Specific premature epigenetic aging of cartilage in osteoarthritis

Vidal-Bralo, Laura; Lopez-Golan, Yolanda; Mera, Antonio; Rego-Pérez, Ignacio; Horvath, Steve; Zhang, Yuhua; Real, Álvaro del; Zhai, Guangju; Blanco, Francisco J.; Riancho, José A.; Gomez-Reino, Juan J.; Gonzalez, Antonio

doi:10.18632/aging.101053

Cited by 36 publications

(16 citation statements)

References 51 publications

(108 reference statements)

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“…84,85 The latter is especially relevant in cells with limited replicative ability that are involved in the long-term maintenance of tissue homeostasis, like articular chondrocytes. Recent studies showed that OA chondrocytes display features of premature epigenetic aging 86 and the senescenceassociated secretory phenotype. 87 Also contributing to disease progression is the accumulation of advanced glycation end products (AGEs), which can modify chondrocyte responses and lead to cartilage matrix degradation.…”

Section: Osteoarthritismentioning

confidence: 99%

Phenotypic instability of chondrocytes in osteoarthritis: on a path to hypertrophy

Singh

Goldring

Otero

2018

Ann. N.Y. Acad. Sci.

108

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Articular chondrocytes are quiescent, fully differentiated cells responsible for the homeostasis of adult articular cartilage by maintaining cellular survival functions and the fine-tuned balance between anabolic and catabolic functions. This balance requires phenotypic stability that is lost in osteoarthritis (OA), a disease that affects and involves all joint tissues and especially impacts articular cartilage structural integrity. In OA, articular chondrocytes respond to the accumulation of injurious biochemical and biomechanical insults by shifting toward a degradative and hypertrophy-like state, involving abnormal matrix production and increased aggrecanase and collagenase activities. Hypertrophy is a necessary, transient developmental stage in growth plate chondrocytes that culminates in bone formation; in OA, however, chondrocyte hypertrophy is catastrophic and it is believed to initiate and perpetuate a cascade of events that ultimately result in permanent cartilage damage. Emphasizing changes in DNA methylation status and alterations in NF-κB signaling in OA, this review summarizes the data from the literature highlighting the loss of phenotypic stability and the hypertrophic differentiation of OA chondrocytes as central contributing factors to OA pathogenesis.

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“…Methylation patterns can also be used to calculate a so‐called “epigenetic age,” which is thought to reflect biological aging and has been linked to a whole range of age‐related diseases and time of death . One study examined the relation between this “epigenetic clock” and osteoarthritis and observed accelerated aging in OA cartilage …”

Section: Dna Methylation and Skeletal Disordersmentioning

confidence: 99%

Role of Epigenomics in Bone and Cartilage Disease

Meurs¹,

Boer²,

López-Delgado³

et al. 2019

J Bone Miner Res

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Phenotypic variation in skeletal traits and diseases is the product of genetic and environmental factors. Epigenetic mechanisms include information-containing factors, other than DNA sequence, that cause stable changes in gene expression and are maintained during cell divisions. They represent a link between environmental influences, genome features, and the resulting phenotype. The main epigenetic factors are DNA methylation, posttranslational changes of histones, and higher-order chromatin structure. Sometimes non-coding RNAs, such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), are also included in the broad term of epigenetic factors. There is rapidly expanding experimental evidence for a role of epigenetic factors in the differentiation of bone cells and the pathogenesis of skeletal disorders, such as osteoporosis and osteoarthritis. However, different from genetic factors, epigenetic signatures are cell-and tissue-specific and can change with time. Thus, elucidating their role has particular difficulties, especially in human studies. Nevertheless, epigenomewide association studies are beginning to disclose some disease-specific patterns that help to understand skeletal cell biology and may lead to development of new epigenetic-based biomarkers, as well as new drug targets useful for treating diffuse and localized disorders. Here we provide an overview and update of recent advances on the role of epigenomics in bone and cartilage diseases.Besides chromatin-related marks and structure, non-coding RNAs (ncRNAs) are also frequently included among the mechanisms of epigenetic control. (8) They are classified as small RNAs (<200 nucleotides) and long RNAs (>200 nucleotides). The best-known subset of small RNAs are microRNAs (miRNAs, 18 to 25 nucleotides), which inhibit protein synthesis by binding to the 3 0 -untranslated region of target mRNAs. Long non-coding RNAs (lncRNAs) modulate the activity of both nearby genes and distant genes by a variety of mechanisms. For instance, they often serve as scaffolds for transcription factors and other molecules involved in initiation of transcription, including Box 1. Epigenomics-Related TermsChromatin: The complex of DNA and its packaging molecules. The core of the chromatin is the nucleosome, which consists of an octamer of 4 histones around which 147 bp of DNA is wrapped around.Chromosome conformation capture and Hi-C: Techniques used to map the spatial (3D) organization of the chromatin in the nucleus. Chromosome conformation capture (3C) quantifies the number of interactions between a given loci and the rest of the genome. In Hi-C, all genomic interaction between all genomic regions are quantified.CTCF: CCCTC-binding factor, highly conserved zinc finger protein involved in diverse genomic regulatory functions, including transcriptional activation/repression, insulation, imprinting, and X-chromosome inactivation, through mediating the formation of chromatin loops. DNA methyl-transferases (DNMTs): Family of enzymes responsible for the methylation of DNA. DNMT1...

