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Article(id=1240651443116495498, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240651438955754377, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202312254, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1702569600000, receivedDateStr=2023-12-15, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773723954227, onlineDateStr=2026-03-17, pubDate=1719244800000, pubDateStr=2024-06-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773723954227, onlineIssueDateStr=2026-03-17, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773723954227, creator=13701087609, updateTime=1773723954227, updator=13701087609, issue=Issue{id=1240651438955754377, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='12', pageStart='2113', pageEnd='2912', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773723953236, creator=13701087609, updateTime=1773723953236, updator=13701087609, preIssue=null, nextIssue=null, ext=null, issueFiles=null}, startPage=2152, endPage=2158, ext={EN=ArticleExt(id=1240651444819382991, articleId=1240651443116495498, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Relationship between intestinal flora and type 2 diabetes: a two-sample Mendelian randomization study, columnId=1228016567443718970, journalTitle=Modern Preventive Medicine, columnName=Epidemiology and Statistical Methods Advances, runingTitle=null, highlight=null, articleAbstract=
Objective

To explore the causal association between gut microbiota and type 2 diabetes mellitus (T2DM) using two-sample Mendelian randomization.

Methods

The data of single nucleotide polymorphisms (SNP) of gut microbiota as an exposure factor and type 2 diabetes mellitus as an outcome variable were obtained from the public genome-wide association study database. MR-Egger, weighted median method, inverse variance weighted method (IVW), simple model, and weighted model were used for MR Analysis. The MR-Egger method and IVW method were used for heterogeneity analysis. MR-Egger intercept was used to test the pleiotropy of the data, and the leave-one-out method was used for sensitivity analysis to evaluate the robustness of the results.

Results

A total of 7 gut microbiota were found to be associated with type 2 diabetes in East Asians, and the risk bacteria were Eubacteriumnodatumgroup, Ruminococcaceae UCG010, Lachnospiraceae NK4A136 group, Victivall, and protect bacteria were Enterorhabdus, Erysipelatoclostridium, Romboutsia. There were a total of four kinds of intestinal flora in the European population associated with type 2 diabetes, dangerous bacteria were Howardella, Eubacteriumruminantiumgroup, Eubacteriumventriosumgroup, and protect bacteria were FamilyXIIIAD3011group.

Conclusion

Specific gut microbiota may have causal effects on the risk of type 2 diabetes.

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目的

利用两样本孟德尔随机化法探讨肠道菌群与2型糖尿病之间的因果关联。

方法

在公开的全基因组关联研究数据库中获取暴露因素肠道菌群及结局变量2型糖尿病的单核苷酸多态性（SNP）数据；采用MR-Egger、加权中位数法、逆方差加权法(IVW)、简单模型、加权模型5种回归模型进行MR分析，采用MR-Egger法和IVW法进行异质性分析，MR-Egger截距测试数据的多效性，留一法进行敏感性分析，评估结果的稳健性。

结果

在东亚人群中共有7种肠道菌群与2型糖尿病相关，其中危险菌有:Eubacteriumnodatumgroup, RuminococcaceaeUCG010,LachnospiraceaeNK4A136group,Victivall,保护菌有:Enterorhabdus,Erysipelatoclostridium, Romboutsia; 在欧洲人群中共有4种肠道菌群与2型糖尿病相关，危险菌有:Howardella,Eubacteriumruminantiumgroup,Eubacteriumventriosumgroup，保护菌有:FamilyXIIIAD3011group。

结论

特定肠道菌群对2型糖尿病风险具有一定因果关联。

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陆灏，E-mail:
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陶丽宇（1993—），女，博士在读，研究方向：中西医结合防治糖尿病及其并发症

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陶丽宇（1993—），女，博士在读，研究方向：中西医结合防治糖尿病及其并发症

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Summary table of GWAS data information

