Interplay between genetics and epigenetics in osteoarthritis

Abstract

Research into the molecular genetics of osteoarthritis (OA) has been substantially bolstered in the past few years by the implementation of powerful genome-wide scans that have revealed a large number of novel risk loci associated with the disease. This refreshing wave of discovery has occurred concurrently with epigenetic studies of joint tissues that have examined DNA methylation, histone modifications and regulatory RNAs. These epigenetic analyses have involved investigations of joint development, homeostasis and disease and have used both human samples and animal models. What has become apparent from a comparison of these two complementary approaches is that many OA genetic risk signals interact with, map to or correlate with epigenetic mediators. This discovery implies that epigenetic mechanisms, and their effect on gene expression, are a major conduit through which OA genetic risk polymorphisms exert their functional effects. This observation is particularly exciting as it provides mechanistic insight into OA susceptibility. Furthermore, this knowledge reveals avenues for attenuating the negative effect of risk-conferring alleles by exposing the epigenome as an exploitable target for therapeutic intervention in OA.

Key points

  • Genome-wide association studies have uncovered a large number of novel osteoarthritis (OA) genetic risk loci in the past decade.

  • The vast majority of these risk loci map to non-coding regions of the genome and are predicted to increase disease risk by modulating the expression of target genes.

  • Many of these risk loci map close to or correlate with epigenetic mediators.

  • Epigenetic features and mediators therefore represent a mechanistic link between OA genetic risk factors and the onset or progression of disease.

  • Emerging genomic technologies, including assay for transposase-accessible chromatin using sequencing (ATAC-seq), genome editing and single-cell analyses, are starting to facilitate the interpretation of these epigenetic effects in OA.

  • Epigenetic features are amenable to modulation and, as such, are potential therapeutic targets.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Proposed mechanism of RUNX2 regulation by an OA-associated mQTL.
Fig. 2: Histone modifiers involved in cartilage development and homeostasis.
Fig. 3: Interactions between SOX9, ROCR, miR-140 and RUNX2 during chondrogenesis and articular cartilage homeostasis.
Fig. 4: The CRISPR–Cas9 system: repurposing for epigenome modulation.

References

  1. 1.

    Styrkarsdottir, U. et al. Whole-genome sequencing identifies rare genotypes in COMP and CHADL associated with high risk of hip osteoarthritis. Nat. Genet. 49, 801–805 (2017).

  2. 2.

    Zengini, E. et al. Genome-wide analyses using UK Biobank data provide insights into the genetic architecture of osteoarthritis. Nat. Genet. 50, 549–558 (2018).

  3. 3.

    Styrkarsdottir, U. et al. Meta-analysis of Icelandic and UK data sets identifies missense variants in SMO, IL11, COL11A1 and 13 more new loci associated with osteoarthritis. Nat. Genet. 50, 1681–1687 (2018).

  4. 4.

    Tachmazidou, I. et al. Identification of new therapeutic targets for osteoarthritis through genome-wide analyses of UK Biobank data. Nat. Genet. 51, 230–236 (2019).

  5. 5.

    Styrkarsdottir, U. et al. GWAS of bone size yields twelve loci that also affect height, BMD, osteoarthritis or fractures. Nat. Commun. 10, 2054 (2019).

  6. 6.

    Gallagher, M. D. & Chen-Plotkin, A. S. The post-GWAS era: from association to function. Am. J. Hum. Genet. 102, 717–730 (2018).

  7. 7.

    den Hollander, W. et al. Annotating transcriptional effects of genetic variants in disease-relevant tissue: transcriptome-wide allelic imbalance in osteoarthritic cartilage. Arthritis Rheumatol. 71, 561–570 (2019).

  8. 8.

    Styrkarsdottir, U. et al. Severe osteoarthritis of the hand associates with common variants within the ALDH1A2 gene and with rare variants at 1p31. Nat. Genet. 46, 498–502 (2014).

  9. 9.

    Shepherd, C. et al. Functional characterization of the osteoarthritis genetic risk residing at ALDH1A2 identifies rs12915901 as a key target variant. Arthritis Rheumatol. 70, 1577–1587 (2018).

  10. 10.

    den Hollander, W. et al. Genome-wide association and functional studies identify a role for matrix Gla protein in osteoarthritis of the hand. Ann. Rheum. Dis. 76, 2046–2053 (2017).

  11. 11.

    Shepherd, C., Reese, A. E., Reynard, L. N. & Loughlin, J. Expression analysis of the osteoarthritis genetic susceptibility mapping to the matrix Gla protein gene MGP. Arthritis Res. Ther. 21, 149 (2019).

