Immuno Omics:Unravelling the Immune System’s Inner Workings

Immuno Omics:Unravelling the Immune System’s Inner Workings

Single cell analysis, CRISPR, glycomics, and other advanced technologies are making it possible to finally uncover the root causes of autoimmune diseases and possibly diagnose and treat them earlier. One of the most difficult questions in all of medical science today is “Why do immune cells turn against the body in the absence of infection or transplants?” That process is at the root of dozens of conditions and is why autoimmune diseases represent one of the largest unmet medical markets in the world.  The market for treating asthma alone is expected to reach more than $20 billion by 2024, according to Grand View Research. 

But now, new omic approaches are offering a way to shed more light on the immune system, what influences it, and how it proceeds from “well” to “diseased.”

Searching for the links between pathways and disease

One recent breakthrough study came from the Open Targets Initiative, a pioneering public-private collaboration aimed at the systematic identification and prioritization of drug targets to improve the success rate for drug discovery and development. The consortium is a pre-competitive partnership between pharmaceutical companies, not-for-profit research institutes, and the EMBL’s European Bioinformatics Institute (EMBL-EBI). 

“Complex diseases are a particular challenge,” explained Blagoje Soskic, Ph.D., of the Wellcome Sanger Instititue, the lead author on the most recent publication from the initiative: “Chromatin Activity at GWAS Loci Identifies T Cell States Driving Complex Immune Diseases.” That study appeared in Nature Genetics, in Sept. 2019. Studying complex conditions can require thousands of patients to get statistically meaningful results. Further, scientists are finding that it is not just the coding segments of the genome that matter. “Only about 2% of the genome codes for proteins. But the non-coding, or ‘junk,’ sections of the genome are full of regulatory DNA,” said Eddie Cano-Gamez, a researcher at the Wellcome Sanger Institute and co-author of the recent Open Targets paper. “These segments are not modifying the gene, they are changing how it is expressed.”

One of the things Open Targets aims to understand is which immune cell states are most important for autoimmune diseases. That will help drug developers home in on potential new drug targets for complex conditions such as asthma and irritable bowel syndrome (IBD). To achieve this, large-scale genomic experiments and public domain computational techniques are combined with traditional pharmaceutical R&D approaches to identify causal links between targets, pathways, and diseases. 

Earlier research established that thousands of genetic variants are more common in patients with immune disease than in healthy people. That creates the proverbial needle in a haystack problem of discovering which variants actually matter. Researchers have found these immune-disease-associated variants are enriched in active chromatin regions of T cells and macrophages. However, it is not known whether they function in specific cell states. Many are in poorly understood areas of the genome and are believed to be involved in regulating immune cell function. There is also a tremendous need to understand more about cytokines, which are the signaling proteins transmitted between immune cells during inflammation.  

In this latest study, the Open Targets team analyzed parts of the genome that were active in immune cells from healthy volunteers, then they compared them against all genetic variants implicated in different immune diseases. They also stimulated T cells and macrophages in the presence of more than a dozen cytokines and profiled active and open chromatin regions. In total, they studied 55 different cell states in order to better understand immune disease inflammation and the effects of the signaling chemicals in these cells. 

They found that T cell activation induced major chromatin remodeling. Meanwhile, the presence of cytokines “fine-tuned” the magnitude of those changes. To better measure these changes, the group developed a statistical method to account for even subtle shifts in the chromatin landscape that still identified single-nucleotide polymorphism (SNP) enrichment across cell states.   

Their research suggested immune-disease-associated variants have a greater effect in early rather than late activation of memory CD4 T cells. The researchers also revealed that one particular cell type and cell state—early activation of memory T cells—had the most active DNA across the same regions as the genetic variants implicated in immune diseases. This pointed towards the initial activation of these T cells being important in disease development.

Surprisingly, the research showed that the cytokines generally only had subtle effects on the DNA activity, and played a lesser role in most of the diseases studied. “What we have found is that a lot of these variants have a very small effect,” said Cano-Gamez. That means scientists need many more patients in each study to get firm answers on certain questions.  “We have to follow up with single-cell analyses,” he added, “because there are multiple cells in the immune system and more than one are involved in any process.”  

One ongoing project is a single cell map of how different T cells respond to cytokines. The researchers are also interested in using gene editing to further study immune cells. “We are particularly interested in seeing what happens if we eliminate certain non-coding cells,” said Cano-Gamez. “Does that make the cell more disease-like or more like a healthy cell.”

The impact of single-cell analysis 

One of the biggest breakthroughs for studying the immune system has been single-cell analysis. “By studying large numbers of individual immune cells, researchers have, amongst other things, discovered previously unknown cell types, discovered more about the interface between a fetus and the maternal immune system, and begun to understand the rules that underpin specific antigen recognition by T cells,” said Mike Stubbington, staff computational biologist at 10x Genomics.

Droplet-based microfluidic methods have permitted an ever-increasing scale of single-cell approaches. It is now possible to routinely study tens of thousands of cells in a single experiment and identify rare cell types that would otherwise not be seen. Furthermore, there are now approaches that make it possible to sequence, at high resolution, the full repertoire of antigen receptors present within T and B cells. “That allows us to draw conclusions about how individual cell types respond to an immune challenge,” Stubbington said. 

