ABSTRACT. This review of osteoarthritis literature is focused on recently published (post 2010) articles, but older articles of importance are included as well. The review is thorough but not necessarily comprehensive. An emphasis has been placed on summarizing information that relates to prediction and prevention of osteoarthritis.
- OVERVIEW
Osteoarthritis (OA) is a degenerative joint disease (Tanchev, 2017). The word “osteoarthritis” can be broken down into “osteo” (bone) “arthr-” (joint) and “itis” implying inflammation. This can be misleading because inflammation is not a primary feature of the degenerative disease. Technically, “osteoarthrosis” means degeneration of the joint while “osteoarthritis” means inflammation of the joint. To be clear, here we will use “osteoarthritis” or “osteoarthrosis” to refer to the degenerative joint disease. Note that rheumatoid arthritis is primarily an inflammatory pathologic entity. Erosive osteoarthritis is a rare subtype of generalized osteoarthritis (Punzi, 2004). Low-grade inflammation does appear to play a role in OA; Inflammatory mediators play a pivotal role in the initiation and perpetuation of the OA process (Barenbaum, 2013).
The UK Biobank is an international health resource for those working to prevent disease, including OA (UKBiobank, 2020). During the years 2006– 2010 the UK Biobank recruited 500, 000 people aged 40 − 69 to take part in their project. Each person was measured, provided blood, urine, and saliva samples, and agreed to have their health followed. UK Biobank data refers to osteoarthrosis of the hip, knee, and other joints including categories for shoulder, upper arm, forearm, hand, pelvic region and thigh, lower leg, ankle and foot, other, site unspecified, and multiple. According to the US National Institute of Arthritis and Musculoskeletal and Skin Diseases, the joints most commonly affected by OA include hands (ends of the fingers and at the base and ends of the thumbs), knees, hips, neck, and lower back (NIAMS, 2020). OA is characterized by progressive cartilage destruction in
FIGURE 1. Osteoarthritis: Image obtained from AAOS weight-bearing areas of the joints and osteophyte (bone spur) formation in the non-weight-bearing parts (Guincamp et al., 2000).
The strict definition of OA excludes many individuals with OA. The expanded definition of Cisternas et al. (2016) has an optimal combination of sensitivity and specificity. Cisternas et al. (2016) estimate that 13.4% of the US adult population (25-74 years of age) has OA. Global prevalence of OA increased 32.9% from 2005 to 2015 (Murray and Vos, 2016). About half of respondents, aged 50+, to a survey in the UK reported suffering from OA (Oo et al., 2018). The World Health Organization reports that 10% − 15% of adults worldwide over 60 years of age have some degree of OA, with wide variation, as low as 2.8% in Romania compared to 18.3% in Hungary (WHO, 2020). Worldwide, OA is about twice as common in women than men (WHO, 2020). Global adult prevalence of symptomatic OA is expected to rise to 35% in 2030, making it the single greatest cause of disability globally (Oo et al., 2018). Muskuloskeletal disorders currently make up 6.7% of global years of healthy life lost due to disability (March, 2014). For further information on OA incidence and prevalence relating to age see Anderson and Loeser (2010) and Figure 2. OA incidence starts rising at about 40 years of age and peaks at 70 or 80 years of age (Zhang and Jordan, 2010, Figure 1). Age-adjusted, global prevalence is about 3.80% for knee OA and about 0.85% for hip OA (Cross et al., 2013)
- SYMPTOMS
The Mayo Clinic (2020) lists the following symptoms of osteoarthritis: pain, stiffness, tenderness, loss of flexibility, a grating sensation, bone spurs, and swelling. Figure 3 shows representations of a healthy joint and a joint with severe OA. Figure 4 shows X-ray images of a healthy knee and a knee with OA. About a third of people whose x rays show evidence of osteoarthritis report pain or other symptoms (NIAMS, 2015). Later in Section 5 we will discuss diagnosis of OA and the role that pain plays in the diagnosis. Random weather fluctuations, especially changes in atmospheric pressure, have been observed to be associated with OA pain (Figueiredo, Figueiredo, and Dantas, 2010). Exercise may reduce pain (Sinusas, 2012).
