Abstract Background Unbiased in silico approaches applied to genome-wide data prioritized putative functional gene variants associating with treatment-resistant ophthalmoplegic myasthenia gravis (OP-MG). Although altered expression of genes harbouring these variants, or associated pathways, were shown in patient-derived transdifferentiated-myocyte models, gene expression in orbital-derived muscle was required to test the validity of the predictions. Methods We sampled orbicularis oculi muscle (OOM) and one paralysed extraocular muscle (EOM) from six individuals with OP-MG during blepharoptosis and re-alignment surgeries, respectively. For controls, the OOMs were sampled from four individuals without myasthenia undergoing surgery for non-muscle causes of ptosis, and one non-paralysed EOM. Using a qPCR array, expression of 120 genes was compared between OP-MG and control OOMs, profiling putative “OP-MG” genes, genes in related biological pathways and genes reported to be dysregulated in MG cases or experimental MG models, and in EOMs of cases with strabismus. Normalization was performed with two stable reference genes. Differential gene expression was compared between OP-MG and control samples using the ΔΔCT method. Co-expression was analysed by pairwise correlation of gene transcripts to infer expression networks. Results Overall, transcript levels were similar in OOMs and EOMs (p = 0.72). In OOMs, significant downregulated expression of eight genes was observed in OP-MG cases compared with controls (> twofold; p ≤ 0.016), including TFAM, a mitochondrial transcription factor, and genes related to the following pathways: atrophy signalling; muscle regeneration and contraction; glycogen synthesis; and extracellular matrix remodelling. Several microRNAs, known to be highly expressed in EOMs, are predicted to regulate some of these genes. Co-expression analyses of gene-pairs suggested high interconnectedness of gene expression networks in OP-MG muscle, but not controls (r > 0.96, p < 0.01). Significant inverse directions of gene-pair correlations were noted in OP-MG versus controls OOM networks (r ≥ 0.92, p < 0.001) involving most OP-MG genes overlapping prominently with muscle atrophy/contractility and oxidative metabolism genes. Conclusions The gene expression in orbital muscles derived from OP-MG individuals compared with normal controls, support the pathogenic hypothesis previously generated from whole genome sequence analyses. Repression of gene transcripts in OP-MG orbital muscle implicate tissue-specific regulatory mechanisms, which may inform future biomarker discovery approaches.