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  • Review Article
  • Published:

Genome editing to define the function of risk loci and variants in rheumatic disease

Nature Reviews Rheumatology volume 17, pages 462–474 (2021)Cite this article

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Abstract

Discoveries in human genetic studies have revolutionized our understanding of complex rheumatic and autoimmune diseases, including the identification of hundreds of genetic loci and single nucleotide polymorphisms that potentially predispose individuals to disease. However, in most cases, the exact disease-causing variants and their mechanisms of action remain unresolved. Functional follow-up of these findings is most challenging for genomic variants that are in non-coding genomic regions, where the large majority of common disease-associated variants are located, and/or that probably affect disease progression via cell type-specific gene regulation. To deliver on the therapeutic promise of human genetic studies, defining the mechanisms of action of these alleles is essential. Genome editing technology, such as CRISPR–Cas, has created a vast toolbox for targeted genetic and epigenetic modifications that presents unprecedented opportunities to decipher disease-causing loci, genes and variants in autoimmunity. In this Review, we discuss the past 5–10 years of progress in resolving the mechanisms underlying rheumatic disease-associated alleles, with an emphasis on how genomic editing techniques can enable targeted dissection and mechanistic studies of causal autoimmune risk variants.

Key points

  • Hundreds of autoimmune risk loci have been discovered in coding and non-coding regions of the genome; however, their function and the causal alleles functioning within these loci have been difficult to discern.

  • Advances in genomic editing have made it possible to quickly and effectively investigate autoimmune disease-associated loci and variants using a number of approaches in both cell lines and primary cells.

  • CRISPR–Cas genomic editing can be used to induce insertions and deletions, correct precise mutations and induce epigenetic changes to investigate loci and variants associated with rheumatic diseases.

  • CRISPR–Cas screening approaches are effective tools for whole-genome investigation of autoimmune disease-related genes and detailed resolution of autoimmune risk regions.

  • Resolving the heterogeneity of cell types in rheumatic disorders with unbiased single-cell technologies is critical to understanding the genetics of disease.

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Fig. 1: Studying the genetics of rheumatic diseases.
Fig. 2: Genomic editing to investigate regions of interest in rheumatic diseases.
Fig. 3: Genomic editing to investigate variants of interest in rheumatic disease.

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Acknowledgements

S.R. is supported by funding from the National Institutes of Health (UH2AR067677, U01 HG009379, 1R01AR063759). Y.B. and S.R. are funded by the Broad Institute through the Scientific Projects to Accelerate Research (SPARC) programme and an investigator-initiated grant from Pfizer. P.A.N. is funded by National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) awards 2R01 AR065538, R01 AR075906, R01 AR073201, P30 AR070253, R21 AR076630 and NHLBI award R21 HL150575; the Fundación Bechara; the Arbuckle Family Fund for Arthritis Research; and the Samara Jan Turkel Center. A.M. is funded by NIH awards DP3DK111914-01 and R01DK1199979 and the National Multiple Sclerosis Society. A.M. holds a Career Award for Medical Scientists from the Burroughs Wellcome Fund and received the Lloyd Old STAR career award from the Cancer Research Institute (CRI). The Marson lab has received funding from the Innovative Genomics Institute (IGI), the Parker Institute for Cancer Immunotherapy (PICI), the Chan Zuckerberg Biohub and the Northern California JDRF Center of Excellence.

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  1. Center for Data Sciences, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Yuriy Baglaenko, Dana Macfarlane & Soumya Raychaudhuri

  2. Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA

    Yuriy Baglaenko, Dana Macfarlane, Peter A. Nigrovic & Soumya Raychaudhuri

  3. Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA

    Yuriy Baglaenko & Soumya Raychaudhuri

  4. Gladstone Institutes, San Francisco, CA, USA

    Alexander Marson

  5. Department of Medicine, University of California, San Francisco, CA, USA

    Alexander Marson

  6. Department of Microbiology and Immunology, University of California, San Francisco, CA, USA

    Alexander Marson

  7. Innovative Genomics Institute, University of California, Berkeley, CA, USA

    Alexander Marson

  8. Rosalind Russell/Ephraim P. Engleman Rheumatology Research Center, University of California, San Francisco, San Francisco, CA, USA

    Alexander Marson

  9. Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA

    Alexander Marson

  10. Chan Zuckerberg Biohub, San Francisco, CA, USA

    Alexander Marson

  11. Division of Immunology, Boston Children’s Hospital, Department of Pediatrics, Harvard Medical School, Boston, MA, USA

    Peter A. Nigrovic

  12. Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA

    Soumya Raychaudhuri

  13. Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK

    Soumya Raychaudhuri

Authors
  1. Yuriy Baglaenko
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  2. Dana Macfarlane
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  3. Alexander Marson
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  4. Peter A. Nigrovic
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  5. Soumya Raychaudhuri
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Contributions

The authors contributed to all aspects of the article.