  12. 12.

    Rice, S. J. et al. Prioritization of PLEC and GRINA as osteoarthritis risk genes through the identification and characterization of novel methylation quantitative trait loci. Arthritis Rheumatol. 71, 1285–1296 (2019).

  13. 13.

    Allis, C. D. & Jenuwein, T. The molecular hallmarks of epigenetic control. Nat. Rev. Genet. 17, 487–500 (2016).

  14. 14.

    Simon, T. C. & Jeffries, M. A. The epigenomic landscape in osteoarthritis. Curr. Rheumatol. Rep. 19, 30 (2017).

  15. 15.

    van Meurs, J. B., Boer, C. G., Lopez-Delgado, L. & Riancho, J. A. Role of epigenomics in bone and cartilage disease. J. Bone Miner. Res. 34, 215–230 (2019).

  16. 16.

    Pitsillides, A. A. & Beier, F. Cartilage biology in osteoarthritis–lessons from developmental biology. Nat. Rev. Rheumatol. 7, 654–663 (2011).

  17. 17.

    Sun, M. M. & Beier, F. Chondrocyte hypertrophy in skeletal development, growth, and disease. Birth Defects Res. C. Embryo Today 102, 74–82 (2014).

  18. 18.

    Miranda-Duarte, A. DNA methylation in osteoarthritis: current status and therapeutic implications. Open Rheumatol. J. 12, 37–49 (2018).

  19. 19.

    Rushton, M. D. et al. Characterization of the cartilage DNA methylome in hip and knee osteoarthritis. Arthritis Rheumatol. 66, 2450–2460 (2014).

  20. 20.

    den Hollander, W. et al. Knee and hip articular cartilage have distinct epigenomic landscapes: implications for future cartilage regeneration approaches. Ann. Rheum. Dis. 73, 2208–2212 (2014).

  21. 21.

    Moazedi-Fuerst, F. C. et al. Epigenetic differences in human cartilage between mild and severe OA. J. Orthop. Res. 32, 1636–1645 (2014).

  22. 22.

    Shen, J. et al. DNA methyltransferase 3b regulates articular cartilage homeostasis by altering metabolism. JCI Insight 2, 93612 (2017).

  23. 23.

    Taylor, S. E., Smeriglio, P., Dhulipala, L., Rath, M. & Bhutani, N. A global increase in 5-hydroxymethylcytosine levels marks osteoarthritic chondrocytes. Arthritis Rheumatol. 66, 90–100 (2014).

  24. 24.

    Taylor, S. E., Li, Y. H., Wong, W. H. & Bhutani, N. Genome-wide mapping of DNA hydroxymethylation in osteoarthritic chondrocytes. Arthritis Rheumatol. 67, 2129–2140 (2015).

  25. 25.

    Taylor, S. E. et al. Stable 5-hydroxymethylcytosine (5hmC) acquisition marks gene activation during chondrogenic differentiation. J. Bone. Miner. Res. 31, 524–534 (2015).

  26. 26.

    Bannister, A. J. & Kouzarides, T. Regulation of chromatin by histone modifications. Cell Res. 21, 381–395 (2011).

  27. 27.

    Ferguson, G. B. et al. Mapping molecular landmarks of human skeletal ontogeny and pluripotent stem cell-derived articular chondrocytes. Nat. Commun. 9, 3634 (2018).

  28. 28.

    Jęśko, H. & Strosznajder, R. P. Sirtuins and their interactions with transcription factors and poly(ADP-ribose) polymerases. Folia Neuropathol. 54, 212–233 (2016).

  29. 29.

    Seto, E. & Yoshida, M. Erasers of histone acetylation: the histone deacetylase enzymes. Cold Spring Harb. Perspect. Biol. 6, a018713 (2014).

  30. 30.

    Feigenson, M. et al. Histone deacetylase 3 deletion in mesenchymal progenitor cells hinders long bone development. J. Bone Min. Res. 32, 2453–2465 (2017).

  31. 31.

    Carpio, L. R. et al. Histone deacetylase 3 supports endochondral bone formation by controlling cytokine signaling and matrix remodeling. Sci. Signal. 9, ra79 (2016).

  32. 32.

    Bradley, E. W., Carpio, L. R. & Westendorf, J. J. Histone deacetylase 3 suppression increases PH domain and leucine-rich repeat phosphatase (Phlpp)1 expression in chondrocytes to suppress Akt signaling and matrix secretion. J. Biol. Chem. 288, 9572–9582 (2013).

  33. 33.

    Nishimori, S. et al. PTHrP targets HDAC4 and HDAC5 to repress chondrocyte hypertrophy. JCI Insight 4, 97903 (2019).

