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“心合小肠”理论视域下从“肠-心轴”解析肠道菌群与心肌梗死的因果关联及干预中药预测

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中草药 | 数据挖掘与循证医学 2026,57(7): 2622-2639

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中草药 |数据挖掘与循证医学 2026 , 57 (7) : 2622 -2639

“心合小肠”理论视域下从“肠-心轴”解析肠道菌群与心肌梗死的因果关联及干预中药预测

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宁博¹, 党思杰², 吕宸蕖³, 雷雨轩⁴, 郑张梁¹, 贾陆明¹, 罗成⁵, 杨良滨¹, 葛腾¹, 赵明君⁴, 邹荣军^1,6, 彭继海⁶, 范小平^1,6

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彭继海

作者简介:

宁博: 宁博,博士研究生,研究方向为中西医结合防治心血管疾病的基础与临床研究。E-mail:ningbo9803@163.com

Exploring causal association between gut microbiota and myocardial infarction from perspective of “gut-heart axis” based on theory of “heart-small intestine relationship” and predicting intervention with traditional Chinese medicine

NING Bo, DANG Sijie, LYU Chenqu, LEI Yuxuan, ZHENG Zhangliang, JIA Luming, LUO Cheng, YANG Liangbin, GE Teng, ZHAO Mingjun, ZOU Rongjun, PENG Jihai, FAN Xiaoping

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doi: 10.7501/j.issn.0253-2670.2026.07.017

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摘要

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目的基于“心合小肠”理论与“肠-心轴”学说，采用孟德尔随机化（Mendelian randomization，MR）结合生物信息学方法，明确与心肌梗死（myocardial infarction，MI）存在遗传因果效应的肠道菌群，挖掘其潜在机制并预测干预中药。方法从MiBioGen、IEU GWAS及GEO数据库获取肠道菌群、MI的全基因组关联研究（genome-wide association study，GWAS）及基因表达数据，以逆方差加权法（inverse variance weighted，IVW）为主要方法进行MR分析，通过基因本体（gene ontology，GO）和京都基因与基因组百科全书（Kyoto encyclopedia of genes and genomes，KEGG）富集分析解析机制，借助机器学习筛选核心基因，结合Coremine Medical等数据库预测潜在中药并分析其性味归经与功效。结果 MR分析发现6种肠道菌群与MI存在遗传因果关联，丁酸球菌属Butyricicoccus为保护因素（OR＜1，P＜0.05），毛梭菌属Lachnoclostridium、瘤胃球菌科UCG014属（Ruminococcaceae UCG014）、臭气杆菌属Odoribacter、草酸杆菌属Oxalobacter、塞尔利莫纳斯菌属Sellimonas 5种菌群为风险因素（OR＞1，P＜0.05）。核心基因主要富集于肝配蛋白（Ephrin，Eph）受体信号通路、钙信号通路及丝裂原活化蛋白激酶（mitogen activated protein kinases，MAPK）信号通路等。预测得到596味潜在中药，四气以温、寒、平为主，五味以甘、苦、辛为主，功效以清热解毒为核心，代表中药有人参、三七、黄连等，相关经典名方包括小柴胡汤、桃红四物汤等。结论揭示了肠道菌群介导MI发生的遗传因果关联及分子机制，丰富了“心合小肠”理论的现代生物学内涵，预测的中药为MI的中医药防治提供了新策略，也为“肠-心轴”相关研究提供了参考。

