Immunophenotyping and machine learning-based stratification reveal prognostic immune signatures in Behçet’s disease
This study provided a comprehensive immunophenotypic profile of treatment-naive BD patients. Machine learning integration of lymphocyte subsets and clinical parameters enabled the identification of subgroups at high risk of relapse at an early stage, providing a rationale for personalized treatment strategies.
Authors
- Yiyuan Ao
- Wenjie Zheng (ORCID: https://orcid.org/0000-0002-3165-8185)
- Wei Cao (ORCID: https://orcid.org/0000-0002-8546-6090)
- Ling Qin (ORCID: https://orcid.org/0000-0002-5248-5738)
- Taisheng Li (ORCID: https://orcid.org/0000-0002-7050-5675)
- Yan Daniel Zhao (ORCID: https://orcid.org/0000-0003-3448-0527)
- Li Wang (ORCID: https://orcid.org/0000-0003-0899-5703)
- Lu Li (ORCID: https://orcid.org/0009-0008-1104-8655)
- Lidan Zhao
- Jinjing Liu (ORCID: https://orcid.org/0000-0003-2150-7540)
Institutions
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Peking Union Medical College Hospital (CN)
- National Clinical Research Center for Digestive Diseases (CN)
- Ministry of Science (ME)
- National Clinical Research (US)
Publication Details
- Journal
- Lara D. Veeken
- Published
- 2025-11-21
- DOI
- https://doi.org/10.1093/rheumatology/keaf595
- Primary Topic
- Ocular Diseases and Behçet’s Syndrome
- Type
- article
- Field-Weighted Citation Impact
- 0.00