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Ancestry-based differences in the immune phenotype are associated with lupus activity
Samantha Slight-Webb, … , Judith A. James, Joel M. Guthridge
Samantha Slight-Webb, … , Judith A. James, Joel M. Guthridge
Published August 22, 2023
Citation Information: JCI Insight. 2023;8(16):e169584. https://doi.org/10.1172/jci.insight.169584.
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Resource and Technical Advance Immunology

Ancestry-based differences in the immune phenotype are associated with lupus activity

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Abstract

Systemic lupus erythematosus (SLE) affects 1 in 537 Black women, which is >2-fold more than White women. Black patients develop the disease at a younger age, have more severe symptoms, and have a greater chance of early mortality. We used a multiomics approach to uncover ancestry-associated immune alterations in patients with SLE and healthy controls that may contribute biologically to disease disparities. Cell composition, signaling, epigenetics, and proteomics were evaluated by mass cytometry; droplet-based single-cell transcriptomics and proteomics; and bead-based multiplex soluble mediator levels in plasma. We observed altered whole blood frequencies and enhanced activity in CD8+ T cells, B cells, monocytes, and DCs in Black patients with more active disease. Epigenetic modifications in CD8+ T cells (H3K27ac) could distinguish disease activity level in Black patients and differentiate Black from White patient samples. TLR3/4/7/8/9-related gene expression was elevated in immune cells from Black patients with SLE, and TLR7/8/9 and IFN-α phospho-signaling and cytokine responses were heightened even in immune cells from healthy Black control patients compared with White individuals. TLR stimulation of healthy immune cells recapitulated the ancestry-associated SLE immunophenotypes. This multiomic resource defines ancestry-associated immune phenotypes that differ between Black and White patients with SLE, which may influence the course and severity of SLE and other diseases.

Authors

Samantha Slight-Webb, Kevin Thomas, Miles Smith, Catriona A. Wagner, Susan Macwana, Aleksandra Bylinska, Michele Donato, Mai Dvorak, Sarah E. Chang, Alex Kuo, Peggie Cheung, Laurynas Kalesinskas, Ananthakrishnan Ganesan, Denis Dermadi, Carla J. Guthridge, Wade DeJager, Christian Wright, Mariko H. Foecke, Joan T. Merrill, Eliza Chakravarty, Cristina Arriens, Holden T. Maecker, Purvesh Khatri, Paul J. Utz, Judith A. James, Joel M. Guthridge

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Figure 1

Overview of analysis workflow to catalog ancestry-associated differences in immune phenotypes.

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Overview of analysis workflow to catalog ancestry-associated differences...
A discovery cohort was used for a multiomic systems immunology analysis. Significant results were independently validated either by reusing publicly available data sets or by splitting individuals into 2 matched groups for replication (bold). First, 58 samples, including healthy controls, SLE INACT, and SLE ACT, who self-reported as White or Black, were matched by age, ancestry, and sex. (A) Whole blood was collected, left unstimulated or stimulated, and used for immunophenotyping by mass cytometry and signaling analysis by phospho-CyTOF. Similar data from an independently collected and analyzed set of samples, a larger combined analysis of 33 participants, were used to increase the power. (B) Plasma and supernatants collected after overnight stimulation of whole blood were used to assess 39 different soluble mediators using multiplex bead-based assays and ELISAs. (C) PBMCs were used for droplet-based scRNA-Seq and EpiTOF. For single-cell transcriptomics, PBMCs were washed, depleted of red blood cells and T cells using CD2 depletion to enrich for non–T cell populations, and stained with a 51-plex CITE-Seq panel for dual transcript and protein expression using the 10x Genomics 3′ single-cell droplet methods. These variables were utilized to delineate specific cell lineages, activation, and regulatory markers. (D) PBMCs from healthy controls with no autoimmune disease manifestations who self-reported as White or Black were stimulated for 7 days with IFN-α, TLR7/8, or TLR9 agonists, alone or in combination, to assess immune composition and antibody production by flow cytometry and ELISA, respectively. ANA, antinuclear antibody; CCP, cyclic citrullinated peptide; CSQ, connective tissue screening questionnaire; EpiTOF, CyTOF immune phenotyping with epigenetics; scRNA-Seq, sincle-cell RNA sequencing; MCP-1, monocyte chemoattractant protein-1; PHA, phytohemagglutinin; p-STAT, phosphorylated STAT; RF, rheumatoid factor; SCF, stem cell factor.

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