Session Type: Poster Session (Tuesday)
Session Time: 9:00AM-11:00AM
Background/Purpose: Systemic Lupus Erythematosus (SLE) is a complex autoimmune disease with both sex and ancestral bias. Gene expression analysis has revealed complex heterogeneity between SLE patients, making deconvolution of the data difficult and delineation of the impact of different disease drivers uncertain. We, therefore, sought to understand the individual contributions of ancestry, gender and medications to gene expression heterogeneity, as well as to determine the association of gene expression profiles with various SLE manifestations.
Methods: Bulk Differential Expression (DE) analysis and Gene Set Variation Analysis (GSVA) were carried out on 1903 SLE patients of African (AA), European (EA) and Native American (NAA) ancestry. Modules of genes defined by co-expression in patients and representing either functional or cell specific groups were used to determine the relationship between drugs, SLE manifestations and individual patient gene expression. Logistic regression analysis was used to understand the relative contribution of ancestry, drugs and SLE manifestations to gene expression signatures.
Results: Gene expression analysis between female disease-matched SLE patients of AA, EA, and NAA revealed thousands of DE transcripts between ancestries, but none within a single ancestry. AA, EA and NAA SLE patients had significantly different cellular contributions to gene expression and these differences were related to significantly different percentages of patients in each ancestry with specific signatures. GSVA showed an increase in plasma cells, B cells and T cells in the majority of AA patients and an increase in myeloid cells in most EA and NAA patients. Corticosteroids and immunosuppressives significantly changed gene expression and contributed to the disparate signatures between and within ancestries. Anti-dsDNA autoantibodies and low complement, but not other clinical features of SLE, were significantly associated with gene expression in AA, EA and NAA SLE patients. Despite the impact of medications, ancestry made a significant contribution to gene expression profiles. Notably, we found that differences between AA and EA SLE patients are similar to those between healthy people of these ancestries, and that there were fewer differences between males and females of the same ancestry, than between ancestries.
Conclusion: Combinations of different ancestries, specific medications and autoantibody production associate with gene expression profiles (Figure 1). Importantly, ancestry contributes unique features of gene expression, implying differences in the molecular basis of SLE in these populations. Understanding the contributions of the gene expression signature components may permit a better interpretation of the signatures and their relationship to disease status.
To cite this abstract in AMA style:Catalina M, Bachali P, Yeo A, Geraci N, Petri M, Grammer A, Lipsky P. Ancestry Influences the Gene Expression Profile in Systemic Lupus Erythematosus and Contributes to Transcriptomic Heterogeneity in Lupus Patients [abstract]. Arthritis Rheumatol. 2019; 71 (suppl 10). https://acrabstracts.org/abstract/ancestry-influences-the-gene-expression-profile-in-systemic-lupus-erythematosus-and-contributes-to-transcriptomic-heterogeneity-in-lupus-patients/. Accessed August 13, 2020.
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ACR Meeting Abstracts - https://acrabstracts.org/abstract/ancestry-influences-the-gene-expression-profile-in-systemic-lupus-erythematosus-and-contributes-to-transcriptomic-heterogeneity-in-lupus-patients/