Evidence map›Paper›PMID 37914897›Full record

ArticleScientific reports2023

Causal effect of gut microbiota on DNA methylation phenotypic age acceleration: a two-sample Mendelian randomization study.

Yedong Huang, Xiaoyun Chen, Jingwen Ye, Huan Yi, Xiangqin Zheng

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yedong HuangCollege of Clinical Medicine for Obstetrics and Gynecology & Pediatrics, Fujian Medical University, Fuzhou, China.
Xiaoyun ChenDepartment of Respiratory Medicine, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Jingwen YeShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Huan YiCollege of Clinical Medicine for Obstetrics and Gynecology & Pediatrics, Fujian Medical University, Fuzhou, China. yihuangsrk@126.com.
Xiangqin ZhengCollege of Clinical Medicine for Obstetrics and Gynecology & Pediatrics, Fujian Medical University, Fuzhou, China. zhengxq1118@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The causal relationship between gut microbiota and DNA methylation phenotypic age acceleration remains unclear. This study aims to examine the causal effect of gut microbiota on the acceleration of DNA methylation phenotypic age using Mendelian randomization. A total of 212 gut microbiota were included in this study, and their 16S rRNA sequencing data were obtained from the Genome-wide Association Study (GWAS) database. The GWAS data corresponding to DNA methylation phenotypic age acceleration were selected as the outcome variable. Two-sample Mendelian randomization (TSMR) was conducted using R software. During the analysis process, careful consideration was given to address potential biases arising from linkage disequilibrium and weak instrumental variables. The results from inverse-variance weighting (IVW) analysis revealed significant associations (P < 0.05) between single nucleotide polymorphisms (SNPs) corresponding to 16 gut microbiota species and DNA methylation phenotypic age acceleration. Out of the total, 12 gut microbiota species exhibited consistent and robust causal effects. Among them, 7 displayed a significant positive correlation with the outcome while 5 species showed a significant negative correlation with the outcome. This study utilized Mendelian randomization to unravel the intricate causal effects of various gut microbiota species on DNA methylation phenotypic age acceleration.

Indexed as

Gastrointestinal MicrobiomeAccelerationDNA MethylationGenome-Wide Association StudyMendelian Randomization AnalysisRNA, Ribosomal, 16SRNA, Ribosomal, 16S

Identifiers

PMID37914897
PMCPMC10620208

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.