关键词

心肌梗死 / 肠道菌群 / 心合小肠 / 肠-心轴 / 孟德尔随机化 / 人参 / 三七 / 黄连 / 小柴胡汤 / 桃红四物汤

Abstract

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Objective Based on the theory of “heart-small intestine relationship” and the “gut-heart axis” hypothesis, this study applies Mendelian randomization (MR) and bioinformatics approaches to investigate gut microbiota with genetic causal effects on myocardial infarction (MI), explore underlying mechanisms, and predict potential interventional traditional Chinese medicines. Methods Genome-wide association study (GWAS) and gene expression data for gut microbiota and MI were obtained from the MiBioGen, IEU GWAS and GEO databases. MR analysis was primarily performed using the inverse variance weighted (IVW) method. Potential mechanisms were explored through gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses. Core genes were screened via machine learning algorithms. Potential traditional Chinese medicines were predicted by integrating the Coremine database, and their properties (four qi), flavors (five tastes), meridian tropism, and functions were statistically analyzed. Results MR analysis revealed six gut microbiota taxa with genetically causal associations with MI: Butyricicoccus (a protective factor, OR < 1, P < 0.05), Lachnoclostridium, Ruminococcaceae UCG014, Odoribacter, Oxalobacter, and Sellimonas (risk factors, OR > 1, P < 0.05).The core genes were mainly enriched in signaling pathways including the ephrin receptor signaling pathway, calcium signaling pathway, and mitogen activated protein kinases (MAPK) signaling pathway. A total of 596 potential traditional Chinese medicines were predicted. Their properties (four qi) were predominantly warm, followed by cold and neutral; their flavors (five tastes) were primarily sweet, with bitter and pungent also being notable. The main therapeutic functions identified were clearing heat and detoxifying. Representative medicines included Renshen (Ginseng Radix et Rhizoma), Sanqi (Notoginseng Radix et Rhizoma), and Huanglian (Coptidis Rhizoma). Related classical prescriptions encompassed Xiaochaihu Decoction (小柴胡汤) and Taohong Siwu Decoction (桃红四物汤). Conclusion This study reveals the genetic causal relationship and molecular mechanisms through which gut microbiota mediates the occurrence of MI. It enriches the modern biological connotation of the “heart-small intestine relationship” theory. The predicted traditional Chinese medicines provide new strategies for the traditional Chinese medicine-based prevention and treatment of MI and offer a reference for further investigation into the “gut-heart axis”.

Key words

myocardial infarction / gut microbiota / heart-small intestine relationship / gut-heart axis / Mendelian randomization / Ginseng Radix et Rhizoma / Notoginseng Radix et Rhizoma / Coptidis Rhizoma / Xiaochaihu Decoction / Taohong Siwu Decoction

引用本文

宁博, 党思杰, 吕宸蕖, 雷雨轩, 郑张梁, 贾陆明, 罗成, 杨良滨, 葛腾, 赵明君, 邹荣军, 彭继海, 范小平. “心合小肠”理论视域下从“肠-心轴”解析肠道菌群与心肌梗死的因果关联及干预中药预测. 中草药, 2026 , 57 (7) : 2622 -2639 . DOI: 10.7501/j.issn.0253-2670.2026.07.017

NING Bo, DANG Sijie, LYU Chenqu, LEI Yuxuan, ZHENG Zhangliang, JIA Luming, LUO Cheng, YANG Liangbin, GE Teng, ZHAO Mingjun, ZOU Rongjun, PENG Jihai, FAN Xiaoping. Exploring causal association between gut microbiota and myocardial infarction from perspective of “gut-heart axis” based on theory of “heart-small intestine relationship” and predicting intervention with traditional Chinese medicine[J]. Chinese Traditional and Herbal Drugs, 2026 , 57 (7) : 2622 -2639 . DOI: 10.7501/j.issn.0253-2670.2026.07.017

基金

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国家自然科学基金项目 (82374240,82300315); 国家中医药管理局高水平中医药重点学科建设项目-中医药人才培养重点学科建设项目“中医心病学” (zyyzdxk-2023160); 广东省基础与应用基础研究基金项目 (2024A1515012174,2024A1515013184,2025A1515012690); 广东省中医药局科研项目 (20241120); 国家中医药传承创新发展示范试点项目-广州中医药大学与中山市中医院(第十临床医学院)高水平医院共建项目 (GZYZS2024G15); 广东省中医院毛静远学术经验传承工作室建设项目 (中医二院[2025]17号); 癌症、心脑血管、呼吸和代谢性疾病防治研究国家科技重大专项 (2024ZD0528206,2024ZD0528200); 广东省中医院范小平科研启动经费项目 (2021KT1709)

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2026年第57卷第7期

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doi: 10.7501/j.issn.0253-2670.2026.07.017

接收时间：2025-12-07
首发时间：2026-09-09

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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