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暴露/结局年份GWAS号人种样本量SNP数量PubmedID下载网址
肠道菌群2021混合18 340122 11033 462 485https://mibiogen.gcc.rug.nl/
T2DM2020ebi-a-GCST010118东亚433 54011 222 50732 499 647https://gwas.mrcieu.ac.uk/
T2DM2018ebi-a-GCST005413欧洲70 12714 277 79129 358 691https://gwas.mrcieu.ac.uk/
), ArticleFig(id=1240651450494275673, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240651443116495498, language=CN, label=表1, caption=

GWAS数据信息汇总表

, figureFileSmall=null, figureFileBig=null, tableContent=
暴露/结局年份GWAS号人种样本量SNP数量PubmedID下载网址
肠道菌群2021混合18 340122 11033 462 485https://mibiogen.gcc.rug.nl/
T2DM2020ebi-a-GCST010118东亚433 54011 222 50732 499 647https://gwas.mrcieu.ac.uk/
T2DM2018ebi-a-GCST005413欧洲70 12714 277 79129 358 691https://gwas.mrcieu.ac.uk/
), ArticleFig(id=1240651450628493414, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240651443116495498, language=EN, label=Table 2, caption=

Mendelian randomization analysis of the causal relationship between gut microbiota and T2DM

, figureFileSmall=null, figureFileBig=null, tableContent=
结局暴露SNP数量MR结果（IVW）异质性（IVW）P值多效性（MR Egger）P值
β值P值OR值（95%CI）
T2DM(东亚)Eubacteriumnodatumgroup80.0550.0141.057（1.011~1.105）0.9830.686
Enterorhabdus7-0.0870.0110.917（0.857~0.981）0.1120.223
RuminococcaceaeUCG01070.0950.0481.099（1.001~1.207）0.7610.740
Erysipelatoclostridium15-0.0570.0500.945（0.893~1.000）0.5060.823
LachnospiraceaeNK4A136group120.0690.0401.071（1.003~1.144）0.4100.638
Romboutsia11-0.0740.0310.929（0.868~0.993）0.4370.860
Victivall100.0450.0221.046（1.007~1.088）0.5960.546
T2DM(欧洲)Howardella110.1170.0311.124（1.011~1.250）0.1970.385
FamilyXIIIAD3011group15-0.1920.0170.825（0.705~0.966）0.4030.977
Eubacteriumruminantiumgroup190.1040.0371.109（1.006~1.223）0.7590.354
Eubacteriumventriosumgroup150.1800.0211.197（1.027~1.396）0.7020.231
), ArticleFig(id=1240651450703990892, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240651443116495498, language=CN, label=表2, caption=

肠道菌群与T2DM因果关系的孟德尔分析

, figureFileSmall=null, figureFileBig=null, tableContent=
结局暴露SNP数量MR结果（IVW）异质性（IVW）P值多效性（MR Egger）P值
β值P值OR值（95%CI）
T2DM(东亚)Eubacteriumnodatumgroup80.0550.0141.057（1.011~1.105）0.9830.686
Enterorhabdus7-0.0870.0110.917（0.857~0.981）0.1120.223
RuminococcaceaeUCG01070.0950.0481.099（1.001~1.207）0.7610.740
Erysipelatoclostridium15-0.0570.0500.945（0.893~1.000）0.5060.823
LachnospiraceaeNK4A136group120.0690.0401.071（1.003~1.144）0.4100.638
Romboutsia11-0.0740.0310.929（0.868~0.993）0.4370.860
Victivall100.0450.0221.046（1.007~1.088）0.5960.546
T2DM(欧洲)Howardella110.1170.0311.124（1.011~1.250）0.1970.385
FamilyXIIIAD3011group15-0.1920.0170.825（0.705~0.966）0.4030.977
Eubacteriumruminantiumgroup190.1040.0371.109（1.006~1.223）0.7590.354
Eubacteriumventriosumgroup150.1800.0211.197（1.027~1.396）0.7020.231
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肠道菌群与2型糖尿病关系的两样本孟德尔随机化研究
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陶丽宇 , 陆灏
现代预防医学 | 流行病与统计方法 2024,51(12): 2152-2158
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现代预防医学 | 流行病与统计方法 2024, 51(12): 2152-2158
肠道菌群与2型糖尿病关系的两样本孟德尔随机化研究
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陶丽宇, 陆灏
作者信息
  • 上海中医药大学附属曙光医院，上海 200032

