OBJECTIVE: To elucidate disease-specific molecular changes in osteoarthritis (OA) by analyzing the differential gene expression profile of damaged vs intact cartilage areas within the same joint of patients with OA of the knee using a combination of a novel RNA extraction technique and whole-genome oligonucleotide arrays. METHODS: The transcriptome of macroscopically affected vs intact articular cartilage as determined by visual assessment was analyzed using an optimized mill-based total RNA isolation directly from the tissue and high density synthetic oligonucleotide arrays. Articular cartilage samples were obtained from patients with OA of the knee. Expression of differentially regulated genes was validated by real-time quantitative polymerase chain reaction and immunohistochemistry. RESULTS: The amount of RNA obtained by the optimized extraction procedure was at least 1 microg per 500 mg of cartilage and fulfilled the common quality requirements. After hybridization onto HG-U133 Plus 2.0 GeneChips (Affymetrix), 28.6-51.7% of the probe sets on the microarray showed a detectable signal above the signal threshold in the individual samples. A subset of 411 transcripts, which appeared to be differentially expressed, was obtained when applying predefined filtering criteria. Of these, six genes were found to be up-regulated in the affected cartilage of all patients, including insulin-like growth factor binding protein 3 (IGFBP-3), wnt-1-inducible signaling protein 1 (WISP-1), aquaporin 1 (AQP-1), delta/notch-like EGF-repeat containing transmembrane (DNER), decay accelerating factor (DAF), complement factor I (IF). CONCLUSION: The optimized methodical approach reported here not only allows to determine area-specific gene expression profiles of intraindividually different low-RNA containing OA cartilage specimens. In addition, this study also revealed novel genes not yet reported to play a role in the pathophysiology of joint destruction in OA.
OBJECTIVE: To elucidate disease-specific molecular changes in osteoarthritis (OA) by analyzing the differential gene expression profile of damaged vs intact cartilage areas within the same joint of patients with OA of the knee using a combination of a novel RNA extraction technique and whole-genome oligonucleotide arrays. METHODS: The transcriptome of macroscopically affected vs intact articular cartilage as determined by visual assessment was analyzed using an optimized mill-based total RNA isolation directly from the tissue and high density synthetic oligonucleotide arrays. Articular cartilage samples were obtained from patients with OA of the knee. Expression of differentially regulated genes was validated by real-time quantitative polymerase chain reaction and immunohistochemistry. RESULTS: The amount of RNA obtained by the optimized extraction procedure was at least 1 microg per 500 mg of cartilage and fulfilled the common quality requirements. After hybridization onto HG-U133 Plus 2.0 GeneChips (Affymetrix), 28.6-51.7% of the probe sets on the microarray showed a detectable signal above the signal threshold in the individual samples. A subset of 411 transcripts, which appeared to be differentially expressed, was obtained when applying predefined filtering criteria. Of these, six genes were found to be up-regulated in the affected cartilage of all patients, including insulin-like growth factor binding protein 3 (IGFBP-3), wnt-1-inducible signaling protein 1 (WISP-1), aquaporin 1 (AQP-1), delta/notch-like EGF-repeat containing transmembrane (DNER), decay accelerating factor (DAF), complement factor I (IF). CONCLUSION: The optimized methodical approach reported here not only allows to determine area-specific gene expression profiles of intraindividually different low-RNA containing OA cartilage specimens. In addition, this study also revealed novel genes not yet reported to play a role in the pathophysiology of joint destruction in OA.
Authors: Melissa S Ashwell; Michael G Gonda; Kent Gray; Christian Maltecca; Audrey T O'Nan; Joseph P Cassady; Peter L Mente Journal: J Orthop Res Date: 2012-10-01 Impact factor: 3.494
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: Tracey E Swingler; Jasmine G Waters; Rosemary K Davidson; Caroline J Pennington; Xose S Puente; Clare Darrah; Adele Cooper; Simon T Donell; Geoffrey R Guile; Wenjia Wang; Ian M Clark Journal: Arthritis Res Ther Date: 2009-06-23 Impact factor: 5.156