The role that genetic variation plays in autoimmunity, at the cellular level, is not well understood. This is, in part, due to a lack of large amounts of single-cell expression data. Obtaining these data face challenges in the numbers of people and numbers of cells from each person.

Now, two groups performed single-cell RNA sequencing (scRNA-seq) of immune cells and combined the data with fine mapping of autoimmune disease–associated genetic variants.  Together, this provides a resource that allows the large-scale identification of genotype-phenotype interactions. The work, which brings together population genetics and scRNA-seq data, is a significant milestone in uncovering how genetics contribute to the risk of autoimmune disease at a cellular level.

These findings are published in two papers in Science: “Single-cell eQTL mapping identifies cell typespecific genetic control of autoimmune disease” and “Single-cell RNA-seq reveals cell type–specific molecular and genetic associations to lupus.

Each study investigated hundreds of individuals and more than one million immune cells.

One group studied healthy individuals of both European and Asian descent, as well as individuals diagnosed with systemic lupus erythematosus. The other performed a population-based study investigating how segregating alleles contributes to variation in immune function.

In the first study, the researchers presented scRNA-seq data from 1.27 million peripheral blood mononuclear cells (PMBCs) collected from 982 donors—the OneK1K cohort. They developed a framework for the classification of individual cells. They combined the scRNA-seq data with genotype data, to map the genetic effects on gene expression in each of 14 immune cell types. They were able to identify 26,597 independent cis–expression quantitative trait loci (eQTLs).

The new study links specific genes and immune cell types to an individual’s disease, including multiple sclerosis, rheumatoid arthritis, inflammatory bowel disease, type 1 diabetes, and Crohn’s disease. Integrating these data with autoimmune disease cohorts identifies causal effects for more than 160 loci. The discovery could help individuals find tailored treatments that work for them and guide the development of new drugs.

“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 1 diabetes, spondylitis, inflammatory bowel disease, and Crohn’s disease,” said Joseph Powell, PhD, director of the Garvan-Weizmann Centre for Cellular Genomics. “We were able to do this using single-cell sequencing, a new technology that allows us to detect subtle changes in individual cells.”

The findings showed that most of the genetic effects have an allelic effect on gene expression that is cell type–specific. The results were replicated in two independent cohorts—one of which comprises individuals with a different ancestry from the discovery cohort.

“Some autoimmune diseases can be notoriously difficult to treat,” said Powell. “Because of our immune system’s complexity, and how vastly it varies between individuals, we don’t currently have a good understanding of why a treatment works well in some people but not in others,” he said.

“Our data also provides a new avenue for narrowing down potential drug targets. The potential health and economic impacts of this research are enormous,” said Alex Hewitt, PhD, professor in ophthalmology at the Menzies Institute for Medical Research.

Specifically, using the top associated eQTL single-nucleotide polymorphism (eSNP) at each locus outside the major histocompatibility complex (MHC) region, the researchers identified 990 trans-acting effects, most of which were cell type–specific.

B cell [Ofir Shein-Lumbroso]
They showed how eQTLs have dynamic allelic effects in B cells that are transitioning from naïve to memory states. Their work highlights the importance of investigating cell state–specific effects that underlie immune cell function.

They further investigated how eQTLs affect the expression variation of essential immune genes in specific cell types and provided experimental support for established hypotheses of cellular mechanisms in complex autoimmune diseases.

“The greatest insight from this work will be identification of therapeutic targets and defining subpopulations of immune disease, which can then refine clinical trials to assess drug effectiveness,” Hewitt said.

The researchers say their data could lower the risks associated with developing new treatments. “Pharmaceutical companies may have hundreds of targets and have to make decisions about which they will take forward to Phase I clinical trials, knowing that 90% of potential drug candidates fail during clinical development,” said José Alquicira-Hernández, a PhD student in Powell’s group at the Garvan Institute of Medical Research. “Understanding which cell types are relevant for a particular disease is key for developing new drugs.”

The team is working on a study of Crohn’s disease in collaboration with St. George Hospital that will determine how a patient’s immune genotype affects their response to different treatments, and is looking to establish new trials in a range of autoimmune diseases.

In the second paper, the team focused on systemic lupus erythematosus (SLE). They used multiplexed scRNA-seq (mux-seq) to profile more than 1.2 million PBMCs from 162 SLE cases and 99 healthy controls of either Asian or European ancestry. In this large, multiethnic, cohort, the researchers noted that they “demonstrate mux-seq as a systematic approach to characterize cellular composition, identify cell type–specific transcriptomic signatures, and annotate genetic variants associated with SLE.”

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