Abstract Introduction Osteoarthritis (OA) is a chronic musculoskeletal disease characterized by progressive loss of joint function. Historically, it has been characterized as a disease caused by mechanical trauma, so-called ‘wear and tear’. Over the past two decades, it has come to be understood as a complex systemic disorder involving gene-environmental interactions. Epigenetic changes have been increasingly implicated. Recent improvements in microarray and next-generation sequencing (NGS) technologies have allowed for ever more complex evaluations of epigenetic aberrations associated with the development and progression of OA. Methods A systematic review was conducted in the Pubmed database. We curated studies that presented the results of DNA methylation and noncoding RNA research in human OA and OA animal models since 1985. Results Herein, we discuss recent findings and methodological advancements in OA epigenetics, including a discussion of DNA methylation, including microarray and NGS studies, and noncoding RNAs. Beyond cartilage, we also highlight studies in subchondral bone and peripheral blood mononuclear cells, which highlight widespread and potentially clinically important alterations in epigenetic patterns seen in OA patients. Finally, we discuss epigenetic editing approaches in the context of OA. Conclusions Although a substantial body of literature has already been published in OA, much is still unknown. Future OA epigenetics studies will no doubt continue to broaden our understanding of underlying pathophysiology and perhaps offer novel diagnostics and/or treatments for human OA. Keywords: Osteoarthritis, Epigenetics, Literature review, DNA methylation, Noncoding RNA 1. Introduction Osteoarthritis (OA) is a debilitating musculoskeletal disease that is characterized by a progressive loss of joint function. Patients who suffer from OA often exhibit chronic, significant pain, mobility loss, and functional impairments involving diarthrodial joints (hips, knees, and hands). As average life expectancy rises, OA has emerged as the most rapidly growing major health condition and the leading cause of chronic disability in the United States [[30]1,[31]2]. Our understanding of OA in recent years has changed drastically. Once thought as simple ‘wear and tear’, it is now well understood that a variety of processes, including inappropriate joint loading [[32]3], dysfunctional healing responses to cartilage injury and low-level chronic inflammation [[33]4], both in the synovium [[34]5] and systemically [[35]6] play significant roles. The contributions of genetic variation to OA susceptibility are varied depending on the joint involved; large twin studies have estimated the heritability of severe hip OA to average 73%, whereas the heritability of severe knee OA is far less at 45% [[36]7]. A variety of non-genetic factors have been demonstrated as key contributors to the development of OA, including age, mechanical trauma, and local inflammatory processes [[37]3]. Among many cellular mechanisms responsible for the physiological integration of these environmental signals, epigenetics has emerged as one of the most significant, and has been linked to both development and progression of OA. Epigenetics refers to the study of any heritable changes in gene expression caused by mechanisms other than genomic DNA mutations. Through epigenetics, gene transcription patterns are altered as a response to various internal and environmental signals. The canonical epigenetic control mechanisms include cytosine genomic DNA methylation, noncoding RNA, and histone post-translational modifications [[38]8]. DNA methylation is a process during which DNA methyltransferase (DNMT, see [39]Table 1 for list of abbreviations) enzymes transfer a methyl group from S-adenosyl methionine (SAM, the ‘methyl donor’) onto the C5 position of cytosine (5 ​mC) occurring most often in CpG dinucleotides. In vertebrates to date there have been three DNMTs identified (DNMT1, DNMT3a, DNMT3b) [[40]9]. DNMT1 is the maintenance methyltransferase, functioning to maintain existing DNA methylation patterns during DNA replication, whereas DNMT3a and DNMT3b play a role in de novo creation of DNA methylation patterns. Hypermethylation in gene regulatory regions generally suppresses gene transcription whereas hypomethylation generally enhances it. DNA methylation changes are a fluid process with changes occurring throughout an organism's lifespan. However, several months or years after birth, there is a tremendous rise in DNA methylation levels [[41]10] where the majority of methylation patterns are ‘set’ in differentiated tissues. Active ‘demethylation’ of cytosine ‘occurs when ten-eleven translocases (TET) convert 5 ​mC into 5-hydroxymethylcytosine (5 ​hmC), 5-formylcytosine (5 ​fC), or 