Evidence map›Paper›PMID 35715833›Full record

ArticleMilitary Medical Research2022

Characterization of oral and gut microbiome and plasma metabolomics in COVID-19 patients after 1-year follow-up.

Guang-Ying Cui, Ben-Chen Rao, Zhao-Hai Zeng, Xue-Mei Wang, Tong Ren, Hai-Yu Wang, Hong Luo, Hong-Yan Ren, Chao Liu, Su-Ying Ding and 5 more

Abstract read
In one paragraph

Article in Military Medical Research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

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

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  9. ThickFrontiers in cellular and infection microbiology · 2025
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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

15 authors.

Guang-Ying Cui *Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Ben-Chen Rao *Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Zhao-Hai Zeng *Department of Infectious Diseases, Guangshan County People's Hospital, Guangshan County, Xinyang, 465450, Henan, China.
Xue-Mei Wang *Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Tong Ren *Department of Breast Surgery, Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Hai-Yu WangDepartment of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Hong LuoDepartment of Infectious Diseases, Guangshan County People's Hospital, Guangshan County, Xinyang, 465450, Henan, China.
Hong-Yan RenShanghai Mobio Biomedical Technology Co., Ltd, Shanghai, 201111, China.
Chao LiuShanghai Mobio Biomedical Technology Co., Ltd, Shanghai, 201111, China.
Su-Ying DingHealth Management Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Jun-Jie TanDepartment of Infectious Diseases, Guangshan County People's Hospital, Guangshan County, Xinyang, 465450, Henan, China.
Zhen-Guo LiuDepartment of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Ya-Wen ZouDepartment of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Zhi-Gang RenDepartment of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China. fccrenzg@zzu.edu.cn.ORCID 0000-0003-0798-3444
Zu-Jiang YuDepartment of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China. johnyuem@zzu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDue to the outbreak and rapid spread of coronavirus disease 2019 (COVID-19), more than 160 million patients have become convalescents worldwide to date. Significant alterations have occurred in the gut and oral microbiome and metabonomics of patients with COVID-19. However, it is unknown whether their characteristics return to normal after the 1-year recovery.

methodsWe recruited 35 confirmed patients to provide specimens at discharge and one year later, as well as 160 healthy controls. A total of 497 samples were prospectively collected, including 219 tongue-coating, 129 stool and 149 plasma samples. Tongue-coating and stool samples were subjected to 16S rRNA sequencing, and plasma samples were subjected to untargeted metabolomics testing.

resultsThe oral and gut microbiome and metabolomics characteristics of the 1-year convalescents were restored to a large extent but did not completely return to normal. In the recovery process, the microbial diversity gradually increased. Butyric acid-producing microbes and Bifidobacterium gradually increased, whereas lipopolysaccharide-producing microbes gradually decreased. In addition, sphingosine-1-phosphate, which is closely related to the inflammatory factor storm of COVID-19, increased significantly during the recovery process. Moreover, the predictive models established based on the microbiome and metabolites of patients at the time of discharge reached high efficacy in predicting their neutralizing antibody levels one year later.

conclusionsThis study is the first to characterize the oral and gut microbiome and metabonomics in 1-year convalescents of COVID-19. The key microbiome and metabolites in the process of recovery were identified, and provided new treatment ideas for accelerating recovery. And the predictive models based on the microbiome and metabolomics afford new insights for predicting the recovery situation which benefited affected individuals and healthcare.

Indexed as

COVID-19Gastrointestinal MicrobiomeFollow-Up StudiesHumansMetabolomicsRNA, Ribosomal, 16SRNA, Ribosomal, 16SConvalescentsCoronavirus disease 2019 (COVID-19)Gut microbiomeIndividual outcomesOral microbiomePatient stratificationPlasma metabonomicsPredictivePreventive and personalized medicine (3PM)

Identifiers

PMID35715833
PMCPMC9204369

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Registered trials

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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.