Metagenome-genome-wide association studies reveal human genetic impact on the oral microbiome

Liu, Xiaoyu; Tong, Xin; Zhu, Jun; Tian, Lei; Jie, Zhigang; Zou, Yunzeng; X, Lin; Liang, Huiqing; Li, Wei; Ju, Yi‐Hsu; Qin, Yue; Zou, Li; Lu, Hanqing; Xu, Xiaowei; Yang, Huanming; Wang, J; Zong, Yang; W, Liu; Hou, Yayi; Zhu, Shanfeng; X, Jin; Jia, Haiqiang; Zhang, T

doi:10.1101/2021.05.06.443017

Cited by 2 publications

(1 citation statement)

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“…in China. The protocols for blood and stool collection, as well as the whole genome and metagenomic sequencing, were similar to our previous studies 5,[42][43][44] . For blood samples, buffy coat was isolated and DNA was extracted using HiPure Blood DNA Mini Kit (Magen, Cat.…”

Section: Methodsmentioning

confidence: 95%

Mendelian randomization analyses support causal relationships between blood metabolites and the gut microbiome

et al. 2022

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The gut microbiome has been implicated in a variety of physiological states, but controversy over causality remains unresolved. Here, we performed bidirectional Mendelian randomization (MR) analyses on 3,432 Chinese individuals with whole genome, whole metagenome, anthropometric, and blood metabolic trait data. We identified 58 causal relationships between the gut microbiome and blood metabolites, and replicated 43 of them. Increased relative abundances of fecal Oscillibacter and Alistipes were causally linked to decreased triglyceride concentration. Conversely, blood metabolites such as glutamic acid appeared to decrease fecal Oxalobacter, and members of Proteobacteria were influenced by metabolites such as 5-methyltetrahydrofolic acid, alanine, glutamate, and selenium. Two-sample MR with data from Biobank Japan partly corroborated results with triglyceride and with uric acid, and also provided causal support for published fecal bacterial markers for cancer and cardiovascular diseases. This study illustrates the value of human genetic information to help prioritize gut microbial features for mechanistic and clinical studies.Metagenome-wide association studies (MWAS) using human stool samples, as well as animal models, especially germ-free mice, have pointed to a potential role of the gut microbiome in diseases such as cardiometabolic, autoimmune, neuropsychiatric disorders and cancer, with mechanistic investigations for diseases such as obesity, colorectal cancer and schizophrenia [1][2][3][4] . Twin-based heritability estimation and more recent metagenome-genome-wide association studies (M-GWAS) have questioned the traditional view of the gut microbiota as a purely environmental factor 5-9 , although the extent of the genetic influence remains controversial 7,10 . Yet, all these published cohorts, except for human sequences in the metagenomic data of HMP (Human Microbiome Project), utilized array data for human genetics, and most of them had 16S rRNA gene amplicon sequencing for the fecal microbiota [5][6][7][8][9] .As the gut microbiome is considered to be highly dynamic, causality has been an unresolved issue in the field. Mendelian randomization (MR) 11 offers an opportunity to distinguish between causal and non-causal effects from cross-sectional data, without animal studies or randomized controlled trials. An early study used MR to look at the gut microbiota and ischemic heart disease 12 . Recently, a study used MR to confirm that increased relative abundance of bacteria producing the fecal volatile short-chain fatty acid (SCFA) butyrate was causally linked to improved insulin response to oral glucose challenge; in contrast, another fecal SCFA, propionate, was causally related to an increased risk of T2D 13 . However, both studies used genotype data, and it was not clear to what extent the genetic factors explained the microbial feature of interest.In this study, we present a large-scale M-GWAS using whole genome and fecal microbiome, followed by bidirectional MR for the fecal microbiome and anthropometric...

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Section: Methodsmentioning

confidence: 95%

Mendelian randomization analyses support causal relationships between blood metabolites and the gut microbiome

et al. 2022

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Mendelian randomization analyses support causal relationships between blood metabolites and the gut microbiome

Liu

Tong

Zou

et al. 2020

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AbstractThe gut microbiome has been implicated in a variety of physiological states. Controversy over causality, however, has always haunted microbiome studies. Here, we utilized the bidirectional Mendelian randomization (MR) approach to address questions that are not yet mature for more costly randomized interventions. From a total of 3,432 Chinese individuals with shotgun sequencing data for whole genome and whole metagenome, as well as anthropometric and blood metabolic traits, we identified 58 causal relationships between the gut microbiome and blood metabolites, and replicated 43 out of the 58. Gut microbiome could determine features in the blood. For example, increased fecal relative abundances of Oscillibacter and Alistipes were causally linked to decreased triglyceride concentration, and fecal microbial module pectin degradation might increase serum uric acid. On the other hand, blood features may determine gut microbial features, e.g. glutamic acid appeared to decrease Oxalobacter, and a few members of Proteobacteria were unidirectionally influenced by cardiometabolically important metabolites such as 5-methyltetrahydrofolic acid, alanine, as well as selenium. This study illustrates the value of human genetic information to help prioritize gut microbial features for mechanistic and clinical studies. The results are consistent with whole-body cross-talks of the microbiome and the circulating molecules.

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Metagenome-genome-wide association studies reveal human genetic impact on the oral microbiome

Cited by 2 publications

References 56 publications

Mendelian randomization analyses support causal relationships between blood metabolites and the gut microbiome

Mendelian randomization analyses support causal relationships between blood metabolites and the gut microbiome

Mendelian randomization analyses support causal relationships between blood metabolites and the gut microbiome

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