Evidence map›Paper›PMID 38868571›Full record

ReviewiMeta2022

Decoding microbial genomes to understand their functional roles in human complex diseases.

Yifeng Wang, Quanbin Dong, Shixian Hu, Huayiyang Zou, Tingting Wu, Jing Shi, Haifeng Zhang, Yanhui Sheng, Wei Sun, Xiangqing Kong and 1 more

Abstract readReview
In one paragraph

Review in iMeta, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
–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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  20. International journal of nanomedicine · 2024
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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

11 authors.

Yifeng WangDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University Nanjing Medical University Nanjing Jiangsu China.
Quanbin DongDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University Nanjing Medical University Nanjing Jiangsu China.
Shixian HuInstitute of Precision Medicine, The First Affiliated Hospital of Sun Yat-Sen University Sun Yat-Sen University Guangzhou Guangdong China.
Huayiyang ZouDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University Nanjing Medical University Nanjing Jiangsu China.
Tingting WuDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University Nanjing Medical University Nanjing Jiangsu China.
Jing ShiDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University Nanjing Medical University Nanjing Jiangsu China.
Haifeng ZhangDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University Nanjing Medical University Nanjing Jiangsu China.
Yanhui ShengDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University Nanjing Medical University Nanjing Jiangsu China.
Wei SunDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University Nanjing Medical University Nanjing Jiangsu China.
Xiangqing KongDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University Nanjing Medical University Nanjing Jiangsu China.
Lianmin ChenDepartment of Cardiology, The First Affiliated Hospital of Nanjing Medical University Nanjing Medical University Nanjing Jiangsu China.ORCID 0000-0003-0660-3518

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Complex diseases such as cardiovascular disease (CVD), obesity, inflammatory bowel disease (IBD), kidney disease, type 2 diabetes (T2D), and cancer have become a major burden to public health and affect more than 20% of the population worldwide. The etiology of complex diseases is not yet clear, but they are traditionally thought to be caused by genetics and environmental factors (e.g., dietary habits), and by their interactions. Besides this, increasing pieces of evidence now highlight that the intestinal microbiota may contribute substantially to the health and disease of the human host via their metabolic molecules. Therefore, decoding the microbial genomes has been an important strategy to shed light on their functional potential. In this review, we summarize the roles of the gut microbiome in complex diseases from its functional perspective. We further introduce artificial tools in decoding microbial genomes to profile their functionalities. Finally, state-of-the-art techniques have been highlighted which may contribute to a mechanistic understanding of the gut microbiome in human complex diseases and promote the development of the gut microbiome-based personalized medicine.

Indexed as

complex diseasegut microbiomehost–microbe interactionsmetabolites

Identifiers

PMID38868571
PMCPMC10989872

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.