key: cord-0686825-zzgpppsf authors: Freuer, D.; Linseisen, J.; Meisinger, C. title: Obesity has an impact on COVID-19 susceptibility and severity: a two-sample Mendelian randomization study date: 2020-07-16 journal: nan DOI: 10.1101/2020.07.14.20153825 sha: d797bc244b1763b80576574aa60b18ff9b33886d doc_id: 686825 cord_uid: zzgpppsf Background Recent observational studies suggested obesity to be a possible risk factor for COVID-19 disease in the wake of the coronavirus (SARS-CoV-2) infection. However, the causality as well as the role of body fat distribution in this context still unclear. Thus, using a two-sample Mendelian randomization (MR) approach, we investigated the causal impact of obesity on the susceptibility and severity of COVID-19. Methods Obesity was quantified by body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR). Summary statistics of genome-wide association studies (GWASs) for these anthropometric measures were drawn from the GIANT consortium (Locke et al. (n=322154); Shungin et al. (n=232101)) and for the COVID-19 susceptibility (n=1079768) as well as hospitalization (n = 900687) from the COVID-19 Host Genetics Initiative. Causal estimates were calculated using Single Nucleotide Polymorphisms (SNPs) and sensitivity analyses were done applying several robust MR techniques. Results Genetically predicted BMI was significantly associated (per one SD) with both, COVID-19 susceptibility (OR=1.41; 95% CI: 1.15 - 1.72; P-value=0.001) and hospitalization (OR=1.60; 95% CI: 1.19 - 2.14; P-value=0.006). WC was associated with the susceptibility (OR=1.38; 95% CI: 1.07 - 1.78; P-value=0.015) but not with hospitalization. WHR was not associated with any of the COVID-19 outcomes. Conclusions This study provides evidence for a causal impact of overall obesity on the susceptibility and severity of COVID-19. Therefore, obese people should be regarded as a risk group. Future research is necessary to investigate the underlying mechanisms linking obesity with COVID-19. At the end of 2019, there was an outbreak of a coronavirus infection (SARS-CoV-2), which is partly associated with very severe disease courses; this COVID-19 outbreak developed into a pandemic within a short period of time (1) . This pandemic with currently more than ten million infected subjects and a high number of deaths requires the study of risk factors associated with a higher susceptibility to the virus or a more severe course of the disease to identify high risk groups that require special protection. As consequence of the 2009 H1N1 influenza A virus pandemic, obesity was identified for the first time as a risk factor for increased disease severity and mortality in infected individuals(2; 3). These observations have led to the assumption that obese people may be vulnerable to a more severe COVID-19 disease course. Very recent, observational studies confirm that obesity could be a risk factor for hospitalization with COVID-19 and also a significant predictor for mortality among inpatients with this infection (4) (5) (6) . This is in line with previous studies suggesting obesity as an independent predictor of infectious diseases, such as blood stream infection, urinary infections, respiratory infections, and skin infections (7) . However, so far, research on the causal role of obesity on the susceptibility to SARS-CoV-2 and severity of the disease is missing. A Mendelian randomization approach offers the possibility to examine causality by using genetic variants as instruments, which are explicitly associated with the exposure. Thus, it is possible to minimize confounding and preclude reverse causation because variants are randomly allocated from parents to offspring at conception. In this study we investigated causal effects of BMI, waist circumference (WC), and waist-hip-ratio (WHR) on the risk of SARS-CoV-2 infection and severe course of COVID-19 disease. In a two-sample Mendelian randomization (MR) approach genetic variants were used to assess causal effects of obesity as a modifiable risk factor on COVID-19 susceptibility and hospitalization as a consequence of an infection with the SARS-CoV-2 virus. Details on the MR-design were described elsewhere (8) (9) (10) . . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted July 16, 2020. . https://doi.org/10.1101/2020.07.14.20153825 doi: medRxiv preprint The a priori statistical power for the binary traits susceptibility and hospitalization due to COVID-19 disease was calculated according to Burgess et al.