南方医科大学学报 ›› 2026, Vol. 46 ›› Issue (8): 1926-1935.doi: 10.12122/j.issn.1673-4254.2026.08.20
• • 上一篇
李德臣1,2(
), 李彦杰2(
), 杨新宇1, 王亚文1, 渠燕飞1
收稿日期:2025-12-22
出版日期:2026-08-20
发布日期:2026-08-01
通讯作者:
李彦杰
E-mail:3397216447@qq.com;yanjieli2008@126.com
作者简介:李德臣,在读硕士研究生,E-mail: 3397216447@qq.com
基金资助:
Dechen LI1,2(
), Yanjie LI2(
), Xinyu YANG1, Yawen WANG1, Yanfei QU1
Received:2025-12-22
Online:2026-08-20
Published:2026-08-01
Contact:
Yanjie LI
E-mail:3397216447@qq.com;yanjieli2008@126.com
摘要:
目的 孟德尔随机化(MR)探究肠道菌群(GM)与阿尔茨海默症(AD)的因果关联及循环代谢物的介导作用,为AD相关生物标志物和干预靶点提供遗传学依据。 方法 基于全基因组关联分析数据,采用两样本MR设计开展研究。筛选473种GM及233种循环代谢物的有效工具变量,通过R软件进行统计分析,以逆方差加权法作为主要分析方法,MR-Egger法和加权中位数法作为补充验证;结合多种敏感性分析评估结果稳定性,并通过反向MR分析验证因果关系方向;再进一步采用中介MR分析明确循环代谢物的潜在介导效应。 结果 马赛阴性杆菌丰度与AD发病风险之间存在正向因果关联(OR=1.204,95% CI:1.020-1.421,P=0.028),敏感性分析结果稳定可靠(P>0.05),反向MR分析未发现AD对马赛阴性杆菌丰度存在显著因果效应(P=0.678)。中介MR分析显示,在马赛阴性杆菌对AD的总效应中,经极小型极低密度脂蛋白中游离胆固醇与总脂质比率(v-VLDL FC/TL)介导的间接效应占6.63%。 结论 从遗传因果推断层面提示,马赛阴性杆菌可能与AD发病风险升高相关,且v-VLDL FC/TL可能在其中发挥部分中介作用,这为AD的预防和治疗提供了潜在靶点。
李德臣, 李彦杰, 杨新宇, 王亚文, 渠燕飞. 473种肠道菌群与阿尔茨海默症:基于233种循环代谢物的孟德尔随机化中介分析[J]. 南方医科大学学报, 2026, 46(8): 1926-1935.
Dechen LI, Yanjie LI, Xinyu YANG, Yawen WANG, Yanfei QU. Association between 473 gut microbiota and Alzheimer's disease: a Mendelian randomization mediation analysis of 233 circulating metabolites[J]. Journal of Southern Medical University, 2026, 46(8): 1926-1935.
| Rank | Outcome | Method | β | SE | P |
|---|---|---|---|---|---|
| Kingdom | Cyanobacteria | IVW | -0.016 | 0.009 | 0.082 |
| Phylum | Actinobacteriota | IVW | 0.011 | 0.018 | 0.548 |
| Order | Francisellales | IVW | -0.005 | 0.007 | 0.447 |
| Order | Parachlamydiales | IVW | -0.007 | 0.006 | 0.223 |
| Order | Sporomusales | IVW | 0.004 | 0.005 | 0.382 |
| Family | Desulfovibrionaceae | IVW | 0.008 | 0.015 | 0.608 |
| Family | Treponemataceae | IVW | -0.011 | 0.016 | 0.513 |
| Genus | Eubacterium Q | IVW | -0.006 | 0.020 | 0.766 |
| Genus | Klebsiella | IVW | -0.002 | 0.006 | 0.690 |
| Genus | Spirillospora | IVW | 0.016 | 0.014 | 0.254 |
| Genus | Azorhizobium | IVW | -0.001 | 0.006 | 0.850 |
| Species | Bifidobacterium adolescentis | IVW | -0.012 | 0.008 | 0.135 |
| Species | Negativibacillus massiliensis | IVW | 0.006 | 0.015 | 0.678 |
| Species | CAG-110 | IVW | -0.004 | 0.028 | 0.898 |
| Species | CAG-449 | IVW | -0.006 | 0.009 | 0.496 |
| Species | CAG-488 | IVW | 0.001 | 0.033 | 0.996 |
| Species | Massiliomicrobiota sp002160815 | IVW | -0.001 | 0.013 | 0.974 |
| Species | Bifidobacterium pseudocatenulatum | IVW | 0.001 | 0.005 | 0.807 |
