Yaochen Lou, Yan Du, Feng Jiang, Jun Guan
Número de descargas:
2258
Número de visitas:
1077
Citas:
0
Compártelo:
Objective: this study aimed to investigate if childhood body mass index (BMI) causally contributed to the risk of endometrial cancer (EC), which had not been well answered. Methods: genetic instruments were selected using single-nucleotide polymorphisms (SNPs) associated with childhood BMI in European population from a large-scale genome-wide association studies (GWAS, n = 39,620). A two-sample Mendelian randomization (MR) study was performed to evaluate the effect of higher childhood BMI on risk of EC. The data for endometrioid EC was obtained from a GWAS dataset comprising 54,884 individuals (8,758 cases and 46,126 controls). Inverse variance weighting (IVW), weighted median, weighted mode, and MR-Egger regression approaches were applied. Results: we selected 16 SNPs with genome-wide significance in childhood BMI for the analysis. The IVW analysis provided a causal link between childhood BMI and EC (beta = 0.408, standard error [SE] = 0.088, p < 0.001). Similarly, the weighted median method also provided robust evidence for the causal correlation (beta = 0.390, SE = 0.119, p < 0.001). Although the MR-Egger regression did not achieve the same significance (beta = 0.071, SE = 0.362, p = 0.848), it showed a minimal intercept value indicating small bias for directionality of pleiotropic effects (intercept = 0.024; p = 0.354). Through Cochran's Q test and visual inspection via funnel plot, the assessment of heterogeneity found no evidence of heterogeneity or asymmetry in our findings, further supporting the absence of directional pleiotropy. Conclusions: childhood BMI and risk of EC might be causally related, and early-life intervention on weight control might be considered for children to reduce the life-span risk of EC.
Palabras Clave: Childhood body mass index. Endometrial cancer. Mendelian randomization. Risk factor. GWAS.
Gisela Cruz , Karina Maeshiro
Anxela Soto Rodríguez , José Luis García Soidán , Mª Jesús Arias Gómez , Raquel Leirós Rodríguez , Alberto Del Álamo Alonso , Mª Reyes Pérez Fernández
Tuğçe Akıllıoğlu , Murat Baş , Gizem Köse
Changlong Wei , Xiaofang Wang , Jinsheng Zeng , Gongyin Zhang
Zhijian He , Lujia Zhu , Jie He , Xinwei Chen , Xiaoyang Li , Jian Yu
Nana Zhao , Yunfei Lu , Junjie Liu
Shupeng Chen , Meiling Zhang , Yao Gao , Yingjian Zeng
Ying Li , Yuhan Wang , Lianying Guo , Ye Yu , Mengqi Jiang , Lili Deng , Qingyi Zhou , Lu Sun , Xu Feng , Zhuo Zhang
Lingyue Zhao , Chunsheng Cheng , Guozhen Ma , Guangju Feng , Xingguang Wang
Ting Shen , Yining Guan , Jiaru Cai , Yizhou Jin , Yixin Jiang , Jiaying Lin , Chenxin Yan , Jiawei Sun
Ruizhi Ye , Fengming Zhang , Guangxian You
Sergio Vladimir Flores-Carrasco , Ángel Roco Videla , Román Montaña-Ramírez
Bingfu Wang , Yulong Song , Yujian Fan , Zhiqiang Zhao
Ana Beatriz Vasconcelos de Oliveira , Denise Zaffari , José Antonio Tesser Poloni , Morgana Weber , Rochele Cassanta Rossi , Alexandre Losekann
Feng Cheng , Yingjia Zhu , Xiaojing Zhang , Fei Xia
ChatGPT y otras herramientas de inteligencia artif...
Introducción: los micronutrientes participan en la...