Rheumatology and immunology research · 2026
Neuropsychiatric systemic lupus erythematosus subtypes identified by unsupervised clustering: A single-center cohort study.
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Fang Weiting, Zhao Jiuliang, Xu Dong, Wang Ziqian, Li Mengtao, Fan Siyuan, Li Tao, Xie Manqing, Liu Zeyu, You Hui, Wang Yanhong, Zhang Shangzhu, Zeng Xiaofeng
Аннотация
BACKGROUND AND OBJECTIVES: Neuropsychiatric (NP) manifestations are common, heterogeneous and severe in systemic lupus erythematosus (SLE) patients, with attribution to SLE remaining diagnostically challenging. Traditional classification focuses on clinical syndromes, overlooking neuropsychiatric systemic lupus erythematosus (NPSLE) immunological heterogeneity. To address the heterogeneity of NPSLE, this study aimed to delineate distinct disease subgroups by clustering patients based on their antibody profiles. These subgroups were then evaluated for diferences in clinical presentation and prognosis, to better characterize disease subsets and support individualized approaches to diagnosis and management.
METHODS: This retrospective single-center study included hospitalized SLE patients with NP manifestations, collecting demographic, clinical and laboratory data. Patients were classified as NPSLE or non-NPSLE by clinical judgment after excluding alternative causes. Hierarchical cluster analysis explored autoantibody-clinical feature associations.
RESULTS: Among the 167 patients analyzed, 152 had NP manifestations attributed to SLE. Central nervous system (CNS) involvement was predominant (89.1%), with seizures, cerebrovascular disease, acute confusional state (ACS), and demyelinating syndrome being most prevalent manifestations. Hierarchical clustering of 152 NPSLE patients identified two subgroups: Cluster 1 (23.7%) demonstrated cerebrovascular injury as the predominant manifestation, with higher positivity rates of antiphospholipid antibodies (APLs) (P < 0.01) and a higher incidence of cerebrovascular disease (P < 0.01). Cluster 2 (76.3%) showed immune-mediated inflammatory profile, with higher positivity of anti-SSA (P < 0.01), antidsDNA (P < 0.05), and anti-RiboP antibodies (P < 0.05). Neurological involvement predominantly manifesting as ACS (P < 0.05), accompanied by a higher frequency of fever and joint involvement.
CONCLUSIONS: In this study, NPSLE exhibited distinct serological profiles and segregated into two immunologically defined clusters, reflecting its clinical and biological heterogeneity, and suggesting that immunological profiling may enhance precise classification and personalized management of affected patients.
METHODS: This retrospective single-center study included hospitalized SLE patients with NP manifestations, collecting demographic, clinical and laboratory data. Patients were classified as NPSLE or non-NPSLE by clinical judgment after excluding alternative causes. Hierarchical cluster analysis explored autoantibody-clinical feature associations.
RESULTS: Among the 167 patients analyzed, 152 had NP manifestations attributed to SLE. Central nervous system (CNS) involvement was predominant (89.1%), with seizures, cerebrovascular disease, acute confusional state (ACS), and demyelinating syndrome being most prevalent manifestations. Hierarchical clustering of 152 NPSLE patients identified two subgroups: Cluster 1 (23.7%) demonstrated cerebrovascular injury as the predominant manifestation, with higher positivity rates of antiphospholipid antibodies (APLs) (P < 0.01) and a higher incidence of cerebrovascular disease (P < 0.01). Cluster 2 (76.3%) showed immune-mediated inflammatory profile, with higher positivity of anti-SSA (P < 0.01), antidsDNA (P < 0.05), and anti-RiboP antibodies (P < 0.05). Neurological involvement predominantly manifesting as ACS (P < 0.05), accompanied by a higher frequency of fever and joint involvement.
CONCLUSIONS: In this study, NPSLE exhibited distinct serological profiles and segregated into two immunologically defined clusters, reflecting its clinical and biological heterogeneity, and suggesting that immunological profiling may enhance precise classification and personalized management of affected patients.