The Arabidopsis thioredoxin TRXh5regulates the S-nitrosylation pattern of the TIRK receptor being both proteins essential in the modulation of defences to Tetranychus urticae

The interaction between plants and phytophagous arthropods encompasses a complex network of molecules, signals, and pathways to overcome defences generated by each interacting organism. Although most of the elements and modulators involved in this interplay are still unidentified, plant redox homeostasis and signalling are essential for the establishment of defence responses. Here, focusing on the response of Arabidopsis thaliana to the spider mite Tetranychus urticae, we demonstrate the involvement in plant defence of the thioredoxin TRXh5, a small redox protein whose expression is induced by mite infestation. TRXh5 is localized in the cell membrane system and cytoplasm and is associated with alterations in the content of reactive oxygen and nitrogen species. Protein S-nitrosylation signal in TRXh5 over-expression lines is decreased and alteration in TRXh5 level produces changes in the JA/SA hormonal crosstalk of infested plants. Moreover, TRXh5 interacts and likely regulates the redox state of an uncharacterized receptor-like kinase, named THIOREDOXIN INTERACTING RECEPTOR KINASE (TIRK), also induced by mite herbivory. Feeding bioassays performed withTRXh5 over-expression plants result in lower leaf damage and reduced egg accumulation after T. urticae infestation than in wild-type (WT) plants. In contrast, mites cause a more severe injury in trxh5 mutant lines where a greater number of eggs accumulates. Likewise, analysis of TIRK-gain and -loss-of-function lines demonstrate the defence role of this receptor in Arabidopsis against T. urticae. Altogether, our findings demonstrate the interaction between TRXh5 and TIRK and highlight the importance of TRXh5 and TIRK in the establishment of effective Arabidopsis defences against spider mite herbivory.Grants PID2020-115219RB-I00, RED2018-102397-T and RyC17MESFB funded by MCIN/AEI/10.13039/501100011033, as appropriate, by “ERDF A way of making Europe” and by the “European Union” supported this work. Grants, SIMQG-263-1HWZ8Q UPM-Banco Santander Universidades, RyC2017-21814 and PRE2018-083375 from MCIN/AEI supported AA, MES and IRD, respectively. The Spanish Ministry of Science and Innovation (MCIN), the State Research Agency (AEI) and the European Regional Development Fund (ERDF; grant MEC-PID2021-122280NB-I00) financed MCRP and LMS. The Government of Canada through the Ontario Research Fund (RE08-067) and the Natural Sciences and Engineering Research Council of Canada (NSERC, RGPIB-2018-04538) supported VG

Role of age and comorbidities in mortality of patients with infective endocarditis

[Purpose]: The aim of this study was to analyse the characteristics of patients with IE in three groups of age and to assess the ability of age and the Charlson Comorbidity Index (CCI) to predict mortality. [Methods]: Prospective cohort study of all patients with IE included in the GAMES Spanish database between 2008 and 2015.Patients were stratified into three age groups:<65 years,65 to 80 years,and ≥ 80 years.The area under the receiver-operating characteristic (AUROC) curve was calculated to quantify the diagnostic accuracy of the CCI to predict mortality risk. [Results]: A total of 3120 patients with IE (1327 < 65 years;1291 65-80 years;502 ≥ 80 years) were enrolled.Fever and heart failure were the most common presentations of IE, with no differences among age groups.Patients ≥80 years who underwent surgery were significantly lower compared with other age groups (14.3%,65 years; 20.5%,65-79 years; 31.3%,≥80 years). In-hospital mortality was lower in the <65-year group (20.3%,<65 years;30.1%,65-79 years;34.7%,≥80 years;p < 0.001) as well as 1-year mortality (3.2%, <65 years; 5.5%, 65-80 years;7.6%,≥80 years; p = 0.003).Independent predictors of mortality were age ≥ 80 years (hazard ratio [HR]:2.78;95% confidence interval [CI]:2.32–3.34), CCI ≥ 3 (HR:1.62; 95% CI:1.39–1.88),and non-performed surgery (HR:1.64;95% CI:11.16–1.58).When the three age groups were compared,the AUROC curve for CCI was significantly larger for patients aged <65 years(p < 0.001) for both in-hospital and 1-year mortality. [Conclusion]: There were no differences in the clinical presentation of IE between the groups. Age ≥ 80 years, high comorbidity (measured by CCI),and non-performance of surgery were independent predictors of mortality in patients with IE.CCI could help to identify those patients with IE and surgical indication who present a lower risk of in-hospital and 1-year mortality after surgery, especially in the <65-year group

