OBJECTIVE: To identify osteoarthritis (OA) progression-modulating pathways in articular cartilage and their respective regulatory epigenetic and genetic determinants in end-stage disease. METHODS: Transcriptional activity of CpG was assessed using gene expression data and DNA methylation data for preserved and lesional articular cartilage samples. Disease-responsive transcriptionally active CpG were identified by means of differential methylation between preserved and lesional cartilage. Transcriptionally relevant genetic determinants were addressed by means of single-nucleotide polymorphisms (SNPs) proximal to the OA-responsive transcriptionally active CpG. Statistical analyses were corrected for age, sex, joint, and technical covariates. A random effect was included to correct for possible correlations between paired samples. RESULTS: Of 9,838 transcribed genes in articular cartilage, 2,324 correlated with the methylation status of 3,748 transcriptionally active CpG; both negative (n = 1,741) and positive (n = 2,007) correlations were observed. Hypomethylation and hypermethylation (false discovery rate of <0.05, |Δβ| > 0.05) were observed for 62 and 25 transcriptionally active CpG, respectively, covering 70 unique genes. Enrichment for developmental and extracellular matrix maintenance pathways indicated possible reactivation of endochondral ossification. Finally, we observed 31 and 26 genes for which methylation and expression, respectively, were additionally affected by genetic variation. CONCLUSION: We identified tissue-specific genes involved in OA disease progression, reflected by genetic and pathologic epigenetic regulation of transcription, primarily at genes involved in development. Therefore, transcriptionally active SNPs near these genes may serve as putative susceptibility alleles. Our results constitute an important step toward understanding the reported widespread epigenetic changes occurring in OA articular cartilage and toward subsequent development of treatments targeting disease-driving pathways.
OBJECTIVE: To identify osteoarthritis (OA) progression-modulating pathways in articular cartilage and their respective regulatory epigenetic and genetic determinants in end-stage disease. METHODS: Transcriptional activity of CpG was assessed using gene expression data and DNA methylation data for preserved and lesional articular cartilage samples. Disease-responsive transcriptionally active CpG were identified by means of differential methylation between preserved and lesional cartilage. Transcriptionally relevant genetic determinants were addressed by means of single-nucleotide polymorphisms (SNPs) proximal to the OA-responsive transcriptionally active CpG. Statistical analyses were corrected for age, sex, joint, and technical covariates. A random effect was included to correct for possible correlations between paired samples. RESULTS: Of 9,838 transcribed genes in articular cartilage, 2,324 correlated with the methylation status of 3,748 transcriptionally active CpG; both negative (n = 1,741) and positive (n = 2,007) correlations were observed. Hypomethylation and hypermethylation (false discovery rate of <0.05, |Δβ| > 0.05) were observed for 62 and 25 transcriptionally active CpG, respectively, covering 70 unique genes. Enrichment for developmental and extracellular matrix maintenance pathways indicated possible reactivation of endochondral ossification. Finally, we observed 31 and 26 genes for which methylation and expression, respectively, were additionally affected by genetic variation. CONCLUSION: We identified tissue-specific genes involved in OA disease progression, reflected by genetic and pathologic epigenetic regulation of transcription, primarily at genes involved in development. Therefore, transcriptionally active SNPs near these genes may serve as putative susceptibility alleles. Our results constitute an important step toward understanding the reported widespread epigenetic changes occurring in OA articular cartilage and toward subsequent development of treatments targeting disease-driving pathways.
Authors: Carolina A Bonin; Eric A Lewallen; Saurabh Baheti; Elizabeth W Bradley; Michael J Stuart; Daniel J Berry; Andre J van Wijnen; Jennifer J Westendorf Journal: Gene Date: 2015-10-17 Impact factor: 3.688
Authors: Eric A Lewallen; Carolina A Bonin; Xin Li; Jay Smith; Marcel Karperien; A Noelle Larson; David G Lewallen; Simon M Cool; Jennifer J Westendorf; Aaron J Krych; Alexey A Leontovich; Hee-Jeong Im; Andre J van Wijnen Journal: Gene Date: 2016-07-01 Impact factor: 3.688
Authors: Michael D Rushton; Louise N Reynard; David A Young; Colin Shepherd; Guillaume Aubourg; Fiona Gee; Rebecca Darlay; David Deehan; Heather J Cordell; John Loughlin Journal: Hum Mol Genet Date: 2015-10-13 Impact factor: 6.150