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“…Using data from Ribel-Mason and colleagues [ 160 ], Horvath observed that in muscle, DNA methylation age correlated poorly with chronological age [ 158 ]. In OA patients, accelerated epigenetic ageing was demonstrated in articular cartilage but not in bone or blood [ 161 ]. We anticipate further developments in this area as approaches for genome-wide analysis of DNA methylation are applied to ageing cohorts in which there are relevant additional measures of musculoskeletal function.…”

Section: Conclusion Future Perspectives and Priorities For Researchmentioning

confidence: 99%

Developing a toolkit for the assessment and monitoring of musculoskeletal ageing

et al. 2018

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The complexities and heterogeneity of the ageing process have slowed the development of consensus on appropriate biomarkers of healthy ageing. The Medical Research Council–Arthritis Research UK Centre for Integrated research into Musculoskeletal Ageing (CIMA) is a collaboration between researchers and clinicians at the Universities of Liverpool, Sheffield and Newcastle. One of CIMA’s objectives is to ‘Identify and share optimal techniques and approaches to monitor age-related changes in all musculoskeletal tissues, and to provide an integrated assessment of musculoskeletal function’—in other words to develop a toolkit for assessing musculoskeletal ageing. This toolkit is envisaged as an instrument that can be used to characterise and quantify musculoskeletal function during ‘normal’ ageing, lend itself to use in large-scale, internationally important cohorts, and provide a set of biomarker outcome measures for epidemiological and intervention studies designed to enhance healthy musculoskeletal ageing. Such potential biomarkers include: biochemical measurements in biofluids or tissue samples, in vivo measurements of body composition, imaging of structural and physical properties, and functional tests. This review assesses candidate biomarkers of musculoskeletal ageing under these four headings, details their biological bases, strengths and limitations, and makes practical recommendations for their use. In addition, we identify gaps in the evidence base and priorities for further research on biomarkers of musculoskeletal ageing.

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“…Although late-onset articular cartilage degeneration is common and age is one of the most important risk factors for the disease, the relationship between old age and OA is not fully understood 2. In the past it was believed that the link with age was due to ‘wear and tear’ of articular cartilage by continuous mechanical stress; we now know, however, that OA involves an active response to injury comprising remodelling of articular cartilage and subchondral bone, in addition to synovial inflammation and damage to other joint structures such as ligaments and menisci 3…”

Section: Mitochondrial Dna and Ageingmentioning

confidence: 99%

Mitochondrial DNA haplogroups and ageing mechanisms in osteoarthritis

Valdes

Goldring

2017

Ann Rheum Dis

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“…These findings have sparked intense interest regarding the role of DNA methylation in the ageing process and also opened up a number of key questions. Interestingly, while initially designed to predict chronological age, there is evidence that the epigenetic age also reflects biological age and is predictive of functional decline [10][11][12][13][14][15][16][17][18][19][20][21][22]. This suggests that the observed methylation signatures might be caused by an intrinsic biological ageing process.…”

Section: Introductionmentioning

confidence: 99%

Multi-tissue DNA methylation age predictor in mouse

Stubbs

Bonder

Stark

et al. 2017

Preprint

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Background: DNA methylation changes at a discrete set of sites in the human genome are predictive of chronological and biological age. However, it is not known whether these changes are causative or a consequence of an underlying ageing process. It has also not been shown whether this epigenetic clock is unique to humans or conserved in the more experimentally tractable mouse. Results: We have generated a comprehensive set of genome-scale base-resolution methylation maps from multiple mouse tissues spanning a wide range of ages. Many CpG sites show significant tissue-independent correlations with age which allowed us to develop a multi-tissue predictor of age in the mouse. Our model, which estimates age based on DNA methylation at 329 unique CpG sites, has a median absolute error of 3.33 weeks and has similar properties to the recently described human epigenetic clock. Using publicly available datasets, we find that the mouse clock is accurate enough to measure effects on biological age, including in the context of interventions. While females and males show no significant differences in predicted DNA methylation age, ovariectomy results in significant age acceleration in females. Furthermore, we identify significant differences in age-acceleration dependent on the lipid content of the diet. Conclusions: Here we identify and characterise an epigenetic predictor of age in mice, the mouse epigenetic clock. This clock will be instrumental for understanding the biology of ageing and will allow modulation of its ticking rate and resetting the clock in vivo to study the impact on biological age.

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Specific premature epigenetic aging of cartilage in osteoarthritis

Cited by 36 publications

References 51 publications

Phenotypic instability of chondrocytes in osteoarthritis: on a path to hypertrophy

Role of Epigenomics in Bone and Cartilage Disease

Developing a toolkit for the assessment and monitoring of musculoskeletal ageing

Mitochondrial DNA haplogroups and ageing mechanisms in osteoarthritis

Multi-tissue DNA methylation age predictor in mouse

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