Single-Cell RNA Sequencing Identifies Mechanisms Underlying Autoimmune Diseases

Two recently published studies were designed to help understand how gene expression patterns are cell-type and context specific and can explain observed variation in immune cell function among individuals. These studies also identified causal links between genome-wide analyses and expression quantitative trait loci, identifying potential mechanisms underlying autoimmune diseases.

To identify how implicated loci affect gene expression in immune cells from individuals from different populations, two research groups performed single-cell RNA sequencing of immune cells, with each study investigating hundreds of individuals and more than one million immune cells.

The studies examined both proximal (cis) and distal (trans) genetic variants affecting gene expression in 14 different immune cell types. One research group studied healthy individuals of both European and Asian descent, as well as individuals diagnosed with systemic lupus erythematosus. The other group performed a population-based study investigating how segregating alleles contribute to variation in immune function.

The studies capitalized on the Garvan Institute of Medical Research (Darlinghurst, Australia) OneK1K cohort, which consists of single-cell RNA sequencing (scRNA-seq) data from 1.27 million peripheral blood mononuclear cells (PMBCs) collected from 982 donors.

The investigators worked in the context of The Garvan-Weizmann Centre for Cellular Genomics Molecular Services, which provided state-of-the-art advanced single cell platforms. The Centre combines the expertise of the The Garvan Institute of Medical Research with that of the Weizmann Institute of Science (Rehovot, Israel). The research facility offered services in single cell Immuno-profiling, ATAC sequencing, and Multiomics (ATAC+RNA Sequencing), and its Flow Services component provided cytometry services as well as expert consultation in the field of cytometry.

Over the course of the work, the investigators developed a framework for the classification of individual cells, and by combining the scRNA-seq data with genotype data, they mapped the genetic effects on gene expression in each of 14 immune cell types and identified 26,597 independent cis–expression quantitative trait loci (eQTLs). They showed that most of these had an allelic effect on gene expression that was cell type–specific. These results replicated in two independent cohorts, one of which comprised individuals with a different ancestry to the discovery cohort. Over all loci, the discovery and replication cohorts had a concordance of allelic direction ranging from 72.2 to 98.1% across cell types. In addition, the investigators integrated genetic association data for seven common autoimmune diseases and identified significant enrichment of genetic effects operating in a cell type–specific manner.

“We analyzed the genomic profile of over one million cells from 1,000 people to identify a fingerprint linking genetic markers to diseases such as multiple sclerosis, rheumatoid arthritis, lupus, type I diabetes, spondylitis, inflammatory bowel disease, and Crohn’s disease,” said senior author Dr. Joseph Powell, director of the Garvan Institute of Medical Research. “We were able to do this using single cell sequencing, a new technology that allows us to detect subtle changes in individual cells. Some autoimmune diseases can be notoriously difficult to treat. Because of our immune system’s complexity, and how vastly it varies between individuals, we do not currently have a good understanding of why a treatment works well in some people but not in others. The greatest insight from this work will be identification of therapeutic targets and defining sub-populations of immune disease, which can then refine clinical trials to assess drug effectiveness.”

The studies were published in the April 8, 2022, online edition of the journal Science.

Related Links:
Garvan Institute of Medical Research 
Weizmann Institute of Science 

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