    • 陶丽宇（1993—），女，博士在读，研究方向：中西医结合防治糖尿病及其并发症

通讯作者:

陆灏，E-mail:
Relationship between intestinal flora and type 2 diabetes: a two-sample Mendelian randomization study
Li-yu TAO, Hao LU
Affiliations
  • Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200032, China
出版时间: 2024-06-25 doi: 10.20043/j.cnki.MPM.202312254
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摘要
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目的

利用两样本孟德尔随机化法探讨肠道菌群与2型糖尿病之间的因果关联。

方法

在公开的全基因组关联研究数据库中获取暴露因素肠道菌群及结局变量2型糖尿病的单核苷酸多态性（SNP）数据；采用MR-Egger、加权中位数法、逆方差加权法(IVW)、简单模型、加权模型5种回归模型进行MR分析，采用MR-Egger法和IVW法进行异质性分析，MR-Egger截距测试数据的多效性，留一法进行敏感性分析，评估结果的稳健性。

结果

在东亚人群中共有7种肠道菌群与2型糖尿病相关，其中危险菌有:Eubacteriumnodatumgroup, RuminococcaceaeUCG010,LachnospiraceaeNK4A136group,Victivall,保护菌有:Enterorhabdus,Erysipelatoclostridium, Romboutsia; 在欧洲人群中共有4种肠道菌群与2型糖尿病相关，危险菌有:Howardella,Eubacteriumruminantiumgroup,Eubacteriumventriosumgroup，保护菌有:FamilyXIIIAD3011group。

结论

特定肠道菌群对2型糖尿病风险具有一定因果关联。

肠道菌群  /  2型糖尿病  /  孟德尔随机化
Objective

To explore the causal association between gut microbiota and type 2 diabetes mellitus (T2DM) using two-sample Mendelian randomization.

Methods

The data of single nucleotide polymorphisms (SNP) of gut microbiota as an exposure factor and type 2 diabetes mellitus as an outcome variable were obtained from the public genome-wide association study database. MR-Egger, weighted median method, inverse variance weighted method (IVW), simple model, and weighted model were used for MR Analysis. The MR-Egger method and IVW method were used for heterogeneity analysis. MR-Egger intercept was used to test the pleiotropy of the data, and the leave-one-out method was used for sensitivity analysis to evaluate the robustness of the results.

Results

A total of 7 gut microbiota were found to be associated with type 2 diabetes in East Asians, and the risk bacteria were Eubacteriumnodatumgroup, Ruminococcaceae UCG010, Lachnospiraceae NK4A136 group, Victivall, and protect bacteria were Enterorhabdus, Erysipelatoclostridium, Romboutsia. There were a total of four kinds of intestinal flora in the European population associated with type 2 diabetes, dangerous bacteria were Howardella, Eubacteriumruminantiumgroup, Eubacteriumventriosumgroup, and protect bacteria were FamilyXIIIAD3011group.

Conclusion

Specific gut microbiota may have causal effects on the risk of type 2 diabetes.

