Genetic evidence for causal relationships between age at natural menopause and the risk of ageing-associated adverse health outcomes

The causal effects of age at menarche and age at menopause on sepsis: A two-sample Mendelian randomization analysis

OBJECTIVES

To determine whether the age at menarche (AAM) and the age at menopause (ANM) are causally related to the development of sepsis.

METHODS

We performed a two-sample Mendelian randomization (MR) analysis by utilizing summary statistics from genome-wide association study (GWAS) datasets for both the exposure and outcome variables. Single nucleotide polymorphisms (SNPs) that exhibited significant associations with AAM and ANM were chosen as instrumental variables to estimate the causal effects on sepsis. Our study employed a variety of methods, including MR-Egger regression, weighted median estimation, inverse variance weighting, a simple model, and a weighted model. Odds ratios (ORs) along with their corresponding 95% confidence intervals (CIs) were used as the primary indicators for assessing causality. Furthermore, we conducted sensitivity analyses to explore the presence of genetic heterogeneity and validate the robustness of the tools employed.

RESULT

Our analysis revealed a significant negative causal relationship between AAM and the risk of sepsis (IVW: OR = 0.870, 95% CI = 0.793-0.955, P = 0.003). However, our Mendelian randomization (MR) analysis did not yield sufficient evidence to support a causal link between ANM and sepsis (IVW: OR = 0.987, 95% CI = 0.971-1.004, P = 0.129).

CONCLUSIONS

Our findings suggest that an earlier AAM may be associated with an increased risk of sepsis. However, we did not find sufficient evidence to support a causal relationship between ANM and sepsis.

Age at Menopause and the Risk of Stroke: Observational and Mendelian Randomization Analysis in 204 244 Postmenopausal Women

Background Observational studies have shown that women with an early menopause are at higher risk of stroke compared with women with a later menopause. However, associations with stroke subtypes are inconsistent, and the causality is unclear. Methods and Results We analyzed data of the UK Biobank and EPIC-CVD (European Prospective Investigation Into Cancer and Nutrition-Cardiovascular Diseases) study. A total of 204 244 postmenopausal women without a history of stroke at baseline were included (7883 from EPIC-CVD [5292 from the subcohort], 196 361 from the UK Biobank). Pooled mean baseline age was 58.9 years (SD, 5.8), and pooled mean age at menopause was 47.8 years (SD, 6.2). Over a median follow-up of 12.6 years (interquartile range, 11.8-13.3), 6770 women experienced a stroke (5155 ischemic strokes, 1615 hemorrhagic strokes, 976 intracerebral hemorrhages, and 639 subarachnoid hemorrhages). In multivariable adjusted observational Cox regression analyses, the pooled hazard ratios per 5 years younger age at menopause were 1.09 (95% CI, 1.07-1.12) for stroke, 1.09 (95% CI, 1.06-1.13) for ischemic stroke, 1.10 (95% CI, 1.04-1.16) for hemorrhagic stroke, 1.14 (95% CI, 1.08-1.20) for intracerebral hemorrhage, and 1.00 (95% CI, 0.84-1.20) for subarachnoid hemorrhage. When using 2-sample Mendelian randomization analysis, we found no statistically significant association between genetically proxied age at menopause and risk of any type of stroke. Conclusions In our study, earlier age at menopause was related to a higher risk of stroke. We found no statistically significant association between genetically proxied age at menopause and risk of stroke, suggesting no causal relationship.

Review of mendelian randomization studies on age at natural menopause

Menopause marks the end of the reproductive phase of life. Based on epidemiological studies, abnormal age at natural menopause (ANM) is thought to contribute to a number of adverse outcomes, such as osteoporosis, cardiovascular disease, and cancer. However, the causality of these associations remains unclear. A powerful epidemiological method known as Mendelian randomization (MR) can be used to clarify the causality between ANM and other diseases or traits. The present review describes MR studies that included ANM as an exposure, outcome and mediator. The findings of MR analyses on ANM have revealed that higher body mass index, poor educational level, early age at menarche, early age at first live birth, early age at first sexual intercourse, and autoimmune thyroid disease appear to be involved in early ANM etiology. The etiology of late ANM appears to be influenced by higher free thyroxine 4 and methylene tetrahydrofolate reductase gene mutations. Furthermore, early ANM has been found to be causally associated with an increased risk of osteoporosis, fracture, type 2 diabetes mellitus, glycosylated hemoglobin, and the homeostasis model of insulin resistance level. In addition, late ANM has been found to be causally associated with an increased systolic blood pressure, higher risk of breast cancer, endometrial cancer, endometrioid ovarian carcinoma, lung cancer, longevity, airflow obstruction, and lower risk of Parkinson's disease. ANM is also a mediator for breast cancer caused by birth weight and childhood body size. However, due to the different instrumental variables used, some results of studies are inconsistent. Future studies with more valid genetic variants are needed for traits with discrepancies between MRs or between MR and other types of epidemiological studies.

Genetic causal relationship between age at menarche and benign oesophageal neoplasia identified by a Mendelian randomization study

OBJECTIVE

The occurrence and development of oesophageal neoplasia (ON) is closely related to hormone changes. The aim of this study was to investigate the causal relationships between age at menarche (AAMA) or age at menopause (AAMO) and benign oesophageal neoplasia (BON) or malignant oesophageal neoplasia (MON) from a genetic perspective.

METHODS

Genome-wide association study (GWAS) summary data of exposures (AAMA and AAMO) and outcomes (BON and MON) were obtained from the IEU OpenGWAS database. We performed a two-sample Mendelian randomization (MR) study between them. The inverse variance weighted (IVW) was used as the main analysis method, while the MR Egger, weighted median, simple mode, and weighted mode were supplementary methods. The maximum likelihood, penalized weighted median, and IVW (fixed effects) were validation methods. We used Cochran's Q statistic and Rucker's Q statistic to detect heterogeneity. The intercept test of the MR Egger and global test of MR pleiotropy residual sum and outlier (MR-PRESSO) were used to detect horizontal pleiotropy, and the distortion test of the MR-PRESSO analysis was used to detect outliers. The leave-one-out analysis was used to detect whether the MR analysis was affected by single nucleotide polymorphisms (SNPs). In addition, the MR robust adjusted profile score (MR-RAPS) method was used to assess the robustness of MR analysis.

RESULTS

The random-effects IVW results showed that AAMA had a negative genetic causal relationship with BON (odds ratio [OR] = 0.285 [95% confidence interval [CI]: 0.130-0.623], P = 0.002). The weighted median, maximum likelihood, penalized weighted median, and IVW (fixed effects) were consistent with random-effects IVW (P < 0.05). The MR Egger, simple mode and weighted mode results showed that AAMA had no genetic causal relationship with BON (P > 0.05). However, there were no causal genetic relationships between AAMA and MON (OR = 1.132 [95%CI: 0.621-2.063], P = 0.685), AAMO and BON (OR = 0.989 [95%CI: 0.755-1.296], P = 0.935), or AAMO and MON (OR = 1.129 [95%CI: 0.938-1.359], P = 0.200). The MR Egger, weighted median, simple mode, weighted mode, maximum likelihood, penalized weighted median, and IVW (fixed effects) were consistent with a random-effects IVW (P > 0.05). MR analysis results showed no heterogeneity, the horizontal pleiotropy and outliers (P > 0.05). They were not driven by a single SNP, and were normally distributed (P > 0.05).

CONCLUSION

Only AAMA has a negative genetic causal relationship with BON, and no genetic causal relationships exist between AAMA and MON, AAMO and BON, or AAMO and MON. However, it cannot be ruled out that they are related at other levels besides genetics.