  34. 34.

    Vega, R. B. et al. Histone deacetylase 4 controls chondrocyte hypertrophy during skeletogenesis. Cell 119, 555–566 (2004).

  35. 35.

    Bradley, E. W., Carpio, L. R., Olson, E. N. & Westendorf, J. J. Histone deacetylase 7 (Hdac7) suppresses chondrocyte proliferation and β-catenin activity during endochondral ossification. J. Biol. Chem. 290, 118–126 (2015).

  36. 36.

    Cao, K. et al. Decreased histone deacetylase 4 is associated with human osteoarthritis cartilage degeneration by releasing histone deacetylase 4 inhibition of runt-related transcription factor-2 and increasing osteoarthritis-related genes: a novel mechanism of human osteoarthritis cartilage degeneration. Arthritis Res. Ther. 16, 491 (2014).

  37. 37.

    Culley, K. L. et al. Class I histone deacetylase inhibition modulates metalloproteinase expression and blocks cytokine-induced cartilage degradation. Arthritis Rheum. 65, 1822–1830 (2013).

  38. 38.

    Khan, N. M. & Haqqi, T. M. Epigenetics in osteoarthritis: potential of HDAC inhibitors as therapeutics. Pharmacol. Res. 128, 73–79 (2017).

  39. 39.

    Gabay, O. et al. Sirtuin 1 enzymatic activity is required for cartilage homeostasis in vivo in a mouse model. Arthritis Rheum. 65, 159–166 (2013).

  40. 40.

    Gabay, O. et al. Increased apoptotic chondrocytes in articular cartilage from adult heterozygous SirT1 mice. Ann. Rheum. Dis. 71, 613–616 (2012).

  41. 41.

    Gabay, O. et al. Sirt1-deficient mice exhibit an altered cartilage phenotype. Joint Bone Spine 80, 613–620 (2013).

  42. 42.

    Wang, Y., Zhao, X., Lotz, M., Terkeltaub, R. & Liu-Bryan, R. Mitochondrial biogenesis is impaired in osteoarthritis chondrocytes but reversible via peroxisome proliferator-activated receptor γ coactivator 1α. Arthritis Rheumatol. 67, 2141–2153 (2015).

  43. 43.

    Fu, Y. et al. Aging promotes SIRT3-dependent cartilage SOD2 acetylation and osteoarthritis. Arthritis Rheumatol. 68, 1887–1898 (2016).

  44. 44.

    Piao, J. et al. Sirt6 regulates postnatal growth plate differentiation and proliferation via Ihh signalling. Sci. Rep. 3, 3022 (2013).

  45. 45.

    Wu, Y. et al. Overexpression of Sirtuin 6 suppresses cellular senescence and NF-κB mediated inflammatory responses in osteoarthritis development. Sci. Rep. 5, 17602 (2015).

  46. 46.

    Nagai, K. et al. Depletion of SIRT6 causes cellular senescence, DNA damage, and telomere dysfunction in human chondrocytes. Osteoarthr. Cartil. 23, 1412–1420 (2015).

  47. 47.

    Castaño Betancourt, M. C. et al. Genome-wide association and functional studies identify the DOT1L gene to be involved in cartilage thickness and hip osteoarthritis. Proc. Natl Acad. Sci. USA 109, 8218–8223 (2012).

  48. 48.

    Monteagudo, S. et al. DOT1L safeguards cartilage homeostasis and protects against osteoarthritis. Nat. Commun. 8, 15889 (2017).

  49. 49.

    Cornelis, F. M. et al. Increased susceptibility to develop spontaneous and post-traumatic osteoarthritis in Dot1l-deficient mice. Osteoarthr. Cartil. 27, 513–525 (2019).

  50. 50.

    Yang, L. et al. ESET histone methyltransferase is essential to hypertrophic differentiation of growth plate chondrocytes and formation of epiphyseal plates. Dev. Biol. 380, 99–110 (2013).

  51. 51.

    Lui, J. C. et al. EZH1 and EZH2 promote skeletal growth by repressing inhibitors of chondrocyte proliferation and hypertrophy. Nat. Commun. 7, 13685 (2016).

  52. 52.

    Chen, L. et al. The inhibition of EZH2 ameliorates osteoarthritis development through the Wnt/β-catenin pathway. Sci. Rep. 6, 29176 (2016).

  53. 53.

    Zhang, F. et al. JMJD3 promotes chondrocyte proliferation and hypertrophy during endochondral bone formation in mice. J. Mol. Cell Biol. 7, 23–34 (2015).

  54. 54.

