Assessing causal relationships between COVID-19 and non-alcoholic fatty liver disease
Authors: Dong Liu, Qianlong Zhang, Pinqing Bai, Jian Zhao
Journal: Journal of Hepatology (2021)

We read with great interest two manuscripts by Ji et al. and Valenti et al. Recently, Ji et al. found that patients with coronavirus disease 2019 (COVID-19) had a higher risk of liver injury or severe outcomes, and meanwhile, patients with non-alcoholic fatty liver disease (NAFLD) had an increased risk of progression to severe COVID-19 infection.[1]Ji D. Qin E. Xu J. Zhang D. Cheng G. Wang Y. et al.Non-alcoholic fatty liver diseases in patients with COVID-19: a retrospective study.J Hepatol. 2020; 73: 451-453Abstract Full Text Full Text PDF PubMed Scopus (382) Google Scholar However, more recently, Valenti et al. found that metabolic-associated fatty liver disease (MAFLD) may not associate with the susceptibility and severity of COVID-19.[2]Valenti L. Jamialahmadi O. Romeo S. Lack of genetic evidence that fatty liver disease predisposes to COVID-19.J Hepatol. 2020; 73: 709-711Abstract Full Text Full Text PDF PubMed Scopus (24) Google Scholar Thus, causal relationships between COVID-19 and NAFLD still remain unclear. In this work, we conducted a bidirectional two-sample Mendelian randomization (MR) analysis to examine causal relationships between COVID-19 susceptibility/severity (including COVID-19 infection, COVID-19 hospitalization, and severe COVID-19 symptoms) and NAFLD. MR is a causal inference approach that uses genetic variants as instrumental variables (IVs) to draw causal inferences between risk factors and health outcomes in observational study settings. It could overcome problems of confounding and reverse causality and is widespread for assessing causal relationships.[3]Davey Smith G. Hemani G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies.Hum Mol Genet. 2014; 23: R89-R98Crossref PubMed Scopus (1687) Google Scholar For COVID-19, we used data from the latest and largest genome-wide association study (GWAS), COVID-19 Host Genetics Initiative (COVID-19 HGI) (N = 2,586,691), which was released on June 15, 2021.[4]COVID-19 Host Genetics InitiativeThe COVID-19 Host Genetics Initiative, a global initiative to elucidate the role of host genetic factors in susceptibility and severity of the SARS-CoV-2 virus pandemic.Eur J Hum Genet. 2020; 28: 715-718Crossref PubMed Scopus (461) Google Scholar Three subgroups of European ancestry COVID-19 case-control studies included Group 1: COVID-1-infected cases vs. population (case = 87,870 and control = 2,210,804), Group 2: hospitalized COVID-19 cases vs. population (case = 17,992 and control = 1,810,493), and Group 3: very severe respiratory confirmed COVID-19 cases vs. population (case = 4,606 and control = 702,801). Group 1 and Group 2 used the latest Round 6 data, and Group 3 used Round 5 data due to lacking of the latest wave of European ancestry data. We used the latest European ancestry UK Biobank (UKB) GWAS results of NAFLD (1,687 cases and 398,277 controls), which were based on TOPMed imputed data and analyzed using SAIGE (https://pheweb.org/UKB-TOPMed/). The NAFLD outcome in UKB GWAS was defined according to the ICD-9 571.8 "Other chronic non-alcoholic liver disease". Although this definition of NAFLD might not include all clinical or histological cases, we found that the top hits of this GWAS included previously identified loci for NAFLD. The COVID-19 GWAS was adjusted for sex, ancestry and date of sample collection, and the UKB GWAS was adjusted for sex, birth year and first 4 principal components. All the genetic IVs selected in our study were genome-wide significant (p <5×10-8) with minor allele frequency greater than 1%. After linkage disequilibrium (LD) clumping (clumping with window = 10,000 kb, R2 = 0.001 in PLINK 1.9), there were 7 single nucleotide polymorphisms (SNPs) remaining for COVID-19 infection, 10 SNPs for hospitalized COVID-19, 8 SNPs for severe COVID-19, and 4 SNPs for NAFLD, respectively (Fig. 1A). In the main MR analysis, we performed separate two-sample MR analyses with three COVID-19 phenotypes (i.e., COVID-19 infection, COVID-19 hospitalization, and COVID-19 severity) as exposures and NAFLD as the outcome. To further understand the causal effect of NAFLD on each COVID-19 phenotype, 4 genome-wide significant SNPs for NAFLD were selected as IVs. For the main analysis, we implemented the multiplicative random effect inverse-variance weighted (IVW) method to generate a causal estimate using the TwoSampleMR package.[5]Hemani G. Zheng J. Elsworth B. Wade K.H. Haberland V. Baird D. et al.The MR-Base platform supports systematic causal inference across the human phenome.Elife. 