key: cord-0913863-2jw15w28
authors: Zhang, K.; Guo, Y.; Wang, Z.-X.; Ding, J.-M.; Yao, S.; Chen, H.; Zhu, D.-L.; Huang, W.; Dong, S.-S.; Yang, T.-L.
title: Causally Associations of Blood Lipids Levels with COVID-19 Risk: Mendelian Randomization Study
date: 2020-07-07
journal: nan
DOI: 10.1101/2020.07.07.20147926
sha: f37cbfd2aed8d693e2e9440079f5602148a6cd66
doc_id: 913863
cord_uid: 2jw15w28

Background: Coronavirus disease 2019 (COVID-19) is a global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2). It has been found that coronary artery disease (CAD) is a comorbid condition for COVID-19. As the risk factors of CAD, whether blood lipids levels are causally related to increasing susceptibility and severity of COVID-19 is still unknown. Design: We performed two-sample Mendelian Randomization (MR) analyses to explore whether dyslipidemia, low density lipoprotein cholesterol (LDL-c), high density lipoprotein cholesterol (HDL-c), triglyceride (TG) and total cholesterol (TC) were causally related to COVID-19 risk and severity. The GWAS summary data of blood lipids involving in 188,578 individuals and dyslipidemia in a total of 53,991 individuals were used as exposures, respectively. Two COVID-19 GWASs including 1,221 infected patients and 1,610 severe patients defined as respiratory failure were employed as outcomes. Based on the MR estimates, we further carried out gene-based and gene-set analysis to explain the potential mechanism for causal effect. Results: The MR results showed that dyslipidemia was casually associated with the susceptibility of COVID-19 and induced 27% higher odds for COVID-19 infection (MR-IVW OR = 1.27, 95% CI: 1.08 to 1.49, p-value = 3.18 x 10-3). Moreover, the increasing level of blood TC will raise 14 % higher odds for the susceptibility of COVID-19 (MR-IVW OR = 1.14, 95% CI: 1.04 to 1.25, p-value = 5.07 x 10-3). Gene-based analysis identified that ABO gene was associated with TC and the gene-set analysis found that immune processes were involved in the risk effect of TC. Conclusions: We obtained three conclusions: 1) Dyslipidemia is casually associated with the susceptibility of COVID-19; 2) TC is a risk factor for the susceptibility of COVID-19; 3) The different susceptibility of COVID-19 in specific blood group may be partly explained by the TC concentration in diverse ABO blood groups.

For each exposure GWAS, we performed harmonization process using the following criteria:

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The copyright holder for this preprint this version posted July 7, 2020. . https://doi.org/10.1101/2020.07.07.20147926 doi: medRxiv preprint 1) Remove the SNPs located in major histocompatibility complex (MHC) region. 82 2) Select the SNPs with a common frequency of the effect allele (EAF) (> 0.01 and < 0.99). 83 3) Standardize the effect size (β) and standard error (se) for each GWAS data with the function of minor 84 allele frequency and sample size using the following formula 12 : 2 ) , se = 1 √ 2p(1-p)(n +z 2 ) 86 where z = β/se from the original summary data, p is the minor allele frequency, and n is the total sample 87 size. 100 We conducted four complementary two-sample MR methods, including Inverse-Variance Weighted 101 (IVW) method, weighted median method, weighted mode method and MR-Egger method, which make 102 different assumptions about horizontal pleiotropy.

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The IVW method assumes balanced pleiotropy 15 . The pleiotropy is assessed via Cochran's Q statistic 105 and presented as excessive heterogeneity which will inflate the estimate of MR analysis 16 . The MR-

Egger method is based on the assumption which indicate instrument strength independent of the direct 107 effects 15 . MR-Egger estimates can be also evaluated by the regression dilution I 2 (GX) 17 according to the 108 assumption that no measurement error in the SNP exposure effects. If I 2 (GX) 17 was sufficiently low (I 2

(GX) < 0.9), the correction analysis was conducted to assess the causal effect by SIMEX. The intercept 110 term of MR-Egger method can used for evaluating the directional pleiotropic effect 18 . When the 111 intercept is zero or its p-value was not significant (p-value > 0.05) were considered as non-pleiotropy.

Moreover, we also used the Rucker's Qʹ statistic 19 to measure the heterogeneity for MR-Egger method.