    Dai, J. et al. Kdm6b regulates cartilage development and homeostasis through anabolic metabolism. Ann. Rheum. Dis. 76, 1295–1303 (2017).

  55. 55.

    Endisha, H., Rockel, J., Jurisica, I. & Kapoor, M. The complex landscape of microRNAs in articular cartilage: biology, pathology, and therapeutic targets. JCI Insight 3, 121630 (2018).

  56. 56.

    Malemud, C. J. MicroRNAs and osteoarthritis. Cells 7, E92 (2018).

  57. 57.

    Trachana, V., Ntoumou, E., Anastasopoulou, L. & Tsezou, A. Studying microRNAs in osteoarthritis: critical overview of different analytical approaches. Mech. Ageing Dev. 171, 15–23 (2018).

  58. 58.

    Ajekigbe, B. et al. Identification of long non-coding RNAs expressed in knee and hip osteoarthritic cartilage. Osteoarthr. Cartil. 27, 694–702 (2019).

  59. 59.

    Xiang, S., Li, Z., Bian, Y. & Weng, X. Identification of changed expression of mRNAs and lncRNAs in osteoarthritic synovium by RNA-sequencing. Gene 685, 55–61 (2019).

  60. 60.

    Hu, J. et al. Long non-coding RNA HOTAIR promotes osteoarthritis progression via miR-17-5p/FUT2/β-catenin axis. Cell Death Dis. 9, 711 (2018).

  61. 61.

    Carlson, H. L. et al. LncRNA-HIT functions as an epigenetic regulator of chondrogenesis through its recruitment of p100/CBP complexes. PLoS Genet. 11, e1005680 (2015).

  62. 62.

    Barter, M. J. et al. The long non-coding RNA ROCR contributes to SOX9 expression and chondrogenic differentiation of human mesenchymal stem cells. Development 144, 4510–4521 (2017).

  63. 63.

    Rowley, M. J. & Corces, V. G. Organizational principles of 3D genome architecture. Nat. Rev. Genet. 19, 789–800 (2018).

  64. 64.

    Bompadre, O. & Andrey, G. Chromatin topology in development and disease. Curr. Opin. Genet. Dev. 55, 32–38 (2019).

  65. 65.

    Sivakumar, A., de Las Heras, J. I. & Schirmer, E. C. Spatial genome organization: from development to disease. Front. Cell Dev. Biol. 7, 18 (2019).

  66. 66.

    Soshnikova, N., Montavon, T., Leleu, M., Galjart, N. & Duboule, D. Functional analysis of CTCF during mammalian limb development. Dev. Cell 19, 819–830 (2010).

  67. 67.

    Lupiáñez, D. G. et al. Disruptions of topological chromatin domains cause pathogenic rewiring of gene-enhancer interactions. Cell 161, 1012–1025 (2015).

  68. 68.

    Kraft, K. et al. Serial genomic inversions induce tissue-specific architectural stripes, gene misexpression and congenital malformations. Nat. Cell Biol. 21, 305–310 (2019).

  69. 69.

    Hannon, E. et al. Leveraging DNA-methylation quantitative trait loci to characterise the relationship between methylomic variation, gene expression, and complex traits. Am. J. Hum. Genet. 103, 654–665 (2018).

  70. 70.

    Rushton, M. D. et al. Methylation quantitative trait locus analysis of osteoarthritis links epigenetics with genetic risk. Hum. Mol. Genet. 24, 7432–7444 (2015).

  71. 71.

    Rice, S. J. et al. Identification of a novel, methylation-dependent, RUNX2 regulatory region associated with osteoarthritis risk. Hum. Mol. Genet. 27, 3464–3474 (2018).

  72. 72.

    Rice, S. J., Cheung, K., Reynard, L. N. & Loughlin, J. Discovery and analysis of methylation quantitative trait loci (mQTLs) mapping to novel osteoarthritis genetic risk signals. Osteoarthr. Cartil. 27, 1545–1556 (2019).

  73. 73.

    Wang, X. et al. Regulation of MMP-13 expression by RUNX2 and FGF2 in osteoarthritic cartilage. Osteoarthr. Cartil. 12, 963–973 (2004).

  74. 74.

    van der Kraan, P. M. & van den Berg, W. B. Chondrocyte hypertrophy and osteoarthritis: role in initiation and progression of cartilage degeneration? Osteoarthr. Cartil. 20, 223–232 (2012).

  75. 75.

    Reynard, L. N., Bui, C., Syddall, C. M. & Loughlin, J. CpG methylation regulates allelic expression of GDF5 by modulating binding of SP1 and SP3 repressor proteins to the osteoarthritis SNP rs143383. Hum. Genet. 133, 1059–1073 (2014).

