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. 2024 Aug 11;52(10):2503–2511. doi: 10.1177/03635465241262797

Association of Serum Biochemical Biomarker Profiles of Joint Tissue Inflammation and Cartilage Metabolism With Posttraumatic Osteoarthritis-Related Symptoms at 12 Months After ACLR

Caroline Lisee †,*, Sarah Obudzinski , Brian G Pietrosimone ‡,§, R Alexander Creighton , Ganesh Kamath , Lara Longobardi , Richard Loeser , Todd A Schwartz ‖,, Jeffrey T Spang
PMCID: PMC11344971  PMID: 39129267

Abstract

Background:

Anterior cruciate ligament injury and anterior cruciate ligament reconstruction (ACLR) are risk factors for symptomatic posttraumatic osteoarthritis (PTOA). After ACLR, individuals demonstrate altered joint tissue metabolism indicative of increased inflammation and cartilage breakdown. Serum biomarker changes have been associated with tibiofemoral cartilage composition indicative of worse knee joint health but not with PTOA-related symptoms.

Purpose/Hypothesis:

The purpose of this study was to determine associations between changes in serum biomarker profiles from the preoperative sample collection to 6 months after ACLR and clinically relevant knee PTOA symptoms at 12 months after ACLR. It was hypothesized that increases in biomarkers of inflammation, cartilage metabolism, and cartilage degradation would be associated with clinically relevant PTOA symptoms after ACLR.

Study Design:

Case-control study; Level of evidence, 3.

Methods:

Individuals undergoing primary ACLR were included (N = 30). Serum samples collected preoperatively and 6 months after ACLR were processed to measure markers indicative of changes in inflammation (ie, monocyte chemoattract protein 1 [MCP-1]) and cartilage breakdown (ie, cartilage oligomeric matrix protein [COMP], matrix metalloproteinase 3, ratio of type II collagen breakdown to type II collagen synthesis). Knee injury and Osteoarthritis Outcome Score surveys were completed at 12 months after ACLR and used to identify participants with and without clinically relevant PTOA-related symptoms. K-means cluster analyses were used to determine serum biomarker profiles. One-way analyses of variance and logistic regressions were used to assess differences in Knee injury and Osteoarthritis Outcome Score subscale scores and clinically relevant PTOA-related symptoms between biomarker profiles.

Results:

Two profiles were identified and characterized based on decreases (profile 1: 67% female; age, 21.4 ± 5.1 years; body mass index, 24.4 ± 2.4) and increases (profile 2: 33% female; age, 21.3 ± 3.2 years; body mass index, 23.4 ± 2.6) in sMCP-1 and sCOMP preoperatively to 6 months after ACLR. Participants with profile 2 did not demonstrate differences in knee pain, symptoms, activities of daily living, sports function, or quality of life at 12 months after ACLR compared to those with profile 1 (P = .56-.81; η2 = 0.002-0.012). No statistically significant associations were noted between biomarker profiles and clinically relevant PTOA-related symptoms (odds ratio, 1.30; 95% CI, 0.23-6.33).

Conclusion:

Serum biomarker changes in MCP-1 and sCOMP within the first 6 months after ACLR were not associated with clinically relevant PTOA-related symptoms.

Keywords: knee ligaments, ACL, biology of cartilage, injury prevention


The risk of developing posttraumatic osteoarthritis (PTOA) after anterior cruciate ligament (ACL) injury and ACL reconstruction (ACLR) remains high18,39,47 despite operative and rehabilitative advances to regain knee joint stability and return individuals to previous levels of physical activity. Approximately 50% of individuals who sustain an ACL injury will develop radiographic evidence of PTOA (ie, disease) within 20 years of injury regardless of surgery.18,39,47 Although radiographic findings do not always occur concurrently with clinically relevant PTOA symptoms, 6 similar rates of symptomatic PTOA (ie, illness) have been reported reaching nearly 50% within 2 decades of ACL injury. 30 Symptomatic PTOA characterizes the pain and disability that patients experience along with pathological changes in the joint and serves as patients’ catalyst for contacting health care providers to pursue treatment. 57 Identifying individuals at risk for clinically relevant PTOA symptom development is important for improving patient care and reducing the societal burden of the disease. 57 Clinically relevant PTOA symptoms may be classified using the Knee injury and Osteoarthritis Outcome Score (KOOS) patient-reported questionnaire, which includes subscales used to grade the severity of a patient's knee symptoms, pain, ability to complete activities of daily living, participation in sport, and quality of life. 49 KOOS subscale cut-off values are aimed at classifying individuals who report substantial knee symptoms that would cause them to seek medical treatment 17 and have been applied in individuals after isolated meniscectomies and ACLRs.16,20,25,30,32,54 Despite patients having elevated rates of symptomatic PTOA compared with their uninjured counterparts, 51 health care providers lack clinically accessible tools to identify individuals after ACLR who are at greatest risk of clinically relevant PTOA symptoms and evidence-based interventions to mitigate illness development. Biochemical markers can be used as preradiographic indicators of altered joint tissue metabolism because metabolic changes are present at higher concentrations before irreversible structural joint tissue changes develop. Therefore, biochemical markers may be used to identify individuals at high risk for clinically relevant PTOA symptom development and used as targets for therapeutic intervention. 28

