Open Access

Telomere length as a predictive biomarker in osteoporosis (Review)

  • Authors:
    • Fotios Kakridonis
    • Spyros G. Pneumatikos
    • Elena Vakonaki
    • Aikaterini Berdiaki
    • Manolis N. Tzatzarakis
    • Persefoni Fragkiadaki
    • Demetrios A. Spandidos
    • Stella Baliou
    • Petros Ioannou
    • Eleftheria Hatzidaki
    • Dragana Nikitovic
    • Aristidis Tsatsakis
    • Elias Vasiliadis
  • View Affiliations

  • Published online on: October 3, 2023     https://doi.org/10.3892/br.2023.1669
  • Article Number: 87
  • Copyright: © Kakridonis et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )


Abstract

Telomeres are the ends of chromosomes that protect them from DNA damage. There is evidence to suggest that telomere shortening appears with advanced age. Since aging is a significant risk factor for developing age‑related complications, it is plausible that telomere shortening may be involved in the development of osteoporosis. The present review summarizes the potential of telomere shortening as a biomarker for detecting the onset of osteoporosis. For the purposes of the present review, the following scientific databases were searched for relevant articles: PubMed/NCBI, Cochrane Library of Systematic Reviews, Scopus, Embase and Google Scholar. The present review includes randomized and non‑randomized controlled studies and case series involving humans, irrespective of the time of their publication. In six out of the 11 included studies providing data on humans, there was at least a weak association between telomere length and osteoporosis, with the remaining studies exhibiting no such association. As a result, telomere shortening may be used as a biomarker or as part of a panel of biomarkers for tracking the onset and progression of osteoporosis.

1. Introduction

The primary function of telomeres is to prevent the destruction of the genome from the DNA damage response (DDR), thus ensuring genomic stability during DNA replication (1). Structurally, the ends of telomeres are single-stranded, whereas telomeres are double-stranded at all their length (2). The numerous repetitive sequences of the hexanucleotide 5'-TTAGGG-3' are organized in a complex, three-dimensional lariat-like structure known as the telomere-loop (t-loop) (3). When the 3' end of a single DNA strand of telomeres is inserted into a double-stranded duplex of telomeres, the formation of a D-loop occurs (4). In the t-loop structure, 3' single-stranded G-rich overhangs, known as G-overhangs, protrude from the double-stranded telomeric region (5). The organization of telomeres in forming such looped structures is crucial and protects them from degradation. This t-loop conformation requires the presence of specific telomeric interacting proteins, such as telomeric repeat binding factor 1 (TRF-1), telomeric repeat binding factor 2 (TRF-2), TRF-1 interacting nuclear protein 2 (TIN-2), telomeric overhang binding protein 1 (POT-1), TIN-2 and POT-1 interacting protein 1 and repressor-activator protein 1, that stabilize the t-loop (2). As mentioned earlier, telomere-binding proteins comprise the ‘shelterin’ protein complex (6). Telomere shortening arises from incomplete lagging strand DNA synthesis, resulting in single-stranded overhangs. During the aging process, telomeres are progressively shortened below a certain threshold due to each cell division, known as the ‘end-replication problem’ (6). For that reason, it has been demonstrated that telomere shortening is associated with advanced aging (7) (Fig. 1). Accordingly, the genetic rescue of telomerase can compensate for premature aging in telomerase-deficient mice (8). Similarly, nutraceutical supplements can sustain the telomere length (TL) at a greater extent in females than males (9). Additionally, nutraceutical formulations can attenuate aging by increasing the physical action of aged animals (10).

Aging arises from multiple mechanisms, such as cellular senescence, genome instability, metabolic dysfunction, mitochondrial deterioration, microbial dysbiosis and sustained low inflammation, epigenetic alterations including DNA methylation, stem cell exhaustion, disturbed cellular communication, proteasomal degradation or dysregulated autophagy and telomere shortening (11). According to the American Federation for Aging Research (AFAR) (12), the hallmarks of aging have been defined based on the following criteria: i) The prediction of life expectancy than natural chronologic age; ii) be subject to experiments to elucidate characteristics that accelerate aging; iii) be subject to investigations to shed light on mechanisms underlying the prevention of aging; iv) be minimally invasive without harming individuals (13). The compliance of TL to the criteria noted by the AFAR defines telomere shortening as a reliable biomarker of aging (14,15).

Notably, telomere shortening represents an essential hallmark of the aging process, and it is accelerated in age-related disorders (7). For example, short telomeres have been observed in leukocytes of osteoporotic patients compared to long ones of controls, whereas long telomeres have been reported in females with low osteoporosis risk (16). In agreement with the aforementioned findings, it has been demonstrated that aged osteocytes that were senescent through a high p16 expression were associated with bone loss (17).

Osteoporosis is an aging-related disease of bone metabolism, is prevalent among the elderly, and at least 200 million cases worldwide have been reported (18). The characteristic features of osteoporosis are an increased vulnerability to bone fractures and high fragility due to low bone mass and deterioration of bone microstructure (19). Osteoporosis imposes a significant economic burden in the aging society, necessitating the identification of markers that stratify individuals to osteoporosis (20). Post-menopausal women are mainly exposed to bone fractures, such as vertebral and hip fractures (21). In Europe and the USA, >30% of women and 20% of men >50 years of age have osteoporosis (22). At the same time, it is also estimated that >40% of post-menopausal women and 30% of men can experience a fracture related to osteoporosis during their lifetimes (23,24).

A complete understanding of the mechanisms underlying osteoporosis is crucial in order to develop effective therapeutic strategies to attenuate its progression. Among the factors determining bone loss are low estrogen levels in post-menopausal women and low testosterone levels in men, resulting in osteoporosis (25). Estrogen-deprivation-related osteoporosis observed in post-menopausal women appears to differ from age-related osteoporosis (26,27). However, estrogen is not the only factor that contributes to bone loss during aging (28); bone homeostasis can also be affected by parathyroid hormone, vitamin D (cholecalciferol), calcitonin and corticosteroids (29) (Fig. 2).