Gut microbiota  /  Type 2 diabetes mellitus  /  Mendelian randomization
陶丽宇, 陆灏. 肠道菌群与2型糖尿病关系的两样本孟德尔随机化研究. 现代预防医学, 2024 , 51 (12) : 2152 -2158 . DOI: 10.20043/j.cnki.MPM.202312254
Li-yu TAO, Hao LU. Relationship between intestinal flora and type 2 diabetes: a two-sample Mendelian randomization study[J]. Modern Preventive Medicine, 2024 , 51 (12) : 2152 -2158 . DOI: 10.20043/j.cnki.MPM.202312254
正文
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2型糖尿病（Type 2 Diabetes Mellitus,T2DM）是一种常见的慢性代谢性疾病，多发于中老年人。根据国际糖尿病联合会的数据，截至2021年全球T2DM患者的数量超过4.19亿人，预计到2045年全球以T2DM为主的20~79岁人群糖尿病患病率将上升至12.2%[1]。我国的T2DM患病率较高，可能与生活方式和人口老龄化等因素有关[2]。如果不得到有效管理和控制，T2DM可能会引发包括心血管疾病、肾脏疾病、神经系统并发症、眼部疾病和足部问题等多种慢性并发症，严重影响患者的生活质量[3]。
随着16S核糖体核糖核酸（16S ribosomal Ribonucleic Acid, 16SrRNA）基因测序和宏基因组测序及代谢组学的发展，对肠道菌群的组成、功能和代谢潜能研究逐渐深入，近年来研究表明肠道菌群在T2DM的发病和代谢调节中可能起到一定作用。Xiao等[4]通过16SrRNA检测78例健康人和55例T2DM患者的粪便标本，发现T2DM组出现肠道菌群失衡，其中Bifidobacterium、Actinobacteria、Lactobacillales等为T2DM相关的标记菌。Zhang等[5]发现糖尿病前期组、T2DM组与非糖尿病组患者肠道菌群有显著差异，尤其是在属水平上，提示早期干预糖尿病前期患者的肠道菌群可能对阻止发展为T2DM有一定的意义，并发现T2DM组的Prevotella和Alloprevotella的相对丰度显著升高而Bacteroides的相对丰度明显降低。此外越来越多的临床及动物实验研究表明二甲双胍[6]、电针[7]、中药单体[8]、中药复方[9]等可以通过调节肠道菌群的结构和代谢活动，降低全身炎症水平，从而对血糖的控制产生作用，但肠道菌群具体的菌种、功能和代谢产物在T2DM中的作用、在不同人群中的一致性、以及肠道菌群与其他因素的相互作用等都尚未确定。
孟德尔随机化（Mendelian randomization，MR）是一种基于自然界现象的随机化设计，用于评估因果关系[10]。它的基本原理是基于遗传变异与暴露因素之间的随机分配。遗传变异通常在受精时就确定下来，并且独立于环境和行为因素。因此，通过利用遗传变异在人群中的分布，可以获得类似于实验设计的比较组，以评估暴露因素对结果的因果效应。通过利用遗传变异的随机性，孟德尔随机化可以提供更可靠的因果推断，并帮助揭示潜在的治疗目标或干预措施。孟德尔随机化在实验设计中具有降低偏倚、增强内部有效性、增强可比性、控制混杂变量和科学可解释性等优点[11]。
为克服临床观察性研究中的混杂因素和反向因果关系的干扰，此次研究采用两样本孟德尔随机化方法来评估肠道菌群与T2DM之间的因果关系，通过基因层面的分析揭示T2DM的发生发展机制，以期为开发更具针对性的微生物治疗方法，为T2DM的预防和管理提供新的方法和策略提供依据。
1　资料和方法
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1.1　设计根据孟德尔随机化研究的报告规范（Strengthening the reporting ofobservational studies in epidemiology using Mendelianrandomization，STROBE-MR）进行研究设计[12]
