UNASSIGNED: In this study, we conducted a two-sample MR study to evaluate the causal effects of eight body fat distribution indicators on AAM. Inverse variance weighted (IVW) method was used for primary analysis, while supplementary approaches such as MR-Egger and weighted median were also utilized. Considering that the eight exposures were highly correlated, we performed an MR Bayesian model averaging (MR-BMA) analysis to prioritize the effect of major exposure on AAM. A series of sensitivity analyses were also performed.
UNASSIGNED: From a range of 82-105 single nucleotide polymorphisms (SNPs) were utilized as genetic instrumental variables for each of the exposure factors. After Bonferroni correction, we found that whole body fat mass (β: -0.17; 95% CI: -0.24, -0.11), left leg fat percentage (β: -0.14; 95% CI: -0.21, -0.07), left leg fat mass (β: -0.20; 95% CI: -0.27, -0.12), left arm fat percentage (β: -0.18; 95% CI: -0.26, -0.11) and left arm fat mass (β: -0.18; 95%CI: -0.26, -0.10) were associated with decreased AAM using random effects IVW method. And the beta coefficients for all MR evaluation methods exhibited consistent trends. MR-BMA method validated that left arm fat percentage plays a dominant role in AAM.
UNASSIGNED: Our MR study suggested that body fat has broad impacts on AAM. Obtaining more information on body measurements would greatly enhance our comprehension of pubertal development.
■在这项研究中,我们进行了一项双样本MR研究,以评估8个体脂分布指标对AAM的因果影响.采用逆方差加权(IVW)方法进行初步分析,同时还使用了MR-Egger和加权中位数等补充方法。考虑到八次曝光高度相关,我们进行了MR贝叶斯模型平均(MR-BMA)分析,以确定主要暴露对AAM的影响.还进行了一系列的敏感性分析。
■使用82-105个单核苷酸多态性(SNP)作为每个暴露因素的遗传工具变量。Bonferroni校正后,我们发现全身脂肪量(β:-0.17;95%CI:-0.24,-0.11),左腿脂肪百分比(β:-0.14;95%CI:-0.21,-0.07),左腿脂肪量(β:-0.20;95%CI:-0.27,-0.12),左臂脂肪百分比(β:-0.18;95%CI:-0.26,-0.11)和左臂脂肪质量(β:-0.18;95CI:-0.26,-0.10)与使用随机效应IVW方法的AAM降低相关。所有MR评估方法的β系数均表现出一致的趋势。MR-BMA方法验证了左臂脂肪百分比在AAM中起主导作用。
■我们的MR研究表明,身体脂肪对AAM有广泛的影响。获得更多有关身体测量的信息将大大提高我们对青春期发育的理解。