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Patient ancestry significantly contributes to molecular heterogeneity of systemic lupus erythematosus
Michelle D. Catalina, … , Amrie C. Grammer, Peter E. Lipsky
Michelle D. Catalina, … , Amrie C. Grammer, Peter E. Lipsky
Published August 6, 2020
Citation Information: JCI Insight. 2020;5(15):e140380. https://doi.org/10.1172/jci.insight.140380.
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Research Article

Patient ancestry significantly contributes to molecular heterogeneity of systemic lupus erythematosus

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Abstract

Gene expression signatures can stratify patients with heterogeneous diseases, such as systemic lupus erythematosus (SLE), yet understanding the contributions of ancestral background to this heterogeneity is not well understood. We hypothesized that ancestry would significantly influence gene expression signatures and measured 34 gene modules in 1566 SLE patients of African ancestry (AA), European ancestry (EA), or Native American ancestry (NAA). Healthy subject ancestry-specific gene expression provided the transcriptomic background upon which the SLE patient signatures were built. Although standard therapy affected every gene signature and significantly increased myeloid cell signatures, logistic regression analysis determined that ancestral background significantly changed 23 of 34 gene signatures. Additionally, the strongest association to gene expression changes was found with autoantibodies, and this also had etiology in ancestry: the AA predisposition to have both RNP and dsDNA autoantibodies compared with EA predisposition to have only anti-dsDNA. A machine learning approach was used to determine a gene signature characteristic to distinguish AA SLE and was most influenced by genes characteristic of the perturbed B cell axis in AA SLE patients.

Authors

Michelle D. Catalina, Prathyusha Bachali, Anthony E. Yeo, Nicholas S. Geraci, Michelle A. Petri, Amrie C. Grammer, Peter E. Lipsky

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Figure 2

Gene expression differences in SLE patients are similar to ancestral gene expression differences in healthy controls.

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Gene expression differences in SLE patients are similar to ancestral gen...
(A) Limma DE analysis was carried out between HC AA and EA for 2 separate data sets (Supplemental Table 9). Increased (Up in AA) and decreased (Up in EA) transcripts were compared with 4 SLE cohorts of AA DE to EA. Overlap P values were all below 1 × 10–22 for OR above 1. (B) GSVA for the 34 cell and process modules was carried out on healthy AA and EA subjects from 2 separate data sets. Welch’s t test was used to determine significant differences between ancestral GSVA scores; the mean and CI for the 10 GSVA scores significantly different (P < 0.05) between ancestries are shown.

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