key: cord-0718185-povbymcm
authors: Luo, Shan; Liang, Ying; Wong, Tommy Hon Ting; Schooling, Catherine Mary; Au Yeung, Shiu Lun
title: Identifying factors contributing to increased susceptibility to COVID-19 risk: a systematic review of Mendelian randomization studies
date: 2022-04-20
journal: Int J Epidemiol
DOI: 10.1093/ije/dyac076
sha: c9a3226f7047e36ab729ed8b3f81e0c538a36b04
doc_id: 718185
cord_uid: povbymcm

BACKGROUND: To summarize modifiable factors for coronavirus disease 2019 (COVID-19) suggested by Mendelian randomization studies. METHODS: In this systematic review, we searched PubMed, EMBASE and MEDLINE, from inception to 15 November 2021, for Mendelian randomization studies in English. We selected studies that assessed associations of genetically predicted exposures with COVID-19-related outcomes (severity, hospitalization and susceptibility). Risk of bias of the included studies was evaluated based on the consideration of the three main assumptions for instrumental variable analyses. RESULTS: We identified 700 studies through systematic search, of which 50 Mendelian randomization studies were included. Included studies have explored a wide range of socio-demographic factors, lifestyle attributes, anthropometrics and biomarkers, predisposition to diseases and druggable targets in COVID-19 risk. Mendelian randomization studies suggested that increases in smoking, obesity and inflammatory factors were associated with higher risk of COVID-19. Predisposition to ischaemic stroke, combined bipolar disorder and schizophrenia, attention-deficit and hyperactivity disorder, chronic kidney disease and idiopathic pulmonary fibrosis was potentially associated with higher COVID-19 risk. Druggable targets, such as higher protein expression of histo-blood group ABO system transferase (ABO), interleukin (IL)-6 and lower protein expression of 2′-5′ oligoadenylate synthetase 1 (OAS1) were associated with higher risk of COVID-19. There was no strong genetic evidence supporting the role of vitamin D, glycaemic traits and predisposition to cardiometabolic diseases in COVID-19 risk. CONCLUSION: This review summarizes modifiable factors for intervention (e.g. smoking, obesity and inflammatory factors) and proteomic signatures (e.g. OAS1 and IL-6) that could help identify drugs for treating COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic is a major global health threat. As of 1 December 2021, the number of cases exceeded 261 million and led to 5.2 million deaths. 1 COVID-19-related research has increased exponentially, although concerns over quality exist, 2 including retraction of studies using questionable data sources. 3 Paradoxical protective effects, such as smoking reducing the risk of COVID-19-related deaths, 4 could arise from selection bias in an observational setting. 5 Given the uncertainty of findings from a single study, in particular observational studies, systematic reviews are increasingly used to consolidate the evidence base for prevention and treatment of COVID-19. 6, 7 Identifying causes of increased susceptibility, hospitalization and severity to COVID-19 based on less biased epidemiologic designs is important to inform prevention and treatment strategies. Mendelian randomization, a study design less susceptible to confounding than conventional observational studies, can help identify causes and possible therapeutic targets. 8 For example, a Mendelian randomization study showed genetic inhibition of the interleukin (IL)-6 receptor may protect against severe COVID-19, 9 consistently with subsequent randomized-controlled trials (RCTs). 6 However, to date, there is no systematic review of Mendelian randomization studies concerning COVID-19 and hence possible targets of intervention/drug reposition opportunities have not been systematically evaluated. This is particularly important as herd immunity is challenging to achieve in view of newly emerging variants, 10 vaccine hesitancy 11 and vaccine inequity. 12 We conducted this systematic review to evaluate possible factors (e.g. socio-demographic factors, lifestyle attributes, anthropometrics, biomarkers, predisposition to diseases and druggable targets) contributing to the risk of COVID-19 from Mendelian randomization studies.

We conducted this systematic review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. 13 The protocol of the systematic review was registered at the International Prospective Register of Systematic Reviews (PROSPERO) on 30 April 2021 (CRD42021252079).

We included Mendelian randomization studies that assessed the associations of genetically predicted exposures with COVID-19-related outcomes. COVID-19 outcomes included the severity, hospitalization and susceptibility of COVID-19. Two reviewers (Y.L. and T.H.T.W.) independently searched published studies in PubMed, EMBASE and MEDLINE from inception to 15 November 2021. We used a pre-defined search strategy, with key search terms ('Mendelian randomization' OR 'Mendelian randomisation') AND ('COVID19' OR 'coronavirus disease 2019') AND ('genome-wide association study' OR 'GWAS'). We restricted the language to English and human studies using PubMed filters. We also manually searched the reference lists of the retrieved studies to identify additional studies. Detailed search term combinations for each database can be found in the Supplementary material (available as Supplementary data at IJE online).

