Journal List > J Rheum Dis > v.26(2) > 1122081

Lee and Song: Causal Association between Rheumatoid Arthritis with the Increased Risk of Type 2 Diabetes: A Mendelian Randomization Analysis

Abstract

Objective

This study aimed to examine whether rheumatoid arthritis (RA) is causally associated with type 2 diabetes (T2D).

Methods

We performed a two-sample Mendelian randomization (MR) analysis using the inverse-variance weighted (IVW), weighted median, and MR-Egger regression methods. We used the publicly available summary statistics datasets from a genomewide association studies (GWAS) meta-analysis of 5,539 autoantibody-positive individuals with RA and 20,169 controls of European descent, and a GWAS dataset of 10,247 individuals with T2D and 53,924 controls, overwhelmingly of European descent as outcomes.

Results

We selected 10 single-nucleotide polymorphisms from GWAS data on RA as instrumental variables to improve the inference. The IVW method supported a causal association between RA and T2D (β=0.044, standard error [SE]=0.022, p=0.047). The MR-Egger analysis showed a causal association between RA and T2D (β=0.093, SE=0.033, p=0.023). In addition, the weighted median approach supported a causal association between RA and T2D (β=0.056, SE=0.025, p=0.028). The association between RA and T2D was consistently observed using IVW, MR Egger, and weighted median methods. Cochran's Q test indicated no evidence of heterogeneity between instrumental variable estimates based on individual variants and MR-Egger regression revealed that directional pleiotropy was unlikely to have biased the results (in-tercept=−0.030; p=0.101).

Conclusion

MR analysis supports that RA may be causally associated with an increased risk of T2D.

REFERENCES

1. Edwards CJ, Cooper C. Early environmental factors and rheumatoid arthritis. Clin Exp Immunol. 2006; 143:1–5.
crossref
2. Lee YH, Bae SC, Choi SJ, Ji JD, Song GG. Genomewide pathway analysis of genomewide association studies on systemic lupus erythematosus and rheumatoid arthritis. Mol Biol Rep. 2012; 39:10627–35.
crossref
3. Prentki M, Nolan CJ. Islet beta cell failure in type 2 diabetes. J Clin Invest. 2006; 116:1802–12.
4. Avina-Zubieta JA, Thomas J, Sadatsafavi M, Lehman AJ, Lacaille D. Risk of incident cardiovascular events in patients with rheumatoid arthritis: a meta-analysis of observational studies. Ann Rheum Dis. 2012; 71:1524–9.
crossref
5. Shah AD, Langenberg C, Rapsomaniki E, Denaxas S, Pujades-Rodriguez M, Gale CP, et al. Type 2 diabetes and incidence of cardiovascular diseases: a cohort study in 1· 9 million people. Lancet Diabetes Endocrinol. 2015; 3:105–13.
6. Nicolau J, Lequerré T, Bacquet H, Vittecoq O. Rheumatoid arthritis, insulin resistance, and diabetes. Joint Bone Spine. 2017; 84:411–6.
crossref
7. Solomon DH, Love TJ, Canning C, Schneeweiss S. Risk of diabetes among patients with rheumatoid arthritis, psoriatic arthritis and psoriasis. Ann Rheum Dis. 2010; 69:2114–7.
crossref
8. Su CC, Chen IeC, Young FN, Lian IeB. Risk of diabetes in patients with rheumatoid arthritis: a 12-year retrospective cohort study. J Rheumatol. 2013; 40:1513–8.
crossref
9. Simard JF, Mittleman MA. Prevalent rheumatoid arthritis and diabetes among NHANES III participants aged 60 and older. J Rheumatol. 2007; 34:469–73.
10. Ozen G, Pedro S, Holmqvist ME, Avery M, Wolfe F, Michaud K. Risk of diabetes mellitus associated with disease-modifying antirheumatic drugs and statins in rheumatoid arthritis. Ann Rheum Dis. 2017; 76:848–54.
crossref
11. Jiang P, Li H, Li X. Diabetes mellitus risk factors in rheumatoid arthritis: a systematic review and meta-analysis. Clin Exp Rheumatol. 2015; 33:115–21.
12. Burgess S, Daniel RM, Butterworth AS, Thompson SG. EPIC-InterAct Consortium. Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways. Int J Epidemiol. 2015; 44:484–95.
crossref
13. Lawlor DA. Commentary: two-sample Mendelian randomization: opportunities and challenges. Int J Epidemiol. 2016; 45:908–15.
crossref
14. Stahl EA, Raychaudhuri S, Remmers EF, Xie G, Eyre S, Thomson BP, et al. Genomewide association study meta-analysis identifies seven new rheumatoid arthritis risk loci. Nat Genet. 2010; 42:508–14.
15. Morris AP, Voight BF, Teslovich TM, Ferreira T, Segrè AV, Steinthorsdottir V, et al. Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat Genet. 2012; 44:981–90.
crossref
16. Burgess S, Butterworth A, Thompson SG. Mendelian randomization analysis with multiple genetic variants using summarized data. Genet Epidemiol. 2013; 37:658–65.
crossref
17. Okada Y, Wu D, Trynka G, Raj T, Terao C, Ikari K, et al. Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature. 2014; 506:376–81.
18. Pierce BL, Burgess S. Efficient design for Mendelian randomization studies: subsample and 2-sample instrumental variable estimators. Am J Epidemiol. 2013; 178:1177–84.
crossref
19. Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol. 2015; 44:512–25.
crossref
20. Burgess S, Thompson SG. Interpreting findings from Mendelian randomization using the MR-Egger method. Eur J Epidemiol. 2017; 32:377–89.
crossref
21. Bowden J, Davey Smith G, Haycock PC, Burgess S. Consistent estimation in Mendelian randomization with some invalid instruments using a weighted median estimator. Genet Epidemiol. 2016; 40:304–14.
crossref
22. Hemani G, Zheng J, Wade KH, Laurin C, Elsworth B, Burgess S, et al. MR-Base: a platform for systematic causal inference across the phenome using billions of genetic associations. bioRxiv. 2016; DOI: DOI: 10.1101/078972.
crossref
23. Egger M, Smith GD, Phillips AN. Meta-analysis: principles and procedures. BMJ. 1997; 315:1533–7.
crossref
24. Popa C, Netea MG, van Riel PL, van der Meer JW, Stalenhoef AF. The role of TNF-alpha in chronic inflammatory conditions, intermediary metabolism, and cardiovascular risk. J Lipid Res. 2007; 48:751–62.
25. Song GG, Bae SC, Lee YH. Association between vitamin D intake and the risk of rheumatoid arthritis: a meta-analysis. Clin Rheumatol. 2012; 31:1733–9.
crossref
26. Viswanathan M, Berkman ND, Dryden DM, Hartling L. Assessing risk of bias and confounding in observational studies of interventions or exposures: further development of the RTI item bank. Rockville (MD): Agency for Healthcare Research and Quality (US);. 2013; Aug. Report No.: 13-EHC106-EF 2013.
27. Smith GD, Ebrahim S. Mendelian randomization: genetic variants as instruments for strengthening causal inference in observational studies. Weinstein M, Vaupel JW, Wachter KW, editors. Biosocial surveys. Washington (DC): National Academies Press (US);2008.
28. Smith GD, Ebrahim S. Mendelian randomization: prospects, potentials, and limitations. Int J Epidemiol. 2004; 33:30–42.
crossref
29. Swerdlow DI, Kuchenbaecker KB, Shah S, Sofat R, Holmes MV, White J, et al. Selecting instruments for Mendelian randomization in the wake of genomewide association studies. Int J Epidemiol. 2016; 45:1600–16.
crossref

