The Association between Circulating Lipids and Female Infertility Risk: A Univariable and Multivariable Mendelian Randomization Analysis

Abstract

Background: Although observational studies have demonstrated that blood lipids are associated with female infertility, the causality of this association remains unclear. We performed a univariable and multivariable Mendelian randomization (MR) analysis to evaluate the causal relationship between blood lipids and female infertility. Methods: Single-nucleotide polymorphisms associated with lipid traits in univariate analysis were obtained from the Million Veteran Program (MVP) and Global Lipids Genetics Consortium (GLGC), involving up to 215,551 and 188,577 European individuals, respectively. Blood lipids in multivariate analysis were obtained from the latest genome-wide association study meta-analysis with lipid levels in 73 studies encompassing >300,000 participants. Data on female infertility were obtained from the FinnGen Consortium R6 release, which included 6481 samples and 75,450 controls. Subsequently, MR analysis was performed using inverse variance-weighted (IVW), weighted median, weighted-mode, simple-mode and MR-Egger regression to demonstrate the causal relationship between lipids and female infertility. Results: After controlling confounding factors including body mass index and age at menarche, two-sample MR demonstrated that genetically predicted LDL-C and TC were causally associated with the risk of female infertility (When the genetic instruments come from the MVP database, LDL-C and female infertility, IVW OR: 1.13, 95% CI: 1.001–1.269, p = 0.047; TC and female infertility, IVW OR: 1.16, 95% CI: 1.018–1.317, p = 0.025, and when the genetic instruments came from the GLGC database, LDL-C and female infertility, IVW OR: 1.10, 95% CI: 1.008–1.210, p = 0.033; TC and female infertility, IVW OR: 1.14, 95% CI: 1.024–1.258, p = 0.015). However, the IVW estimate showed that HDL-C was not significantly associated with the risk of female infertility (when the genetic instruments came from the MVP database, IVW OR: 1.00, 95% CI: 0.887–1.128, p = 0.999; when the genetic instruments came from the GLGC database, IVW OR: 1.00, 95% CI: 0.896–1.111, p = 0.968). The multivariable MR analysis also provided evidence that LDL-C (OR: 1.12, 95% CI: 1.006–1.243, p = 0.042) was significantly associated with the risk of female infertility after considering the correlation of all lipid-related traits. Conclusion: These findings support a causal relationship between increased LDL-cholesterol and increased female infertility risk. Furthermore, the association between lipid-related traits and female infertility risk merits more studies.

Evaluation of Lipids and Lipid-Related Transcripts in Human and Ovine Theca Cells and an in Vitro Mouse Model Exposed to the Obesogen Chemical Tributyltin

“… 97 Nevertheless, higher lipid storage in the form of lipid droplets can progressively lead to chronic tissue injury via these cellular stress responses and eventually fibrosis or cancer, such as that reported in fatty liver. 119 , 120 Although associations between systemic dyslipidemia and infertility have been reported, 8 – 12 , 121 , 122 the potential clinical consequences of higher lipid droplet accumulation in ovarian cells remain virtually unexplored.…”

Association between depression and infertility risk among American women aged 18–45 years: the mediating effect of the NHHR

“…Additionally, TG, HDL-C and hs-CRP were identified as independent risk factors for unexplained infertility [ 43 ]. In contrast, an MR study revealed that the likelihood of female infertility was raised by 13% and 16% for every incremental rise in LDL-C and TC levels, respectively, and there was no evidence that HDL-C was prominently related to female infertility risk [ 44 ]. Notably, HDL is the primary lipoprotein present in ovarian follicular fluid (FF), which is mainly derived from plasma [ 45 ].…”

The causal effects of intelligence and fluid intelligence on Parkinson’s disease: a Mendelian randomization study

“…A causal relationship between exposure factors and outcome was indicated only when the p -value of the IVW method was less than 0.05. When assuming that all SNPs are valid IVs, the IVW method can provide a valid estimate of the causal relationship between exposure factors and outcome ( Zhu et al, 2023 ). In addition, the results of MR analysis were visualized through scatter plots, forest plots and funnel plots.…”