The value of synovial and serum biomarkers for predicting PTOA development after ACL injury was first demonstrated in animal models5,15,22,55 and later investigated in human participants.36,43,44 The FNIH Biomarkers Consortium recommends that a panel of biomarkers be used to better understand the various presentations of osteoarthritis development and mechanistic pathways for therapeutic intervention. 28 Furthermore, changes in biomarkers over time are stronger predictors of idiopathic knee osteoarthritis compared with a single assessment. 29 Biomarkers including monocyte chemoattract protein 1 (MCP-1), cartilage oligomeric matrix protein (COMP), matrix metalloproteinase 3 (MMP-3), and the ratio of type II collagen breakdown (C2C) to type II collagen synthesis (CPII) either increase within the first 6 to 12 months after ACL injury and ACLR or are elevated compared with those in uninjured individuals.37,45,53 MCP-1 is a marker of inflammation and may also aid in mediating pain. 61 COMP and C2C:CPII play a pivotal role in cartilage metabolism,3,10,31,50 whereas MMP-3 is associated with cartilage degradation.9,10,48,58 Both MCP-1 and COMP have been linked to development and progression of idiopathic osteoarthritis.1,27,38,42 Changes in these biomarkers over time after ACL injury and ACLR have been used to identify biochemical profiles associated with worsening knee joint health. 34 Specifically, serum profiles with increasing concentrations of MCP-1 and COMP over the first 6 months after ACLR have been associated with worse tibiofemoral articular cartilage composition on magnetic resonance imaging (MRI) scans, indicative of low proteoglycan density at 12 months postoperatively. 34 Development of such profiles holds promise for better identifying patients at high risk for clinically relevant PTOA symptoms after ACLR and determining therapeutic targets for intervention to reduce the risk of illness development.

Although synovial and serum biochemical biomarker profiles have been associated with preradiographic MRI evidence of cartilage degeneration indicative of poor knee joint health,2,34 it is unclear whether these biochemical changes are also associated with clinically relevant PTOA symptoms. Therefore, the purpose of this study was to determine whether changes in serum biochemical biomarker profiles from the preoperative levels to 6 months after ACLR are associated with clinically relevant PTOA symptoms at 12 months after ACLR. We hypothesized that patients with increased levels of biomarkers of inflammation, cartilage metabolism, and cartilage degradation 6 months after ACLR relative to preoperative levels would have greater odds of reporting clinically relevant PTOA-related symptoms 12 months after ACLR.

Methods

This prospective, longitudinal cohort study included participants with a primary history of ACL injury undergoing ACLR. Serum samples were collected preoperatively (6.89 ± 3.59 days after ACL injury) and at 6 months after ACLR (196.74 ± 22.44 days after ACLR). Patient-reported outcomes were collected at 12 months postoperatively (369.20 ± 9.96 days after ACLR) and used to classify patients reporting and not reporting clinically relevant PTOA symptoms. This study was approved by the institutional review board at the University of North Carolina at Chapel Hill. All participants ≥18 years old provided written informed consent before study enrollment. Participants <18 years old provided assent, and their parent or guardian provided parental permission to consent to participate.

