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      Shared genetic etiology between idiopathic pulmonary fibrosis and COVID-19 severity

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          Abstract

          Background

          Idiopathic pulmonary fibrosis (IPF) is a complex lung disease, characterized by progressive lung scarring. Severe COVID-19 is associated with substantial pneumonitis and has a number of shared major risk factors with IPF. This study aimed to determine the genetic correlation between IPF and severe COVID-19 and assess a potential causal role of genetically increased risk of IPF on COVID-19 severity.

          Methods

          The genetic correlation between IPF and COVID-19 severity was estimated with linkage disequilibrium (LD) score regression. We performed a Mendelian randomization (MR) study for IPF causality in COVID-19. Genetic variants associated with IPF susceptibility ( P<5 × 10 −8) in previous genome-wide association studies (GWAS) were used as instrumental variables (IVs). Effect estimates of those IVs on COVID-19 severity were gathered from the GWAS meta-analysis by the COVID-19 Host Genetics Initiative (4,336 cases & 623,902 controls).

          Findings

          We detected a positive genetic correlation of IPF with COVID-19 severity (rg=0·31 [95% CI 0·04–0·57], P = 0·023). The MR estimates for severe COVID-19 did not reveal any genetic association (OR 1·05, [95% CI 0·92–1·20], P = 0·43). However, outlier analysis revealed that the IPF risk allele rs35705950 at MUC5B had a different effect compared with the other variants. When rs35705950 was excluded, MR results provided evidence that genetically increased risk of IPF has a causal effect on COVID-19 severity (OR 1·21, [95% CI 1·06–1·38], P = 4·24 × 10 −3). Furthermore, the IPF risk-allele at MUC5B showed an apparent protective effect against COVID-19 hospitalization only in older adults (OR 0·86, [95% CI 0·73–1·00], P = 2·99 × 10 −2) .

          Interpretation

          The strongest genetic determinant of IPF, rs35705950 at MUC5B, seems to confer protection against COVID-19, whereas the combined effect of all other IPF risk loci seem to confer risk of COVID-19 severity. The observed effect of rs35705950 could either be due to protective effects of mucin over-production on the airways or a consequence of selection bias due to (1) a patient group that is heavily enriched for the rs35705950 T undertaking strict self-isolation and/or (2) due to survival bias of the rs35705950 non-IPF risk allele carriers. Due to the diverse impact of IPF causal variants on SARS-CoV-2 infection, with a possible selection bias as an explanation, further investigation is needed to address this apparent paradox between variance at MUC5B and other IPF genetic risk factors.

          Funding

          Novo Nordisk Foundation and Oak Foundation.

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          Most cited references42

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          OpenSAFELY: factors associated with COVID-19 death in 17 million patients

          COVID-19 has rapidly impacted on mortality worldwide. 1 There is unprecedented urgency to understand who is most at risk of severe outcomes, requiring new approaches for timely analysis of large datasets. Working on behalf of NHS England we created OpenSAFELY: a secure health analytics platform covering 40% of all patients in England, holding patient data within the existing data centre of a major primary care electronic health records vendor. Primary care records of 17,278,392 adults were pseudonymously linked to 10,926 COVID-19 related deaths. COVID-19 related death was associated with: being male (hazard ratio 1.59, 95%CI 1.53-1.65); older age and deprivation (both with a strong gradient); diabetes; severe asthma; and various other medical conditions. Compared to people with white ethnicity, black and South Asian people were at higher risk even after adjustment for other factors (HR 1.48, 1.29-1.69 and 1.45, 1.32-1.58 respectively). We have quantified a range of clinical risk factors for COVID-19 related death in the largest cohort study conducted by any country to date. OpenSAFELY is rapidly adding further patients’ records; we will update and extend results regularly.
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            Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression

            Background: The number of Mendelian randomization analyses including large numbers of genetic variants is rapidly increasing. This is due to the proliferation of genome-wide association studies, and the desire to obtain more precise estimates of causal effects. However, some genetic variants may not be valid instrumental variables, in particular due to them having more than one proximal phenotypic correlate (pleiotropy). Methods: We view Mendelian randomization with multiple instruments as a meta-analysis, and show that bias caused by pleiotropy can be regarded as analogous to small study bias. Causal estimates using each instrument can be displayed visually by a funnel plot to assess potential asymmetry. Egger regression, a tool to detect small study bias in meta-analysis, can be adapted to test for bias from pleiotropy, and the slope coefficient from Egger regression provides an estimate of the causal effect. Under the assumption that the association of each genetic variant with the exposure is independent of the pleiotropic effect of the variant (not via the exposure), Egger’s test gives a valid test of the null causal hypothesis and a consistent causal effect estimate even when all the genetic variants are invalid instrumental variables. Results: We illustrate the use of this approach by re-analysing two published Mendelian randomization studies of the causal effect of height on lung function, and the causal effect of blood pressure on coronary artery disease risk. The conservative nature of this approach is illustrated with these examples. Conclusions: An adaption of Egger regression (which we call MR-Egger) can detect some violations of the standard instrumental variable assumptions, and provide an effect estimate which is not subject to these violations. The approach provides a sensitivity analysis for the robustness of the findings from a Mendelian randomization investigation.
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              Pathophysiology, Transmission, Diagnosis, and Treatment of Coronavirus Disease 2019 (COVID-19): A Review

              The coronavirus disease 2019 (COVID-19) pandemic, due to the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a worldwide sudden and substantial increase in hospitalizations for pneumonia with multiorgan disease. This review discusses current evidence regarding the pathophysiology, transmission, diagnosis, and management of COVID-19.
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                Author and article information

                Journal
                EBioMedicine
                EBioMedicine
                EBioMedicine
                The Author(s). Published by Elsevier B.V.
                2352-3964
                10 March 2021
                March 2021
                10 March 2021
                : 65
                : 103277
                Affiliations
                [a ]Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
                [b ]Department of Clinical Sciences, Lund University Diabetes Centre, Malmö, Sweden
                [c ]Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
                [d ]Department of Health Sciences, University of Leicester, Leicester, United Kingdom
                [e ]Massachusetts General Hospital, Boston, MA, United States
                [f ]Broad Institute of Harvard and MIT, Cambridge, MA, United States
                [g ]Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States
                [h ]Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom
                [i ]Intensive Care Unit, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom
                [j ]NIHR, Leicester Respiratory, Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
                [k ]Nottingham University Hospitals NHS Trust, City Campus, Nottingham, United Kingdom
                [l ]NIHR Biomedical Research Centre, University of Nottingham, Nottingham, United Kingdom
                Author notes
                [* ]Corresponding author at: Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark.
                Article
                S2352-3964(21)00070-0 103277
                10.1016/j.ebiom.2021.103277
                7946355
                33714028
                bd2826f4-4efb-46c8-99f4-ebbb084fe729
                © 2021 The Author(s)

                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.

                History
                : 18 December 2020
                : 23 February 2021
                : 23 February 2021
                Categories
                Research Paper

                mendelian randomization,covid-19,idiopathic pulmonary fibrosis,muc5b,mucin

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