Evidence map›Paper›PMID 40489251›Full record

ReviewInternational immunology2025

Cellular metabolism in Th9, Th17, and Treg cell differentiation.

Toshio Kanno, Keiko Nakano, Yusuke Endo

Abstract readReview
In one paragraph

Review in International immunology, 2025. 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
–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

12 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. 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

3 authors.

Toshio KannoDepartment of Frontier Research and Development, Laboratory of Medical Omics Research, Kazusa DNA Research Institute, 2-6-7 Kazusa Kamatari, Kisarazu, Chiba 292-0818, Japan.
Keiko NakanoDepartment of Frontier Research and Development, Laboratory of Medical Omics Research, Kazusa DNA Research Institute, 2-6-7 Kazusa Kamatari, Kisarazu, Chiba 292-0818, Japan.
Yusuke EndoDepartment of Frontier Research and Development, Laboratory of Medical Omics Research, Kazusa DNA Research Institute, 2-6-7 Kazusa Kamatari, Kisarazu, Chiba 292-0818, Japan.ORCID 0000-0002-7223-1938

Funding

FOREST JPMJFR225XKAZUSA 23K14552
6 · The paper itself

Abstract

CD4+ helper T (Th) cell subsets play an essential role in the regulation of adaptive immunity. Th9, Th17, and regulatory T (Treg) cells require transforming growth factor-beta (TGF-β) for their differentiation; however, their respective functions are highly distinct. Recent studies have highlighted the critical role of cellular metabolism in initiating clonal expansion and facilitating the effector differentiation of Th cells. Upon antigen exposure, naïve CD4+ T cells undergo metabolic reprogramming to fulfill their bioenergetic and biosynthetic demands. This process involves a shift from fatty acid oxidation to glycolysis, which ensures a sufficient energy supply for activation and proliferation. Lipid metabolism plays a pivotal role in modulating the differentiation and function of Th17, Treg, and Th9 cells. This review explores the influence of metabolic pathways on key transcription factors, including retinoic-acid-related orphan receptor gamma t (RORγt) and SMADs, and emphasizes their regulatory roles in Th cell differentiation. Furthermore, it discusses emerging therapeutic strategies aimed at targeting cellular metabolism to address autoimmune and inflammatory diseases associated with these T-cell subsets.

Indexed as

Cell DifferentiationTh17 CellsT-Lymphocytes, Helper-InducerT-Lymphocytes, RegulatoryAnimalsHumansACC1lipid metabolismRORγt

Identifiers

PMID40489251
PMCPMC12658748

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.