- Email: [email protected]
Specific increase of methylation age in osteoarthritis cartilage
Osteoarthritis and Cartilage 24 (2016) S63eS534
Poster Presentations Posters Aging 91 SPECIFIC INCREASE OF METHYLATION AGE IN OSTEOARTHRITIS CARTILAGE L. Vidal y, Y. Lopez-Golan y, I. Rego-Perez z, S. Horvath x, F.J. Blanco z, J.A. Riancho k, J.J. Gomez-Reino y, A. Gonzalez y. y Inst. Investigacion Sanitaria-Hosp. Clinico Univ. de Santiago, Santiago de Compostela, Spain; z INIBIC-Complejo Hosp. Univ. A Coruna, A Coruna, Spain; x David Geffen Sch. of Med., Univ. of California Los Angeles, Los Angeles, CA, USA; k Hosp. U. bM. Valdecilla-IFIMAV, Univ. of Cantabria, Santander, Spain Purpose: The major risk factor for osteoarthritis (OA) is old age. However, the relationship between aging and OA is incompletely understood. Among the joint changes associated with old age are chondrocyte senescence, the decline in matrix production and an altered response to trauma. However, a systemic component of premature aging has also been suggested by the increased presence of old-age comorbidities in the OA patients and by a biomarker of cellular age, telomere length. Telomere shortening has been observed in OA chondrocytes, but also in a study of blood cells from hand OA patients (Zhai et al. Ann Rheum Dis 2006). The reproducibility and implications of these changes in blood cells are still unclear. The recent discovery of a new biomarker of cellular age provides a new opportunity to address these questions. This biomarker is made of changes in DNA methylation at specific sites in the genome. It correlates with chronological age in healthy controls more accurately than telomere length. Therefore, we have analyzed this biomarker at the blood, cartilage and bone levels to distinguish between joint specific and systemic evidence of accelerated aging. Methods: Three collections of samples were investigated. The first included 890 blood samples stratified as 273 from severe hip OA patients, 229 from severe knee OA patients, 206 from hand OA patients and 182 from controls without OA symptoms and without OA in hip radiographs. The second collection included tibial plateau cartilage samples from 18 cadavers with no macroscopic signs of OA and from 23 knee OA patients undergoing joint replacement surgery. The third collection included femoral head bone samples from 34 osteoporosis fracture (OP) patients, 11 healthy control cadavers without signs of OA and 33 hip OA patients at the time of total joint replacement. Methylation age was determined by analyzing CpG methylation at specific sites. For the blood samples, we analyzed a panel of eight sites derived from Weidner et al. (Genome Biol. 2014) and analyzed with methylation-sensitive single-nucleotide primer extension. For the cartilage and bone samples, we used a panel of 353 age-related CpG sites described by Horvath in (Genome Biol. 2013) as multi-tissue age predictor. Methylation data for these analyses were obtained with the Illumina Methylation array. Statistical analysis included comparison of methylation age between OA patients and controls with ANCOVA (age and sex as covariates), or with t-test comparing model-adjusted ages. Results: The blood 8 CpG panel produced methylation age that showed a median absolute deviation of 5.07 years and r2 ¼ 0.68 (p < 1016) in relation with chronological age in the published set of 390 healthy controls (ages 20 to 80 years) from Weidner et al. These estimates were better than the obtained with the previously proposed panels with 3 CpG or 5 CpG for blood. When the 8 CpG panel was applied to our 182 controls without OA, methylation age showed an absolute median
1063-4584/$ e see front matter
deviation of 6.7 years and r2 ¼ 0.52 (p < 1016) in relation with chronological age. These validation steps preceded application of the panel to OA blood samples. The methylation ages obtained in this way were similar to the chronological ages for knee, hip and for hand OA (Table 1). Therefore, none of the OA groups showed accelerated aging in blood cells as assessed with methylation age. Other tissues require the multi-tissue age predictor developed by Horvath. We applied it to cartilage samples and observed that methylation age of OA cartilage was 2.84 years older than methylation age of control cartilage. This difference was significant in the two types of analyses done (Table 1). In contrast, bone tissue of OA patients did not show different methylation age than control bone.
