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      Greater risk of severe COVID-19 in Black, Asian and Minority Ethnic populations is not explained by cardiometabolic, socioeconomic or behavioural factors, or by 25(OH)-vitamin D status: study of 1326 cases from the UK Biobank

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          Abstract

          Background

          We examined whether the greater severity of coronavirus disease 2019 (COVID-19) amongst men and Black, Asian and Minority Ethnic (BAME) individuals is explained by cardiometabolic, socio-economic or behavioural factors.

          Methods

          We studied 4510 UK Biobank participants tested for COVID-19 (positive, n = 1326). Multivariate logistic regression models including age, sex and ethnicity were used to test whether addition of (1) cardiometabolic factors [diabetes, hypertension, high cholesterol, prior myocardial infarction, smoking and body mass index (BMI)]; (2) 25(OH)-vitamin D; (3) poor diet; (4) Townsend deprivation score; (5) housing (home type, overcrowding) or (6) behavioural factors (sociability, risk taking) attenuated sex/ethnicity associations with COVID-19 status.

          Results

          There was over-representation of men and BAME ethnicities in the COVID-19 positive group. BAME individuals had, on average, poorer cardiometabolic profile, lower 25(OH)-vitamin D, greater material deprivation, and were more likely to live in larger households and in flats/apartments. Male sex, BAME ethnicity, higher BMI, higher Townsend deprivation score and household overcrowding were independently associated with significantly greater odds of COVID-19. The pattern of association was consistent for men and women; cardiometabolic, socio-demographic and behavioural factors did not attenuate sex/ethnicity associations.

          Conclusions

          In this study, sex and ethnicity differential pattern of COVID-19 was not adequately explained by variations in cardiometabolic factors, 25(OH)-vitamin D levels or socio-economic factors. Factors which underlie ethnic differences in COVID-19 may not be easily captured, and so investigation of alternative biological and genetic susceptibilities as well as more comprehensive assessment of the complex economic, social and behavioural differences should be prioritised.

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          Most cited references17

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          COVID-19: the gendered impacts of the outbreak

          Policies and public health efforts have not addressed the gendered impacts of disease outbreaks. 1 The response to coronavirus disease 2019 (COVID-19) appears no different. We are not aware of any gender analysis of the outbreak by global health institutions or governments in affected countries or in preparedness phases. Recognising the extent to which disease outbreaks affect women and men differently is a fundamental step to understanding the primary and secondary effects of a health emergency on different individuals and communities, and for creating effective, equitable policies and interventions. Although sex-disaggregated data for COVID-19 show equal numbers of cases between men and women so far, there seem to be sex differences in mortality and vulnerability to the disease. 2 Emerging evidence suggests that more men than women are dying, potentially due to sex-based immunological 3 or gendered differences, such as patterns and prevalence of smoking. 4 However, current sex-disaggregated data are incomplete, cautioning against early assumptions. Simultaneously, data from the State Council Information Office in China suggest that more than 90% of health-care workers in Hubei province are women, emphasising the gendered nature of the health workforce and the risk that predominantly female health workers incur. 5 The closure of schools to control COVID-19 transmission in China, Hong Kong, Italy, South Korea, and beyond might have a differential effect on women, who provide most of the informal care within families, with the consequence of limiting their work and economic opportunities. Travel restrictions cause financial challenges and uncertainty for mostly female foreign domestic workers, many of whom travel in southeast Asia between the Philippines, Indonesia, Hong Kong, and Singapore. 6 Consideration is further needed of the gendered implications of quarantine, such as whether women and men's different physical, cultural, security, and sanitary needs are recognised. Experience from past outbreaks shows the importance of incorporating a gender analysis into preparedness and response efforts to improve the effectiveness of health interventions and promote gender and health equity goals. During the 2014–16 west African outbreak of Ebola virus disease, gendered norms meant that women were more likely to be infected by the virus, given their predominant roles as caregivers within families and as front-line health-care workers. 7 Women were less likely than men to have power in decision making around the outbreak, and their needs were largely unmet. 8 For example, resources for reproductive and sexual health were diverted to the emergency response, contributing to a rise in maternal mortality in a region with one of the highest rates in the world. 9 During the Zika virus outbreak, differences in power between men and women meant that women did not have autonomy over their sexual and reproductive lives, 10 which was compounded by their inadequate access to health care and insufficient financial resources to travel to hospitals for check-ups for their children, despite women doing most of the community vector control activities. 11 Given their front-line interaction with communities, it is concerning that women have not been fully incorporated into global health security surveillance, detection, and prevention mechanisms. Women's socially prescribed care roles typically place them in a prime position to identify trends at the local level that might signal the start of an outbreak and thus improve global health security. Although women should not be further burdened, particularly considering much of their labour during health crises goes underpaid or unpaid, incorporating women's voices and knowledge could be empowering and improve outbreak preparedness and response. Despite the WHO Executive Board recognising the need to include women in decision making for outbreak preparedness and response, 12 there is inadequate women's representation in national and global COVID-19 policy spaces, such as in the White House Coronavirus Task Force. 13 © 2020 Miguel Medina/Contributor/Getty Images 2020 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. If the response to disease outbreaks such as COVID-19 is to be effective and not reproduce or perpetuate gender and health inequities, it is important that gender norms, roles, and relations that influence women's and men's differential vulnerability to infection, exposure to pathogens, and treatment received, as well as how these may differ among different groups of women and men, are considered and addressed. We call on governments and global health institutions to consider the sex and gender effects of the COVID-19 outbreak, both direct and indirect, and conduct an analysis of the gendered impacts of the multiple outbreaks, incorporating the voices of women on the front line of the response to COVID-19 and of those most affected by the disease within preparedness and response policies or practices going forward.
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            Comparative genetic analysis of the novel coronavirus (2019-nCoV/SARS-CoV-2) receptor ACE2 in different populations

