Impact of physical activity and mechanical loading on biomarkers typically used in osteoarthritis assessment: current concepts and knowledge gaps

Abstract

There is an ongoing need to develop prognostic and diagnostic biomarkers for osteoarthritis (OA). Understanding how biomarkers change in response to physical activity may be vital for understanding if a patient has a joint that is failing to adapt to a given loading stimulus. The purpose of this review is to describe how biomarker changes after joint loading may help detect early OA and determine prognosis. This may help to inform and more specifically target interventions and clinical trials. We conducted a critical review of the relevant literature that was published to January 2016. There is extensive OA biomarker research, specifically basal biomarker concentrations; however, there is limited research surrounding biomarker response to load. Some of this limited research includes the response of minimal biomarkers reflecting bone, synovium, inflammatory, and cartilage responses to load. Biomarker changes occur in bone and cartilage in response to a variety of activities and are influenced by variables such as body weight, load, vibration, and activity time. Biomarker responses to loading tasks may serve as a measure of overall joint health and be predictive of structural changes. Biomarkers adapt to training over time, and this may indicate a need for a gradual return to physical activity after an injury to allow time for joint tissues to adapt to load. Biomarker responses to physical activity may be monitored to determine appropriate loading levels and safety for return to activity.

Introduction

Despite osteoarthritis (OA) being a common cause of disability there are no clinically accepted therapies to prevent or slow disease progression. Development of structure-modifying therapies is hindered by a lack of good outcome measures, an inability to detect early-stage OA, and an inability to identify clinically-relevant phenotypes, which is a subset of people where an interaction of genetics and environment may influence disease onset/progression or therapeutic response [Kraus et al. 2011]. Biomarkers, which are biological measures that reflect normal or pathological processes, may be evaluated in body fluids (e.g. blood or urine) to monitor joint processes and homeostasis [Biomarkers Definitions Working Group, 2001]. Resting biomarker concentrations can be informative about the overall physiological state of a patient but are less informative for determining if a patient’s joint is failing to adapt to a given loading stimulus, since there is limited information about how OA biomarkers change in response to loading and physical activity in vivo.

Experts developed the BIPEDS classification system for OA biomarkers, indicating there are biomarker categories based on: burden of disease, investigational, prognostic, efficacy of intervention, diagnostic, as well as safety [Bauer et al. 2006; Kraus et al. 2011]. A systematic review revealed that there were some biomarkers elevated within at-risk post knee injury populations that were similar to OA participants, however, none of these biomarkers, which are collected at rest, have been validated within this BIPEDS classification system [Harkey et al. 2015].

Biomarker sensitivity and clinical utility may be impeded by different OA phenotypes and overall biomarker heterogeneity [Kraus et al. 2011]. Biomarker concentration heterogeneity may be attributable to many confounding factors such as weight [Denning et al. 2015], activity level [Cattano et al. 2016a, 2016b], and gender [Niehoff et al. 2011]. We may be able to improve biomarker sensitivity if we are able to account for changes in biomarker concentrations due to physical activity or load as previously reported [Cattano et al. 2016b]. Biomarker responses to load may be helpful in monitoring safety as defined by joint health status following a return to physical activity after injury or surgical repair to ensure a progressive and safe return to physical activity. Researchers and clinicians need to understand what a normal biomarker response to activities is in order to ascertain a biomarker change threshold that is potentially dangerous in early OA onset and progression after an injury. The purpose of this review is to evaluate the current literature on how common OA biomarkers respond to exercise-related loading activities. Particular focus will be placed on young physically active individuals at risk of developing OA after a knee joint injury. Ultimately, this information can help to identify potential biomarkers that could be utilized for monitoring safe levels of physical activity, including return to physical activity after an injury.

Materials and methods

We conducted a critical review of published literature through to July 2016. We focused our database searches on the biomarkers identified in the Kraus and colleagues OARSI Application of Biomarkers paper [Kraus et al. 2011] as this publication identified and recommended biomarkers to be studied in OA research. Databases searched were CINAHL, Medline with Full Text, and SPORTDiscus. Search strategies consisted of searching for each identified biomarker ‘and’ activity search terms that included physical activity, exercise, run, walk, and load. The reference lists of all full-text articles were also screened for additional articles that were not identified through the electronic database search; with no additional articles being identified.

