Age at menarche, age at natural menopause, and risk of rheumatoid arthritis – a Mendelian randomization study.

Hormonal reproductive factors have been suggested to play an important role in the etiology of rheumatoid arthritis (RA), an autoimmune inflammatory disorder affecting primarily women. We conducted a two-sample Mendelian randomization (MR) study examining three relevant exposures, age at menarche (AAM), age at natural menopause (ANM), and age at first birth (AFB) with the risk of RA.
We collected summary statistics from the hitherto largest GWAS conducted in AAM (N = 329,345), ANM (N = 69,360), AFB (N = 251,151), and RA (N = 14,361, N = 43,923), all of European ancestry. We constructed strong instruments using hundreds of exposure-associated genetic variants and estimated causal relationship through different MR approaches including an inverse-variance weighted method, an MR-Egger regression and a weighted median method. We conducted a multivariable MR to control for pleiotropic effect acting in particular through obesity and socioeconomic status. We also performed important sensitivity analyses to verify model assumptions.
We did not find any evidence in support for a causal association between genetically predicted reproductive factors and risk of RA (OR = 1.06 [0.98-1.15]; OR = 1.05 [0.98-1.11], OR  = 0.85 [0.65-1.10]). Results remained consistent after removing palindromic SNPs (OR = 1.06 [0.97-1.15], OR = 1.05 [0.98-1.13], OR = 0.81 [0.61-1.07]) or excluding SNPs associated with potential confounding traits (OR = 1.03 [0.94-1.12], OR = 1.04 [0.95-1.14]). No outlying instrument was identified through the leave-one-out analysis.
Our MR study does not convincingly support a casual effect of reproductive factors, as reflected by age at menarche, age at menopause, and age at first birth, on the development of RA. Despite the largely augmented set of instruments we used, these instruments only explained a modest proportion of phenotypic variance of exposures. Our knowledge regarding this topic is still insufficient and future studies with larger sample size should be designed to replicate or dispute our findings.