Participants

Participants between the ages of 16 and 35 years were recruited at an orthopaedic surgery clinic at the University of North Carolina at Chapel Hill (Figure 1). Participants were included if they had an acute ACL injury (date of injury within 15 days of clinic presentation) and if they were planning to undergo ACLR by 1 of 3 fellowship-trained orthopaedic sports surgeons (G.K., J.T.S., R.A.C.). Participants were excluded if they were not planning to undergo ACLR, if they required reconstruction or repair of >1 ligament, if they had a history of ACL injury or ACLR to either limb, or if they had previously been diagnosed with any type of knee arthritis. Participants with meniscal repairs and meniscectomies were included in the study unless the meniscectomy involved excising greater than one-third of the meniscus. All participants underwent arthroscopic-assisted single-incision ACLR that entailed a bone–patellar tendon–bone autograft as previous described.34,46 Meniscal and chondral injuries were identified via an arthroscopic assessment during surgery, and a chart review of electronic medical records was performed to determine concomitant meniscal procedures performed at the time of ACLR to aid in characterizing participants. After ACLR, all participants were referred for supervised rehabilitation therapy by a licensed physical therapist or athletic trainer. Each participant was provided with structured rehabilitation guidelines consisting of 6 phases starting the first week after ACLR and continuing for 6 to 9 months postoperatively as previously described.34,46,59,60

Figure 1.

Figure 1.

Flowchart of participant recruitment and analysis based on recommendations from Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. 13 ACL, anterior cruciate ligament; ACLR, anterior cruciate ligament reconstruction; PROs, patient-reported outcomes.

Biochemical Biomarker Analysis

Blood samples from the antecubital fossa were collected in 5-mL serum separation tube vacutainers, allowed to clot for 30 minutes, centrifuged at 3000 rpm and −4°C, and stored in aliquots at −80°C. Upon completion of the study, serum samples were batch processed in duplicate using commercial enzyme-linked immunosorbent assays to determine biomarker serum concentrations of MCP-1 (sMCP-1), COMP (sCOMP), and MMP-3 (sMMP-3) (R&D Systems) as well as C2C:CPII (sC2C:sCPII) ratio (IBEX Technologies). The aforementioned biomarkers were selected because previous literature indicated that ≥1 of the biomarkers demonstrate (1) higher concentrations in individuals at 6 and/or 12 months after ACLR compared with uninjured controls,37,45,53 (2) increases in concentrations in individuals at 6 and 12 months after ACLR compared with preoperative time points,37,53 (3) associations with worse cartilage composition after ACLR, 34 and (4) links to idiopathic osteoarthritis.1,9,10,27,42,58 All sample concentrations were inspected to determine whether they exceeded the mean minimal detectable dose for each assay, including sMCP1 ≥ 1.7 pg/mL, sMMP-3 ≥ 0.009 ng/mL, sCOMP ≥ 0.01 ng/mL, sC2C ≥ 10 ng/mL, and sCPII ≥ 35 ng/mL. All samples exceeded the mean minimal detectable levels and were retained for assessment. Inter- and intra-assay variabilities were less than the 10% coefficient of variance.

Patient-Reported Outcomes

All participants completed the KOOS questionnaire at 12 months after ACLR. The KOOS is a 42-item self-administered questionnaire that has been validated to assess self-reported knee function after ACLR. 49 The questionnaire consists of 5 subscales: Pain, Symptoms, Activities of Daily Living (ADL), Sports and Recreation Function (Sport), and Knee-Related Quality of Life (QOL). Each subscale is scored from 0 to 100, with higher scores representing improved knee function. Englund et al 17 established clinically accessible criteria to characterize a “symptomatic knee” after traumatic knee injury, described as knee symptoms severe enough for an individual to seek medical care. This classification has since become accepted as a measure of individuals with clinically relevant PTOA symptoms after ACLR.16,20,25,30,32,54 Participants were classified as symptomatic if their KOOS QOL was ≤87.5 and if their scores on 2 of the remaing subscales were as follows: ≤87.5 (KOOS Pain), ≤87.5 (KOOS Symptoms), ≤86.8 (KOOS ADL), and ≤85.0 (KOOS Sport).

