- Email: [email protected]
Genetic variability in response to knee joint injury in multiple LGXSM recombinant inbred mouse strains
S208
Abstracts / Osteoarthritis and Cartilage 25 (2017) S76eS444
NCOA3 gene transcription. Further experiments will elucidate the mechanism of this modulation. 331 EPIGENETIC AND TRANSCRIPTIONAL EFFECTS OPERATE ON THE SUPT3H AND RUNX2 GENES RESIDING AT THE CHROMOSOME 6P21.1 OSTEOARTHRITIS SUSCEPTIBILITY LOCUS AND CORRELATE WITH THE ASSOCIATION SIGNAL
is active in numerous joint tissues, indicating the joint-wide effect of OA genetic susceptibility. The 3' and 5' limits of the DML have been defined to a region less than 600bp. An eQTL is operating on both SUPT3H and RUNX2, consistent with evidence of concomitant expression of the two genes. This study demonstrates that both genes are targets for the epigenetic and genetic effects operating on the OA risk region marked by rs10948172.
S.J. Rice, G. Aubourg, A.K. Sorial, D. Deehan, J. Loughlin, L.N. Reynard. Newcastle Univ., Newcastle upon Tyne, United Kingdom Purpose: The rs10948172 single nucleotide polymorphism (SNP) has been associated with osteoarthritis (OA) at genome-wide significance. This SNP marks a 570kb region of chromosome 6p21.1, containing 218 SNPs in high linkage disequilibrium (LD) with rs10948172 (r2>0.8). The nearest genes are SUPT3H and RUNX2, which have a syntenic relationship. RUNX2 encodes a transcription factor essential for skeletogenesis, and has two isoforms with distinct promoter regions, P1 and P2. SUPT3H encodes a histone modulator. The SUPT3H promoter positively influences RUNX2 P1 activity in trans. A CpG island located 82kb upstream of rs10948172 contains 48 CpGs. Methylation at 6 of these, including cg13979708, cg19254793, cg20913747, and cg18551225, correlates with rs10948172 genotype in OA joint tissues. The risk allele (G) is associated with DNA hypomethylation. rs10948172 therefore marks a differentially methylated locus (DML) that acts as a methylation quantitative trait locus (meQTL) in OA. A study investigating cartilage thickness and OA has recently reported rs10948155 and rs12206662 as independent association signals. They are located at the SUPT3H-RUNX2 locus, 7kb upstream of the DML, and within intron 2 of RUNX2, respectively. The aims of this study were: 1) to define the limits of the DML and determine whether the meQTL operates in bone; 2) to identify at which SNP the greatest genotypic effect upon DNA methylation resides; and 3) to investigate whether an expression quantitative trait locus (eQTL) is operating on SUPT3H and/or RUNX2 and could therefore be the ultimate functional mechanism behind the OA association signal. Methods: Pyrosequencing assays were designed for additional CpGs. DNA and RNA were extracted from joint tissues of OA patients (synovium, n ¼ 86; fat pad, n ¼ 80; bone, n ¼ 30). DNA was bisulphite converted and methylation quantified by pyrosequencing. Patient DNA samples were genotyped at rs10948172, rs10948155, and also rs62435998, one of two SNPs in perfect LD (r2 ¼ 1) that are located within the DML and are in high LD (r2>0.7) with both rs10948172 and rs10948155. cDNA was synthesised from RNA and gene expression levels of SUPT3H, RUNX2 P1, and both RUNX2 isoforms were measured using qPCR. The proxy SNP rs529125 was used to measure SUPT3H allelic expression imbalance (AEI) in heterozygote patients. To measure AEI in RUNX2, rs1200428, located in the 3' UTR of the gene, was used. LD between SNPs was calculated using SHEsis. Results: An meQTL was identified at 11/14 CpGs tested in synovium, and 8/12 CpGs in fat pad. At 3 CpGs, located þ450, þ462, and þ464bp downstream of cg13979708, no meQTL was identified in either tissue (p>0.05). At a CpG located -124bp upstream of cg10979708, an meQTL was identified in synovium (n ¼ 82, p < 0.001), but was not detected in fat pad (n ¼ 