Causal Effects of Gut Microbiota on Gout and Hyperuricemia: Insights from Genome-Wide Mendelian Randomization, RNA-Sequencing, 16S rRNA Sequencing, and Metabolomes.

IF 3.8 3区生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY

Bioscience Reports Pub Date : 2024-11-04 DOI:10.1042/BSR20240595

Xia Liu, Zhe Feng, Fenglian Zhang, Bo Wang, Zhijuan Wei, Nanqing Liao, Min Zhang, Jian Liang, Lisheng Wang

{"title":"Causal Effects of Gut Microbiota on Gout and Hyperuricemia: Insights from Genome-Wide Mendelian Randomization, RNA-Sequencing, 16S rRNA Sequencing, and Metabolomes.","authors":"Xia Liu, Zhe Feng, Fenglian Zhang, Bo Wang, Zhijuan Wei, Nanqing Liao, Min Zhang, Jian Liang, Lisheng Wang","doi":"10.1042/BSR20240595","DOIUrl":null,"url":null,"abstract":"Background: This study investigated the causal relationship between gut microbiota (GM), serum metabolome, and host transcriptome in the development of gout and hyperuricemia (HUA) using genome-wide association studies (GWAS) data and HUA mouse model experiments.  Methods: Mendelian randomization (MR) analysis of GWAS summary statistics was performed using an inverse variance weighted (IVW) approach to determine predict the causal role of the gut microbiota on gout. The HUA mouse model was used to characterize changes in the gut microbiome, host metabolome, and host kidney transcriptome by integrating cecal 16S rRNA sequencing, untargeted serum metabolomics, and host mRNA sequencing.  Results: Our analysis demonstrated causal effects of seven gut microbiota taxa on gout, including genera of Ruminococcus, Odoribacter, and Bacteroides. Thirty-eight, immune cell traits were associated with gout. Dysbiosis of Dubosiella, Lactobacillus,Bacteroides, Alloprevotella, and Lachnospiraceae_NK4A136_group genera were associated with changes in the serum metabolites and kidney transcriptome of the HUA model mice. The changes in the gut microbiome of the HUA model mice correlated significantly with alterations in the levels of serum metabolites such as taurodeoxycholic acid, phenylacetylglycine, vanylglycol, methyl hexadecanoic acid, carnosol, 6-aminopenicillanic acid, sphinganine, p-hydroxyphenylacetic acid, pyridoxamine, and de-o-methylsterigmatocystin, and expression of kidney genes such as CNDP2, SELENOP, TTR, CAR3, SLC12A3, SCD1, PIGR, CD74, MFSD4B5, and NAPSA.  Conclusion: Our study demonstrated a causal relationship between GM, immune cells, and gout. HUA development involved alterations in the vitamin B6 metabolism because of gut microbiota dysbiosis that resulted in altered pyridoxamine and pyridoxal levels, dysregulated sphingolipid metabolism, and excessive inflammation..","PeriodicalId":8926,"journal":{"name":"Bioscience Reports","volume":" ","pages":""},"PeriodicalIF":3.8000,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioscience Reports","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1042/BSR20240595","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

Background: This study investigated the causal relationship between gut microbiota (GM), serum metabolome, and host transcriptome in the development of gout and hyperuricemia (HUA) using genome-wide association studies (GWAS) data and HUA mouse model experiments. Methods: Mendelian randomization (MR) analysis of GWAS summary statistics was performed using an inverse variance weighted (IVW) approach to determine predict the causal role of the gut microbiota on gout. The HUA mouse model was used to characterize changes in the gut microbiome, host metabolome, and host kidney transcriptome by integrating cecal 16S rRNA sequencing, untargeted serum metabolomics, and host mRNA sequencing.

Results: Our analysis demonstrated causal effects of seven gut microbiota taxa on gout, including genera of Ruminococcus, Odoribacter, and Bacteroides. Thirty-eight, immune cell traits were associated with gout. Dysbiosis of Dubosiella, Lactobacillus,Bacteroides, Alloprevotella, and Lachnospiraceae_NK4A136_group genera were associated with changes in the serum metabolites and kidney transcriptome of the HUA model mice. The changes in the gut microbiome of the HUA model mice correlated significantly with alterations in the levels of serum metabolites such as taurodeoxycholic acid, phenylacetylglycine, vanylglycol, methyl hexadecanoic acid, carnosol, 6-aminopenicillanic acid, sphinganine, p-hydroxyphenylacetic acid, pyridoxamine, and de-o-methylsterigmatocystin, and expression of kidney genes such as CNDP2, SELENOP, TTR, CAR3, SLC12A3, SCD1, PIGR, CD74, MFSD4B5, and NAPSA.

Conclusion: Our study demonstrated a causal relationship between GM, immune cells, and gout. HUA development involved alterations in the vitamin B6 metabolism because of gut microbiota dysbiosis that resulted in altered pyridoxamine and pyridoxal levels, dysregulated sphingolipid metabolism, and excessive inflammation.

查看原文本刊更多论文

肠道微生物群对痛风和高尿酸血症的因果效应：全基因组孟德尔随机化、RNA测序、16S rRNA测序和代谢组的启示。

研究背景本研究利用全基因组关联研究（GWAS）数据和HUA小鼠模型实验，研究了痛风和高尿酸血症（HUA）发病过程中肠道微生物群（GM）、血清代谢组和宿主转录组之间的因果关系：采用反方差加权法（IVW）对全基因组关联研究（GWAS）摘要统计进行孟德尔随机化（MR）分析，以确定预测肠道微生物群对痛风的因果作用。通过整合盲肠 16S rRNA 测序、非靶向血清代谢组学和宿主 mRNA 测序，利用 HUA 小鼠模型描述了肠道微生物组、宿主代谢组和宿主肾脏转录组的变化：我们的分析表明，七个肠道微生物群分类群对痛风有因果影响，其中包括反刍球菌属、Odoribacter 和 Bacteroides。38种免疫细胞特征与痛风有关。Dubosiella、Lactobacillus、Bacteroides、Alloprevotella和Lachnospiraceae_NK4A136_group等菌属的菌群失调与HUA模型小鼠血清代谢物和肾脏转录组的变化有关。6-氨基青霉烷酸、鞘氨醇、对羟基苯乙酸、吡哆胺和去甲基异麦角胱氨酸等肾脏代谢产物，以及 CNDP2、SELENOP、TTR、CAR3、SLC12A3、SCD1、PIGR、CD74、MFSD4B5 和 NAPSA 等肾脏基因的表达。结论：我们的研究证明了 GM、免疫细胞和痛风之间的因果关系。由于肠道微生物群失调导致吡哆胺和吡哆醛水平改变、鞘脂代谢失调和过度炎症，HUA 的发生涉及维生素 B6 代谢的改变。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Bioscience Reports 生物-细胞生物学

CiteScore

8.50

自引率

0.00%

发文量

380

审稿时长

6-12 weeks

期刊介绍： Bioscience Reports provides a home for sound scientific research in all areas of cell biology and molecular life sciences. Since 2012, Bioscience Reports has been fully Open Access and publishes all papers under the liberal CC BY licence, giving the life science community quality research to share and discuss.Content before 2012 is subscription-only, and is accessible via archive purchase. Articles are assessed on soundness, providing a home for valid findings and data. We welcome papers that span disciplines (e.g. chemistry, medicine), including papers describing: -new methodologies -tools and reagents to probe biological questions -mechanistic details -disease mechanisms -metabolic processes and their regulation -structure and function -bioenergetics