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Non-coding RNAs constitute 99% of total cellular RNA
content and, alongside DNA methylation and histone
modification, represent one of three major epigenetic
mechanisms that contribute to health and disease1.
Although non-coding RNAs are encoded in DNA and
transcribed to RNA, they are not translated to protein;
however, this does not negate their important role in
regulating cellular processes. The precise mechanism of
action is dependent on the class of non-coding RNA —
short non-coding RNAs (such as microRNAs (miRNAs)),
long non-coding RNAs (lncRNAs) or circular RNAs
(circRNAs) — although all types ultimately function
to regulate the expression of specific gene targets1. As
such, non-coding RNAs are essential for establishing
and maintaining homeostatic balance in biological sys-
tems, including regulating the signalling pathways and
biological processes that govern joint development2.
Deregulation of this balance contributes to the patho-
genesis of joint diseases such as osteoarthritis (OA) and
rheumatoid arthritis (RA)3,4.
Non-coding RNAs are found in almost all joint tissues
and biofluids across different species, demonstrating
their biological importance5. In joint disease, non-coding
RNAs have been explored as potential biomarkers,
mediators of pathogenesis and therapeutic targets.
Adding to the complexity of these epigenetic regula-
tors, the different classes of non-coding RNAs can pro-
vide redundancy by targeting the same genes, work in
concert by targeting the same pathways and directly
interact to regulate gene expression6. Although this
putative ‘interactome’ of non-coding RNAs has yet
to be comprehensively explored in joint health and
disease, its elucidation is improving with the use of tech-
nologies for high-throughput profiling and integrative
computational analysis.
To demonstrate that ‘non-coding’ does not mean
‘non-essential’, in this Review we discuss literature pub-
lished in the past 2 years on non-coding RNAs in OA
and RA. We first describe the classes of non-coding
RNAs and their mechanisms of action, followed by the
role of non-coding RNAs in osteogenesis and chondro-
genesis, two vital biological processes in joint develop-
ment. We next review non-coding RNAs in OA and RA
joint tissues and biofluids, and their roles in inflam-
mation, cell death, cell proliferation and extracellular
matrix (ECM) dysregulation. Finally, we discuss the
therapeutic potential of non-coding RNAs in OA and
RA and the deep-dive efforts that will be required in
the future to unravel the complex interactions among
non-coding RNAs.
The non-coding RNA interactome
in joint health and disease
ShabanaA.Ali
1,2 ✉ , MandyJ.Peffers3, MichelleJ.Ormseth4,5, IgorJurisica6,7 and
MohitKapoor
6,8 ✉
Abstract | Non-coding RNAs have distinct regulatory roles in the pathogenesis of joint diseases
including osteoarthritis (OA) and rheumatoid arthritis (RA). As the amount of high-throughput
profiling studies and mechanistic investigations of microRNAs, long non-coding RNAs and
circular RNAs in joint tissues and biofluids has increased, data have emerged that suggest
complex interactions among non-coding RNAs that are often overlooked as critical regulators
of gene expression. Identifying these non-coding RNAs and their interactions is useful for
understanding both joint health and disease. Non-coding RNAs regulate signalling pathways
and biological processes that are important for normal joint development but, when
dysregulated, can contribute to disease. The specific expression profiles of non-coding
RNAs in various disease states support their roles as promising candidate biomarkers,
mediators of pathogenic mechanisms and potential therapeutic targets. This Review
synthesizes literature published in the past 2 years on the role of non-coding RNAs in
OA and RA with a focus on inflammation, cell death, cell proliferation and extracellular
matrix dysregulation. Research to date makes it apparent that ‘non-coding’ does not mean
‘non-essential’ and that non-coding RNAs are important parts of a complex interactome
that underlies OA and RA.
✉e-mail: sali14@hfhs.org;
mohit.kapoor@uhnresearch.ca
https://doi.org/10.1038/
s41584-021-00687-y
REVIEWS
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Classes of non-coding RNAs
Non-coding RNAs are classified on the basis of their
biogenesis, length and mechanism of action (FIG.1a).
Following transcription, non-coding RNAs are pro-
cessed to form short, long or circular non-coding RNAs
with unique secondary and tertiary structures. The first
class are short non-coding RNAs, which are fewer than
200 nucleotides in length. This class includes miRNAs,
small nucleolar RNAs (snoRNAs), small nuclear RNAs,
Piwi-interacting RNAs (piRNAs), small interfering
RNAs (siRNAs), transfer RNAs (tRNAs), tRNA-derived
fragments (tRFs) and Y RNA fragments (YRFs)5. The
most frequently studied of the short non-coding RNAs
are miRNAs. miRNA biogenesis begins with a primary
miRNA transcript from the intron, exon or intergenic
region of the host gene, followed by processing within
the nucleus to produce a precursor miRNA. After
export to the cytoplasm, the precursor miRNA under-
goes cleavage to produce the mature miRNA. Mature
miRNAs are single stranded, 18–24 nucleotides in length
and function to inhibit target gene expression through
mRNA degradation or repression of translation4 (FIG.1b).
The second class of non-coding RNAs are lncRNAs,
which are greater than 200 nucleotides in length. Similar to
short non-coding RNAs, lncRNAs function to modulate
mRNA stability and translation in the cytoplasm through
multiple mechanisms, including the post-translational
modification of target molecules7 (FIG.1c). Circular forms
of lncRNAs, or circRNAs, comprise 1–5 introns or exons
and form a covalently closed loop structure that func-
tions as an miRNA sponge, protein sponge or scaffold
for translation5,6 (FIG.1d). miRNA sponging depends
on the presence of miRNA response elements within
lncRNAs and circRNAs that can specifically bind and
sequester miRNAs, thereby blocking their activity. This
sponging is a type of competing endogenous RNA activity
andisa mechanism through which the different classes
of non-coding RNAs can directly interact. circRNAs pri-
marily function as competing endogenous RNAs, binding
to miRNA response elements and reducing the quantity
of miRNAs available to target mRNA, thereby promoting
mRNA stability or protein expression6. In this Review, we
focus on miRNAs, lncRNAs and circRNAs, as these types
of non-coding RNA have been explored the most in OA
and RA to date3,8.
Non-coding RNAs in joint development
Healthy joint development is dependent on precise
regulation of the signalling pathways that govern oste-
ogenesis and chondrogenesis, among other processes,
and if these become dysregulated, joint pathologies
can result. miRNAs, lncRNAs, circRNAs and even
piRNAs are differentially expressed during the early
stages of osteogenic and chondrogenic differentiation
in human bone marrow-derived mesenchymal stro-
mal cells and/or bone marrow-derived mesenchymal
stem cells (BMSCs), suggesting that non-coding RNAs
might affect these processes9,10. Non-coding RNAs can
also regulate important signalling pathways, including
the Wnt–β-catenin and Hedgehog signalling pathways,
which are essential for tissue induction, patterning,
growth and morphogenesis11. For example, overexpres-
sion of miR-378 in transgenic mice results in abnormal
bone formation and quality, as well as compromised
osteogenic differentiation in both mouse and human
BMSCs12. Interestingly, miR-378 targets two Wnt fam-
ily members, Wnt6 and Wnt10a, thereby attenuating
Wnt–β-catenin signalling12. These results suggest that
miRNAs might be upstream regulators of certain devel-
opmental signalling pathways, which has implications
for bone health.
