采用孟德尔随机化分析揭示代谢因素与卵巢癌风险之间的因果关联。
Unveiling the causal link between metabolic factors and ovarian cancer risk using Mendelian randomization analysis.
机构信息
Hunan Provincial University Key Laboratory of the Fundamental and Clinical Research on Functional Nucleic Acid, Changsha Medical University, Changsha, China.
Hunan Key Laboratory of The Research and Development of Novel Pharmaceutical Preparations, School of Pharmaceutical Science, Changsha Medical University, Changsha, China.
出版信息
Front Endocrinol (Lausanne). 2024 Jun 5;15:1401648. doi: 10.3389/fendo.2024.1401648. eCollection 2024.
BACKGROUND
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.
METHOD
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.
RESULT
The IVW findings demonstrated a causal associations between 10 metabolic factors and an increased risk of OC. Including "Basal metabolic rate" (OR= 1.24, = 6.86×10); "Body fat percentage" (OR= 1.22, = 8.20×10); "Hip circumference" (OR= 1.20, = 5.92×10); "Trunk fat mass" (OR= 1.15, = 1.03×10); "Trunk fat percentage" (OR= 1.25, = 8.55×10); "Waist circumference" (OR= 1.23, = 3.28×10); "Weight" (OR= 1.21, = 9.82×10); "Whole body fat mass" (OR= 1.21, = 4.90×10); "Whole body fat-free mass" (OR= 1.19, = 4.11×10) and "Whole body water mass" (OR= 1.21, = 1.85×10).
CONCLUSION
Several 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（OC）的发生密切相关，但人体测量指标作为代谢异常和 OC 的风险指标之间的关系尚不一致。
方法
孟德尔随机化（MR）方法是一种广泛用于确定因果关系的方法。我们的研究使用了全基因组关联研究（GWAS）的汇总统计数据，并使用逆方差加权（IVW）以及 MR-Egger 和加权中位数（WM）补充分析来评估暴露与结果之间的因果关系。此外，还使用了其他敏感性研究，如单样本分析和 MR-PRESSO，以评估关联的稳定性。
结果
IVW 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，=6.86×10）；“体脂百分比”（OR=1.22，=8.20×10）；“臀围”（OR=1.20，=5.92×10）；“躯干脂肪量”（OR=1.15，=1.03×10）；“躯干脂肪百分比”（OR=1.25，=8.55×10）；“腰围”（OR=1.23，=3.28×10）；“体重”（OR=1.21，=9.82×10）；“全身脂肪量”（OR=1.21，=4.90×10）；“全身去脂体重”（OR=1.19，=4.11×10）和“全身水体重”（OR=1.21，=1.85×10）。
结论
几种与脂肪蓄积和分布改变相关的代谢标志物与 OC 风险增加显著相关。
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