采用两样本MR方法，并满足以下三个假设。假设（1）：强相关假设，即选定的工具变量单核苷酸多态性（Single nucleotide polymorphism，SNP）与暴露因素肠道菌群显著关联；假设（2）：独立性假设，即工具变量SNP在人群中是随机分布的，与其他环境和行为因素等混杂因素无关；假设（3）：排他性限制，即工具变量SNP与结局变量T2DM无直接关联，只能通过暴露因素肠道菌群进行因果联系。MR研究设计和假设概述，见图1。
1.2　资料
1.2.1　暴露数据
从MiBioGen联盟（https://mibiogen.gcc.rug.nl/）对来自18 340个个体(24个队列)的16S粪便微生物组进行的荟萃分析中，获取了肠道菌群的全基因组关联研究（Genome-wide association studies,GWAS）数据作为暴露因素，研究对象包括中东人、东亚人、拉美裔美国人、非洲裔美国人和混血儿，超过72%来自欧洲。该数据集一共包含211种肠道菌群，分别从界、门、纲、目、科、属去定义一种肠道菌群，其包含了9个门、16个纲、20个目、35个科和131个属[13]。
1.2.2　结局数据
T2DM的GWAS数据从IEU OpenGWAS project（https://gwas.mrcieu.ac.uk/）网站获得，以“Type 2 Diabetes”为检索词，根据样本量、年限、种族等选择了Spracklen[14]和Bonàs-Guarch[15]等发表的两个T2DM遗传数据集（ebi-a-GCST010118和ebi-a-GCST005413）作为结局变量。“ebi-a-GCST010118”为Spracklen CN等于2020年发表的全基因组T2DM遗传数据集中包括77 418名东亚受试者(77 418例病例和356 122例对照)。“ebi-a-GCST005413”为Bonas-Guarch S等于2018年发表的包括70 127名欧洲受试者(12 931例病例和57 196例对照)的数据集。以上所有数据均来自公开发表的GWAS数据，每项研究都通过当地伦理委员会的批准，所有受试者均签署了知情同意书。
1.3　方法
1.3.1　工具变量
首先为了满足第一个假设，对肠道菌群的SNP进行筛选，保留属水平的肠道菌群，使用Pearson相关系数、线性回归模型等进行计算SNP与肠道菌群的相关性，将显著性水平设定为P<1×10-5，筛选出强相关的SNP；然后以连锁不平衡区域距离kb=10 000、连锁不平衡系数r2=0.001为阈值，去除连锁不平衡的SNP[16]；最后根据SNP获取效应等位基因频率（Effect allele frequency，EAF），转换为最小等位基因频率（Minor allele frequency，MAF），再根据公示：R2=2×（1-MAF）×MAF×β/SD计算R2值，其中MAF是指具有最小等位基因频率的基因型在样本中的频率，β是指该SNP对表型的效应大小或影响程度，使用回归模型进行估计，SD是指表型数据的标准差。R2反映了SNP与表型之间的共变性程度，取值范围为0到1，R2越大表示该SNP对表型的解释能力越强。依据F统计量的计算公式：F=[（n-K-1)]/K×[R2/(1-R22)]计算单个SNP的F统计量，用于进行基因组关联研究中SNP与表型之间的统计显著性检验，其中n表示样本大小，K表示自变量的数量（通常为SNP的数量），最后以F检验值>10为筛选条件去除弱工具变量。提取结局变量的SNP，将暴露因素SNP与结局变量SNP合并，使效应位点保持一致，并删除存在回文序列SNP，使用MR多效残差和离群值(MR-Pleiotropy residual sum and outlier，MR-PRESSO)用于测试和校准水平多效性的异常值，得到用于MR的工具变量。
1.3.2　MR分析
