Evidence map›Paper›PMID 34151035›Full record

ArticleSynthetic and systems biotechnology2021

Association between the nasopharyngeal microbiome and metabolome in patients with COVID-19.

Jing Liu, Sheng Liu, Zhao Zhang, Xuejun Lee, Wenxuan Wu, Zhanlian Huang, Ziying Lei, Wenxiong Xu, Dabiao Chen, Xing Wu and 10 more

Open access · goldAbstract read
In one paragraph

Article in Synthetic and systems biotechnology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 1 pooled it
5.7field-weighted citation impact, top 3% of its field
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

33 citing papers in PubMed, 1 synthesis or guideline pooled it, 76 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Effect of nasal carriage ofMicrobiology spectrum · 2024
    Article
  12. Article
  13. The nasopharyngeal microbiome in COVID-19.Emerging microbes & infections · 2023
    Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

20 authors at 1 institution in 1 country.

Jing LiuDepartment of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510630, China.
Sheng LiuThe Center for Infection and Immunity Study (CIIS), School of Medicine, Sun Yat-sen University, Shenzhen, China.
Zhao ZhangSouth China Institute of Biomedicine, Guangzhou, Guangdong, 510535, China.
Xuejun LeeDepartment of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510630, China.
Wenxuan WuThe Center for Infection and Immunity Study (CIIS), School of Medicine, Sun Yat-sen University, Shenzhen, China.
Zhanlian HuangDepartment of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510630, China.
Ziying LeiDepartment of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510630, China.
Wenxiong XuDepartment of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510630, China.
Dabiao ChenDepartment of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510630, China.
Xing WuSouth China Institute of Biomedicine, Guangzhou, Guangdong, 510535, China.
Yang GuoThe Center for Infection and Immunity Study (CIIS), School of Medicine, Sun Yat-sen University, Shenzhen, China.
Liang PengDepartment of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510630, China.
Bingliang LinDepartment of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510630, China.
Yutian ChongDepartment of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510630, China.
Xiangyu MouThe Center for Infection and Immunity Study (CIIS), School of Medicine, Sun Yat-sen University, Shenzhen, China.
Mang ShiThe Center for Infection and Immunity Study (CIIS), School of Medicine, Sun Yat-sen University, Shenzhen, China.
Ping LanThe Center for Infection and Immunity Study (CIIS), School of Medicine, Sun Yat-sen University, Shenzhen, China.
Tao ChenSouth China Institute of Biomedicine, Guangzhou, Guangdong, 510535, China.
Wenjing ZhaoThe Center for Infection and Immunity Study (CIIS), School of Medicine, Sun Yat-sen University, Shenzhen, China.
Zhiliang GaoDepartment of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, 510630, China.
Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

SARS-CoV-2, the causative agent for COVID-19, infect human mainly via respiratory tract, which is heavily inhabited by local microbiota. However, the interaction between SARS-CoV-2 and nasopharyngeal microbiota, and the association with metabolome has not been well characterized. Here, metabolomic analysis of blood, urine, and nasopharyngeal swabs from a group of COVID-19 and non-COVID-19 patients, and metagenomic analysis of pharyngeal samples were used to identify the key features of COVID-19. Results showed lactic acid, l-proline, and chlorogenic acid methyl ester (CME) were significantly reduced in the sera of COVID-19 patients compared with non-COVID-19 ones. Nasopharyngeal commensal bacteria including

Indexed as

COVID-19MetabolomeNasopharyngeal microbiomeSARS-CoV-2Susceptibility

Identifiers

PMID34151035
PMCPMC8200311
OpenAlexW3169915883

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.