| Species | GCA-900066135 sp900066135 | IVW | 0.001 | 0.007 | 0.990 |
表2 19种肠道菌群与阿尔茨海默症的反向MR分析结果
Tab.2 Results of reverse Mendelian randomization analysis between AD and 19 gut microbiota taxa
| Rank | Outcome | Method | β | SE | P |
|---|---|---|---|---|---|
| Kingdom | Cyanobacteria | IVW | -0.016 | 0.009 | 0.082 |
| Phylum | Actinobacteriota | IVW | 0.011 | 0.018 | 0.548 |
| Order | Francisellales | IVW | -0.005 | 0.007 | 0.447 |
| Order | Parachlamydiales | IVW | -0.007 | 0.006 | 0.223 |
| Order | Sporomusales | IVW | 0.004 | 0.005 | 0.382 |
| Family | Desulfovibrionaceae | IVW | 0.008 | 0.015 | 0.608 |
| Family | Treponemataceae | IVW | -0.011 | 0.016 | 0.513 |
| Genus | Eubacterium Q | IVW | -0.006 | 0.020 | 0.766 |
| Genus | Klebsiella | IVW | -0.002 | 0.006 | 0.690 |
| Genus | Spirillospora | IVW | 0.016 | 0.014 | 0.254 |
| Genus | Azorhizobium | IVW | -0.001 | 0.006 | 0.850 |
| Species | Bifidobacterium adolescentis | IVW | -0.012 | 0.008 | 0.135 |
| Species | Negativibacillus massiliensis | IVW | 0.006 | 0.015 | 0.678 |
| Species | CAG-110 | IVW | -0.004 | 0.028 | 0.898 |
| Species | CAG-449 | IVW | -0.006 | 0.009 | 0.496 |
| Species | CAG-488 | IVW | 0.001 | 0.033 | 0.996 |
| Species | Massiliomicrobiota sp002160815 | IVW | -0.001 | 0.013 | 0.974 |
| Species | Bifidobacterium pseudocatenulatum | IVW | 0.001 | 0.005 | 0.807 |
| Species | GCA-900066135 sp900066135 | IVW | 0.001 | 0.007 | 0.990 |
| Exposure | Outcome | Methods | β | SE | P |
|---|---|---|---|---|---|
| AD | v-VLDL FC/TL | MR Egger | -0.009 | 0.012 | 0.457 |
| AD | v-VLDL FC/TL | Weighted median | -0.016 | 0.007 | 0.135 |
| AD | v-VLDL FC/TL | IVW | -0.005 | 0.008 | 0.547 |
表3 代谢物(v-VLDL FC/TL)与阿尔茨海默症的反向因果分析
Tab.3 Reverse causal analysis of metabolites (v-VLDL FC/TL) and AD
| Exposure | Outcome | Methods | β | SE | P |
|---|---|---|---|---|---|
| AD | v-VLDL FC/TL | MR Egger | -0.009 | 0.012 | 0.457 |
| AD | v-VLDL FC/TL | Weighted median | -0.016 | 0.007 | 0.135 |
| AD | v-VLDL FC/TL | IVW | -0.005 | 0.008 | 0.547 |
图4 马赛阴性杆菌-代谢物-阿尔茨海默症的因果关联分析图
Fig.4 Causal association analysis among Negativibacillus massiliensis, metabolites, and AD. A: Forest plot of the association between the metabolite (v-VLDL FC/TL) and AD. B: Forest plot of the association between Negativibacillus massiliensis and v-VLDL FC/TL. C: Leave-one-out analysis of the association between v-VLDL FC/TL and AD. D: Leave-one-out analysis of the association between Negativibacillus massiliensis and v-VLDL FC/TL.