Bone remodeling has been reported as a key parameter for determining the onset and progression of osteoporosis. In bone remodeling, osteoclasts and osteoblasts are implicated in orchestrating bone architecture through the degradation of old bone (bone resorption) and the formation of new bone (bone formation), respectively (30). Previous research has analyzed the signaling pathways that regulate the balance between osteoclastic bone resorption and osteoblastic bone formation. Such signaling pathways are the following: Receptor activator of nuclear factor-κB (RANK)/RANK ligand (RANKL)/osteoprotegerin (OPG) and canonical Wnt (31). For example, OPG prevents the binding of RANKL to the RANK receptor, thus preventing osteoclast function (27) (Fig. 3). Currently, several pharmaceutical agents, including bisphosphonates, estrogens, the selective estrogen receptor modulator, raloxifene, the human monoclonal antibody, denosumab, and the recombinant human parathormone, 1-34 teriparatide, are commonly used to treat osteoporosis effectively (18) (Fig. 3). Recently, romosozumab (ROMO), an approved monoclonal antibody directed against sclerostin in several countries for the treatment of osteoporosis in post-menopausal women who are at a high risk of fractures, has attracted significant attention owing to its ability to reinforce bone formation. At the same time, it can attenuate bone resorption after its short-term use (32,33). The underlying molecular mechanism of ROMO relies on the induction of the Wnt signaling pathway since the action of ROMO is directed to prevent sclerostin-a glycoprotein, which exerts inhibitory effects on osteoblasts and further induces bone resorption (32,33). Following the review of three-phase clinical trials, researchers have previously evaluated the superior effect of ROMO compared with teriparatide in post-menopausal women with osteoporosis who were at a high risk of fractures and they were previously treated with bisphosphonate therapy, thereby causing bone remodeling and increasing bone mineral density (BMD) (34). Despite therapeutic options, their clinical efficacy is hindered due to the emerging side-effects after their long-term use, making it urgent to identify novel and effective therapeutic interventions against osteoporosis (35). In this direction, further investigations are required to elucidate the possible cardiovascular events after using ROMO in postmenopausal women with a risk of high fractures (33).

Since telomere shortening is considered a molecular hallmark of aging (11), a summary of the state of the field provides clues that telomere shortening can be a driver for the onset and progression of osteoporosis. In the present review, a discussion was performed of the current research data on the possible association of TL with osteoporosis in humans.

2. Clinical studies regarding telomere length and osteoporosis

Initially, it was generally questionable whether TL can contribute independently to aging as a biomarker (36-38). To answer that question, a number of studies have demonstrated that TL can fulfill the main prerequisites defined by the AFAR. Epidemiological and clinical studies have provided evidence that telomere shortening is the most widely and reliable biomarker that characterizes the aging process (15,39). Numerous studies have illustrated a strong association between different biomarkers and the onset of aging; current aging markers are not without drawbacks. Indeed, other features have been employed to evaluate various aspects of the aging process since the mechanism underlying the aging process in humans is incredibly complicated.

Apart from the crucial involvement of telomere shortening in aging, biomarkers of aging are usually used for evaluating the progression of age-related disorders, such as osteoporosis (40). Identifying preventive strategies against osteoporosis requires precise and reliable biomarkers for assessing the rate of osteoporosis. Over the past decades, age-related telomere shortening has attracted increasing attention in research as one of the most promising fields.

The literature search performed herein resulted in the isolation of relevant published articles; there were three non-randomized-controlled studies and eight longitudinal cohort studies. The main findings of the review are summarized in Table I.

Table I

The main findings of the published articles.

Table I

The main findings of the published articles.

Authors, year of publication, countryParticipantsOutcome measuresMain findings(Refs.)
Kveiborg et al, 1999, DenmarkYoung (aged 20-26 years), elderly (aged 48-85 years, and patients with osteoporosis (aged 52-81 years)TL in peripheral blood leukocytesNo significant changes were observed between patients with osteoporosis and the age-matched controls(60)
Bekaert et al, 2005, Belgium352 Healthy males, 71-86 years of ageTL in the leucocytes of peripheral bloodAge-corrected mean telomere restriction fragment length was associated with longitudinal bone loss at the total forearm, particularly at the mid-region of the forearm and at the ultra-distal forearm(41)
Valdes et al, 2007, UK2,150 Healthy and osteoporotic women, 18-79 years of ageTelomere leukocyte length, bone mineral density, and osteoporosisTL positively related to bone mineral density of both the forearm and the spinal column(16)
Sanders et al, 2009, USA2,750 Healthy and osteoporotic adults, 71-79 years of ageTelomere leukocyte length, bone mineral density, and osteoporosisTL was not related to bone mineral density, osteoporosis, and risk of fractures(65)
Tang et al, 2010, China1,867 Elderly adults (mean age, 72 years)Telomere leukocyte length and hip bone mineral densityNo association was found between TL and baseline bone mineral density or bone loss over a 4-year period(61)
Tamayo et al, 2010, Spain35 Adults aged >40 years with osteoporosis vs. 130 healthy individualsTelomere leukocyte length and osteoporosisTelomere leukocyte length was statistically significantly shorter in patients with osteoporosis(45)
Nielsen et al, 2015, Denmark420 Women (mean age, 63.9 years; range, 25-93 years)Telomere leukocyte length and bone mineral densityNo statistically significant associations were found between leukocyte TL and bone mineral density(46)
Kalyan et al, 2018, Canada73 Women with HIV (mean age, 43 years)Telomere leukocyte length and bone mineral densityReduction of leukocyte TL was statistically significantly related to lower bone mineral density(49)
Tao et al, 2019, China1,017 Elderly Chinese adults (mean age, 66.4 years) from whom 433 were males and 584 cases were females at the post-menopausal stage and probably osteoporoticTelomere leukocyte length and bone mineral densityLeukocyte TL was found to be associated with a lower bone mineral density and osteoporosis in elderly women, but not in the male population(51)
Kirk et al, 2022, Australia20,400 Elderly adults with osteosarcopenia (n=205) compared to the matched controls in the UK Biobank (mean age 67.8 years, 53% male)Telomere leukocyte length and osteosarcopeniaNo association was found between leukocyte TL and osteosarcopenia or femoral neck bone mineral density(62)
Curtis et al, 2022, UK111,395 Adults in the UK (mean age, 56.7 years)Telomere leukocyte length and risk of fracturesWeak association in females, even weaker in males(53)

[i] HIV, human immunodeficiency virus; TL, telomere length.

