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Abstract Number: 1279

Whole Blood Gene Expression Defined Subgroups of Treatment Naïve Children and Adolescents with Childhood-onset Systemic Lupus Erythematosus.

Reagan Reid1, Huayun Hou2, Isha Datar2, Daniela Dominguez3, Andrea Knight4, Deborah Levy5, Lawrence Ng6, Zhaoyu Ding2, Michael Wilson2, Lauren Erdman7, Eleanor Pullenayegum2 and Linda Hiraki5, 1The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada, 2SickKids Research Institute, Toronto, ON, Canada, 3The Hospital for Sick Children, Toronto, Canada, 4Hospital for Sick Children, Toronto, ON, Canada, 5The Hospital for Sick Children, Toronto, ON, Canada, 6The Hospital for Sick Children, Toronto, Canada, Toronto, ON, Canada, 7University of Cincinnati, Cincinnati, OH

Meeting: ACR Convergence 2025

Keywords: Cohort Study, Epidemiology, Gene Expression, Pediatric rheumatology, Systemic lupus erythematosus (SLE)

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Session Information

Date: Monday, October 27, 2025

Title: (1272–1305) Pediatric Rheumatology – Clinical Poster II

Session Type: Poster Session B

Session Time: 10:30AM-12:30PM

Background/Purpose: Childhood-onset systemic lupus erythematosus (cSLE) is a clinically and genetically heterogeneous disease. We aimed to define subgroups of new diagnosis patients based on treatment naive gene expression profiles. We then examined how subgroup membership related to gene pathways, demographic and clinical features.

Methods: Participants were diagnosed and followed in a tertiary care Lupus clinic and met SLE classification criteria. Clinical and laboratory data including disease activity and damage indices were prospectively collected and stored in a dedicated database. Participants were genotyped on a multi-ethnic array and ancestry was genetically inferred. Whole blood was collected prior to treatment initiation with glucocorticoids or other potent immunosuppressants, and whole blood transcriptome wide RNA-sequencing was completed. We identified distinct participant clusters based on gene expression profiles using K-means clustering. Clinical and demographic feature differences between clusters were assessed using ANOVA and Fishers exact test. We generated ranked genes lists based on expression profile for each cluster, by comparing each cluster relative to the others using gene set enrichment analysis (gseGO, clusterProfiler). To gain an understanding of the underlying activated/suppressed processes within each cluster we assessed Gene Ontology (GO) biological processes within each cluster.

Results: The cohort included 75 children and adolescents with cSLE with RNA-sequencing on treatment naïve whole blood samples. Initial K-means plots identified three clusters and one outlier which was excluded resulting in the final cohort. The group was 81% female with a median age at SLE diagnosis of 13.8 years (IQR: 12.1, 15.4).; full participant characteristics are presented in Table 1. We identified three clusters (Figure 1). Clusters differed significantly in proportion of individuals with lupus nephritis (LN) (Cluster 1= 25%, Cluster 2= 59%, Cluster 3= 40%, P= 0.03); the clinical and demographic composition of each cluster is summarized in Table 2. Cluster 1 was characterized by activation of protein synthesis (RPL10, RPL13, RPS14) and signaling pathways (GPR162, FCER1A, CSF1R), whereas cell cycle processes (CDC16, BCL6, RMI1) were supressed. Cluster 2 showed enrichment of ribosomal related pathways (UTP20, UTO4, MAK16) and chromosomal processes (BUB1, NCAPG, MYBL2) while suppressed pathways related to secretory granules (ATP8B4, ATP11A, CST3) and innate immune responses (P2RY1, PIK3CB, MAP1B). Cluster 3 showed up-regulation of secretory granules and vesicles (CD177, MMP8, LTF) while down-regulated pathways were related to ribosomal (MRPL20, RPS9, RPS3A) and RNA pathways (ABT1, RPP38, KARS1) and the adaptive immune response (TRAV41, TRAV27, TRGV8).

Conclusion: In a clinically heterogeneous, multiethnic cohort of patients with cSLE, treatment naïve whole blood RNAseq genome wide expression generated three discrete clusters of patients. LN was most prevalent in cluster 2 which was characterized by increased activation of ribosomal and chromosomal pathways. Next steps include examining cell specific gene expression pathways.

Supporting image 1Table 1 Patient Characteristics.

Supporting image 2Table 2 Clinical and demographic features across clusters.

P values were obtained from ANOVA for age cluster differences and Fishers exact test for sex, inferred ancestry, and lupus nephritis cluster differences.

Supporting image 3Figure 1 K-means Clusters.


Disclosures: R. Reid: None; H. Hou: None; I. Datar: None; D. Dominguez: None; A. Knight: Pfizer, 6; D. Levy: AbbVie/Abbott, 5, AstraZeneca, 5, Bristol-Myers Squibb(BMS), 5, Roche, 5; L. Ng: None; Z. Ding: None; M. Wilson: None; L. Erdman: None; E. Pullenayegum: None; L. Hiraki: Janssen, 2, 5.

To cite this abstract in AMA style:

Reid R, Hou H, Datar I, Dominguez D, Knight A, Levy D, Ng L, Ding Z, Wilson M, Erdman L, Pullenayegum E, Hiraki L. Whole Blood Gene Expression Defined Subgroups of Treatment Naïve Children and Adolescents with Childhood-onset Systemic Lupus Erythematosus. [abstract]. Arthritis Rheumatol. 2025; 77 (suppl 9). https://acrabstracts.org/abstract/whole-blood-gene-expression-defined-subgroups-of-treatment-naive-children-and-adolescents-with-childhood-onset-systemic-lupus-erythematosus/. Accessed .
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