Why do we have no effective treatments for osteoarthritis?

Due to the increasing mean age of the global population, it is believed that OA will become the fourth leading cause of disability worldwide by 2020.⁵ Symptoms vary from moderate pain to disability – which in turn can lead to low mood and depression6 – as well as progressive cartilage loss, subchondral bone thickening, osteophyte formation and joint space narrowing.² Growing evidence implicates the impairment of several physiological mechanisms in the pathogenesis of OA,^7-9 and despite these recent advances in understanding the pathogenesis of OA thus far, they have failed to deliver any disease-modifying therapeutics.

Current therapeutics

Depending on the severity of OA, patients are firstly advised to lose weight and modify their lifestyles through diet and exercise.¹⁰ Use of supplements including glucosamine and chondroitin is common; however, the efficacy of these supplements remains controversial.¹¹ Topical creams are also used to reduce local pain, but patients are usually initially prescribed oral paracetamol and/or non-steroidal anti-inflammatory drugs.¹² Further treatment involves intra-articular injections of corticosteroids, hyaluronic acid or biologics (and new intra-articular injectable drugs are in the pipeline).¹³ The end-point treatment for OA remains that of joint replacement surgery,¹⁴ which offers less pain and improvements in physical function, yet many patients don’t reach the comparable mobility level of their population peers.¹⁴ Furthermore, a person’s age and state of health (ie, any comorbidities) may exclude them from joint replacement surgery, particularly when further surgery is required on other joints or the same joint in the future.¹⁵ Hence, more research is required to find effective therapies to tackle OA.

Challenges in drug discovery

Unlike the case of rheumatoid arthritis, where TNF-α inhibitors have been blockbuster successes, there are no precise causative targets in OA (that we know of) that will have the same impactful therapeutic benefit.¹⁶ The lack of effective targets makes OA drug discovery highly challenging and less attractive. In addition, the OA field has reached a consensus that the disease has different patient subsets that require greater classification and will impact drug discovery in the future.¹⁷ Another challenge is translating pre-clinical modelling data into human clinical trials. The field has made progress in the last two decades in establishing disease models of cartilage degradation, ageing, pain and joint injuries; but these models are not readily translating the benefits seen in vivo to man.¹⁸ The final challenge remains that of endpoints in clinical trials. Disease biomarkers are lacking, and patient-reported outcomes are not reliable (high placebo effects),¹⁹ producing data with a high degree of variability.²⁰ Furthermore, the slow progressive and unpredictable nature of the disease means trials are not cost effective.

What we must achieve together

If drug discovery was a sport, the player might have to play for a lifetime to see a win. However, we know from past experiences that big wins are possible. The hurdles faced in OA drug discovery are challenging but can be satisfying if we work together with the right mindset. We must be open to the possibility that multiple factors may drive different disease phenotypes (ie, obesity-associated OA, trauma-associated OA, ageing-associated OA) and targeting one risk factor may not produce the desired silver bullet. The field is moving in the right direction by focusing on better patient stratification, which will help to identify treatments for specific patient subsets in the future.²¹ This requires a global consensus on how to conduct both translational research and basic science research. The use of in vivo models of OA has made many scientific discoveries possible in the field.^18,22 However, more must be done to train young researchers regarding the use/consideration of multiple models of OA in their research. Utilising different animal models in a single study will take time (and resources) but yield more realistic translatable datasets. The use of mouse models has been invaluable to the field, but larger animal models may be better suited for producing results that are more comparable to human OA.²³ Finding a suitable infrastructure to enable basic science labs access to larger animal models will be a challenge, but arguably rewarding if met. Finally, we need to address the elephant in the room: how we can efficiently track disease progression in trials. In recent years, the OA field has concentrated its efforts on biomarker research,²⁴ but more needs to be done. The latest approach of patient stratification should be conducted with extensive ‘omics’ approaches to identify biomarkers for different patient subsets. This can only happen with global collaboration where each party contributes their scientific strengths, biobank samples and patient data (if possible) to the larger mission. The acceleration into biomarker discovery should be accompanied by the expansion in OA imaging research. A solution to the dilemma of lengthy trials and the current poor endpoint readouts is to produce imaging-based endpoints to test drug efficacy.

Conclusions

In all, we need to chip away together on four main goals: (i) better patient stratification for disease phenotyping; (ii) development of imaging-based efficacy endpoints; (iii) diversifying the use of animal models in basic science; and (iv) finding better biomarkers for different patient subsets. I am in awe of the myriad drug discoveries that have been made and ask myself ‘why not in OA?’. I am optimistic that major breakthroughs in the quest for effective OA treatments will come in my lifetime.

Biography

Dr Pradeep Sacitharan obtained his D.Phil in Cellular and Molecular Medicine at the University of Oxford investigating disease pathways in osteoarthritis. Thereafter, he received the EIT fellowship (University of Oxford), Fulbright All Disciplines Research Award (Harvard Medical School), Daniel Turnberg Fellowship (Hebrew University of Jerusalem) and an EMBO fellowship (Sorbonne University) to continue his research with world leaders in the field. His research has been highly recognised, leading to numerous international prizes. Currently, he is based at the Institute of Aging and Chronic Disease, University of Liverpool.

