A Study of the Causal Effect of Gut Microbiota on Genetic Prediction of Metabolic Syndrome

doi:10.12114/j.issn.1007-9572.2024.0327

Abstract

Abstract:

Background

Many observational studies have found an association between the gut microbiome and metabolic syndrome (MetS) and its components, but the causal relationship between them is not yet clear.

Objective

To explore a bidirectional causal relationship between the gut microbiota and the MetS and its components.

Methods

This study obtained gut microbiota-associated single nucleotide polymorphisms from MiBioGen, obtained summary statistics of MetS and its components in the UK Biobank, Complex Trait Genetics (CTG), and other consortiums studies, and performed bidirectional two-sample Mendelian randomization analyses to assess the relationship between causal relationships. In addition, a series of sensitivity analyses were performed to verify the robustness of the Mendelian randomization analysis results. To obtain a more rigorous causal interpretation, Bonferroni correction was used to test the strength of the causal relationship between gut microbiota and MetS.

Results

Inverse variance weighted estimation showed that Bifidobacteriaceae (OR=0.96, 95%CI=0.93-0.98, P=1.49×10^-3) had a significant negative causal relationship with MetS. There was a significant positive causal relationship between some gut microbiota and waist circumference, such as class.Melainabacteria (OR=1.02, 95%CI=1.01-1.03, P=1.90×10^-3), order.Gastranaerophilales (OR=1.02, 95%CI=1.01-1.03, P=1.61×10^-3), order.NB1n (OR=1.02, 95%CI=1.01-1.03, P=2.00×10^-3), and genus..Eubacteriumhalliigroup (OR=1.03, 95%CI=1.01-1.04, P=6.97×10^-4), among others. However, inverse Mendelian randomization analysis did not support a causal relationship. Sensitivity analyses showed there was no heterogeneity or horizontal pleiotropy.

Conclusion

This bidrectional Mendelian randomization study provides evidence of a clear causal relationship of gut microbiota on MetS and components, but does not support reverse causality. This finding provides new ideas for the management of MetS. Further randomized controlled trials are still needed in the future to elucidate the relationship between the effects of microbial agents such as probiotics on MetS.

Key words: Gut microbiota, Metabolic syndrome, Mendelian randomization, Causal relationship

摘要：

背景

许多观察性研究发现肠道微生物群与代谢综合征（MetS）及其组成部分存在相关性，但两者之间的因果关系尚不明确。

目的

本研究旨在探讨肠道微生物群与MetS及其组成部分之间的双向因果关系。

方法

从MiBioGen获得肠道微生物群相关的单核苷酸多态性，在英国生物样本库、Complex Trait Genetics（CTG）和其他联盟研究中获得了MetS及其组成部分的汇总统计数据，采用双向两样本孟德尔随机化分析，评估两者的因果关系。除此之外，通过一系列敏感性分析验证孟德尔随机化分析结果的稳健性。为了获得更严格的因果关系解释，使用Bonferroni校正检验肠道菌群和MetS之间因果关系的强度。

结果

逆方差加权估计结果表明，双歧杆菌（Bifidobacteriaceae）（OR=0.96，95%CI=0.93~0.98，P=1.49×10^-3）与MetS有明显的负向因果关系。部分肠道菌群与腰围之间存在明显的正向因果关系，如酶莱纳菌纲（class.Melainabacteria）（OR=1.02，95%CI=1.01~1.03，P=1.90×10^-3）、胃厌氧杆菌目（order.Gastranaerophilales）（OR=1.02，95%CI=1.01~1.03，P=1.61×10^-3）、NB1n目（order.NB1n）（OR=1.02，95%CI=1.01~1.03，P=2.00×10^-3）和霍氏真杆菌群（genus..Eubacteriumhalliigroup）（OR=1.03，95%CI=1.01~1.04，P=6.97×10^-4）等，但是反向孟德尔随机化分析不支持两者之间的因果关系。敏感性分析表明不存在异质性或水平多效性。

结论

这项双向孟德尔随机化研究提供了肠道微生物群与MetS及其组成部分有明显的因果关系证据，但是不支持反向因果关系。这个发现为MetS的防治提供了新的思路。未来仍需要通过进一步的随机对照试验来阐明益生菌等微生物制剂与MetS的关系。

关键词: 肠道微生物群, 代谢综合征, 孟德尔随机化, 因果关系

CLC Number:

R 378.2　R 589

LUO Xiu,MA Zhaoli,HUANG Mengyu, et al. A Study of the Causal Effect of Gut Microbiota on Genetic Prediction of Metabolic Syndrome[J]. Chinese General Practice, 2026, 29(05): 612-622. DOI: 10.12114/j.issn.1007-9572.2024.0327.
罗秀,麻钊丽,黄梦宇等. 肠道微生物群对代谢综合征的遗传预测因果效应研究[J]. 中国全科医学, 2026, 29(05): 612-622. DOI: 10.12114/j.issn.1007-9572.2024.0327.

