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Abstract Number: 0593

Genetic Risk Profiles Predict Clinical Heterogeneity in Systemic Lupus Erythematosus

Nina Oparina1, Sarah Reid1, Ahmne Sayadi1, Maija-Leena Eloranta1, Martina Frodlund2, Karoline Lerang3, Andreas Jönsen4, Øyvind Molberg3, Solbritt Rantapää-Dahlqvist5, Anna Rudin6, Chrisopher Sjöwall7, Anders Bengtsson8, Lars Rönnblom1 and Dag Leonard1, 1Department of Medical Sciences, Uppsala University, Uppsala, Sweden, 2Department of Biomedical and Clinical Sciences, Division of Inflammation and Infection/Rheumatology, Linköping University, Linköping, Linkoping, Sweden, 3Department of Rheumatology, Oslo University Hospital, Oslo, Norway, 4Department of Clinical Sciences, Lund University,, Lund, Sweden, 5Department of Public Health and Clinical Medicine/Rheumatology, Umeå University, Umeå, Sweden, 6Department of Rheumatology and Inflammation Research, Institute of Medicine, Sahlgrenska Academy of University of Gothenburg, Gothenburg, Sweden, 7Department of Biomedical and Clinical Sciences, Division of Inflammation and Infection/Rheumatology, Linköping University, Linköping, Sweden, 8Department of Clinical Sciences, Lund University, Lund, Sweden

Meeting: ACR Convergence 2025

Keywords: genetics, risk factors, Systemic lupus erythematosus (SLE)

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Session Information

Date: Sunday, October 26, 2025

Title: (0593–0640) Systemic Lupus Erythematosus – Diagnosis, Manifestations, & Outcomes Poster I

Session Type: Poster Session A

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

Background/Purpose: Systemic lupus erythematosus (SLE) is an autoimmune disease with diverse clinical manifestations. Genetic predisposition contributes significantly to its pathogenesis, and higher genetic load is linked to more severe disease1. This study aims to elucidate the role of genetic variation in shaping the clinical heterogeneity observed in SLE.

Methods: Scandinavian SLE patients meeting the 1997 ACR criteria were genotyped using Illumina’s Global Screening Array, with clinical data extracted from medical records. Participants were randomly assigned to a discovery (n=884) and a test (n=524) cohort. A weighted SLE polygenic risk score (SLE-PRS) was calculated using 138 established non-HLA SLE risk single nucleotide variants (SNVs) (GWAS-significant in European populations). Subphenotype-specific PRSs were constructed in the discovery cohort, by analysis of 4,088 SNVs previously associated with immune or inflammatory diseases. Validation in the test cohort was conducted using logistic regression comparing the top quartile to the remainder, adjusting for sex and age, with model performance evaluated via ROC curve analysis. Disease and pathway enrichment analyses were conducted using FUMA2 and Metascape3.

Results: The SLE-PRS was associated with nephritis (OR=1.4, p=1.1×10-5, AUC=0.60) and photosensitivity (OR=1.1, p=3.6×10-3, AUC=0.57), but not with other ACR-97 manifestations. Excluding SNVs not associated with specific SLE subphenotypes enhanced the predictive accuracy of the SLE-PRS, with improved performance for nephritis (OR=1.6, p=4.4×10-6, AUC=0.61) and serositis (OR=1.3, p=0.02, AUC=0.56).We next developed subphenotype-specific PRSs, each comprising an average of 34 SNVs. Of the total 307 SNVs, 26 were shared across multiple PRSs, with the largest overlap observed in the immunological disorder-PRS (9 shared SNVs). The nephritis-PRS contained the largest fraction of known SLE loci (23%). Several PRSs demonstrated predictive ability, including the malar rash-PRS (OR=1.3, p=7.1×10-5, AUC 0.66), nephritis-PRS (OR=1.4, p=4.6×10-12, AUC 0.70), and neurological disorder-PRS (OR=1.1, p=0.02, AUC 0.60). Enrichment analysis of SNV annotated genes showed significant association between multiple sclerosis and all PRSs, with the strongest association for neurological disease (p=1.17×10-11). Functional enrichment analysis showed strong association between photosensitivity and the Nuclear factor of activated T-cells (NFAT) pathway (p=7.8×10-12) and hematological manifestations with interleukine-27 signaling (p=2.5×10-6).

Conclusion: The results demonstrate that subphenotype-specific PRSs are selectively associated with distinct clinical manifestations of SLE, and that inclusion of non-SLE risk SNVs can enhance predictive power. The limited overlap of contributing SNVs across PRSs underscores the genetic heterogeneity of SLE. Functional enrichment analyses further reveal distinct biological pathways underlying different disease features, pointing to potential targets for personalized therapeutic strategies.References: 1. Reid S. et al. Ann Rheum Dis. (2019).2. Watanabe K. et al. Nat. Commun. (2017).3. Zhou Y. et al. Nat. Commun. (2019).


Disclosures: N. Oparina: None; S. Reid: None; A. Sayadi: None; M. Eloranta: None; M. Frodlund: None; K. Lerang: None; A. Jönsen: None; Ø. Molberg: None; S. Rantapää-Dahlqvist: None; A. Rudin: None; C. Sjöwall: Bristol-Myers Squibb(BMS), 3; A. Bengtsson: None; L. Rönnblom: AstraZeneca, 6, Biogen, 2; D. Leonard: None.

To cite this abstract in AMA style:

Oparina N, Reid S, Sayadi A, Eloranta M, Frodlund M, Lerang K, Jönsen A, Molberg Ø, Rantapää-Dahlqvist S, Rudin A, Sjöwall C, Bengtsson A, Rönnblom L, Leonard D. Genetic Risk Profiles Predict Clinical Heterogeneity in Systemic Lupus Erythematosus [abstract]. Arthritis Rheumatol. 2025; 77 (suppl 9). https://acrabstracts.org/abstract/genetic-risk-profiles-predict-clinical-heterogeneity-in-systemic-lupus-erythematosus/. Accessed .
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