■一些流行病学研究表明,与怀孕期间血压正常的妇女相比,发生先兆子痫(PE)的孕妇的母体血浆中睾丸激素水平升高,揭示了女性高雄激素血症与PE之间的潜在关联。探讨高雄激素血症与PE的因果关系,这项研究选择了总睾酮(TT),生物可利用的睾酮(BIOT),和性激素结合球蛋白(SHBG)作为暴露因子,PE和慢性高血压叠加PE作为疾病结局。双样本孟德尔随机化(MR)分析用于遗传剖析三个暴露因素之间的因果关系(TT,BIOT,和SHBG)以及PE和慢性高血压合并PE的结局。
■两个独立的全基因组关联研究(GWAS)数据库用于双样本MR分析。在来自英国生物库队列的女性参与者的GWAS数据中,与TT相关的单核苷酸多态性(SNP),BIOT,和SHBG进行了分析,涉及230454、188507和188908样本,分别。来自芬兰数据库的PE和慢性高血压与叠加PE的GWAS数据用于计算SNP,涉及3556例PE病例和114735例对照,以及38例合并PE的慢性高血压和114735例对照。为了满足MR分析中工具相关性和独立性的假设,与暴露相关的SNP在全基因组水平(P<5.0×10-8),基于R2<0.001的聚类阈值和大于10000kb的等位基因距离,排除了连锁不平衡干扰。已知的混杂因素,包括以前的PE,慢性肾病,慢性高血压,糖尿病,系统性红斑狼疮,或抗磷脂综合征,还进行了鉴定,并删除了相关的SNP。最后,我们根据结果GWAS中与暴露相关的SNP提取结果数据,整合暴露和结果数据,去除回文序列。五种遗传因果分析方法,包括逆方差加权法(IVW),MR-Egger回归,加权中位数法,简单的模式方法,和加权模式方法,被用来推断因果关系。在IVW中,假设选择的SNP满足3个假设,并提供了最理想的效应估计.因此,IVW被用作本研究的主要分析方法。考虑到工具变量之间的潜在异质性,随机效应IVW用于MR分析。使用比值比(OR)和相应的95%置信区间(CI)解释结果,以解释暴露因素对PE和合并PE的慢性高血压的影响。如果CI不包括1且P值小于0.05,则认为差异具有统计学意义。进行敏感性分析以评估异质性和多效性。使用Cochran的Q检验检查异质性,使用MR-Egger截距分析评估多效性。此外,我们进行了留一法分析,以检查个体SNP是否驱动了因果关系.为了进一步验证调查结果,使用相同的方法和结果变量进行MR分析,但是不同的暴露因素,包括根据BMI(WHRadjBMI)和25-羟维生素D水平调整的腰臀比,WHRadjBMI和PE的MR结果作为阳性对照,25-羟维生素D水平和PE的MR结果作为阴性对照。
■根据选择遗传工具变量的标准,186、127和262个SNP被鉴定为与睾酮指标TT显著相关的遗传工具变量,BIOT,SHBGMR分析未发现TT之间存在因果关系,BIOT,和SHBG水平以及合并PE的发展为PE和慢性高血压的风险。IVW方法预测遗传预测的TT(OR[95%CI]=1.018[0.897-1.156],P=0.78),生物(OR[95%CI]=1.11[0.874-1.408],P=0.392),和SHBG(OR[95%CI]=0.855[0.659-1.109],P=0.239)与PE无关。同样,遗传预测的TT(OR[95%CI]=1.222[0.548-2.722],P=0.624),生物(OR[95%CI]=1.066[0.242-4.695],P=0.933),和SHBG(OR[95%CI]=0.529[0.119-2.343],P=0.402)与合并PE的慢性高血压没有显着相关。此外,使用MR-Egger方法进行MR分析,加权中位数法,简单的模式方法,和加权模式方法产生了一致的结果,表明睾酮水平升高与PE或合并PE的慢性高血压之间没有显著的因果关系。在PE分析中观察到SHBG的异质性(CochranQ检验,P=0.01),并在PE分析中检测到BIOT的多效性(MR-Egger截距分析,P=0.014),这表明工具变量不会通过BIOT影响PE。其他工具变量没有显示出显著的异质性或多效性。留一法分析证实,MR分析的结果不是由单个工具变量驱动的。与以前的MR研究一致,使用WHRadjBMI和25-羟维生素D水平的对照MR分析结果支持了MR分析方法和本研究所用方法的准确性.
■MR分析结果表明,当前的遗传证据不支持TT之间的因果关系,BIOT,和SHBG水平与PE和慢性高血压的发展叠加PE。这项研究表明,睾酮升高可能是PE的危险因素,但不是直接原因。
UNASSIGNED: Some epidemiological studies have shown that pregnant women who develop preeclampsia (PE) have elevated levels of testosterone in their maternal plasma compared to women with normal blood pressure during pregnancy, revealing a potential association between
hyperandrogenism in women and PE. To explore the causal relationship between
hyperandrogenism and PE, this study selected total testosterone (TT), bioavailable testosterone (BIOT), and sex hormone binding globulin (SHBG) as exposure factors and PE and chronic hypertension with superimposed PE as disease outcomes. Two-sample Mendelian randomization (MR) analyses were used to genetically dissect the causal relationships between the three exposure factors (TT, BIOT, and SHBG) and the outcomes of PE and chronic hypertension with superimposed PE.
