With the help of single-cell RNA sequencing, a University of California, San Francisco-led team teased out some of the processes and regulatory pathways behind systemic lupus erythematosus (SLE), profiling shifts in blood cell composition and the expression of distinct blood cell types in more than 150 individuals with the heterogeneous autoimmune condition.
“Single-cell sequencing is transforming our understanding of complex tissues,” but its application to large population cohorts has been limited, co-senior and co-corresponding author Chun Jimmie Ye, a rheumatology, human genetics, epidemiology, and biostatistics researcher affiliated with UCSF, the Parker Institute for Cancer Immunotherapy, and Chan Zuckerberg Biohub, said in an email.
“Large sample sizes are particularly important for studying complex autoimmune diseases such as lupus,” Ye added, “where patients present a variety of symptoms and may respond very differently to current treatments.”
Past research has demonstrated that SLE is overrepresented in women, and in individuals with Asian, African, or Hispanic ancestry, the researchers noted in their study, published in Science on Thursday.
Using a method called “multiplexed scRNA-seq” (mux-seq), they assessed more than 1.2 million peripheral blood mononuclear cells (PBMC) isolated from 162 individuals with SLE and 99 unaffected controls, drawn from the California Lupus Epidemiology Study and the Immune Variation project.
“In a large ancestrally diverse cohort, we demonstrated the use of mux-seq as a systematic approach to characterize changes in cell type composition and cell type-specific gene expression in adult SLE,” the authors explained.
The single-cell transcriptomic approach was complemented by additional T-cell receptor sequencing, and array-based genotyping data, together with analyses of new single-cell ATAC-seq profiles on stimulated and unstimulated PBMCs from five healthy individuals.
“The integration of richer epigenetic and cellular phenotypes along with improvements to current transcriptomic workflows will undoubtedly improve molecular sub-phenotyping of SLE, the power to detect cell type-specific and cell context-specific molecular QTLs, and the resolution for annotating SLE associations,” the authors wrote.
The resulting dataset highlighted gene expression shifts found in specific cell types in the SLE samples, the team reported, while distinguishing between two molecular subtypes of SLE. In particular, the analyses suggested that participants’ ancestry influenced “both the composition and state of immune cells,” Ye noted, “which may explain the disparities in lupus susceptibility and severity.”
In monocyte white blood cells from the SLE cases, for example, the team saw higher-than-usual expression of genes stimulated by the type 1 interferon. SLE samples were also marked by a dip in naive CD4-positive T cell representation, but broader collections of cytotoxic CD8-positive T cells expressing GZMH granzyme genes.
Along with analyses suggesting that the cell type-specific expression features detected in the analyses can help to distinguish between individuals with or without SLE — and to narrow in on molecular subtypes within the condition — the researchers used expression quantitative trait locus analyses and other approaches to explore the potential mechanisms behind the genetic associations influencing autoimmunity and other SLE features across several cell types.
“As a foundational component of the Human Cell Atlas, a Chan Zuckerberg Initiative funded effort to systematically map cells in humans, this data is broadly available to researchers around the world as a reference for current and future studies,” Ye said.
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