61, p ¼ 0.06). The strongest genotypic effect was observed at cg13979708 in synovium (percentage of variability explained by genotype was 66.1% for rs10948172, 41.6 % for rs62435998, 19.0% for rs10948155). The genotypic effect at all CpGs followed the trend rs10948172 > rs62435998 > rs10948155. LD was calculated between all SNPs investigated (Figure 1). At all investigated CpGs, the meQTL was strongest in synovium > fat pad > bone. Six CpGs were investigated in bone (n ¼ 30), and an meQTL was identified at cg13979708 (p < 0.05). AEI of SUPT3H was observed in all three tissues (synovium, n ¼ 27, p < 0.0001; bone, n ¼ 10, p < 0.001; fat pad, n ¼ 21, p < 0.01). The risk allele (G) was associated with increased gene expression. Data also suggest the presence of RUNX2 AEI in synovium. A positive correlation in gene expression was observed between SUPT3H and the RUNX2 P1 transcript in synovium (n ¼ 75, r2 ¼ 0.21, p < 0.0001), fat pad (n ¼ 36, r2 ¼ 0.38, p < 0.0001), and bone (n ¼ 29, r2 ¼ 0.69, p < 0.0001). When both RUNX2 isoforms were compared to SUPT3H expression, a similar effect was observed (r2 ¼ 0.24, p < 0.0001; r2 ¼ 0.40, p < 0.0001; and r2 ¼ 0.81, p < 0.0001, respectively). Conclusions: The greatest genotypic effect on methylation was observed at rs10948172, indicating that the meQTL is primarily modulated by rs10948172 or a SNP in very high LD with it. This meQTL
Figure 1. LD (r2) between SNPs residing at the SUPT3H-RUNX2 susceptibility locus. n ¼ 378-534. 332 GENETIC VARIABILITY IN RESPONSE TO KNEE JOINT INJURY IN MULTIPLE LGXSM RECOMBINANT INBRED MOUSE STRAINS N. Chinzei y, M. Rai y, S. Hashimoto z, K. Takebe x, L.J. Sandell y. y Washington Univ. Sch. of Med., St. Louis, MO, USA; z Kobe Univ. Graduate Sch. of Med., Kobe, Japan; x Kohnan Kakogawa Hosp., Kakogawa, Japan Purpose: Osteoarthritis (OA) is a slow progressing, irreversible joint disorder. Emerging evidence indicates that 50e75% of variation in OA in humans is genetic, however, how gene mutations cause and/or protect individuals from OA remains elusive. Evidence from genome-wide association studies in humans has shown that OA appears to be highly polygenic with multiple risk-alleles conferring small effects. Thus, the knowledge of the genetic contribution to the susceptibility or protection from OA would greatly contribute to our understanding of OA and would provide not only potential treatment strategies but may also help predict individuals who are at risk for developing OA. We used a population genetics approach to screen mouse strains for their susceptibility to post-traumatic OA. Here, we used 12 recombinant inbred (RI) strains of mice generated from LG/J (large) by SM/J (small) intercross. Individuals within an RI strain are genetically identical but each strain is a different recombination of the parental genotypes therefore any phenotypic differences indicate genetic differences. Methods: 10-wk old male mice (n ¼ 3-10) were anesthetized to induce post-traumatic OA in the right knee by destabilization of medial meniscus (DMM). Left knee served as a sham control. Mice were sacrificed at 8-wk after surgery and processed for histology. Coronal sections taken through the joint were stained with toluidine blue staining. Post-traumatic OA was assessed by cartilage degeneration (OARSI score) and synovitis. Prior to histology, joints were scanned using micro-CT for the 3-dimentional analysis of trabecular bone volume fraction (BV/TV), trabecular number (Tb.N.), trabecular thickness (Tb.Th.), trabecular separation (Tb.Sp.), structure model index (SMI), and connectivity
Abstracts / Osteoarthritis and Cartilage 25 (2017) S76eS444
S209
