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Low-frequency and rare genetic variants associated with rheumatoid arthritis risk

Nature Reviews Rheumatology volume 20, pages 290–300 (2024)Cite this article

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Abstract

Rheumatoid arthritis (RA) has an estimated heritability of nearly 50%, which is particularly high in seropositive RA. HLA alleles account for a large proportion of this heritability, in addition to many common single-nucleotide polymorphisms with smaller individual effects. Low-frequency and rare variants, such as those captured by next-generation sequencing, can also have a large role in heritability in some individuals. Rare variant discovery has informed the development of drugs such as inhibitors of PCSK9 and Janus kinases. Some 34 low-frequency and rare variants are currently associated with RA risk. One variant (19:10352442G>C in TYK2) was identified in five separate studies, and might therefore represent a promising therapeutic target. Following a set of best practices in future studies, including studying diverse populations, using large sample sizes, validating RA and serostatus, replicating findings, adjusting for other variants and performing functional assessment, could help to ensure the relevance of identified variants. Exciting opportunities are now on the horizon for genetics in RA, including larger datasets and consortia, whole-genome sequencing and direct applications of findings in the management, and especially treatment, of RA.

Key points

  • The greatest contributors to RA heritability are the major histocompatibility complex (MHC) proteins, encoded by the human leukocyte antigen (HLA) region on chromosome 6.

  • Low-frequency and rare variants captured by next-generation sequencing can have large effects on both individual-level heritability and population-level drug discovery.

  • Thus far, 34 low-frequency and rare variants have been associated with RA, including variants in immune-related genes such as TYK2 that might represent therapeutic targets.

  • Best practice for identifying rare variants in RA includes studying diverse populations, including ≥3,000 affected individuals, validating RA, examining serostatus, replicating findings, adjusting for known variants and performing functional assessment.

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Fig. 1: Chromosomal location of the 32 genes with identified low-frequency and rare variants associated with RA.
Fig. 2: Detectable rare-variant effect size as a function of sample size and number of controls.

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Acknowledgements

This manuscript was supported by the Rheumatology Research Foundation Scientist Development Award (V.L.K.).

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  1. Division of Rheumatology, Mayo Clinic, Rochester, MN, USA

    Vanessa L. Kronzer

  2. Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Jeffrey A. Sparks & Soumya Raychaudhuri

  3. Center for Data Sciences, Brigham and Women’s Hospital, Boston, MA, USA

    Soumya Raychaudhuri

  4. Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA

    Soumya Raychaudhuri

  5. Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA

    James R. Cerhan

Authors
  1. Vanessa L. Kronzer
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  2. Jeffrey A. Sparks
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  3. Soumya Raychaudhuri
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  4. James R. Cerhan
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Contributions

V.L.K., J.A.S. & J.R.C. researched data for the article. All authors contributed substantially to discussion of the content. All authors wrote the article. All authors reviewed and/or edited the manuscript before submission.

Corresponding author

Correspondence to Vanessa L. Kronzer.

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Competing interests

J.A.S. reports consulting fees from AbbVie, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Gilead, Inova Diagnostics, Janssen, Optum and Pfizer. The remaining authors declare no competing interests.

Peer review

Peer review information

Nature Reviews Rheumatology thanks Mikael Benson, Saedis Saevarsdottir and the other, anonymous, reviewer for their contribution to the peer review of this work.

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Related links

ABC: https://github.com/broadinstitute/ABC-Enhancer-Gene-Prediction

ANNOVAR: https://annovar.openbioinformatics.org/en/latest/user-guide/download/

CADD: https://cadd.gs.washington.edu/

CAVA: https://www.rdm.ox.ac.uk/research/lunter-group/lunter-group/cava-clinical-annotation-of-variants

gnomAD: https://gnomad.broadinstitute.org/

GTEx: https://gtexportal.org/home/

MetaDome: https://stuart.radboudumc.nl/metadome/

Polyphen-2: http://genetics.bwh.harvard.edu/pph2/

ProteinPaint: https://proteinpaint.stjude.org/

REVEL: https://sites.google.com/site/revelgenomics/about

SCENT: https://github.com/immunogenomics/SCENT

SIFT: https://sift.bii.a-star.edu.sg/

Single-Nucleotide Polymorphism database: https://www.ncbi.nlm.nih.gov/snp/

SpliceAI: https://spliceailookup.broadinstitute.org/

Glossary

Allele

One of two or more alternative forms at the same location of a gene or intergenic region.

Common variants

Genetic variants with a minor allele frequency >5%.

Copy number variation

Variation owing to insertions and deletions of sequences >1,000 base pairs, with copies at least 90% identical.

Exome

The small fraction of the genome (1% in humans) that directly encodes proteins.

Functional annotation

The process of attaching biological information to genetic variants.

Gene-based tests

A statistical approach to genetic analysis that conserves power by combining both the strength and the number of multiple variant associations into one test.

Genome

The complete set of genetic material in any organism.

Genome-wide association study

A study to determine the association of genetic variants throughout the genome with phenotypic traits.

Germline variants

Variants in germ-cell DNA that are inherited at conception.

Heritability

The proportion of a phenotype attributable to genetic factors.

Indel

Insertion or deletion of base pairs from a genetic sequence.

Low-frequency variants

Genetic variants with minor-allele frequency 1–5%.

Minor allele frequency

The frequency of the second most common allele in a given population.

Missing heritability

The gap between predicted and observed heritability, which is observed across many phenotypes.

Next-generation sequencing

(also known as massive parallel sequencing). A group of technologies for DNA sequencing that sequence many reads in parallel.

Phenome-wide association study

A study design for examination of the association between a variant of interest and a large number of phenotypes.

Phenotype

An observable trait that is influenced by genetics and environment.

Rare variants

Genetic variants with minor-allele frequency <1%.

Sanger sequencing

Also known as ‘first-generation sequencing’. A method of DNA sequencing that uses chain-terminating dideoxyneucleotides to produce labelled fragments corresponding to a DNA template.

Single-nucleotide polymorphism

(SNP). A genetic substitution at a single base pair that occurs in at least 1% of the population.

Single-nucleotide variant

(SNV). A genetic substitution at a single base pair.

Somatic variants

Variants that occur in DNA after conception.

Structural variation

Large-scale genomic variation, usually involving >50 base pairs.

Targeted sequencing

DNA sequencing targeting only specific genes.

Transcriptome

The set of all RNA transcripts generated from the genome.

Ultra-rare variants

Genetic variants with very low minor-allele frequency, often defined as <0.1%.

Whole-exome sequencing

DNA sequencing of the full exome.

Whole-genome sequencing

DNA sequencing of the full genome.

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Kronzer, V.L., Sparks, J.A., Raychaudhuri, S. et al. Low-frequency and rare genetic variants associated with rheumatoid arthritis risk. Nat Rev Rheumatol 20, 290–300 (2024). https://doi.org/10.1038/s41584-024-01096-7

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