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Characterisation and diagnostic model of monogenic lupus
Mengyang Yang1, Dan Lu1, Yulu Li1
1Department of Immunology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China.
Immunologic Research
|October 13, 2025
Summary
Diagnosing rare monogenic lupus in children is challenging. This study identifies key clinical features and proposes pathway-specific diagnostic models to aid early detection in pediatric patients.
Area of Science:
- Pediatric Immunology
- Genetics
- Rheumatology
Background:
- Monogenic lupus lacks standardized diagnostic criteria due to its rarity and heterogeneity.
- Previous studies have not comprehensively analyzed diverse pathogenic mechanisms in monogenic lupus.
Purpose of the Study:
- To retrospectively summarize clinical characteristics, genotypes, and treatments of pediatric monogenic lupus patients.
- To develop and evaluate distinct diagnostic models based on various pathogenic pathways for monogenic lupus.
- To improve early identification and diagnosis of monogenic lupus in children.
Main Methods:
- Retrospective analysis of 36 pediatric patients with monogenic lupus and 16 different gene mutations.
- Univariate analysis of pathogenic pathways to identify significant risk factors.
- Application of least absolute shrinkage and selection operator (LASSO) and logistic regression for model construction and evaluation.
Main Results:
- Identified specific risk factors for monogenic lupus in male children under 8.46 years with a family history.
- Characterized distinct clinical presentations associated with Type-I-interferon disorders, immune tolerance pathway defects, and other pathways.
- Proposed optimal diagnostic models for different pathogenic pathways, demonstrating good discrimination and calibration.
Conclusions:
- Increased vigilance for monogenic lupus is warranted in specific pediatric populations.
- Pathway-specific diagnostic models can significantly aid in the early and accurate diagnosis of monogenic lupus in children.
- This research provides a framework for improved diagnostic strategies for rare monogenic autoimmune diseases.