Bone

Bone transmits the majority of load through a joint during physical activity [Garnero et al. 2000]. Recommended serum or urine biomarkers indicative of bone resorption include cross-linked c telopeptide (CTX)-I, N-terminal telopeptide (NTX)-I, and C1, 2C [Kraus et al. 2011]. Other possible bone markers include serum osteocalcin (indicative of bone formation) [Meulenbelt et al. 2007] and urinary pyridinoline and deoxypyridinoline (indicative of bone turnover) [Kraus et al. 2011]. In pharmacologic trials, researchers have demonstrated that interventions targeted towards bone turnover have led to decreases in the concentration of some of these bone biomarkers [Spector et al. 2005; Manicourt et al. 2006], however there is only limited research on the effects of physical activity or load on these biomarkers (Table 1). There has been no research conducted on bone biomarker responses to walking in any population. Running, resistance training, and plyometrics can cause transient increases in serum bone turnover markers (e.g. CTX-I) in young physically active men that gradually return to baseline levels [Whipple et al. 2004; Rogers et al. 2011; Scott et al. 2012]. However, these affects were not seen in another cohort after resistance training [Bemben et al. 2015]. There has not been any research within a female cohort. Bone biomarker increases after certain activities appear to be transient, and certain training protocols may not yield these results. However, there is no available information regarding the use of these biomarkers for disease diagnosis, progression, or safety.

Table 1.

Biomarker response to loads by tissue.