| Exposure | SNPs | Beta | P | F |
|---|---|---|---|---|
| Negativibacillus massiliensis | rs117450486 | 0.013 | 4.1e-08 | 30.106 |
| Negativibacillus massiliensis | rs1242927 | 0.002 | 1.9e-06 | 22.731 |
| Negativibacillus massiliensis | rs1326749 | 0.018 | 8.5e-06 | 19.813 |
| Negativibacillus massiliensis | rs1497993 | 0.043 | 8.7e-06 | 19.786 |
| Negativibacillus massiliensis | rs16851304 | -0.009 | 7.3e-06 | 20.108 |
| Negativibacillus massiliensis | rs17552264 | 0.018 | 6.6e-06 | 20.294 |
| Negativibacillus massiliensis | rs188774576 | 0.029 | 5.1e-06 | 20.801 |
| Negativibacillus massiliensis | rs2641348 | -0.021 | 5.5e-06 | 20.648 |
| Negativibacillus massiliensis | rs2763223 | -0.017 | 8.7e-06 | 19.774 |
| Negativibacillus massiliensis | rs28634441 | 0.009 | 4e-06 | 21.271 |
| Negativibacillus massiliensis | rs36124608 | 0.039 | 9e-06 | 19.719 |
| Negativibacillus massiliensis | rs4898867 | -0.007 | 6.6e-06 | 20.299 |
| Negativibacillus massiliensis | rs4979255 | -0.016 | 5.3e-06 | 20.716 |
| Negativibacillus massiliensis | rs5771271 | -0.023 | 3.7e-06 | 21.393 |
| Negativibacillus massiliensis | rs73279647 | -0.116 | 4.7e-06 | 20.969 |
| Negativibacillus massiliensis | rs74032121 | -0.001 | 2.7e-06 | 22.055 |
| Negativibacillus massiliensis | rs79831182 | -0.016 | 9.4e-06 | 19.621 |
| Negativibacillus massiliensis | rs9384293 | 0.039 | 8.4e-06 | 19.845 |
表5 马赛阴性杆菌相关SNP及其在孟德尔随机化分析中的工具变量特征
Tab.5 SNPs associated with Negativibacillus and their instrumental variable characteristics in Mendelian randomization analysis
| Exposure | SNPs | Beta | P | F |
|---|---|---|---|---|
| Negativibacillus massiliensis | rs117450486 | 0.013 | 4.1e-08 | 30.106 |
| Negativibacillus massiliensis | rs1242927 | 0.002 | 1.9e-06 | 22.731 |
| Negativibacillus massiliensis | rs1326749 | 0.018 | 8.5e-06 | 19.813 |
| Negativibacillus massiliensis | rs1497993 | 0.043 | 8.7e-06 | 19.786 |
| Negativibacillus massiliensis | rs16851304 | -0.009 | 7.3e-06 | 20.108 |
| Negativibacillus massiliensis | rs17552264 | 0.018 | 6.6e-06 | 20.294 |
| Negativibacillus massiliensis | rs188774576 | 0.029 | 5.1e-06 | 20.801 |
| Negativibacillus massiliensis | rs2641348 | -0.021 | 5.5e-06 | 20.648 |
| Negativibacillus massiliensis | rs2763223 | -0.017 | 8.7e-06 | 19.774 |
| Negativibacillus massiliensis | rs28634441 | 0.009 | 4e-06 | 21.271 |
| Negativibacillus massiliensis | rs36124608 | 0.039 | 9e-06 | 19.719 |
| Negativibacillus massiliensis | rs4898867 | -0.007 | 6.6e-06 | 20.299 |
| Negativibacillus massiliensis | rs4979255 | -0.016 | 5.3e-06 | 20.716 |
| Negativibacillus massiliensis | rs5771271 | -0.023 | 3.7e-06 | 21.393 |
| Negativibacillus massiliensis | rs73279647 | -0.116 | 4.7e-06 | 20.969 |
| Negativibacillus massiliensis | rs74032121 | -0.001 | 2.7e-06 | 22.055 |
| Negativibacillus massiliensis | rs79831182 | -0.016 | 9.4e-06 | 19.621 |
| Negativibacillus massiliensis | rs9384293 | 0.039 | 8.4e-06 | 19.845 |
| [1] | Scheltens P, De Strooper B, Kivipelto M, et al. Alzheimer's disease[J]. Lancet, 2021, 397(10284): 1577-90. doi:10.1016/s0140-6736(20)32205-4 |
| [2] | Twarowski B, Herbet M. Inflammatory processes in Alzheimer's disease-pathomechanism, diagnosis and treatment: a review[J]. Int J Mol Sci, 2023, 24(7): 6518. doi:10.3390/ijms24076518 |
| [3] | Ossenkoppele R, van der Kant R, Hansson O. Tau biomarkers in Alzheimer’s disease: towards implementation in clinical practice and trials[J]. Lancet Neurol, 2022, 21(8): 726-34. doi:10.1016/s1474-4422(22)00168-5 |
| [4] | Rostagno AA. Pathogenesis of Alzheimer's disease[J]. Int J Mol Sci, 2022, 24(1): 107. doi:10.3390/ijms24010107 |