5-carboxylcytosine (5caC) intermediates which are rapidly converted to unmethylated cytosine [[42][11], [43][12], [44][13]], thereby facilitating gene expression. Table 1. Abbreviations used in this review and commonly featured in OA epigenetics research. Abbreviation Definition DMP/DML Differentially methylated position or differentially methylated loci, refers to a statistically significant difference in DNA methylation within a target tissue or cell subset of an individual cytosine within a CpG oligodeoxynucleotide. DMR Differentially methylated region, refers to a statistically significant difference n DNA methylation within a target tissue or cell subset of a CpG-dense region. Various definitions of DMR sizes exist; a commonly-used criteria would define a ‘bandwidth’ of 1000 nucleotides with a standard deviation of 500 nucleotides, including a CpG density of at least 2 CpG sites (CpG ‘bandwidth’) within 10 nucleotides of each other. NGS Next generation sequencing, refers to a suite of technologies allowing sequencing of an entire genome at relatively low cost. The most commonly used of these high-throughput DNA sequencing methods is Illumina sequencing by synthesis, operating at an accuracy of ~99.9% with reads on the order of 50-500bp. SNP Single nucleotide polymorphism, refers to a germline substitution of a single nucleotide at a given position within the genome. CpG Cytosine-guanosine dinucleotide, the location within the genome wherein DNA methylation occurs (5′ carbon position of cytosine) within fully differentiated tissues. DMM Disruption of the medial meniscus, a surgical technique commonly used to induce OA-like changes within a mouse stifle (knee) joint 5-hmC 5-hydroxymethylcytosine, a ‘transition state’ between methylated cytosine and unmethylated cytosine. The conversion of 5-mC to 5-hmC is catalyzed by the TET1 enzyme. [45]Open in a new tab Among the noncoding RNAs, the most commonly studied are microRNAs (miRNAs), long noncoding RNAs (lncRNA), Piwi-interacting RNAs (piRNA), small nucleolar RNAs (snoRNAs) [[46]14,[47]15], and circular RNAs (circRNAs) [[48]16] MicroRNAs are the most widely studied non-coding RNAs that have the ability to bind to specific messenger RNAs inducing their cleavage or degradation that ultimately alters protein expression. These short 22 nucleotide-long sequences can alter gene expression by binding to the 3’ tail of mRNAs thus targeting them for degradation. Furthermore, miRNAs can also bind and destabilize mRNAs without inducing degradation [[49]17]. In contrast to miRNAs, lncRNAs, as their name suggests, are long RNAs encompassing a more heterogeneous group of noncoding RNAs that are more than 200 nucleotides in length. lncRNAs perform numerous activities in the body [[50]18] such as using RNA-protein interactions, recruitment of regulatory complexes, and acting as direct local regulators [[51]19] of gene expression. In this review article, we seek to systematically review the recent literature on altered epigenetic patterns associated with OA in humans and animal models, with a specific focus on DNA methylation and noncoding RNAs. As opposed to reviewing studies chronologically, we will instead group publications based on the methodology used, including array-based and next generation sequencing-based approaches to quantification of DNA methylation as well as array-based and sequencing-based noncoding RNA studies. 2. Brief methods: DNA methylation quantitation by sodium bisulfite treatment Only a handful of emerging sequencing technologies have the ability to read DNA methylation patterns. To the present day, the gold standard remains sodium bisulfite conversion of genomic DNA. Treatment of genomic DNA with sodium bisulfite results in deamination of unmethylated cytosines into uracils, whereas methylated and hydroxymethylated (5 ​mC and 5 ​hmC) cytosines are left unconverted. Following subsequent PCR amplification, uracil is converted to thymine, while methylated and hydroxymethylated cytosines are amplified as cytosines. After this process, the treated DNA can be sequenced either by PCR pyrosequencing methods, microarrays, or by large parallel sequencing methods which fall into the category of ‘next generation sequencing’, discussed later in this article. Each of these technologies ultimately differentiates methylated from unmethylated cytosine based on the ratio of cytosine to thymine in the final bisulfite-converted and sequenced product, allowing quantification of DNA methylation patterns at a single nucleotide resolution [[52]20,[53]21]. 