            Dear Editor, The ACE2 gene encodes the angiotensin-converting enzyme-2, which has been proved to be the receptor for both the SARS-coronavirus (SARS-CoV) and the human respiratory coronavirus NL63. Recent studies and analyses indicate that ACE2 could be the host receptor for the novel coronavirus 2019-nCoV/SARS-CoV-2 1,2 . Previous studies demonstrated the positive correlation of ACE2 expression and the infection of SARS-CoV in vitro 3,4 . A number of ACE2 variants could reduce the association between ACE2 and S-protein in SARS-CoV or NL63 5 . Therefore, the expression level and expression pattern of human ACE2 in different tissues might be critical for the susceptibility, symptoms, and outcome of 2019-nCoV/SARS-CoV-2 infection. A recent single-cell RNA-sequencing (RNA-seq) analysis indicated that Asian males may have higher expression of ACE2 6 . Currently, the clinical reports of 2019-nCoV/SARS-CoV-2 infection from non-Asian populations for comparison are very limited. A study from Munich reported four German cases, all of which showed mild clinical symptoms without severe illness 7 . However, the genetic basis of ACE2 expression and function in different populations is still largely unknown. Therefore, genetic analysis of expression quantitative trait loci (eQTLs) 8 and potential functional coding variants in ACE2 among populations are required for further epidemiological investigations of 2019-nCoV/SARS-CoV-2 spreading in East Asian (EAS) and other populations. To systematically investigate the candidate functional coding variants in ACE2 and the allele frequency (AF) differences between populations, we analyzed all the 1700 variants (Supplementary Table S1) in ACE2 gene region from the ChinaMAP (China Metabolic Analytics Project, under reviewing) and 1KGP (1000 Genomes Project) 9 databases. The AFs of 62 variants located in the coding regions of ACE2 in ChinaMAP, 1KGP, and other large-scale genome databases were summarized (Supplementary Table S2). All of the 32 variants potentially affecting the amino acid sequence of ACE2 in databases were shown (Fig. 1a). Previous study showed that the residues near lysine 31, and tyrosine 41, 82–84, and 353–357 in human ACE2 were important for the binding of S-protein in coronavirus 5 . The mutations in these residues were not found in different populations in our study. Only a singleton truncating variant of ACE2 (Gln300X) was identified in the ChinaMAP (Fig. 1a). These data suggested that there was a lack of natural resistant mutations for coronavirus S-protein binding in populations. The effects of low-frequency missense variants in populations for S-protein binding could be further investigated. The distributions of seven hotspot variants (Lys26Arg, Ile468Val, Ala627Val, Asn638Ser, Ser692Pro, Asn720Asp, and Leu731Ile/Leu731Phe) in different populations were shown (Fig. 1b). Six low-frequency loci (rs200180615, rs140473595, rs199951323, rs147311723, rs149039346, and rs73635825) were found to be specific in 1KGP database, the AFs of which were also low in the gnomAD and TopMed 10 database. Only two of these six variants (rs200180615 and rs140473595) could be found in CHB (Han Chinese in Beijing) population with the AF   0.05) and 1 rare variant (rs143695310) in the 15 eQTLs are associated with high expression of ACE2 in tissues (Supplementary Table S3). For instance, the eQTL variant rs4646127 (log allelic fold change = 0.314), which locates in the intron of ACE2 gene, has the highest AFs in both of the ChinaMAP (0.997) and EAS (0.994) populations. Comparatively, the AFs of rs4646127 in EUR (0.651) and AMR (0.754) populations are much lower. These findings suggested the genotypes of ACE2 gene polymorphism may be associated higher expression levels of ACE2 in EAS population. Recent reports of the ACE2 expression analysis in lung tissues from Asian and Caucasian populations are still controversial. The single-cell RNA-seq analysis reported that the Asian donor had much higher ACE2 expression cell ratio than white and African-American donors 6 . In contrast, the ACE2 expression analysis using the RNA-seq and microarray datasets from control lung tissues indicated there were no significant differences between Asian and Caucasian, or male and female 11 . The ACE2-expressing cells are a very small part of cells in lung tissues 6 . The sample size and the purity of ACE2-positive cells in the selected samples would influence the conclusions. Our analysis showed the differences in distribution and AFs of eQTLs for ACE2 in different populations, indicating the diversity of ACE2 expression pattern in populations (Supplementary Table S3). Large-scale and multiple tissue-level analysis of single-cell RNA-seq would be more accurate for the expression analysis of ACE2 in different populations. In addition, our data showed the moderate difference in AFs of eQTLs between South Asian and EAS, which suggests the potential difference of ACE2 expression in different populations and ethnics in Asia (Fig. 1c). In summary, we systematically analyzed coding-region variants in ACE2 and the eQTL variants, which may affect the expression of ACE2 using the GTEx database to compare the genomic characteristics of ACE2 among different populations. Our findings indicated that no direct evidence was identified genetically supporting the existence of coronavirus S-protein binding-resistant ACE2 mutants in different populations (Fig. 1a). The data of variant distribution and AFs may contribute to the further investigations of ACE2, including its roles in acute lung injury and lung function 12 . The East Asian populations have much higher AFs in the eQTL variants associated with higher ACE2 expression in tissues (Fig. 1c), which may suggest different susceptibility or response to 2019-nCoV/SARS-CoV-2 from different populations under the similar conditions. Supplementary information Supplementary Table S1 Supplementary Table S2 Supplementary Table S3
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              Variation in COVID-19 Hospitalizations and Deaths Across New York City Boroughs

