Dietary factors and risk for endometriosis: a Mendelian randomization analysis.

IF 3.9 2区 医学 Q2 NUTRITION & DIETETICS
Xia Zhang, Qiaomei Zheng, Lihong Chen
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引用次数: 0

Abstract

Aims: Observational studies have reported an association between dietary factors and endometriosis, but the causality remains unknown. The study aimed to investigate the potential causal association between dietary factors and endometriosis using Mendelian randomization (MR).

Methods: We performed a two-sample MR analysis to investigate the effects of 18 diet-related exposure factors (alcoholic drinks per week, alcohol intake frequency, processed meat intake, poultry intake, beef intake, non-oily fish intake, oily fish intake, pork intake, lamb/mutton intake, bread intake, cheese intake, cooked vegetable intake, tea intake, fresh fruit intake, cereal intake, salad/raw vegetable intake, coffee intake, dried fruit intake) on the risk of endometriosis using summary statistics from the genome-wide association study (GWAS). The inverse variance weighted (IVW) method was used to deduce the causal association between dietary factors and endometriosis, and sensitivity analyses were further performed.

Results: Processed meat intake (OR = 0.550; 95%CI:0.314-0.965; p = 0.037) and salad / raw vegetable intake (OR = 0.346; 95%CI:0.127-0.943; p = 0.038) were discovered as protective factors for endometriosis. Heterogeneity test revealed no significant heterogeneity (processed meat intake: pIVW=0.607, pMR-Egger=0.548; salad / raw vegetable intake: pIVW=0.678, pMR-Egger=0.620). MR-Egger regression test didn't support any evidence for horizontal pleiotropy (processed meat intake: p for intercept = 0.865; salad / raw vegetable intake: p for intercept = 0.725). No causal relationship was found between other dietary intakes and endometriosis.

Conclusion: These findings suggest that processed meat intake and salad/raw vegetable intake are associated with a decreased risk of endometriosis, but further investigation is required.

饮食因素与子宫内膜异位症的风险:孟德尔随机分析。
目的:观察性研究报道了饮食因素与子宫内膜异位症之间的联系,但因果关系尚不清楚。该研究旨在利用孟德尔随机化(MR)研究饮食因素与子宫内膜异位症之间的潜在因果关系。方法:我们进行了一项双样本磁共振分析,以调查18种饮食相关暴露因素的影响(每周饮酒量、饮酒频率、加工肉类摄入量、家禽摄入量、牛肉摄入量、非油性鱼类摄入量、油性鱼类摄入量、猪肉摄入量、羊肉/羊肉摄入量、面包摄入量、奶酪摄入量、熟蔬菜摄入量、茶摄入量、新鲜水果摄入量、谷物摄入量、沙拉/生蔬菜摄入量、咖啡摄入量、使用全基因组关联研究(GWAS)的汇总统计数据,研究干果摄入量对子宫内膜异位症风险的影响。采用逆方差加权(IVW)法推断饮食因素与子宫内膜异位症之间的因果关系,并进一步进行敏感性分析。结果:加工肉类摄入量(OR = 0.550;95%置信区间:0.314—-0.965;p = 0.037)和沙拉/生蔬菜摄入量(OR = 0.346;95%置信区间:0.127—-0.943;P = 0.038)为子宫内膜异位症的保护因素。异质性检验未发现显著异质性(加工肉类摄入量:pIVW=0.607, pMR-Egger=0.548;沙拉/生蔬菜摄入量:pIVW=0.678, pm - egger =0.620)。MR-Egger回归检验不支持任何水平多效性的证据(加工肉类摄入量:p为截距= 0.865;沙拉/生蔬菜摄入量:p(截距= 0.725)。其他饮食摄入与子宫内膜异位症之间没有因果关系。结论:这些发现表明,加工肉类的摄入和沙拉/生蔬菜的摄入与子宫内膜异位症的风险降低有关,但需要进一步的研究。
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来源期刊
Nutrition & Metabolism
Nutrition & Metabolism 医学-营养学
CiteScore
8.40
自引率
0.00%
发文量
78
审稿时长
4-8 weeks
期刊介绍: Nutrition & Metabolism publishes studies with a clear focus on nutrition and metabolism with applications ranging from nutrition needs, exercise physiology, clinical and population studies, as well as the underlying mechanisms in these aspects. The areas of interest for Nutrition & Metabolism encompass studies in molecular nutrition in the context of obesity, diabetes, lipedemias, metabolic syndrome and exercise physiology. Manuscripts related to molecular, cellular and human metabolism, nutrient sensing and nutrient–gene interactions are also in interest, as are submissions that have employed new and innovative strategies like metabolomics/lipidomics or other omic-based biomarkers to predict nutritional status and metabolic diseases. Key areas we wish to encourage submissions from include: -how diet and specific nutrients interact with genes, proteins or metabolites to influence metabolic phenotypes and disease outcomes; -the role of epigenetic factors and the microbiome in the pathogenesis of metabolic diseases and their influence on metabolic responses to diet and food components; -how diet and other environmental factors affect epigenetics and microbiota; the extent to which genetic and nongenetic factors modify personal metabolic responses to diet and food compositions and the mechanisms involved; -how specific biologic networks and nutrient sensing mechanisms attribute to metabolic variability.
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