  76. 76.

    Smith, E. & Shilatifard, A. Enhancer biology and enhanceropathies. Nat. Struct. Mol. Biol. 21, 210–219 (2014).

  77. 77.

    Solomon, O. et al. Comparison of DNA methylation measured by Illumina 450K and EPIC BeadChips in blood of newborns and 14-year-old children. Epigenetics 13, 655–664 (2018).

  78. 78.

    Evangelou, E. et al. A meta-analysis of genome-wide association studies identifies novel variants associated with osteoarthritis of the hip. Ann. Rheum. Dis. 73, 2130–2136 (2014).

  79. 79.

    Castaño Betancourt, M. C. et al. Novel genetic variants for cartilage thickness and hip osteoarthritis. PLoS Genet. 12, e1006260 (2016).

  80. 80.

    arcOGEN Consortium & arcOGEN Collaborators. Identification of new susceptibility loci for osteoarthritis (arcOGEN); a genome-wide association study. Lancet 380, 815–823 (2012).

  81. 81.

    Gee, F., Rushton, M. D., Loughlin, J. & Reynard, L. N. Correlation of the osteoarthritis susceptibility variants that map to chromosome 20q13 with an expression quantitative trait locus operating on NCOA3 and with functional variation at the polymorphism rs116855380. Arthritis Rheumatol. 67, 2923–2932 (2015).

  82. 82.

    Nguyen, A. T. & Zhang, Y. The diverse functions of Dot1 and H3K79 methylation. Genes Dev. 25, 1345–1358 (2011).

  83. 83.

    Swingler, T. E. et al. The expression and function of microRNAs in chondrogenesis and osteoarthritis. Arthritis Rheum. 64, 1909–1919 (2012).

  84. 84.

    Barter, M. J. et al. Genome-wide microRNA and gene analysis of mesenchymal stem cell chondrogenesis identifies an essential role and multiple targets for miR-140-5p. Stem Cell 33, 3266–3280 (2015).

  85. 85.

    Gonzaga-Jauregui, C. et al. Mutations in COL27A1 cause Steel syndrome and suggest a founder mutation effect in the Puerto Rican population. Eur. J. Hum. Genet. 23, 342–346 (2015).

  86. 86.

    Kotabagi, S., Shah, H., Shukla, A. & Girisha, K. M. Second family provides further evidence for causation of Steel syndrome by biallelic mutations in COL27A1. Clin. Genet. 92, 323–326 (2017).

  87. 87.

    Plumb, D. A. et al. Collagen XXVII organises the pericellular matrix in the growth plate. PLoS One 6, e29422 (2011).

  88. 88.

    Sun, H. et al. MiR-455-3p inhibits the degenerate process of chondrogenic differentiation through modification of DNA methylation. Cell Death Dis. 9, 537 (2018).

  89. 89.

    Yoon, H. J. et al. NF-AT5 is a critical regulator of inflammatory arthritis. Arthritis Rheum. 63, 1843–1852 (2011).

  90. 90.

    Yamashita, S. et al. L-Sox5 and Sox6 proteins enhance chondrogenic miR-140 microRNA expression by strengthening dimeric Sox9 activity. J. Biol. Chem. 287, 22206–22215 (2012).

  91. 91.

    Zou, W. et al. The E3 ubiquitin ligase Wwp2 regulates craniofacial development through mono-ubiquitylation of Goosecoid. Nat. Cell Biol. 13, 59–65 (2011).

  92. 92.

    Li, H. et al. WWP2 is a physiological ubiquitin ligase for phosphatase and tensin homolog (PTEN) in mice. J. Biol. Chem. 293, 8886–8899 (2018).

  93. 93.

    Yang, Y. et al. E3 ligase WWP2 negatively regulates TLR3-mediated innate immune response by targeting TRIF for ubiquitination and degradation. Proc. Natl Acad. Sci. USA 110, 5115–5120 (2013).

  94. 94.

    Inui, M. et al. Dissecting the roles of miR-140 and its host gene. Nat. Cell Biol. 20, 516–518 (2018).

  95. 95.

    Miyaki, S. et al. MicroRNA-140 plays dual roles in both cartilage development and homeostasis. Genes Dev. 24, 1173–1185 (2010).

  96. 96.

    Grigelioniene, G. et al. Gain-of-function mutation of microRNA-140 in human skeletal dysplasia. Nat. Med. 25, 583–590 (2019).

  97. 97.

    Mokuda, S. et al. Wwp2 maintains cartilage homeostasis through regulation of Adamts5. Nat. Commun. 10, 2429 (2019).