Initially, Bekaert et al (41) performed an early observational study comprising 352 elderly healthy male subjects (aged 71-86 years). They found that the mean leukocyte TL (LTL) was reduced with an advanced age. The age-corrected TL was positively associated with bone loss, as confirmed by biochemical analysis of bone turnover and BMD at different distal forearm sites, including the mid-region of the forearm, ultra-distal forearm and the total forearm (41). Furthermore, they elucidated the use of mean LTL as a predictive marker for bone loss, according to the sex steroid status of elderly healthy male individuals (41). For that purpose, telomere restriction fragment (TRF) length analysis was performed along with various examinations of testosterone, estradiol and sex hormone-binding globulin in the blood of males (41). The results proved that the short length of telomere restriction fragment determined bone loss at various sites of their radius and ulna (P<0.05), which was inversely associated with the age of the participants (P=0.049), irrespective of the hormonal status of healthy older adults (41). Furthermore, aged individuals with bone loss had a mean TRF length 423 base pairs (bps), shorter than that of age-matched controls without bone loss, given that the telomere erosion rate in leukocytes appears to be shortened by 23 bps per year (42).

Based on experiments revealing a tight association between telomere shortening and the senescence of osteoblasts in vitro (43,44), a large population-based study was performed in a series of 2,150 female twins (aged 18-80 years), where the association between LTL and BMD was evaluated. A positive association between TL with BMD of the spine and distal forearm (but not with the femoral neck) was revealed, and longer telomeres were associated with a reduced risk of developing osteoporosis at two or more sites in women >50 years of age (16). In a clinical setting, women with osteoporosis had a shorter TL by 117 bps than their matched controls, implying accelerating skeletal aging due to TL. As a result, it was proposed that the LTL could be used as a marker for skeletal aging (16).

In the same year, Tamayo et al (45), in a non-randomized controlled study of 35 elderly patients (aged 59-95 years) with osteoporosis and 130 healthy individuals, found that LTL was statistically significantly shorter (P=0.001) in the osteoporosis group than that in the control group. Nielsen et al (46), in a longitudinal cohort study involving 420 women (mean age, 64 years; range, 25-93 years), did not find a statistically significant association between LTL and BMD; nevertheless, a statistically significant association was indeed observed between LTL and age as well as between body mass index-adjusted age and BMD (46). It was also increasingly apparent that accelerating aging was related to human immunodeficiency virus (HIV) infection, which in turn accounted for telomere damage and mitochondrial DNA damage (47,48). In this context, in a non-randomized-controlled study involving 73 women (mean age, 43 years) living with HIV aged >50 years, it was highlighted that the observed shortening of LTL was statistically significantly related to a lower BMD at the lumbar spine [mean difference, -0.39; 95% confidence interval (CI), -0.61, -0.17] and total hip (mean difference, -0.29; 95% CI, -0.52, -0.07), suggesting that LTL was negatively associated with a low bone mass in women with HIV, and that this connection may be related to the pathophysiology of premature aging in HIV-infected women (49). The aforementioned results were important, given that aged individuals living with HIV had a higher prevalence for osteoporosis, as shown by a pooled odds ratio (OR) at 3.7 compared to their age-matched controls, following a meta-analysis of 20 studies (50).

In agreement with the aforementioned findings, Tao et al (51) conducted a cohort study of 1,017 elderly Chinese adults (mean age, 66.4 years), from whom 584 were older women at the post-menopausal stage and 433 were older men, providing substantial evidence that there was a positive association between LTL and BMD through analysis of the results with multiple linear and ordinal logistic regressions, thereby increasing risk of developing osteoporosis in women at post-menopausal stage (51). Importantly, that positive association of LTL and BMD reduced as women aged. On the contrary, no association was observed between the two parameters mentioned above in older males. As a result, it was concluded that the predictive value of LTL in osteoporosis was sex-dependent (51).

A significant association between short TLs and a low telomerase activity has also been shown to be associated with skeletal pathologies, such as osteoporosis and osteoarthritis, in which the dysregulated restitution of the subchondral bone occurs in the elderly (52).

Recently, Curtis et al (53) analyzed the positive association between LTL and the risk of fractures in a longitudinal cohort study. The authors of that study examined a population of 51,900 males and 59,500 females from the UK Biobank (mean age, 56.7 years). They showed that there was a weak association between a longer LTL and a reduced risk of any fracture in women [hazard ratio (HR)/standard deviation (SD), 0.96], with less evidence found in males (HR/SD, 0.98) (53). According to that study, this was the most extensive relevant study, showing only a weak association between LTL and the risk of fractures (53).

The majority of studies have reported a positive association between telomere shortening and the pathological characteristics of osteoporosis. In particular, telomere shortening is strongly associated with a low BMD (13,52). The mechanism by which telomere shortening causes osteoporosis has come to light through experiments using mice or individuals harboring germline mutations in genes implicated in telomere maintenance (15,40,44,45,48,50,52-59). However, only a limited number of studies contradicted the positive association between telomere shortening and the aggravation of skeletal pathology (60-63).

Initially, Kveiborg et al (60) investigated the LTL derived from 49 healthy women aged 20-26 and 48-85 years, and compared the value of LTL to that of osteoporotic women of 52-81 years of age. They did not observe any marked differences among groups (60). Moreover, that study had no statistical power due to its small study group (<30 individuals), given that the analysis of the results is affected by sample size (64). Similar results were obtained from a longitudinal cohort study in which 2,750 elderly adults (aged 71-79 years) were enrolled (65). The results revealed no association between LTL and BMD at the total hip or femoral neck, changes in BMD over time, the presence of osteoporosis and the risk of fractures in this population of elderly males and females (65). Apart from the negative association between TL and osteoporosis, it was reported that the TL was independent of the following factors: weight, fasting insulin, and fasting glucose in elderly males and females (65). Since systemic inflammation is regarded as the primary mechanism underlying the association between telomere shortening and osteoporosis, and women with osteoporosis are characterized by higher serum levels of C-reactive protein (CRP) than the controls (16,65,66), Sanders et al substantiated the inverse correlation of TL with serum levels of CRP and IL-6(65). Compared to the results from the study by Valdes et al (16), the association of TL with BMD was sex- and age-dependent (16,65). In another longitudinal cohort study of 1,867 elderly Chinese adults (mean age, 72 years), Tang et al (61) found no statistically significant association between TL and baseline BMD at the total hip and femoral neck in both males and females (61).