FIGURE 2. Age and prevalence of OA
- CAUSES
Brandt, Dieppe, and Radin (2009) believe “OA is best defined as failed repair of damage that has been caused by excessive mechanical stress (defined as force/unit area) on joint tissues,” and that “the inflammatory changes in OA are secondary and are caused by particulate and soluble breakdown products of cartilage and bone.” Osteoarthritis is a group of overlapping distinct diseases which may have different etiologies (Brandt, Dieppe, and Radin, 2009). OA reflects a process within the joint that is attempting to contain damage caused by a local mechanical problem. There are many similar diseases labeled as OA. Brandt, Dieppe, and Radin (2009) argue that the primary vs secondary distinction is not meaningful, because OA is always secondary to something.
The OA disease process may be unique to each individual (Chu and An driacchi, 2014). About one third of the middle aged to elderly population has experienced a torn meniscus (England et al., 2012), and meniscal repair surgery may relieve pain but increase risk for OA (England et al., 2012). Clinical and laboratory evidence in humans and animals supports an effect of diabetes on OA (King and Rosenthal, 2015). There are some randomized controlled trials that provide some evidence that lack of exercise can cause OA (Fransen et al., 2014). As long as injury is avoided, exercise does not appear to accelerate the development of osteoarthritis, and it can reduce pain and disability (Bosomworth, 2009). Increased loading on knee or hip joints is probably the main mechanism by which obesity causes OA (Zhang and Jordan, 2010). There are strong associations between obesity and knee OA (Coggon et al., 2001). Knuckle cracking probably does not cause hand OA (deWeber, Olszewski, and Ortolano, 2011).
FIGURE 3. Representations of (top) a healthy joint and (bot tom) a joint with severe OA
Chondrocytes are the only cells found in healthy cartilage. Mechanical stress alters chondrocytes which may contribute to OA development (Guincamp et al., 2000). Repetitive loading of articular cartilage may result in substantial changes of chondrocyte metabolism that ultimately lead to signaling pathways, causing either hypertrophy or apoptosis (Guincamp et al., 2000). A number of molecules and pathways are inhibited by avocado/soybean unsaponifiables (Christiansen et al., 2015), making diet into a plausible cause. Avocado/soybean unsaponifiables are protective (Boileau et al., 2009).
According to Anderson and Loeser (2010) “Aging changes in the musculoskeletal system increase the propensity to OA but the joints affected and the severity of disease are most closely related to other OA risk factors such as joint injury, obesity, genetics, and anatomical factors that affect joint mechanics”. Pre-osteoarthritis (pre-OA) refers to conditions where clinical OA has not yet developed but joint homeostasis has been compromised (Chu and Andriacchi, 2014). OA has an initiation phase and a progression phase (Andriacchi et al., 2004). The initiation phase is associated with kinematic changes that shift load bearing to infrequently loaded regions of the cartilage. The progression phase is defined after cartilage breakdown, and during the progression phase the disease progresses more rapidly with increased load (Andriacchi et al., 2004). There are three broad categories of risk factors for pre-OA. The categories are biology, mechanics, and structure (Chu and An driacchi, 2014). According to Chu and Andriacchi (2014) “a continuously shifting balance of these factors over time ultimately determines whether joint health is maintained or whether the joint shifts into high-risk pre osteoarthritic states and ultimately to irreversible clinical osteoarthritis”. The biology category includes factors that influence cell metabolism, the mechanical category includes any factor that delivers a mechanical stimulus to the cell (i.e. the mechanics of ambulation), and the structural category includes factors like joint alignment and ligament properties (Chu and An driacchi, 2014).
A number of biochemical and biophysical parameters change with aging and change differently in the presence of OA (Grushko, 1988). Osteoarthritis pain is associated with bone marrow lesions (Felson et al., 2001), and pain leads to diagnosis of OA. Careful statistical analysis reveals six symptoms and signs that predict radiographic knee OA (Zhang et al., 2010). The symptoms are persistent knee pain, limited morning stiffness, and reduced function. The signs are crepitus (a grating sound or sensation), restricted movement and bony enlargement. Healthy cartilage is characterized by a low turnover of collagens, whereas the turnover rate of aggrecan is relatively high (Tchetina, 2011). Aggrecan is a protein that in humans is encoded by the ACAN gene. Protein turnover refers to the continual renewal or replacement of protein. Biomarkers are available for cartilage degradation and formation (Gudmann et al., 2014). Endogenous and exogenous hormones are associated with cartilage and bone turnover (Tanamas et al., 2011).
