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

Are GES carbapenemases underdiagnosed? An allelic discrimination assay for their accurate detection and differentiation

GES (Guiana Extended Spectrum) carbapenemases belong to “minor class A carbapenemases” and its prevalence could be underestimated due to the lack of specific tests. The aim of this study was to develop an easy PCR method to differentiate between GES β-lactamases with or without carbapenemase activity, based on an allelic discrimination system of SNPs that encode E104K and G170S mutations, without need of sequencing. Two pair of primers and Affinity Plus probes, labeled with different fluorophores; FAM/IBFQ and YAK/IBFQ, were designed for each one of the SNPs. This allelic discrimination assay allows to detect in real time the presence of all type of GES- βlactamases, being able to differentiate between carbapenemases and extended-spectrum β-lactamase (ESBL), through a quick PCR test that avoid costly sequencing approaches and could help to decrease the current underdiagnosis of minor carbapenemases that scape of phenotypic screenings.Funding: This research was supported by grant from the Instituto de Salud Carlos III (number PI18CIII/00030) CIBER – Consorcio Centro de Investigación Biomédica en Red (CB21/13/00068 and CB21/13/00095) (CIBERINFEC) and Instituto de Salud Carlos III, Ministerio de Ciencia e Innovación and Unión Europea – NextGenerationEU also supported this work

Evolución temporal en el tratamiento transcatéter de la estenosis aórtica: análisis del registro español de TAVI

Introduction and objectives: This study primary endpoint was to present the in-hospital all-cause mortality of the Spanish TAVI registry from its inception until 2018. Secondary endpoints included other in-hospital clinical events, 30-day all-cause mortality, and an assessment of the time trend of this registry. Methods: All consecutive patients included in the Spanish TAVI registry were analyzed. In this time-based analysis, the population was been divided into patients treated before 2014 (cohort A: 2009-2013) and patients treated between 2014 and 2018 (cohort B). Results: From August 2007 to June 2018, 7180 patients were included. The mean age was 81.2 ± 6.5 years and 53% were women. The logistic EuroSCORE was 12% (8-20). Transfemoral access was used in 89%. In-hospital and 30-day all-cause mortality was 4.7% and 5.7%, respectively. On the time-based analyses during the hospital stay, the rate of myocardial infarction, stroke, need for pacemakers, tamponade, coronary obstruction, and vascular complications was similar between both groups. However, cohort B showed less need for conversion to surgery and malapposition of the valve. Also, the implant success rate increased from 93% to 96% (P < .001). In-hospital and 30-day all-cause mortality was significantly lower in cohort B, ([OR, 0.65; IC95%, 0.48-0.86; P = .003] and [OR, 0.71; IC95%, 0.54-0.92; P = .002], respectively). Conclusions: The time trend analysis of the Spanish TAVI registry showed a change in the patients’ clinical profile and an improvement in the in-hospital clinical outcomes and 30-day all-cause mortality in patients treated more recently.Introducción y objetivos: El objetivo primario de este estudio fue presentar la mortalidad total intrahospitalaria del registro español de implante percutáneo de válvula aórtica (TAVI) desde su inicio hasta el año 2018, y como objetivos secundarios otros eventos clínicos intrahospitalarios, la mortalidad total a los 30 días y la evaluación de cuál ha sido la evolución temporal de este registro. Métodos: Fueron analizados todos los pacientes consecutivos incluidos en el registro español de TAVI. En este análisis temporal se dividió la población en pacientes tratados antes de 2014 (cohorte A: 2009-2013) y pacientes tratados entre los años 2014 y 2018 (cohorte B). Resultados: Desde agosto de 2007 hasta junio de 2018 se incluyeron 7.180 pacientes. La edad media fue de 81,2 ± 6,5 años y el 53% eran mujeres. El EuroSCORE logístico fue del 12% (8-20). Se utilizó un acceso transfemoral en el 89%. La mortalidad total intrahospitalaria fue del 4,7% y a los 30 días fue del 5,7%. En el análisis temporal durante la fase hospitalaria, las tasas de infarto, accidente cerebrovascular, necesidad de marcapasos, taponamiento, obstrucción coronaria y complicaciones vasculares fueron similares en ambos grupos. Sin embargo, en la cohorte B se observó una reducción de la necesidad de conversión a cirugía y de mala posición de la válvula, y además la tasa de éxito del implante fue mayor (93 frente a 96%; p < 0,001). La mortalidad por cualquier causa ajustada tanto intrahospitalaria como a los 30 días, fue significativamente menor en la cohorte B (odds ratio [OR] = 0,65; intervalo de confianza del 95% [IC95%], 0,48-0,86; p = 0,003; y OR = 0,71; IC95%, 0,54-0,92; p = 0,002, respectivamente). Conclusiones: En el análisis temporal del registro español de TAVI se observan un cambio en el perfil clínico de los pacientes y una mejora en la evolución clínica tanto intrahospitalaria como a los 30 días en los pacientes tratados en los últimos años

