Associations between serum metabolites and female cancers: A bidirectional two-sample mendelian randomization study

孟德尔随机化 随机化 遗传学 样品(材料) 肿瘤科 生物 内科学 医学 生理学 基因 临床试验 化学 基因型 遗传变异 色谱法
作者
Z. Alexander Cao,XiongZhi Long,LiQin Yuan
出处
期刊:The Journal of Steroid Biochemistry and Molecular Biology [Elsevier]
卷期号:243: 106584-106584 被引量:3
标识
DOI:10.1016/j.jsbmb.2024.106584
摘要

Female cancers, especially breast, ovarian, cervical and endometrial cancers, constitute a major threat to women's health worldwide. In view of the complex genetic background of cancers cannot be fully explained with current genetic information, we used a bidirectional two-sample mendelian randomization approach to explore the causal associations between serum metabolites and four major female cancers-breast, ovarian, cervical and endometrial cancers. We analyzed the metabolites dataset from the Canadian Longitudinal Study of Aging and cancer datasets from the 10th round of the Finngen project. Replication analyses was performed with Cancer Association Consortium and Leo's studies. Instrumental variables were analyzed using methods including the Wald ratio, inverse-variance weighted, MR-Egger, and weighted median. To ensure robustness, sensitivity analyses were performed using Cochrane's Q, Egger's intercept, MR-PRESSO, and leave-one-out methods. After meticulous analysis, we obtained levels of 3-hydroxyoleoylcarnitine, hexadecanedioate, tetradecanedioate and carnitine C14 with robust causal associations with breast cancer, levels of 5alpha-androstan-3alpha,17beta-diol monosulfate (1), androstenediol (3beta,17beta) monosulfate (1), androsterone sulfate, and 5alpha-androstan-3beta,17beta-diol disulfate causal associations with endometrial cancer. The reverse analysis showed that breast, ovarian, and endometrial cancer and survival of breast and ovarian cancer were found to have causal relationships with 8, 5, 2, 6, and 3 metabolites, respectively. These insights underscore the potential roles of specific metabolites in the etiology of female cancers, providing new biomarkers for early detection, risk stratification, and disease progression monitoring. Further research could elucidate how these metabolites influence specific pathways in cancer development, offering theoretical foundations for prevention and treatment strategies.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
刚刚
orixero应助冷艳惜梦采纳,获得10
1秒前
爆米花应助yan采纳,获得10
2秒前
田様应助贤弟采纳,获得10
2秒前
3秒前
jiayouya发布了新的文献求助10
4秒前
眠羊发布了新的文献求助10
5秒前
怕孤单的忆灵关注了科研通微信公众号
5秒前
尹天扬完成签到,获得积分10
5秒前
C22完成签到,获得积分10
6秒前
FashionBoy应助zfihead采纳,获得10
6秒前
6秒前
JG完成签到,获得积分10
6秒前
9秒前
10秒前
王凯完成签到,获得积分10
11秒前
11秒前
huqing发布了新的文献求助60
12秒前
12秒前
ddboys1009发布了新的文献求助10
12秒前
13秒前
C22发布了新的文献求助10
14秒前
王凯发布了新的文献求助10
15秒前
冷艳惜梦发布了新的文献求助10
15秒前
cinnamonbrd发布了新的文献求助10
16秒前
16秒前
17秒前
17秒前
17秒前
18秒前
18秒前
量子星尘发布了新的文献求助10
20秒前
snow发布了新的文献求助30
20秒前
上官若男应助赶路人采纳,获得10
21秒前
小马甲应助毅诚菌采纳,获得10
22秒前
23秒前
cleva完成签到,获得积分10
23秒前
专注的问筠完成签到,获得积分10
23秒前
23秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
人脑智能与人工智能 1000
King Tyrant 720
Silicon in Organic, Organometallic, and Polymer Chemistry 500
Principles of Plasma Discharges and Materials Processing, 3rd Edition 400
Pharmacology for Chemists: Drug Discovery in Context 400
El poder y la palabra: prensa y poder político en las dictaduras : el régimen de Franco ante la prensa y el periodismo 400
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5604157
求助须知:如何正确求助?哪些是违规求助? 4688985
关于积分的说明 14857229
捐赠科研通 4696839
什么是DOI,文献DOI怎么找? 2541204
邀请新用户注册赠送积分活动 1507328
关于科研通互助平台的介绍 1471851