Abstract. Introduction. Risk factors for osteoarthritis include raised BMI and female gender. Whether these two factors influenced synovial gene expression was investigated using a triangulation and modelling strategy which generated 12 datasets of gene expression in synovial tissue from three knee pathologies with matching BMI groups, obese and overweight, and gender distributions. Methodology. Intra-operative synovial biopsies were immersed in RNAlater at 4oC before storage at -80oC. Total RNA was extracted using RNAeasy with gDNA removal. Following RT- PCR and quality assessment, cDNA was applied to Affymetrix Clariom D microarray gene chips. Bioinformatics analyses were performed. Linear models were prepared in limma with gender and BMI factors incorporated sequentially for each pathology comparison, generating 12 models of probes differentially expressed at FDR p<0.05 and Bayes number, B>0. Data analysis of differently expressed genes utilized Ingenuity Pathway Analysis and Cytoscape with Cluego and Cytohubba plug-ins. Results. Expression of 453 synovial genes was influenced by BMI and gender, 360 encode proteins such as HIF-1a, HSF1, HSPA4, HSPA5. Top canonical pathways include Unfolded protein response, Protein Ubiquiitation and Clathrin mediated endocytosis signalling linked by modulation of