Patellar tendinopathy outcome predictors in jumping athletes: feasibility of measures for a cohort study

Self-reported bio-psycho-social factors partially distinguish patellar tendinopathy from other knee problems and explain patellar tendinopathy severity in jumping athletes: A case-control study

OBJECTIVE

To determine what combinations of self-reported factors distinguish patellar tendinopathy (PT) from other knee problems, and explain PT severity variance.

DESIGN

Case-control study.

SETTING

Social media, private practice and National Health Service.

PARTICIPANTS

An international sample of jumping athletes diagnosed with either PT (n = 132; 30.7 ± 8.9 years; 80 males; VISA-P = 61.6 ± 16.0) or another musculoskeletal knee condition (n = 89; 31.8 ± 9.9 years; 47 males; VISA-P = 62.9 ± 21.2) by a clinician in the last 6 months.

MAIN OUTCOME MEASURES

We considered clinical diagnosis (case = having PT vs control = having other knee problems) as the dependent variable. Severity and sporting impact were defined by VISA-P and availability, respectively.

RESULTS

A model comprising seven factors distinguished PT from other knee problems; training duration (OR = 1.10), sport type (OR = 2.31), injured side (OR = 2.28), pain onset (OR = 1.97), morning pain (OR = 1.89), condition acceptability (OR = 0.39) and swelling (OR = 0.37). Sports-specific function (OR = 1.02) and player level (OR = 4.11) explained sporting availability. 44% of PT severity variance was explained by quality of life (β = 0.32), sports-specific function (β = 0.38) and age (β = -0.17).

CONCLUSION

Sports-specific, biomedical and psychological factors partially distinguish PT from other knee problems. Availability is mainly explained by sports-specific factors, while psychosocial factors impact on severity. Adding sports-specific and bio-psycho-social factors into assessments could help better identification and management of jumping athletes with PT.

Analysis of the lncRNA-Associated Competing Endogenous RNA (ceRNA) Network for Tendinopathy

Background

We aimed to construct the lncRNA-associated competing endogenous RNA (ceRNA) network and distinguish feature lncRNAs associated with tendinopathy.

Methods

We downloaded the gene profile of GSE26051 from the Gene Expression Omnibus (GEO), including 23 normal samples and 23 diseased tendons. Differentially expressed mRNAs (DEmRNAs) and differentially expressed lncRNAs (DElncRNAs) were identified, and functional and pathway enrichment analyses were performed. Protein-protein interaction (PPI) network was constructed and further analyzed by module mining. Moreover, a ceRNA regulatory network was constructed based on the identified lncRNA–mRNA coexpression relationship pairs and miRNA–mRNA regulation pairs.

Results

We identified 1117 DEmRNAs and 57 DElncRNAs from the GEO data. The downregulated DEmRNAs were particularly associated with muscle contraction and muscle filament, while the upregulated ones were linked to extracellular matrix organization and cell adhesion. From the PPI network, 11 modules were extracted. Genes in MCODE 2 (such as TPM4) were significantly involved in cardiomyopathy, and genes in MCODE 4 (such as COL4A3 and COL4A4) were involved in focal adhesion, ECM-receptor interaction, and PI3K-Akt signaling pathway. The ceRNA network contained 7 lncRNAs (MIR133A1HG, LINC01405, PRKCQ-AS1, C10orf71-AS1, MBNL1-AS1, HOTAIRM1, and DNM3OS), 63 mRNAs, and 41 miRNAs. Downregulated lncRNA MIR133A1HG could competitively bind with hsa-miR-659-3p and hsa-miR-218-1-3p to regulate the TPM3. Meanwhile, MIR133A1HG could competitively bind with hsa-miR-1179 to regulate the COL4A3. Downregulated C10orf71-AS1 could competitively bind with hsa-miR-130a-5p to regulate the COL4A4.

Conclusions

Seven important lncRNAs, particularly MIR133A1HG and C10orf71-AS1, were found associated with tendinopathy according to the lncRNA-associated ceRNA network.