Table 1. Differences in methylation age between OA and control tissues. Tissue
OA
Methylation Age difference OA - Controls in years (95 % CI)
T-test p-value
ANCOVA p-value
Blood
Knee Hip Hand Knee Hip
0.04 (0.9 to 1.0) 0.72 (1.7 to 0.3) 0.01 (1.1 to 1.1) 2.84 (0.4 to 5.3) 0.04 (1.8 to 1.9)
0.98 0.15 0.94 0.03 0.97
0.93 0.11 0.98 0.006 0.34
Cartilage Bone
Conclusions: Methylation age as a measure of cellular age was increased in OA cartilage samples in a tissue specific way. The systemic component previously reported in blood with analysis of telomere length was not observed with methylation age questioning its relevance. Funding: Supported by grants PI15/01651, PI12/00615 and RD12/0009/ 0008 of the Instituto de Salud Carlos III (Spain) that are partially financed by the European Regional Development Fund of the EU. 92 THE ROLE OF MICRORNAS IN OSTEOARTHRITIS AND AGEINGRELATED FUNCTIONAL DECLINE IN JOINT TISSUE HOMEOSTASIS. L. House y, G. Bou-Gharios y, M. Peffers y, P. Milner y, P.D. Clegg y, D.A. Young z, K.A. Whysall y. y Univ. of Liverpool, Liverpool, United Kingdom; z Univ. of Newcastle, Newcastle, United Kingdom Purpose: Osteoarthritis is a degenerative disease associated with changes in the articular cartilage and bone, severely affecting patients’ mobility and quality of life. A similar, but less acute decline is also seen during ageing. microRNAs (miRs) are novel post-transcriptional regulators of gene expression. microRNAs have been implicated in different aspects of musculoskeletal ageing through their differential expression, however the functional consequences of this are still not fully understood.
Poster Presentations Posters Aging 91 SPECIFIC INCREASE OF METHYLATION AGE IN OSTEOARTHRITIS CARTILAGE L. Vidal y, Y. Lopez-Golan y, I. Rego-Perez z, S. Horvath x, F.J. Blanco z, J.A. Riancho k, J.J. Gomez-Reino y, A. Gonzalez y. y Inst. Investigacion Sanitaria-Hosp. Clinico Univ. de Santiago, Santiago de Compostela, Spain; z INIBIC-Complejo Hosp. Univ. A Coruna, A Coruna, Spain; x David Geffen Sch. of Med., Univ. of California Los Angeles, Los Angeles, CA, USA; k Hosp. U. bM. Valdecilla-IFIMAV, Univ. of Cantabria, Santander, Spain Purpose: The major risk factor for osteoarthritis (OA) is old age. However, the relationship between aging and OA is incompletely understood. Among the joint changes associated with old age are chondrocyte senescence, the decline in matrix production and an altered response to trauma. However, a systemic component of premature aging has also been suggested by the increased presence of old-age comorbidities in the OA patients and by a biomarker of cellular age, telomere length. Telomere shortening has been observed in OA chondrocytes, but also in a study of blood cells from hand OA patients (Zhai et al. Ann Rheum Dis 2006). The reproducibility and implications of these changes in blood cells are still unclear. The recent discovery of a new biomarker of cellular age provides a new opportunity to address these questions. This biomarker is made of changes in DNA methylation at specific sites in the genome. It correlates with chronological age in healthy controls more accurately than telomere length. Therefore, we have analyzed this biomarker at the blood, cartilage and bone levels to distinguish between joint specific and systemic evidence of accelerated aging. Methods: Three collections of samples were investigated. The first included 890 blood samples stratified as 273 from severe hip OA patients, 229 from severe knee OA patients, 206 from hand OA patients and 182 from controls without OA symptoms and without OA in hip radiographs. The second collection included tibial plateau cartilage samples from 18 cadavers with no macroscopic signs of OA and from 23 knee OA patients undergoing joint replacement surgery. The third