We excluded studies that (i) were duplicated across databases; (ii) were without sufficient original data (e.g. reviews, commentaries, corrections and abstracts); (iii) were not Mendelian randomization studies, including studies that only reported variant-outcome associations [i.e. a reduced form of instrumental variable (IV) analysis]; or (iv) did not include COVID-19 phenotypes as the outcomes. Two reviewers (Y.L. and T.H.T.W.) independently screened the titles, abstracts and full text if necessary of all retrieved studies, and compared and resolved any possible discrepancies. A third reviewer (S.L.) was consulted if the discrepancies were not resolved. The study selection process was summarized in a PRISMA flowchart.

For each included Mendelian randomization study, one reviewer (Y.L.) extracted key information using a tailored template based on the PRISMA checklist 13 and the guidelines for strengthening the reporting of observational studies in epidemiology using Mendelian randomization (STROBE-MR). 14 These included the name of the first author, the year of publication, the type of Mendelian randomization study (one-sample or two-sample), the number of genetic variants, the data source(s) and ancestry for the genetic variants and outcomes, the sample size of the outcome, the effect estimate for exposure on outcome and the corresponding 95% CI. For a one-sample Mendelian randomization study, both one-sample methods (e.g. twostage least square and a genetic risk score) and two-sample methods (e.g. a meta-analysis of Wald estimates, i.e. inverse variance weighted) were considered as the main analysis. 15 For a two-sample Mendelian randomization study, inverse variance weighted was normally considered as the main analysis. 15 By default, we extracted the effect estimates with 95% CI from the main analysis reported in the main text. In addition, for associations reaching statistical significance (nominal P-value < 0.05, or P-value after correcting for multiple testing, if mentioned in the original studies), we additionally extracted the results from the sensitivity analyses (e.g. different sets of genetic variants or statistical methods). The extracted data were verified by another reviewer (S.L.).

There is no quality assessment tool available for systematic reviews of Mendelian randomization studies. Mendelian randomization studies rely on three main IV assumptions for a valid causal inference. 16 Specifically, the genetic variant is strongly associated with the exposure (IV1: relevance), independent of the (measured and unmeasured) confounding factors of the exposure-outcome association (IV2: independence) and has no effect on the outcome except via the exposure (IV3: exclusion-restriction). 16 Reviewers (S.L., Y.L. and S.L.A.Y.) independently evaluated whether the included Mendelian randomization studies assessed the validity of each IV assumption adequately. Any inconsistencies were resolved by discussion until a consensus was reached.

For the relevance assumption, we checked the strength of the instruments such as P-values of the variant-exposure association (usually genome-wide significant, P-value < 5 Â 10 -8 ), instrument strength (F-statistic > 10 indicates that weak instrument bias is less likely) and the variance of exposure explained by the variants (R 2 ). 17 We rated IV1 as 'high' if the selection of variants used genomewide significance (P-value < 5 Â 10 -8 ) and an Fstatistic > 10; as 'moderate' if the selection of variants used a more lenient significance threshold (P-value range from 0.05 to 5 Â 10 -8 ) and an F-statistic > 10; and 'poor' if none of above was assessed, reported or met.

It is assumed that the variant is largely independent of potential confounders because of the random allocation of genetic variants at conception. 18 For the independence assumption, we evaluated whether IV2 was assessed in each study, such as exploring the variant-confounder(s) association using individual-level data or curated databases (e.g. PhenoScanner), 19 controlling for population stratification or use of ethnically homogenous populations, or assessing the possibility of confounding by linkage disequilibrium (LD) using Bayesian colocalization analysis (for cis-Mendelian randomization studies only). 20 The posterior probability of Hypothesis 4 (two traits share a common variant) > 0.80 from colocalization analysis supports causality, i.e. the putative association by the cis-Mendelian randomization study is less likely confounded by variants in LD. 20 We rated IV2 as 'high' if this assumption was properly assessed using the above-mentioned approaches, 'moderate' if this assumption was only described and 'poor' if the assumption was not described.

Although the exclusion-restriction assumption cannot be fully verified, this can be partly checked via assessment of horizontal pleiotropy, 21 e.g. searching for genetic pleiotropic effects via curated databases or the use of statistical methods that rely on different and alternative IV assumptions, such as weighted median (majority valid), weighted mode (plurality valid) and Mendelian randomization-Egger (instrument strength independent of direct effect). [22] [23] [24] We rated IV3 as 'high' if this assumption was properly assessed using abovementioned approaches, 'moderate' if this assumption was only described and 'poor' if the assumption was not described.

