饮食因素与子痫前期因果关系的孟德尔随机化分析

doi:10.6040/j.issn.1671-7554.0.2023.1136

摘要/Abstract

摘要： 目的探讨饮食因素与子痫前期的可能因果效应。方法利用全基因组关联研究(genome-wide association studies, GWAS)数据,采用逆方差加权法(inverse-variance weighted, IVW)、加权中位数(weighted median, WM)、MR Egger回归(MR-Egger regression)进行孟德尔随机化(Mendelian randomization, MR)分析,评估饮食因素与子痫前期的因果关系。并且,进行异质性检验、敏感性分析、多效性分析。结果奶酪摄入量(IVW: OR=0.504, 95%CI: 0.314~0.808, P=0.004)、沙拉/生蔬菜摄入量(IVW: OR=0.195, 95%CI: 0.041~0.923, P=0.039)与子痫前期存在负向因果关系。且所有结果均不存在多效性,留一法亦提示所得结果稳健。其他饮食因素未发现与子痫前期具有因果关系。结论这项双样本MR分析发现奶酪摄入量、沙拉/生蔬菜摄入量与欧洲人群子痫前期风险降低有关,但仍需更大的GWAS数据进一步验证这种关系,同时研究其中潜在关联机制,以支持该结论。此外,其他饮食因素未发现与子痫前期具有因果关系。

关键词: 饮食, 奶酪, 蔬菜, 子痫前期, 孟德尔随机化

Abstract: Objective To explore the potential causal link between dietary factors and preeclampsia. Methods By leveraging Genome-wide association studies(GWAS)data, Mendelian randomization(MR)analyses were employed utilizing Inverse-variance weighted(IVW), Weighted median(WM), and MR-Egger regression techniques to assess the causal association between dietary factors and preeclampsia. Furthermore, heterogeneity tests, sensitivity analyses, and pleiotropy assessments to were conducted ensure the robustness of the findings. Results The analysis revealed a negative causal relationship between preeclampsia and the consumption of cheese(IVW: OR=0.504, 95%CI: 0.314-0.808, P=0.004)as well as salads/raw vegetables(IVW: OR=0.195, 95%CI: 0.041-0.923, P=0.039). All results demonstrated an absence of pleiotropic effects, and the leave-one-out approach further validated the robustness of the findings. No causal associations were observed between preeclampsia and other dietary factors examined. Conclusion A reduced risk of preeclampsia associated with cheese intake and the consumption of salads/raw vegetables is identified in European populations. However, confirmation of these relationships and exploration of the underlying mechanisms require validation using larger GWAS datasets. Additionally, no causal links are established between preeclampsia and the remaining dietary factors investigated.

Key words: Diet, Cheese, Vegetable, Preeclampsia, Mendelian randomization

中图分类号:

R714.7

张展,李建锋,李燕玲,王博雯,昂文成林龙珠,王鑫,张小明,谢萍. 饮食因素与子痫前期因果关系的孟德尔随机化分析[J]. 山东大学学报 (医学版), 2024, 62(8): 59-66.

ZHANG Zhan, LI Jianfeng, LI Yanling, WANG Bowen, ANGWEN Chenglinlongzhu, WANG Xin, ZHANG Xiaoming, XIE Ping. Mendelian randomization analysis of causality between dietary factors and preeclampsia[J]. Journal of Shandong University (Health Sciences), 2024, 62(8): 59-66.