Recently, Kirk et al (62) provided insight into the association between LTL and the incidence of osteosarcopenia in a population of 20,400 elderly adults (mean age, 68 years; 47% females) from the UK Biobank (62). Osteosarcopenia, according to the World Health Organization (WHO) criteria, is defined as follows: i) Bone density of the femoral neck T-score ≤-1; along with ii) a low appendicular lean mass as calculated from the relation mass/height2 or low grip strength; and iii) a slow walking pace (63). One of the results of that study was that LTL was not associated either with osteosarcopenia or the low bone density of the femoral neck. The authors suggest it may be worth studying the same outcome measures in an older population (>74 years) (62).

3. Challenges of studying telomere length in osteoporosis

The inconsistency among studies presented herein may be related to variability in the population of studies, the methodology of studies and the size of the groups, establishing different aspects of statistical analysis. Furthermore, a discrepancy can arise through measuring TL in leukocytes and not in bone cells like osteoblasts.

After adjusting for age, two epidemiological research studies have reported a statistically significant association between LTL and BMD, though measuring LTL via Southern blot analysis (16,41). On the contrary, when LTL was evaluated through quantitative polymerase chain reaction (qPCR), no link was found between LTL and BMD (61,65). It is generally accepted that the qPCR is more accurate and reliable than Southern blot analysis, due to its high-throughput nature and sensitivity (67); however, this comparison appears to be underestimated as no report comparing the two methodologies has been performed to date, at least to the best of our knowledge (64).

Indeed, the high inconsistency of results may be attributed to different methods used to measure TL. In this direction, several reliable methods exist to evaluate TL with various forms of sensitivity, either at the population or at the single-cell level. Initially, studies used Southern blot analysis to evaluate the length distribution of the terminal restriction fragments in cells. Then, other studies performed qPCR to measure the copy number of telomere repeats in homogenized cells, obtaining a general image of the enrichment of telomere ends in cells (14). Significant advances in the telomere field have been noted, using telomere shortest length assay (TeSLA) . In the former technique, the length of all telomeres can be evaluated. In the TeSLA technique, PCR amplifies telomeres at the single-chromosome level, and gel electrophoresis then enables the evaluation of their length (14,68). Recently, the most precise method to evaluate TL at a single-cell level and at a single-chromosome level is quantitative fluorescence in situ hybridization (qFISH) with the use of telomere peptide nucleic acid (PNA) probe (14). Epidemiologists isolating peripheral blood (PB) usually follow the latter. Among all these techniques, only qFISH allows the measurement of individual TLs at single cell level (14). Despite the superiority of qFISH compared to other techniques, the qFISH can recognize the telomeric repeats that the PNA probe defines.

However, DNA methylation-based methods have been used to evaluate the TL (69). The sensitivity and the reproducibility of the aforementioned innovative methods regarding TL have been enhanced at a single-cell level; however, they are not considered complete. The inconsistency of DNA methylation-based methods arises from differences among techniques (70). It should also be taken into consideration that the reproducibility of TL is hampered by other parameters involving the processing and storage of samples (71). Accordingly, the differences among studies can arise from the different statistical methods used and intrinsic variations among the study groups of each study. The mechanisms underlying age-related telomere shortening remain incompletely understood, since the phenomenon is complex and multifaceted. In addition to the above, the inter-individual variability of samples themselves can complicate the TL measurements to be precise (72), rendering it very difficult to use telomere shortening as a single routine biomarker in clinical practice (73). Those limitations need to be addressed before establishing telomere shortening as a biomarker of osteoporosis in clinical settings.

4. Role of telomere shortening in premature aging disorders associated with osteoporosis

Clues of aging mechanisms arise from segmental progeroid disorders in humans. Apart from the direct significance of telomere shortening in osteoporosis, dyskeratosis congenita and Werner syndrome (WS) constitute two genetic diseases that are characterized by common signs of telomere shortening and premature osteoporosis (74-76). Notably, the standard features of the two diseases are premature osteoporosis and telomere shortening owing to the loss of function mutations in maintaining TL homeostasis (77). In the aforementioned genetic disorders, osteoporosis is accomplished to a greater extent than that achieved with natural aging, and the distribution of included osteoporosis in WS appears at the limbs more than the axial skeleton (78,79). In both diseases, increased systemic inflammation and impaired immune system are implicated in their pathophysiology, as represented by telomere shortening in their lymphocytes (80).

Since Wrn helicase plays a crucial role in sustaining TL (81), it is apparent that dysfunctional telomeres are accelerated in double mutant Wrn-/- telomerase RNA component (Terc)-/- mice. Double-deficient mice have been shown to exhibit an abnormal proliferation of their bone-forming cells, and they are characterized by bone loss and age-related osteoporosis owing to the disrupted differentiation of osteoblasts, accompanied by advanced senescence observed in mesenchymal stem cells and the normal differentiation of osteoclasts (82). As a result, the osteoporosis observed in double-deficient mice appears to arise from damage in the distribution and the functionality of osteoblasts (57), suggesting the significance of a short TL in the risk of fractures. Consistent with the aforementioned findings, the transfection of telomerase reverse transcriptase (TERT) into osteoblasts that are implanted into Wrn-/- Terc-/- mice has been shown to restore bone homeostasis (57).

5. Conclusions and future perspectives

The present review discussed different results regarding the usefulness of TL for identifying individuals with a higher susceptibility for developing osteoporosis and also highlighted the significance of TL in patients with osteoporosis. Indeed, the present review proposes that TL shortening may be used as a prognostic or predictive marker to evaluate the onset and progression of osteoporosis. However, further large and well-characterized cohorts with large sample sizes and proper design are urgently required to gain new insight into the mechanisms through which telomere shortening leads to the development of osteoporosis and to encourage the use of telomere shortening as a predictive tool for the onset and progression of osteoporosis.

Thus, it remains questionable whether telomere shortening can be a reliable biomarker of osteoporosis or comprising a part of a composite panel of biomarkers for osteoporosis. Moreover, a combination of panel markers can exert greater predictive value in evaluating the progression of osteoporosis than single measures. In parallel, telomere shortening can serve as a predictive tool for assessing the risk of developing osteoporosis.