density index (CDI). Subchondral bone plate-thickness and ectopic calcifications were also measured. Results: There was a significant genotype (strain) by procedure (surgery) interaction for all parameters studied (except for CDI and Tb.N.) (P < 0.05) indicating strain differences for susceptibility to OA. We observed that different RI strains exhibited varying degree of cartilage degeneration (Fig. 1A). We were able to segregate strains into susceptible (e.g. LGXSM-33, LGXSM-46, LGXSM-5, SM/J) and protected (e.g. LGXSM-6, LGXSM-131b, LGXSM-163, LG/J) categories in addition to some intermediate strains (e.g. LGXSM-18, LGXSM-19, LGXSM-120a) based on summed OA score (Fig. 1B), synovitis and ectopic calcification. Furthermore, we found a significant (P < 0.001) correlation (r ¼ 0.68) between summed OA score and synovitis suggesting that 47% (r2 ¼ 0.47) of variance is shared between cartilage degeneration and synovitis. Conclusions: Our study identified a number of mouse strains that are protected or susceptible to post-traumatic OA, which is explained by their genetic composition. Further investigation into gene expression profile of these strains will identify the exact genomic regions (expression quantitative trait loci) that orchestrate the phenotypic differences. These studies can further identify the pathways and mechanisms underlying OA susceptibility.
patterns (A-E) and indicated biological pathways that mediate the alterations in transcription. Functional links that connect the identified expression patterns to the PPAR signaling, adipogenesis (A); Wnt signaling (B); endochondral ossification (C); matrix metalloproteinases, ACE/RAGE pathway (D); Toll-like receptor and IL1 signaling (E) pathways were found. The dynamic profiles of transcriptional changes were assigned to cellular compartments of the knee joint. Conclusions: Our study provides evidences that the progression of cartilage damage is driven by complex but precise regulation of gene patterns that are induced or suppressed during a various stages of cartilage damage. We see a sharp temporary loss of the transcripts involved in WNT pathway as well as constant downregulation of genes related to endochondral ossification. While, the decrease of transcript abundance of genes connected to PPARG-signaling was more gradual. Transcripts related to immunological response show early, while connected to matrix metalloproteinases delayed increase in the abundance levels. We conclude that the expression of PPARG-signaling genes correlates negatively with the different stages of OA, and matrix metalloproteinases genes correlate positively with OA development. Moreover, our results indicate that the observed transcriptional alterations are located in the diverse cellular compartments of the knee cartilage. We can speculate that during OA pathogenesis synoviocytes, osteoblasts, fibroblasts epithelial and immunological cells process specific molecular complementary (diseaserelevant intracellular signaling cascades) or contrary physiological programs. The presented classification of transcriptional alterations associated with the development of cartilage degeneration provides novel insight into the OA disease process. Integration across multiple tissues holds the promise of identifying new areas of so far unrecognized molecular networks and of characterising OA processes in depth, thus leading to the development of new therapeutic interventions. Supported by National Science Centre, Poland grants: OPUS UMO-2014/13/B/NZ7/ 02311, ETIUDA UMO-2015/16/T/NZ7/00052 and statutory funds.
Figure 1. Strain differences in cartilage degeneration and OA score. A. Representative images showing cartilage degeneration on the medial tibial plateau: (a) sham, (b) no degeneration (only focal proteoglycan loss), (c) moderate degeneration, (d) severe degeneration with fibrillation (arrows show cartilage degeneration), scale bar ¼ 100 mm, B. Summed OA score. Lowercase letters in the graph indicate significant differences (P < 0.05) among RI strains. No significant differences were found in sham knees.