If the difference Q − Qʹ is sufficiently extreme with respect to a χ2 distribution with the 1 degree of 114 freedom, we indicated that directional pleiotropy is an important factor and MR-Egger model provides 115 a better fit than the IVW method 20 CC-BY-NC-ND 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 7, 2020. . https://doi.org/10.1101/2020.07.07.20147926 doi: medRxiv preprint Sensitivity analysis 126 Leave-one-out sensitivity analysis was implemented to assess whether any significant results were 127 generated by a specific SNP in IVW models. (GRCh37 or hg19) 23 . The GWGAS analysis was performed to quantify the degree of association for 141 each gene to TC and to compute the correlations between genes are estimated according to LD statistics.

The LD reference was also from Phase 3 of 1,000 Genomes.

Gene-set analysis 144 The gene-set analysis is built as an independent layer around the gene analysis, while it also on the 145 strength of the gene p-value and gene correlation matrix from the previous step in order to compensate 146 for the dependencies between genes 22 . A total of 7,521 gene sets were derived from Gene Ontology 147 . CC-BY-NC-ND 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 7, 2020. Multiple testing correction 152 We employed false discovery rate (FDR) to address multiple comparisons issue and the adjusted p-153 value < 0.05 was used for judging significance. For MR estimates, we adopted an FDR control 154 procedure for the susceptibility and severity of COVID-19 separately. Table S1 .

Causal effect of dyslipidemia on COVID-19 163 We evaluated whether dyslipidemia is causally related to COVID-19 firstly. The assessment of 164 pleiotropy is shown in Table S1 . Since there was no significant evidence of pleiotropy (all p value > 165 0.05, Table S1), we chose IVW as the main MR method. We found that dyslipidemia was causally 166 associated with the susceptibility of COVID-19 after FDR correction (MR-IVW p-value = 3.18 × 10 -3 , 167 FDR = 1.30 × 10 -2 ) ( Table 1 ). The estimate of IVW showed that dyslipidemia could raise 27% odds for 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 7, 2020. Figure 2 ). In sensitivity analyses, the results of leave-one-out 173 permutation didn't find individual influential SNPs in IVW models (p-value < 0.05) ( Figure S1 ).

Causal effect of blood lipids on COVID-19 176 We further assessed the causal effects of blood lipids levels, including HDL-c, LDL-c, TC and TG on 177 COVID-19 to identify the specific risk lipid. We didn't detect any evidence of pleiotropy as well (all p 178 value > 0.05, Table S1), thus we still chose IVW as the main MR method. We identified TC was a risk 179 factor for the susceptibility of COVID-19 (MR-IVW p-value = 5.07 × 10 -3 , FDR = 1.30 × 10 -2 ) ( Table 1) . (Table 1) . Leave-one-out analysis indicated that no single SNP was driving the causal 184 estimates ( Figure S1 ). We also measured the relationship between four blood lipids and severe COVID- 185 19. Consistent with dyslipidemia, there was no causal effects for blood lipids-COVID-19 severity pairs.

Gene-based and gene-set analyses for TC 188 In our above results, we have discovered the risk effect of TC to the susceptibility of COVID-19. We 189 wonder explain the internal linkage between TC and COVID-19 preliminarily, thus we investigated the 190 potential mechanism of TC by gene-based and gene-set analysis.

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The copyright holder for this preprint this version posted July 7, 2020. Table S2 ). It should be noticed that ABO was identified to be associated with TC significantly (p-value 195 = 6.80 × 10 −11 , FDR = 1.43 × 10 −8 ). Some observational studies have found that the level of blood lipids 196 was related to ABO blood group and Table 2 lists the detailed information about these observational 197 studies [24] [25] [26] [27] [28] [29] . All of these studies provide a conclusion that TC is higher in A or non-O blood group, but 198 lower in O blood group. On the other side, GWAS on severe COVID-19 has revealed the relationship 199 between ABO blood group locus and COVID-19 11 . It has been found a higher risk in blood group A 200 than in other blood group and a protective effect in blood group O, which was coincident with the results 201 of observational investigations based on phenotype [30] [31] [32] . In general, we inferred that the different 202 susceptibility of COVID-19 in specific blood group may be partly explained by the TC levels in diverse 203 ABO blood group ( Figure 3B ).

Gene-set analysis for TC 205 For the GO biological processes, we identified 89 processes significantly associated with TC (FDR < 206 0.05), which are mostly involved in lipid metabolism (Table S3) . For the KEGG pathways, we just 207 identified 2 pathways (Carbohydrate metabolism and Glycan biosynthesis and metabolism) 208 significantly associated with TC after FDR corrections. Besides, we also found 20 KEGG pathways 209 with nominally significant associations with TC (p-value < 0.05) (Table S4 ). In all related CC-BY-NC-ND 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 7, 2020. In this study, we implemented two-sample MR analyses to explore the possible causal associations 219 between blood lipids and COVID-19. We have found potential causal effects of dyslipidemia and blood 220 TC on the infected risk of COVID-19.