(14) . According to Supplemental Table S5, where the explained phenotypic variances are between 0.60 % for WHR and 1.3 % for BMI. Given a type I error of 5 %, our analyses were sufficiently powered (≥ 80 %) when the expected OR per one standard deviation of the respective anthropometric measure for SARS-CoV-2 infection and hospitalization was ≥ 1.5 in genetically instrumented BMI/WC/WHR. Causal estimates of the relationship between anthropometric measures and Covid-19 susceptibility as well as hospitalization were calculated, applying an inverse-variance weighted (IVW) meta-analysis using modified second order weights within the radial regression framework. This approach provides the highest statistical power if the key assumptions of the Mendelian randomization are met. To assess and validate these assumptions we performed several sensitivity analyses that consider different patterns of violations. Among others, we used the MR-PRESSO (Pleiotropy RESidual Sum and Outlier) method for two issues: the global test detected (based on observed residual sum of squares) horizontal pleiotropy and the outlier test identified potential outlier SNPs at a threshold of 0.05 [Supplemental Table S6 ]. Under the Instrument Strength Independent of Direct Effect (InSIDE) assumption, the radial MR-Egger intercept test was used for assessing directional pleiotropy. Substantial heterogeneity within the IVW and MR-Egger methods was quantified and tested using Cochran's as well as Rücker's Q statistics [Supplemental Table S7 ]. If necessary, we moved from fixed to random effects models that account for balanced horizontal and directional pleiotropy, respectively. Furthermore, we investigated influential SNPs based on the respective Q statistic and several plots (e.g. radial, funnel, leave-one-out, and SNP-exposure-outcome association plots). To assess consistency of causal estimates in case of horizontal pleiotropy as well as outlier occurrence, we additionally performed three types of robust estimation methods. The first was the weighted median approach that requires at least 50 % of the genetic variants to be valid instruments. The second was the weighted mode method, which is consistent even if less than 50 % of the genetic variants are valid. Third, we conducted a many weak instruments . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 16, 2020. . https://doi.org/10.1101/2020.07.14.20153825 doi: medRxiv preprint analysis using the RAPS (Robust Adjusted Profile Score) method and controlled for systematic pleiotropy in form of overdispersion, if necessary. After application of the Bonferroni correction to account for multiple testing issues, P-values with P < 0.008 were considered statistically significant and values of 0.008 ≤ P < 0.05 as suggestive significant. All reported ORs were expressed per one standard deviation increment of each body composition measure. Significance thresholds were set to = 0.01 for testing the Q statistics and = 0.05 for the PRESSO global test. Analyses were performed using primarily the TwoSampleMR (version 0.5.4) and MRPRESSO (version 1.0) packages of the statistical Software R (version: 4.0.0). is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 16, 2020. . https://doi.org/10.1101/2020.07.14.20153825 doi: medRxiv preprint robust RAPS, and PRESSO models led to the same decisions as the IVW approach. Beyond that, overdispersion could not be detected within the RAPS method. The present study using genetic instruments for BMI, WC, and WHR from publicly available large-scale GWAS provides evidence for a causal role of general and abdominal obesity regarding SARS-CoV-2 susceptibility and disease severity. In addition to the recently published observational studies assuming that obesity might be an independent risk showed that the prevalence of obesity was higher in critical ill COVID-19 patients in comparison to non-critical cases (OR = 1.96; 95 % CI: 1.13-3.42) even after multivariable adjustment (15; 16) . A study from New York City including 4 103 patients suffering from COVID-19 reported that a BMI > 40 kg/m² was the strongest predictor after old age for hospitalization due to COVID-19 (5) . In a prospective cohort study based on the ISARIC WHO Clinical Characterization Protocol including 16 749 hospitalized patients, it was found that 17% of the patients needed critical care. Being elderly, male and obese were associated with adverse outcomes (4) . In that study, obese patients had a HR of 1.37 (95 % CI 1.16 -1.63) for death after adjustment for age and sex in the analysis. Another cohort study based on linked electronic health records of 17 million adult NHS patients reported an increased in-hospital mortality risk due to COVID-19 for obese patients even after multivariable adjustment (HR of 1.27 for BMI 30 -34.9 kg/m² and a HR of 2.27 for BMI >=40 kg/m2) (6) . Several mechanisms may explain why obese people are at increased risk for COVID-19 infection. Inflammation and the immune system in obese individuals could play a role in relation to viral diseases. In adipose tissue there is a high production of pro-inflammatory cytokines causing chronic low-grade inflammation and immune dysregulation (17; 18) . Results from animal models revealed that the role of obesity in increasing the risk of influenza morbidity and mortality is due to the impairment of the immune response to this pathogen (19) . Green et al. proposed that hyperinsulinemia or hyperleptinemia which occurs predominantly in obese subjects may lead to a metabolic dysregulation of T cells, resulting in an impairment of the activation and function of these adaptive immune cells in response to influenza . