An Appraisal of the Role of Previously Reported Risk Factors in the Age at Menopause Using Mendelian Randomization

Abstract

Objective: Menopause at a young age is associated with many health problems in women, including osteoporosis, depressive symptoms, coronary disease, and stroke. Many traditional observational studies have reported some potential risk factors for early menopause but have drawn different conclusions. This inconsistency can be attributed mainly to unmodified confounding factors. Identifying the factors causally associated with age at menopause is important for early intervention in women with abnormal menopause timing, and for improving the quality of life for postmenopausal women. This study aims to appraise whether the previously reported risk factors are causally associated with early age at natural menopause (ANM) susceptibility. Methods: We used Mendelian randomization, a statistical method wherein genetic variants are used to determine whether an observational association between a risk factor and an outcome is consistent with a causal effect. Results: Women with earlier age at menarche (β = 0.34, se = 0.16, p = 0.035), lower education level (β = 1.19, se = 0.41, p = 0.004) and higher body mass index (β = −0.05, se = 0.02, p = 0.027) had greater risk for early ANM. The causal link between early age at menarche and early ANM was replicated using ReproGen consortium data (β = 0.23, se = 0.07, p = 0.001). However, a current smoking habit, one of previously reported risk factors, was less likely to be correlated causally with early ANM, suggesting that previous observational studies may not have sufficiently adjusted for confounders. Conclusion: Our results help to identify the risk factors of ANM via a genetics approach and future research into the biological mechanism could further help with targeted prevention for early menopause.

The relationships between women’s reproductive factors: a Mendelian randomization analysis

“…We substantiate the genetic correlation between reproductive factors shown in previous studies, while showing additional correlations that have not been previously investigated. (57,58) Our study supports evidence for a positive causal link between AAM and age at menopause, (11)(12)(13)(14)(15)(16)59,60) and opposes previous studies that have shown the inverse association, (17,18) or no association. (19)(20)(21)(22)(23)(24) Furthermore our findings support one study that found little evidence for an association between AAM and parity.…”

“…(26) Additionally, we corroborated the findings of previous MR studies that identified a positive causal relationship between AAM and AFB, ALB and age at menopause, and between AFS and ALB. (59)(60)(61) Many estimates identified in the primary analysis appear consistent across sensitivity analyses that aim to account for biases. However, some results did not persist in sensitivity analyses checking for robustness to sample overlap and winner's curse.…”

Shared Genetics Between Age at Menopause, Early Menopause, POI and Other Traits

“…Furthermore, a GRS for adult BMI increasing variants with BMI profiles from early to late adulthood showed that this association was strongest in women with EM (Song et al, 2018). However, (bidirectional) MR analysis did not identify evidence for a causal relationship between ANM and BMI (Day et al, 2015;Ruth et al, 2021;Sarnowski et al, 2018), while a study of Ding et al suggests that there is genetic support for a causal association between higher BMI and earlier ANM (Ding et al, 2020). These contrasting results are likely due to differences in SNP selection and differences in sample size.…”

Prevalence and Risk Factors of Premature Ovarian Insufficiency/Early Menopause

“…Observational associations do not indicate causation; however, more recent mendelian analyses suggest causation by linking single nucleotide polymorphisms (SNPs) with risk factors for earlier menopause including earlier age at menarche and lower education level. 21 We will discuss risk factors for POI and early menopause which is divided into the following categories: (1) genetic factors, (2) family history, (3) autoimmunity, (4) early life factors, (5) reproductive factors, (6) lifestyle factors, (7) environmental factors, and (8) iatrogenic factors (summarized in ►Fig. 1 and ►Table 1).…”