Back

Single-cell Landscape of T Cell Heterogeneity in Kawasaki Disease: STAT3/JAK Axis Regulates the Lineage Differentiation Bias of Th17 Cells

Song, S.; Zong, Y.; Xu, Y.; Chen, L.; Zhou, Y.; Chen, L.; Li, G.; Xiao, T.; Huang, M.

2026-03-23 bioinformatics
10.64898/2026.03.18.712795 bioRxiv
Show abstract

BackgroundKawasaki disease (KD) is a pediatric systemic vasculitis in which T-cell-mediated immune responses play a pivotal role. However, the precise dynamic evolution of T-cell subsets during disease progression remains poorly understood. MethodsSingle-cell RNA sequencing (scRNA-seq) was employed to perform high-resolution annotation of peripheral blood mononuclear cells (PBMCs) from healthy controls and KD patients, both pre- and post- IVIG treatment. T-cell developmental trajectories were reconstructed via Monocle3-based pseudotime analysis. Furthermore, the functional significance of the significant pathway was validated in a CAWS-induced KD murine model. ResultsA high-resolution single-cell landscape identified 13 distinct T-cell subtypes. Pseudotime analysis revealed a significant lineage commitment of CD4+ T cells toward a Th17 phenotype during the acute phase of KD, synchronized with the transcriptional upregulation of the STAT3/JAK signaling axis. Animal experiments further demonstrated that pharmacological inhibition of this pathway substantially attenuated inflammatory infiltration in the cardiac vasculature of KD mice. ConclusionThis study identifies the STAT3/JAK-mediated Th17 differentiation bias as a potential regulatory program associated with acute inflammation in Kawasaki disease, thereby highlighting the STAT3/JAK axis as a potential therapeutic target.

Matching journals

The top 14 journals account for 50% of the predicted probability mass.

1
JCI Insight
241 papers in training set
Top 0.4%
7.0%
2
Frontiers in Immunology
586 papers in training set
Top 1%
6.5%
3
Arteriosclerosis, Thrombosis, and Vascular Biology
65 papers in training set
Top 0.5%
5.0%
4
Frontiers in Genetics
197 papers in training set
Top 2%
4.1%
5
Journal of Thrombosis and Haemostasis
28 papers in training set
Top 0.2%
3.7%
6
Scientific Reports
3102 papers in training set
Top 34%
3.7%
7
BMC Medical Genomics
36 papers in training set
Top 0.1%
3.7%
8
Arthritis & Rheumatology
33 papers in training set
Top 0.2%
3.7%
9
PLOS ONE
4510 papers in training set
Top 44%
2.8%
10
Journal of Translational Medicine
46 papers in training set
Top 0.3%
2.8%
11
Advanced Science
249 papers in training set
Top 8%
2.1%
12
Frontiers in Cardiovascular Medicine
49 papers in training set
Top 1%
1.9%
13
Human Genomics
21 papers in training set
Top 0.1%
1.9%
14
PLOS Computational Biology
1633 papers in training set
Top 14%
1.9%
50% of probability mass above
15
International Journal of Molecular Sciences
453 papers in training set
Top 6%
1.8%
16
Nature Communications
4913 papers in training set
Top 50%
1.7%
17
Molecular Therapy - Nucleic Acids
24 papers in training set
Top 0.1%
1.7%
18
The Journal of Infectious Diseases
182 papers in training set
Top 2%
1.7%
19
American Journal of Respiratory and Critical Care Medicine
39 papers in training set
Top 0.5%
1.7%
20
Clinical Infectious Diseases
231 papers in training set
Top 3%
1.7%
21
eBioMedicine
130 papers in training set
Top 2%
1.5%
22
Genome Medicine
154 papers in training set
Top 5%
1.4%
23
Computers in Biology and Medicine
120 papers in training set
Top 3%
1.4%
24
International Immunopharmacology
15 papers in training set
Top 0.2%
1.3%
25
Cell Reports Medicine
140 papers in training set
Top 6%
1.0%
26
Annals of the Rheumatic Diseases
32 papers in training set
Top 0.5%
1.0%
27
Immunology
29 papers in training set
Top 0.8%
0.9%
28
Frontiers in Medicine
113 papers in training set
Top 6%
0.8%
29
Computational and Structural Biotechnology Journal
216 papers in training set
Top 8%
0.8%
30
iScience
1063 papers in training set
Top 31%
0.8%