Acknowledgements

Not applicable.

Funding

Funding: No funding was received.

Availability of data and materials

Not applicable.

Authors' contributions

All authors (FK, SP, EVakonaki, AB, MNT, PF, DAS, SB, AT, PI, EH, DN and EVasileiadis) contributed to the conception and design of the study. FK, SB, EV, AB, PF and MNT searched the literature for articles to be included in the present review, which were then examined and reviewed by SP, EH, SB, PI, DAS, DN, AT and EVasileiadis. FK, EVasileiadis, SB, EV and AB drafted and wrote the manuscript. MNT, DN, EH, SB, PI, DAS, DN, AT and SP revised the manuscript. AB, SB and DN designed the figures. FK and EVakonaki designed the table and SB revised the table. All authors have read and approved the final version of the manuscript. Data authentication is not applicable.

Ethics approval and consent to participate

Not applicable.

Patient consent for publication

Not applicable.

Competing interests

DAS is the editor-in-chief for the journal, but had no personal involvement in the reviewing process, or any influence in terms of adjudicating on the final decision for this article. The other authors declare that they have no competing interests.

References

1 

Shay JW: Telomeres and aging. Curr Opin Cell Biol. 52:1–7. 2018.PubMed/NCBI View Article : Google Scholar

2 

Gruber HJ, Semeraro MD, Renner W and Herrmann M: Telomeres and Age-Related Diseases. Biomedicines. 9(1335)2021.PubMed/NCBI View Article : Google Scholar

3 

Griffith JD, Comeau L, Rosenfield S, Stansel RM, Bianchi A, Moss H and de Lange T: Mammalian Telomeres End in a Large Duplex Loop. Cell. 97:503–514. 1999.PubMed/NCBI View Article : Google Scholar

4 

Greider CW: Telomeres Do D-Loop-T-Loop. Cell. 97:419–422. 1999.PubMed/NCBI View Article : Google Scholar

5 

Turner KJ, Vasu V and Griffin DK: Telomere biology and human phenotype. Cells. 8(73)2019.PubMed/NCBI View Article : Google Scholar

6 

de Lange T: Shelterin: The protein complex that shapes and safeguards human telomeres. Genes Dev. 19:2100–2110. 2005.PubMed/NCBI View Article : Google Scholar

7 

Blasco MA: Telomere length, stem cells and aging. Nat Chem Biol. 3:640–649. 2007.PubMed/NCBI View Article : Google Scholar

8 

Jaskelioff M, Muller FL, Paik JH, Thomas E, Jiang S, Adams AC, Sahin E, Kost-Alimova M, Protopopov A, Cadiñanos J, et al: Telomerase reactivation reverses tissue degeneration in aged telomerase-deficient mice. Nature. 469:102–106. 2011.PubMed/NCBI View Article : Google Scholar

9 

Tsoukalas D, Fragkiadaki P, Docea AO, Alegakis AK, Sarandi E, Vakonaki E, Salataj E, Kouvidi E, Nikitovic D, Kovatsi L, et al: Association of nutraceutical supplements with longer telomere length. Int J Mol Med. 44:218–226. 2019.PubMed/NCBI View Article : Google Scholar

10 

Tsoukalas D, Buga AM, Docea AO, Sarandi E, Mitrut R, Renieri E, Spandidos DA, Rogoveanu I, Cercelaru L, Niculescu M, et al: Reversal of brain aging by targeting telomerase: A nutraceutical approach. Int J Mol Med. 48(199)2021.PubMed/NCBI View Article : Google Scholar

11 

López-Otín C, Blasco MA, Partridge L, Serrano M and Kroemer G: The Hallmarks of Aging. Cell. 153:1194–1217. 2013.PubMed/NCBI View Article : Google Scholar

12 

Lederman S: American Federation for Aging Research. In: Encyclopedia of Gerontology and Population Aging. Gu D and Dupre ME (eds). Springer, Cham, pp1–5, 2020.

13 

Vaiserman A and Krasnienkov D: Telomere length as a marker of biological age: State-of-the-Art, open issues, and future perspectives. Front Genet. 11(630186)2021.PubMed/NCBI View Article : Google Scholar

14 

Rossiello F, Jurk D, Passos JF and d'Adda di Fagagna F: Telomere dysfunction in ageing and age-related diseases. Nat Cell Biol. 24:135–147. 2022.PubMed/NCBI View Article : Google Scholar

15 

Sanders JL and Newman AB: Telomere length in epidemiology: A biomarker of aging, age-related disease, both, or neither? Epidemiol Rev. 35:112–131. 2013.PubMed/NCBI View Article : Google Scholar

16 

Valdes AM, Richards JB, Gardner JP, Swaminathan R, Kimura M, Xiaobin L, Aviv A and Spector TD: Telomere length in leukocytes correlates with bone mineral density and is shorter in women with osteoporosis. Osteoporos Int. 18:1203–1210. 2007.PubMed/NCBI View Article : Google Scholar

17 

Farr JN and Khosla S: Cellular senescence in bone. Bone. 121:121–133. 2019.PubMed/NCBI View Article : Google Scholar

18 

Sozen T, Ozisik L and Basaran NC: An overview and management of osteoporosis. Eur J Rheumatol. 4:46–56. 2017.PubMed/NCBI View Article : Google Scholar

19 

Chen X, Hu Y, Geng Z and Su J: The ‘Three in One’ Bone repair strategy for osteoporotic fractures. Front Endocrinol (Lausanne). 13(910602)2022.PubMed/NCBI View Article : Google Scholar

20 

Dimai HP, Redlich K, Peretz M, Borgström F, Siebert U and Mahlich J: Economic burden of osteoporotic fractures in Austria. Health Econ Rev. 2(12)2012.PubMed/NCBI View Article : Google Scholar

21 

Johnston CB and Dagar M: Osteoporosis in older adults. Med Clin North Am. 104:873–884. 2020.PubMed/NCBI View Article : Google Scholar

22 

Pignolo RJ, Law SF and Chandra A: Bone aging, cellular senescence, and osteoporosis. JBMR Plus. 5(e10488)2021.PubMed/NCBI View Article : Google Scholar