Preprints are now increasingly used in the dissemination of COVID-19 research. 25 Two reviewers (T.H.T.W. and Y.L.) also searched unpublished studies from preprint servers (medRxiv and bioRxiv) using the same search strategy, which may help anticipate upcoming research findings. Two reviewers (T.H.T.W. and S.L.) identified eligible studies with the same selection criteria. We did not include preprints that were published in peer-reviewed journals as they would have been included in our main search. As these preprints have not been peer-reviewed, we only briefly summarized the findings given the concerns over validity. 26 

Based on a preliminary search, we found that the majority of the Mendelian randomization studies used the COVID-19 Host Genetics Initiative (HGI) 27 to obtain genetic associations with COVID-19, although the version and hence the sample size used varied across studies. As such, we did not conduct a meta-analysis to pool estimates from Mendelian randomization studies of the same topic.

The search returned 700 studies, of which 318 remained after removing 382 duplicates. A further 198 studies were excluded on title and/or abstract as not meeting the eligibility criteria, leaving 120 studies. A further 75 studies were excluded after full text review because they were not Mendelian randomization studies or did not assess COVID-19 outcomes. Five additional studies were identified via the reference list. In total, 50 eligible Mendelian randomization studies were included in this review ( Figure 1 ). The included studies were published between May 2020 and November 2021.

The characteristics of the included Mendelian randomization studies are presented in Table 1 . Of the 50 studies, 46 used a two-sample study design. Forty-one studies used COVID-19 HGI to obtain the genetic associations of outcomes, whilst several studies used the GWAS conducted in the UK Biobank, 28 cohorts from Italy and Spain, 29 studies focused on druggable targets, 9,67-78 amongst which one study also explored the effects of cardiometabolic exposures. 77 The findings from these Mendelian randomization studies are summarized in Supplementary Table S1 (available as Supplementary data at IJE online). Eleven of these studies reported the assessment of all three IV assumptions. Most studies were rated as having high validity for IV1 relevance (41/50) and IV3 exclusion-restriction (44/50). Only 13 studies were rated as having high validity for IV2 independence given that these studies conducted analyses to assess the plausibility of IV2 (Supplementary  Table S2 , available as Supplementary data at IJE online).

Two Mendelian randomization studies assessed the role of educational attainment in COVID-19, which showed that higher educational attainment was associated with reduced risk of COVID-19 severity and hospitalization but not COVID-19 susceptibility. 43, 61 One of these studies also showed that higher intelligence was associated with reduced risk of COVID-19 hospitalization (Supplementary  Table S1 , available as Supplementary data at IJE online). 43

Six Mendelian randomization studies consistently demonstrated strong associations of smoking traits, including smoking initiation, smoking heaviness and lifetime smoking index (which combined smoking initiation, duration, heaviness and cessation), in the risk of COVID-19 severity, hospitalization and mortality. 27, 34, 45, 53, 56, 57 Four Mendelian randomization studies explored the role of alcohol drinking in COVID-19 risk, 37, 45, 56, 57 of which two studies found null association. 45, 56 However, a study in UK Biobank provided suggestive evidence that alcohol drinking traits (being a frequent drinker and weekly alcohol consumption) were associated with higher risk of COVID-19 severity and mortality amongst participants who were obese. 37 In addition, a study found that alcohol use disorder and cannabis use were nominally associated with higher risk of COVID-19 susceptibility. 57 The role of physical activity in the risk of COVID-19 was inconsistent. Higher accelerometer-measured physical activity was associated with lower risk of COVID-19 severity in COVID-19 HGI. 45 However, null associations of self-reported moderate-to-vigorous physical activity and acceleration vector magnitude physical activity in COVID-19 susceptibility were reported using UK Biobank. 63 There was no evidence supporting the role of sleep duration in COVID-19 risk (Supplementary Table S1 , available as Supplementary data at IJE online). 27 

Mendelian randomization studies have explored the role of a wide range of anthropometrics and biomarkers in COVID-19 risk, including anthropometrics, blood pressure, coagulation factors, cytokines, inflammatory markers, glycaemic traits, haematological traits, lipids, liver functions, renal functions and vitamins. 27 27, 32, 38, 42, 45, 53 and one study also showed that increase in height was associated with higher risk of COVID-19 susceptibility. 27 Consistent evidence showed systolic and diastolic blood pressure to have no role in COVID-19 risk, 27, 32, 42, 49, 53 although one study found that higher pulse pressure was associated with higher risk of COVID-19 hospitalization in people of mixed ancestry but not of European ancestry. 49 Coagulation factors [higher von Willebrand factor (VWF) and lower disintegrin and metalloprotease with a thrombospondin type 1 motif member 13 (ADAMTS13)] 64 and lower cytokine [macrophage inflammatory protein 1 b (MIP1b)] 44 were associated with higher risk of COVID-19.

