Evidence map›Paper›PMID 33721144›Full record

ArticleIntensive care medicine experimental2021

Longitudinal multi-omics transition associated with fatality in critically ill COVID-19 patients.

Chaoyang Sun, Yuzhe Sun, Ping Wu, Wencheng Ding, Shiyou Wang, Jiafeng Li, Langchao Liang, Chaochao Chai, Yu Fu, Zhiming Li and 11 more

Open access · goldAbstract read
In one paragraph

Article in Intensive care medicine experimental, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
1.7field-weighted citation impact, top 20% 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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 14 citations in OpenAlex.

  1. Pooled it
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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

21 authors at 3 institutions in 1 country.

Chaoyang Sun *Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China.
Yuzhe Sun *BGI-Shenzhen, Shenzhen, 518083, China.
Ping Wu *Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China.
Wencheng Ding *Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China.
Shiyou Wang *BGI-Shenzhen, Shenzhen, 518083, China.
Jiafeng LiBGI-Shenzhen, Shenzhen, 518083, China.
Langchao LiangBGI-Shenzhen, Shenzhen, 518083, China.
Chaochao ChaiBGI-Shenzhen, Shenzhen, 518083, China.
Yu FuCancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China.
Zhiming LiBGI-Shenzhen, Shenzhen, 518083, China.
Linnan ZhuShenzhen Bay Laboratory, Shenzhen, 518107, China.
Jia JuBGI-Shenzhen, Shenzhen, 518083, China.
Xin LiaoDepartment of Geriatrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China.
Xiaoyuan HuangCancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China.
Ling FengDepartment of Gynecology and Obstetrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science & Technology, Wuhan, China.
Ding MaCancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China.
Liang HeCancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China. whuheliang@outlook.com.
Dongsheng ChenBGI-Shenzhen, Shenzhen, 518083, China. chendongsheng@genomics.cn.
Gang ChenCancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China. tjchengang@hust.edu.cn.
Xin JinBGI-Shenzhen, Shenzhen, 518083, China. jinxin@genomics.cn.
Peng WuCancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Medical College, Tongji Hospital, Huazhong University of Science and Technology, Wuhan, China. pengwu8626@tjh.tjmu.edu.cn.ORCID http://orcid.org/0000-0003-4498-7663
Tongji Hospital · CNBGI Group (China) · CNShenzhen Bay Laboratory · CN

Funding

China National GeneBank (CNGB) and Guangdong Provincial Key Laboratory of Genome Read and Write No. 2017B030301011Funds for Distinguished Young Scholar of South China University of China 2017JQ017National University Basic Scientific Research Special Foundation 2020kfyXGYJ00Natural Science Foundation of Guangdong Province 2017A030306026
6 · The paper itself

Abstract

purposeCritically ill COVID-19 patients have significantly increased risk of death. Although several circulating biomarkers are thought to be related to COVID-19 severity, few studies have focused on the characteristics of critically ill patients with different outcomes. The objective of this study was to perform a longitudinal investigation of the potential mechanisms affecting the prognosis of critically ill COVID-19 patients.

methodsIn addition to clinical data, 113 whole blood samples and 85 serum samples were collected from 33 severe and critical COVID-19 patients without selected comorbidities. Multi-omics analysis was then performed using longitudinal samples.

resultsObvious transcriptional transitions were more frequent in critical survivors than in critical non-survivors, indicating that phase transition may be related to survival. Based on analysis of differentially expressed genes during transition, the erythrocyte differentiation pathway was significantly enriched. Furthermore, clinical data indicated that red blood cell counts showed greater fluctuation in survivors than in non-survivors. Moreover, declining red blood cell counts and hemoglobin levels were validated as prognostic markers of poor outcome in an independent cohort of 114 critical COVID-19 patients. Protein-metabolite-lipid network analysis indicated that tryptophan metabolism and melatonin may contribute to molecular transitions in critical COVID-19 patients with different outcomes.

conclusionsThis study systematically and comprehensively depicted the longitudinal hallmarks of critical COVID-19 patients and indicated that multi-omics transition may impact the prognosis. TAKE HOME MESSAGE: Frequent transcriptional phase transitions may contribute to outcome in critically ill COVID-19 patients. Furthermore, fluctuation in red blood cell and hemoglobin levels may relate to poor prognosis. The biological function of melatonin was suppressed in COVID-19 non-survivors, which may provide a potential theoretical basis for clinical administration.

Indexed as

COVID-19Critically illErythrocyteMelatoninMulti-omics

Identifiers

PMID33721144
PMCPMC7957447
OpenAlexW3111955104

What OpenQuestion holds

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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.