collection included femoral head bone samples from 34 osteoporosis fracture (OP) patients, 11 healthy control cadavers without signs of OA and 33 hip OA patients at the time of total joint replacement. Methylation age was determined by analyzing CpG methylation at specific sites. For the blood samples, we analyzed a panel of eight sites derived from Weidner et al. (Genome Biol. 2014) and analyzed with methylation-sensitive single-nucleotide primer extension. For the cartilage and bone samples, we used a panel of 353 age-related CpG sites described by Horvath in (Genome Biol. 2013) as multi-tissue age predictor. Methylation data for these analyses were obtained with the Illumina Methylation array. Statistical analysis included comparison of methylation age between OA patients and controls with ANCOVA (age and sex as covariates), or with t-test comparing model-adjusted ages. Results: The blood 8 CpG panel produced methylation age that showed a median absolute deviation of 5.07 years and r2 ¼ 0.68 (p < 1016) in relation with chronological age in the published set of 390 healthy controls (ages 20 to 80 years) from Weidner et al. These estimates were better than the obtained with the previously proposed panels with 3 CpG or 5 CpG for blood. When the 8 CpG panel was applied to our 182 controls without OA, methylation age showed an absolute median
1063-4584/$ e see front matter
deviation of 6.7 years and r2 ¼ 0.52 (p < 1016) in relation with chronological age. These validation steps preceded application of the panel to OA blood samples. The methylation ages obtained in this way were similar to the chronological ages for knee, hip and for hand OA (Table 1). Therefore, none of the OA groups showed accelerated aging in blood cells as assessed with methylation age. Other tissues require the multi-tissue age predictor developed by Horvath. We applied it to cartilage samples and observed that methylation age of OA cartilage was 2.84 years older than methylation age of control cartilage. This difference was significant in the two types of analyses done (Table 1). In contrast, bone tissue of OA patients did not show different methylation age than control bone.
Table 1. Differences in methylation age between OA and control tissues. Tissue
OA
Methylation Age difference OA - Controls in years (95 % CI)
T-test p-value
ANCOVA p-value
Blood
Knee Hip Hand Knee Hip
0.04 (0.9 to 1.0) 0.72 (1.7 to 0.3) 0.01 (1.1 to 1.1) 2.84 (0.4 to 5.3) 0.04 (1.8 to 1.9)
0.98 0.15 0.94 0.03 0.97
0.93 0.11 0.98 0.006 0.34
Cartilage Bone
Conclusions: Methylation age as a measure of cellular age was increased in OA cartilage samples in a tissue specific way. The systemic component previously reported in blood with analysis of telomere length was not observed with methylation age questioning its relevance. Funding: Supported by grants PI15/01651, PI12/00615 and RD12/0009/ 0008 of the Instituto de Salud Carlos III (Spain) that are partially financed by the European Regional Development Fund of the EU. 92 THE ROLE OF MICRORNAS IN OSTEOARTHRITIS AND AGEINGRELATED FUNCTIONAL DECLINE IN JOINT TISSUE HOMEOSTASIS. L. House y, G. Bou-Gharios y, M. Peffers y, P. Milner y, P.D. Clegg y, D.A. Young z, K.A. Whysall y. y Univ. of Liverpool, Liverpool, United Kingdom; z Univ. of Newcastle, Newcastle, United Kingdom Purpose: Osteoarthritis is a degenerative disease associated with changes in the articular cartilage and bone, severely affecting patients’ mobility and quality of life. A similar, but less acute decline is also seen during ageing. microRNAs (miRs) are novel post-transcriptional regulators of gene expression. microRNAs have been implicated in different aspects of musculoskeletal ageing through their differential expression, however the functional consequences of this are still not fully understood.