334 MOLECULAR PHENOTYPING OF PATIENT CHONDROCYTES REVEALS GENES AND PATHWAYS INVOLVED IN OSTEOARTHRITIS
333 THE DISSECTION OF GENE PATTERNS ALTERED IN KNEE CARTILAGE IN A RAT MODEL OF OSTEOARTHRITIS M. Korostynski, N. Malek, M. Piechota, K. Starowicz. Inst. of Pharmacology Polish Academy of Sci., KRAKOW, Poland Purpose: Osteoarthritis (OA) is a joint disease that mostly affects cartilage. It is the most common cause of musculoskeletal pain and disability in the knee joint. Gene regulations are implicated in driving an imbalance between the expression of catabolic and anabolic factors, leading eventually to osteoarthritic cartilage degeneration. Functional genomics is a challenging new way to address a complex disease like osteoarthritis on a molecular level. A functional genomic approach to OA focuses on measuring changes in gene expression, allowing to discover new factors involved in the disease as well as factors involved in joint tissue development or maintenance. A deeper understanding of molecular events within the tissue cells (i.e., the chondrocytes) will provide new cellular targets for therapeutic intervention. Methods: We applied transcriptomics study in order to compare data between healthy and various OA states to better understand the mechanisms underlying a disease. In our model, knee OA was induced in male Wistar rats by intra-articular sodium monoiodoacetate (MIA) injection. Whole-genome microarrays were used to analyze gene expression alterations in a time-course of OA development (2, 14 and 28 days) in rat knee joint. We used bioinformatics tools to recognize and characterize patterns of co-expressed transcripts. Results: The identified groups of genes were analyzed for enrichment of regulatory mechanisms, functional classes and cell-type specific expression. The analysis of transcriptional alterations revealed 272 regulated transcripts (ANOVA FDR<0.1% and fold>2). Bioinformatics approaches led to the identification of five main gene expression
J. Steinberg y, G. Ritchie y, T. Roumeliotis y, R. Jayasuriya z, R. Brooks x, A. Binch k, K. Shah z, R. Coyle y, M. Pardo y, C. Le Maitre k, Y. Ramos ¶, R. Nelissen ¶, I. Meulenbelt ¶, A. McCaskie x, J. Choudhary y, M. Wilkinson z, E. Zeggini y. y Wellcome Trust Sanger Inst., Hinxton, United Kingdom,; z Univ. of Sheffield, Sheffield, United Kingdom; x Univ. of Cambridge, Cambridge, United Kingdom; k Sheffield Hallam Univ., Sheffield, United Kingdom; ¶ Leiden Univ. Med. Ctr., Leiden, Netherlands Purpose: Musculoskeletal disease is the second greatest cause of disability world-wide, affecting over 1.7 billion people. Osteoarthritis (OA) affects over 40% of individuals over the age of 70, is a leading cause of pain and loss of physical function, and is associated with higher risk of quality of life decline, comorbidity and death. The health economic burden of OA is increasing, commensurate with longevity and obesity prevalence. In the absence of a curative therapy, management strategies are shifting to disease prevention and treatment of early OA. However, the underlying mechanisms of disease pathogenesis and progression are poorly characterised. Unlike for many other diseases, the relevant tissue for OA is readily accessible at joint replacement surgery. This enables the study of molecular processes at the right tissue, both to fill a gap in our fundamental understanding of biology and to identify novel therapeutic avenues. Methods: The epigenome, transcriptome and proteome of cell types relevant to OA remain relatively uncharacterised. We have characterised isolated chondrocytes from intact and degraded cartilage samples following total knee replacement in 12 patients in terms of epigenetics (Illumina 450k methylation array), gene expression (RNAseq) and protein expression (quantitative proteomics). We have established a robust pipeline for collecting tissue, extracting high-quality DNA, RNA and protein, and processing samples through the omics platforms. The pilot has also instigated the development of systems biology approaches for the integration of multidimensional data. Results: We find a significant negative correlation between promoter region methylation and gene expression (Spearman’s rho ¼ -0.43, p < 2.2 x 10-16) and a positive correlation (rho ¼ 0.29, p < 2.2 x 10-16) between RNA and protein expression levels. We identify five discordant cases in which the gene is significantly over-expressed at the RNA level and significantly less abundant at the protein level in the degraded tissue (COL4A2, CXCL12, FGF10, HTRA3 and WNT5B). All five proteins are
Abstracts / Osteoarthritis and Cartilage 25 (2017) S76eS444
NCOA3 gene transcription. Further experiments will elucidate the mechanism of this modulation. 331 EPIGENETIC AND TRANSCRIPTIONAL EFFECTS OPERATE ON THE SUPT3H AND RUNX2 GENES RESIDING AT THE CHROMOSOME 6P21.1 OSTEOARTHRITIS SUSCEPTIBILITY LOCUS AND CORRELATE WITH THE ASSOCIATION SIGNAL
is active in numerous joint tissues, indicating the joint-wide effect of OA genetic susceptibility. The 3' and 5' limits of the DML have been defined to a region less than 600bp. An eQTL is operating on both SUPT3H and RUNX2, consistent with evidence of concomitant expression of the two genes. This study demonstrates that both genes are targets for the epigenetic and genetic effects operating on the OA risk region marked by rs10948172.