采用两样本MR方法，使用MR-Egger回归法、加权中位数(Weighted median, WME)法、逆方差加权（Inverse variance weighted, IVW）法、简单模型(Simple mode, SM)法和加权模型(Weighted mode,WM)法来验证肠道菌群遗传变异与T2DM之间的因果关联。MR-Egger回归是通过使用遗传变异作为工具变量来估计因果效应，并考虑到可能存在的倾向性和反向因果关系。WME是将每个研究的效应估计值进行排序，并根据研究的权重计算加权中位数来得到合并估计值。WME具有较好的鲁棒性，对于某些情况下的异质性效果较好。IVW是一种常用的合并估计方法，它将每个研究的效应估计值按照其方差的倒数进行加权，然后将加权后的效应估计进行平均。SM是基于每个研究中的效应方向来决定最终的合并效应方向。如果大多数研究都得到相同的效应方向，则简单模型法将采用该方向作为合并结果，否则将不合并结果。WM是根据每个研究的权重来合并效应方向，根据研究的权重，加权模型将选择具有较高权重的效应方向作为最终的合并结果。以上5种方法中IVW法被用作MR的主要方法，其余用于改进IVW法的估计结果，测试MR结果的一致性，或检测和纠正水平异质性。
1.4　统计学分析
使用R语言4.3.1软件进行数据统计分析和作图，文中用到的R包主要有：“VaviantAnnotation”、“TwosampleMR”、“gwasglue”、“ieugwasr”。来自不同的分析平台、实验人群等工具变量可能存在异质性，从而影响MR的结果。在IVW和MR-Egger中采用Cochran Q检验评估纳入的SNP之间的异质性，P<0.05说明研究中存在异质性。如果工具变量通过暴露因素以外的其他因素影响结局发生时，说明工具变量有多效性。多效性会导致独立性和排他性假设不成立。MR-Egger回归截距测试评估多效性，P<0.05认为存在水平多效性。留一法(Leave-one-out)进行敏感性分析，评估单个SNP对合并的IVW估计值的影响，如果通过剔除某个SNP后，其他SNP所得到的因果关系估计结果与总结果有显著差异，这表明对于该SNP对因果关系估计结果非常敏感。MR结果以β值、P值、相对危险度(Odds ratio，OR)和95%可信区间（Confidence interval,CI）表示，因果关系的检验水准α=0.05，β值>0，表述细菌与疾病呈正相关，β值<0，表述细菌与疾病呈负相关，OR值>1，表述细菌与疾病呈正相关，OR值<1，表述细菌与疾病呈负相关。
2　结果
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2.1　工具变量
肠道菌群与T2DM的工具变量的详细数据信息见表1。根据P<1×10-5筛选出与属水平的肠道菌群强相关的工具变量有7 089个，以kb=10 000、r2=0.001为阈值去除连锁不平衡后，剩余1 531个SNP，根据SNP计算效应位点的频率，并得出F检验值的范围为14.58~88.42，表明不存在弱工具变量偏倚。分别提取东亚人群和欧洲人群T2DM的工具变量，其中东亚人群T2DM的SNP共有1 273个，欧洲人群T2DM的SNP共有1 504个，通过与肠道菌群SNP进行合并并保持效应位点一致后，并删除存在回文序列SNP，最终纳入1 219个SNP作为工具变量来评估肠道菌群和东亚人群T2DM之间的关联，1 466个SNP作为工具变量来评估肠道菌群和欧洲人群T2DM之间的关联。
2.2　肠道菌群与T2DM的因果关系
根据IVW法进行MR分析发现在131个属水平的肠道菌群中，与东亚人群T2DM有关的肠道菌群有7种，其中呈正相关的是Eubacteriumnodatum group、Ruminococcaceae UCG010、LachnospiraceaeNK4A136group、Victivall(β值均>0，OR值均>1且P<0.05），表示其为东亚人群T2DM的危险菌；呈负相关的有Enterorhabdus、Erysipelatoclostridium、Romboutsia(β值均<0，OR值均<1且P<0.05），表示其为东亚人群T2DM的保护菌。对与东亚人群T2DM存在相关性的肠道菌群进行逐一MR，并对五种MR方法的组合效应和单个SNP效应进行可视化，以及异质性和多效性分析，MR Egger回归截距未发现水平多效性（P>0.05），Cochran Q检验未发现异质性（P>0.05），进一步表明因果效应不受多效性的影响，主要结果见表2和散点图2A。