Impacto de la COVID-19 en el tratamiento del infarto agudo de miocardio con elevación del segmento ST. La experiencia Española

The COVID-19 outbreak has had an unclear impact on the treatment and outcomes of patients with ST-segment elevation myocardial infarction (STEMI). The aim of this study was to assess changes in STEMI management during the COVID-19 outbreak. Using a multicenter, nationwide, retrospective, observational registry of consecutive patients who were managed in 75 specific STEMI care centers in Spain, we compared patient and procedural characteristics and in-hospital outcomes in 2 different cohorts with 30-day follow-up according to whether the patients had been treated before or after COVID-19. Suspected STEMI patients treated in STEMI networks decreased by 27.6% and patients with confirmed STEMI fell from 1305 to 1009 (22.7%). There were no differences in reperfusion strategy (> 94% treated with primary percutaneous coronary intervention in both cohorts). Patients treated with primary percutaneous coronary intervention during the COVID-19 outbreak had a longer ischemic time (233 [150-375] vs 200 [140-332] minutes, P < .001) but showed no differences in the time from first medical contact to reperfusion. In-hospital mortality was higher during COVID-19 (7.5% vs 5.1%; unadjusted OR, 1.50; 95%CI, 1.07-2.11; P < .001); this association remained after adjustment for confounders (risk-adjusted OR, 1.88; 95%CI, 1.12-3.14; P = .017). In the 2020 cohort, there was a 6.3% incidence of confirmed SARS-CoV-2 infection during hospitalization. The number of STEMI patients treated during the current COVID-19 outbreak fell vs the previous year and there was an increase in the median time from symptom onset to reperfusion and a significant 2-fold increase in the rate of in-hospital mortality. No changes in reperfusion strategy were detected, with primary percutaneous coronary intervention performed for the vast majority of patients. The co-existence of STEMI and SARS-CoV-2 infection was relatively infrequent.S

Human immunodeficiency virus continuum of care in 11 european union countries at the end of 2016 overall and by key population: Have we made progress?

Background. High uptake of antiretroviral treatment (ART) is essential to reduce human immunodeficiency virus (HIV) transmission and related mortality; however, gaps in care exist. We aimed to construct the continuum of HIV care (CoC) in 2016 in 11 European Union (EU) countries, overall and by key population and sex. To estimate progress toward the Joint United Nations Programme on HIV/AIDS (UNAIDS) 90-90-90 target, we compared 2016 to 2013 estimates for the same countries, representing 73% of the population in the region. Methods. A CoC with the following 4 stages was constructed: number of people living with HIV (PLHIV); proportion of PLHIV diagnosed; proportion of those diagnosed who ever initiated ART; and proportion of those ever treated who achieved viral suppression at their last visit. Results. We estimated that 87% of PLHIV were diagnosed; 92% of those diagnosed had ever initiated ART; and 91% of those ever on ART, or 73% of all PLHIV, were virally suppressed. Corresponding figures for men having sex with men were: 86%, 93%, 93%, 74%; for people who inject drugs: 94%, 88%, 85%, 70%; and for heterosexuals: 86%, 92%, 91%, 72%. The proportion suppressed of all PLHIV ranged from 59% to 86% across countries. Conclusions. The EU is close to the 90-90-90 target and achieved the UNAIDS target of 73% of all PLHIV virally suppressed, significant progress since 2013 when 60% of all PLHIV were virally suppressed. Strengthening of testing programs and treatment support, along with prevention interventions, are needed to achieve HIV epidemic control

GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19

Data availability: Downloadable summary data are available through the GenOMICC data site (https://genomicc.org/data). Summary statistics are available, but without the 23andMe summary statistics, except for the 10,000 most significant hits, for which full summary statistics are available. The full GWAS summary statistics for the 23andMe discovery dataset will be made available through 23andMe to qualified researchers under an agreement with 23andMe that protects the privacy of the 23andMe participants. For further information and to apply for access to the data, see the 23andMe website (https://research.23andMe.com/dataset-access/). All individual-level genotype and whole-genome sequencing data (for both academic and commercial uses) can be accessed through the UKRI/HDR UK Outbreak Data Analysis Platform (https://odap.ac.uk). A restricted dataset for a subset of GenOMICC participants is also available through the Genomics England data service. Monocyte RNA-seq data are available under the title ‘Monocyte gene expression data’ within the Oxford University Research Archives (https://doi.org/10.5287/ora-ko7q2nq66). Sequencing data will be made freely available to organizations and researchers to conduct research in accordance with the UK Policy Framework for Health and Social Care Research through a data access agreement. Sequencing data have been deposited at the European Genome–Phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGAS00001007111.Extended data figures and tables are available online at https://www.nature.com/articles/s41586-023-06034-3#Sec21 .Supplementary information is available online at https://www.nature.com/articles/s41586-023-06034-3#Sec22 .Code availability: Code to calculate the imputation of P values on the basis of SNPs in linkage disequilibrium is available at GitHub (https://github.com/baillielab/GenOMICC_GWAS).Acknowledgements: We thank the members of the Banco Nacional de ADN and the GRA@CE cohort group; and the research participants and employees of 23andMe for making this work possible. A full list of contributors who have provided data that were collated in the HGI project, including previous iterations, is available online (https://www.covid19hg.org/acknowledgements).Change history: 11 July 2023: A Correction to this paper has been published at: https://doi.org/10.1038/s41586-023-06383-z. -- In the version of this article initially published, the name of Ana Margarita Baldión-Elorza, of the SCOURGE Consortium, appeared incorrectly (as Ana María Baldion) and has now been amended in the HTML and PDF versions of the article.Copyright © The Author(s) 2023, Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).GenOMICC was funded by Sepsis Research (the Fiona Elizabeth Agnew Trust), the Intensive Care Society, a Wellcome Trust Senior Research Fellowship (to J.K.B., 223164/Z/21/Z), the Department of Health and Social Care (DHSC), Illumina, LifeArc, the Medical Research Council, UKRI, a BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070 and BBS/E/D/30002275) and UKRI grants MC_PC_20004, MC_PC_19025, MC_PC_1905 and MRNO2995X/1. A.D.B. acknowledges funding from the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z), the Edinburgh Clinical Academic Track (ECAT) programme. This research is supported in part by the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant MC_PC_20029). Laboratory work was funded by a Wellcome Intermediate Clinical Fellowship to B.F. (201488/Z/16/Z). We acknowledge the staff at NHS Digital, Public Health England and the Intensive Care National Audit and Research Centre who provided clinical data on the participants; and the National Institute for Healthcare Research Clinical Research Network (NIHR CRN) and the Chief Scientist’s Office (Scotland), who facilitate recruitment into research studies in NHS hospitals, and to the global ISARIC and InFACT consortia. GenOMICC genotype controls were obtained using UK Biobank Resource under project 788 funded by Roslin Institute Strategic Programme Grants from the BBSRC (BBS/E/D/10002070 and BBS/E/D/30002275) and Health Data Research UK (HDR-9004 and HDR-9003). UK Biobank data were used in the GSMR analyses presented here under project 66982. The UK Biobank was established by the Wellcome Trust medical charity, Medical Research Council, Department of Health, Scottish Government and the Northwest Regional Development Agency. It has also had funding from the Welsh Assembly Government, British Heart Foundation and Diabetes UK. The work of L.K. was supported by an RCUK Innovation Fellowship from the National Productivity Investment Fund (MR/R026408/1). J.Y. is supported by the Westlake Education Foundation. SCOURGE is funded by the Instituto de Salud Carlos III (COV20_00622 to A.C., PI20/00876 to C.F.), European Union (ERDF) ‘A way of making Europe’, Fundación Amancio Ortega, Banco de Santander (to A.C.), Cabildo Insular de Tenerife (CGIEU0000219140 ‘Apuestas científicas del ITER para colaborar en la lucha contra la COVID-19’ to C.F.) and Fundación Canaria Instituto de Investigación Sanitaria de Canarias (PIFIISC20/57 to C.F.). We also acknowledge the contribution of the Centro National de Genotipado (CEGEN) and Centro de Supercomputación de Galicia (CESGA) for funding this project by providing supercomputing infrastructures. A.D.L. is a recipient of fellowships from the National Council for Scientific and Technological Development (CNPq)-Brazil (309173/2019-1 and 201527/2020-0)