  98. 98.

    Bi, W., Deng, J. M., Zhang, Z., Behringer, R. R. & de Crombrugghe, B. Sox9 is required for cartilage formation. Nat. Genet. 22, 85–89 (1999).

  99. 99.

    Yao, B. et al. The SOX9 upstream region prone to chromosomal aberrations causing campomelic dysplasia contains multiple cartilage enhancers. Nucleic Acids Res. 43, 5394–5408 (2015).

  100. 100.

    Baird, D. A. et al. Identification of novel loci associated with hip shape: a meta-analysis of genomewide association studies. J. Bone Miner. Res. 34, 241–251 (2019).

  101. 101.

    Tuddenham, L. et al. The cartilage specific microRNA-140 targets histone deacetylase 4 in mouse cells. FEBS Lett. 580, 4214–4217 (2006).

  102. 102.

    Papaioannou, G. et al. MicroRNA-140 provides robustness to the regulation of hypertrophic chondrocyte differentiation by the PTHrP-HDAC4 pathway. J. Bone Miner. Res. 30, 1044–1052 (2015).

  103. 103.

    Miyaki, S. et al. MicroRNA-140 is expressed in differentiated human articular chondrocytes and modulates interleukin-1 responses. Arthritis Rheum. 60, 2723–2730 (2009).

  104. 104.

    Arroyo, J. D. et al. Argonaute2 complexes carry a population of circulating microRNAs independent of vesicles in human plasma. Proc. Natl Acad. Sci. USA 108, 5003–5008 (2011).

  105. 105.

    Kosaka, N., Iguchi, H. & Ochiya, T. Circulating microRNA in body fluid: a new potential biomarker for cancer diagnosis and prognosis. Cancer Sci. 101, 2087–2092 (2010).

  106. 106.

    Lanford, R. E. et al. Therapeutic silencing of microRNA-122 in primates with chronic hepatitis C virus infection. Science 327, 198–201 (2010).

  107. 107.

    Vickers, K. C., Palmisano, B. T., Shoucri, B. M., Shamburek, R. D. & Remaley, A. T. MicroRNAs are transported in plasma and delivered to recipient cells by high-density lipoproteins. Nat. Cell Biol. 13, 423–433 (2011).

  108. 108.

    Ntoumou, E. et al. Serum microRNA array analysis identifies miR-140-3p, miR-33b-3p and miR-671-3p as potential osteoarthritis biomarkers involved in metabolic processes. Clin. Epigenetics 9, 127 (2017).

  109. 109.

    Borgonio Cuadra, V. M., González-Huerta, N. C., Romero-Córdoba, S., Hidalgo-Miranda, A. & Miranda-Duarte, A. Altered expression of circulating microRNA in plasma of patients with primary osteoarthritis and in silico analysis of their pathways. PLoS One 9, e97690 (2014).

  110. 110.

    Beyer, C. et al. Signature of circulating microRNAs in osteoarthritis. Ann. Rheum. Dis. 74, e18 (2015).

  111. 111.

    Kong, R., Gao, J., Si, Y. & Zhao, D. Combination of circulating miR-19b-3p, miR-122-5p and miR-486-5p expressions correlates with risk and disease severity of knee osteoarthritis. Am. J. Transl Res. 9, 2852–2864 (2017).

  112. 112.

    Zhao, G. et al. Droplet digital PCR-based circulating microRNA detection serve as a promising diagnostic method for gastric cancer. BMC Cancer 18, 676 (2018).

  113. 113.

    Zhang, S. et al. Exosomes derived from human embryonic mesenchymal stem cells promote osteochondral regeneration. Osteoarthr. Cartil. 24, 2135–2140 (2016).

  114. 114.

    Tao, S. C. et al. Exosomes derived from miR-140-5p-overexpressing human synovial mesenchymal stem cells enhance cartilage tissue regeneration and prevent osteoarthritis of the knee in a rat model. Theranostics 7, 180–195 (2017).

  115. 115.

    Dunham, I. et al. An integrated encylopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).

  116. 116.

    Reynard, L. N. Analysis of genetics and DNA methylation in osteoarthritis: what have we learnt about the disease? Semin. Cell Dev. Biol. 62, 57–66 (2017).

  117. 117.

    Kundaje, A. et al. Integrative analysis of 111 reference human epigenomes. Nature 518, 317–330 (2015).

  118. 118.

    Herlofsen, S. R. et al. Genome-wide map of quantified epigenetic changes during in vitro chondrogenic differentiation of primary human mesenchymal stem cells. BMC Genomics 14, 105 (2013).