参考文献

[1] Achamrah N, Ditisheim A. Nutritional approach to preeclampsia prevention[J]. Curr Opin Clin Nutr Metab Care, 2018, 21(3): 168-173.
[2] Brantsaeter AL, Haugen M, Samuelsen SO, et al. A dietary pattern characterized by high intake of vegetables, fruits, and vegetable oils is associated with reduced risk of preeclampsia in nulliparous pregnant Norwegian women[J]. J Nutr, 2009, 139(6): 1162-1168.
[3] Allen R, Rogozinska E, Sivarajasingam P, et al. Effect of diet- and lifestyle-based metabolic risk-modifying interventions on preeclampsia: a meta-analysis[J]. Acta Obstet Gynecol Scand, 2014, 93(10): 973-985.
[4] Syngelaki A, Sequeira Campos M, Roberge S, et al. Diet and exercise for preeclampsia prevention in overweight and obese pregnant women: systematic review and meta-analysis[J]. J Matern Fetal Neonatal Med, 2019, 32(20):3495-3501.
[5] Lawlor DA, Harbord RM, Sterne JA, et al. Mendelian randomization: using genes as instruments for making causal inferences in epidemiology[J]. Stat Med, 2008, 27(8): 1133-1163.
[6] Burgess S, Labrecque JA. Mendelian randomization with a binary exposure variable: interpretation and presentation of causal estimates[J]. Eur J Epidemiol, 2018, 33(10): 947-952.
[7] Botelho J, Machado V, Mendes JJ, et al. Causal association between periodontitis and Parkinsons disease: a bidirectional Mendelian randomization study[J]. Genes, 2021, 12(5): 772.
[8] Hartwig FP, Davey Smith G, Bowden J. Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption[J]. Int J Epidemiol, 2017, 46(6): 1985-1998.
[9] Phelan M, Kerins D. The potential role of milk-derived peptides in cardiovascular disease[J]. Food Funct, 2011, 2(3/4): 153-167.
[10] Helal A, Tagliazucchi D. Peptidomics profile, bioactive peptides identification and biological activities of six different cheese varieties[J]. Biology, 2023, 12(1): 78.
[11] Miguel M, Gómez-Ruiz Já, Recio I, et al. Changes in arterial blood pressure after single oral administration of milk-casein-derived peptides in spontaneously hypertensive rats[J]. Mol Nutr Food Res, 2010, 54(10): 1422-1427.
[12] Engberink MF, Hendriksen MA, Schouten EG, et al. Inverse association between dairy intake and hypertension: the Rotterdam Study[J]. Am J Clin Nutr, 2009, 89(6): 1877-1883.
[13] Khaing W, Vallibhakara SA, Tantrakul V, et al. Calcium and vitamin D supplementation for prevention of preeclampsia: a systematic review and network meta-analysis[J]. Nutrients, 2017, 9(10): 1141.
[14] Woo Kinshella ML, Sarr C, Sandhu A, et al. Calcium for pre-eclampsia prevention: a systematic review and network meta-analysis to guide personalised antenatal care[J]. BJOG, 2022, 129(11): 1833-1843.
[15] Carroli G, Merialdi M, Wojdyla D, et al. Effects of calcium supplementation on uteroplacental and fetoplacental blood flow in low-calcium-intake mothers: a randomized controlled trial[J]. Am J Obstet Gynecol, 2010, 202(1): 45.e1-9.
[16] DeSousa J, Tong M, Wei J, et al. The anti-inflammatory effect of calcium for preventing endothelial cell activation in preeclampsia[J]. J Hum Hypertens, 2016, 30(5): 303-308.
[17] Nordqvist M, Jacobsson B, Brantsæter AL, et al. Timing of probiotic milk consumption during pregnancy and effects on the incidence of preeclampsia and preterm delivery: a prospective observational cohort study in Norway[J]. BMJ Open, 2018, 8(1): e018021. doi:10.1136/bmjopen-2017-018021.
[18] Oniszczuk A, Oniszczuk T, Gancarz M, et al. Role of gut microbiota, probiotics and prebiotics in the cardiovascular diseases[J]. Molecules, 2021, 26(4): 1172.
[19] Matsutomo T. Potential benefits of garlic and other dietary supplements for the management of hypertension[J]. Exp Ther Med, 2020, 19(2): 1479-1484.