Figure 1.
Forest plot of the causal effects of rheumatoid arthri-tis-associated single-nucleotide polymorphisms on type 2 diabetes. MR: Mendelian randomization, IVW: inverse-variance weighted.
jrd-26-131f1.tif
Figure 2.
Scatter plots of the genetic associations of rheumatoid arthritis against those of type 2 diabetes. The slopes of each line represent the causal association for each method. Blue line represents the inverse-variance weighted estimate, green line represents the weighted median estimate, and dark blue line represents the MR-Egger estimate. SNP: single-nucleotide polymorphism.
jrd-26-131f2.tif
Table 1.
Instrumental single-nucleotide polymorphisms associated with RA and T2D GWASs
Instrumental SNP Gene Chromosome loci Effect allele Exposure (RA) Outcome (T2D)
Beta SE p-value Beta SE p-value
rs10040327 IL6ST 5 A −0.288 0.044 6.65E-11 −0.037 0.039 0.344
rs3087243 CTLA4 2 A −0.139 0.023 2.24E-08 0.014 0.023 0.534
rs396458 CYP21A2 6 G −0.528 0.035 9.15E-50 0.043 0.033 0.195
rs460568 C6orf120 6 T 0.262 0.031 3.81E-16 0.027 0.032 0.391
rs4810485 CD40 20 T −0.163 0.030 5.69E-09 0.016 0.026 0.538
rs6679677 DCLRE1B 1 A 0.663 0.038 4.39E-70 −0.007 0.036 0.855
rs6920220 LOC102723649 6 A 0.199 0.029 2.49E-12 −0.008 0.028 0.777
rs9268145 C6orf10 6 G 1.058 0.027 <5.00E-08 0.089 0.028 0.001
rs9277412 HLA-DPB1 6 T −0.357 0.029 1.80E-39 0.014 0.025 0.564
rs9784876 TAP2 6 A 0.668 0.047 2.40E-46 0.067 0.042 0.110

RA: rheumatoid arthritis, T2D: type 2 diabetes, GWAS: genomewide association study, SNP: single-nucleotide polymorphism, Beta: beta coefficient, SE: standard error, IL6ST: interleukin 6 signal transducer, CTLA4: cytotoxic T-lymphocyte-associated protein 4, CYP21A2: cytochrome P450 family 21 subfamily A member 2, C6orf120: chromosome 6 open reading frame 120, CD40: cluster of differentiation 40, DCLRE1B: DNA crosslink repair 1B, LOC102723649: uncharacterized LOC102723649, C6orf10: chromosome 6 open reading frame 10, HLA-DPB1: major histocompatibility complex, Class II, DP Beta 1, TAP2: transporter 2, ATP binding cassette subfamily B member.

Table 2.
MR estimates from each method used to determine the causal effect of rheumatoid arthritis on the risk of type 2 diabetes
MR method Number of SNPs Beta coefficient Standard error Association p-value Cochran Q-statistic Heterogeneity p-value
Inverse variance weighted 10 0.044 0.022 0.047 12.14 0.206
MR-Egger 10 0.093 0.033 0.023 8.50 0.387
Weighted median 10 0.056 0.025 0.028 NA NA

MR: Mendelian randomization, SNP: single-nucleotide polymorphism, NA: not available.

TOOLS
Similar articles