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 16, 2020. . https://doi.org/10.1101/2020.07.14.20153825 doi: medRxiv preprint viruses (19) . In this context, Honce et al. emphasized especially the role of visceral adiposity (20) . Which metabolic and immune derangements in obese people are responsible for the increased susceptibility to SARS-CoV-2 infections should be subject of further research. In connection with COVID-19 it is discussed that the SARS-CoV receptor ACE2 is also used by the SARS-CoV-2 spike protein (a special surface glycoprotein) as a cellular entry receptor (21) . In human tissue ACE2 is expressed in the lung, the main target site for COVID-19 infection, but also in extrapulmonary tissues including heart, kidney, and intestine. Furthermore, obesity upregulates ACE2 receptor and therefore obese subjects have larger amounts of ACE2 (22) . It can be assumed that analogous to SARS-CoV(23), excessive ACE2 may competitively bind with SARS-CoV-2 not only to neutralize the virus but also rescue cellular ACE2 activity which negatively regulates the renin-angiotensin system to protect the lung from injury (24) . Through the downregulation of ACE2 activity angiotensin II, the substrate for ACE, will accumulate and lead to increased neutrophil accumulation, increased vascular permeability, and pulmonary oedema, which will lead to severe lung injury. Because obesity is associated with a dysregulation of the reninangiotensin-aldosterone system and thus among other things linked to an overexpression of angiotensin II (25) . This represent an important link between obesity and severity of COVID-19. Strengths of the study include that we performed a range of robust MR methods to conduct sensitivity analyses for different patterns of pleiotropy. The use of three anthropometric measures, that have different views on body fat distribution, allowed us to compare as well as differentiate between overall obesity and body fat distribution as exposures. Furthermore, they strengthened evidence by reciprocal verification. However, our study also has limitations. The relationship between obesity and the risk of acquiring COVID-19 disease is influenced by selection bias, because people with no, uncomplicated or milder symptoms often were not tested regarding SARS-CoV-2 infection. This causes bias towards the null hypothesis due to false negatives (type II error) and reduces therefore the power by underestimating the true causal effect. Sex-specific samples would lead to higher precision, although we did not expect large differences between men and women. Furthermore, the present study was conducted in subjects of European ancestry and therefore the findings could not be applied to other ethnicities. Our study is the first strengthening the evidence that overall and abdominal obesity is causally associated with the susceptibility to and the severity of SARS-CoV-2 virus infections. Future research is necessary to investigate the underlying mechanisms linking (abdominal) obesity with COVID-19. Since the prevalence of obesity is still increasing in many countries and the probability of emerging and re-emerging infectious diseases might be high in the future . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 16, 2020. . https://doi.org/10.1101/2020.07.14.20153825 doi: medRxiv preprint (26) , intensive public health interventions targeting obesity are necessary to reduce morbidity and mortality due to infectious diseases such as COVID-19. The authors did not receive funding for this study. Funding information of the genome-wide association studies is specified in the cited studies. All authors declare that they have nothing to disclose. The present study is based on summary-level data that have been made publically available. Summary data from . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 16, 2020. . https://doi.org/10.1101/2020.07.14.20153825 doi: medRxiv preprint Table 1 Mendelian randomization estimates for the association between body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) related Single Nucleotide Polymorphisms (SNPs) and COVID-19 susceptibility . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted July 16, 2020. . https://doi.org/10.1101/2020.07.14.20153825 doi: medRxiv preprint Table 2 Mendelian randomization estimates for the association between body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) related Single Nucleotide Polymorphisms (SNPs) and hospitalization due to severity of COVID-19 disease . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted July 16, 2020. . https://doi.org/10.1101/2020.07.14.20153825 doi: medRxiv preprint Figure 1 Causal estimates (odds ratios and 95 % confidence intervals) of body mass index (BMI), waist circumference (WC), and waist-to-hip ratio (WHR) with COVID-19 susceptibility and hospitalization. Grey points with dashed confidence intervals correspond to estimates biased regarding the influential SNP rs12549058. . CC-BY 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. 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