S.J. Rice, G. Aubourg, A.K. Sorial, D. Deehan, J. Loughlin, L.N. Reynard. Newcastle Univ., Newcastle upon Tyne, United Kingdom Purpose: The rs10948172 single nucleotide polymorphism (SNP) has been associated with osteoarthritis (OA) at genome-wide significance. This SNP marks a 570kb region of chromosome 6p21.1, containing 218 SNPs in high linkage disequilibrium (LD) with rs10948172 (r2>0.8). The nearest genes are SUPT3H and RUNX2, which have a syntenic relationship. RUNX2 encodes a transcription factor essential for skeletogenesis, and has two isoforms with distinct promoter regions, P1 and P2. SUPT3H encodes a histone modulator. The SUPT3H promoter positively influences RUNX2 P1 activity in trans. A CpG island located 82kb upstream of rs10948172 contains 48 CpGs. Methylation at 6 of these, including cg13979708, cg19254793, cg20913747, and cg18551225, correlates with rs10948172 genotype in OA joint tissues. The risk allele (G) is associated with DNA hypomethylation. rs10948172 therefore marks a differentially methylated locus (DML) that acts as a methylation quantitative trait locus (meQTL) in OA. A study investigating cartilage thickness and OA has recently reported rs10948155 and rs12206662 as independent association signals. They are located at the SUPT3H-RUNX2 locus, 7kb upstream of the DML, and within intron 2 of RUNX2, respectively. The aims of this study were: 1) to define the limits of the DML and determine whether the meQTL operates in bone; 2) to identify at which SNP the greatest genotypic effect upon DNA methylation resides; and 3) to investigate whether an expression quantitative trait locus (eQTL) is operating on SUPT3H and/or RUNX2 and could therefore be the ultimate functional mechanism behind the OA association signal. Methods: Pyrosequencing assays were designed for additional CpGs. DNA and RNA were extracted from joint tissues of OA patients (synovium, n ¼ 86; fat pad, n ¼ 80; bone, n ¼ 30). DNA was bisulphite converted and methylation quantified by pyrosequencing. Patient DNA samples were genotyped at rs10948172, rs10948155, and also rs62435998, one of two SNPs in perfect LD (r2 ¼ 1) that are located within the DML and are in high LD (r2>0.7) with both rs10948172 and rs10948155. cDNA was synthesised from RNA and gene expression levels of SUPT3H, RUNX2 P1, and both RUNX2 isoforms were measured using qPCR. The proxy SNP rs529125 was used to measure SUPT3H allelic expression imbalance (AEI) in heterozygote patients. To measure AEI in RUNX2, rs1200428, located in the 3' UTR of the gene, was used. LD between SNPs was calculated using SHEsis. Results: An meQTL was identified at 11/14 CpGs tested in synovium, and 8/12 CpGs in fat pad. At 3 CpGs, located þ450, þ462, and þ464bp downstream of cg13979708, no meQTL was identified in either tissue (p>0.05). At a CpG located -124bp upstream of cg10979708, an meQTL was identified in synovium (n ¼ 82, p < 0.001), but was not detected in fat pad (n ¼ 61, p ¼ 0.06). The strongest genotypic effect was observed at cg13979708 in synovium (percentage of variability explained by genotype was 66.1% for rs10948172, 41.6 % for rs62435998, 19.0% for rs10948155). The genotypic effect at all CpGs followed the trend rs10948172 > rs62435998 > rs10948155. LD was calculated between all SNPs investigated (Figure 1). At all investigated CpGs, the meQTL was strongest in synovium > fat pad > bone. Six CpGs were investigated in bone (n ¼ 30), and an meQTL was identified at cg13979708 (p < 0.05). AEI of SUPT3H was observed in all three tissues (synovium, n ¼ 27, p < 0.0001; bone, n ¼ 10, p < 0.001; fat pad, n ¼ 21, p < 0.01). The risk allele (G) was associated with increased gene expression. Data also suggest the presence of RUNX2 AEI in synovium. A positive correlation in gene expression was observed between SUPT3H and the RUNX2 P1 transcript in synovium (n ¼ 75, r2 ¼ 0.21, p < 0.0001), fat pad (n ¼ 36, r2 ¼ 0.38, p < 0.0001), and bone (n ¼ 29, r2 ¼ 0.69, p < 0.0001). When both RUNX2 isoforms were compared to SUPT3H expression, a similar effect was observed (r2 ¼ 0.24, p < 0.0001; r2 ¼ 0.40, p < 0.0001; and r2 ¼ 0.81, p < 0.0001, respectively). Conclusions: The greatest genotypic effect on methylation was observed at rs10948172, indicating that the meQTL is primarily modulated by rs10948172 or a SNP in very high LD with it. This meQTL
Figure 1. LD (r2) between SNPs residing at the SUPT3H-RUNX2 susceptibility locus. n ¼ 378-534. 332 GENETIC VARIABILITY IN RESPONSE TO KNEE JOINT INJURY IN MULTIPLE LGXSM RECOMBINANT INBRED MOUSE STRAINS N. Chinzei y, M. Rai y, S. Hashimoto z, K. Takebe x, L.J. Sandell y. y Washington Univ. Sch. of Med., St. Louis, MO, USA; z Kobe Univ. Graduate Sch. of Med., Kobe, Japan; x Kohnan Kakogawa Hosp., Kakogawa, Japan Purpose: Osteoarthritis (OA) is a slow progressing, irreversible joint disorder. Emerging evidence indicates that 50e75% of variation in OA in humans is genetic, however, how gene mutations cause and/or protect individuals from OA remains elusive. Evidence from genome-wide association studies in humans has shown that OA appears to be highly polygenic with multiple risk-alleles conferring small effects. Thus, the knowledge of the genetic contribution to the susceptibility or protection from OA would greatly contribute to our understanding of OA and would provide not only potential treatment strategies but may also help predict individuals who are at risk for developing OA. We used a population genetics approach to screen mouse strains for their susceptibility to post-traumatic OA. Here, we used 12 recombinant inbred (RI) strains of mice generated from LG/J (large) by SM/J (small) intercross. Individuals within an RI strain are genetically identical but each strain is a different recombination of the parental genotypes therefore any phenotypic differences indicate genetic differences. Methods: 10-wk old male mice (n ¼ 3-10) were anesthetized to induce post-traumatic OA in the right knee by destabilization of medial meniscus (DMM). Left knee served as a sham control. Mice were sacrificed at 8-wk after surgery and processed for histology. Coronal sections taken through the joint were stained with toluidine blue staining. Post-traumatic OA was assessed by cartilage degeneration (OARSI score) and synovitis. Prior to histology, joints were scanned using micro-CT for the 3-dimentional analysis of trabecular bone volume fraction (BV/TV), trabecular number (Tb.N.), trabecular thickness (Tb.Th.), trabecular separation (Tb.Sp.), structure model index (SMI), and connectivity
Abstracts / Osteoarthritis and Cartilage 25 (2017) S76eS444
S209