Chondrogenesis is essential for endochondral and
intramembranous ossification and for tissue homeo-
stasis, and is also subject to regulation by non-coding
RNAs. The Indian Hedgehog signalling pathway is
well known to regulate chondrogenesis during normal
development13. The gene encoding Indian Hedgehog
contains two putative sites at which miR-1 can bind and
inhibit its activity, resulting in increased expression of
type II collagen and aggrecan and decreased expression
of type X collagen and matrix metalloproteinase 13 in
mouse thorax chondrocytes14. These results suggest
that miR-1 induces an anabolic effect in chondrocytes
through inhibition of the Indian Hedgehog pathway,
which is consistent with previous findings that aber-
rant activation of the Indian Hedgehog pathway can
have catabolic effects on cartilage15. Furthermore, the
transcription factor SOX9, which is critical for mes-
enchymal condensation prior to chondrogenesis, is
targeted by miR-30a to inhibit chondrogenic differenti-
ation in human BMSCs16, again demonstrating a direct
Key points
•Anincreasingbodyofliteratureonnon-codingRNAsinjointhealthanddiseasehas
revealedimportantregulatoryfunctionsthatindicatethat‘non-coding’doesnot
equateto‘non-essential’.
•Non-codingRNAs,includingmicroRNAs,longnon-codingRNAsandcircularRNAs,
candirectlyinteractandhaveco-regulatoryfunctions.
•Inosteoarthritisandrheumatoidarthritis,non-codingRNAsareimportantcontributors
topathogenesisandserveaspotentialbiomarkersandtherapeutictargets.
•Withtheemergenceofdatafromhigh-throughputstudies,detailedreportingand
accurateannotationofresultsarerequiredtointegrateindividualstudiesandenable
interrogationofthenon-codingRNAinteractome.
•Anexpandedunderstandingofthenon-codingRNAinteractomecouldreveal
essentialregulatorymechanismsandnoveltherapeuticopportunitiesfor
osteoarthritis,rheumatoidarthritisandotherrelatedjointdiseases.
Author addresses
1BoneandJointCenter,DepartmentofOrthopaedicSurgery,HenryFordHealthSystem,
Detroit,MI,USA.
2CenterforMolecularMedicineandGenetics,SchoolofMedicine,WayneState
University,Detroit,MI,USA.
3DepartmentofMusculoskeletalBiology,InstituteofLifeCourseandMedicalSciences,
UniversityofLiverpool,Liverpool,UK.
4DepartmentofResearchandDevelopment,VeteransAffairsMedicalCenter,Nashville,
TN,USA.
5DepartmentofMedicine,VanderbiltUniversityMedicalCenter,Nashville,TN,USA.
6OsteoarthritisResearchProgram,DivisionofOrthopaedics,SchroederArthritisInstitute,
KrembilResearchInstitute,UniversityHealthNetwork,Toronto,Ontario,Canada.
7DataScienceDiscoveryCentreforChronicDiseases,KrembilResearchInstitute,
UniversityHealthNetwork,Toronto,Ontario,Canada.
8DepartmentofSurgeryandDepartmentofLaboratoryMedicineandPathobiology,
UniversityofToronto,Toronto,Ontario,Canada.
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regulatory role for miRNAs in established mechanisms
that govern chondrogenesis.
Looking at interactions between classes of non-
coding RNAs in osteogenesis and chondrogenesis, evi-
dence exists of competing endogenous RNA activity.
The lncRNA LINC00707 sponges miR-145 in human
BMSCs and increases the expression of lipoprotein
receptor-related protein 5, a co-receptor for Wnt pro-
teins, thereby promoting osteogenic differentiation17.
Similarly, the lncRNA ADAMTS9-AS2 sponges miR-
942-5p in human BMSCs and increases expression of the
transcription factor SCRG1, thereby promoting chon-
drogenic differentiation18. circRNAs have also emerged
as novel orchestrators of signalling pathways that gov-
ern osteogenesis19. Relevant to development, an axis
has been identified whereby circRNA_0079201 sponges
miR-140-3p in human chondrocytes and increases
expression of the transcription factor SMAD2, thereby
suppressing cell proliferation, hypertrophy and endo-
chondral ossification20. Taken together, these examples
illustrate an important role for non-coding RNAs in gov-
erning signalling pathways and biological processes in
joint development that have implications for joint health
and disease.
Non-coding RNAs in OA and RA
Expression in joint tissues
Strong evidence exists to support cell-specific and
tissue-specific expression patterns of non-coding RNAs
in OA and RA21,22. Two studies used microarrays to
compare cartilage from patients with OA and healthy
individuals and identified 58 and 70 differentially
expressed miRNAs, respectively23,24. Beyond miRNAs,
a diverse range of non-coding RNAs have been identified
miRNA IncRNA
• Immune cells
• Synovial cells
• Chondrocytes
• Bone cells
• Adipocytes
Chromatin
Cell
DNA RNA
Short non-coding RNAs
(<200 nt)
Long non-coding RNAs
(>200 nt)
snRNA, snoRNA, piRNA,
siRNA, tRNA, tRF & YRF
Blood
Synovial
fluid
Urine
Extracellular
vesicles
pre-miRNA miRNA
IncRNA circRNA
mRNA cleavage
Protein scaffolding
Translational
repression
a
b c d
Transcriptional regulation
circRNA
Synovial joint
Translational regulation
miRNA sponging
miRNA sponging
Translational
scaffolding
Protein sponging
Fig. 1 | Biogenesis and function of microRNAs, long non-coding RNAs and circular RNAs. Within the synovial joint,
several cell types can be a source of non-coding RNAs that are transcribed from DNA (part a). Non-coding RNAs can
function within the producing cell or in a target cell, and are secreted into biofluids as free molecules or within extracellular
vesicles. Potential functions for microRNAs (miRNAs) include mRNA cleavage and translational repression (part b); for long
non-coding RNAs (lncRNAs) include transcriptional regulation, translational regulation, protein scaffolding and miRNA
sponging (part c); and for circular RNAs (circRNAs) include miRNA sponging, protein sponging and translational scaffolding
(part d). nt, nucleotides; piRNA, Piwi-interacting RNA; siRNA, small interfering RNA; snRNA, small nuclear RNA; snoRNA,
small nucleolar RNA; tRF, tRNA-derived fragment; tRNA, transfer RNA; YRF, Y RNA fragment.
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in primary human OA chondrocytes and cartilage,
including lncRNA MFI2-AS1, lncRNA LOXL1-AS1,
tRF-3003a and U3 snoRNA25–28. In primary human
synoviocytes and synovial tissue in OA and RA, reports
have focused on lncRNAs such as MALAT1, NEAT1
and PVT1 (REFS29–31). MALAT1 expression crosses tis-
sue types, being increased in both the synovium29 and
subchondral bone32 of patients with OA compared
with healthy individuals. Similarly, NEAT1 expression
crosses both tissue types and diseases, being increased
in OA cartilage30 and in RA synovium33. These examples
demonstrate a non-coding RNA expression pattern that
is not only tissue specific, but potentially also disease
specific, and support the need for further studies focused
on profiling non-coding RNAs in other tissues and cells
implicated in OA and RA, including bone34,35, adipose
tissue36, meniscus37 and macrophages38,39. Furthermore,
this profiling should take into account unique patient
endotypes40,41 and apply appropriate inclusion and exclu-
sion criteria during the selection of participants to facil-
itate the interpretation of findings and integration with
other studies.