The inflammatory marker C-reactive protein (CRP) was nominally associated with higher risk of COVID-19 hospitalization and susceptibility in one study 42 but not another study. 27 There is suggestive evidence showed that haematological traits (higher basophil count, basophil percentage of white cells, lymphocyte count, myeloid white cell count, neutrophil count, red blood cell count, white blood cell count and lower mean corpuscular haemoglobin) were associated with reduced risk of COVID-19 severity and hospitalization. 27, 58, 59 Evidence was inconsistent for lipids with risk of COVID-19, 27, 32, 39, 42, 53, 55, 62, 65 where some suggested that higher low-density lipoprotein (LDL)-cholesterol, 32, 42 small very LDL cholesterol (VLDL) particles, 55 apolipoprotein B, 62 total cholesterol and total cholesterol in medium VLDL 55, 62 and triglycerides 27,62 were associated with higher risk of COVID-19 whereas others suggested null association. 27, 32, 39, 42, 53, 62, 65 Suggestive evidence showed that lower albumin and higher direct bilirubin were associated with higher risk of COVID-19 hospitalization 59 but null associations for other liver function markers [alanine aminotransferase (ALT), alkaline phosphatase (ALP), aspartate aminotransferase (AST), c-glutamyl transferase (GGT), indirect bilirubin, total bilirubin and total protein]. 59, 65 No evidence was found for the role of leukocyte telomere length (a determinant of longevity) in COVID-19. 60 Consistent evidence showed that glycaemic traits (HbA 1c , fasting insulin, fasting glucose and 2-h glucose), 31, 32, 42 high density lipoprotein (HDL) cholesterol and apolipoprotein A, 27, 32, 39, 42, 62, 65 renal traits [creatinine-based estimated glomerular filtration rate (eGFR) and serum creatinine] 27, 42, 59 and vitamins C and D 27, 33, 35, 40, 46, 47, 52 were not associated with risk of COVID-19 (Supplementary Table S1 , available as Supplementary data at IJE online).

Thirteen Mendelian randomization studies explored whether predisposition to diseases (including diseases of the circulatory, digestive, nervous, respiratory, genitourinary, musculoskeletal systems and connective tissue, metabolic diseases and mental disorders) increased COVID-19 risk. 27, 31, 36, 41, 42, [48] [49] [50] [51] 53, 54, 62, 66 Positive association of predisposition to ischaemic stroke in COVID-19 risk was found in one study 27 but not in another study. 66 There was no evidence supporting the role of other circulatory diseases (coronary artery disease, heart failure, any stroke, cardioembolic stroke, large artery stroke and small vessel stroke) in COVID-10 risk. 27, 42, 66 One study found that predisposition to combined bipolar disorder and schizophrenia was associated with higher risk of COVID-19 (based on self-reported symptoms), 50 although other studies suggested null association of predisposition to bipolar disorder and predisposition to schizophrenia and COVID-19 risk. 27, 48 One study suggested a positive association between predisposition to attention-deficit and hyperactivity disorder (ADHD), 48 chronic kidney disease 42 and idiopathic pulmonary fibrosis 36 with COVID-19 risk but this was not confirmed in another study. 27 There was suggestive evidence that predisposition to gastro-esophageal reflux disease was associated with higher risk of COVID-19 hospitalization 51 and an inverse association of predisposition to allergic disease with COVID-19 susceptibility. 41 There was no strong evidence supporting predisposition to metabolic diseases (diabetes, type 1 diabetes, type 2 diabetes), 27, 31, 42, 49, 53 mental disorders (autism spectrum disorder, depression, insomnia symptoms), 27,48 lupus, rheumatoid arthritis, asthma, risk tolerance and diseases of the nervous system (Alzheimer's disease, amyotrophic lateral sclerosis, multiple sclerosis, and Parkinson's disease) 27, 54 in COVID-19 risk (Supplementary Table S1 , available as Supplementary data at IJE online).

There were 13 cis-Mendelian randomization studies that explored potential druggable targets on COVID-19 risk, 9, [67] [68] [69] [70] [71] [72] [73] [74] [75] [76] [77] [78] of which 4 studies performed Bayesian colocalization analysis to assess whether the putative association was confounded by LD. 67, 71, 73, 78 Both cis-Mendelian randomization studies and colocalization analyses (PPH4 > 0.80) suggested that higher circulating protein histo-blood group ABO system transferase (ABO) 67, 73, 78 and lower circulating 2 0 -5 0 oligoadenylate synthetase 1 (OAS1) 73, 78 were associated with higher risk of COVID-19, regardless of severity. Inhibition of IL6 receptor (proxied by lower CRP) 9,67,68,74 and its common signaltransducing receptor subunit, glycoprotein 130 (gp130), 77 higher IL10 receptor beta subunit (IL10RB) 78 and higher IL17 receptor A (IL17RA) 72 were associated with lower risk of COVID-19. There was no evidence supporting the role of protein angiotensin-converting enzyme (ACE), ACE2 and liver/lymph node-specific intercellular adhesion molecule-3-grabbing non-integrin (L-SIGN) in COVID-19 risk, 69, 70 although positive association of dendritic cell (DC)-SIGN (also known as cluster of differentiation, CD209) in COVID-19 susceptibility and severity was found. 67, 70 Higher protein expression of family with sequence similarity 3, member D (FAM3D), intercellular adhesion molecule 1 (ICAM1) and sulfhydryl oxidase 2 (QSOX2) and lower protein expression of e-selectin (SELE) were associated with higher COVID-19 risk. 67 Extensive tissue-specific gene expression of druggable targets has also been explored 71, 73, 75, 76, 78 in which gene expression of OAS1, 78 ACE2, 71 IL10RB 71 and interferon (IFN) alpha receptor 2 (IFNAR2) 71, 73, 75, 76 across several tissues was related to COVID-19 risk (Supplementary  Table S1 , available as Supplementary data at IJE online).

