Evidence map›Paper›PMID 36466818›Full record

ReviewFrontiers in immunology2022

Immune response to arbovirus infection in obesity.

Muddassar Hameed, Elizabeth Geerling, Amelia K Pinto, Iqra Miraj, James Weger-Lucarelli

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

13 citing papers in PubMed, 15 citations in OpenAlex.

  1. Observational
  2. Article
  3. Article
  4. Arboviruses in Cancer therapy: pros and cons.Journal of neurovirology · 2026
    Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Towards modelling tick-virus interactions using the weakly pathogenicFrontiers in cellular and infection microbiology · 2024
    Article
  11. Article
  12. Article
  13. Review
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

5 authors at 3 institutions in 2 countries.

Muddassar HameedDepartment of Biomedical Sciences and Pathobiology, VA-MD Regional College of Veterinary Medicine, Virginia Tech, Blacksburg, VA, United States.
Elizabeth GeerlingDepartment of Molecular Microbiology and Immunology, Saint Louis University, St. Louis, MO, United States.
Amelia K PintoDepartment of Molecular Microbiology and Immunology, Saint Louis University, St. Louis, MO, United States.
Iqra MirajCollege of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China.
James Weger-LucarelliDepartment of Biomedical Sciences and Pathobiology, VA-MD Regional College of Veterinary Medicine, Virginia Tech, Blacksburg, VA, United States.
Saint Louis University · USVirginia Tech · USZhejiang University · CN

Funding

The Role of Obesity on Alphavirus Disease SeverityR21AI153919 · NIAID · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI WEGER, JAMES D · 2021 to 2022
$421k
NIAID NIH HHS R21 AI153919
6 · The paper itself

Abstract

Obesity is a global health problem that affects 650 million people worldwide and leads to diverse changes in host immunity. Individuals with obesity experience an increase in the size and the number of adipocytes, which function as an endocrine organ and release various adipocytokines such as leptin and adiponectin that exert wide ranging effects on other cells. In individuals with obesity, macrophages account for up to 40% of adipose tissue (AT) cells, three times more than in adipose tissue (10%) of healthy weight individuals and secrete several cytokines and chemokines such as interleukin (IL)-1β, chemokine C-C ligand (CCL)-2, IL-6, CCL5, and tumor necrosis factor (TNF)-α, leading to the development of inflammation. Overall, obesity-derived cytokines strongly affect immune responses and make patients with obesity more prone to severe symptoms than patients with a healthy weight. Several epidemiological studies reported a strong association between obesity and severe arthropod-borne virus (arbovirus) infections such as dengue virus (DENV), chikungunya virus (CHIKV), West Nile virus (WNV), and Sindbis virus (SINV). Recently, experimental investigations found that DENV, WNV, CHIKV and Mayaro virus (MAYV) infections cause worsened disease outcomes in infected diet induced obese (DIO) mice groups compared to infected healthy-weight animals. The mechanisms leading to higher susceptibility to severe infections in individuals with obesity remain unknown, though a better understanding of the causes will help scientists and clinicians develop host directed therapies to treat severe disease. In this review article, we summarize the effects of obesity on the host immune response in the context of arboviral infections. We have outlined that obesity makes the host more susceptible to infectious agents, likely by disrupting the functions of innate and adaptive immune cells. We have also discussed the immune response of DIO mouse models against some important arboviruses such as CHIKV, MAYV, DENV, and WNV. We can speculate that obesity-induced disruption of innate and adaptive immune cell function in arboviral infections ultimately affects the course of arboviral disease. Therefore, further studies are needed to explore the cellular and molecular aspects of immunity that are compromised in obesity during arboviral infections or vaccination, which will be helpful in developing specific therapeutic/prophylactic interventions to prevent immunopathology and disease progression in individuals with obesity.

Indexed as

Arbovirus InfectionsChikungunya virusWest Nile virusAnimalsImmunityMiceMice, ObeseObesityadipocytesarbovirusescytokinesinterferonsobesity

Identifiers

PMID36466818
PMCPMC9716109
OpenAlexW4309277290

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.