The following comments are derived from information gained in attendance at the 2020 annual conference of the International Society for Environmental Epidemiology. There were some talks referencing “tissue-specific gene expression.” Gamini et al. (2017) have conducted a genome-wide analysis of the cartilage-specific gene expression pattern. They identified several transcription factors that are enriched in cartilage as potential candidates for therapeutic targets. Ni et al. (2015) have linked prenatal ethanol exposure with OA later in life. In exposed rat offspring they observed down-regulation of IGF-1 signaling and retarding of articular cartilage development. Intrauterine programming by exposures and subsequent diet may predispose individuals toward higher cholesterol and osteoarthritis (Ni et al., 2015b). Early-life factors, like prenatal exposure to cigarette smoke, birth weight, and breast feeding, are associated with rheumatoid arthritis (Colebatch and Edwards, 2011). Cigarette smoke and high birth weight appear to be harmful while breastfeeding appears to be protective (Colebatch and Edwards, 2011). Evidence suggests certain systems can be ‘programmed’ by early experiences in a permanent way, eventually resulting in diseases, including OA (Cooper et al., 2009). Numerous studies (e.g. the HOME study) have demonstrated adverse effects on bone from exposures to lead, phthalates, and per- and polyfluoroalkyl substances (PFAS). Joseph Braun has observed associations between prenatal PFAS exposure and adiposity. Causes of obesity may be root causes that contribute to OA development and disease later in life.
Causal factors thus include weight, exercise, diet, and also past injuries, past environmental exposures, known structural problems, mechanical stress, and genomic variables. While treatments are most often applied after an OA diagnosis, we argue here that an effective treatment is one that removes or counteracts a likely cause of OA development. For example, experts strongly recommend weight loss as a nonpharmacologic way to manage knee OA (Hochberg et al., 2012). Other treatments shown to be effective in RCTs include exercise and some herbal dietary supplements (see Section 6).
- RISK FACTORS
Articular cartilage contains a high concentration of acid glycosaminoglycans (GAG), and the concentration gradually increases from the articular surface to the deep zone, while the profile is adapted to physiological function and mechanical properties of cartilage (Maroudas, 1976). Another older study by Bollet and Nance (1966) identified chondroitin sulfate concentration, water, and ash content as possible predictors. More recently, OA symptoms are managed with glucosamine plus chondroitin sulfate supplements, but evidence for effectiveness is sometimes weak (Grover and Samp son, 2016). Figure 1 of Grover and Sampson (2016) displays a path model showing the role of oxidative stress in cartilage damage during OA.
Georgiev and Angelov (2019) identified six categories of modifiable risk factors: weight, comorbidity, occupation, physical activity, biomechanical factors, and dietary exposures. Madry, Luyten, and Facchini (2012) identify the following as risk factors for early OA: genetic predisposition, mechanical factors such as axial malalignment, and aging. Diabetes affects articular tissues and is associated with OA (King and Rosenthal, 2015). Obesity is associated with knee OA (Coggon et al., 2001). Tanamas et al. (2011) have conducted a systematic review and found evidence that sex hormones are associated with OA.
According to Nguyen et al. (2017) there are “no key therapeutics for OA”, but they summarize promising biomarkers present in accessible biological fluids such as blood, urine, and synovial fluid. Kraus et al. (2015) recommend the use of soluble biomarkers in OA clinical trials, and suggest that such use will eventually lead to accurate identification of individuals at earlier stages of OA. Hosnijeh et al. (2015) has reviewed evidence of biomarkers for osteoarthritis and their use during risk assessment, and they distinguish between markers that predict incidence from markers that predict progression, and distinguish also between knee and hip OA.