Biomarker	Exposure	Participants	Outcome after physical activity					Author
			<15 min	16–30 min	0.51–2 h	2.1–24 h	24.1–48 h
Cartilage
COMP	Marathon	8 endurance-trained runners		↑	↑	BL	BL	[Neidhart et al. 2000]
COMP	Uphill walk (14 km)	58 recreationally-active males & females (~20 y/o)			↑	BL		[Pruksakorn et al. 2013]
COMP	Flat walk (14 km)	24 recreationally-active males & females (~20 y/o)			↑	BL		[Pruksakorn et al. 2013]
COMP	30-min walk (–40% BW)	12 males & females (~20 y/o)	BL	BL	BL			[Denning et al. 2015]
COMP	30-min walk	12 males & females (~20 y/o)	↑	BL at 15 min	BL			[Denning et al. 2015]
COMP	30-min walk (+40% BW)	12 males & females (~20 y/o)	↑	↑	BL at 0.5			[Denning et al. 2015]
COMP	30 min walking at 5 km/h (12-week running intervention)	12 sedentary males (~21 y/o)	↑					[Celik et al. 2013]
COMP	30 min walking at 5 km/h (12-week cycling intervention)	12 sedentary males (~21 y/o)	↑					[Celik et al. 2013]
COMP	30 min walking at 5 km/h (12-week swimming intervention)	12 sedentary males (~22 y/o)	↑					[Celik et al. 2013]
COMP	30 min walking at 5 km/h (12-week control)	12 sedentary males (~22 y/o)	↑					[Celik et al. 2013]
COMP	Running	5 moderately active males (~26 y/o)		↑		BL		[Niehoff et al. 2010]
COMP	Knee bends	5 moderately active males (~26 y/o)		BL				[Niehoff et al. 2010]
COMP	Lymphatic drainage	5 moderately active males (~26 y/o)		BL				[Niehoff et al. 2010]
COMP	Rest	5 moderately active males (~26 y/o)		↓	↓			[Niehoff et al. 2010]
COMP	Marathon	11 marathon-trained males (~50 y/o)	↑	↑	↑	↑	BL	[Kim et al. 2009]
COMP	Ultramarathon	15 ultramarathon-trained males (~52 y/o)	↑		↑	↑	↑	[Kim et al. 2009]
COMP	30-min walk	17 males & females (~59 y/o)	↑			↓ 5.5 h post		[Erhart-Hledik et al. 2012]
COMP	30-min walk	42 OA patients (~60 y/o)	↑	BL		↓ 5.5 h post		[Mundermann et al. 2009]
COMP	30-min walk	41 controls (~57 y/o)	↑	BL		↓ 5.5 h post		[Mundermann et al. 2009]
COMP	Drop landing	14 sedentary males & females (~23 y/o)	↑	↑	BL	BL		[Niehoff et al. 2011]
COMP	30 min running (2.2 m/s)	14 sedentary males & females (~23 y/o)	↑	↑	BL	BL		[Niehoff et al. 2011]
COMP	Resting	14 sedentary males & females (~23 y/o)	BL	BL	BL	BL		[Niehoff et al. 2011]
COMP	Spring soccer season	21 male and female collegiate soccer (~19 y/o)						[Hoch et al. 2012]
COMP	Spring soccer season	6 female soccer players (~19 y/o)						[Mateer et al. 2015]
Bone
BAP	Resistance training	12 physically active males (~43 y/o)	BL	BL	BL	BL		[Rogers et al. 2011]
BAP	Plyometrics	12 physically active males (~43 y/o)	BL	BL	BL	BL		[Rogers et al. 2011]
CTX-I	Resistance exercise (without whole body vibration)	10 physically active males (~23 y/o)		BL				[Bemben et al. 2015]
CTX-I	Resistance exercise (with whole body vibration)	10 physically active males (~23 y/o)		↓ post WBV				[Bemben et al. 2015]
OC	Resistance training	12 physically active males (~43 y/o)	BL	BL	BL	BL		[Rogers et al. 2011]
OC	Plyometrics	12 physically active males (~43 y/o)	↓	BL	BL	BL		[Rogers et al. 2011]
CTX-I	Resistance training	12 physically active males (~43 y/o)	BL	BL	↓	BL		[Rogers et al. 2011]
CTX-I	Plyometrics	12 physically active males (~43 y/o)	BL	BL	↑	↑		[Rogers et al. 2011]
CTX-I	Resistance exercise (without whole body vibration)	10 physically active males (~23 y/o)		BL				[Bemben et al. 2015]
CTX-I	Resistance exercise (with whole body vibration)	10 physically active males (~23 y/o)		↓ post WBV				[Bemben et al. 2015]
TRAP5b	Resistance training	12 physically active males (~43 y/o)	↓	↓	BL	BL		[Rogers et al. 2011]
TRAP5b	Plyometrics	12 physically active males (~43 y/o)	↓	↓	BL	BL		[Rogers et al. 2011]
