Abstract
Objectives:
Anterior cruciate ligament (ACL) tears are common in the adolescent athletic population. While ACL reconstruction (ACLR) enjoys largely good clinical results, there is clear variability in patient outcomes that cannot be easily explained by surgical technique. In particular, the occurrence of arthrofibrosis, muscular dysfunction, failure to return to sport and even post-traumatic osteoarthritis are difficult to predict based on demographic parameters. There is ample evidence in animal models that synovial inflammation plays a critical role in the development of joint dysfunction after ligament injury, however the role of synovial inflammation in a clinical ACL population has not been studied previously. Adolescents provide an ideal population in which to study post-ACL joint dysfunction as they typically have no pre-existing joint degeneration.
We hypothesized that higher synovial immune cell infiltration at the time of ACLR would correlate with worse clinical outcomes (e.g., early loss of motion or arthrofibrosis). To investigate this hypothesis, flow cytometry of synovial samples provided a snapshot of the cellular composition of the synovium, scRNA-seq comprehensively examined a subset of those samples, and correlations with patient-reported clinical outcomes were analyzed.
Methods:
Patients aged 12-18 years undergoing primary ACLR were enrolled in an IRB-approved prospective study and demographic/injury information collected. At the time of surgery, an arthroscopic synovial biopsy from the prefemoral synovium was digested into a single cell suspension for immune profiling by multicolor flow cytometry and scRNA-seq. Flow cytometry data (n = 17) was acquired on a multi-channel flow cytometer and then analyzed by Principle Component Analysis (PCA) and hierarchical clustering to group the patients by their synovial immune cell profile. Some cells from 6 of the 17 samples were also used for scRNA-seq. Droplet barcoding of cells, RNA library construction, and sequencing of 41,842 cells total was followed generation of t-SNE and UMAP visualizations. Cells were identified by known cell type markers and prevalence analyzed via two-way ANOVA. Clinical outcomes were collected from 2-week, 6-week, 3-month, 6-month, and final postoperative clinical visits (range of motion, complications) and from patient surveys (IKDC, ACL-RSI). Statistical analysis of demographic/injury variables and clinical outcomes included mixed-effects longitudinal analysis, ANOVA, linear regression, and Pearson/Spearman correlations.
Results:
Seventeen patients were enrolled (9 female/8 male) with a mean follow-up of 8.9 ± months. Analysis of flow cytometry immune profiling revealed three clusters/immunotypes explaining 92.62% of the variation between patients (Fig. 1). There were no significant differences in age, sex, or concomitant meniscal/chondral injury between clusters. The immune cell profile of Type 3 indicated significantly higher immune cell infiltration into the synovium (45% ± 11%, p < 0.005), particularly of adaptive immune cells. Type 1 had lower immune cell infiltration (31.6% ± 3.8%) and adaptive immune contribution while Type 2 was intermediate. Type 1 also had a greater time between injury and surgery (median 99 days, 51-989; p < 0.05) than Type 2 (median 32 days, 21-38) and Type 3 (median 32 days, 13-42), and Type 1 synovium contained more mast cells (2.7 ± 0.78% of total cells, p < 0.05) than Type 2 (1.0 ± 0.39 %) and Type 3 (1.3 ± 0.82%). When a subset of these synovium tissues (n = 6) were analyzed via scRNA-seq, 25 cell types were identified overall (Fig. 2) with immunotype 3 trending towards more T cells and B cells, and a higher CD8+ to CD4+ T cell ratio. The overall immune profile pattern shown as a heatmap (Fig. 3) suggests that Type 3 synovium may experience higher adaptive inflammation compared to Type 1.
The mean 6-month IKDC scores (n = 17, p = 0.99) were 77.93 ± 8.19 for Type 1, 78.55 ± 7.85 for Type 2, and 79.88 ± 14.44 for Type 3 (Fig. 4A). The mean 6-month ACL-RSI scores (n = 15, p = 0.33) were 78.58 ± 15.4 for Type 1, 72.33 ± 11.8 for Type 2, and 57.83 ± 26.4 for Type 3 (Fig. 4A). Knee range of motion was significantly worse for Type 3 in both extension and flexion (Fig. 4B-C, mixed effects p < 0.05), particularly in the 2-week to 3-month post-op range. Additionally, no complications occurred for patients in Type 1, one case of very mild loss of extension (< 3 degrees) was observed in Type 2, while significant complications occurred in Type 3 including one ACL re-rupture requiring revision and a separate case of arthrofibrosis with a 30-degreeflexion contracture requiring lysis of adhesions.
Conclusions:
Our pilot study provides the first analysis of immune cell behavior in the synovium of ACL injured knees at the time of ACLR. Three immunotypes were discovered. Type 1, the cluster with the lowest overall and adaptive inflammatory response corresponded to patients with a mean 3-month delay between injury and surgery. These patients also had the best clinical outcomes. Type 2 and Type 3 clusters included more acute surgeries (~ 1-month post-injury). However, Type 3 showed significantly higher inflammatory infiltrate, adaptive immune cell presence, and a prevalence of cytotoxic T cells. In turn, these patients had decreased early range of motion, lower ACL-RSI scores at 6 months, and higher incidence of surgical arthrofibrosis and graft failure. Thus, while time between injury and surgery is a contributor to inflammation levels at the time of ACLR, there are intrinsic, patient-specific differences in their acute inflammatory response that also contribute. Understanding these patient-specific differences in a larger prospective cohort might help guide targeted prevention strategies for arthrofibrosis, failure to return to sport, or even post-traumatic osteoarthritis.