Sequencing is the gold standard approach for iden-
tifying tissue-specific non-coding RNAs, their targets
and their interactions. In a 2019 study that compared
lesioned with preserved cartilage from patients with
knee or hip OA, RNA sequencing was used to identify
142 miRNAs and 2,387 mRNAs that were prioritized
into a regulatory network comprising 62 miRNAs that
targeted 238 mRNAs42, which showed joint-specific
expression patterns. Similarly, 1,068 mRNAs, 21miRNAs
and 395miRNA–mRNA pairs were identified in syn-
ovial tissue from patients with knee OA using RNA
sequencing43. Given the large number of candidate
non-coding RNAs identified through sequencing,
a deeper dive into the biological relevance of prioritized
candidates is required through validation studies. In syn-
ovium, canonical correlation analysis of RNA sequenc-
ing and small RNA sequencing data has been used to
identify miRNA–mRNA co-expression patterns44.
Specifically, five miRNAs and four genes were predicted
to be associated with pain in knee OA, suggesting their
potential utility as biomarkers.
Although obtaining tissue samples by biopsy might
be considered too invasive for use in biomarker detec-
tion, evidence from RA suggests that the amount of
non-coding RNAs in the circulation might differ from
that found in tissues. For example, the amount of miR-22
is increased in plasma from patients with RA compared
with that from healthy individuals and is associated with
disease activity in RA45,46, but is decreased in synovial
tissue from patients with RA compared with synovium
from healthy individuals47. It is unclear whether this
tissue-specific difference in miR-22 expression is due
to sponging (as is the case for miR-145-5p, which is
sponged by the lncRNA PVT1 in RA synovium to pro-
duce lower concentrations in the synovium than in the
serum31) or other mechanisms of non-coding RNA regu-
lation. Nevertheless, these data suggest that, in addition
to tissue-specific expression patterns, biofluid-specific
patterns of non-coding RNA expression must also be
considered.
Expression in biofluids
Non-coding RNAs can be secreted by cells either as
free RNA molecules or encapsulated into extracellu-
lar vesicles such as exosomes and can be identified in
biofluids including blood, urine and synovial fluid36,48,49
(FIG.1). Given their association with disease activity,
non-coding RNAs are thought to represent excellent
candidate biomarkers50. Non-coding RNA classes are
broadly altered in plasma from patients with RA, in
which sets of miRNAs and tRFs are enriched and sets of
YRFs are depleted compared with healthy individuals46.
Such non-coding RNA class shifts might be caused by
broad changes in RNA processing mechanisms, such as
the upregulation of Dicer and Drosha in RA peripheral
blood mononuclear cells (PBMCs)51, which are a major
source of non-coding RNAs in plasma. Surprisingly,
non-coding RNAs of microbial origin have also been
detected in human plasma; the abundance of microbial
small RNAs and specific microbial tRFs were inversely
associated with disease activity in two separate cohorts of
patients with RA and also predicted response to therapy,
suggesting that they might be useful as biomarkers52.
Non-coding RNA profiling in OA biofluids has
focused on miRNAs in the circulation because sam-
ples are accessible by minimally invasive blood draw
(TABLE1). Approaches used include real-time PCR53,54,
real-time PCR miRNA arrays55, miRNA microarrays35,38
and, most recently, miRNA sequencing of serum56,
plasma57 and plasma-isolated extracellular vesicles58.
miRNA sequencing is of particular interest as it ena-
bles the discovery of novel miRNAs that are potentially
unique to a disease stage or phenotype57,59. Fewer reports
have described miRNA profiles in urine or synovial
fluid than in blood60,61. Real-time PCR miRNA arrays
were used to interrogate synovial fluid samples taken
before and 6 months after high tibial osteotomy in six
patients with knee OA at Kellgren–Lawrence grade II
or III60. Three miRNAs were identified as being differ-
entially expressed at the two time points and, following
validation by real-time PCR in 22 additional patients,
increased miR-30c-5p was found to correlate with
reduced postoperative pain60. Looking beyond miRNAs,
lncRNAs and circRNAs are also dysregulated in OA
biofluids62. For example, the expression of lncRNAs
CAIF, LUADT1 and SNHG9 are decreased in OA syno-
vial fluid63–65, whereas CTBP1-AS2, MCM3AP-AS1 and
CASC2 are increased66–68, although the utility of these
lncRNAs as biomarkers requires further research.
To date, no consistent profile of non-coding RNAs
has been identified and validated in biofluids across
OA or RA studies. Among the challenges faced by
researchers are differences across studies in the joints
characterized, the profiling platforms used, the bioflu-
ids profiled and how the patient groups are defined, all
of which make it difficult to directly compare findings
(TABLE1). Going forward, panels of non-coding RNAs
(potentially from multiple classes) could prove to be
more reliable as biomarkers than an individual entity or
class owing to the variable expression and interactions
of individual non-coding RNAs. In addition to their
roles as biomarkers, non-coding RNAs in biofluids
might also function as systemic regulators of disease in
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distal joints. Two studies from 2020 found alterations in
the concentrations of circulating miRNAs that directly
target single-nucleotide polymorphisms in CXCR4 and
ADAMTS5 loci69,70, both of which are related to OA risk.
These results point to non-coding RNAs as circulating
epigenetic factors that regulate risk loci in arthritis as an
exciting new avenue for future research.
Role in pathogenesis
As important regulators of gene expression, non-coding
RNAs can be expected to have pleiotropic effects in poly-
genic diseases such as OA and RA. Data suggest that
non-coding RNAs can have both beneficial (such as
maintaining tissue homeostasis) and detrimental (such
as inducing tissue destruction) effects on the joints4,22.
In fact, miRNAs regulate a diverse range of cellular
processes (including inflammation71–74, apoptosis75–78,
ECM dysregulation79,80, chondrocyte differentiation81,
oxidative stress82 and autophagy83–85), signalling path-
ways (including transforming growth factor-β86,87,
fibroblast growth factor (FGF)88, Wnt–β-catenin89–91 and
Hedgehog92) and mediators (including the transcription
factors FOXM1, SOX5, SOX6 and SOX9, and oestro-
gen receptor-α93–98) that are relevant for OA and RA.
Similarly, lncRNAs (TABLE2) and circRNAs (TABLE3)
can have multi-target regulatory effects on cell pheno-
type and tissue homeostasis and have the potential to
mediate pathogenic mechanisms in OA and RA6,62,99.
Table 1 | Circulating microRNAs with potential for use as biomarkers in OA and RA
Disease Platform Biofluid Number of
patients
Number of controls
(type)
Differentially expressed
miRNAs
Ref.
