Go to The Journal of Clinical Investigation
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Publication alerts by email
  • Transfers
  • Advertising
  • Job board
  • Contact
  • Physician-Scientist Development
  • Current issue
  • Past issues
  • By specialty
    • COVID-19
    • Cardiology
    • Immunology
    • Metabolism
    • Nephrology
    • Oncology
    • Pulmonology
    • All ...
  • Videos
  • Collections
    • In-Press Preview
    • Resource and Technical Advances
    • Clinical Research and Public Health
    • Research Letters
    • Editorials
    • Perspectives
    • Physician-Scientist Development
    • Reviews
    • Top read articles

  • Current issue
  • Past issues
  • Specialties
  • In-Press Preview
  • Resource and Technical Advances
  • Clinical Research and Public Health
  • Research Letters
  • Editorials
  • Perspectives
  • Physician-Scientist Development
  • Reviews
  • Top read articles
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Publication alerts by email
  • Transfers
  • Advertising
  • Job board
  • Contact

Usage Information

A systems immunology approach identifies the collective impact of 5 miRs in Th2 inflammation
Ayşe Kılıç, … , Amitabh Sharma, Harald Renz
Ayşe Kılıç, … , Amitabh Sharma, Harald Renz
Published June 7, 2018
Citation Information: JCI Insight. 2018;3(11):e97503. https://doi.org/10.1172/jci.insight.97503.
View: Text | PDF
Research Article Immunology Inflammation Article has an altmetric score of 1

A systems immunology approach identifies the collective impact of 5 miRs in Th2 inflammation

  • Text
  • PDF
Abstract

Allergic asthma is a chronic inflammatory disease dominated by a CD4+ T helper 2 (Th2) cell signature. The immune response amplifies in self-enforcing loops, promoting Th2-driven cellular immunity and leaving the host unable to terminate inflammation. Posttranscriptional mechanisms, including microRNAs (miRs), are pivotal in maintaining immune homeostasis. Since an altered expression of various miRs has been associated with T cell–driven diseases, including asthma, we hypothesized that miRs control mechanisms ensuring Th2 stability and maintenance in the lung. We isolated murine CD4+ Th2 cells from allergic inflamed lungs and profiled gene and miR expression. Instead of focusing on the magnitude of miR differential expression, here we addressed the secondary consequences for the set of molecular interactions in the cell, the interactome. We developed the Impact of Differential Expression Across Layers, a network-based algorithm to prioritize disease-relevant miRs based on the central role of their targets in the molecular interactome. This method identified 5 Th2-related miRs (mir27b, mir206, mir106b, mir203, and mir23b) whose antagonization led to a sharp reduction of the Th2 phenotype. Overall, a systems biology tool was developed and validated, highlighting the role of miRs in Th2-driven immune response. This result offers potentially novel approaches for therapeutic interventions.

Authors

Ayşe Kılıç, Marc Santolini, Taiji Nakano, Matthias Schiller, Mizue Teranishi, Pascal Gellert, Yuliya Ponomareva, Thomas Braun, Shizuka Uchida, Scott T. Weiss, Amitabh Sharma, Harald Renz

×

Usage data is cumulative from August 2024 through August 2025.

Usage JCI PMC
Text version 747 55
PDF 59 17
Figure 220 1
Table 18 0
Supplemental data 29 0
Citation downloads 65 0
Totals 1,138 73
Total Views 1,211
Created with Highcharts 3.0.9MonthTotalAug 24Sep 24Oct 24Nov 24Dec 24Jan 25Feb 25Mar 25Apr 25May 25Jun 25Jul 25Aug 250250500750100012501500
JCI Citation downloads
JCI Figure
JCI Text version
JCI PDF
JCI Supplemental data
JCI Table
PMC Text version
PMC PDF
Total JCI usage
Total PMC usage
Total usage
(Click and drag on plot area to zoom in. Click legend items above to toggle)

Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

Advertisement

Copyright © 2025 American Society for Clinical Investigation
ISSN 2379-3708

Sign up for email alerts

Posted by 2 X users
30 readers on Mendeley
See more details