基于孟德尔随机化分析肠道菌群、血液代谢物和肥胖的因果关系

doi:10.6040/j.issn.1671-7554.0.2025.0279

摘要/Abstract

摘要： 目的采用孟德尔随机化方法探讨肠道菌群、血液代谢物和肥胖之间的因果关系。方法使用MiBioGen联盟数据库中人类肠道菌群的全基因组关联分析(genome-wide association study, GWAS)数据作为暴露因素,英国医学研究理事会整合流行病学单元开放全基因组关联研究数据库(MRC Integrative Epidemiology Unit Open GWAS Database, IEU openGWAS)中肥胖数据作为结局变量,美国国家人类基因组研究所-欧洲生物信息研究所全基因组关联研究资源库(National Human Genome Research Institute-European Bioinformatics Institute Genome-Wide Association Studies Catalog, NHGRI-EBI GWAS Catalog)中获得1 400种血液代谢物作为中介,使用随机效应逆方差加权法、MR Egger回归法、加权中位数法、加权众数法和简单众数法等5种方法进行两步孟德尔随机化(two-step Mendelian randomization, TSMR)和多变量孟德尔随机化(multivariable Mendelian randomization, MVMR)探索肠道菌群、血液代谢物、肥胖之间的因果关系,并对孟德尔随机化(Mendelian randomization, MR)结果进行敏感性分析,评估结果的稳健性。结果 7种肠道菌群与肥胖存在因果关系,而肥胖会导致5种肠道菌群的变化。在两步MR中,霍氏真杆菌属菌群(genus Eubacterium hallii group)、颤螺菌属(genus Oscillibacter)、草酸杆菌属(genus Oxalobacter)、萨特菌属(genus Sutterella)与肥胖存在因果关系。多变量的MR显示草酸杆菌属与肥胖的相关性可能由5α-雄烷-3α,17α-二醇单硫酸酯水平介导的,介导比例为8.504%;萨特菌属与肥胖的相关性是由胆酸盐与腺苷-5'-单磷酸(cholate to adenosine 5'-monophosphate, AMP)比值介导的,介导比例为12.135%。结论目前的MR研究提供了支持草酸杆菌属、萨特菌属与肥胖以及可能潜在介导代谢物之间因果关系的证据。

关键词: 肠道菌群, 肥胖, 孟德尔随机化, 因果效应, 遗传分析

Abstract: Objective To utilise the Mendelian randomisation method to investigate the causal relationships between gut microbiota, blood metabolites, and obesity. Methods The human gut microbiota genome-wide association study(GWAS)data were obtained from the MiBioGen consortium database and utilised as exposure factors. The obesity data were obtained from the MRC Integrative Epidemiology Unit openGWAS database(IEU OpenGWAS)as outcomes. The data on 1,400 blood metabolites were sourced from the National Human Genome Research Institute-European Bioinformatics Institute Genome-Wide Association Studies Catalog(NHGRI-EBI GWAS Catalog)as mediators. Five methods(random-effects inverse variance weighting, MR Egger regression, weighted median, weighted mode, and simple mode)were employed for two-step Mendelian randomisation(TSMR)and multivariable Mendelian randomisation(MVMR)to explore the causal relationships between gut microbiota, blood metabolites, and obesity. Sensitivity analyses were conducted to assess the robustness of the MR results. Results A total of seven gut microbiota taxa were identified as having a causal relationship with obesity, while obesity was found to cause changes in five gut microbiota taxa. In the TSMR analysis, the genus Eubacterium hallii group, genus Oscillibacter, genus Oxalobacter, and genus Sutterella were found to be causally associated with obesity. MVMR analysis indicated that the association between genus Oxalobacter and obesity may be facilitated by 5alpha-androstan-3alpha,17alpha-diol monosulfate levels, with a mediation proportion of 8.504%. The association between genus Sutterella and obesity was likely mediated by the ratio of cholic acid to adenosine 5'-monophosphate(AMP), with a mediation proportion of 12.135%. Conclusion Current MR studies provide evidence supporting a causal relationship between genus Oxalobacter, genus Sutterella and obesity and potentially mediating metabolites.

Key words: Gut Microbiota, Obesity, Mendelian randomization, Cause-effect, Genetic analysis

中图分类号:

R574

赵万霞,詹群璋,金婷,刘玉新,曲崇正,吴剑纯. 基于孟德尔随机化分析肠道菌群、血液代谢物和肥胖的因果关系[J]. 山东大学学报 (医学版), 2026, 64(4): 72-82.

ZHAO Wanxia, ZHAN Qunzhang, JIN Ting, LIU Yuxin, QU Chongzheng, WU Jianchun. Mendelian randomization analysis of the causal relationships between gut microbiota, blood metabolites, and obesity[J]. Journal of Shandong University (Health Sciences), 2026, 64(4): 72-82.