Statistical Analysis

Changes in biochemical biomarker concentrations were calculated as the absolute differences in concentrations preoperatively to 6 months after ACLR. A k-means cluster analysis was used to determine serum biochemical biomarker profiles based on changes in sMCP-1, sCOMP, sMMP-3, and sC2C:sCPII preoperatively to 6 months after ACLR. The statistical approach to identify profiles based on changes in biomarker concentrations was similar to that of a previous study reporting that participants with profiles of increased sMCP-1 and sCOMP from the preoperative assessment to 6 months after ACLR demonstrated MRI outcomes indicative of lower lateral tibiofemoral cartilage proteoglycan density. 34 A k-means cluster analysis is a type of data reduction that allows for the identification of a predetermined number of profiles of participants with similar biomarker characteristics because biomarker concentrations may behave differently between participants and/or across biomarker types. For example, a homogeneous group of participants may be identified based on increases in the concentrations of 1 biomarker but the decreases or lack of changes in concentrations of another biomarker. The k-means cluster analyses are sensitive to outliers and different outcome scales (ie, change in sMCP-1 preoperatively to 6 months after ACLR range, −167.20 to 189.40 vs change in sC2C:sCPII preoperatively to 6 months after ACLR range, −0.25 to 1.18). 26 Therefore, biochemical biomarker concentrations were transformed into z-scores to assess for outliers and to aid in the k-means cluster analysis. Participants who had biochemical biomarker concentrations that exceeded 3 standard deviations were removed from the analysis. 24 Two participants were removed from the analysis based on these criteria (participant 1: male; age, 20 years; preoperative body mass index [BMI], 22.7 and participant 2: female; age, 22 years; preoperative BMI, 22.2). Two-cluster solutions (mean silhouette, 0.55) and 3-cluster solutions (mean silhouette, 0.50) were calculated using the k-means cluster analysis. Quality of the clusters was calculated based on a mean silhouette value to assess the strength of the differences of observations between clusters while maintaining the similarity of observations within a cluster (poor, < 0.3; fair, 0.40-0.50; good, >0.50). 56 A mean silhouette assessment is calculated based on the mean intra- and intercluster distances across observations. Higher values indicate that observation distances within a cluster are small (ie, similar) but observation distances between clusters are large (ie, different). 56 The 2-cluster solution was retained for further analysis. Separate 1-way analyses of variance were used to determine statistically significant differences between profiles for biochemical biomarker concentrations preoperatively, differences between profiles at 6 months after ACLR, and changes from preoperative assessment to 6 months after ACLR, which will aid in characterizing the biochemical profiles between the clusters.

Means and standard deviations as well as counts and percentages were calculated for participant characteristics and knee injury history outcomes to describe participant characteristics. Differences in participant characteristics and knee injury history outcomes between cohorts were assessed via independent t test or chi-square test. One-way analyses of variance were also used to assess for differences in KOOS subscale scores between clusters. Partial η2 effect sizes were calculated to determine the magnitude of differences between groups. Effect sizes were interpreted as small (η2 < 0.06), medium (η2 = 0.06-0.14), and large (η2 > 0.14). 11 Odds ratios (ORs) and 95% CIs were calculated via logistic regression to determine the odds of biochemical biomarker groups (ie, independent variable) being classified as symptomatic by reporting clinically relevant, osteoarthritis-related symptoms (ie, dependent variable). Finally, Pearson r correlations were used to determine the associations of biochemical biomarker concentrations preoperatively and at 6 months and the changes from preoperative assessment to 6 months after ACLR with KOOS subscales to determine whether any biomarkers had independent associations with patient-reported outcomes beyond the cluster relationships. All statistical analyses were performed using the Statistical Package for Social Sciences (SPSS, Version 28.0; IBM). Alpha level was set to 0.05.

Post Hoc Analysis

Previous studies have reported that biochemical biomarkers and KOOS scores are influenced by sex.7,29 Therefore, we performed a post hoc analysis using 1-way analyses of covariance to compare KOOS subscales (ie, dependent variable) between biochemical biomarker groups (ie, independent variable) while controlling for sex (ie, covariate). Logistic regression analyses were replicated from the primary analysis to assess the associations of biochemical biomarker groups (ie, independent variable) and clinically relevant osteoarthritis-related symptoms (ie, dependent variable) while controlling for sex (ie, covariate).