Genomics alone is unlikely to reliably identify individuals who will develop disease, but single-nucleotide polymorphisms have been associated with hip shape, body-mass index, and bone mineral density (Glyn-Jones et al., 2015). Abnormal joint biomechanics, such as Hip dysplasia (reduction of acetabular coverage of the femoral head), Femoroacetabular impingement (abnormal contact between the proximal femur and acetabulum), bone morphology, limb alignment, unequal leg length, poor quadriceps function, and results of high intensity sports during adolescence, are associated with OA, some conferring up to 10 fold increased risk of OA development within 5 years, but most individuals with abnormal joint mechanics still don’t develop OA (Glyn-Jones et al., 2015). Bone mineral density predicts incidence but not progression (Glyn-Jones et al., 2015).
In early OA the cartilage surface may be discontinuous, showing fibrillation and vertical fissures (Madry, Luyten, and Facchini, 2012), and observation of these symptoms could be used to forecast end-stage or more severe OA. Damaged cartilage may cause inflammation and inflammatory cytokines produced during episodes of synovitis can act back on the cartilage and accelerate the destructive process of OA (Guincamp et al., 2000). Subchondral bone is the layer of bone just below the cartilage, and changes in the subchondral bone are seen with OA (Li et al., 2013). Subchondral bone sclerosis (stiffening) together with cartilage degradation is a hallmark of OA (Li et al., 2013). Factors affecting subchondral bone integrity include genetic predisposition, gender, age, weight, activity, joint injury, joint malalignment, abnormal and joint shape (Li et al., 2013). These risk factors are thought to induce OA pathogenesis as shown in Figure 5. Also, micro cracks are thought to play a vital role in the initiation and progression of OA (Li et al., 2013). Figure 6 shows a picture of microcracks.
- DIAGNOSIS
Doctors diagnose clinical OA through a review of symptoms, physical examination, X-rays, and lab tests (CDC, 2020). There are calls for careful and better definitions of OA consistent with a new taxonomy of diseases that defines and describes diseases on the basis of their intrinsic biology in addition to traditional signs and symptoms (Kraus et al., 2015b). That article by Kraus et al. (2015b) is worth a careful read. Elsewhere, there are clinical criteria for classification of symptomatic OA of the hands (Altman et al., 1990).
Cisternas et al. (2016) have a “probable OA” definition for OA that includes ICD-9-CM codes 715 (osteoarthritis and allied disorders), 716 (other and unspecified arthropathies), or 719 (other and unspecified disorders of joint). They state that their “probable” OA definition has optimal specificity and sensitivity, and they argue that people who on surveys report non-specific arthritis actually have OA. This is how they estimate that about 13% of the US adult population has OA.
Clinical symptoms can predict radiological OA but only approximately (Zhang et al., 2010). Positive predictive values increase from around 70% up to near 100% when the number of clinical symptoms increases (Sita et al., 2002). Specificities are higher than sensitivities (Sita et al., 2002). Specificities give probabilities for symptoms given radiographic OA and sensitivities give probabilities for absence of symptoms given absence of radiographic OA. Our models may produce more reliable forecasts for low-risk patients. Nonetheless, the high cost of OA makes a less reliable OA prediction cause for serious concern. One idea we had was to recommend a pre-OA test for individuals who are at high risk for OA.
FIGURE 5. OA pathogenesis as depicted in Li et al. (2013).
The problem with using symptoms to define OA is that symptoms develop only after the disease is advanced, and symptoms fluctuate (Glyn-Jones et al., 2015). In an attempt to describe OA at an early stage Glyn-Jones et al. (2015) define structural osteoarthritis as “evident cartilage loss without inflammatory or crystal arthropathy, irrespective of whether the patient has symptoms.” A limitation of that approach is an inability to predict whether structural OA will progress to clinical OA. Glyn-Jones et al. (2015) state further that “interventions used when patients have few or no symptoms must have a low-risk profile and proven effectiveness to be ethically acceptable.”