There were 24 studies identified from the preprint servers that explored a wide range of socio-demographic factors, lifestyle attributes, anthropometrics, biomarkers, predisposition to diseases and druggable targets (Supplementary  Table S3 , available as Supplementary data at IJE online). Some studies corroborated previous findings, such as the detrimental role of smoking and obesity. 79, 100 There is one Mendelian randomization study in an East Asian population that also showed a detrimental effect of obesity in severe COVID-19. 88 Others identified new determinants including increased testosterone, 96 and reduced carnitine and acetylcarnitine 84 was associated with higher risk of COVID-19 severity and hospitalization, respectively. The updated GWAS of COVID-19 HGI included assessment of a wide range of exposures in COVID-19 risk and highlighted increased liability of type 2 diabetes associated with higher risk of COVID-19 susceptibility and hospitalization, although the association was abolished after adjusting for BMI. 82 Another study that was published in a peer-reviewed journal showed accelerated ageing was associated with higher COVID-19 risk, although the publication was not indexed in PubMed. 102 However, there were methodological concerns in some studies, such as interpreting liability as the effect of disease diagnosis, 87 the lack of comprehensive assessment of IV assumptions 96 and insufficient details for replication. 100 

To the best of our knowledge, this is the first systematic review focusing on evidence concerning factors contributing to COVID-19 from Mendelian randomization studies. This systematic review summarizes modifiable risk factors for intervention (e.g. obesity and smoking), as well as proteomic signatures (e.g. OAS1 and IL6) that could help identify relevant drugs for treatment of COVID-19.