参考文献

[1] Powell-Wiley TM, Poirier P, Burke LE, et al. Obesity and cardiovascular disease: a scientific statement from the American heart association[J]. Circulation, 2021, 143(21): 984-1010.
[2] WHO. Obesity and overweight[EB/OL].(2024-03-01)[2024-04-20]. https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight
[3] Wei YX, Zhan YQ, Carlsson S. Childhood adiposity and novel subtypes of diabetes in adults: a Mendelian randomisation and genome-wide genetic correlation study[J]. Lancet Glob Health, 2023, 11(Suppl 1): S1. doi: 10.1016/S2214-109X(23)00086-4
[4] Kim MS, Kim WJ, Khera AV, et al. Association between adiposity and cardiovascular outcomes: an umbrella review and meta-analysis of observational and mendelian randomization studies[J]. Eur Heart J, 2021, 42(34): 3388-3403.
[5] Aron-Wisnewsky J, Warmbrunn MV, Nieuwdorp M, et al. Metabolism and metabolic disorders and the microbiome: the intestinal microbiota associated with obesity, lipid metabolism, and metabolic health: pathophysiology and therapeutic strategies[J]. Gastroenterology, 2021, 160(2): 573-599.
[6] Liu P, Zhang Y, Zhang Z, et al. Antibiotic-induced dysbiosis of the gut microbiota impairs gene expression in gut-liver axis of mice [J]. Genes(Basel), 2023, 14(7): 1423.
[7] Asadi A, Shadab Mehr N, Mohamadi MH, et al. Obesity and gut-microbiota-brain axis: a narrative review[J]. J Clin Lab Anal, 2022, 36(5): e24420. doi: 10.1002/jcla.24420
[8] Su XM, Gao YH, Yang RC. Gut microbiota-derived tryptophan metabolites maintain gut and systemic homeostasis[J]. Cells, 2022, 11(15): 2296.doi: 10.3390/cells12050793
[9] Li Y, Wang X, Zhang ZT, et al. Effect of the gut microbiome, plasma metabolome, peripheral cells, and inflammatory cytokines on obesity: a bidirectional two-sample Mendelian randomization study and mediation analysis[J]. Front Immunol, 2024, 15: 1348347. doi: 10.3389/fimmu.2024.1348347
[10] Avuthu N, Guda C. Meta-analysis of altered gut microbiota reveals microbial and metabolic biomarkers for colorectal cancer[J]. Microbiol Spectr, 2022,10(4): e0001322.doi: 10.1128/spectrum.00013-22
[11] Jemimah S, Chabib CMM, Hadjileontiadis L, et al. Gut microbiome dysbiosis in Alzheimers disease and mild cognitive impairment: a systematic review and meta-analysis[J]. PLoS One, 2023, 18(5): e0285346. doi:10.1371/journal.pone.0285346
[12] Dai HJ, Hou T, Wang Q, et al. Causal relationships between the gut microbiome, blood lipids, and heart fai-lure: a Mendelian randomization analysis[J]. Eur J Prev Cardiol, 2023, 30(12): 1274-1282.
[13] Meng CJ, Deng PZ, Miao RJ, et al. Gut microbiome and risk of ischaemic stroke: a comprehensive Mendelian randomization study[J]. Eur J Prev Cardiol, 2023, 30(7): 613-620.
[14] Liu HJ, Zhang Y, Zhang HH, et al. Effect of plasma vitamin C levels on Parkinsons disease and age at onset: a Mendelian randomization study[J]. J Transl Med, 2021, 19(1): 221. doi: 10.1186/s12967-021-02892-5
[15] Ji D, Chen WZ, Zhang L, et al. Gut microbiota, circulating cytokines and dementia: a Mendelian randomization study[J]. J Neuroinflammation, 2024, 21(1): 2. doi: 10.1186/s12974-023-02999-0
[16] Fan JY, Zhou Y, Meng R, et al. Cross-talks between gut microbiota and tobacco smoking: a two-sample Mendelian randomization study[J]. BMC Med, 2023, 21(1): 163. doi: 10.1186/s12916-023-02863-1
[17] Yu MZ, Shang Y, Han LL, et al. Bowel habits, obesity, intestinal microbiota and their influence on hemorrhoidal disease: a Mendelian randomization study[J]. Clin Exp Gastroenterol, 2024, 17: 157-164. doi: 10.2147/CEG.S450807
[18] Chen YH, Lu TY, Pettersson-Kymmer U, et al. Genomic atlas of the plasma metabolome prioritizes metabolites implicated in human diseases[J]. Nat Genet, 2023, 55(1): 44-53.
[19] Liu XM, Tong X, Zou YQ, et al. Mendelian randomization analyses support causal relationships between blood metabolites and the gut microbiome[J]. Nat Genet, 2022, 54(1): 52-61.
[20] Xu SH, Liu YF, Wang Q, et al. Gut microbiota in combination with blood metabolites reveals characteristics of the disease cluster of coronary artery disease and cognitive impairment: a Mendelian randomization study[J]. Front Immunol, 2024, 14: 1308002. doi: 10.3389/fimmu.2023.1308002