TRAP5b	Resistance exercise (without whole body vibration)	10 physically active males (~23 y/o)		BL				[Bemben et al. 2015]
TRAP5b	Resistance exercise (with whole body vibration)	10 physically active males (~23 y/o)		↑				[Bemben et al. 2015]
Synovium
IL-1beta	Marathon	8 endurance-trained runners		BL	BL	BL	BL	[Neidhart et al. 2000]
IL-1beta	Running for 60 min (55%, 65% and 75% VO2Max)	10 males (~28 y/o)		n/a	n/a			[Scott et al. 2011]
CPK	Marathon	11 marathon-trained males (~50 y/o)		↑	↑	↑		[Kim et al. 2009]
CPK	Ultramarathon	15 ultramarathon-trained males (~52 y/o)		↑	↑	↑		[Kim et al. 2009]
CRP	Marathon	8 endurance trained runners		BL	BL	↑	↑	[Neidhart et al. 2000]
CRP	Marathon	11 marathon-trained males (~50 y/o)	BL	BL	BL	↑ 1 day	↑	[Kim et al. 2009]
CRP	Ultramarathon	15 ultramarathon-trained males (~52 y/o)	↑	↑	↑	↑	↑	[Kim et al. 2009]
HA	Uphill walk (14 km)	58 recreationally active males & females (~20 y/o)			↓	↑		[Pruksakorn et al. 2013]
HA	Flat walk (14 km)	24 recreationally active males & females (~20 y/o)			↓	↑		[Pruksakorn et al. 2013]
sIL-6R	Marathon	8 endurance-trained runners		BL	BL	BL	BL	[Neidhart et al. 2000]
IL-6	Running for 60 min (55%, 65% and 75% VO2Max)	10 males (~28 y/o)		↑	↑	↑		[Scott et al. 2011]
IL-6	Marathon	8 endurance-trained runners		↑	↑	BL	BL	[Neidhart et al. 2000]
IL-1ra	Running for 60 min (55%, 65% and 75% VO2Max)	10 males (~28 y/o)		↑	↑			[Scott et al. 2011]
IL-1ra	Marathon	8 endurance-trained runners	↑	↑	↑	BL	BL	[Neidhart et al. 2000]
MIA	Marathon	8 endurance-trained runners		BL	BL	↑ in 5 of 8	↑ in 5 of 8	[Neidhart et al. 2000]
MMP-1	Acute resistance exercise test (pre)	16 recreationally active males (~28 y/o)	↑		BL			[Urso et al. 2009]
MMP-1	Acute resistance exercise test (post 8-week intervention calisthenic)	8 recreationally active males (~28 y/o)	↑		BL			[Urso et al. 2009]
MMP-1	Acute resistance exercise test (post 8 week intervention resistance)	8 recreationally active males (~28 y/o)	↑		BL			[Urso et al. 2009]
MMP-2	Acute resistance exercise test (pre)	16 recreationally active males (~28 y/o)	↑	↑	BL			[Urso et al. 2009]
MMP-2	Acute resistance exercise test (post 8-week intervention calisthenic)	8 recreationally active males (~28 y/o)	↑	↑	BL			[Urso et al. 2009]
MMP-2	Acute resistance exercise test (post 8-week intervention resistance)	8 recreationally active males (~28 y/o)	↑	↑	BL			[Urso et al. 2009]
MMP-3	Acute resistance exercise test (pre)	16 recreationally active males (~28 y/o)	↑	↑				[Urso et al. 2009]
MMP-3	Acute resistance exercise test (post 8-week intervention calisthenic)	8 recreationally active males (~28 y/o)	BL	BL				[Urso et al. 2009]
MMP-3	Acute resistance exercise test (post 8-week intervention resistance)	8 recreationally active males (~28 y/o)	BL	BL				[Urso et al. 2009]
MMP-9	Acute resistance exercise test (pre)	16 recreationally active males (~28 y/o)	↓					[Urso et al. 2009]
MMP-9	Acute resistance exercise test (post 8-week intervention calisthenic)	8 recreationally active males (~28 y/o)	↑					[Urso et al. 2009]
MMP-9	Acute resistance exercise test (post 8-week intervention resistance)	8 recreationally active males (~28 y/o)	↓					[Urso et al. 2009]
sTNFRII	Marathon	8 endurance-trained runners		BL	BL	BL	BL	[Neidhart et al. 2000]
TNF-alpha	Marathon	8 endurance-trained runners		↑	↑	BL	BL	[Neidhart et al. 2000]
TNF-alpha	Running for 60 min (55%, 65% and 75% VO2Max)	10 males (~28 y/o)		↑	BL at 1 h			[Scott et al. 2011]
WF6	Uphill walk (14 km)	58 recreationally active males & females (~20 y/o)			↑	↓		[Pruksakorn et al. 2013]
WF6	Flat walk (14 km)	24 recreationally active males & females (~20 y/o)			↓	↓		[Pruksakorn et al. 2013]