| [5] | Bomasang-Layno E, Bronsther R. Diagnosis and treatment of Alzheimer's disease: : an update[J]. Dela J Public Health, 2021, 7(4): 74-85. doi:10.32481/djph.2021.09.009 |
| [6] | Li SP, Han WF, He QC, et al. Relationship between intestinal microflora and hepatocellular cancer based on gut-liver axis theory[J]. Contrast Media Mol Imaging, 2022, 2022: 6533628. doi:10.1155/2022/6533628 |
| [7] | Socała K, Doboszewska U, Szopa A, et al. The role of microbiota-gut-brain axis in neuropsychiatric and neurological disorders[J]. Pharmacol Res, 2021, 172: 105840. doi:10.1016/j.phrs.2021.105840 |
| [8] | O’Riordan KJ, Moloney GM, Keane L, et al. The gut microbiota-immune-brain axis: Therapeutic implications[J]. Cell Rep Med, 2025, 6(3): 101982. doi:10.1016/j.xcrm.2025.101982 |
| [9] | Lu X, Xue ZY, Qian Y, et al. Changes in intestinal microflora and its metabolites underlie the cognitive impairment in preterm rats[J]. Front Cell Infect Microbiol, 2022, 12: 945851. doi:10.3389/fcimb.2022.945851 |
| [10] | Silva YP, Bernardi A, Frozza RL. The role of short-chain fatty acids from gut microbiota in gut-brain communication[J]. Front Endocrinol, 2020, 11: 25. doi:10.3389/fendo.2020.00025 |
| [11] | He M, Wei WQ, Zhang YC, et al. Gut microbial metabolites SCFAs and chronic kidney disease[J]. J Transl Med, 2024, 22(1): 172. doi:10.1186/s12967-024-04974-6 |
| [12] | Wang YL, Li L, Zhao XD, et al. Intestinal microflora changes in patients with mild Alzheimer's disease in a Chinese cohort[J]. J Alzheimers Dis, 2022, 88(2): 563-75. doi:10.3233/jad-220076 |
| [13] | Elmas A, Spehar K, Do R, et al. Associations of circulating biomarkers with disease risks: a two-sample Mendelian randomization study[J]. Int J Mol Sci, 2024, 25(13): 7376. doi:10.3390/ijms25137376 |
| [14] | Bhattacharyya U, John J, Lam M, et al. Circulating blood-based proteins in psychopathology and cognition: a Mendelian randomization study[J]. JAMA Psychiatry, 2025, 82(5): 481-91. doi:10.1001/jamapsychiatry.2025.0033 |
| [15] | Lv YC, Cheng X, Dong Q. SGLT1 and SGLT2 inhibition, circulating metabolites, and cerebral small vessel disease: a mediation Mendelian Randomization study[J]. Cardiovasc Diabetol, 2024, 23(1): 157. doi:10.1186/s12933-024-02255-6 |
| [16] | Huang SY, Yang YX, Zhang YR, et al. Investigating causal relations between circulating metabolites and Alzheimer's disease: a Mendelian randomization study[J]. J Alzheimers Dis, 2022, 87(1): 463-77. doi:10.3233/jad-220050 |
| [17] | Tettevi EJ, Simpong DL, Maina M, et al. Antibiotic-induced gut dysbiosis modulates Alzheimer's disease-associated gene expression and protein aggregation in 3xTg-AD mice via the gut–brain axis[J]. Brain Behav, 2025, 15(10): e70946. doi:10.1002/brb3.70946 |
| [18] | 雷雯慧, 高 婕, 徐 鹏, 等. 阿尔茨海默病肠道细菌和真菌菌群结构和组成改变研究[J]. 中国微生态学杂志, 2024, 36(5): 577-83. doi:10.13381/j.cnki.cjm.202405013 |
| [19] | Loh JS, Mak WQ, Tan LKS, et al. Microbiota-gut-brain axis and its therapeutic applications in neurodegenerative diseases[J]. Signal Transduct Target Ther, 2024, 9(1): 37. doi:10.1038/s41392-024-01743-1 |
| [20] | Qin YW, Havulinna AS, Liu Y, et al. Combined effects of host genetics and diet on human gut microbiota and incident disease in a single population cohort[J]. Nat Genet, 2022, 54(2): 134-42. doi:10.1038/s41588-021-00991-z |
| [21] | Karjalainen MK, Karthikeyan S, Oliver-Williams C, et al. Genome-wide characterization of circulating metabolic biomarkers[J]. Nature, 2024, 628(8006): 130-8. |
| [22] | Li PS, Wang HY, Guo L, et al. Association between gut microbiota and preeclampsia-eclampsia: a two-sample Mendelian random-ization study[J]. BMC Med, 2022, 20(1): 443. doi:10.1186/s12916-022-02657-x |