Knee OA Real-time PCR Plasma 150 150 (healthy individuals,
traumatic amputation or
meniscus injury)
Reduced in OA: miR-200c-3p,
miR-100-5p and miR-1826
53
Knee OA Real-time PCR Serum 10 10 (trauma) Reduced in OA: let-7e 54
Hip OA Real-time PCR Serum 28 2 (femoral neck fracture) Increased in OA: miR-146a-5p 169
RA Real-time PCR Plasma 125 30 (healthy individuals) Reduced in RA: miR-155 170
RA Real-time PCR Serum 20 20 (healthy individuals) Increased in RA: miR-138 171
RA Real-time PCR Blood 90 30 (healthy individuals) Increased in RA: miR-155,
miR-150, miR-146a, miR-146b,
miR-125a-5p and miR-223
172
RA Real-time PCR Serum 18 76 (SLE, SSc or MCTD) Increased in RA: miR-145 and
miR-181a
173
Knee OA Real-time PCR array Serum 114 (high pain relief
1 year post-TKR)
22 (low pain relief 1 year
post TKR)
Increased in low pain
relief group: miR-146a-5p,
miR-145-5p and miR-130b-3p
55
Knee OA Microarray Blood 55 (healthy individuals) Decreased in OA: miR-582-5p
and miR-424-5p
35
RA Microarray Blood 5 (early RA) 5 (healthy individuals),
5 (CPP+ healthy individuals)
Increased in RA: miR-361-5p 174
RA Microarray Serum 9 (divided into
3 pools)
15 (healthy individuals;
divided into 5 pools)
Increased in RA: miR-187-5p,
miR-4532 and miR-4516;
decreased in RA: miR-125a-3p,
miR-575, miR-191-3p,
miR-6865-3p, miR-197-3p,
miR-6886-3p, miR-1237-3p
and miR-4436b-5p
175
RA Microarray Serum exosomes 22 (in clinical
remission)
20 (not in clinical
remission)
Increased in clinical remission
group: miR-1915-3p and
miR-6511-5p
176
Knee OA Next-generation
sequencing
Serum 10 10 (healthy individuals) Increased in OA: miR-146a-5p
and miR-186-5p
56
Knee OA Next-generation
sequencing
Plasma 41 (early-stage OA) 50 (late-stage OA) Increased in early-stage OA:
miR-335-3p, miR-199a-5p,
miR-671-3p, miR-1260b,
miR-191-3p, miR-335-5p
and miR-543
57
Knee, hip or
hand OA
Next-generation
sequencing
Plasma extracellular
vesicles
23 23 (healthy individuals) None 58
RA Next-generation
sequencing
Plasma 167 91 (healthy individuals) Increased in RA: miR-22-3p,
miR-24-3p, miR-96-5p,
miR-134-5p, miR-140-3p
and miR-627-5p
45
Includes articles published between 2019 and 2021. CPP, cyclic citrullinated peptide antibody; MCTD, mixed connective tissue disease; miRNA, microRNA;
OA, osteoarthritis; RA, rheumatoid arthritis; SLE, systemic lupus erythematosus; SSc, systemic sclerosis; TKR, total knee replacement.
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For example, lncRNAs can function through regulation
of histone methylation100, targeting single-nucleotide
polymorphisms101 and miRNA sponging30,102 to regu-
late cellular processes as diverse as apoptosis103,104, cell
proliferation103 and ECM degradation102,105,106. In the fol-
lowing sections, we curate literature published in thepast
2 years on non-coding RNAs in inflammation, cell
death, cell proliferation and ECM dysregulation in OA
and RA. Overall, although further research is required
to elucidate the interrelated effects of non-coding RNAs
on the pathogenesis of OA and RA, existing evidence
suggests that there could be merit to therapeutically
targeting non-coding RNAs in these diseases.
Inflammation. A variety of signalling molecules,
including non-coding RNAs, can induce and regulate
joint inflammation. Cytokines such as IL-1β, TNF and
IL-6 are often used as markers to gauge inflammatory
responses in chondrocytes and fibroblast-like syn-
oviocytes (FLSs). Amounts of these three cytokines
were reduced in mouse primary chondrocytes by an
increase in miR-410-3p107, and in supernatant from
lipopolysaccharide-treated human chondrocytes by
a decrease in miR-20a108; both outcomes were medi-
ated by nuclear factor-κB (NF-κB) signalling. NF-κB
can regulate the expression of miRNAs, but miRNAs
can also regulate the expression of NF-κB; for exam-
ple, an increase in miR‐382‐3p leads to a decrease in
phosphorylated NF-κB in IL‐1β‐stimulated human
OA chondrocytes109. Furthermore, miR-140-5p can
reduce human chondrocyte senescence110 and can work
synergistically with miR-146a to reduce NF-κΒ phos-
phorylation and the production of pro-inflammatory
cytokines in OA chondrocytes111. These studies suggest
that miRNAs regulate inflammatory responses through
mechanisms that include canonical signalling path-
ways (such as NF-κB) and cytokines (such as IL-1β,
IL-6 and TNF) in OA, and similar results have been
reported in RA47. lncRNAs are also important media-
tors of inflammation in human OA chondrocytes. The
lncRNAs PACER, CILinc01 and CILinc02 all show
rapid and transient induction in response to IL-1β and
other pro-inflammatory stimuli, indicating important
regulatory roles112.
In RA, non-coding RNAs in circulating immune
cells, synovial immune cells and FLSs contribute to
excess inflammation. T helper 17 (TH17) cells that
produce cytokines such as IL-17 and IL-22 stimulate
inflammatory responses from FLSs and macrophages in
RA to further promote synovial inflammation113.
In RA PBMCs, the lncRNA NEAT1 (which is present in
increased amounts compared with healthy individuals)
Table 2 | Long non-coding RNAs of mechanistic importance in OA and RA
lncRNA Change in expression Mechanism Effects Ref.
CTBP1-AS2 Increased in OA synovial fluid Increased methylation of
miR-130a
Promotes proliferation in OA chondrocytes 66
XIST Increased in OA cartilage Binds TIMP3 promoter and
accelerates methylation
Increases collagen degradation in OA chondrocytes 106
LINC01534 Increased in OA cartilage Sponges miR-140-5p Promotes ECM degradation (decreases aggrecan, type II
collagen and increases MMP3, MMP9 and MMP13) and
increases pro-inflammatory mediators (NO, PGE2, IL-6, IL-8
and TNF) in IL-1β-treated chondrocytes
138
H19 Increased in OA cartilage Sponges miR-140-5p Increases apoptosis, reduces cell proliferation, increases ECM
degradation (increases MMP1 and MMP13 and decreases type II
collagen) and increases ECM calcification in chondrocytes
137
Increased in RA FLSs and
synovium
Sponges miR-103a, which
negatively regulates IL15
and DKK1
Increases inflammation and joint destruction in mice with CAIA 177
NEAT1 Increased in OA cartilage Sponges miR-377-3p, which
negatively regulates ITGA6
Reduces cell proliferation and increases apoptosis, ECM
degradation and inflammation in IL-1β-treated chondrocytes
30
Increased in RA FLSs and
synovium
Sponges miR-410-3p, which
negatively regulates YY1
Increases cell proliferation and TNF and MMP9 expression and
decreases apoptosis in RA FLSs
33
Increased in RA PBMC
exosomes
Sponges miR-23a, which
negatively regulates the
MDM2–SIRT6 axis
Increases FLS proliferation and inflammation 135
Increased in RA PBMCs and
TH17 cells
Reduces ubiquitylation
of STAT3
Increases TH17 cell differentiation and disease severity in mice
with CIA
114
PINT Decreased in RA FLSs and
synovium
Sponges miR-155-5p, which
negatively regulates SOCS1
Increases cell proliferation, invasion and pro-inflammatory
cytokine production in RA FLSs
178
PVT1 Increased in RA synovium Sponges miR-145-5p Increases cell proliferation and pro-inflammatory cytokine
production and decreases apoptosis in RA FLSs
31
Increased in RA synovium Sponges miR-543, which
negatively regulates SCUBE2
Increases cell proliferation and IL-1β expression and decreases
apoptosis in RA FLSs
179
Includes articles published between 2019 and 2021. CAIA, collagen antibody-induced arthritis; CIA, collagen-induced arthritis; ECM, extracellular matrix;
FLS, fibroblast-like synoviocyte; lncRNA, long non-coding RNA; MDM2, E3 ubiquitin-protein ligase MDM2; MMP, matrix metalloproteinase; NO, nitric oxide;
OA, osteoarthritis; PBMC, peripheral blood mononuclear cell; PGE2, prostaglandin E2; RA, rheumatoid arthritis; SIRT6, sirtuin 6; STAT3, signal transducer and
activator of transcription 3; TH17 cell, T helper 17 cell.