  119. 119.

    Liu, Y. et al. Chromatin accessibility landscape of articular knee cartilage reveals aberrant enhancer regulation in osteoarthritis. Sci. Rep. 8, 15499 (2018).

  120. 120.

    Hakim, O. & Misteli, T. SnapShot: chromosome conformation capture. Cell 148, 1068.e1–1068.e2 (2012).

  121. 121.

    Varela-Eirin, M. et al. Targeting of chondrocyte plasticity via connexin43 modulation attenuates cellular senescence and fosters a pro-regenerative environment in osteoarthritis. Cell Death Dis. 9, 1166 (2018).

  122. 122.

    Fu, L. et al. Up-regulation of FOXD1 by YAP alleviates senescence and osteoarthritis. PLoS Biol. 17, e3000201 (2019).

  123. 123.

    Ren, X. et al. Maintenance of nuclear homeostasis by CBX4 alleviates senescence and osteoarthritis. Cell Rep. 26, 3643–3656 (2019).

  124. 124.

    Thakore, P. I., Black, J. B., Hilton, I. B. & Gersbach, C. A. Editing the epigenome: technologies for programmable transcription and epigenetic modulation. Nat. Methods 13, 127–137 (2016).

  125. 125.

    Farhang, N. et al. CRISPR-based epigenome editing of cytokine receptors for the promotion of cell survival and tissue deposition in inflammatory environments. Tissue Eng. Part. A 23, 738–749 (2017).

  126. 126.

    Soul, J., Hardingham, T., Boot-Handford, R. & Schwartz, J. M. SkeletalVis: an exploration and meta-analysis data portal of cross-species skeletal transcriptomics data. Bioinformatics 35, 2283–2290 (2019).

  127. 127.

    Shema, E., Bernstein, B. E. & Buenrostro, J. D. Single-cell and single-molecule epigenomics to uncover genome regulation at unprecedented resolution. Nat. Genet. 51, 19–25 (2019).

  128. 128.

    Chan, C. K. et al. Identification of the human skeletal stem cell. Cell 175, 43–56 (2018).

  129. 129.

    Ji, Q. et al. Single-cell RNA-seq analysis reveals the progression of human osteoarthritis. Ann. Rheum. Dis. 78, 100–110 (2018).

  130. 130.

    Jiang, Y. & Tuan, R. S. Origin and function of cartilage stem/progenitor cells in osteoarthritis. Nat. Rev. Rheumatol. 11, 206–212 (2015).

  131. 131.

    Buenrostro, J. D. et al. Single-cell chromatin accessibility reveals principles of regulatory variation. Nature 523, 486–490 (2015).

  132. 132.

    Cusanovich, D. A. et al. Multiplex single cell profiling of chromatin accessibility by combinatorial cellular indexing. Science 348, 910–914 (2015).

  133. 133.

    Ståhl, P. L. et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science 353, 78–82 (2016).

  134. 134.

    Singh, P., Marcu, K. B., Goldring, M. B. & Otero, M. Phenotypic instability of chondrocytes in osteoarthritis: on a path to hypertrophy. Ann. N. Y. Acad. Sci. 1442, 17–34 (2019).

  135. 135.

    Aspden, R. M. & Saunders, F. R. Osteoarthritis as an organ disease: from the cradle to the grave. Eur. Cell Mater. 37, 74–87 (2019).

  136. 136.

    Nelson, A. E. et al. A machine learning approach to knee osteoarthritis phenotyping: data from the FNIH Biomarkers Consortium. Osteoarthr. Cartil. 27, 994–1001 (2019).

  137. 137.

    Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y. & Greenleaf, W. J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213–1218 (2013).

  138. 138.

    Lara-Astiaso, D. et al. Immunogenetics. Chromatin state dynamics during blood formation. Science 345, 943–949 (2014).

  139. 139.

    Corces, M. R. et al. The chromatin accessibility landscape of primary human cancers. Science 362, eaav1898 (2018).

  140. 140.

    Yoshida, H. et al. The cis-regulatory atlas of the mouse immune system. Cell 176, 897–912 (2019).

  141. 141.

    Ludwig, C. H. & Bintu, L. Mapping chromatin modifications at the single cell level. Development 146, dev170217 (2019).

Download references

Acknowledgements

S.J.R. and J.L. acknowledge research support from Versus Arthritis (grant 20771), the Medical Research Council and Versus Arthritis as part of the Centre for Integrated research into Musculoskeletal Ageing (CIMA, grant JXR 10641, MR/P020941/1 and MR/R502182/1), the Ruth and Lionel Jacobson Charitable Trust, the JGW Patterson Foundation and the Newcastle upon Tyne Hospitals NHS Charity. F.B. acknowledges research support from the Canadian Institutes of Health Research (CIHR; application number 332438). D.A.Y. acknowledges research support from the JGW Patterson Foundation and the Dunhill Medical Trust (grant R476/0516).

