Evidence map›Paper›PMID 34677374›Full record

ArticleMetabolites2021

SARS-CoV2 Infection Alters Tryptophan Catabolism and Phospholipid Metabolism.

Gagandeep Kaur, Xiangming Ji, Irfan Rahman

Open access · goldAbstract read
In one paragraph

Article in Metabolites, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.7field-weighted citation impact, top 18% 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

12 citing papers in PubMed, 29 citations in OpenAlex.

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  11. COVIDomics: The Proteomic and Metabolomic Signatures of COVID-19.International journal of molecular sciences · 2022
    Review
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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

3 authors at 2 institutions in 1 country.

Gagandeep KaurDepartment of Environmental Medicine, University of Rochester Medical Center, Rochester, NY 14642, USA.
Xiangming JiDepartment of Nutrition, Byrdine F. Lewis School of Nursing and Health Professions, Georgia State University, Atlanta, GA 30302, USA.
Irfan RahmanDepartment of Environmental Medicine, University of Rochester Medical Center, Rochester, NY 14642, USA.ORCID 0000-0003-2274-2454
University of Rochester Medical Center · USGeorgia State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronavirus disease 2019 (COVID-19) has so far infected hundreds of million individuals, with several million deaths worldwide. The lack of understanding of the disease pathophysiology and the host's immune response has resulted in this rapid spread of the disease on a global scale. In this respect, we employed UPLC-MS to compare the metabolites in the serum from COVID-19-positive patients and COVID-19-recovered subjects to determine the metabolic changes responsible for an infection. Our investigations revealed significant increase in the levels of serum phospholipids including sphingomyelins, phosphatidylcholines and arachidonic acid in the serum of COVID-19-positive patients as compared to COVID-19-recovered individuals. We further show increased levels of tryptophan and its metabolites in the serum of COVID-19-positive patients thus emphasizing the role of tryptophan metabolism in the disease pathogenesis of COVID-19. Future studies are required to determine the changes in the lipid and tryptophan metabolism at various stages of COVID-19 disease development, progression and recovery to better understand the host-pathogen interaction and the long-term effects of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) infection in humans.

Indexed as

COVID-19lipid metabolismmetabolomicSARS-CoV2tryptophan metabolism

Identifiers

PMID34677374
PMCPMC8538244
OpenAlexW3203066442

What OpenQuestion holds

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LicenceCC BY
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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.