Results

Biochemical Biomarker Profiles

Participants were dichotomized using k-means cluster analyses based on changes in biochemical biomarker profiles from initial ACL injury to 6 months after ACLR (Appendix Figure A1, available in the online version of this article). Profile 1 (n = 18) was characterized by decreases in sMCP-1 and sCOMP preoperatively to 6 months after ACLR (sMCP-1: P < .001, η2 = 0.47; sCOMP: P < .001, η2 = 0.42) (Table 1). Profile 2 (n = 12) was characterized by increases in sMCP-1 and sCOMP preoperatively to 6 months after ACLR (Table 1). No statistically significant differences were found for sMMP-3 (P = .13; η2 = 0.08) or sC2C:sCPII (P = .26; η2 = 0.04) between profiles (Table 1). Profile 1 also demonstrated lower sMCP-1 (P = .01; η2 = 0.23) and sCOMP (P = .002; η2 = 0.30) at 6 months after ACLR but greater sC2C:sCPII ratio (P = .02; η2 = 0.18) at 6 months after ACLR compared with profile 2 (Table 1). No statistically significant differences were found between profiles for sMCP-1, sCOMP, sMMP-3, or sC2C:sCPII ratio preoperatively (P = .13-.84; η2 = 0.002-0.08) (Table 1).

Table 1.

Concentrations of Serum Biochemical Biomarkers Between Profiles a

Biochemical Biomarker Time Point All Participants (N = 30) Profile 1: Decreased sMCP-1 and sCOMP
(n = 18)
Profile 2: Increased sMCP-1 and sCOMP
(n = 12)
P
sMCP-1, pg/mL Preop 318.08 ± 94.50 315.11 ± 88.32 322.53 ± 107.03 .84
6 mo after ACLR 332.1 ± 125.92 283.94 ± 89.15 404.44 ± 141.46 .01 b
Δ Preop to 6 mo after ACLR 167.20 ± 189.40 −31.17 ± 65.24 81.90 ± 53.82 <.001 b
sCOMP, ng/mL Preop 142.94 ± 57.43 150.07 ± 53.68 132.26 ± 63.52 .42
6 mo after ACLR 142.07 ± 51.55 119.61 ± 35.32 175.76 ± 54.89 .002 b
Δ Preop to 6 mo after ACLR −111.80 ± 128.25 −30.47 ± 37.14 43.51 ± 53.38 <.001 b
sMMP-3, ng/mL Preop 10.84 ± 4.71 9.79 ± 3.06 12.42 ± 6.28 .20
6 mo after ACLR 14.02 ± 6.92 11.83 ± 4.36 17.31 ± 8.80 .07
Δ Preop to 6 mo after ACLR −7.42 ± 19.04 2.05 ± 4.50 4.89 ± 5.26 .13
sC2C:CPII Preop 0.40 ± 0.21 0.43 ± 0.23 0.35 ± 0.17 .34
6 mo after ACLR 0.45 ± 0.17 0.51 ± 0.19 0.36 ± 0.11 .02 b
Δ Preop to 6 mo after ACLR −0.25 ± 0.42 0.08 ± 0.18 0.01 ± 0.15 .26
a

Values are expressed as mean ± SD. ACLR, anterior cruciate ligament reconstruction; Preop, preoperative; sC2C:sCPII, ratio of type II collagen breakdown to type II collagen synthesis; sCOMP, serum cartilage oligomeric matrix protein; sMCP-1, serum monocyte chemoattract protein 1; sMMP-3, serum matrix metalloproteinase 3.

b

Statistically significant difference (P < .05).

Participants

Thirty participants completed all study visits and were included for analysis. Their characteristics are reported in Table 2. No statistically significant differences were found in age, BMI, meniscal injury, chondral injury, meniscal repair, or meniscectomy between the 2 cohorts (P = .31-.93). Although not statistically significant (P = .07), more female participants were represented in profile 1 (67%) compared with profile 2 (33%).

Table 2.

Participant Characteristics a

All Participants (N = 30) Profile 1: Decreased sMCP-1 and sCOMP
(n = 18)
Profile 2: Increased sMCP-1 and sCOMP
(n = 12)
P
Sex, female 53 (16) 67 (12) 33 (4) .07
Age, y b 21.3 ± 4.2 21.4 ± 5.1 21.3 ± 3.2 .93
Body mass indexb 24.0 ± 2.5 24.4 ± 2.4 23.4 ± 2.6 .31
Meniscal injury 73 (22) 72 (13) 75 (9) .87
Chondral injury 37 (11) 33 (6) 42 (5) .73
Meniscal repair 47 (14) 50 (9) 42 (5) .65
Meniscectomy 57 (17) 56 (10) 58 (7) .88
Reported clinically relevant PTOA symptoms c 30 (9) 28 (5) 33 (4) .75
a

Values are expressed as % (n) or mean ± SD. PTOA, posttraumatic osteoarthritis; sCOMP, serum cartilage oligomeric matrix protein; sMCP-1, serum monocyte chemoattract protein 1.

b

Collected preoperatively.

c

Collected 12 months after anterior cruciate ligament reconstruction.