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targets signal transducer and activator of transcription 3,
causing decreased ubiquitylation-mediated degradation
and leading to an increase in TH17 cell differentiation114.
Similarly, a lack of the miRNA let-7g-5p in patients with
RA promotes the differentiation of naive CD4+ Tcells
into TH17 cells, whereas the treatment of mice with
collagen-induced arthritis (CIA) with let-7g-5p mim-
ics decreases the number of TH17 cells in the blood and
spleen, leading to reduced synovial hyperplasia, pannus
formation and cartilage destruction115. Macrophages
with a pro-inflammatory phenotype (M1-like) are
also enriched in active RA synovium116. An increase in
miR-155 in monocytes from patients with RA impairs
monocyte differentiation into an inflammation-resolving
phenotype (M2-like)117 and, in RA synovial tissue and
fluid, an increase in miR-221-3p leads to decreased
IL-10 production (via direct targeting of Janus kinase 3)
in M2-like macrophages and acts synergistically with
miR-155-5p to increase the production of IL-12 (which
is specific to M1-like macrophages)118. Given the role
of inflammation in OA and RA, understanding the
contribution of non-coding RNAs to its underlying
mechanisms could provide new insights.
Cell death and cell proliferation. Abnormal cell death
and cell proliferation in joint tissues create hallmark
features of OA (such as cartilage degeneration) and RA
(such as synovial hyperplasia). Studies have reported
the effects of a variety of miRNAs on chondrocyte
apoptosis. For example, increased expression of miR-
33b-3p, miR‐9‐5p or miR‐27a decreased chondro-
cyte apoptosis119–121, whereas increased expression of
miR-486-5p, miR-363-3p or miR-455-3p increased
chondrocyte apoptosis75,122,123. The mechanisms through
which unique miRNAs affect cell death and cell prolif-
eration can often converge onto a single pathway, such
as the phosphoinositide 3-kinase (PI3K)–AKT sig-
nalling pathway124–131. Beneficial effects produced by
miRNAs through regulation of the PI3K–AKT pathway
include a reduction in apoptosis and cartilage degen-
eration caused by an increase in miR-455-3p124, the
promotion of chondrocyte proliferation and reduced
apoptosis caused by a decrease in miR-34a125 and a
reduction in chondrocyte apoptosis and inflammation
caused by an increase in miR-128-3p126. Conversely,
increased amounts of miR‐155, miR-1236 or miR-103 all
promote chondrocyte apoptosis by targeting PI3K127–129.
Table 3 | Circular RNAs of mechanistic importance in OA and RA
circRNA Change in expression Mechanism Effects Ref.
circ_0136474 Increased in OA cartilage Sponges miR-127-5p, which
negatively regulates MMP13
Suppresses cell proliferation and increases
apoptosis in OA chondrocytes
180
circ_0009119 Decreased in OA cartilage Sponges miR-26a, which
negatively regulates PTEN
Protects OA chondrocytes from IL-1β-induced
apoptosis
181
circ_0001722 (circCDK14) Decreased in OA cartilage Sponges miR-125a-5p, which
negatively regulates SMAD2
Regulates ECM metabolism (decreases MMP3
and MMP13; increases SOX9 and type II
collagen), inhibits apoptosis and promotes cell
proliferation in chondrocytes
182
circ_0023404 (circRNF121) Increased in OA cartilage LEF1 increases circRNF121
expression, which sponges
miR-665, which negatively
regulates MYD88
Regulates degradation of ECM (increases
MMP13 and ADAMTS5; decreases type II
collagen and aggrecan), apoptosis and cell
proliferation in chondrocytes
163
circ_0000284 (circHIPK3) Increased in OA cartilage Sponges miR-124, which
negatively regulates SOX8
Inhibits apoptosis in chondrocytes 183
circVCAN Increased in OA cartilage Inhibits activation of NF-κB
signalling pathway
Increases cell proliferation and decreases
apoptosis in OA chondrocytes
184
circ_0008956 (circUBE2G1) Increased in OA cartilage Sponges miR-373, which
negatively regulates HIF1A
circUBE2G1 inhibition reduces the effects of
LPS in OA chondrocyte viability and apoptosis
185
circPSM3 Increased in OA cartilage Sponges miRNA-296-5p Inhibits cell proliferation and differentiation in
OA chondrocytes
186
circCDR1as Increased in OA cartilage Sponges miR-641, which
negatively regulates FGF2
Regulates ECM metabolism (increases MMP13
and IL-6; decreases type II collagen)
187
circTMBIM6 Increased in OA cartilage Sponges miR-27a, which
negatively regulates MMP13
Regulates ECM degradation (increases
MMP13)
188
circ_0000448 (circGCN1L1) Increased in OA TMJ
synovium
Sponges miR-330-3p, which
negatively regulates TNF
Increases chondrocyte apoptosis and ECM
metabolism (increases MMP3, MMP13 and
ADAMTS4; decreases type II collagen),
and increases synoviocyte hyperplasia and
inflammation
189
circ_0088036 Increased in RA FLSs Sponges miR-140-3p, which
negatively regulates SIRT1
Increases FLS proliferation and migration 190
circ_09505 Increased in RA PBMCs Sponges miR-6089, which
negatively regulates AKT1
Increases macrophage proliferation and
cell-cycle progression
191
Includes articles published between 2019 and 2021. ADAMTS, a disintegrin and metalloproteinase with thrombospondin motifs; circRNA, circular RNA; ECM,
extracellular matrix; FLS, fibroblast-like synoviocyte; LEF1, lymphoid enhancer-binding factor 1; LPS, lipopolysaccharide; MMP, matrix metalloproteinase; NF-κB, nuclear
factor-κB; OA, osteoarthritis; PBMC, peripheral blood mononuclear cell; RA, rheumatoid arthritis; SOX9, transcription factor SOX9; TMJ, temporomandibular joint.
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Other pathways, such as NF-κB132, can also mediate the
effect of non-coding RNAs on chondrocyte apoptosis.
In addition, lncRNAs and circRNAs can interact with
miRNAs to regulate cell death and cell proliferation.