2018; 7Crossref PubMed Scopus (2573) Google Scholar Moreover, we conducted sensitivity analyses, including MR Egger regression, weighted median, and MR-PRESSO, to account for potential heterogeneity and horizontal pleiotropy (supplementary information). p values less than 0.05 were considered statistically significant. As shown in Fig. 1, the IVW analysis generated little evidence of a causal effect of COVID-19 infection (odds ratio (OR) 1.054; 95% CI 0.696 –1.596), COVID-19 hospitalization (OR 0.973; 95% CI 0.750–1.263), and severe COVID-19 (OR 0.919; 95% CI 0.839–1.007) on NAFLD. Meanwhile, NAFLD did not appear to have a causal effect on COVID-19 infection (OR 0.991; 95% CI 0.970–1.013), hospitalization (OR 0.991; 95% CI 0.896–1.096) or severe COVID-19 (OR 0.904; 95% CI 0.731–1.118). All the sensitivity analyses showed broadly consistent results. No significant horizontal pleiotropy was detected by MR Egger regression or MR-PRESSO. Detailed MR Egger regression intercepts and MR-PRESSO global test results are presented in Table S1-S2. There was no evidence derived from this work to support causal relationships between COVID-19 susceptibility/severity and NAFLD, which are consistent with results from previous genetic studies.[2]Valenti L. Jamialahmadi O. Romeo S. Lack of genetic evidence that fatty liver disease predisposes to COVID-19.J Hepatol. 2020; 73: 709-711Abstract Full Text Full Text PDF PubMed Scopus (24) Google Scholar,[6]Bianco C. Baselli G. Malvestiti F. Santoro L. Pelusi S. Manunta M. et al.Genetic insight into COVID-19-related liver injury.Liver Int. 2021; 41: 227-229Crossref PubMed Scopus (9) Google Scholar On the contrary, Innes et al. found that the rs738409 C>G variant in patatin-like phospholipase domain-containing protein 3 (PNPLA3), which is well studied in the genetic regulation of NAFLD and liver injury, played a protective role in COVID-19 severity.[7]Innes H. Buch S. Barnes E. Hampe J. Marjot T. Stickel F. The rs738409 G allele in PNPLA3 is associated with a reduced risk of COVID-19 mortality and hospitalization.Gastroenterology. 2021; 160: 2599-2601 e2592Abstract Full Text Full Text PDF PubMed Scopus (9) Google Scholar Previous observational studies revealed that COVID-19-infected patients had an increased risk of liver injury,[8]Zhang C. Shi L. Wang F.S. Liver injury in COVID-19: management and challenges.Lancet Gastroenterol Hepatol. 2020; 5: 428-430Abstract Full Text Full Text PDF PubMed Scopus (1308) Google Scholar,[9]Marjot T. Webb G.J. Barritt A. St Moon A.M. Stamataki Z. Wong V.W. et al.COVID-19 and liver disease: mechanistic and clinical perspectives.Nat Rev Gastroenterol Hepatol. 2021; 18: 348-364Crossref PubMed Scopus (229) Google Scholar however, unmeasured/unmeasurable confounding cannot be ruled out in conventional multivariable regression analysis. In fact, our findings derived from the MR analysis could minimize confounding bias or reverse causation.[3]Davey Smith G. Hemani G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies.Hum Mol Genet. 2014; 23: R89-R98Crossref PubMed Scopus (1687) Google Scholar It is worthy of note that collider bias, which could distort the relationship between exposures and outcomes, existed in many observational studies and cannot be completely overcome by MR.[10]Griffith G.J. Morris T.T. Tudball M.J. Herbert A. Mancano G. Pike L. et al.Collider bias undermines our understanding of COVID-19 disease risk and severity.Nat Commun. 2020; 11: 5749Crossref PubMed Scopus (439) Google Scholar To investigate the potential impact of collider bias on the MR estimation, we replicated the bidirectional two-sample MR analysis using data from a previously published GWAS by Namjou et al., where genetic associations might be biased due to adjusting for a collider variable (e.g., BMI). Details on methods, results, and directed acyclic graph are included in the supplementary information. Future larger randomly sampled cohort studies on COVID-19 and NAFLD and rigorous statistical analysis might be helpful to minimize the impact of collider bias. In conclusion, we found little evidence to support a causal relationship between COVID-19 susceptibility/severity and NAFLD. The authors received no financial support to produce this work. All authors drafted and reviewed this manuscript. The authors declare no conflicts of interest that relate to this work. Please refer to the accompanying ICMJE disclosure forms for further details. The following are the supplementary data to this article: Download .pdf (.63 MB) Help with pdf files Multimedia component 1 Download .pdf (.26 MB) Help with pdf files Multimedia component 2