Associations Between Biomarkers and PTOA-Related Symptoms

Biochemical biomarker profiles with increasing sMCP-1 and sCOMP preoperatively to 6 months after ACLR did not demonstrate statistically significant differences in self-reported KOOS Pain (mean difference, −1.78; P = .56; η2 = 0.012), KOOS Symptoms (mean difference, −1.39; P = .73; η2 = 0.004), KOOS ADL (mean difference, −0.47; P = .81; η2 = 0.002), KOOS Sport (mean difference, −2.36; P = .68; η2 = 0.006), or KOOS QOL (mean difference, −2.10; P = .73; η2 = 0.004) at 12 months after ACLR compared with biochemical biomarker profiles that showed decreasing inflammation and cartilage breakdown (Figure 2). No statistically significant associations were seen between the biochemical biomarker profiles and clinically relevant PTOA-related knee symptoms (OR, 1.30; 95% CI, 0.23-6.33). When participants were not clustered into groups, greater sCOMP concentrations preoperatively (r = −0.40; P = .03) and lower sMMP-3 concentrations 6 months after ACLR (r = 0.38; P = .04) were associated with worse KOOS QOL at 12 months after ACLR. All other associations between biomarker concentrations, regardless of time point, and KOOS subscale scores at 12 months after ACLR were weak and not statistically significant (r = −0.27 to 0.29; P = .11 to .985) (Appendix Tables A3-A5, available online).

Figure 2.

Figure 2.

Differences in Knee injury and Osteoarthritis Outcome Score (KOOS) subscales between biochemical biomarker profile groups. White indicates profile 1, characterized by decreased serum monocyte chemoattract protein 1 (sMCP-1) and serum cartilage oligomeric matrix protein (sCOMP) from preoperative sample collection to 6 months after anterior cruciate ligament reconstruction (ACLR). Gray indicates profile 2, characterized by increased sMCP-1 and sCOMP from preoperative sample collection to 6 months after ACLR. The grey box represents the interquartile range. The black horizontal line represents the median. The box black vertical line represents the minimum and maximum data points excluding outliers.

Post Hoc Analysis

After controlling for sex, we found no statistically significant differences in KOOS Pain (P = .85; η2 = 0.012), KOOS Symptoms (P = .87; η2 = 0.002), KOOS ADL (P = .71; η2 = 0.009), KOOS Sport (P = .15; η2 = 0.002), and KOOS QOL (P = .54; η2 < 0.001) at 12 months after ACLR between biochemical biomarker profiles based on changes in concentrations preoperatively to 6 months after ACLR. Although not statistically significant, female participants tended to report lower KOOS Sport scores at 12 months after ACLR compared with male participants (P = .06) (Appendix Table A1, available online). Additionally, no statistically significant associations were found between biochemical biomarker profiles based on changes in concentrations preoperatively to 6 months after ACLR and clinically relevant PTOA-related knee symptoms at 12 months after ACLR after controlling for sex (OR, 1.41; 95% CI, 0.26-7.60) (Appendix Table A2, available online).

Discussion

We identified 2 biochemical biomarker profiles based on a panel of biomarkers characterizing inflammation and cartilage metabolism changes over time. The first cohort was characterized by decreases in sMCP-1 and sCOMP preoperatively to 6 months after ACLR but greater sC2C:sCPII ratio at 6 months after ACLR. The second group had increases in sMCP-1 and sCOMP but lower sC2C:sCPII ratio at 6 months after ACLR. Contrary to our hypotheses, self-reported knee function in pain, symptoms, activities of daily living, sport, and quality of life did not differ between cohorts with varying biomarker profiles. Furthermore, there were no differences in symptomatic PTOA status between the 2 cohorts. These findings suggest that changes in the measured serum biochemical biomarker profiles after ACLR may not be useful in identifying individuals at risk for developing clinically relevant PTOA-related knee symptoms.