Figures/Tables 5

References 64

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暴露因素	结局指标	方法	SNP（个）	OR（95%CI）	P值	Q_pval	Egger_intercept	p-Egger_intercept
双歧杆菌目	MetS	MR Egger	8	0.89（0.79~1.01）	0.11
		IVW	8	0.96（0.93~0.98）	1.49×10^-3	0.92	4.70×10^-3	0.28
		WME	8	0.96（0.92~0.99）	0.01
		SM	8	0.96（0.91~1.01）	0.14
		WM	8	0.96（0.91~1.01）	0.13
双歧杆菌科	MetS	MR Egger	8	0.89（0.79~1.01）	0.11
		IVW	8	0.96（0.93~0.98）	1.49×10^-3	0.92	4.70×10^-3	0.28
		WME	8	0.96（0.92~0.99）	0.01
		SM	8	0.96（0.91~1.01）	0.14
		WM	8	0.96（0.91~1.01）	0.13
梅莱纳菌纲	WC	MR Egger	10	1.02（0.98~1.05）	0.38
		IVW	10	1.02（1.01~1.03）	1.90×10^-3	0.81	3.81×10^-4	0.85
		WME	10	1.02（1.00~1.04）	0.02
		SM	10	1.01（0.99~1.04）	0.36
		WM	10	1.01（0.99~1.04）	0.38
胃厌氧杆菌目	WC	MR Egger	9	1.01（0.98~1.05）	0.53
		IVW	9	1.02（1.01~1.03）	1.61×10^-3	0.88	1.08×10^-3	0.63
		WME	9	1.02（1.00~1.04）	0.02
		SM	9	1.02（0.99~1.04）	0.18
		WM	9	1.01（0.99~1.04）	0.28
NB1n目	WC	MR Egger	16	1.01（0.96~1.07）	0.62
		IVW	16	1.02（1.01~1.03）	2.00×10^-3	0.42	-6.02×10^-4	0.87
		WME	16	1.02（1.01~1.03）	0.01
		SM	16	1.02（1.00~1.04）	0.06
		WM	16	1.02（1.00~1.04）	0.08
霍氏真杆菌群	WC	MR Egger	15	1.03（0.99~1.06）	0.13
		IVW	15	1.03（1.01~1.04）	6.97×10^-4	0.43	-7.35×10^-5	0.96
		WME	15	1.03（1.01~1.05）	0.01
		SM	15	1.04（1.00~1.08）	0.07
		WM	15	1.04（1.01~1.07）	0.03

暴露因素	结局指标	方法	SNP（个）	OR（95%CI）	P值	Q_pval	Egger_intercept	p-Egger_intercept
双歧杆菌目	MetS	MR Egger	8	0.89（0.79~1.01）	0.11
		IVW	8	0.96（0.93~0.98）	1.49×10^-3	0.92	4.70×10^-3	0.28
		WME	8	0.96（0.92~0.99）	0.01
		SM	8	0.96（0.91~1.01）	0.14
		WM	8	0.96（0.91~1.01）	0.13
双歧杆菌科	MetS	MR Egger	8	0.89（0.79~1.01）	0.11
		IVW	8	0.96（0.93~0.98）	1.49×10^-3	0.92	4.70×10^-3	0.28
		WME	8	0.96（0.92~0.99）	0.01
		SM	8	0.96（0.91~1.01）	0.14
		WM	8	0.96（0.91~1.01）	0.13
梅莱纳菌纲	WC	MR Egger	10	1.02（0.98~1.05）	0.38
		IVW	10	1.02（1.01~1.03）	1.90×10^-3	0.81	3.81×10^-4	0.85
		WME	10	1.02（1.00~1.04）	0.02
		SM	10	1.01（0.99~1.04）	0.36
		WM	10	1.01（0.99~1.04）	0.38
胃厌氧杆菌目	WC	MR Egger	9	1.01（0.98~1.05）	0.53
		IVW	9	1.02（1.01~1.03）	1.61×10^-3	0.88	1.08×10^-3	0.63
		WME	9	1.02（1.00~1.04）	0.02
		SM	9	1.02（0.99~1.04）	0.18
		WM	9	1.01（0.99~1.04）	0.28
NB1n目	WC	MR Egger	16	1.01（0.96~1.07）	0.62
		IVW	16	1.02（1.01~1.03）	2.00×10^-3	0.42	-6.02×10^-4	0.87
		WME	16	1.02（1.01~1.03）	0.01
		SM	16	1.02（1.00~1.04）	0.06
		WM	16	1.02（1.00~1.04）	0.08
霍氏真杆菌群	WC	MR Egger	15	1.03（0.99~1.06）	0.13
		IVW	15	1.03（1.01~1.04）	6.97×10^-4	0.43	-7.35×10^-5	0.96
		WME	15	1.03（1.01~1.05）	0.01
		SM	15	1.04（1.00~1.08）	0.07
		WM	15	1.04（1.01~1.07）	0.03

