In this two-sample MR analysis, we found genetic support for a causal association between higher educational attainment and lower risk of RA. On the basis of the intercept estimates of the pleiotropy test, we found no evidence of pleiotropy that likely influenced our results.
In fact, education inequalities in risk of RA have long been noted. Pincus and colleagues identified an association between a lower level of formal education and higher mortality and morbidity related to RA over a 9-year period. Another study found that formal education level can be a significant marker of clinical status in RA. However, some studies have revealed that level of formal education is not significantly associated with risk of RA[27, 28].
Given that these studies with inconsistent conclusions were either based on limited samples or only explored correlations from epidemiological observational studies, few studies have clearly and consistently demonstrated a biological link underlying this association. By applying MR analysis in the current study to alleviate these problems, we provided concrete evidence to support an inverse association of educational attainment with risk of RA. The credibility of this study was verified by using several data sources with large sample sizes. A previous two-sample MR study conducted by Bae and Lee used statistical data of years of education from the UK Biobank GWAS (n = 293,723) as the exposure and a meta-analysis of GWAS of RA with autoantibody (n = 5,539) and European controls (n = 20,169) as the outcome. Here, we expanded the exposure sample size to over 1 million individuals (N = 1,131,881) and chose the latest meta-analysis of GWAS, which included 58,284 individuals of European ancestry (14,361 RA cases and 43,923 controls). Furthermore, individuals with RA who were seropositive and seronegative for ACPA or RF were enrolled in this MR analysis. Thus, the causative association between educational attainment and risk of RA were fully explored in patients with RA.
In total, the identified exposure SNPs accounted for approximately 11% of the variance in educational attainment. The effect size of the independent SNPs corresponding to an educational increase was obtained as follows: the median effect size corresponded to 1.7 weeks of schooling per allele (95% CI: 1.1–2.6 weeks). Furthermore, the genes related to these SNPs are involved in almost all aspects of neuron-to-neuron communication. The dramatic increase in our sample size enabled us to promote the power of the test.
To obtain unbiased estimates, MR needs to fulfill three key assumptions: (1) genetic variants should be strongly associated with the exposure; (2) genetic variants extracted for exposure should be independent of any confounder; and (3) the genetic variants affect the outcome only through the exposure. The MR approach, which is the closest approximation to a randomized controlled trial, offers one of the most compelling methods to determine causation if there are confounders, because it can minimize the effect of the confounding factors and provide sufficient statistical power for causal estimation.
We used three different methods of estimation for the MR analyses: IVW, weighted median, and MR-Egger method. The IVW and weighted median analyses suggested a negative causal association between educational attainment and RA, whereas the MR-Egger method showed no proof of a causative association between educational attainment and RA. However, the MR-Egger test leads to a loss of precision and power. The weighted median method, which is not influenced by outlying genetic variants, improves the power of causal effect detection and effectively decreases type I error. Therefore, the weighted median method has a distinct advantage over the MR-Egger test, and its results in this study were the same as those of the IVW method.
The results of our MR analysis might be biased by pleiotropy. Heterogeneity tests suggested an apparent sign of heterogeneity (Q value(df) = 594.21(372), p = 1.82×10− 12). However, heterogeneity was decreased after removing the outlying SNP (Q value(df) = 425.7(371), p = 0.03). Additionally, there was no indication of pleiotropy (p intercept = 0.34). Therefore, we deemed that the conclusion would not be biased significantly by the heterogeneity of the analysis because several robust methods were performed, which can provide reliable inferences and statistical support when some genetic variants violate the assumptions.
The major strength of this study is that the MR design allowed us to investigate the causal association between educational attainment and RA using a large sample size. However, the study has several limitations. The summary GWAS data were restricted to individuals of European descent, and, because ethnicity may affect causality, our results may not be fully representative of the whole population. Another limiting factor was that this applied analysis could not be stratified by sex and age; thus, we could not assess sex discrepancies and potential nonlinear associations.
In conclusion, our aim in this study was to assess the causal effect of educational attainment and risk of RA by using two-sample MR analysis. An updated MR analysis is warranted to confirm our findings of a potential causal association between increased educational attainment and lower risk of RA. These results advocate the current clinical practice for RA surveillance in patients with lower educational attainment.