The immune cell transcription factor T-bet: A novel metabolic regulator
Open accessAbstract
Obesity-associated insulin resistance is accompanied by an alteration in the Th1/Th2 balance in adipose tissue. T-bet (Tbx21) is an immune cell transcription factor originally described as the master regulator of Th1 cell development, although is now recognized to have a role in both the adaptive and innate immune systems. T-bet also directs T-cell homing to pro-inflammatory sites by the regulation of CXCR3 expression. T-bet(-/-) mice have increased visceral adiposity but are more insulin-sensitive, exhibiting reduced immune cell content and cytokine secretion specifically in the visceral fat depot, perhaps due to altered T-cell trafficking. Studies of T-bet deficiency on Rag2-- and IFN-γ-deficient backgrounds indicate the importance of CD4(+) T cells and IFN-γ in this model. This favorable metabolic phenotype, uncoupling adiposity from insulin resistance, is present in young lean mice yet persists with age and increasing obesity. We suggest a novel role for T-bet in metabolic regulation.
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SCENIC+ analysis revealed 180 eRegulons, including SPI1, JDP2, RUNX1 in Kupffer cells; EBF1 and PAX5 in B cells; GATA3 and LEF1 in T cells; GATA4, MEIS1 and MAF in LSECs; LHX2 and TEAD1 in HSCs; WT1 in fibroblasts; and TEAD4, DOX4 and HNF1B in BECs, among others, in agreement with literature.
“This analysis revealed 180 eRegulons, including SPI1, JDP2, RUNX1 in Kupffer cells; EBF1 and PAX5 in B cells; GATA3 and LEF1 in T cells; GATA4, MEIS1 and MAF in LSECs; LHX2 and TEAD1 in HSCs; WT1 in fibroblasts; and TEAD4, DOX4 and HNF1B in BECs, among others, and in agreement with literature15–20.”
From Single-cell spatial multi-omics and deep learning dissect enhancer-driven gene regulatory networks in liver zonation (2024) · cites this paper as [17]
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Experimental — accuracy not yet measuredThis approach identified PU.1, Runx, and Irf as candidate TFs for Kupffer cell enhancers; Pax5 and Ebf1 for B cells; Tbx21 for T cells; Meis1, Maf and Gata4 for LSECs; Mef2c and Lhx2 for HSC; and Tead4, Sox9 and Hnf1b for BECs.
“this approach identified PU.1, Runx, and Irf as candidate TFs for Kupffer cell enhancers37; Pax5 and Ebf1 for B cells38; Tbx21 for T cells39; Meis1, Maf and Gata4 for LSECs40; Mef2c and Lhx2 for HSC41; and Tead4, Sox9 and Hnf1b for BECs42”
From Enhancer grammar of liver cell types and hepatocyte zonation states (2022) · cites this paper as [39]
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- Authors
- Stolarczyk, E., Lord, G. M., & Howard, J. K.
- Affiliations
- King's College London (GB)
- Corresponding author
- Howard, Jane K
- Venue
- Adipocyte
- Publisher
- Informa UK Limited
- Published
- 2013-08-28
- Volume
- 3
- Issue
- 1
- Pages
- 58-62
- ISSN
- 2162-3945 (ISSN-L)
- 2162-397X
- PMC
- PMC3917935
- OpenAlex
- W1987176235
- Cited by
- 32
- References
- 51
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 4 · 2023: 7 · 2022: 1 · 2021: 1 · 2020: 3 · 2019: 2 · 2016: 3 · 2015: 2 · 2014: 2
- FWCI
- 1.70
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by-nc
- Locations
- Adipocyte (publishedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Research Portal (King's College London) (publishedVersion, other-oa)
- Spiral (Imperial College London) (submittedVersion, other-oa)
- Funders
- Medical Research Council (MR/J006742/1, MR/K002996/1)
- Topics
- Health Sciences › Medicine › Epidemiology › Adipokines, Inflammation, and Metabolic Diseases
- Health Sciences › Medicine › Physiology › Adipose Tissue and Metabolism
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Keywords
- T-bet, TBX21, obesity, insulin resistance, Th1/Th2 balance, adipose tissue, visceral fat, T cell migration, CXCR3, CD4+ T cells, interferon-gamma, metabolic regulation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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