^*Note: All noted increases or decreases at time points were statistically significant changes (p ⩽ 0.05).

↑, increased; ↓, decreased; BAP, bone-specific alkaline phosphatase; BL, baseline; BW, body weight; COMP, cartilage oligomeric matrix protein; CPK, creatine phosphokinase; CRP, high-sensitivity C-reactive protein; HA, hyaluronic acid; IL, interleukin; n/a, not applicable; MIA, melanoma inhibitory activity; MMP, matrix metalloproteinase; OA, osteoarthritis; OC, osteocalcin; sTNFRII, soluble tumor necrosing factor receptor II; TRAP5b, tartrate-resistant acid phosphatase 5b; TNF, tumor necrosis factor; VO₂Max, maximal oxygen consumption; WBV, whole body vibration; WF6, chondroitin sulfate-WF6; y/o, years old

Synovium

Though OA has not historically been considered an inflammatory disease, synovitis and inflammation are common in patients with OA [Aigner et al. 2006]. The recommended biomarkers specific to synovium are matrix metalloproteinase (MMP)-3 (joint tissue degradation & synovitis), hyaluronic acid (HA; synovitis), MMP-13 (protein breakdown), as well as urinary glucosyl-galactosyl-pyridinoline (synovium breakdown) [Meulenbelt et al. 2007; Kraus et al. 2011]. MMP-3 and MMP-13, which are expressed by both cartilage and synovium, are elevated in patients with OA [Sandell and Aigner, 2001] and decrease in response to a limited number of anti-inflammatory therapies in pharmacologic trials [Lohmander et al. 2005; Manicourt et al. 2006]; however there is limited research on the effects of physical activity or load on these biomarkers. Healthy participants had larger decreases in HA concentrations within 1 h of walking on an inclined hill in comparison with walking on a flat surface [Pruksakorn et al. 2013]. A running task also causes increases in inflammatory biomarkers. Within a group of runners training for a marathon, interleukin (IL)-1 receptor agonist (anti-inflammatory), tumor necrosis factor (TNF)-α (pro-inflammatory), and IL-6 (inflammatory marker) were all elevated immediately post-marathon and gradually returned to baseline levels within 24–48 h [Neidhart et al. 2000]. MMP-3 significantly increased after an acute resistance exercise training program in an untrained male cohort (mean age: 26); however, that change was eliminated after an 8-week training program involving calisthenics [Urso et al. 2009].

Similar to some other tissue biomarkers, inflammatory biomarkers [i.e. IL-1 receptor agonist (anti-inflammatory), TNF-α (pro-inflammatory), IL-6 (inflammatory)] are also elevated after a running task and gradually return to baseline levels [Neidhart et al. 2000]. Similar to bone biomarkers, synovium biomarkers appear to transiently respond to certain activities, and there is evidence that training protocols may mitigate the biomarker responses (Table 1). However, there are no studies currently available that have assessed biomarker change for diagnosis, prognosis, or safety.

Cartilage

Cartilage is biphasic and water diffuses through it to provide nutrients and modulate compressive stiffness in response to physical activity demands [Pearle et al. 2005; Martel-Pelletier et al. 2008]. Cartilage markers, particularly cartilage oligomeric matrix protein (COMP), have been the most frequently studied tissue biomarkers in response to physical activity and in OA. Some common serum COMP, CTX-II, serum concentrations of biomarkers of type I and type II collagen (C1, 2C), and those specific to type II collagen (C2C) and urinary collagen type II neoepitope, as well as cartilage synthesis markers specific to type II collagen (CPII), and N-propeptide of type IIA collagen, which are most prominent in articular cartilage [Meulenbelt et al. 2007; Kraus et al. 2011]. Many researchers have primarily focused their efforts on COMP (cartilage degradation) in response to load, and have reported a temporary dose-dependent increased concentration of COMP in response to physical activity that gradually returns to baseline levels.

Cartilage oligomeric matrix protein response to walking

COMP response to activity has been studied in the healthy population, and exercise causes increases in COMP concentrations immediately post-activity. A 30-min walking task at a self-selected pace significantly elevated serum COMP concentration levels by 5–10% in both a younger (age range: 21–32 years) [Celik et al. 2013; Denning et al. 2015] and older (mean age: 57 years) population [Mundermann et al. 2009]. Increased intensities, such as walking on an incline, significantly elevated COMP concentration levels in comparison with a walk on a level surface in healthy (mean age: 20 years) participants [Pruksakorn et al. 2013].