For example, lncRNA CTBP1-AS2 is upregulated
in OA synovial fluid and regulates the expression of
miR-130a through methylation in OA chondrocytes,
but not in healthy chondrocytes, to promote cell
proliferation66. New evidence to support the impor-
tance of non-coding RNAs in regulating cell death and
proliferation is also continuing to emerge133 (TABLE3).
In RA, expression of miR-483-3p, which is thought to
be oncogenic in several human cancers, is increased; in
FLSs, this miRNA directly targets IGF1 mRNA (which
encodes insulin-like growth factor 1; IGF1) to impair
apoptosis and induce tumour-like proliferation134.
Expression of the lncRNA NEAT1 is also increased in
human RA synovial tissue33 and PBMCs114. Delivery of
NEAT1 to RA FLSs via plasma exosomes isolated from
humans and mice caused sponging of miR-23a and
miR-410-3p and thereby increased the expression of
their targets (including E3 ubiquitin-protein ligase
MDM2 and transcriptional repressor protein YY1), lead-
ing to a decrease in apoptosis and an increase in FLS
proliferation and inflammation33,135. Furthermore, the
reduction of NEAT1 via siRNA can reduce the severity
of CIA in mice114. These results illustrate the possibility of
targeting non-coding RNAs to modulate cell death and
cell proliferation.
Extracellular matrix dysregulation. miRNAs, lncRNAs,
circRNAs and even snoRNAs have been implicated in
ECM dysregulation in joint tissues such as cartilage, syn-
ovium and bone. IL-1β is widely used to induce cellular
responses that mimic pathological conditions including
inflammation109, apoptosis127 and cartilage degradation97.
Researchers often use IL-1β to stimulate a response in
chondrocytes invitro that is subsequently rescued or
exacerbated by manipulating a non-coding RNA. In
cultured human chondrocytes, increased miR-377-3p
expression reversed IL-1β-induced upregulation of
inflammatory markers, cartilage degradation markers
and chondrocyte apoptosis30. In a different experimen-
tal model, human chondrocytes transfected with an
miR-613 agonist for 48 hours prior to administration of
IL-1β had reduced markers of inflammation, apoptosis
and cartilage degradation compared with IL-1β-treated
cells136. A tentative role for the NEAT1–miR-377-
3p–ITGA6 axis has been described in IL-1β-treated
chondrocytes, in which NEAT1 might function as
an miR-377-3p sponge, thereby upregulating ITGA6
expression to affect inflammatory responses, apoptosis
and ECM degradation30. Among other notable lncR-
NAs, XIST increases collagen degradation in OA chon-
drocytes via increasing TIMP3 promoter methylation
through the recruitment of a DNA methyltransferase106.
Furthermore, in OA cartilage, expression of the lncRNAs
H19 and LINC01534 is increased and ECM degrada-
tion is promoted through their individual binding to
miR-140-5p137,138, an miRNA that is well characterized in
OA for its cartilage matrix remodelling effects139. Roles
for circRNAs (TABLE3) and snoRNAs28,140,141 have also been
described in ECM metabolism. For example, impaired
expression of U3 snoRNA, SNORD26 or SNORD96A
alters the protein translation capacity of chondrocytes,
chondrocyte differentiation, pro-inflammatory pathways
and the expression of markers of OA28,141.
Notably, ECM dysregulation can actually facilitate
intercellular communication by making otherwise dense
cartilage and bone matrices more permeable to extra-
cellular vesicles that carry non-coding RNAs. Evidence
from RA suggests that both chondrocytes and osteo-
blasts can respond to miRNAs carried by FLS-derived
exosomes. In one study, exosomes from FLSs carrying
miR-106b induced chondrocyte apoptosis and reduced
proliferation by directly targeting PDK4 mRNA142.
In another study, exosomes from FLSs carrying
miR-486-5p were phagocytosed by osteoblasts and pro-
moted their differentiation and the expression of ECM
markers such as type I collagen143. Given that inflamed
and hyperplastic synovium is a common feature of RA,
exosomes secreted by FLSs could serve as messengers to
induce damage in surrounding joint tissues.
Therapeutic potential
Non-coding RNAs represent promising therapeu-
tic targets in OA and RA because their activity can be
modulated via small molecules and biological delivery
systems (such as exosomes144–146) to reduce features
of disease, and even pain, in experimental models of
arthritis147,148. The cargo of these delivery systems can
include non-coding RNA mimics (known as agomirs),
non-coding RNA inhibitors (known as antagomirs) and
other molecules, such as transcription factors. For exam-
ple, in mouse cells invitro, the lncRNA MM2P promotes
macrophage polarization towards an M2-like pheno-
type and stimulates the release of exosomes containing
SOX9 mRNA and protein from these cells, which can
induce the production of ECM components in cultured
chondrocytes149. As these exosomes contain a functional
transcription factor (SOX9) that is known to promote
chondrocyte anabolism, they represent a potential
therapeutic strategy to restore cartilage homeostasis.
An important consideration in harnessing the
potential of non-coding RNAs as possible therapeu-
tics is the route of administration, whether systemic or
intra-articular, so that the therapy can reach the intended
target tissues. Systemic administration of non-coding
RNAs can be achieved by intravenous injection. Using
this method, an miR-365 agomir decreased disease
severity in mice with CIA, potentially through downreg-
ulation of IGF1 (REF.78). Similarly, following intravenous
injection, the concentration of an miR-26a mimic was
increased in articular cartilage and could reduce disease
severity in rats with CIA through the downregulation of
connective tissue growth factor (CTGF)150. Intravenous
injection of exosomes has also been explored.
BMSC-derived exosomes enriched with miR-320a,
which directly downregulates C-X-C chemokine
ligand 9, could decrease disease severity in mice with
CIA following intravenous injection151. Furthermore,
BMSC-secreted exosomes enriched with miR-192-5p
could be found in the synovial tissue of rats with CIA
after intravenous injection, and could decrease disease
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severity, potentially through downregulation of the
signalling molecule RAC2 (REF.152). These data suggest
that non-coding RNAs were able to traffic to the joints
in rats and mice with CIA, where they reduced syno-
vial inflammation, cartilage damage and bone erosion.
However, because a single non-coding RNA can have
multiple gene targets, local modulation (such as direct
injection of miRNA agomirs and antagomirs into the
joint) is also being explored to avoid unwanted systemic
effects. In mice with CIA, intra-articular delivery of
miR-146a-5p agomir decreased disease activity, synovial
hyperplasia, the invasiveness of the pannus and cartilage
erosion, potentially through downregulation of CTGF153.
Similarly in rats with CIA, intra-articular delivery of
miR-141-3p agomir improved disease outcomes via
direct binding of the transcription factor FOXC1, which
functions as an oncogene to promote tumour and RA
FLS proliferation154. Intra-articular delivery of exosomes
is also possible, and exosomes can even be engineered
to target cells of interest. For example, the fusion of
chondrocyte-affinity peptide to lysosome-associated
membrane glycoprotein 2b molecules on the surface
of exosomes promoted the trafficking and fusion of the
exosomes to chondrocytes, the efficient delivery of
miR-140 and the mitigation of disease progression in a
rat surgical model of OA155.