The 2 profiles identified in the current cohort differed based on serum biomarkers related to inflammation (ie, sMCP-1) 61 and cartilage metabolism (ie, sCOMP and sC2C:sCPII ratio).3,10,31,50 Both profiles demonstrated unique characteristics related specifically to cartilage metabolism. Profile 2 was characterized based on increases in biomarkers of inflammation (ie, sMCP-1) and cartilage metabolism (ie, sCOMP) linked to idiopathic osteoarthritis preoperatively to 6 months after ACLR, whereas profile 1 had greater type II collagen degradation to synthesis (ie, sC2C:sCPII ratio) at 6 months after ACLR (Table 1). Although an increase in sC2C:sCPII ratio is consistent with an increase in type II collagen degradation, 10 it is less clear how changes in sCOMP may be interpreted because it has been considered a marker of cartilage synthesis and degradation. sCOMP is one of the most commonly explored biomarkers in osteoarthritis. 21 Greater sCOMP concentrations have been linked to idiopathic osteoarthritis pathology and radiographic osteoarthritis progression. 21 Regardless, increases in sCOMP may occur due to the presence of sCOMP fragments in serum that are consistent with cartilage degradation, 31 whereas intact synovial fluid COMP produced by the cartilage may be due to increased cartilage synthesis.3,50 Future research is needed to determine the interaction between the specific metabolic processes linked to these biomarkers and to better understand the differences in joint tissue metabolism of subgroups of individuals after ACLR who are at risk for PTOA.

Similar serum biochemical biomarker profiles indicative of increasing sMCP-1 and sCOMP from preoperatively to 6 months after ACLR have been associated with worse tibiofemoral cartilage composition. 34 Other studies have also reported associations between synovial fluid biochemical biomarker profiles, including high MCP-1, with worse cartilage degeneration2,40 but not self-reported knee function 2 to 5 years after ACLR. 40 One possible explanation for these contrasting results is that early joint tissue metabolism of cartilage breakdown may not cause early PTOA symptoms and disability after ACLR. Osteoarthritis is a disease of the entire joint in which many types of tissues may be affected (ie, meniscus, synovium, ligaments, bone, etc) 35 and related to the development of symptoms and disability. This is supported by previous literature that failed to identify associations between synovial fluid biochemical biomarkers of cartilage degradation after ACL injury with radiographic and symptomatic PTOA 16 years after injury. 41 Although our results suggest a lack of relationship between serum biochemical biomarker changes and self-reported knee function, previous literature has reported associations between synovial biochemical biomarkers indicative of high joint inflammation (ie, interleukin 1 receptor antagonist, interleukin 1α, and interleukin 6) at the time of ACLR and worse self-reported knee function up to 2 years after ACLR.19,33,52 Therefore, changes in serum catabolic biochemical biomarkers may be useful only in identifying individuals with altered cartilage composition related to preradiographic PTOA development but not PTOA-related symptoms. Future research should consider focusing on assessment of synovial fluid biochemical biomarkers of knee joint inflammation such as cytokines in comparison to serum biochemical biomarkers to determine individuals at risk for PTOA symptom development.

Interestingly, we noted a higher proportion of female participants with the profile of decreasing biomarkers of inflammation and cartilage breakdown (ie, sMCP-1 and sCOMP, respectively) and a notable association between sex and the KOOS Sport subscale (P = .06), with female participants reporting worse self-reported knee function in sport compared with men. The association between cluster profile groups and the KOOS Sport subscale remained unchanged when controlled for sex; thus, it is unlikely that sex differences between groups influenced our primary results. However, sex is an important biological outcome that has been shown to influence patient-reported outcomes7,12,14 and biochemical biomarkers 8 after ACLR. Furthermore, male and female patients may require different rehabilitation approaches to improve clinical outcomes after ACLR. 4 Sex differences continue to demonstrate disparate short-term and long-term outcomes after ACLR and should be considered as an important biological covariate in future research efforts.