Socio-demographic factors and lifestyle attributes Our review found two Mendelian randomization investigations of the role of socio-demographic factors (education attainment and intelligence) in COVID-19. This is consistent with previous observational studies 103 and highlights the issue of inequalities in the COVID-19 pandemic. Possible pathways may include unhealthy lifestyles associated with lower socio-economic position such as smoking, and possibly physical inactivity and alcohol drinking, where our review suggested a possible link with increasing risk of COVID-19 severity and hospitalization, 27, 34, 37, 45, 53, 56, 57 and are consistent with conventional observational studies. 104, 105 A popular mechanism related to increased risk of COVID-19 concerning smoking was an increased expression of ACE2, a receptor for SARS-CoV-2 in the airway epithelium. 106 This is also consistent with the cis-Mendelian randomization study that showed high gene expression of ACE2 at the Brodmann area 9 (BA9) at the brain frontal cortex was associated with higher risk of COVID-19 hospitalization. 71 This evidence supports the recent call from the World Health Organization (WHO) regarding the importance of tobacco cessation in reducing severe COVID-19. 107 Whilst obesity and hence subsequent pro-inflammatory response may explain why people who were physically inactive have higher risk of COVID-19, 108 whether alcohol use is relevant to COVID-19 remains unclear where only a possible positive association amongst participants who were obese was observed. 37 Anthropometrics and biomarkers Our review highlights that CRP, MIP1b, VWF, ADAMTS13, height, obesity and some haematological traits have a role in COVID-19 risk. Age is a key host factor determining disease severity and progression, 109 and age-related immunosenescence and age-related decrease in physiological reserve can contribute to vulnerability to COVID-19 in older adults. 110 Furthermore, ageing may induce a more pro-inflammatory environment (i.e. inflammaging); 111 the same phenomenon may also explain the potential harmful effects of obesity in COVID-19 risk, 112 alongside downstream factors such as reduced ADAMTS13 activity and increased VWF. 113 The finding that basophil count was inversely associated with the hospitalization and severity of COVID-19 58 is consistent with a small immune-monitoring study that observed a positive correlation between basophil count and the level of IgG antibody against SARS-CoV-2. 114 This may then enhance the adaptive immune response to SARS-CoV-2 infection. 115 Predisposition to diseases Our review highlights the role of genetic predisposition to ischaemic stroke, idiopathic pulmonary fibrosis, ADHD and combined bipolar disorder and schizophrenia in COVID-19 risk. These findings are consistent with some but not all studies. 116 Possible biological mechanisms included differing profile of individuals with bipolar disorders and schizophrenia 117 and their genetic variability across human leukocyte antigens that could contribute to differences in immune responses to SARS-CoV-2 infections. 118 Alternatively, relevant societal factors may include socio-economic deprivation, social isolation 119 and barriers to accessing healthcare services for COVID-19 in individuals with mental health disorders and neurodevelopmental disorders. 120 Possible mechanisms for the link of ischaemic stroke and COVID-19 risk may again be due to the pro-inflammatory environment and increased coagulation factors. 121 Although genetic predisposition to chronic kidney disease was related to higher risk of hospitalized COVID-19, renal traits (creatinine-based eGFR and creatinine) were not related to COVID-19 and the underlying mechanisms linking kidney function and COVID-19 have yet to be established. 122 One limitation with Mendelian randomization studies using binary disease exposures is the interpretation, as the effect may represent the consequence of liability to disease instead of having the disease. 123 Protein targets for potential drug reposition The cis-Mendelian randomization studies integrated with colocalization analyses provided strong genetic evidence for several druggable targets, which can help prioritize possible targets to be tested in an RCT. 124 For example, some cis-Mendelian randomization studies suggested that IL6related pathways (e.g. IL6 receptor and soluble gp130) are related to the risk of COVID-19. 9, 77 These are generally consistent with suggestive evidence from RCTs that evaluated the efficacy of IL-6 antagonists (tocilizumab, sarilumab and siltuximab) for COVID-19 severity. 125 Whether relevant medications such as soluble gp130Fc (Olamkicept) can be repurposed to reduce the severity of COVID-19 should be explored. 126, 127 Strong genetic evidence suggested a positive association of protein ABO with the risk of COVID-19. 73, 78 Nevertheless, ABO is highly pleiotropic and has been linked to various phenotypes, 78 suggesting that these cis-Mendelian randomization studies may still suffer from horizontal pleiotropy and should be interpreted with caution. OAS1 variants (rs10735079, rs6489867 and rs4767027, in high LD r 2 > 0.80) were associated with susceptibility to SARS-CoV-1 and SARS-CoV-2 in populations of different ancestries. 76, 128, 129 The protective effects of protein OAS1 in COVID-19 risk may be due to increased levels of p46 isoform, 73, 78 which was later verified in a human genetic analysis. 130 ACE2 is a functional receptor for SARS-CoV-1 and SARS-CoV-2. 131, 132 Human recombinant soluble ACE2 (hrsACE2) reduced SARS-CoV-2 viral load in infected Vero-E6 cells 133 and its role as a therapeutic target for COVID-19 is currently being explored in a phase II clinical trial (NCT04335136). 134 DC-SIGN was considered as a potential receptor for SARS-CoV-2. 135 However, the testing of hydroxychloroquine (a modulator of the dendritic cell) 136 has been halted due to increased mortality risk reported in RCTs. 137 

This is the first systematic review on COVID-19-related Mendelian randomization studies to have summarized potentially more credible evidence concerning causes of COVID-19 risk. Nevertheless, there are some limitations in this review. First, Mendelian randomization studies rely on IV assumptions (e.g. relevance, independence and exclusionrestriction), 16 although most studies have addressed/acknowledged these assumptions when conducting respective Mendelian randomization studies (Supplementary Table S2 , available as Supplementary data at IJE online). It is not generally acknowledged that Mendelian randomization studies, like all observational studies, are open to selection bias from inevitably only including survivors of the genetic predictors of the exposure and competing risk of COVID-19. 138 As a result, Mendelian randomization studies may not fully identify effects of harmful exposures on COVID-19 because people who have died from a harmful exposure or from a competing risk of COVID-19 are not available for recruitment. Second, Mendelian randomization studies based on an earlier release of COVID-19 HGI databases (with small number of cases) and the cis-Mendelian randomization studies (with single genetic variant) have relatively lower statistical power and hence null findings from these studies should be interpreted with caution. Third, most (82%) studies used COVID-19 HGI to obtain the variant-outcome associations, given it is the largest available GWAS available, implying that meta-analysis of studies addressing the same question was technically impossible to increase statistical power. Fourth, most studies pertained to populations of predominantly European ancestry and might not be generalizable to other populations, although causes are usually consistent but not always relevant. Genetic data from diverse ancestral populations can better evaluate whether determinants of COVID-19 risk and its severity vary across ethnicities or possibly identify causes of COVID-19 not evident in European populations. 139 Fifth, we only included published studies in this review, given the varying quality of preprints, although such issues also applied to published studies (Supplementary Table S2 , available as Supplementary data at IJE online). However, given that preprints may foreshadow upcoming publications, we summarized the findings from the preprints briefly although interpretation of these findings should be with caution (Supplementary Table S3 , available as Supplementary data at IJE online). Sixth, the factors chosen for investigation may represent those that are best understood rather than those most relevant to equitably protecting the population against the effects of COVID-19. For example, the greater vulnerability of disadvantaged populations and of men to COVID- 19 has not yet been investigated using Mendelian randomization. Lastly, whether these factors contribute to milder forms of COVID-19, which comprises most cases, requires additional investigation in larger studies. This is of particular relevance given a recent prospective study indicated that young, homeisolated adults with mild to moderate COVID-19 suffer from long-term complications from COVID-19. 140 This systematic review highlighted increases in smoking, obesity and inflammatory factors as causes of increased risk of COVID-19, whilst other factors that were thought to be relevant to COVID-19, such as vitamin D, were unlikely causal in increased susceptibility to COVID-19. Our study also summarized possible druggable targets that are related to COVID-19 risk, thus providing additional insights regarding the prioritization and repositioning of medications to mitigate the risk of COVID-19. This systematic review reveals factors contributing to COVID-19 risk that would guide subsequent policy interventions to mitigate the global COVID-19 pandemic.