DNA barcoding can also be used to sequence a large pool of antigens of interest from single cells and ask which antigen receptors are able to bind them. “This will transform our understanding of a fundamental function of the immune system: how its various cells recognize ‘non-self’ proteins,” added Stubbington.

Since we still do not understand all of the cell types present in the immune system, a major application of single-cell methods currently  is ‘atlassing’ cells to discover novel types and gain more information about the ones that we already know. The Human Cell Atlas project has already generated a large amount of data from the immune system, as well as other organ systems in the human body.

With single-cell genomics methods, researchers will be able to answer many more of the field’s fundamental questions, including:

  • How do immune cells recognize non-self antigens?
  • What happens when immune cells mount a response? 
  • What happens in the immune system in response to specific diseases?
  • How does the immune system interact with cancer? How can we use this knowledge to improve cancer therapies?
  • How do all of the cells in the immune system interact with each other and with other cells in the body as part of a cellular ecosystem?

It’s also important to recognize that although most information about immune cells comes from blood samples, the immune system does not exist just as a set of cells suspended in blood. Immune cells also infiltrate almost all tissues of the body, including solid tumors, for example.  Researchers are seeking to understand how immune cells (and other cells they interact with) act within tissues. “New spatially-resolved methods will provide researchers with the tools to address this challenge,” said Stubbington. 10x, for example, offers the Visium Spatial Gene Expression Solution, which analyzes complete transcriptomes in intact tissue sections.

Adding CRISPR and more on top

CRISPR is also giving a boost to autoimmune disease studies. Researchers at the University of California, San Francisco (UCSF), for example, used CRISPR activation (CRISPRa) to study the ILRA (Interleukin 2 apha) protein, which signals T cells whether they should heighten or dampen an inflammatory response. If the signal is faulty, T cells will not suppress inflammation. That can lead to autoimmune disorders, such as Crohn’s disease and IBD.

CRISPRa uses a guide RNA to target a section of the genome, but rather than cutting  those sequences (as CRISPR typically does) it activates them to show their impact on gene expression. In 2017, Jacob Corn, Ph.D., professor of genome biology now at ETH Zurich, and Alexander Marson, M.D., Ph.D., at UCSF created 20,000 guide RNAs for use with CRISPRa. “We essentially performed 20,000 experiments in parallel to find all the sequences that turn on this gene,” said Marson, an assistant professor of microbiology and immunology, via email. Targeting some of the sequences with CRISPRa did increase IL2RA production, yielding a short list of locations that might be important for regulating the fate of T cells. By targeting the CRISPRa complex to thousands of different potential enhancer sites, they reasoned, they would be able to determine which had the ability to turn on a particular gene, even if that gene was far away from the enhancer on the chromosome.

“This is a fundamentally different way of looking at non-coding regulatory sequences,” Dimitre Simeonov, a Ph.D. student in Marson’s lab at UCSF and the study’s other lead author, said in a press release.

Yuriy Baglaenko, a postdoctoral researcher at Brigham and Women’s Hospital, is also using CRISPR-Cas9 for gene editing immune cells. According to a recent blog post, one of Baglaenko’s projects stemmed from his realization that while CRISPR has been used extensively to generically manipulate T cells, it has not been widely applied to extend understanding of B cells.  As a result, he developed a means of using CRISPR to genetically edit primary human B cells, which is  described in the June 2018 issue of  Journal of Immunological Methods. Working with primary B cells is more challenging than working with T cells, according to Baglaenko. In his study, he found that an important factor for achieving “good editing efficiency” in CRISPR  studies was to deliver the guide RNA and Cas9 into cells in the ribonucleoprotein format.

The Ultra-DD consortium is a group committed to defining and validating novel targets in autoimmune and inflammatory diseases using patient-cell derived assays.  The group has access to tissue and cells from patients with lupus, myositis, ankylosing spondylitis, dupuytren’s disease patients, and more, via hospitals in Oxford, U.K., and Stockholm. It is a partnership between clinicians, academic researchers, pharma, and disease foundations and sponsors the Open-Source Target Discovery Partnership, to identify and validate under-explored protein targets.

In a recent paper published in Nature Genetics in July, Ultra-DD members used a “genetics-led” approach to identify the drug target landscape of 30 immune-related traits. The researchers combined functional genomic and immune-related annotations with knowledge of network connectivity to maximize “the informativeness of genetics for target validation, defining the target prioritization landscape” for the traits under study. They then used a priority index (Pi) pipeline with inputs from genome-wide association study (GWAS) variants for specific immune traits. This genetics-led drug target prioritization approach identified current therapeutics, activity in high-throughput cellular screens (including L10000, CRISPR, mutagenesis, and patient-derived cell assays), and allowed prioritization of under-explored targets.   

Ultra-DD’s “priority index” is an open-access, scalable system aimed at accelerating early-stage drug target selection for immune-mediated disease.

Due to the complexity of unraveling autoimmune disease, it will likely take all of the above reference approaches and more to fully understand the workings of the immune system in AI diseases and eventually the identification of promising therapeutic targets. As these new technologies are knitted together, they will create avenues for even bolder research approaches and offer new promise for diagnosis and treatment of autoimmune disease.