The current study had several limitations. This study used serum rather than synovial biomarkers. Serum biomarkers provide an assessment of systemic tissue metabolism rather than local knee joint tissue metabolism. Although it is clinically more feasible to collect serial serum samples over time, 23 it is possible that these do not adequately depict joint tissue metabolism occurring locally within the knee. Our study included a modest sample size that may have contributed to limited power in detecting differences in patient-reported outcomes between biochemical biomarker profile groups; thus, our results should be considered preliminary. We included a modest number of biomarkers in the analysis, with most biochemical biomarkers focused on cartilage degradation. Although these biomarkers are relevant after ACLR, as supported by previous studies,45,53,61 other biomarkers may need to be considered in future research. The current study analysis focused on grouping participants based on the changes in their biomarker concentrations from preoperative sample collection to 6 months after ACLR. This approach was limited as it did not group individuals based on magnitude of differences between individual participants at a single time point (ie, preoperatively or 6 months after ACLR). Therefore, a participant with minimal decreases in sMCP-1 and sCOMP biomarker concentrations may have been grouped in profile 1 even if the magnitude of his or her sMCP-1 and sCOMP concentrations preoperatively or at 6 months may have been considerably higher compared with a participant with profile 2. We chose this approach based on recommendations from the FNIH Biomarkers Consortium that changes in biomarker concentrations over time may be more predictive than biomarker concentrations at a single time point. 29 Furthermore, a previous study 34 reported that changes in biomarker concentrations from preoperative assessment to 6 months after ACLR were associated with cartilage composition indicative of proteoglycan density, and we chose to take a similar approach to determine whether a similar relationship existed with PTOA-related knee symptoms. Finally, our study did not assess radiographic evidence of PTOA and included follow-up only to 1 year. Future research may investigate the relationship between symptomatic (ie, illness) and radiographic (ie, disease) evidence of PTOA, which may require a longer follow-up than 1 year.

Conclusion

The results of this preliminary study suggest that our chosen serum biochemical biomarker profiles of sMCP-1 and sCOMP changes were not associated with clinically relevant PTOA symptom development at 1 year after ACLR. Future fully powered studies with more complete biomarker assessments are needed to establish clinically accessible tools to identify individuals at high risk of symptomatic PTOA and targets for therapeutic intervention to reduce the risk of symptomatic PTOA after ACLR.

Supplemental Material

sj-pdf-1-ajs-10.1177_03635465241262797 – Supplemental material for Association of Serum Biochemical Biomarker Profiles of Joint Tissue Inflammation and Cartilage Metabolism With Posttraumatic Osteoarthritis-Related Symptoms at 12 Months After ACLR

Supplemental material, sj-pdf-1-ajs-10.1177_03635465241262797 for Association of Serum Biochemical Biomarker Profiles of Joint Tissue Inflammation and Cartilage Metabolism With Posttraumatic Osteoarthritis-Related Symptoms at 12 Months After ACLR by Caroline Lisee, Sarah Obudzinski, Brian G. Pietrosimone, R. Alexander Creighton, Ganesh Kamath, Lara Longobardi, Richard Loeser, Todd A. Schwartz and Jeffrey T. Spang in The American Journal of Sports Medicine

Footnotes

Submitted June 16, 2023; accepted May 15, 2024.

One or more of the authors has declared the following potential conflict of interest or source of funding: Research reported in this manuscript was supported by funding from the University of North Carolina's Department of Orthopaedics Laurence E. Dahners Research Grant, the National Institute of Arthritis and Musculoskeletal and Skin Disease of the National Institutes of Health (1R03 AR066840-01A1 and P30 AR072580), the North Carolina Translational and Clinical Sciences (TraCS) Institute, and the National Athletic Trainers’ Association Research and Education Foundation (14NewINV001). R.A.C. has received consulting fees from Arthrex and support for education from SouthTech Orthopedics. G.K. has received compensation for services other than consulting from Arthrex. J.S. has received support for education from SouthTech Orthopedics. AOSSM checks author disclosures against the Open Payments Database (OPD). AOSSM has not conducted an independent investigation on the OPD and disclaims any liability or responsibility relating thereto.

ORCID iD: Caroline Lisee Inline graphic https://orcid.org/0000-0003-1771-5734

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Associated Data

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Supplementary Materials

sj-pdf-1-ajs-10.1177_03635465241262797 – Supplemental material for Association of Serum Biochemical Biomarker Profiles of Joint Tissue Inflammation and Cartilage Metabolism With Posttraumatic Osteoarthritis-Related Symptoms at 12 Months After ACLR

Supplemental material, sj-pdf-1-ajs-10.1177_03635465241262797 for Association of Serum Biochemical Biomarker Profiles of Joint Tissue Inflammation and Cartilage Metabolism With Posttraumatic Osteoarthritis-Related Symptoms at 12 Months After ACLR by Caroline Lisee, Sarah Obudzinski, Brian G. Pietrosimone, R. Alexander Creighton, Ganesh Kamath, Lara Longobardi, Richard Loeser, Todd A. Schwartz and Jeffrey T. Spang in The American Journal of Sports Medicine


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