| [23] | Wu J, Li CS, Huang WY, et al. Gut microbiota promote the propagation of pathologic α-syn from gut to brain in a gut-originated mouse model of Parkinson's disease[J]. Brain Behav Immun, 2025, 128: 152-69. doi:10.1016/j.bbi.2025.04.001 |
| [24] | Yadav S, Raj RG. Parkinson's disease and the gut microbiota connection: unveiling dysbiosis and exploring therapeutic horizons[J]. Neuroscience, 2025, 581: 1-15. doi:10.1016/j.neuroscience.2025.07.003 |
| [25] | Yan ZZ, Yang F, Cao JW, et al. Alterations of gut microbiota and metabolome with Parkinson's disease[J]. Microb Pathog, 2021, 160: 105187. doi:10.1016/j.micpath.2021.105187 |
| [26] | Kalyanaraman B, Cheng G, Hardy M. Gut microbiome, short-chain fatty acids, alpha-synuclein, neuroinflammation, and ROS/RNS: Relevance to Parkinson's disease and therapeutic implications[J]. Redox Biol, 2024, 71: 103092. doi:10.1016/j.redox.2024.103092 |
| [27] | Aho VTE, Houser MC, Pereira PAB, et al. Relationships of gut microbiota, short-chain fatty acids, inflammation, and the gut barrier in Parkinson's disease[J]. Mol Neurodegener, 2021, 16(1): 6. doi:10.1186/s13024-021-00427-6 |
| [28] | Chen Z, Chen ZY, Jin XL. Mendelian randomization supports causality between overweight status and accelerated aging[J]. Aging Cell, 2023, 22(8): e13899. doi:10.1111/acel.13899 |
| [29] | Lv XF, Liang FQ, Liu SS, et al. Causal relationship between diet and knee osteoarthritis: a Mendelian randomization analysis[J]. PLoS One, 2024, 19(1): e0297269. doi:10.1371/journal.pone.0297269 |
| [30] | Liang Z, Zhao L, Lou Y, et al. Causal effects of circulating lipids and lipid-lowering drugs on the risk of epilepsy: a two-sample Mendelian randomization study[J]. QJM, 2023, 116(6): 421-8. doi:10.1093/qjmed/hcad048 |
| [31] | Zhu X, Huang SJ, Kang WY, et al. Associations between polyunsaturated fatty acid concentrations and Parkinson's disease: a two-sample Mendelian randomization study[J]. Front Aging Neurosci, 2023, 15: 1123239. doi:10.3389/fnagi.2023.1123239 |
| [32] | Ndongo S, Dubourg G, Bittar F, et al. Marseillibacter massiliensis gen. nov., sp. nov., a new bacterial genus isolated from the human gut[J]. New Microbes New Infect, 2017, 16: 30-1. doi:10.1016/j.nmni.2016.12.006 |
| [33] | Tran VTA, Kang YJ, Kim HK, et al. Oral pathogenic bacteria-inducing neurodegenerative microgliosis in human neural cell platform[J]. Int J Mol Sci, 2021, 22(13): 6925. doi:10.3390/ijms22136925 |
| [34] | Wu LC, Du LL, Ju QQ, et al. Silencing TLR4/MyD88/NF‑κB signaling pathway alleviated inflammation of corneal epithelial cells infected by ISE[J]. Inflammation, 2021, 44(2): 633-44. doi:10.1007/s10753-020-01363-1 |
| [35] | Shi J, Wang F, Tang L, et al. Akkermansia muciniphila attenuates LPS-induced acute kidney injury by inhibiting TLR4/NF‑κB pathway[J]. FEMS Microbiol Lett, 2022, 369(1): fnac103. doi:10.1093/femsle/fnac103 |
| [36] | Wu XY, Wei JJ, Ran W, et al. The gut microbiota-xanthurenic acid-aromatic hydrocarbon receptor axis mediates the anticolitic effects of trilobatin[J]. Adv Sci, 2025, 12(10): 2412234. doi:10.1002/advs.202412234 |
| [37] | Yu X, Shen GX, Zhang Y, et al. Genetically predicted small dense low-density lipoprotein cholesterol and ischemic stroke subtype: multivariable Mendelian randomization study[J]. Front Endocrinol, 2024, 15: 1404234. doi:10.3389/fendo.2024.1404234 |
| [38] | Hashemi M, Banerjee S, Lyubchenko YL. Free cholesterol accelerates aβ self-assembly on membranes at physiological concentration[J]. Int J Mol Sci, 2022, 23(5): 2803. doi:10.3390/ijms23052803 |
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