RECOVER: A Multi-site Pathology Study of Post-Acute Sequelae of SARS-CoV-2 Infection (data not yet released)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 (i) non-hospitalized patients who die 30 days or later from symptom onset of COVID-19, and (ii) hospitalized patients who die 30 days or later after discharge from a hospitalization for COVID-19. The study will include decedents who had previously fully recovered from SARS-CoV-2 infection (i.e., >30 days from onset in non-hospitalized, or >30 days from discharge in hospitalized patients), and decedents who meet clinical criteria of PASC as defined by the recent World Health Organization publication (see Section 5.4 below). The autopsy study will also explore the pathology of acute SARS-CoV-2 infection in a smaller subset of patients who died 15-30 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 phs003463

• Lebanon_HighCov_seq

  We propose to investigate the genomics of a Lebanese sample. we plan (1) genotyping (2.5M) of 120 Lebanese individuals, choosing this platform to allow comparison with the 1000 Genomes and African Genome Variation project populations, (2) 8x sequencing of 100 individuals to provide unbiased population-level sequence information including allele frequencies, and (3) 30x sequencing of four individuals to allow inferences such as from PSMC/MSMC to be obtained. The current form is for the high-coverage sequencing. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002085

• Lebanon_LowCov_seq

  we propose to investigate the genomics of a Lebanese sample. we plan (1) genotyping (2.5M) of 120 Lebanese individuals, choosing this platform to allow comparison with the 1000 Genomes and African Genome Variation project populations, (2) 8x sequencing of 100 individuals to provide unbiased population-level sequence information including allele frequencies, and (3) 30x sequencing of four individuals to allow inferences such as from PSMC/MSMC to be obtained. The current form is for the low-coverage sequencing. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002084

• National Institute of General Medical Sciences (NIGMS) Human Genetic Cell Repository Human Variation Panels including 100 African-Americans (HD100AA), 100 Caucasians (HD100CAU), 100 Han People of Los Angeles (HD100CHI) and 100 Mexican American Community of Los Angeles (HD100MEX)

  The Human Genetic Cell Repository is sponsored by the National Institute of General Medical Sciences (NIGMS) with the mission of supplying scientists with the materials for accelerating disease gene discovery and functional studies. The resources available include highly-characterized, contaminant-free cell cultures and high quality, well-characterized DNA samples derived from these cultures, both subjected to rigorous quality control. The Repository was established in 1972 at Coriell and contains more than 9,500 cell lines, primarily fibroblasts and transformed lymphoblasts. The Repository has a major emphasis on inherited diseases and chromosomally aberrant cell lines. In addition, it contains a large collection dedicated to understanding human variation that includes samples from populations around the world, the CEPH collection, the Polymorphism Discovery Resource, Human Variation and many apparently healthy controls. The Human Variation collection provides cell lines and DNA samples from a variety of populations. The panels of African-Americans (HD100AA) and Caucasians (100CAU) used for this study are comprised of samples present in the Repository that were originally collected over the years from apparently healthy people to be used as "controls", for example, unaffected family members of persons with identified mono-genetic diseases. The samples for the Han people of Los Angeles (HD100CHI) and the Mexican American Community of Los Angeles (HD100MEX), however, were collected relatively recently from volunteers, identified as member of these communities, specifically for use in these panels. The Coriell Genotyping and Microarray Center in conjunction with the NIGMS repository used the Affymetrix Genome-Wide Human SNP 6.0 platform to genotype 400 samples from the NIGMS human variation panels. The populations genotyped included Americans of African, Caucasian, Mexican, and Han Chinese ancestry. The Affymetrix SNP 6.0 array detects approximately 940,000 SNPs and provides copy number information for more than 900,000 additional locations across the genome.

  Study phs000211

• Efficient prediction of a spatial transcriptomics profile better characterizes breast cancer tissue sections without costly experimentation

  Spatial transcriptomics is an emerging technology requiring costly reagents and considerable skills, limiting the identification of transcriptional markers related to histology. Here, we show that predicted spatial gene-expressions in unmeasured regions and tissues can enhance biologists��� histological interpretations. We developed the Deep learning model for Spatial gene Clusters and Expression, DeepSpaCE and confirmed its performance using the spatial-transcriptome profiles and immunohistochemistry images of consecutive human breast cancer tissue sections. For example, the predicted expression patterns of SPARC, an invasion marker, highlighted a small tumor-invasion region that is difficult to identify using raw data of spatial transcriptome alone because of a lack of measurements. We further developed semi-supervised DeepSpaCE using unlabeled histology images and increased the imputation accuracy of consecutive sections, enhancing applicability for a small sample size. Our method enables users to derive hidden histological characters via spatial transcriptome and gene annotations, leading to accelerated biological discoveries without additional experiments.

  Study JGAS000290

• Validation_of_AML_Mutational_Screening

  We recently worked-up a pulldown protocol for studying 21 genes recurrently mutated in AML (Study1770). Our manuscript is currently under revision and to address the reviewers' comments we need to validate some mutations by re-sequencing. In this add-on study we will be using PCR followed by MiSeq for this purpose.

  Study EGAS00001000430

• Sensitive detection of tumor mutations from blood and its application to immunotherapy prognosis

  Cell-free DNA (cfDNA) is attractive for many applications, including cancer detection, locating, and monitoring. A fundamental task underlying these applications is the SNV calling from cfDNA, which, however, faces a new challenge, namely, the generally very low tumor content in cfDNA. Thus all existing callers fail to achieve satisfactory performance. Here we present cfSNV, a method incorporating multi-layer error suppression and hierarchical mutation calling, to address this important challenge. Furthermore, by leveraging cfDNA’s comprehensive coverage of clonal landscape, for the first time cfSNV can profile mutations even in subclones. In both simulated and real patient data, cfSNV vastly outperforms existing tools, showing tens of times increase in sensitivity in detecting mutations with low allele frequency while maintaining high precision. cfSNV can enhance the clinical utilities of cfDNA by dramatically reducing the required sequencing depth and therefore reduce the cost by magnitudes, and further make the Whole-Exome-Sequencing of cfDNA a viable option. As an example, we demonstrate that cfDNA-WES allows a new biomarker to effectively select patients for immunotherapy.

  Study EGAS00001004373