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

Safety and efficacy of prolonged use of dalbavancin in bone and joint infections

Dalbavancin is a lipoglycopeptide with potent activity against Gram-positive microorganisms, a long half-life, a favorable safety profile, and a high concentration in bone, which makes it an interesting alternative for treatment of osteoarticular infections. We performed a multicentric retrospective study of all patients with an osteoarticular infection (septic arthritis, spondylodiscitis, osteomyelitis, or orthopedic implant-related infection) treated with at least one dose of dalbavancin between 2016 and 2017 in 30 institutions in Spain. In order to evaluate the response, patients with or without an orthopedic implant were separated. A total of 64 patients were included. Staphylococcus epidermidis and Staphylococcus aureus were the most frequent microorganisms. The reasons for switching to dalbavancin were simplification (53.1%), adverse events (25%), or failure (21.9%). There were 7 adverse events, and no patient had to discontinue dalbavancin. In 45 cases, infection was related to an orthopedic implant. The implant material was retained in 23 cases, including that in 15 (65.2%) patients that were classified as cured and 8 (34.8%) that presented improvement. In 21 cases, the implants were removed, including those in 16 (76.2%) cases that were considered successes, 4 (19%) cases were considered improved, and 1 (4.8%) case that was considered a failure. Among the 19 cases without implants, 14 (73.7%) were considered cured, 3 (15.8%) were considered improved, and 2 (10.5%) were considered failures. The results show that dalbavancin is a well-tolerated antibiotic, even when 2 doses are administered, and is associated with a high cure rate. These are preliminary data with a short follow-up; therefore, it is necessary to gain more experience and, in the future, to establish the most appropriate dose and frequency.This study was supported by the Bone and Joint Infection Study Group (SGR 253) of the Agència de Gestió d’Ajuts Universitaris I de Recerca (AGAUR) and by the Red Española de Investigación en Patología Infecciosa (REIPI). L. Morata is the recipient of a Rio-Hortega grant (CM 15/00129) from the Instituto de Salud Carlos III

Prosthetic Valve Candida spp. Endocarditis: New Insights into Long-term Prognosis-The ESCAPE Study

Background. Prosthetic valve endocarditis caused by Candida spp. (PVE-C) is rare and devastating, with international guidelines based on expert recommendations supporting the combination of surgery and subsequent azole treatment. Methods. We retrospectively analyzed PVE-C cases collected in Spain and France between 2001 and 2015, with a focus on management and outcome. Results. Forty-six cases were followed up for a median of 9 months. Twenty-two patients (48%) had a history of endocarditis, 30 cases (65%) were nosocomial or healthcare related, and 9 (20%) patients were intravenous drug users. "Induction" therapy consisted mainly of liposomal amphotericin B (L-amB)-based (n = 21) or echinocandin-based therapy (n = 13). Overall, 19 patients (41%) were operated on. Patients &lt;66 years old and without cardiac failure were more likely to undergo cardiac surgery (adjusted odds ratios [aORs], 6.80 [95% confdence interval [CI], 1.59-29.13] and 10.92 [1.15-104.06], respectively). Surgery was not associated with better survival rates at 6 months. Patients who received L-amB alone had a better 6-month survival rate than those who received an echinocandin alone (aOR, 13.52; 95% CI, 1.03-838.10). "Maintenance" fluconazole therapy, prescribed in 21 patients for a median duration of 13 months (range, 2-84 months), led to minor adverse effects. Conclusion. L-amB induction treatment improves survival in patients with PVE-C. Medical treatment followed by long-term maintenance fluconazole may be the best treatment option for frail patients

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)