背景:虽然已经广泛研究了抗苗勒管激素(AMH)与绝经年龄之间的表型关联,AMH在预测绝经年龄中的作用目前是有争议的,这两个特征的遗传结构或因果关系还没有得到很好的理解。
目的:我们旨在探索AMH与绝经年龄之间的共同遗传结构,为了鉴定共有的多效性基因座和基因,并调查因果关联和潜在的因果中介。
方法:使用来自欧洲人AMH(N=7,049)和绝经年龄(N=201,323)的全基因组关联研究的汇总统计数据,我们通过连锁不平衡评分回归研究了AMH与绝经年龄之间的全球遗传结构.我们在复合零假设(PLACO)下采用多效性分析,遗传关联的功能图谱和注释(FUMA),基因注释的多标记分析(MAGMA),和共定位分析,以确定具有多效性作用的基因座和基因。使用用于基因特异性表达分析的连锁不平衡评分(LDSC-SEG)进行基于GTEx数据的组织富集分析。通过基于汇总数据的孟德尔随机化(SMR)另外鉴定共享的功能基因。通过两个样本孟德尔随机化(MR)检查AMH与绝经年龄之间的关系,使用共定位和代谢物介导的分析进一步探索了潜在的介质。
结果:AMH与绝经年龄呈正相关(相关系数=0.88,P=1.33×10-5)。通过使用PLACO和FUMA,42个显著的多效性位点与AMH和绝经年龄相关,其中10个(rs10734411,rs61913600,rs2277339,rs75770066,rs28416520,rs9796,rs11668344,rs403727,rs6011452和rs622237617)具有共同定位。此外,通过MAGMA鉴定了245个显著的多效性基因。AMH与绝经年龄之间的遗传关联明显集中在包括全血在内的各种组织中,大脑,心,肝脏,肌肉,胰腺,还有肾脏.Further,SMR分析显示9个基因可能对AMH和绝经年龄都有致病作用。两个样本的MR分析提示了绝经年龄对AMH的潜在因果影响,极低密度脂蛋白被确定为潜在的介质。
结论:我们的研究揭示了AMH与绝经年龄之间的共同遗传结构,为实验研究和个体治疗提供基础,以增强生殖结果。此外,我们的研究结果强调,仅仅依靠AMH不足以准确预测绝经年龄,和其他因素的组合需要考虑。探索旨在延缓更年期发作的新疗法有望实现,特别是当基于共享的基因结构靶向共享的基因时。
BACKGROUND: While the phenotypic association between anti-Müllerian hormone (AMH) and age at menopause has been widely studied, the role of AMH in predicting the age at menopause is currently controversial, and the genetic architecture or causal relationships underlying these two traits is not well understood.
OBJECTIVE: We aimed to explore the shared genetic architecture between AMH and age at menopause, to identify shared pleiotropic loci and genes, and to investigate causal association and potential causal mediators.
METHODS: Using summary statistics from publicly available genome-wide association studies on AMH (N=7,049) and age at menopause (N=201,323) in Europeans, we investigated the global genetic architecture between AMH and age at menopause through linkage disequilibrium score regression. We employed pleiotropic analysis under composite null hypothesis (PLACO), Functional Mapping and Annotation of Genetic Associations (FUMA), Multimarker analysis of GenoMic annotation (MAGMA), and colocalization analysis to identify loci and genes with pleiotropic effects. Tissue enrichment analysis based on GTEx data was conducted using the Linkage Disequilibrium Score for the specific expression of genes analysis (LDSC-SEG). Functional genes that were shared were additionally identified through summary data-based Mendelian randomization (SMR). The relationship between AMH and age at menopause was examined through two-sample Mendelian randomization (MR), and potential mediators were further explored using colocalization and metabolite-mediated analysis.
RESULTS: A positive genetic association (correlation coefficient = 0.88, P = 1.33 × 10-5) was observed between AMH and age at menopause. By using PLACO and FUMA, 42 significant pleiotropic loci were identified that were associated with AMH and age at menopause, and ten of these (rs10734411, rs61913600, rs2277339, rs75770066, rs28416520, rs9796, rs11668344, rs403727, rs6011452, and rs62237617) had colocalized loci. Additionally, 245 significant pleiotropic genes were identified by MAGMA. Genetic associations between AMH and age at menopause were markedly concentrated in various tissues including whole blood, brain, heart, liver, muscle, pancreas, and kidneys. Further, SMR analysis revealed nine genes that may have a causative effect on both AMH and age at menopause. A potential causal effect of age at menopause on AMH was suggested by two-sample MR analysis, with very-low-density lipoprotein identified as a potential mediator.
CONCLUSIONS: Our study revealed a shared genetic architecture between AMH and age at menopause, providing a basis for experimental investigations and individual therapies to enhance reproductive outcomes. Furthermore, our findings emphasized that relying solely on AMH is not sufficient for accurately predicting the age at menopause, and a combination of other factors needs to be considered. Exploring new therapeutics aimed at delaying at the onset of menopause holds promise, particularly when targeting shared genes based on their shared genetic architecture.