根据IVW法进行MR分析发现在131个属水平的肠道菌群中，在欧洲人群中共有4种肠道菌群与T2DM相关，呈正相关的危险菌有：Howardella、Eubacteriumruminantiumgroup、Eubacteriumventriosumgroup(β值均>0，OR值均>1且P<0.05），呈负相关的保护菌有：FamilyXIIIAD3011group(β值均<0，OR值均<1且P<0.05）。对与欧洲人群T2DM存在相关性的肠道菌群进行逐一MR并进行可视化，以及异质性和多效性分析，MR Egger回归截距未观察到水平多效性（P>0.05），进一步表明因果效应不受多效性的影响，Cochran Q检验也未观察到存在异质性（P>0.05），主要结果见表2和散点图2B。
2.3　敏感性分析
通过留一法敏感性分析，验证每个SNP对总体因果估计的影响。在去除每个SNP后，对剩余的SNP再次进行了系统的MR分析，结果保持一致，表明所有SNP的计算结果之间存在显著的因果关系，见图3。此外，为了进一步检验结果的稳健性，绘制了T2DM相关的肠道菌的漏斗图，结果显示均基本对称，表明其因果效应不受潜在因素影响而发生偏倚，见图4。
3　讨论
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文章利用双样本MR分析探究了肠道菌群与T2DM之间的因果关联，结果观察到在东亚人群中共有7种肠道菌群与T2DM相关，其中与Eubacteriumnodatumgroup、RuminococcaceaeUCG010、LachnospiraceaeNK4A136group、Victivall呈正相关；与Enterorhabdus、Erysipelatoclostridium、Romboutsia 3种菌呈负相关；在欧洲人群中共有4种肠道菌群与T2DM相关，其中Howardella、Eubacteriumruminantiumgroup、Eubacteriumventriosumgroup呈正相关，FamilyXIIIAD3011group呈负相关；敏感性分析中通过留一法检测，未发现任何SNP对因果关联结果有显著影响，证实了结果的稳健性，提示特定肠道菌群对T2DM风险具有一定因果关联。
T2DM的机制尚未完全阐明，近年来研究表明，肠道菌群可能参与了几种潜在机制。首先，T2DM患者的肠道菌群结构失调导致肠道菌群的功能异常，进而影响能量代谢、炎症反应和胰岛素敏感性等因素，从而促进T2DM的发生和发展。此外，肠道菌群的代谢物短链脂肪酸和胆汁酸可激活肠内分泌细胞表达的几种关键受体，从而增加关键肠道肽的分泌，包括胰高血糖素样肽1（Glucagon-like peptide 1, GLP-1）、GLP-2和多肽YY（Peptide YY, PYY）。GLP-1、GLP-2和PYY可以降低葡萄糖浓度、肠道通透性、细胞因子和淀粉酶释放，从而改善糖尿病期间的代谢紊乱和炎症[17]。通过这些潜在机制，肠道微生物群可能调节肠道内和肌肉、脂肪组织和肝脏中的许多代谢通路参与T2DM的发生发展。人体内约有500~1 000种肠道菌群，不同研究中对于不同菌群与T2DM的关联性的报道可能不尽相同。
Eubacteriumnodatumgroup为嗜酸菌属，参与多种代谢过程，包括碳水化合物的发酵和产生有益的代谢产物，如短链脂肪酸。LachnospiraceaeNK4A136group为毛螺菌科，参与葡萄糖、纤维素和其他多聚糖的发酵等代谢过程，进而产生短链脂肪酸等有益的代谢产物。Victivall为肠杆菌科，可以利用营养物质如葡萄糖、纤维素和其他多聚糖进行发酵，并产生有益的代谢产物，例如丙酸、丁酸和乙酸等短链脂肪酸，此次研究发现上述3种菌群均与东亚人群T2DM呈正相关。RuminococcaceaeUCG010属于拟杆菌门，参与肠道内多种代谢过程，包括葡萄糖、麦芽糖和木糖的发酵，以及有机酸、气体和其他代谢产物的产生。Chen等[18]发现RuminococcaceaeUCG010的高丰度与T2DM的风险呈负相关，表明其对T2DM的保护作用。然而，Esquivel-Hernández等[19]在一个墨西哥队列中观察到，RuminococcaceaeUCG010与T2DM呈正相关，这也与此次研究中东亚人群的结果相同。Enterorhabdus对于纤维素的分解、葡萄糖代谢、脂肪酸生成等过程起到一定的作用，Huang等[20]发现在T2DM合并认知障碍患者中丰度增加，为T2DM中的危险菌，与此次研究结果一致。