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

Designing a new scale to measure anxiety symptoms in Parkinson's disease: item selection based on canonical correlation analysis

Background and purpose: The lack of appropriate measures has hindered the research on anxiety syndromes in Parkinson's disease (PD). The objective of the present cross-sectional, international study was to identify shared elements and grouping of components from anxiety scales as a basis for designing a new scale for use in PD. Methods: For this purpose, 342 consecutive PD patients were assessed by means of the Mini International Neuropsychiatric Inventory (depression and anxiety sections), the Clinical Global Impression of severity of the anxiety symptoms, the Hamilton Anxiety Rating Scale (HARS), the Neuropsychiatric Inventory (section E), the Beck Anxiety Inventory (BAI) and the Anxiety subscale of the Hospital Anxiety and Depression Scale (HADS-A). Results: As the HADS-A showed a weak correlation with the HARS and BAI, it was not considered for more analyses. HARS and BAI exploratory factor analysis identified nine factors (62% of the variance), with only two of them combining items from both scales. Therefore, a canonical correlation model (a method to identify relations between components of two groups of variables) was built and it showed four factors grouping items from both scales: the first factor corresponded to 'generalized anxiety'; the second factor included muscular, sensory and autonomic 'non-specific somatic symptoms'; the third factor was dominated by 'respiratory symptoms'; and the fourth factor included 'cardiovascular symptoms'. Conclusions: BAI is heavily focused on panic symptoms, whilst HARS is more focused towards generalized anxiety symptoms. The new scale should include additional components in order to assess both episodic and persistent anxiety as well as items for evaluation of avoidance behaviour

Gender-related differences in the burden of non-motor symptoms in Parkinson's disease

Differences in the expression of non-motor symptoms (NMS) by Parkinson's disease (PD) patients may have important implications for their management and prognosis. Gender is a basic epidemiological variable that could influence such expression. the present study evaluated the prevalence and severity of NMS by gender in an international sample of 951 PD patients, 62.63% males, using the non-motor symptoms scale (NMSS). Assessments for motor impairment and complications, global severity, and health state were also applied. All disease stages were included. No significant gender differences were found for demographic and clinical characteristics. for the entire sample, the most prevalent symptoms were Nocturia (64.88%) and Fatigue (62.78%) and the most prevalent affected domains were Sleep/Fatigue (84.02%) and Miscellaneous (82.44%). Fatigue, feelings of nervousness, feelings of sadness, constipation, restless legs, and pain were more common and severe in women. On the contrary, daytime sleepiness, dribbling saliva, interest in sex, and problems having sex were more prevalent and severe in men. Regarding the NMSS domains, Mood/Apathy and Miscellaneous problems (pain, loss of taste or smell, weight change, and excessive sweating) were predominantly affected in women and Sexual dysfunction in men. No other significant differences by gender were observed. To conclude, in this study significant differences between men and women in prevalence and severity of fatigue, mood, sexual and digestive problems, pain, restless legs, and daytime sleepiness were found. Gender-related patterns of NMS involvement may be relevant for clinical trials in PD.Reina Sofia Fdn, Alzheimer Ctr, Res Unit, Madrid 28031, SpainCIBERNED Carlos III Inst Hlth, Madrid 28031, SpainTransylvania Univ, Dept Neurol, Emergency Univ Hosp, Fac Med, Brasov, RomaniaUniv Lund Hosp, Dept Neurol, S-22185 Lund, SwedenCent Hosp, Dept Neurol, Bremerhaven, GermanyLeiden Univ, Dept Neurol, Med Ctr, Leiden, NetherlandsIRCCS San Camillo, Dept Parkinsons Dis, Venice, ItalySpanish Council Sci Res, Stat Anal Unit, Ctr Human & Social Sci, Madrid, SpainUniversidade Federal de São Paulo, Dept Neurol, Movement Disorders Sect, São Paulo, BrazilParacelsus Elena Hosp, Ctr Parkinsonism & Movement Disorders, Kassel, GermanyKarolinska Inst, Stockholm, SwedenStavanger Univ Hosp, Dept Psychiat, Stavanger, NorwayUniv London Imperial Coll Sci Technol & Med, Dept Med, London, EnglandKings Coll Hosp, Natl Parkinson Fdn, Ctr Excellence, London, EnglandUniv Hosp Lewisham, London, EnglandUniversidade Federal de São Paulo, Dept Neurol, Movement Disorders Sect, São Paulo, BrazilWeb of Scienc

Assessing the non-motor symptoms of Parkinson's disease:MDS-UPDRS and NMS Scale

Background and purpose Although Parkinson's disease (PD) is characterized by typical motor manifestations, non‐motor symptoms (NMS) are an outstanding part of the disease. At present, several specific instruments for assessment of NMS are available. The objective of our study was to determine the performance of the Movement Disorder Society‐Unified Parkinson's Disease Rating Scale (MDS‐UPDRS): Part I – Non‐Motor Aspects of Experiences of Daily Living (nM‐EDL) compared with the Non‐Motor Symptoms Scale (NMSS). Methods To this purpose, 434 consecutive patients with PD were included in an international, observational, cross‐sectional study. The association between scores of both scales was determined by the Spearman rank correlation coefficient. Equations for transformation of total score of a scale to the other were constructed from weighted regression models and both, transformed and observed score, contrasted by means of the Lin's Concordance Correlation Coefficient (LCCC) and Bland–Altman plot. Results As a whole, the prevalence of the NMS according to each scale was quite similar, and most of the correlations between their corresponding components were high (rS > 0.60). The total score correlation of the MDS‐UPDRS Part I with the NMSS was high (rS = 0.81). Concerning the transformed scores, estimated scores only partially approach the observed ones (sharing about 60–64% of the variance) because residual variance increased with increasing magnitudes of the scores, i.e. the most severe patients (Bland–Altman plot; LCCC < 0.60 for severe patients). Conclusions (i) MDS‐UPDRS Part I (nM‐EDL) and NMSS showed a strong convergent validity; (ii) however, transformed scores using the equations from weighted regression models showed that for patients with the most severe NMS they are not concordant. Click here to view the accompanying paper in this issue

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)