Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, individuals with clonal mosaic events (clonal mosaicism for chromosome alterations and/or loss of chromosome Y) showed an increased risk of COVID-19 lethality

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Prevalence, incidence, and severity associated with viral respiratory tract infections in Colombian adults before the COVID-19 pandemic

6 páginasAbstract Background Acute respiratory illness (ARI) remains the leading cause of global morbidity. Its primary etiology is viral; nevertheless, viral pathogen identification is limited. Clinical information about Latin America's viral etiology, outcomes, and severity is unknown. This study aims to identify the clinical burden of respiratory viral infections, severity, and adult outcomes. Methods This multicentric, population-based study was conducted through the Health Institute of Bogotá, Colombia, including adult patients diagnosed with ARI between 2013 and 2019. Data collection followed ARI public health surveillance program. Incidence, etiological pathogens, and mortality were calculated. Results A total of 2304 patients were included in the study. ARI was most frequently reported in 2018 (23.3% [538/2304]). Incidence varies between years, maintaining a range between 3.5 and 8.4. The most frequent clinical diagnosis was pneumonia in 59.1%. Etiological viral detection was obtained in 21.5% of patients [495/2304], principally by Influenza A. Mortality was 21.8%, and ICU admission was 7.3%. The type of event did not predict the causative pathogen, disease severity, or mortality. Conclusions ARI is a leading cause of morbidity and mortality in Colombia. ARI incidence varies per year and is caused mainly by Influenza A. The classification used in the surveillance program does not correlate with viral etiology, disease severity, and mortality

Using an on-site laboratory for fecal steroid analysis in wild white-faced capuchins

Beehner JC, Alfaro J, Allen C, et al. Using an on-site laboratory for fecal steroid analysis in wild white-faced capuchins. General and Comparative Endocrinology . 2022;329: 114109.Hormone laboratories located "on-site" where field studies are being conducted have a number of advantages. On-site laboratories allow hormone analyses to proceed in near-real-time, minimize logistics of sample permits/shipping, contribute to in-country capacity-building, and (our focus here) facilitate cross-site collaboration through shared methods and a shared laboratory. Here we provide proof-of-concept that an on-site hormone laboratory (the Taboga Field Laboratory, located in the Taboga Forest Reserve, Costa Rica) can successfully run endocrine analyses in a remote location. Using fecal samples from wild white-faced capuchins (Cebus imitator) from three Costa Rican forests, we validate the extraction and analysis of four steroid hormones (glucocorticoids, testosterone, estradiol, progesterone) across six assays (DetectX and ISWE, all from Arbor Assays). Additionally, as the first collaboration across three long-term, wild capuchin field sites (Lomas Barbudal, Santa Rosa, Taboga) involving local Costa Rican collaborators, this laboratory can serve as a future hub for collaborative exchange. Copyright © 2022 Elsevier Inc. All rights reserved

Using an on-site laboratory for fecal steroid analysis in wild white-faced capuchins.

Hormone laboratories located "on-site" where field studies are being conducted have a number of advantages. On-site laboratories allow hormone analyses to proceed in near-real-time, minimize logistics of sample permits/shipping, contribute to in-country capacity-building, and (our focus here) facilitate cross-site collaboration through shared methods and a shared laboratory. Here we provide proof-of-concept that an on-site hormone laboratory (the Taboga Field Laboratory, located in the Taboga Forest Reserve, Costa Rica) can successfully run endocrine analyses in a remote location. Using fecal samples from wild white-faced capuchins (Cebus imitator) from three Costa Rican forests, we validate the extraction and analysis of four steroid hormones (glucocorticoids, testosterone, estradiol, progesterone) across six assays (DetectX® and ISWE, all from Arbor Assays). Additionally, as the first collaboration across three long-term, wild capuchin field sites (Lomas Barbudal, Santa Rosa, Taboga) involving local Costa Rican collaborators, this laboratory can serve as a future hub for collaborative exchange

Expression Atlas update: insights from sequencing data at both bulk and single cell level

Acknowledgements: We would like to thank Olamidipupo Ajigboye and Helen Parkinson for their contributions in enriching EFO in terms needed to describe samples studied in Atlas; Awais Athar, Ahmed Ali, Ugis Sarkans for their help with the BioStudies interface and assistance in submissions of new functional genomics studies to BioStudies. We would like to thank the Bioconda community, the Galaxy community for assistance with Bioconda and Galaxy. We would like to thank the data wranglers, past and present of the Human Cell Atlas Data Coordination Platform for their assistance collating HCA data for the Single Cell Expression Atlas. Finally, we thank the Expression Atlas SAB members, Jurg Bahler (University College London), Angela Brookes (University of California Santa Cruz), Roderic Guigó (Center for Genomic Regulation, chair), Kathryn Lilley (Cambridge University) and Zemin Zhang (Peking University).Funder: European Molecular Biology Laboratory; DOI: https://doi.org/10.13039/100013060Expression Atlas (www.ebi.ac.uk/gxa) and its newest counterpart the Single Cell Expression Atlas (www.ebi.ac.uk/gxa/sc) are EMBL-EBI’s knowledgebases for gene and protein expression and localisation in bulk and at single cell level. These resources aim to allow users to investigate their expression in normal tissue (baseline) or in response to perturbations such as disease or changes to genotype (differential) across multiple species. Users are invited to search for genes or metadata terms across species or biological conditions in a standardised consistent interface. Alongside these data, new features in Single Cell Expression Atlas allow users to query metadata through our new cell type wheel search. At the experiment level data can be explored through two types of dimensionality reduction plots, t-distributed Stochastic Neighbor Embedding (tSNE) and Uniform Manifold Approximation and Projection (UMAP), overlaid with either clustering or metadata information to assist users’ understanding. Data are also visualised as marker gene heatmaps identifying genes that help confer cluster identity. For some data, additional visualisations are available as interactive cell level anatomograms and cell type gene expression heatmaps

