Immune Repertoire Profiling Reveals Distinct Adaptive Immune Signatures of Dampness ZHENG Across Psoriasis, Rheumatoid Arthritis and Ulcerative Colitis
TL;DR
The findings suggest that TCM‐based phenotyping may offer a meaningful approach for subgrouping autoimmune diseases, thereby providing a foundation for more syndrome differentiation‐based treatment strategies.
Abstract
ABSTRACT Autoimmune diseases, including psoriasis (Ps), rheumatoid arthritis (RA) and ulcerative colitis (UC), pose significant health burdens worldwide. A more refined classification of these diseases is essential for enabling targeted therapeutic strategies. Traditional Chinese Medicine (TCM) is gaining increasing recognition globally, offering potential insights into disease heterogeneity. In this study, we performed comprehensive T cell receptor (TCR) and B cell receptor (BCR) repertoire sequencing in 59 participants, including patients with Ps, RA, UC and healthy controls. Patients were further stratified into Dampness and non‐Dampness groups based on standardized TCM diagnostic criteria. Repertoire composition, clonotype richness, diversity metrics, V gene usage and shared CDR3 patterns were analysed. Machine learning approaches (LASSO, GLM and OPLS‐DA) were applied to identify diagnostic biomarkers, followed by validation in an independent cohort. Compared with healthy controls, Ps, RA and UC patients exhibited reduced clonotype richness and diminished TCR/BCR diversity, indicating adaptive immune contraction. Dampness ZHENG‐specific alterations were observed, including selective IgK and IgL clonotype richness reduction in Ps with dampness, increased TRA/TRB diversity in RA with dampness, and elevated TRG clonotype counts/read proportions in UC with dampness. Stratification by Dampness ZHENG revealed distinct immune repertoire architectures characterized by increased D50 index, reduced proportions of large clones and preferential V gene usage, including TRAV20, TRAV38‐2DV8 and TRAV8‐3. Unsupervised dimensionality reduction demonstrated significant separation between Dampness and non‐Dampness groups across diseases. A three‐gene V‐segment model achieved an AUC of 0.804 and 74.7% accuracy in an independent validation cohort, supporting its potential utility as an objective biomarker for Dampness ZHENG. Our findings suggest that TCM‐based phenotyping may offer a meaningful approach for subgrouping autoimmune diseases, thereby providing a foundation for more syndrome differentiation‐based treatment strategies.