LOXL2 protects temporomandibular joint from mitochondrial dysfunction, apoptosis and osteoarthritis like progression

Temporomandibular joint (TMJ) osteoarthritis (OA) affects a significant population, and there are no FDA-approved drugs for its treatment. Our previous studies showed that lysyl oxidase-like-2 (LOXL2) has anabolic effects on cartilage; however, whether LOXL2 plays a role in relieving TMJ-OA remains unknown. The goal of this study was to comprehensively investigate LOXL2 mechanism in TMJ protection, with an emphasis on transcriptomic network analysis, mitochondria, and apoptosis during TMJ-OA. We showed that the TMJ is transcriptionally unique compared to the knee, with elevated Loxl2 expression and cartilage-degenerative genes, potentially indicating its different mechanisms of action. Aggrecan promoter-specific homozygous deletion of Loxl2 in mice resulted in a cartilage-degeneration phenotype, mitochondrial dysfunction, NF-?ß-mediated chondrocyte apoptosis, and inflammatory immune response leading to TMJ-OA-like conditions. IL-1ß is known to induce osteoarthritis via NF-?ß. With regard to translation, adenoviral-Loxl2 transduction in ex-vivo goat cartilage reduced the IL-1ß-mediated degenerative effects. Importantly, LOXL2 preserved IL-1ß–induced mitochondrial dysfunction, p62-mediated mitophagy, apoptosis, and extracellular matrix degeneration. Overall, we identified the protective role of LOXL2 during natural TMJ-OA-like progression and established LOXL2 as a potential candidate gene therapy candidate for future therapeutics. Overall design: A total of 20 temporomandibular joint (TMJ) tissue samples from Acan-Cre;Loxl2^fl/fl mice (Jax #019148) were subjected to RNA sequencing using the Illumina NovaSeq 6000 platform. Among these, 8 samples were vehicle-treated controls, and 12 were LOXL2 conditional knockouts. Raw fastq files were processed by aligning the reads to the Mus musculus mm10 genome assembly. Gene expression levels were quantified using featureCounts to generate a count matrix. Differential gene expression analysis was performed using the DESeq2 package in R, where standard normalization and filtering were applied to identify significant changes in gene expression between the control and knockout groups.