References

1. Bijlsma JWJ, Berenbaum F, Lafeber FPJG. Osteoarthritis: an update with relevance for clinical practice. Lancet [Internet]. 2011 Jun 18 [cited 2014 Mar 21];377(9783):2115–26. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21684382
2. Glyn-Jones S, Palmer AJR, Agricola R, Price AJ, Vincent TL, Weinans H, et al. Osteoarthritis. Lancet [Internet]. 2015;386(9991):376–87. Available from: http://linkinghub.elsevier.com/retrieve/pii/S0140673614608023
3. Ma VY, Chan L, Carruthers KJ. Incidence, prevalence, costs, and impact on disability of common conditions requiring rehabilitation in the united states: Stroke, spinal cord injury, traumatic brain injury, multiple sclerosis, osteoarthritis, rheumatoid arthritis, limb loss, and back pain. Archives of Physical Medicine and Rehabilitation. 2014.
4. Yelin E, Murphy L, Cisternas MG, Foreman AJ, Pasta DJ, Helmick CG. Medical care expenditures and earnings losses among persons with arthritis and other rheumatic conditions in 2003, and comparisons with 1997. Arthritis Rheum. 2007
5. Woolf AD, Pfleger B. Burden of major musculoskeletal conditions. Bull World Health Organ. 2003;81(9):646–56.
6. Neogi T. The epidemiology and impact of pain in osteoarthritis. Osteoarthr Cartil. 2013;
7. Kapoor M, Martel-Pelletier J, Lajeunesse D, Pelletier JP, Fahmi H. Role of proinflammatory cytokines in the pathophysiology of osteoarthritis. Nat Rev Rheumatol [Internet]. 2011;7(1):33–42. Available from: http://dx.doi.org/10.1038/nrrheum.2010.196
8. Sacitharan PK, Vincent TL. Cellular ageing mechanisms in osteoarthritis. Mamm Genome [Internet]. 2016;27(7):421–9. Available from: http://dx.doi.org/10.1007/s00335-016-9641-z
9. Mobasheri A, Rayman MP, Gualillo O, Sellam J, Van Der Kraan P, Fearon U. The role of metabolism in the pathogenesis of osteoarthritis. Nature Reviews Rheumatology. 2017.
10. Yusuf E. Pharmacologic and Non-Pharmacologic Treatment of Osteoarthritis. Curr Treat Options Rheumatol. 2016
11. Wieland HA, Michaelis M, Kirschbaum BJ, Rudolphi KA. Osteoarthritis – an untreatable disease? Nat Rev Drug Discov [Internet]. 2005 Apr [cited 2014 Mar 19];4(4):331–44. Available from: http://www.ncbi.nlm.nih.gov/pubmed/15803196
12. Cheng DS, Visco CJ. Pharmaceutical therapy for osteoarthritis. PM R [Internet]. 2012 May [cited 2014 Apr 22];4(5 Suppl):S82-8. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22632707
13. Thysen S, Luyten FP, Lories RJU. Targets, models and challenges in osteoarthritis research. Dis Model Mech. 2015
14. OARSI. Osteoarthritis: A Serious Disease, Submitted to the U.S. Food and Drug Administration. Oarsi [Internet]. 2016; Available from: https://www.oarsi.org/sites/default/files/docs/2016/oarsi_white_paper_oa_serious_disease_121416_1.pdf
15. Fang M, Noiseux N, Linson E, Cram P. The Effect of Advancing Age on Total Joint Replacement Outcomes. Geriatr Orthop Surg Rehabil. 2015.
16. Calich ALG, Domiciano DS, Fuller R. Osteoarthritis: Can anti-cytokine therapy play a role in treatment? Clin Rheumatol. 2010;29(5):451–5.
17. Kraus VB, Blanco FJ, Englund M, Karsdal MA, Lohmander LS. Call for standardized definitions of osteoarthritis and risk stratification for clinical trials and clinical use. Osteoarthritis and Cartilage. 2015.
18. Fang H, Beier F. Mouse models of osteoarthritis: modelling risk factors and assessing outcomes. Nat Rev Rheumatol [Internet]. 2014 Jul [cited 2014 Jul 15];10(7):413–21. Available from: http://www.ncbi.nlm.nih.gov/pubmed/24662645
19. Bannuru RR, Schmid CH, Kent DM, Vaysbrot EE, Wong JB, McAlindon TE. Comparative effectiveness of pharmacologic interventions for knee osteoarthritis: A systematic review and network meta-analysis. Annals of Internal Medicine. 2015.
20. McAlindon TE, Driban JB, Henrotin Y, Hunter DJ, Jiang GL, Skou ST, et al. OARSI Clinical Trials Recommendations: Design, conduct, and reporting of clinical trials for knee osteoarthritis. Osteoarthritis and Cartilage. 2015.
21. Berenbaum F. Deep phenotyping of osteoarthritis: a step forward. Ann Rheum Dis [Internet]. 2019 Jan 1;78(1):3 LP-5. Available from: http://ard.bmj.com/content/78/1/3.abstract
22. Little CB, Hunter DJ. Post-traumatic osteoarthritis: from mouse models to clinical trials. Nat Rev Rheumatol. 2013;9(8):485–97.
23. Cope PJ, Ourradi K, Li Y, Sharif M. Models of osteoarthritis: the good, the bad and the promising. Osteoarthr Cartil [Internet]. 2019 Feb 1 [cited 2019 Jan 29];27(2):230–9. Available from: https://www.sciencedirect.com/science/article/pii/S1063458418315073
24. Lotz M, Martel-Pelletier J, Christiansen C, Brandi ML, Bruyère O, Chapurlat R, et al. Value of biomarkers in osteoarthritis: current status and perspectives. Ann Rheum Dis [Internet]. 2013 Nov 1 [cited 2019 Jan 29];72(11):1756–63. Available from: https://ard.bmj.com/content/72/11/1756