Not applicable. All the work was developed using published data.

The data underlying this article are available in the article and in its online Supplementary material.

Supplementary data are available at IJE online. 

None.

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Smoking is significantly associated with increased risk of COVID-19 and other respiratory infections

White blood cells and severe covid-19: a Mendelian randomization study

Liver and kidney function biomarkers, blood cell traits and risk of severe COVID-19: a Mendelian randomization study

Shorter leukocyte telomere length is associated with adverse COVID-19 outcomes: a cohort study in UK Biobank

Educational attainment decreases the risk of COVID-19 severity in the European population: a twosample Mendelian randomization study

Causal associations between blood lipids and COVID-19 risk: a two-sample Mendelian randomization study

Physical activity and COVID-19: an observational and Mendelian randomisation study

Coagulation factors and the incidence of COVID-19 severity: Mendelian randomization analyses and supporting evidence

A Chinese host genetic study discovered IFNs and causality of laboratory traits on COVID-19 severity

Leveraging genetic data to elucidate the relationship between COVID-19 and ischemic stroke

A proteome-wide genetic investigation identifies several SARS-CoV-2-exploited host targets of clinical relevance

Genetic IL-6R variants and therapeutic inhibition of IL-6 receptor signalling in COVID-19-authors' reply

The effect of angiotensin-converting enzyme levels on COVID-19 susceptibility and severity: a Mendelian randomization study

SARS-CoV-2 impairs dendritic cells and regulates DC-SIGN gene expression in tissues

Actionable druggable genome-wide Mendelian randomization identifies repurposing opportunities for COVID-19

Comparative host-coronavirus protein interaction networks reveal pan-viral disease mechanisms

Multi-omics highlights ABO plasma protein as a causal risk factor for COVID-19

Genetically proxied interleukin-6 receptor inhibition: opposing associations with COVID-19 and pneumonia

Mendelian randomization analysis identified genes pleiotropically associated with the risk and prognosis of COVID-19

Genetic mechanisms of critical illness in COVID-19

Evaluating the effects of cardiometabolic exposures on circulating proteins which may contribute to severe SARS-CoV-2

A Neanderthal OAS1 isoform protects individuals of European ancestry against COVID-19 susceptibility and severity

The effect of obesity-related traits on COVID-19 severe respiratory symptoms is mediated by socioeconomic status: a multivariable Mendelian randomization study. medRxiv

New susceptibility loci for severe COVID-19 by detailed GWAS analysis in European populations. medRxiv

Association of lipid-lowering drugs with COVID-19 outcomes from a Mendelian randomization study

Mapping the human genetic architecture of COVID-19: an update. medRxiv

SARS-CoV-2 infects blood monocytes to activate NLRP3 and AIM2 inflammasomes, pyroptosis and cytokine release. medRxiv

Mendelian randomization analyses show that higher acetyl-carnitine and carnitine levels in blood protect against severe Covid19. medRxiv

Mendelian randomisation identifies alternative splicing of the FAS death receptor as a mediator of severe COVID-19. medRxiv

Critically ill COVID-19 status associated trait genetics reveals CDK6 inhibitors as potential treatment. medRxiv

Association between Alzheimer's disease and COVID-19: A bidirectional Mendelian randomization. medRxiv

Japan COVID-19 Task Force: a nation-wide consortium to elucidate host genetics of COVID-19 pandemic in Japan. medRxiv

Proteome-wide Mendelian randomization identifies causal links between blood proteins and severe COVID-19

Genetic validation of the use of tocilizumab, statins and dexamethasone in COVID-19. medRxiv