[20] Kinshella MW, Omar S, Scherbinsky K, et al. Maternal dietary patterns and pregnancy hypertension in low- and middle-income countries: a systematic review and meta-analysis[J]. Adv Nutr, 2021, 12(6): 2387-2400.
[21] Mekie M, Mekonnen W, Assegid M. Cohabitation duration, obstetric, behavioral and nutritional factors predict preeclampsia among nulliparous women in West Amhara Zones of Ethiopia: age matched case control study[J]. PLoS One, 2020, 15(1): e0228127. doi:10.1371/journal.pone.0228127.
[22] Endeshaw M, Abebe F, Bedimo M, et al. Diet and pre-eclampsia: a prospective multicentre case-control study in Ethiopia[J]. Midwifery, 2015, 31(6): 617-624.
[23] Zerfu TA, Mekuria A. Pregnant women have inadequate fiber intake while consuming fiber-rich diets in low-income rural setting: Evidences from Analysis of common “ready-to-eat” stable foods[J]. Food Sci Nutr, 2019, 7(10): 3286-3292.
[24] Bînǎ AM, Sturza A, Iancu I, et al. Placental oxidative stress and monoamine oxidase expression are increased in severe preeclampsia: a pilot study[J]. Mol Cell Biochem, 2022, 477(12): 2851-2861.
[25] Aouache R, Biquard L, Vaiman D, et al. Oxidative stress in preeclampsia and placental diseases[J]. Int J Mol Sci, 2018, 19(5): 1496.
[26] Chiarello DI, Abad C, Rojas D, et al. Oxidative stress: normal pregnancy versus preeclampsia[J]. Biochim Biophys Acta Mol Basis Dis, 2020, 1866(2): 165354. doi:10.1016/j.bbadis.2018.12.005.
[27] Ebegboni VJ, Balahmar RM, Dickenson JM, et al. The effects of flavonoids on human first trimester trophoblast spheroidal stem cell self-renewal, invasion and JNK/p38 MAPK activation: understanding the cytoprotective effects of these phytonutrients against oxidative stress[J]. Biochem Pharmacol, 2019, 164: 289-298. doi:10.1016/j.bcp.2019.04.023.
[28] Meltzer HM, Brantsæter AL, Nilsen RM, et al. Effect of dietary factors in pregnancy on risk of pregnancy complications: results from the Norwegian Mother and Child Cohort Study[J]. Am J Clin Nutr, 2011, 94(6): 1970-1974.
[29] Hsu CC, Jhang HR, Chang WT, et al. Associations between dietary patterns and kidney function indicators in type 2 diabetes[J]. Clin Nutr, 2014, 33(1): 98-105.
[30] Kondo K, Morino K, Nishio Y, et al. Fiber-rich diet with brown rice improves endothelial function in type 2 diabetes mellitus: a randomized controlled trial[J]. PLoS One, 2017, 12(6): e0179869. doi:10.1371/journal.pone.0179869.
[31] Foo SY, Heller ER, Wykrzykowska J, et al. Vascular effects of a low-carbohydrate high-protein diet[J]. Proc Natl Acad Sci U S A, 2009, 106(36): 15418-15423.
[32] Schoenaker DA, Soedamah-Muthu SS, Callaway LK, et al. Prepregnancy dietary patterns and risk of developing hypertensive disorders of pregnancy: results from the Australian Longitudinal Study on Womens Health[J]. Am J Clin Nutr, 2015, 102(1): 94-101.
[33] Pellegrini N, Chiavaro E, Gardana C, et al. Effect of different cooking methods on color, phytochemical concentration, and antioxidant capacity of raw and frozen brassica vegetables[J]. J Agric Food Chem, 2010, 58(7): 4310-4321.
[34] Miglio C, Chiavaro E, Visconti A, et al. Effects of different cooking methods on nutritional and physicochemical characteristics of selected vegetables[J]. J Agric Food Chem, 2008, 56(1): 139-147.
[35] Shi J, Le Maguer M. Lycopene in tomatoes: chemical and physical properties affected by food processing[J]. Crit Rev Biotechnol, 2000, 20(4): 293-334.
[36] Boyko EJ. Observational research: opportunities and limitations[J]. J Diabetes Complications, 2013, 27(6): 642-648.

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