Erysipelatoclostridium为梭菌属，引起的感染可以导致多种疾病，包括肠炎、食物中毒和伤口感染等，还产生多种外毒素，其中包括产气荚膜毒素是其主要致病因子之一，然而此次研究中其与T2DM呈负相关。Romboutsia属于长梭菌科，在维持肠道健康和平衡中起着重要的作用，它们可能参与食物消化、营养物质代谢和免疫调节等方面的过程。以上3种肠道菌在此次研究东亚人群中与T2DM呈负相关。Eubacteriumruminantiumgroup是一组革兰氏阳性菌属，可以代谢复杂的碳水化合物，包括木质素和纤维素，将这些化合物转化为营养物质。Howardella为霍瓦德氏菌属，也被报道与糖尿病相关[21]，Eubacteriumventriosumgroup为优拟杆菌属，参与纤维素的分解、产生短链脂肪酸等，以上菌群与欧洲人群T2DM呈正相关，此外，此次研究还发现FamilyXIIIAD3011group与欧洲人群T2DM之间呈负相关，目前对这些属的研究仍相对匮乏，未来需要对其在T2DM中的作用进行更多的研究。以上结果中Eubacteriumnodatumgroup、LachnospiraceaeNK4A136group、RuminococcaceaeUCG010等菌群在T2DM中的作用存在争议，不同的研究得出的结果也不尽相同，此次研究为这些有争议的肠道菌群的作用提供参考，同时也说明单个菌群的变化不能解释T2DM的发病率，特定的菌属可能在特定的生物环境中有不同类型的影响。
虽然此次MR研究为既往观察性研究提供了因果关联依据，也为从肠道菌群角度治疗T2DM提供了有力证据，但仍有一些局限性。首先仅探究了肠道菌群与T2DM之间的因果关系，而未研究其他潜在因素的影响。T2DM发病机制复杂，可能涉及多种病理过程如肠道菌群代谢产物的共同作用等，同时，受到年龄、体重、生活方式、身体质量指数等多种因素的影响，进一步研究可以综合考虑这些因素，并分析它们与肠道菌群之间的相互作用。其次两个GWAS的参与者为东亚人群和欧洲人群，因此我们的结果的适用性需要进一步研究。此外，尽管作者采用了MR分析方法来增强因果推断的可靠性，但此次研究是基于数据库中的遗传变异关联性数据，因此，此次研究得出的因果关系并非绝对结论，需要结合队列研究、临床试验和功能研究的证据，明确T2DM与肠道菌群之间的关联，从而有助于探索T2DM的发病机制。
基金
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  • 国家自然科学基金资助项目(82074381; 81874434)
  • 上海市临床重点专科建设项目-中医内分泌(shslczdzk05401)
  • 上海市卫生健康委员会中医药科研项目(2024BJ019)
文献
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2024年第51卷第12期
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doi: 10.20043/j.cnki.MPM.202312254
  • 接收时间：2023-12-15
  • 首发时间：2026-03-17
  • 出版时间：2024-06-25
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  • 收稿日期：2023-12-15
基金
国家自然科学基金资助项目(82074381; 81874434)
上海市临床重点专科建设项目-中医内分泌(shslczdzk05401)
上海市卫生健康委员会中医药科研项目(2024BJ019)
作者信息
    上海中医药大学附属曙光医院，上海 200032

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陆灏，E-mail:
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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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