Clinical OA can be diagnosed with radiographic scoring systems (Kellgren and Lawrence, 1957; Altman and Gold, 2007), but joint space width alone is more sensitive and reliable (Gossec et al., 2009). While joint space width is accepted by the US Food and Drug Administration to prove effectiveness of disease-modifying osteoarthritis drugs, it cannot detect localized cartilage damage, and so it is unsuitable for the detection of early OA (Glyn-Jones et al., 2015). Physiological MRI permits detection of the very first changes that occur during osteoarthritis development by assessing the biochemical composition of tissue and improved MRI protocols are under development (Glyn-Jones et al., 2015). For instance, signal decay times (T2 values) are strongly correlated with water content (Chou et al., 2008).
FIGURE 6. Image of microcracks from Dr. Kuliwaba obtained from Li et al. (2013). Arrows point to linear microcracks and arrowheads point to diffuse microdamage.
- TREATMENTS
Osteras et al. (2017) have reviewed randomized, controlled trials (RCTs) studying the effect of exercise on hand OA and concluded that the quality of evidence was low and reported effect sizes small. French et al. (2011) summarize RCTs and claim that manual therapy is effective for hip and knee OA. Analysis of RCTs shows that only a few physical therapy treatments are effective for knee OA (Wang et al., 2012).
Paracetamol (acetaminophen) has only minor effects on OA related pain and function (Leopoldino et al., 2019). Stronger more reliable effects on OA pain and function were observed from a review of RCTs studying anti inflammatory NSAIDs (DaCosta et al., 2017). RCTs have shown dietary supplementation with Chondroitin to be barely effective in reducing pain (Singh et al., 2016). OA treatment with opioids reduces pain and improves function (?).
Arguments made on the basis of biological mechanisms support the claim that diet affects OA and dietary supplements may provide effective treatment of OA (Christiansen et al., 2015). Some RCTs show effectiveness of herbs, but it is not conclusive, and there are some safety concerns (Cameron et al., 2009). Silva et al. (2011) conducted a review and claim that capsaicin (from chili peppers) gel and S-adenosyl methionine are effective, and reported some evidence of effect also for Indian Frankincense, methylsulfonylmethane, and rose hip. Oral curcumin supplements appear to be safe and effective treatment for OA as shown in an RCT (Haroyan et al., 2018). However, many previous RCTs investigating a variety of outcomes failed to demonstrate effects of curcurim, and chemists have called curcumin a “highly improbable lead” (Nelson et al., 2017).
Randomized trials support the claims that exercise improves symptoms of OA, does not increase progression of joint degeneration but reduces knee pain and all-cause disability, as long as vigorous sports and trauma are avoided (Bosomworth, 2009). RCTs show reduction in pain and improved function in hip OA after exercise, and the effect sizes were larger than observed with paracetamol or NSAIDs (McConnel, Hernandez-Molina, and Reichenbach, 2014). There is evidence that the treatment effect of exercise increases with the number of exercise sessions (Hagen et al., 2012). Strength training is effective (McAlindon et al., 2014).
A summary of lower quality RCTs (Hari et al., 2015) shows possible small, short-term effects of corticosteroid injections on pain and function. It is uncertain whether or not acupuncture is effective (McAlindon et al., 2014). There is little to no evidence that electrostimulation is effective for treating OA (Nuesch et al., 2009). There is some weaker evidence for an effect of meditation from a small intervention study (Selfe and Innes, 2013). Weight loss of 5% to 10% of body weight has a small effect on physical function, more so than on pain, and this was seen in an RCT (Bruyere et al., 2014). Hochberg et al. (2012) review evidence and recommend joint splints, thermal modalities, aquatic exercise, tai chi, wedge insoles, and walking aids.
Roughly 350,000 hip replacements are done each year in the US, and the yearly rate is increasing (Puccio and Mattei, 2015). Tissue engineering aims to reconstitute a tissue both structurally and functionally, but as of 2014, none of the proposed approaches have advanced beyond the phase of experimental development to the level of clinical induction (Hunziker et al., 2014). Tissue engineering requires an understanding of the complex interplay between mechanical, inflammatory, and biochemical factors (Sanchez-Adams et al., 2014). Recently, Song et al. (2020) reviewed clinical trials showing Mesenchymal stem cells to be safe and effective in treating OA.
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