density index (CDI). Subchondral bone plate-thickness and ectopic calcifications were also measured. Results: There was a significant genotype (strain) by procedure (surgery) interaction for all parameters studied (except for CDI and Tb.N.) (P < 0.05) indicating strain differences for susceptibility to OA. We observed that different RI strains exhibited varying degree of cartilage degeneration (Fig. 1A). We were able to segregate strains into susceptible (e.g. LGXSM-33, LGXSM-46, LGXSM-5, SM/J) and protected (e.g. LGXSM-6, LGXSM-131b, LGXSM-163, LG/J) categories in addition to some intermediate strains (e.g. LGXSM-18, LGXSM-19, LGXSM-120a) based on summed OA score (Fig. 1B), synovitis and ectopic calcification. Furthermore, we found a significant (P < 0.001) correlation (r ¼ 0.68) between summed OA score and synovitis suggesting that 47% (r2 ¼ 0.47) of variance is shared between cartilage degeneration and synovitis. Conclusions: Our study identified a number of mouse strains that are protected or susceptible to post-traumatic OA, which is explained by their genetic composition. Further investigation into gene expression profile of these strains will identify the exact genomic regions (expression quantitative trait loci) that orchestrate the phenotypic differences. These studies can further identify the pathways and mechanisms underlying OA susceptibility.
patterns (A-E) and indicated biological pathways that mediate the alterations in transcription. Functional links that connect the identified expression patterns to the PPAR signaling, adipogenesis (A); Wnt signaling (B); endochondral ossification (C); matrix metalloproteinases, ACE/RAGE pathway (D); Toll-like receptor and IL1 signaling (E) pathways were found. The dynamic profiles of transcriptional changes were assigned to cellular compartments of the knee joint. Conclusions: Our study provides evidences that the progression of cartilage damage is driven by complex but precise regulation of gene patterns that are induced or suppressed during a various stages of cartilage damage. We see a sharp temporary loss of the transcripts involved in WNT pathway as well as constant downregulation of genes related to endochondral ossification. While, the decrease of transcript abundance of genes connected to PPARG-signaling was more gradual. Transcripts related to immunological response show early, while connected to matrix metalloproteinases delayed increase in the abundance levels. We conclude that the expression of PPARG-signaling genes correlates negatively with the different stages of OA, and matrix metalloproteinases genes correlate positively with OA development. Moreover, our results indicate that the observed transcriptional alterations are located in the diverse cellular compartments of the knee cartilage. We can speculate that during OA pathogenesis synoviocytes, osteoblasts, fibroblasts epithelial and immunological cells process specific molecular complementary (diseaserelevant intracellular signaling cascades) or contrary physiological programs. The presented classification of transcriptional alterations associated with the development of cartilage degeneration provides novel insight into the OA disease process. Integration across multiple tissues holds the promise of identifying new areas of so far unrecognized molecular networks and of characterising OA processes in depth, thus leading to the development of new therapeutic interventions. Supported by National Science Centre, Poland grants: OPUS UMO-2014/13/B/NZ7/ 02311, ETIUDA UMO-2015/16/T/NZ7/00052 and statutory funds.
Figure 1. Strain differences in cartilage degeneration and OA score. A. Representative images showing cartilage degeneration on the medial tibial plateau: (a) sham, (b) no degeneration (only focal proteoglycan loss), (c) moderate degeneration, (d) severe degeneration with fibrillation (arrows show cartilage degeneration), scale bar ¼ 100 mm, B. Summed OA score. Lowercase letters in the graph indicate significant differences (P < 0.05) among RI strains. No significant differences were found in sham knees.
