Evidence map›Paper›PMID 35783436›Full record

ReviewFrontiers in microbiology2022

Metaomics in Clinical Laboratory: Potential Driving Force for Innovative Disease Diagnosis.

Liang Wang, Fen Li, Bin Gu, Pengfei Qu, Qinghua Liu, Junjiao Wang, Jiawei Tang, Shubin Cai, Qi Zhao, Zhong Ming

Abstract readReview
In one paragraph

Review in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Review
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

10 authors.

Liang WangDepartment of Bioinformatics, School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, China.
Fen LiDepartment of Laboratory Medicine, Huaiyin Hospital, Huai'an, China.
Bin GuDepartment of Bioinformatics, School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, China.
Pengfei QuThe First School of Clinical Medicine, Xuzhou Medical University, Xuzhou, China.
Qinghua LiuState Key Laboratory of Quality Research in Chinese Medicines, Macau University of Science and Technology, Taipa, Macao SAR, China.
Junjiao WangDepartment of Bioinformatics, School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, China.
Jiawei TangDepartment of Bioinformatics, School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, China.
Shubin CaiCollege of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China.
Qi ZhaoSchool of Computer Science and Software Engineering, University of Science and Technology Liaoning, Anshan, China.
Zhong MingCollege of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Currently, more and more studies suggested that reductionism was lack of holistic and integrative view of biological processes, leading to limited understanding of complex systems like microbiota and the associated diseases. In fact, microbes are rarely present in individuals but normally live in complex multispecies communities. With the recent development of a variety of metaomics techniques, microbes could be dissected dynamically in both temporal and spatial scales. Therefore, in-depth understanding of human microbiome from different aspects such as genomes, transcriptomes, proteomes, and metabolomes could provide novel insights into their functional roles, which also holds the potential in making them diagnostic biomarkers in many human diseases, though there is still a huge gap to fill for the purpose. In this mini-review, we went through the frontlines of the metaomics techniques and explored their potential applications in clinical diagnoses of human diseases, e.g., infectious diseases, through which we concluded that novel diagnostic methods based on human microbiomes shall be achieved in the near future, while the limitations of these techniques such as standard procedures and computational challenges for rapid and accurate analysis of metaomics data in clinical settings were also examined.

Indexed as

biomarkerdiseasesmicrobiologymicrobiomeomicsrapid diagnosis

Identifiers

PMID35783436
PMCPMC9247514

What OpenQuestion holds

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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.