Corresponding author

Correspondence to Soumya Raychaudhuri.

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Competing interests

P.A.N. has been supported by investigator-initiated research grants from AbbVie, Bristol-Myers Squibb, Novartis, Pfizer, Sobi; consulting fees from Bristol-Myers Squibb (BMS), Cerecor, Miach Orthopedics, Novartis, Pfizer, Quench Bio, Sigilon, Simcere, Sobi, Exo Therapeutics and XBiotech; royalties from UpToDate Inc.; and salary support from the Childhood Arthritis and Rheumatology Research Alliance (CARRA). A.M. is a compensated co-founder, member of the boards of directors and a member of the scientific advisory boards of Spotlight Therapeutics and Arsenal Biosciences. A.M. was a compensated member of the scientific advisory board at PACT Pharma and was a compensated adviser to Juno Therapeutics and Trizell. A.M. owns stock in Arsenal Biosciences, Spotlight Therapeutics and PACT Pharma. A.M. has received honoraria from Merck and Vertex, a consulting fee from AlphaSights, and is an investor in and informal adviser to Offline Ventures. The Marson lab has received research support from Juno Therapeutics, Epinomics, Sanofi, GlaxoSmithKline, Gilead, and Anthem and reagents from Illumina. A.M. is an inventor on multiple inventions with the Whitehead Institute, UCSF and the Gladstone Institutes, including some that have been licensed. S.R. is a founder for Mestag, Inc, served in the past year as an adviser to Gilead, Biogen, Merck, Pfizer, Janssen and Abbvie. Y.B. and D.M. have no competing interests.

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Peer review information

Nature Reviews Rheumatology thanks S. Tripathi, D. Ewart and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Glossary

CUT&Tag

A technique that uses antibodies specific for DNA binding proteins to measure DNA regions bound by these proteins. The antibodies are tethered to a Tn5 transposase fusion protein and, following antibody-binding, activation of the transposase cleaves nearby DNA and generates fragment libraries for sequencing, the data of which are used to identify the bound regions.

CUT&RUN

Similar to CUT&Tag, this technique analyses DNA regions bound by specific proteins using targeted antibodies. Unlike with CUT&Tag, the antibody is tethered to a micrococcal nuclease, which fragments nearby DNA elements.

ATAC-seq

A technique used for assaying areas of open chromatin in the genome; the method relies on unguided Tn5 transposase-induced fragmentation of the genome.

IMPACT

A computational genome annotation strategy that identifies regulatory elements defined by cell-state-specific transcription factor binding profiles.

Massively parallel reporter assay

A technique used to identify regulatory regions of the genome in a high-throughput assay. Regions of interest are cloned into a minimal reporter with a unique barcode and a promoter to create a large pool of constructs. Constructs are expressed into cells and the RNA and DNA are sequenced to estimate the effects of each regulatory region on barcode gene expression, indicating regulatory capacity.

Fluorescent in situ hybridization

A technique that measures RNA expression by flow cytometry using hybridization and amplification of fluorescent RNA probes.

Single-cell RNA sequencing

An approach for measuring the expression of RNA in individual cells using droplet or plate-based technology.

Computational fine mapping

A process by which a trait-associated region from a genome-wide association study is further analysed to identify genetic variants that are likely to causally influence the trait, usually through the integration of additional epigenetic or genomic data.

Expression quantitative trait loci

Trait-associated regions that can explain a notable portion of the changes in expression of a gene.

Electromobility shift assays

A molecular biology technique that measures the interaction of DNA and proteins on a protein-binding gel.

Luciferase assays

A technique used to identify regions of the genome that can regulate gene expression. In these assays, the region of interest is cloned upstream or downstream of the gene encoding luciferase and the resultant plasmids are transfected into cells to measure the effect of the modification on luciferase expression.

Affinity precipitation assays

A technique that is similar to electromobility shift assays, with the exception that bound complexes are magnetically pulled down prior to examination on a protein-binding gel.

Droplet-based RNAseq

A single-cell RNA sequencing method that relies on droplet generation and encapsulation of individual cells.

Mass cytometry

A type of single-cell analysis that tags cells with antibodies conjugated to heavy metals to then analyse staining intensity by time-of-flight mass spectrometry.

HyPR-seq

A droplet-based targeted single-cell sequencing technique that involves hybridizing DNA probes to selected RNA to measure the expression of genes.

Directed evolution

A process of protein engineering that mimics biological evolution. A library of mutated genes is expressed in cell lines and a phenotype is selected; the process is repeated with new mutations and harsher selection conditions until a desired outcome is achieved.

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Baglaenko, Y., Macfarlane, D., Marson, A. et al. Genome editing to define the function of risk loci and variants in rheumatic disease. Nat Rev Rheumatol 17, 462–474 (2021). https://doi.org/10.1038/s41584-021-00637-8

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