[21] Gagnon E, Mitchell PL, Manikpurage HD, et al. Impact of the gut microbiota and associated metabolites on cardiometabolic traits, chronic diseases and human longevity: a Mendelian randomization study[J]. J Transl Med, 2023, 21(1): 60. doi: 10.1186/s12967-022-03799-5
[22] Wang XJ, Lu CR, Li X, et al. Exploring causal effects of gut microbiota and metabolites on body fat percentage using two-sample Mendelian randomization[J]. Diabetes Obes Metab, 2024, 26(9): 3541-3551.
[23] Long YW, Tang LH, Zhou YY, et al. Causal relationship between gut microbiota and cancers: a two-sample Mendelian randomisation study[J]. BMC Med, 2023, 21(1): 66. doi: 10.1186/s12916-023-02761-6
[24] Cui GH, Li SJ, Ye H, et al. Gut microbiome and frailty: insight from genetic correlation and mendelian randomization[J]. Gut Microbes, 2023, 15(2): 2282795. doi: 10.1080/19490976.2023.2282795
[25] Li PS, Wang HY, Guo L, et al. Association between gut Microbiota and preeclampsia-eclampsia: a two-sample mendelian randomization study[J]. BMC Med, 2022, 20(1): 443. doi: 10.1186/s12916-022-02657-x
[26] Zhao J, Pan X, Hao D, et al. Causal associations of gut microbiota and metabolites on sepsis: a two-sample Mendelian randomization study[J]. Front Immunol, 2023, 14: 1190230. doi: 10.3389/fimmu.2023.1190230
[27] Yao S, Han JZ, Guo J, et al. The causal relationships between gut microbiota, brain volume, and intelligence: a two-step Mendelian randomization analysis[J]. Biol Psychiatry, 2024, 96(6): 463-472.
[28] Grant AJ, Burgess S. Pleiotropy robust methods for multivariable Mendelian randomization[J]. Stat Med, 2021, 40(26): 5813-5830.
[29] Carter AR, Sanderson E, Hammerton G, et al. Mendelian randomisation for Mediation analysis: current methods and challenges for implementation[J]. Eur J Epidemiol, 2021, 36(5): 465-478.
[30] Wu XR, Lin DH, Li Q, et al. Investigating causal associations among gut microbiota, gut microbiota-derived metabolites, and gestational diabetes mellitus: a bidirectional Mendelian randomization study[J]. Aging(Albany NY), 2023, 15(16): 8345-8366.
[31] Yasir M, Angelakis E, Bibi F, et al. Comparison of the gut microbiota of people in France and Saudi Arabia[J]. Nutr Diabetes, 2015, 5(4): e153. doi: 10.1038/nutd.2015.3
[32] Squillario M, Bonaretti C, Valle AL, et al. Gut-microbiota in children and adolescents with obesity: inferred functional analysis and machine-learning algorithms to classify microorganisms[J]. Sci Rep, 2023, 13(1): 11294. doi: 10.1038/s41598-023-36533-2
[33] Joo M, Nam S. Adolescent gut microbiome imbalance and its association with immune response in inflammatory bowel diseases and obesity[J]. BMC Microbiol, 2024, 24(1): 268.
[34] Mbakwa CA, Hermes GDA, Penders J, et al. Gut microbiota and body weight in school-aged children: the KOALA birth cohort study[J]. Obesity(Silver Spring), 2018, 26(11): 1767-1776.
[35] Liu SY, Li F, Cai YJ, et al. Unraveling the mystery: a Mendelian randomized exploration of gut microbiota and different types of obesity[J]. Front Cell Infect Microbiol, 2024, 14: 1352109. doi: 10.3389/fcimb.2024.1352109
[36] Toubon G, Butel MJ, Rozé JC, et al. Association between gut microbiota at 3.5 years of age and body mass index at 5 years: results from two French nationwide birth cohorts[J]. Int J Obes(Lond), 2024, 48(4): 503-511.
[37] Guindo CO, Davoust B, Drancourt M, et al. Diversity of methanogens in animals gut[J]. Microorganisms, 2020, 9(1): 13. doi: 10.3390/microorganisms9010013
[38] Lin H, Li J, Sun MY, et al. Effects of hazelnut soluble dietary fiber on lipid-lowering and gut microbiota in high-fat-diet-fed rats[J]. Int J Biol Macromol, 2024, 256(Pt 2): 128538. doi: 10.1016/j.ijbiomac.2023.128538
[39] Chen X, Han LH, Xu WZ. Dissecting causal relationships between gut microbiota, blood metabolites, and glioblastoma multiforme: a two-sample Mendelian randomization study[J]. Front Microbiol, 2024, 15: 1403316. doi: 10.3389/fmicb.2024.1403316
[40] Bajaj JS, Tandon P, OLeary JG, et al. Admission se-rum metabolites and thyroxine predict advanced hepatic encephalopathy in a multicenter inpatient cirrhosis cohort[J]. Clin Gastroenterol Hepatol, 2023, 21(4): 1031-1040.

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