DataSheet_1_Unveiling the causal link between metabolic factors and ovarian cancer risk using Mendelian randomization analysis.docx

BackgroundMetabolic abnormalities are closely tied to the development of ovarian cancer (OC), yet the relationship between anthropometric indicators as risk indicators for metabolic abnormalities and OC lacks consistency.
MethodThe Mendelian randomization (MR) approach is a widely used methodology for determining causal relationships. Our study employed summary statistics from the genome-wide association studies (GWAS), and we used inverse variance weighting (IVW) together with MR-Egger and weighted median (WM) supplementary analyses to assess causal relationships between exposure and outcome. Furthermore, additional sensitivity studies, such as leave-one-out analyses and MR-PRESSO were used to assess the stability of the associations.
ResultThe IVW findings demonstrated a causal associations between 10 metabolic factors and an increased risk of OC. Including “Basal metabolic rate” (OR= 1.24, P= 6.86×10-4); “Body fat percentage” (OR= 1.22, P= 8.20×10-3); “Hip circumference” (OR= 1.20, P= 5.92×10-4); “Trunk fat mass” (OR= 1.15, P= 1.03×10-2); “Trunk fat percentage” (OR= 1.25, P= 8.55×10-4); “Waist circumference” (OR= 1.23, P= 3.28×10-3); “Weight” (OR= 1.21, P= 9.82×10-4); “Whole body fat mass” (OR= 1.21, P= 4.90×10-4); “Whole body fat-free mass” (OR= 1.19, P= 4.11×10-3) and “Whole body water mass” (OR= 1.21, P= 1.85×10-3).
ConclusionSeveral metabolic markers linked to altered fat accumulation and distribution are significantly associated with an increased risk of OC.

背景：代谢异常与卵巢癌（Ovarian Cancer, OC）的发生发展密切相关，但以人体测量学指标作为代谢异常风险标志物与卵巢癌之间的关联尚未达成一致。
方法：孟德尔随机化（Mendelian Randomization, MR）是目前用于推断因果关联的主流研究方法。本研究采用全基因组关联研究（Genome-Wide Association Studies, GWAS）的汇总统计数据，使用逆方差加权（Inverse Variance Weighting, IVW）结合MR-Egger及加权中位数（Weighted Median, WM）补充分析，以评估暴露因素与结局之间的因果关联。此外，本研究还通过留一法分析（leave-one-out analyses）及MR-PRESSO等敏感性分析，评估关联结果的稳定性。
结果：逆方差加权分析结果显示，10种代谢因素与卵巢癌风险升高存在因果关联，具体包括：基础代谢率（Basal Metabolic Rate, OR=1.24, P=6.86×10^-4）、体脂百分比（Body Fat Percentage, OR=1.22, P=8.20×10^-3）、臀围（Hip Circumference, OR=1.20, P=5.92×10^-4）、躯干脂肪量（Trunk Fat Mass, OR=1.15, P=1.03×10^-2）、躯干脂肪百分比（Trunk Fat Percentage, OR=1.25, P=8.55×10^-4）、腰围（Waist Circumference, OR=1.23, P=3.28×10^-3）、体重（Weight, OR=1.21, P=9.82×10^-4）、全身脂肪量（Whole Body Fat Mass, OR=1.21, P=4.90×10^-4）、全身去脂体重（Whole Body Fat-Free Mass, OR=1.19, P=4.11×10^-3）及全身水量（Whole Body Water Mass, OR=1.21, P=1.85×10^-3）。
结论：多种与脂肪堆积及分布异常相关的代谢标志物，与卵巢癌风险升高存在显著关联。