PDF(Pubmed)
Abstract：
UNASSIGNED: Metabolic 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.
UNASSIGNED: The 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.
UNASSIGNED: The 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).
UNASSIGNED: Several metabolic markers linked to altered fat accumulation and distribution are significantly associated with an increased risk of OC.
UNASSIGNED: The 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.
UNASSIGNED: The 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).
UNASSIGNED: Several metabolic markers linked to altered fat accumulation and distribution are significantly associated with an increased risk of OC.
摘要：
■代谢异常与卵巢癌（OC）的发展密切相关，然而,作为代谢异常危险指标的人体测量指标与OC之间的关系缺乏一致性.
■孟德尔随机化（MR）方法是一种用于确定因果关系的广泛使用的方法。我们的研究采用了全基因组关联研究(GWAS)的汇总统计数据，我们使用逆方差加权(IVW)以及MR-Egger和加权中位数(WM)辅助分析来评估暴露与结局之间的因果关系.此外，额外的敏感性研究，如留一法分析和MR-PRESSO等用于评估关联的稳定性.
■IVW研究结果表明，10种代谢因素与OC风险增加之间存在因果关系。包括“基础代谢率”（OR=1.24，P=6.86×10-4）；\“身体脂肪百分比”（OR=1.22，P=8.20×10-3）；\“臀围”（OR=1.20，P=5.92×10-4）；\“躯干脂肪质量\”（OR=1.10×10-1.1，P=10-1.1，P=10=10=1.
与脂肪积累和分布改变相关的几种代谢标志物与OC风险增加显著相关。
■孟德尔随机化（MR）方法是一种用于确定因果关系的广泛使用的方法。我们的研究采用了全基因组关联研究(GWAS)的汇总统计数据，我们使用逆方差加权(IVW)以及MR-Egger和加权中位数(WM)辅助分析来评估暴露与结局之间的因果关系.此外，额外的敏感性研究，如留一法分析和MR-PRESSO等用于评估关联的稳定性.
■IVW研究结果表明，10种代谢因素与OC风险增加之间存在因果关系。包括“基础代谢率”（OR=1.24，P=6.86×10-4）；\“身体脂肪百分比”（OR=1.22，P=8.20×10-3）；\“臀围”（OR=1.20，P=5.92×10-4）；\“躯干脂肪质量\”（OR=1.10×10-1.1，P=10-1.1，P=10=10=1.
与脂肪积累和分布改变相关的几种代谢标志物与OC风险增加显著相关。