The effect of circulating zinc, selenium, copper and vitamin K1 on COVID-19 outcomes: a Mendelian randomization study

A two-sample robust Bayesian Mendelian Randomization method accounting for linkage disequilibrium and idiosyncratic pleiotropy with applications to the COVID-19 outcomes

Mendelian randomization analysis to characterize causal association between coronary artery disease and COVID-19. medRxiv

Exploring causal relationships between COVID-19 and cardiometabolic disorders: a bi-directional Mendelian randomization study. medRxiv

Neuropsychiatric disorders as risk factors and consequences of COVID-19: a Mendelian randomization study. medRxiv

Genetically determined serum testosterone level and Covid-19 illness level: a Mendelian randomization study. medRxiv

A novel penalized inversevariance weighted estimator for Mendelian randomization with applications to COVID-19 outcomes. medRxiv

Common and rare variant analyses combined with single-cell multiomics reveal cell-type-specific molecular mechanisms of COVID-19 severity. medRxiv

Causal associations between COVID-19 and atrial fibrillation: a bidirectional Mendelian randomization study

Smoking and COVID-19: a two-sample Mendelian randomization study. medRxiv

Multi-omics study revealing putative drug targets of COVID-19 severity and other viral infection diseases. medRxiv

Genetic and phenotypic analysis of the causal relationship between aging and COVID-19

Association of social and demographic factors with COVID-19 incidence and death rates in the US

Current smoking and COVID-19 risk: results from a population symptom app in over 2.4 million people

Physical inactivity is associated with a higher risk for severe COVID-19 outcomes: a study in 48 440 adult patients

Smoking, ACE-2 and COVID-19: ongoing controversies

World Health Organization. The importance of tobacco cessation in the context of the COVID-19 pandemic

Associations between body-mass index and COVID-19 severity in 6.9 million people in England: a prospective, community-based, cohort study

Pathophysiology transmission, diagnosis, and treatment of coronavirus disease 2019 (COVID-19): a review

Aging immunity may exacerbate COVID-19

Inflammageing: chronic inflammation in ageing, cardiovascular disease, and frailty

Obesity, inflammation, and outcomes in Covid-19

Effects of inflammatory cytokines on the release and cleavage of the endothelial cell-derived ultralarge von Willebrand factor multimers under flow

Systemslevel immunomonitoring from acute to recovery phase of severe COVID-19

Basophils enhance immunological memory responses

Comorbidities in SARS-CoV-2 patients: a systematic review and meta-analysis

International Schizophrenia Consortium. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder

Understanding the genetic contribution of the human leukocyte antigen system to common major psychiatric disorders in a world pandemic context

Socioeconomic deprivation index is associated with psychiatric disorders: an observational and genome-wide gene-by-environment interaction analysis in the UK Biobank cohort

Association between mental health disorders and mortality among patients with COVID-19 in 7 countries: a systematic review and metaanalysis

Ischemic stroke, inflammation, and endotheliopathy in COVID-19 patients

Coronavirus disease 2019 in chronic kidney disease

Mendelian randomization with a binary exposure variable: interpretation and presentation of causal estimates

Phenome-wide Mendelian randomization mapping the influence of the plasma proteome on complex diseases

Tocilizumab in COVID-19: a meta-analysis, trial sequential analysis, and meta-regression of randomizedcontrolled trials

Soluble interleukin-6 receptor in the COVID-19 cytokine storm syndrome

Is IL-6 a key cytokine target for therapy in COVID-19?

Polymorphisms of interferon-inducible genes OAS-1 and MxA associated with SARS in the Vietnamese population

Association of SARS susceptibility with single nucleic acid polymorphisms of OAS1 and MxA genes: a case-control study

Endomembrane targeting of human OAS1 p46 augments antiviral activity

Angiotensin-converting enzyme 2 is a functional receptor for the SARS coronavirus

SARS-CoV-2 cell entry depends on ACE2 and TMPRSS2 and is blocked by a clinically proven protease inhibitor

Inhibition of SARS-CoV-2 infections in engineered human tissues using clinical-grade soluble human ACE2

A trimeric human angiotensinconverting enzyme 2 as an anti-SARS-CoV-2 agent

CD209L/L-SIGN and CD209/DC-SIGN act as receptors for SARS-CoV-2

Mechanisms of action of hydroxychloroquine and chloroquine: implications for rheumatology

Mortality outcomes with hydroxychloroquine and chloroquine in COVID-19 from an international collaborative meta-analysis of randomized trials

Letter in response to 'Bias in two-sample Mendelian randomization when using heritable covariable-adjusted summary associations'-'Interpreting Mendelian randomization studies pre-adjusted for the heritable covariable survival to recruitment'

Genetic analyses of diverse populations improves discovery for complex traits

Bergen COVID-19 Research Group et al. Long COVID in a prospective cohort of home-isolated patients

None declared.