暴露因素	结局指标	方法	SNP （个）	OR（95%CI）	P值
MetS	双歧杆菌目	MR Egger	164	1.18（0.81~1.73）	0.39
		IVW	164	1.00（0.87~1.14）	0.97
		WME	164	0.97（0.81~1.18）	0.78
		SM	164	0.84（0.51~1.37）	0.48
		WM	164	0.90（0.65~1.25）	0.53
MetS	双歧杆菌科	MR Egger	164	1.18（0.81~1.73）	0.39
		IVW	164	1.00（0.87~1.14）	0.97
		WME	164	0.97（0.81`1.18）	0.78
		SM	164	0.84（0.51~1.37）	0.48
		WM	164	0.90（0.65~1.25）	0.53
WC	梅莱纳菌纲	MR Egger	303	1.03（0.66~1.59）	0.90
		IVW	303	0.94（0.81~1.10）	0.46
		WME	303	0.78（0.60~1.02）	0.07
		SM	303	0.58（0.29~1.19）	0.14
		WM	303	0.73（0.45~1.19）	0.21
WC	胃厌氧杆菌目	MR Egger	303	1.03（0.66~1.59）	0.91
		IVW	303	0.95（0.81~1.10）	0.47
		WME	303	0.82（0.63~1.06）	0.13
		SM	303	0.63（0.29~1.38）	0.25
		WM	303	0.76（0.48~1.21）	0.25
WC	NB1n目	MR Egger	303	0.68（0.42~1.08）	0.10
		IVW	303	0.90（0.77~1.06）	0.23
		WME	303	0.90（0.69~1.17）	0.41
		SM	303	0.81（0.35~1.92）	0.64
		WM	303	0.69（0.42~1.14）	0.15
WC	霍氏真杆菌群	MR Egger	303	0.99（0.76~1.28）	0.94
		IVW	303	1.02（0.93~1.11）	0.73
		WME	303	1.02（0.88~1.18）	0.80
		SM	303	1.28（0.82~1.98）	0.28
		WM	303	0.83（0.61~1.11）	0.20

暴露因素	结局指标	方法	SNP （个）	OR（95%CI）	P值
MetS	双歧杆菌目	MR Egger	164	1.18（0.81~1.73）	0.39
		IVW	164	1.00（0.87~1.14）	0.97
		WME	164	0.97（0.81~1.18）	0.78
		SM	164	0.84（0.51~1.37）	0.48
		WM	164	0.90（0.65~1.25）	0.53
MetS	双歧杆菌科	MR Egger	164	1.18（0.81~1.73）	0.39
		IVW	164	1.00（0.87~1.14）	0.97
		WME	164	0.97（0.81`1.18）	0.78
		SM	164	0.84（0.51~1.37）	0.48
		WM	164	0.90（0.65~1.25）	0.53
WC	梅莱纳菌纲	MR Egger	303	1.03（0.66~1.59）	0.90
		IVW	303	0.94（0.81~1.10）	0.46
		WME	303	0.78（0.60~1.02）	0.07
		SM	303	0.58（0.29~1.19）	0.14
		WM	303	0.73（0.45~1.19）	0.21
WC	胃厌氧杆菌目	MR Egger	303	1.03（0.66~1.59）	0.91
		IVW	303	0.95（0.81~1.10）	0.47
		WME	303	0.82（0.63~1.06）	0.13
		SM	303	0.63（0.29~1.38）	0.25
		WM	303	0.76（0.48~1.21）	0.25
WC	NB1n目	MR Egger	303	0.68（0.42~1.08）	0.10
		IVW	303	0.90（0.77~1.06）	0.23
		WME	303	0.90（0.69~1.17）	0.41
		SM	303	0.81（0.35~1.92）	0.64
		WM	303	0.69（0.42~1.14）	0.15
WC	霍氏真杆菌群	MR Egger	303	0.99（0.76~1.28）	0.94
		IVW	303	1.02（0.93~1.11）	0.73
		WME	303	1.02（0.88~1.18）	0.80
		SM	303	1.28（0.82~1.98）	0.28
		WM	303	0.83（0.61~1.11）	0.20