Evidence map›Paper›PMID 39188722›Full record

ReviewFrontiers in immunology2024

Obesity-compromised immunity in post-COVID-19 condition: a critical control point of chronicity.

Soonwoo Jang, Wooyoung Hong, Yuseok Moon

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. 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

3 authors.

Soonwoo JangLaboratory of Mucosal Exposome and Biomodulation, Department of Integrative Biomedical Sciences, Pusan National University, Yangsan, Republic of Korea.
Wooyoung HongDepartment of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, United States.
Yuseok MoonLaboratory of Mucosal Exposome and Biomodulation, Department of Integrative Biomedical Sciences, Pusan National University, Yangsan, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Post-COVID-19 condition is recognized as a multifactorial disorder, with persistent presence of viral antigens, discordant immunity, delayed viral clearance, and chronic inflammation. Obesity has emerged as an independent risk factor for both SARS-CoV-2 infection and its subsequent sequelae. In this study, we aimed to predict the molecular mechanisms linking obesity and post-COVID-19 distress. Viral antigen-exposed adipose tissues display remarkable levels of viral receptors, facilitating viral entry, deposition, and chronic release of inflammatory mediators and cells in patients. Subsequently, obesity-associated inflammatory insults are predicted to disturb cellular and humoral immunity by triggering abnormal cell differentiation and lymphocyte exhaustion. In particular, the decline in SARS-CoV-2 antibody titers and T-cell exhaustion due to chronic inflammation may account for delayed virus clearance and persistent activation of inflammatory responses. Taken together, obesity-associated defective immunity is a critical control point of intervention against post-COVID-19 progression, particularly in subjects with chronic metabolic distress.

Indexed as

COVID-19ObesitySARS-CoV-2Adipose TissueChronic DiseaseHumansImmunity, HumoralInflammationT-LymphocytesACE2adipose tissueCOVID-19immunitylong COVIDobesitypost COVID-19 conditionSARS-CoV-2

Identifiers

PMID39188722
PMCPMC11345197

What OpenQuestion holds

Textmetadata
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.