              This study describes demographic characteristics and hospital bed capacities of the 5 New York City boroughs, and evaluates whether differences in testing for coronavirus disease 2019 (COVID-19), hospitalizations, and deaths have emerged as a signal of racial, ethnic, and financial disparities.
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                Author and article information

                Journal
                J Public Health (Oxf)
                J Public Health (Oxf)
                pubmed
                Journal of Public Health (Oxford, England)
                Oxford University Press
                1741-3842
                1741-3850
                19 June 2020
                : fdaa095
                Affiliations
                [1 ] William Harvey Research Institute , NIHR Barts Biomedical Research Centre, Queen Mary University of London , London, UK
                [2 ] Barts Heart Centre , St Bartholomew’s Hospital, Barts Health NHS Trust , London, UK
                [3 ] North West Anglia NHS Foundation Trust , Hinchingbrooke Hospital , Huntingdon, UK
                [4 ] MRC Lifecourse Epidemiology Unit , University of Southampton , Southampton, UK
                [5 ] NIHR Southampton Biomedical Research Centre , University of Southampton and University Hospital Southampton NHS Foundation Trust , Southampton, UK
                [6 ] NIHR Biomedical Research Centre , University of Oxford , Oxford, UK
                Author notes
                Address correspondence to Zahra Raisi-Estabragh, E-mail: zahraraisi@ 123456doctors.org.uk .
                Author information
                http://orcid.org/0000-0002-7757-5465
                http://orcid.org/0000-0002-8194-2512
                Article
                fdaa095
                10.1093/pubmed/fdaa095
                7449237
                32556213
                e5d08c91-12a5-42bb-ad76-4b531bdc6b0b
                © The Author(s) 2020. Published by Oxford University Press on behalf of Faculty of Public Health.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 1 June 2020
                : 3 June 2020
                : 3 June 2020
                Page count
                Pages: 10
                Funding
                Funded by: British Heart Foundation Clinical Research Training Fellowship;
                Award ID: FS/17/81/33318
                Funded by: National Institute for Health Research, DOI 10.13039/501100000272;
                Categories
                AcademicSubjects/MED00860
                Original Article
                Custom metadata
                PAP

                Public health
                communicable diseases,epidemiology,public health
                Public health
                communicable diseases, epidemiology, public health

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