23 

Wright NC, Looker AC, Saag KG, Curtis JR, Delzell ES, Randall S and Dawson-Hughes B: The recent prevalence of osteoporosis and low bone mass in the united states based on bone mineral density at the femoral neck or lumbar Spine. J Bone Miner Res. 29:2520–2526. 2014.PubMed/NCBI View Article : Google Scholar

24 

Watts NB, Bilezikian JP, Camacho PM, Greenspan SL, Harris ST, Hodgson SF, Kleerekoper M, Luckey MM, McClung MR, Pollack RP, et al: American association of clinical endocrinologists medical guidelines for clinical practice for the diagnosis and treatment of postmenopausal osteoporosis. Endocr Pract. 16 Suppl 3(Suppl 3):S1–S37. 2010.PubMed/NCBI View Article : Google Scholar

25 

Khosla S: Pathogenesis of Age-Related Bone Loss in Humans. J Gerontol A Biol Sci Med Sci. 68:1226–1235. 2013.PubMed/NCBI View Article : Google Scholar

26 

Chandra A, Lagnado AB, Farr JN, Monroe DG, Park S, Hachfeld C, Tchkonia T, Kirkland JL, Khosla S, Passos JF and Pignolo RJ: Targeted reduction of senescent cell burden alleviates focal radiotherapy-related bone loss. J Bone Miner Res. 35:1119–1131. 2020.PubMed/NCBI View Article : Google Scholar

27 

Chandra A and Rajawat J: Skeletal aging and osteoporosis: Mechanisms and Therapeutics. Int J Mol Sci. 22(3553)2021.PubMed/NCBI View Article : Google Scholar

28 

Farr JN, Rowsey JL, Eckhardt BA, Thicke BS, Fraser DG, Tchkonia T, Kirkland JL, Monroe DG and Khosla S: Independent roles of estrogen deficiency and cellular senescence in the pathogenesis of osteoporosis: Evidence in young adult mice and older humans. J Bone Miner Res. 34:1407–1418. 2019.PubMed/NCBI View Article : Google Scholar

29 

Hachemi Y, Rapp AE, Picke AK, Weidinger G, Ignatius A and Tuckermann J: Molecular mechanisms of glucocorticoids on skeleton and bone regeneration after fracture. J Mol Endocrinol. 61:R75–R90. 2018.PubMed/NCBI View Article : Google Scholar

30 

Siddiqui JA and Partridge NC: Physiological bone remodeling: Systemic regulation and growth factor involvement. Physiology (Bethesda). 31:233–245. 2016.PubMed/NCBI View Article : Google Scholar

31 

Kenkre JS and Bassett J: The bone remodelling cycle. Ann Clin Biochem. 55:308–327. 2018.PubMed/NCBI View Article : Google Scholar

32 

Rauner M, Taipaleenmäki H, Tsourdi E and Winter EM: Osteoporosis treatment with anti-sclerostin antibodies-mechanisms of action and clinical application. J Clin Med. 10(787)2021.PubMed/NCBI View Article : Google Scholar

33 

Fabre S, Funck-Brentano T and Cohen-Solal M: Anti-Sclerostin antibodies in osteoporosis and other bone diseases. J Clin Med. 9(3439)2020.PubMed/NCBI View Article : Google Scholar

34 

Shakeri A and Adanty C: Romosozumab (sclerostin monoclonal antibody) for the treatment of osteoporosis in postmenopausal women: A review. J Popul Ther Clin Pharmacol. 27:e25–e31. 2020.PubMed/NCBI View Article : Google Scholar

35 

Ensrud KE and Crandall CJ: Osteoporosis. Ann Intern Med. 167:ITC17–ITC32. 2017.PubMed/NCBI View Article : Google Scholar

36 

Mather KA, Jorm AF, Parslow RA and Christensen H: Is telomere length a biomarker of aging? A review. J Gerontol A Biol Sci Med Sci. 66A:202–213. 2011.PubMed/NCBI View Article : Google Scholar

37 

Der G, Batty GD, Benzeval M, Deary IJ, Green MJ, McGlynn L, McIntyre A, Robertson T and Shiels PG: Is telomere length a biomarker for aging: Cross-Sectional evidence from the west of scotland? PLoS One. 7(e45166)2012.PubMed/NCBI View Article : Google Scholar

38 

Simons MJ: Questioning causal involvement of telomeres in aging. Ageing Res Rev. 24(Pt B):191–196. 2015.PubMed/NCBI View Article : Google Scholar

39 

Gorenjak V, Akbar S, Stathopoulou MG and Visvikis-Siest S: The future of telomere length in personalized medicine. Front Biosci (Landmark Ed). 23:1628–1654. 2018.PubMed/NCBI View Article : Google Scholar

40 

Fasching CL: Telomere length measurement as a clinical biomarker of aging and disease. Crit Rev Clin Lab Sci. 55:443–465. 2018.PubMed/NCBI View Article : Google Scholar

41 

Bekaert S, Van Pottelbergh I, De Meyer T, Zmierczak H, Kaufman JM, Van Oostveldt P and Goemaere S: Telomere length versus hormonal and bone mineral status in healthy elderly men. Mech Ageing Dev. 126:1115–1122. 2005.PubMed/NCBI View Article : Google Scholar

42 

Cawthon RM, Smith KR, O'Brien E, Sivatchenko A and Kerber RA: Association between telomere length in blood and mortality in people aged 60 years or older. Lancet. 361:393–395. 2003.PubMed/NCBI View Article : Google Scholar

43 

Kassem M and Marie PJ: Senescence-associated intrinsic mechanisms of osteoblast dysfunctions: Age-related mechanisms of osteoblast dysfunctions. Aging Cell. 10:191–197. 2011.PubMed/NCBI View Article : Google Scholar

44 

Wang D and Wang H: Cellular Senescence in Bone. In: Physiology. Heshmati H (ed). IntechOpen, vol. 15 M, 2022.