Expression Atlas update: insights from sequencing data at both bulk and single cell level

Acknowledgements: We would like to thank Olamidipupo Ajigboye and Helen Parkinson for their contributions in enriching EFO in terms needed to describe samples studied in Atlas; Awais Athar, Ahmed Ali, Ugis Sarkans for their help with the BioStudies interface and assistance in submissions of new functional genomics studies to BioStudies. We would like to thank the Bioconda community, the Galaxy community for assistance with Bioconda and Galaxy. We would like to thank the data wranglers, past and present of the Human Cell Atlas Data Coordination Platform for their assistance collating HCA data for the Single Cell Expression Atlas. Finally, we thank the Expression Atlas SAB members, Jurg Bahler (University College London), Angela Brookes (University of California Santa Cruz), Roderic Guigó (Center for Genomic Regulation, chair), Kathryn Lilley (Cambridge University) and Zemin Zhang (Peking University).Funder: European Molecular Biology Laboratory; DOI: https://doi.org/10.13039/100013060Expression Atlas (www.ebi.ac.uk/gxa) and its newest counterpart the Single Cell Expression Atlas (www.ebi.ac.uk/gxa/sc) are EMBL-EBI’s knowledgebases for gene and protein expression and localisation in bulk and at single cell level. These resources aim to allow users to investigate their expression in normal tissue (baseline) or in response to perturbations such as disease or changes to genotype (differential) across multiple species. Users are invited to search for genes or metadata terms across species or biological conditions in a standardised consistent interface. Alongside these data, new features in Single Cell Expression Atlas allow users to query metadata through our new cell type wheel search. At the experiment level data can be explored through two types of dimensionality reduction plots, t-distributed Stochastic Neighbor Embedding (tSNE) and Uniform Manifold Approximation and Projection (UMAP), overlaid with either clustering or metadata information to assist users’ understanding. Data are also visualised as marker gene heatmaps identifying genes that help confer cluster identity. For some data, additional visualisations are available as interactive cell level anatomograms and cell type gene expression heatmaps

Expression Atlas update: insights from sequencing data at both bulk and single cell level

Acknowledgements: We would like to thank Olamidipupo Ajigboye and Helen Parkinson for their contributions in enriching EFO in terms needed to describe samples studied in Atlas; Awais Athar, Ahmed Ali, Ugis Sarkans for their help with the BioStudies interface and assistance in submissions of new functional genomics studies to BioStudies. We would like to thank the Bioconda community, the Galaxy community for assistance with Bioconda and Galaxy. We would like to thank the data wranglers, past and present of the Human Cell Atlas Data Coordination Platform for their assistance collating HCA data for the Single Cell Expression Atlas. Finally, we thank the Expression Atlas SAB members, Jurg Bahler (University College London), Angela Brookes (University of California Santa Cruz), Roderic Guigó (Center for Genomic Regulation, chair), Kathryn Lilley (Cambridge University) and Zemin Zhang (Peking University).Funder: European Molecular Biology Laboratory; DOI: https://doi.org/10.13039/100013060Expression Atlas (www.ebi.ac.uk/gxa) and its newest counterpart the Single Cell Expression Atlas (www.ebi.ac.uk/gxa/sc) are EMBL-EBI’s knowledgebases for gene and protein expression and localisation in bulk and at single cell level. These resources aim to allow users to investigate their expression in normal tissue (baseline) or in response to perturbations such as disease or changes to genotype (differential) across multiple species. Users are invited to search for genes or metadata terms across species or biological conditions in a standardised consistent interface. Alongside these data, new features in Single Cell Expression Atlas allow users to query metadata through our new cell type wheel search. At the experiment level data can be explored through two types of dimensionality reduction plots, t-distributed Stochastic Neighbor Embedding (tSNE) and Uniform Manifold Approximation and Projection (UMAP), overlaid with either clustering or metadata information to assist users’ understanding. Data are also visualised as marker gene heatmaps identifying genes that help confer cluster identity. For some data, additional visualisations are available as interactive cell level anatomograms and cell type gene expression heatmaps