To explain the potential influence of TC on COVID-19, we explored the TC-related genes and gene sets. 223 It is notable that ABO gene performs quite strong relevance to TC, which was also reported by previous 224 GWAS of TC 3 . Besides, some observational studies have found that the blood lipids level was related 225 to ABO blood group. The higher level of TC was found in non-O blood group and was significantly 226 associated with an increased prevalence of CVD [24] [25] [26] [27] [28] [29] . In addition, The GWAS of severe COVID-19 has 227 identified the association signal at ABO blood group locus 11 . Based on the blood-group-specific 228 analysis, they observed a higher risk of COVID-19 in blood group A than in other blood group and a 229 protective effect in blood group O, which was coincident with the results of observational investigations 230 based on phenotype [30] [31] [32] . In summary of these results, we inferred that the different susceptibility of 231 COVID-19 in specific blood group may be partly explained by the TC concentration in diverse ABO 232 blood groups.

The result of gene-set analysis identified a total of 89 biological processes and 20 pathways associated 235 . CC-BY-NC-ND 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 7, 2020. . https://doi.org/10.1101/2020.07.07.20147926 doi: medRxiv preprint with TC. Besides the processes/pathways related to lipid metabolism, six processes/pathways belonged 236 to immune system were shown moderate associations with TC, including three pathways related to 237 immunity and immunodeficiency (negative regulation of lymphocyte mediated immunity, antigen 238 processing and presentation, primary immunodeficiency) and other three processes involved in immune and initiate a variety of signals to start immune process. As a disease caused by the SARS-Cov-2, 245 COVID-19 is in close and direct touch with immunity 33 . Therefore, we raise a hypothesis that the risk 246 effect of TC on COVID-19 may be mediated by the dysfunction of immune system.

This is the first study to characterize the potential causality of blood lipids for the susceptibility and 249 severity of COVID-19 using two-sample MR design rather than observational and perspective studies 250 based on conventional association analysis. The limitations of the current study should be addressed.

Due to the limitation of data resource, our findings are based on European cohort which cannot represent 252 the universal conclusions for other ethnic groups. In addition, the potential mechanism of the risk effect 253 for TC was discussed superficially, which needed to carry out further investigation to get more data 254 support and further experimental verification.

In summary, we carried out a two-sample MR design for blood lipids and COVID-19, and obtained 257 . CC-BY-NC-ND 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 7, 2020. . https://doi.org/10.1101/2020.07.07.20147926 doi: medRxiv preprint following conclusions: 1) Dyslipidemia is causally associated with the susceptibility of COVID-19; 2)

The higher total cholesterol level will increase the susceptibility of COVID-19; 3) The different 259 susceptibility of COVID-19 in specific blood group may be partly explained by the TC concentration 260 in diverse ABO blood groups; 4) The risk effect of total cholesterol on COVID-19 may be mediated by 261 the dysfunction of immunity.

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The authors have nothing to disclose. 

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The copyright holder for this preprint this version posted July 7, 2020. . CC-BY-NC-ND 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 7, 2020. . CC-BY-NC-ND 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 7, 2020. . https://doi.org/10.1101/2020.07.07.20147926 doi: medRxiv preprint Table 1 The MR analysis pipeline of the current study.

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The copyright holder for this preprint this version posted July 7, 2020. . https://doi.org/10.1101/2020.07.07.20147926 doi: medRxiv preprint . CC-BY-NC-ND 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)

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The copyright holder for this preprint this version posted July 7, 2020. . https://doi.org/10.1101/2020.07.07.20147926 doi: medRxiv preprint Supporting information Figure S1 . Scatter plot and leave-one-out analysis plot for dyslipidemia and total cholesterol (COVID- 19) . Table S1 . Assessment of pleiotropy for dyslipidemia and blood lipids to COVID-19 and severe COVID-19. Table S2 . Summary of 243 genes significantly associated (FDR < 0.05) with total cholesterol. Table S3 . Summary of 89 biological processes significantly associated (FDR < 0.05) with total cholesterol. Table S4 . Summary of 20 pathways associated (p-value < 0.05) with total cholesterol. . CC-BY-NC-ND 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)

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