Gender-Specific Hormonal Profiles: Unveiling the Complex Link to Stroke Risk
DOI:
https://doi.org/10.70088/8sttq209Keywords:
sex hormone-binding globulin(SHBG), ischemic stroke, mendelian randomization, genetic susceptibility, hormonal influence, gender disparities, lipid metabolism, immune systemAbstract
Stroke affects women more frequently, suggesting a possible link to sex hormones, yet the evidence for this remains inconclusive. Here, we present a pioneering exploration of the nuanced interplay between genetically predicted sex hormone levels, with a particular focus on testosterone and SHBG, to elucidate their causal relationship with stroke risk. Utilizing Mendelian randomization, we aimed to determine whether SHBG levels causally affect stroke occurrence, with a focus on sex-specific effects and the interplay with established stroke risk factors.
We leveraged genetic variants from comprehensive genome-wide association studies (GWAS), which are known to robustly predict levels of total and bioavailable testosterone, SHBG, and cholesterol. Employing a robust statistical approach, we meticulously analyzed published GWAS summary statistics, applying inverse variance weighting and conducting comprehensive sensitivity analyses with state-of-the-art methods such as MR-Egger, weighted median, and MR-PRESSO. Multivariate analyses further addressed potential confounders, including pleiotropic effects and selection bias.
Strikingly, our results demonstrate that elevated SHBG levels are robustly associated with a markedly reduced stroke risk in women. In contrast, lower SHBG levels were associated with an increased risk of small-vessel ischemic stroke, potentially due to elevated cholesterol. These novel insights not only highlight the intricate interplay among SHBG, cholesterol, and immune system components in the pathogenesis of stroke but also illuminate avenues for future research aimed at unraveling the underlying biological mechanisms.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Ganggui Lu, Man Zhang, Facai Meng, Kaifei Liu, Yi Zhang (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.