UNASSIGNED: Two independent genome-wide association study (GWAS) databases were used for the two-sample MR analysis. In the GWAS data of female participants from the UK Biobank cohort, single nucleotide polymorphisms (SNPs) associated with TT, BIOT, and SHBG were analyzed, involving 230454, 188507, and 188908 samples, respectively. GWAS data on PE and chronic hypertension with superimposed PE from the Finnish database were used to calculate SNP, involving 3556 PE cases and 114735 controls, as well as 38 cases of chronic hypertension with superimposed PE and 114735 controls. To meet the assumptions of instrumental relevance and independence in MR analysis, SNPs associated with exposure were identified at the genome-wide level (P<5.0×10-8), and those in linkage disequilibrium interference were excluded based on clustering thresholds of R 2<0.001 and an allele distance greater than 10000 kb. Known confounding factors, including previous PE, chronic kidney disease, chronic hypertension, diabetes, systemic lupus erythematosus, or antiphospholipid syndrome, were also identified and the relevant SNPs were removed. Finally, we extracted the outcome data based on the exposure-related SNPs in the outcome GWAS, integrating exposure and outcome data, and removing palindromic sequences. Five genetic causal analysis methods, including inverse variance-weighted method (IVW), MR-Egger regression, weighted median method, simple mode method, and weighted mode method, were used to infer causal relationships. In the IVW, it was assumed that the selected SNPs satisfied the three assumptions and provided the most ideal estimate of the effect. IVW was consequently used as the primary analysis method in this study. Considering the potential heterogeneity among the instrumental variables, random-effects IVW was used for MR analysis. The results were interpreted using odds ratios (OR) and the corresponding 95% confidence interval (CI) to explain the impact of exposure factors on PE and chronic hypertension with superimposed PE. If the CI did not include 1 and had a P value less than 0.05, the difference was considered statistically significant. Sensitivity analysis was conducted to assess heterogeneity and pleiotropy. Heterogeneity was examined using Cochran\'s Q test, and pleiotropy was assessed using MR-Egger intercept analysis. Additionally, leave-one-out analysis was conducted to examine whether individual SNPs were driving the causal associations. To further validate the findings, MR analyses were performed using the same methods and outcome variables, but with different exposure factors, including waist-to-hip ratio adjusted for BMI (WHRadjBMI) and 25-hydroxyvitamin D levels, with MR results for WHRadjBMI and PE serving as the positive controls and MR results for 25-hydroxyvitamin D levels and PE as the negative controls.
UNASSIGNED: According to the criteria for selecting genetic instrumental variables, 186, 127, and 262 SNPs were identified as genetic instrumental variables significantly associated with testosterone indicators TT, BIOT, and SHBG. MR analysis did not find a causal relationship between the TT, BIOT, and SHBG levels and the risk of developing PE and chronic hypertension with superimposed PE. The IVW method predicted that genetically predicted TT (OR [95% CI]=1.018 [0.897-1.156], P=0.78), BIOT (OR [95% CI]=1.11 [0.874-1.408], P=0.392), and SHBG (OR [95% CI]=0.855 [0.659-1.109], P=0.239) were not associated with PE. Similarly, genetically predicted TT (OR [95% CI]=1.222 [0.548-2.722], P=0.624), BIOT (OR [95% CI]=1.066 [0.242-4.695], P=0.933), and SHBG (OR [95% CI]=0.529 [0.119-2.343], P=0.402) were not significantly associated with chronic hypertension with superimposed PE. Additionally, MR analysis using the MR-Egger method, weighted median method, simple mode method, and weighted mode method yielded consistent results, indicating no significant causal relationship between elevated testosterone levels and PE or chronic hypertension with superimposed PE. Heterogeneity was observed for SHBG in the analysis with PE (Cochran\'s Q test, P=0.01), and pleiotropy was detected for BIOT in the analysis with PE (MR-Egger intercept analysis, P=0.014), suggesting that the instrumental variables did not affect PE through BIOT. Other instrumental variables did not show significant heterogeneity or pleiotropy. Leave-one-out analysis confirmed that the results of the MR analysis were not driven by individual instrumental variables. Consistent with previous MR studies, the results of the control MR analyses using WHRadjBMI and 25-hydroxyvitamin D levels supported the accuracy of the MR analysis approach and the methods used in this study.
UNASSIGNED: The MR analysis results suggest that current genetic evidence does not support a causal relationship between TT, BIOT, and SHBG levels and the development of PE and chronic hypertension with superimposed PE. This study suggests that elevated testosterone may be a risk factor for PE but not a direct cause.