334 MOLECULAR PHENOTYPING OF PATIENT CHONDROCYTES REVEALS GENES AND PATHWAYS INVOLVED IN OSTEOARTHRITIS
333 THE DISSECTION OF GENE PATTERNS ALTERED IN KNEE CARTILAGE IN A RAT MODEL OF OSTEOARTHRITIS M. Korostynski, N. Malek, M. Piechota, K. Starowicz. Inst. of Pharmacology Polish Academy of Sci., KRAKOW, Poland Purpose: Osteoarthritis (OA) is a joint disease that mostly affects cartilage. It is the most common cause of musculoskeletal pain and disability in the knee joint. Gene regulations are implicated in driving an imbalance between the expression of catabolic and anabolic factors, leading eventually to osteoarthritic cartilage degeneration. Functional genomics is a challenging new way to address a complex disease like osteoarthritis on a molecular level. A functional genomic approach to OA focuses on measuring changes in gene expression, allowing to discover new factors involved in the disease as well as factors involved in joint tissue development or maintenance. A deeper understanding of molecular events within the tissue cells (i.e., the chondrocytes) will provide new cellular targets for therapeutic intervention. Methods: We applied transcriptomics study in order to compare data between healthy and various OA states to better understand the mechanisms underlying a disease. In our model, knee OA was induced in male Wistar rats by intra-articular sodium monoiodoacetate (MIA) injection. Whole-genome microarrays were used to analyze gene expression alterations in a time-course of OA development (2, 14 and 28 days) in rat knee joint. We used bioinformatics tools to recognize and characterize patterns of co-expressed transcripts. Results: The identified groups of genes were analyzed for enrichment of regulatory mechanisms, functional classes and cell-type specific expression. The analysis of transcriptional alterations revealed 272 regulated transcripts (ANOVA FDR<0.1% and fold>2). Bioinformatics approaches led to the identification of five main gene expression
J. Steinberg y, G. Ritchie y, T. Roumeliotis y, R. Jayasuriya z, R. Brooks x, A. Binch k, K. Shah z, R. Coyle y, M. Pardo y, C. Le Maitre k, Y. Ramos ¶, R. Nelissen ¶, I. Meulenbelt ¶, A. McCaskie x, J. Choudhary y, M. Wilkinson z, E. Zeggini y. y Wellcome Trust Sanger Inst., Hinxton, United Kingdom,; z Univ. of Sheffield, Sheffield, United Kingdom; x Univ. of Cambridge, Cambridge, United Kingdom; k Sheffield Hallam Univ., Sheffield, United Kingdom; ¶ Leiden Univ. Med. Ctr., Leiden, Netherlands Purpose: Musculoskeletal disease is the second greatest cause of disability world-wide, affecting over 1.7 billion people. Osteoarthritis (OA) affects over 40% of individuals over the age of 70, is a leading cause of pain and loss of physical function, and is associated with higher risk of quality of life decline, comorbidity and death. The health economic burden of OA is increasing, commensurate with longevity and obesity prevalence. In the absence of a curative therapy, management strategies are shifting to disease prevention and treatment of early OA. However, the underlying mechanisms of disease pathogenesis and progression are poorly characterised. Unlike for many other diseases, the relevant tissue for OA is readily accessible at joint replacement surgery. This enables the study of molecular processes at the right tissue, both to fill a gap in our fundamental understanding of biology and to identify novel therapeutic avenues. Methods: The epigenome, transcriptome and proteome of cell types relevant to OA remain relatively uncharacterised. We have characterised isolated chondrocytes from intact and degraded cartilage samples following total knee replacement in 12 patients in terms of epigenetics (Illumina 450k methylation array), gene expression (RNAseq) and protein expression (quantitative proteomics). We have established a robust pipeline for collecting tissue, extracting high-quality DNA, RNA and protein, and processing samples through the omics platforms. The pilot has also instigated the development of systems biology approaches for the integration of multidimensional data. Results: We find a significant negative correlation between promoter region methylation and gene expression (Spearman’s rho ¼ -0.43, p < 2.2 x 10-16) and a positive correlation (rho ¼ 0.29, p < 2.2 x 10-16) between RNA and protein expression levels. We identify five discordant cases in which the gene is significantly over-expressed at the RNA level and significantly less abundant at the protein level in the degraded tissue (COL4A2, CXCL12, FGF10, HTRA3 and WNT5B). All five proteins are