Body mass has been found to independently affect COMP response to a walking activity [Denning et al. 2015]. Body weight was manipulated through the use of a lower body positive pressure treadmill in a younger cohort [Denning et al. 2015]. Self-selected walking on a treadmill with unadjusted body weight caused a 10% increase in COMP, while the same walking task with a weighted vest resulted in a 22% increase in COMP concentrations [Denning et al. 2015].

The findings within an OA cohort are a little more ambiguous. Contradictory results were reported immediately post-walk at a self-selected pace for 30 min in an OA population [Mundermann et al. 2009; Erhart-Hledik et al. 2012]. This may be related to the different study populations as one study included only females [Subburaj et al. 2012] while the other study included both sexes [Mundermann et al. 2009] with similar age ranges. Notably, baseline COMP concentration levels were not predictive of articular cartilage loss, but COMP changes pre- to post-exercise were [Erhart-Hledik et al. 2012]. Despite these contradictory findings, there is support that there is a relationship between physiologically cartilage changes and cartilage relaxation times as measured by magnetic resonance imaging [Subburaj et al. 2012]. Biomarker changes may serve as a prognostic indicator of impending, sub-clinical OA in at-risk populations, like the post knee injury population; however, further study is needed in these groups.

Cartilage oligomeric matrix protein response to running

Running activities have caused significant increases in COMP in healthy populations, with an apparent dose-dependent response. Among sedentary and physically active individuals, 30 min of running at a self-selected and prescribed pace (2.2 m/s) was related with a 25–40% increase in COMP immediately post-run, which returned to baseline levels within 90 min [Niehoff et al. 2010, Niehoff et al. 2011]. In contrast, physically trained individuals experienced no COMP increase after a 1 h run at a self-selected pace [Kersting et al. 2005]. COMP levels significantly increased within highly trained, marathon-trained individuals at 60–200% after a marathon run, and gradually returned to baseline levels within 24–48 h [Neidhart et al. 2000] after a marathon and within 72 h following an ultramarathon [Kim et al. 2009]. COMP appears to have dose-dependent response with more demanding physical activity causing greater increases that are more prolonged and require a greater amount of time to return to pre-exercise levels. Significant COMP increases occurred in highly trained, marathon-trained individuals after a marathon and ultramarathon run that gradually returned to baseline levels, taking longer after the ultramarathon [Neidhart et al. 2000; Kim et al. 2009]. COMP biomarker response appears to possibly be adaptive and mitigated by training protocols such as a running training protocol [Celik et al. 2013]. Cartilage overall can be conditioned to sustain loads [Andriacchi et al. 2009]; however COMP changes for diagnosis, prognosis, or safety have not been investigated and may be meaningful within young patients with an injury history who are at risk for post-traumatic OA.

Cartilage oligomeric matrix protein response to activity in an osteoarthritis population

COMP response to activity in an OA population has not been as extensively studied. The two studies that evaluated COMP immediately post-walk at a self-selected pace for 30 min in an OA population found contradictory results [Mundermann et al. 2009; Erhart-Hledik et al. 2012]. This may be related to the different study populations as one study included only females [Subburaj et al. 2012] while the other study included both sexes [Mundermann et al. 2009] with similar age ranges. Baseline COMP concentration levels were not predictive of articular cartilage loss, however, COMP changes pre- to post-exercise were predictive of degenerative cartilage changes [Erhart-Hledik et al. 2012]. A few studies have investigated structural cartilage thickness response to activity as well. Cartilage thickness decreases after a 30 min run in both older and younger healthy populations [Cha et al. 2012]. Similarly, cartilage thickness decreases immediately post a 500 m run [Boocock et al. 2009] and 30 min run [Mosher et al. 2005, 2010]. It has been postulated that COMP levels would demonstrate increases following activity because COMP is the primary regulator of articular cartilage water content [Abramson and Krasnokutsky, 2006]. Imaging studies have confirmed dose-dependent response of cartilage, and that cartilage can be conditioned to loading as long as there are no abrupt extrinsic or intrinsic changes [Andriacchi et al. 2009].