45 

Tamayo M, Mosquera A, Rego JI, Fernández-Sueiro JL, Blanco FJ and Fernández JL: Differing patterns of peripheral blood leukocyte telomere length in rheumatologic diseases. Mutat Res. 683:68–73. 2010.PubMed/NCBI View Article : Google Scholar

46 

Nielsen BR, Linneberg A, Bendix L, Harboe M, Christensen K and Schwarz P: Association between leukocyte telomere length and bone mineral density in women 25-93 years of age. Exp Gerontol. 66:25–31. 2015.PubMed/NCBI View Article : Google Scholar

47 

Smith RL, de Boer R, Brul S, Budovskaya Y and van Spek H: Premature and accelerated aging: HIV or HAART? Front Genet. 3(328)2013.PubMed/NCBI View Article : Google Scholar

48 

Deeks SG: HIV infection, inflammation, immunosenescence, and aging. Annu Rev Med. 62:141–155. 2011.PubMed/NCBI View Article : Google Scholar

49 

Kalyan S, Pick N, Mai A, Murray MCM, Kidson K, Chu J, Albert AYK, Côté HCF, Maan EJ, Goshtasebi A, et al: Premature spinal bone loss in women living with HIV is associated with shorter leukocyte telomere length. Int J Environ Res Public Health. 15(1018)2018.PubMed/NCBI View Article : Google Scholar

50 

Brown TT and Qaqish RB: Antiretroviral therapy and the prevalence of osteopenia and osteoporosis: A meta-analytic review. AIDS. 20:2165–2174. 2006.PubMed/NCBI View Article : Google Scholar

51 

Tao L, Huang Q, Yang R, Dai Y, Zeng Y, Li C, Li X, Zeng J and Wang Q: The age modification to leukocyte telomere length effect on bone mineral density and osteoporosis among Chinese elderly women. J Bone Miner Metab. 37:1004–1012. 2019.PubMed/NCBI View Article : Google Scholar

52 

Fragkiadaki P, Nikitovic D, Kalliantasi K, Sarandi E, Thanasoula M, Stivaktakis PD, Nepka C, Spandidos DA, Tosounidis T and Tsatsakis A: Telomere length and telomerase activity in osteoporosis and osteoarthritis. Exp Ther Med. 19:1626–1632. 2020.PubMed/NCBI View Article : Google Scholar

53 

Curtis EM, Codd V, Nelson C, D'Angelo S, Wang Q, Allara E, Kaptoge S, Matthews PM, Tobias JH, Danesh J, et al: Telomere length and risk of incident fracture and arthroplasty: Findings from UK Biobank. J Bone Miner Res. 37:1997–2004. 2022.PubMed/NCBI View Article : Google Scholar

54 

Farr JN, Fraser DG, Wang H, Jaehn K, Ogrodnik MB, Weivoda MM, Drake MT, Tchkonia T, LeBrasseur NK, Kirkland JL, et al: Identification of senescent cells in the bone microenvironment. J Bone Miner Res. 31:1920–1929. 2016.PubMed/NCBI View Article : Google Scholar

55 

Haapanen MJ, Perälä MM, Salonen MK, Guzzardi MA, Iozzo P, Kajantie E, Rantanen T, Simonen M, Pohjolainen P, Eriksson JG and von Bonsdorff MB: Telomere length and frailty: The Helsinki birth cohort study. J Am Med Dir Assoc. 19:658–662. 2018.PubMed/NCBI View Article : Google Scholar

56 

Hong Z, Lin X, Zhou Y, Zheng G, Liao X, Wei Q, Zhang Z and Liang J: Lean body mass but not body fat mass is related with leukocyte telomere length in children. Int J Obes (Lond). 47:67–74. 2023.PubMed/NCBI View Article : Google Scholar

57 

Pignolo RJ, Suda RK, McMillan EA, Shen J, Lee SH, Choi Y, Wright AC and Johnson FB: Defects in telomere maintenance molecules impair osteoblast differentiation and promote osteoporosis. Aging Cell. 7:23–31. 2008.PubMed/NCBI View Article : Google Scholar

58 

Brennan TA, Egan KP, Lindborg CM, Chen Q, Sweetwyne MT, Hankenson KD, Xie SX, Johnson FB and Pignolo RJ: Mouse models of telomere dysfunction phenocopy skeletal changes found in human age-related osteoporosis. Dis Model Mech. 7:583–592. 2014.PubMed/NCBI View Article : Google Scholar

59 

Singh L, Brennan TA, Kim JH, Egan KP, McMillan EA, Chen Q, Hankenson KD, Zhang Y, Emerson SG, Johnson FB and Pignolo RJ: Long-Term functional engraftment of mesenchymal progenitor cells in a mouse model of accelerated aging. Stem Cells. 31:607–611. 2013.PubMed/NCBI View Article : Google Scholar

60 

Kveiborg M, Kassem M, Langdahl B, Eriksen EF, Clark BF and Rattan SI: Telomere shortening during aging of human osteoblasts in vitro and leukocytes in vivo: Lack of excessive telomere loss in osteoporotic patients. Mech Ageing Dev. 106:261–271. 1999.PubMed/NCBI View Article : Google Scholar

61 

Tang NL, Woo J, Suen EW, Liao CD, Leung JC and Leung PC: The effect of telomere length, a marker of biological aging, on bone mineral density in elderly population. Osteoporos Int. 21:89–97. 2010.PubMed/NCBI View Article : Google Scholar

62 

Kirk B, Kuo CL, Xiang M and Duque G: Associations between leukocyte telomere length and osteosarcopenia in 20,400 adults aged 60 years and over: Data from the UK Biobank. Bone. 161(116425)2022.PubMed/NCBI View Article : Google Scholar

63 

Sepúlveda-Loyola W, Phu S, Bani Hassan E, Brennan-Olsen SL, Zanker J, Vogrin S, Conzade R, Kirk B, Al Saedi A, Probst V and Duque G: The joint occurrence of osteoporosis and sarcopenia (Osteosarcopenia): Definitions and Characteristics. J Am Med Dir Assoc. 21:220–225. 2020.PubMed/NCBI View Article : Google Scholar

64 

Aviv A, Valdes AM and Spector TD: Human telomere biology: Pitfalls of moving from the laboratory to epidemiology. Int J Epidemiol. 35:1424–1429. 2006.PubMed/NCBI View Article : Google Scholar

65 

Sanders JL, Cauley JA, Boudreau RM, Zmuda JM, Strotmeyer ES, Opresko PL, Hsueh WC, Cawthon RM, Li R, Harris TB, et al: Leukocyte Telomere length is not associated with BMD, osteoporosis, or fracture in older adults: Results from the health, aging and body composition study. J Bone Miner Res. 24:1531–1536. 2009.PubMed/NCBI View Article : Google Scholar