Alternative strategies for non-coding RNA modula-
tion continue to emerge. For example, transplantation of
cartilage pellets derived from human BMSCs that over-
express beneficial miRNAs (such as miR-27b) inhibited
hypertrophic chondrocyte differentiation during carti-
lage defect repair156. Similarly, intra-articular injection
of human umbilical cord-derived mesenchymal stem
cells transfected to overexpress miR-140 had protec-
tive effects in a rat model of OA157. A biodegradable
delivery system for an miR-365 antagomir based on
non-pathogenic yeast cell wall particles has been devel-
oped that could resist degradation in the gastrointes-
tinal system following oral administration, and which
reduced features of disease in a mouse surgical model
of OA102. Furthermore, cationic liposomes (lipoplexes)
have been used for the intra-articular administration of
miR-17-5p to reduce synovial immune cell infiltration,
inflammation and bone erosion in mice with CIA72.
As an alternative means of suppressing miRNA function,
tough decoy RNAs have been developed, wherein vectors
expressing miRNA target sites bind and reduce specific
miRNA activity in cells; a tough decoy for miR-195-5p
reduced its activity and the occurrence of hypertrophy
in cultured chondrocytes158. Moreover, miRNA agomirs
and antagomirs can be directly modified to improve
their therapeutic properties. To improve specific bind-
ing, locking the conformation of antagomirs (known
as locked nucleic acids) is effective, and intra-articular
delivery of locked nucleic acid antagomirs for
miR-181a-5p and miR-34a-5p could reduce disease
severity in experimental models of OA159,160. To improve
stability and delivery, non-coding RNAs can be conjugated
to other molecules such as atelocollagen; intra-articular
administration of an miR-9a-5p agomir–atelocollagen
complex could effectively reduce disease severity in
rats with CIA161. Additional delivery mechanisms and
considerations for achieving clinical translation of anti-
sense oligonucleotide-based therapies for OA have been
reviewed in detail elsewhere104,162.
Studying the interactions among non-coding
RNAs, including regulators and effectors of circRNA–
miRNA–mRNA axes, could also reveal new avenues
for targeted treatment. One molecular mechanism pro-
posed as a prospective therapeutic target for OA is the
circRNF121–miR-665–MYD88 axis, which is regulated
by the transcription factor LEF1 (REF.163). In human chon-
drocytes, LEF1 increases the expression of circRNF121,
which functions as a sponge for miR-665, thereby
indirectly targeting MYD88. As such, modulation of
miR-665 and circRNF121 could alter MYD88 expression
to promote chondrocyte apoptosis, proliferation and
ECM degradation, both invitro in human chondrocytes
and invivo in a rat model of OA. Furthermore, this axis
was shown to activate the NF-κB signalling pathway163.
Although the data suggest that miR-665 could be tar-
geted to mitigate the detrimental effects of circRNF121,
it is evident that the upstream regulator (LEF1), circRNA
(circRNF121), miRNA (miR-665), gene target (MYD88)
and downstream pathway (NF-кB) could all be potential
targets. These data illustrate the importance of consid-
ering the non-coding RNA interactome for therapeutic
targeting, as one or more of these factors might need to
be modulated to improve disease outcomes (BOX1).
On the basis of the current literature, outstanding
questions remain to be answered before targeting of
non-coding RNAs can be translated into a therapeutic
strategy to improve patient care. First, the appropriate
target must be identified, whether it is the non-coding
RNA, its upstream regulator or the downstream medi-
ator. Second, the appropriate tissue or tissues must be
identified for targeting, as non-coding RNAs are known
to have tissue-specific effects. Third, the appropriate
Box 1 | The non-coding RNA interactome in gene expression regulation
Theregulationofgeneexpressionistightlycontrolled.Non-codingRNAshave
importantrolesinthisprocess,operatingthroughdirectmechanisms(suchas
degradationofgenetranscripts)andindirectmechanisms(suchasinhibitionof
othernon-codingRNAs).Together,thesemechanismscomprisethenon-codingRNA
interactome,whichcanbethoughtofasthecompletesetofthemolecularinteractions
ofnon-codingRNAs.Emergingliteraturesuggeststhatinteractionsamongnon-coding
RNAentitiesandclassesarecommonandhaveconsiderableimplicationsforjoint
diseases.High-throughputprofilingisausefulapproachforbeginningtounravelthe
non-codingRNAinteractome.Forexample,researchershaveusedthreepublicly
availablemicroarraydatasetsforsynoviumfrompatientswithrheumatoidarthritis
(RA)todemonstratepotentialdirectregulationofinterconnectedgenetargetsby
specificlongnon-codingRNAs(lncRNAs),whereinthelncRNAsNEAT1andFAM30A
werepredictedtointeractwithmajorRAhubgenes192.Toexploreinteractionsacross
non-codingRNAclasses,circularRNA(circRNA)–microRNA(miRNA)networkshave
beenconstructedforsynovium193,cartilage194andchondrocytes133,195frompatientswith
osteoarthritis(OA).Forexample,researchershaveusedRNAsequencingtoidentify
OA-relatedcircRNAsincartilage,followedbybioinformaticsanalysestodiscover
166,394circRNA–miRNA–mRNAaxes194.LncRNA–miRNAnetworkshavealsobeen
exploredinOA.Inhumankneecartilage,publiclyavailableRNAsequencingdatahave
beenminedtoidentifydifferentiallyexpressedlncRNAsandmRNAsthatcontribute
toanintegratednetworkofcompetingendogenousRNAs,including10lncRNAs,
69miRNAsand72mRNAs196.Theseindividualprofilingstudiesareanimportantfirst
steptowardsunderstandingthenon-codingRNAinteractome,butneedtobefollowed
byeffortstointegratefindingsacrossstudiessothatcandidatesforfurthervalidation
andpotentialtherapeutictargetingcanbeprioritized.
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delivery mechanism must be identified, including the
vehicle (such as exosomes) and route of administration.
For example, intra-articular delivery might offer ben-
efits over systemic administration by providing local
modulation and thereby reducing unwanted off-target
effects. The answers to these questions and others (such
as the best dosage to use) might be patient-specific,
and tailored RNA-based therapeutics might need
to be administered in a phenotype-dependent manner to
achieve precision medicine in OA and RA. The utility of
RNA-based therapeutics has now achieved global recog-
nition through RNA vaccines, which were first described
over two decades ago164, and it is therefore reasonable
to expect bolstered research efforts into RNA-based
therapeutics, which should include non-coding RNAs.
Future directions
Unravelling the complex interactions among non-coding
RNAs is becoming an important goal; however, the com-
prehensive high-throughput profiling of joint tissues
and biofluids that will be necessary to achieve this aim
comes with its own set of challenges (TABLE4). Although
microarrays are useful for profiling a pre-selected sub-
set of known candidate RNAs, this technique is lim-
ited by factors such as the appropriate selection of an
endogenous reference, which can vary by tissue type165.
Increasingly, next-generation sequencing technologies
are being used to achieve unbiased and quantitative
measures of all varieties of non-coding RNAs. For exam-
ple, next-generation sequencing can be used to identify
the direct binding of miRNAs to target genes through
RNA-immunoprecipitation and high-throughput
sequencing (RIP sequencing), as has been described in
human articular chondrocytes166. This approach ena-
bles the validation of predicted gene targets that are
commonly obtained using prediction tools (TABLE4).
Furthermore, applying sequencing technology to fun-
damental processes in model systems has the potential
to uncover important mechanisms that underlie disease.