Cartilage oligomeric matrix protein and other activities

A few researchers have investigated COMP response to activities other than running. COMP levels did not change in response to repetitive knee bends [Niehoff et al. 2010]. However, COMP levels increased immediately post repetitive drop-landing activities, gradually returning to normal levels within 90 min, which is similar to the response observed in COMP concentrations following 30-min running activities [Niehoff et al. 2010, 2011].

COMP response to 30 min of walking was investigated pre- and post-intervention by Celik and colleagues in participants who were randomized to a 12-week exercise program (i.e. running, swimming, biking, or control) [Celik et al. 2013]. Serum COMP did not significantly increase after the 30-min walk after 12 weeks in the running intervention group; however, it did significantly increase in the other three groups [Celik et al. 2013]. These findings may be indicative of the need for gradual increases in training based on exercise mode so that the joint tissues can safely adapt to the imposed load over a period of time. While more research is needed this may be important following joint injury. Biomarker response to physical activity may be informative and potentially utilized as a safety mechanism in the high-risk, post-knee injury population, but further research in this area is needed. It is possible that biomarker responses to physical activity can be monitored to determine appropriate amounts of loading during return to physical activity.

Serum COMP significantly increased from early- to mid-season and from early- to late-season within a men’s and women’s soccer population [Hoch et al. 2012]. The serum COMP increases from early- to late-season moderately positively correlated with improvements in patient-reported outcomes over the course of the season [Hoch et al. 2012]. Serum COMP concentrations did not change over the course of a spring women’s soccer season with weekly serum analyses, however, the authors reported that activity minutes qualitatively appeared to affect serum COMP concentration [Mateer et al. 2015]. There were significantly greater COMP increases when the female soccer athletes returned to considerable activity after a week of no activity minutes [Mateer et al. 2015]. These findings further support a COMP dose-dependent response, where COMP concentrations seem to change based on the magnitude of activity loads beyond the individual’s adaptive tolerance (Table 1). This dose-dependent response may indicate that a gradual increase in training could be beneficial in returning to physical activity after an injury so that the joint tissues can safely adapt to the imposed load over a period of time.

Gaps and recommendations for future research

There is considerable evidence that there are biomarkers that change in response to various exercise loads and that these changes may be directly influenced by an individual’s training level, an individual’s body weight, or the intensity of the loading. There are an expanding number of biomarkers that are recommended for research for BIPEDS, however these recommendations are based on resting biomarker concentrations and their ability to differentiate and predict OA progression. Future researchers need to explore how these OA-related biomarkers change in vivo in response to loading, and whether these changes, as opposed to resting concentrations, may be diagnostic of early OA and prognostic for radiographic OA.

There seems to be a cartilage-centered focus to the research that has been conducted within biomarker response to loads. COMP has been the primary biomarker that has been investigated in response to physical activity loads. While COMP and some other biomarkers have been investigated, most researchers have focused on populations that are male, older, or inactive. There is limited information regarding how biomarkers respond to physical activity loads in both males and females who are younger and physically active; therefore we do not know what is a normal or expected acute response to an increase or decrease in physical activity versus what is a pathologic response. Particular focus should be directed towards young physically active individuals with a history of a knee joint injury since they are predisposed for early OA development. Gaining an understanding of this pathophysiology could be especially informative for monitoring when individuals with a knee injury history are resuming physical activity given their increased risk for post-traumatic OA.

Summary

Biomarker responses to physical activity may be able to serve as an indicator of tolerance (or intolerance) to physical activity related joint loading. The findings of this review demonstrate that there is a dearth of research investigating multi-tissue biomarker responses, beyond COMP, in a young physically active population. It is important that we establish what a normal biomarker response to acute activity is to ascertain a threshold or timeframe from baseline that may be potentially hazardous for participants’ long-term joint health. Biomarker response to physical activity is an area where future research can focus to determine safe levels of physical activity, especially after a knee injury or surgery, to delay or prevent OA onset and progression. This could help facilitate a gradual and safe return to physical activity after an injury or surgery, with the ultimate goal of eventually monitoring for OA onset and progression.