3. DNA methylation analyses in OA 3.1. Historical context Alterations of DNA methylation patterns as a feature of OA pathogenesis has been suggested since the mid-1980s, when it was found that type I and type II collagen genes were epigenetically regulated in chick embryos [[54]22]. The first evaluation of DNA methylation in OA specifically was performed in 2005, when several key catabolic genes were shown to be demethylated in OA, including ADAMTS4, MMP3, MMP9, and MMP13 [[55]23]. The adipokine leptin was later added to the list of differentially methylated genes in OA [[56]24]. More recent single-gene epigenetic studies have included the OA susceptibility gene GDF5 [[57]25], the Wnt and BMP-Smad signaling gene sclerostin (SOST) [[58]26], and many other key transcription factors, catabolic, and anabolic factors including SOX9, MMP13, and COL9A1 [[59][27], [60][28], [61][29]]. Candidate analysis of inflammation-related genes have also demonstrated differential methylation within cartilage, including interleukin 8 (IL8) [[62]30], interleukin 1 (IL-1β) [[63]31,[64]32]. Starting in the 1990s, DNA microarray technology emerged as both a time and cost-saving solution for large-scale genetic analyses, with subsequent adaptation of this technology to epigenetic analysis. The field has been dominated by Illumina's Infinium BeadArray and BeadChip (Illumina, San Diego, CA, USA) technology since the release of their Infinium HumanMethylation27 BeadArray in 2009 [[65]33]. This first-generation chip provided quantification of roughly 27,000 CpG sites throughout the genome (covering nearly half of known coding regions). As research in epigenetics expanded, it was discovered that the DNA methylations occurring outside of the CpG islands were also vital factors contributing to the alteration of gene expression [[66]34]. To encompass these regions, Illumina created an expanded Infinium HumanMethylation450 BeadChip that allowed surveillance of around 470,000 CpG sites throughout the genome in the early 2010s. However, that still only covered about 2% of CpG loci in the entire human genome. The latest release from Illumina is the Infinium HumanMethylationEPIC BeadChip that covers nearly 850,000 CpG sites of the genome along with, non-CpG differentially methylated sites, enhancers, open chromatin, transcription factor binding sites, and miRNA promoter regions. The Illumina microarrays consist of two types of probes/beads. The M bead type is designed to measure the methylated loci, while the U bead type measures unmethylated loci. Total methylation levels of all the covered loci are calculated by measuring the ratio of the fluorescent signals emitted from methylated over unmethylated sites generally expressed by a beta-value (quantitative methylation ratio that ranges from 0 to 1). Although not as widely utilized, Agilent Technologies also produces microarrays for genetic and epigenetic analyses. Agilent Human Promoter Microarrays (Agilent Technologies, Santa Clara, CA, USA) currently come in three sizes covering different numbers of CpG sites each. All of their arrays cover roughly 21,000 human genes as represented by RefSeq with the only difference being the resolution at which the genes are analyzed. The largest in size is their SurePrint G3 Human Promoter Kit 1 ​× ​1M that covers 966,092 distinct biological features, followed by SurePrint G3 Human promoter 2 ​× ​400 ​K Kit (covers 414,043 distinct biological features), with the smallest being Human Promoter Microarray Kit 1 ​× ​244 ​K (covers 243,504 distinct biological features). 3.2. Infinium HumanMethylation27 BeadChip The development of the 27 ​k microarray allowed, for the first time, a relatively inexpensive and highly reproducible way to quantify genome-wide DNA methylation levels. In 2014, Fernández-Tajes et al. [[67]35] were the first to apply this technology to determine methylome changes in OA cartilage (Overview of differentially methylated pathways from studies included in this article in [68]Fig. 1, timeline of microarray publications [69]Fig. 2). The study identified a total of 91 differentially methylated probes between patients with OA and healthy controls. Among those, the runt-related transcription factor-1 (RUNX1) was the most hypomethylated, while msh homeobox-1 (MSX1) was the most hypermethylated in OA patients relative to controls. Runx1 was recently noted as the gene that plays a vital role in articular cartilage maintenance by enhancing matrix production [[70]36]. Interestingly, in supervised clustering analysis, this study also identified a subset of OA patients that had a variety of epigenetic changes of genes related to inflammatory regulations, activation motifs, and cytokine production. Fig. 1. [71]Fig. 1 [72]Open in a new tab Venn diagram demonstrating gene pathways and families differentially methylated among various knee and hip OA groups. Fig. 2. [73]Fig. 2 [74]Open in a new tab Timeline of major advances in methodologies for studying DNA methylation using array-based techniques, with article references.