For example, combinations of RNA sequencing and
small non-coding RNA sequencing have been applied
to explore chondrogenesis and metabolism in human
BMSCs167, inflammatory cytokine responses in mouse
induced pluripotent stem cells168 and cartilage ageing in
horse chondrocytes140.
Among the limitations of unbiased discovery of
non-coding RNAs is that researchers often focus on just
one or two molecules for further investigation. How and
why these molecules are chosen can be unclear, as other
non-coding RNA entities that could have promising
roles in joint pathobiology are often not investigated
further. Notably, very few non-coding RNA studies in
OA and RA include comparisons with other studies or
meta-analyses with other available non-coding RNA
datasets in order to validate, expand and build a com-
prehensive interactome of these important epigenetic
regulators. However, efforts are ongoing around the
world to curate comprehensive databases of published
evidence to help researchers to investigate the complex
interactions between non-coding RNAs, genes and pro-
teins (TABLE4). To this end, it is critical that nomenclature
and annotations for the non-coding RNAs identified in
studies are systematically reported. For example, inves-
tigators are encouraged to report the strands of miRNAs
(3p or 5p) to ensure accurate integration of their data
with other datasets and analyses. Furthermore, report-
ing of the clinical annotation of samples involved in
non-coding RNA studies is required to enable correla-
tion with molecular and clinical phenotypes. Finally, to
improve the quality of basic and translational research
by applying integrative analytical and machine learning
techniques, well-annotated high-throughput data must
be made available in the correct format (for example, the
raw sequencing datasets) in online repositories.
Conclusions
A substantial surge has occurred in the number of pub-
lished articles related to non-coding RNAs in OA and
RA in the past few years, mostly for miRNAs, lncRNAs
and circRNAs, and to a lesser degree for snoRNAs,
Table 4 | Use of bioinformatics and computational biology tools in non-coding RNA research
Challenge Approach Resources
Analysing high-throughput profiling
data for non-coding RNAs in both
health and disease contexts
A search tool can be used to discover novel
non-coding RNA sequences in deep sequencing data
miRDeep2
Ensuring proper and consistent
naming of all non-coding RNA
entities so that data can be
accurately integrated across studies
Several databases are helpful to ensure the correct
use of primary names and identifiers
miRbase for microRNAs; DIANA-lncBase for long
non-coding RNAs; circBase and circAtlas for circular
RNAs; and Hugo Gene Nomenclature for gene names
Elucidating the potential functions of
non-coding RNAs
Multiple tools can be used for target gene prediction,
including for novel microRNA sequences
TargetScan; mirDIP; miRDB; and miRanda
Interpreting predicted target genes Pathway prediction tools can be used to create
functional groups with biological relevance
(such as signalling cascades)
The Gene Ontology Resource for gene enrichment
analysis; pathDIP for integrated pathway enrichment
analysis; and integrated web portals, such as
Enrichr, for access to diverse types of computational
annotation and overrepresentation analysis
Combining non-coding RNA
datasets to promote integrative
computational analyses
Public repositories can be used to access and deposit
high-throughput data
The NCBI Gene Expression Omnibus repository; the
NCBI Sequence Read Archive; the NCBI Database
of Genotypes and Phenotypes; and the EMBL-EBI
European Nucleotide Archive
EMBL-EBI, European Molecular Biology Laboratory European Bioinformatics Institute; NCBI, National Center for Biotechnology Information.
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tRFs and other non-coding RNAs. This increased
research output has been possible because of advances
in next-generation sequencing technology and the
availability of computational and analytical tools for
data mining. Some of the non-coding RNAs that have
been identified using these methods, as well as their
regulatory interactome, could have crucial roles in joint
health and disease, affecting biological processes and
functioning as biomarkers, mediators of pathogenesis
and potential therapeutic targets. Although these dis-
coveries are promising, a concerted effort is required to
validate, integrate and translate findings from current
studies to harness the full potential of non-coding RNAs
in OA and RA.
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Acknowledgements
The work of M.J.P. is supported by a Wellcome Trust
Intermediate Clinical Fellowship (107471/Z/15/Z) and by the
Medical Research Council and Versus Arthritis as part of
the Medical Research Council Versus Arthritis Centre for
Integrated Research into Musculoskeletal Ageing
(MR/R502182/1). The work of M.J.O. is supported by the
Veterans Health Administration CDA (IK2CX001269) and by
an Arthritis Foundation Delivering on Discovery grant. I.J. is
also at the Departments of Medical Biophysics and Computer
Science, University of Toronto, Toronto, Ontario, Canada and
the Institute of Neuroimmunology, Slovak Academy of
Sciences, Bratislava, Slovakia. The work of I.J. was funded in
part by the Ontario Research Fund (no. 34876 and GL2-01-
030), the Natural Sciences Research Council (NSERC
no. 203475), Genome Canada (DIG2 no. 14408), the Canada
Foundation for Innovation (CFI no. 29272, no. 225404,
no. 33536) and the Canada Research Chair Program (CRC
no. 203373 and no. 225404). Additional support is provided
by the Schroeder Arthritis Institute via the Toronto General and
Western Hospital Foundation, University Health Network.
The work of M.K. is supported by the Canadian Institute
of Health Research Operating grant (no. 156299) and the
Tier 1 Canada Research Chair Award (no. 950-232237).
Author contributions
The authors contributed equally to all aspects of the article.
Competing interests
S.A.A. and M.K. declare that they have filed a US Provisional
Patent Application no. 63/033,463 titled “Circulating
MicroRNAs in Knee Osteoarthritis and Uses Thereof”. The
other authors declare no competing interests.
Disclaimer
None of the funders had a role in study design, data collection
and analysis, decision to publish or preparation of the
manuscript.
Peer review information
Nature Reviews Rheumatology thanks S. Jones and the other,
anonymous, reviewer(s) 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.
Review criteria
A literature search was performed in PubMed for articles
published in the past 2 years using combinations of the fol-
lowing key words: “osteoarthritis”, “rheumatoid arthritis”,
“microRNA”, “long non-coding RNA”, “circular RNA”, “small
nucleolar RNAs” and “transfer RNAs”. Some highly relevant
papers outside the search criteria were also included.
RELATED LINKS
circAtlas: http://159.226.67.237:8080/new/index.php
circBase: http://www.circbase.org/
DIANA-lncBase: https://diana.e-ce.uth.gr/lncbasev3
EMBL-EBI European Nucleotide Archive: https://www.ebi.
ac.uk/ena/browser/home
Enrichr: https://maayanlab.cloud/Enrichr/
Gene Ontology Resource: http://geneontology.org
Hugo Gene Nomenclature: https://www.genenames.org/
miRanda: https://bioweb.pasteur.fr/packages/
pack@miRanda@3.3a
miRbase: http://www.mirbase.org/
miRDB: http://mirdb.org/
miRDeep2: https://github.com/rajewsky-lab/mirdeep2
mirDIP: http://ophid.utoronto.ca/mirDIP/
NCBI Database of Genotypes and Phenotypes:
https://www.ncbi.nlm.nih.gov/gap/
NCBI Gene Expression Omnibus repository:
https://www.ncbi.nlm.nih.gov/gds
NCBI Sequence Read Archive: https://www.ncbi.nlm.nih.gov/sra
pathDIP: http://ophid.utoronto.ca/pathDIP/
TargetScan: http://www.targetscan.org/vert_72/
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