Biomarkers to Predict Rotator Cuff Repair Healing on Postoperative MRI

Rotator cuff repair healing is highly variable with healing failure rates ranging from 11 to 94% [11-15]. A number of variables have been identified which influence rotator cuff repair healing rates including: older age (> 70 years old), size of the tear in anterior posterior dimension, level of tendon retraction, muscle quality and fatty infiltration, osteoporosis, smoking, family history of rotator cuff tears, diagnosis of diabetes mellitus, and level of work activity [7,16-26]. However, there is a paucity of literature and investigation into biomarkers significantly associated with rotator cuff repair healing rates. Tashjian et al. investigated 72 patients undergoing arthroscopic rotator cuff repair for a full-thickness posterosuperior tear. Magnetic resonance imaging studies were performed at a minimum of 1 year postoperatively. The authors found that 42% of repairs failed to heal. Multivariate regression analysis showed a significant association between a family history of rotator cuff tears and overall healing failure (P = .036). Additionally, they identified an increased risk for the presence of a rare allele for SNP rs17583842 single-nucleotide polymorphism (SNP) in the estrogen-related receptor beta (ESRRB) gene. This is the first genetic biomarker to be identified as significantly associated with repair healing. Additional authors have evaluated transcriptomics and gene expression differences in rotator cuff tissue collected during surgery between patients who had good outcomes versus those who had a retear. They found that patients who had poor healing outcomes showed greater expression of gene sets related to extracellular matrix production (P \< .0001) and cellular biosynthetic pathways (P \< .001), while patients who had good healing outcomes showed greater expression of genes associated with the proinflammatory (M1) macrophage phenotype (P \< .05). Although this data is interesting, tissue level biomarkers are less useful in the clinical setting as a preoperative prognostic tool. No studies to our knowledge have identified blood transcriptomic or proteomic biomarkers associated with rotator cuff tear healing.

Therefore, we aim to investigate this through this protocol. Numerous studies have identified that the diagnosis of diabetes mellitus type 2 (DM2) is a risk factor for failure of rotator cuff repair healing [28]. Yang et al. conducted a meta-analysis to compare clinical outcomes and retear rates after rotator cuff repair in patients with and without diabetes. Diabetes was associated with a higher retear rate (19.3% in patients without diabetes vs 28.2% in patients with diabetes; P \< .0001). The retear rate according to the severity of sustained hyperglycemia in the subgroup analysis was 14.6% in patients without diabetes, versus 22.7% in patients with well-controlled diabetes (\<7.0% of preoperative serum HbA1c level; P = .12) and 40% in patients with uncontrolled diabetes (HbA1c level >7.0%; P \< .00001). Recently, studies have identified that serum fructosamine, rather than Hemoglobin A1C percentage, is a more accurate marker of acute glycemic control. Shohat et al. evaluated 1119 patients undergoing total knee arthroplasty. They found that patients with high fructosamine (> 293) were 11.2 times more likely to develop prosthetic joint infection compared with patients with low fructosamine (p = 0.001). Another study published in the prestigious Nature Journal by Shohat et al. assessed the utility of serum fructosamine to predict adverse outcomes following total hip arthroplasty (THA) [30]. Patients with elevated fructosamine were also associated with more readmissions (16.7% vs. 4.4%, p \< 0.007) and a higher mortality rate (3.7% vs. 0.6%, p = 0.057). We hypothesize that fructosamine level is significantly associated with healing rates following rotator cuff repair and plan to investigate this in a prospective fashion through this protocol.

One of the aims of this study protocol is to develop a model using demographics, radiographic parameters/MRI measurements and biomarkers to accurately predict rotator cuff repair healing rates at 1-year following surgery. Kwon et al. conducted a case-control study of 603 patients who underwent arthroscopic rotator cuff repair and had 1-year follow up with a postoperative MRI. Of the 603 patients, the healing rate was 24%. The following independent risk factors were identified in the multivariate analysis: age > 70 years at the time of surgery (P = .003, Odds Ratio (OR) = 2.71), size of the tear in anterior posterior dimension (P = .033, OR = 1.94), level of tendon retraction (P = .000, OR = 4.56), fatty infiltration of infraspinatus exceeding grade 2 (P = .001, OR = 2.91), low bone mineral density as measured on DEXA scans (T score > -2.5, P = .04, OR = 1.95), and high level of work activity (P = .036, OR = 2.18). They created a 15-point scoring system comprised the following: 4 points for retraction; 3 points for fatty infiltration of infraspinatus; and 2 points for anteroposterior tear size, age, bone mineral density, and work activity. These variables were weighted according to multivariate analysis ORs. Patients with less than or equal to 4 points had a 6.0% healing failure rate, and those with greater than or equal to 5 and greater than or equal to 10 points had 55.2% and 86.2% healing failure rates, respectively. This Rotator Cuff Healing Index (ROHI) score is clinically helpful as it can provide preoperative prognostic information to the surgeon and patient to guide decision making on whether to perform an arthroscopic repair, perform a repair with possible patch augmentation, or potentially guide the decision making to a reverse shoulder arthroplasty. Through this study protocol, we aim to identify current accepted protein biomarkers (fructosamine) and perform discovery proteomics and transcriptomics to identify novel biomarkers associated with rotator cuff repair healing.