Author information

Affiliations

Authors

Contributions

The authors contributed equally to all aspects of the article.

Corresponding author

Correspondence to John Loughlin.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information

Nature Reviews Rheumatology thanks M. Goldring, J. Westendorf and I. Meulenbelt for their contribution to the peer review of this work.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related links

ENCODE: https://www.encodeproject.org/

GWAS Catalog: https://www.ebi.ac.uk/gwas/

LNCipedia: https://lncipedia.org

ROADMAP epigenomics project: http://www.roadmapepigenomics.org

SkeletalVis: http://phenome.manchester.ac.uk

The Osteoarthritis Initiative: https://nda.nih.gov/oai

WashU Epigenome Browser: https://epigenomegateway.wustl.edu

Glossary

Linkage disequilibrium

The non-random association of two alleles within a population. Alleles at multiple variants that are in linkage disequilibrium will frequently be inherited together and comprise haplotypes. Large regions of linkage disequilibrium, known as ‘LD blocks’, can occur when there is a lack of haplotype diversity.

Allelic expression imbalance

An imbalance in the relative amount of mRNA derived from each allele in a heterozygote individual, as measured by the use of a single-nucleotide polymorphism in the coding sequence or untranslated regions of a gene; any deviation from a 1:1 ratio (determined using DNA from the patient) implies that one allele is associated with a higher expression level than the other allele.

Chromatin immunoprecipitation sequencing

(ChIP-seq). A technique using antibodies and DNA sequencing to assess which proteins are binding to a DNA sequence, and/or which protein modifications are occurring, at particular points of the genome or genome wide; this technique can be performed on chromatin isolated from cell lines or cells from patients.

Enhancers

Short sequences of DNA (<1,500 bp) that can ‘activate’ gene expression when bound by transcription factors by enhancing the activity of the gene promoter through physical interactions in cis.

Silencers

A sequence of DNA that can repress the expression of a gene through the direct binding of proteins that reduce or block transcription, which predominantly occurs through inhibiting the assembly of transcriptional machinery at a gene promoter.

Methylation quantitative trait loci

(mQTLs). Loci at which there is a correlation between the level of DNA methylation at a CpG site and the genotype at a single nucleotide polymorphism (SNP); mQTL assays are typically performed on DNA derived from cells from patients and can target specific CpGs and SNPs or can analyse the whole genome as part of a genome-wide approach, such as with CpG and genotyping arrays.

Topologically associating domain

(TAD). Regions of the genome in which sequences of DNA can physically interact. Individual TADs are insulated by proteins such as CCCTC-binding factor (CTCF) and cohesin. These domains enable the regulation of target genes by their specific enhancers, while preventing the interaction of regulatory elements with genes outside the TAD.

Methylation and expression quantitative trait locus

(meQTL). A locus at which there is a correlation between the level of methylation at a CpG site and the expression of a gene, the latter being measured directly through quantitative reverse transcription PCR (qRT-PCR) or as part of a genome-wide approach, typically RNA sequencing.

Enhanceropathy

A pathology in which the underlying mechanism of disease involves aberrant function of gene enhancers. This pathology can be caused by altered chromatin state, DNA methylation or sequence variations within the enhancer region. Changes to the enhancer activity result in dysregulation of gene expression.

Gene desert

A region of the genome that is devoid of protein-coding genes. These regions have been linked to several vital regulatory functions and might contain many spatiotemporal enhancers of important genes involved in development, such as SOX9.

Droplet digital PCR

A refinement of the conventional PCR method that uses a water–oil emulsion droplet system. Unlike traditional PCR, where a sample is amplified in a single reaction, droplet digital PCR has the benefit of increased precision through mass sample partitioning; the nucleic acid samples are partitioned into thousands of nanolitre-sized droplets, and PCR amplification is carried out within each droplet, ensuring reliable measurements of the DNA sequence being amplified.

Spatial transcriptomics

A technique developed to quantify RNAs in cells without the need to isolate the cells or to homogenize the tissue, enabling investigators to discern spatial differences in gene expression in complex and heterogeneous tissues.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Rice, S.J., Beier, F., Young, D.A. et al. Interplay between genetics and epigenetics in osteoarthritis. Nat Rev Rheumatol 16, 268–281 (2020). https://doi.org/10.1038/s41584-020-0407-3

Download citation

Further reading