66 

Saeed H, Abdallah BM, Ditzel N, Catala-Lehnen P, Qiu W, Amling M and Kassem M: Telomerase-deficient mice exhibit bone loss owing to defects in osteoblasts and increased osteoclastogenesis by inflammatory microenvironment. J Bone Miner Res. 26:1494–1505. 2011.PubMed/NCBI View Article : Google Scholar

67 

Baird D: New developments in telomere length analysis. Exp Gerontol. 40:363–368. 2005.PubMed/NCBI View Article : Google Scholar

68 

Lai TP, Zhang N, Noh J, Mender I, Tedone E, Huang E, Wright WE, Danuser G and Shay JW: A method for measuring the distribution of the shortest telomeres in cells and tissues. Nat Commun. 8(1356)2017.PubMed/NCBI View Article : Google Scholar

69 

Lu AT, Seeboth A, Tsai PC, Sun D, Quach A, Reiner AP, Kooperberg C, Ferrucci L, Hou L, Baccarelli AA, et al: DNA methylation-based estimator of telomere length. Aging (Albany NY). 11:5895–5923. 2019.PubMed/NCBI View Article : Google Scholar

70 

Dagnall CL, Hicks B, Teshome K, Hutchinson AA, Gadalla SM, Khincha PP, Yeager M and Savage SA: Effect of pre-analytic variables on the reproducibility of qPCR relative telomere length measurement. PLoS One. 12(e0184098)2017.PubMed/NCBI View Article : Google Scholar

71 

Lin J, Smith DL, Esteves K and Drury S: Telomere length measurement by qPCR-Summary of critical factors and recommendations for assay design. Psychoneuroendocrinology. 99:271–278. 2019.PubMed/NCBI View Article : Google Scholar

72 

Bodelon C, Savage SA and Gadalla SM: Telomeres in Molecular Epidemiology Studies. Prog Mol Biol Transl Sci. 125:113–131. 2014.PubMed/NCBI View Article : Google Scholar

73 

Semeraro MD, Smith C, Kaiser M, Levinger I, Duque G, Gruber HJ and Herrmann M: Physical activity, a modulator of aging through effects on telomere biology. Aging (Albany NY). 12:13803–13823. 2020.PubMed/NCBI View Article : Google Scholar

74 

Kirwan M and Dokal I: Dyskeratosis congenita, stem cells and telomeres. Biochim Biophys Acta. 1792:371–379. 2009.PubMed/NCBI View Article : Google Scholar

75 

McGrath JA: Dyskeratosis congenita: New clinical and molecular insights into ribosome function. Lancet. 353:1204–1205. 1999.PubMed/NCBI View Article : Google Scholar

76 

Tsuge K and Shimamoto A: Research on werner syndrome: Trends from past to present and future prospects. Genes (Basel). 13(1802)2022.PubMed/NCBI View Article : Google Scholar

77 

Du X, Shen J, Kugan N, Furth EE, Lombard DB, Cheung C, Pak S, Luo G, Pignolo RJ, DePinho RA, et al: Telomere shortening exposes functions for the mouse werner and bloom syndrome genes. Mol Cell Biol. 24:8437–8446. 2004.PubMed/NCBI View Article : Google Scholar

78 

Hofer AC, Tran RT, Aziz OZ, Wright W, Novelli G, Shay J and Lewis M: Shared phenotypes among segmental progeroid syndromes suggest underlying pathways of aging. J Gerontol A Biol Sci Med Sci. 60:10–20. 2005.PubMed/NCBI View Article : Google Scholar

79 

Mason PJ, Wilson DB and Bessler M: Dyskeratosis Congenita-A disease of dysfunctional telomere maintenance. Curr Mol Med. 5:159–170. 2005.PubMed/NCBI View Article : Google Scholar

80 

Salminen A, Suuronen T, Huuskonen J and Kaarniranta K: NEMO shuttle: A link between DNA damage and NF-kappaB activation in progeroid syndromes? Biochem Biophys Res Commun. 367:715–718. 2008.PubMed/NCBI View Article : Google Scholar

81 

Crabbe L, Verdun RE, Haggblom CI and Karlseder J: Defective telomere lagging strand synthesis in cells lacking WRN Helicase activity. Science. 306:1951–1953. 2004.PubMed/NCBI View Article : Google Scholar

82 

Majors AK, Boehm CA, Nitto H, Midura RJ and Muschler GF: Characterization of human bone marrow stromal cells with respect to osteoblastic differentiation. J Orthop Res. 15:546–557. 1997.PubMed/NCBI View Article : Google Scholar

Related Articles

Journal Cover

November-2023
Volume 19 Issue 5

Print ISSN: 2049-9434
Online ISSN:2049-9442

Sign up for eToc alerts

Recommend to Library

Copy and paste a formatted citation
x
Spandidos Publications style
Kakridonis F, Pneumatikos SG, Vakonaki E, Berdiaki A, Tzatzarakis MN, Fragkiadaki P, Spandidos DA, Baliou S, Ioannou P, Hatzidaki E, Hatzidaki E, et al: Telomere length as a predictive biomarker in osteoporosis (Review). Biomed Rep 19: 87, 2023.
APA
Kakridonis, F., Pneumatikos, S.G., Vakonaki, E., Berdiaki, A., Tzatzarakis, M.N., Fragkiadaki, P. ... Vasiliadis, E. (2023). Telomere length as a predictive biomarker in osteoporosis (Review). Biomedical Reports, 19, 87. https://doi.org/10.3892/br.2023.1669
MLA
Kakridonis, F., Pneumatikos, S. G., Vakonaki, E., Berdiaki, A., Tzatzarakis, M. N., Fragkiadaki, P., Spandidos, D. A., Baliou, S., Ioannou, P., Hatzidaki, E., Nikitovic, D., Tsatsakis, A., Vasiliadis, E."Telomere length as a predictive biomarker in osteoporosis (Review)". Biomedical Reports 19.5 (2023): 87.
Chicago
Kakridonis, F., Pneumatikos, S. G., Vakonaki, E., Berdiaki, A., Tzatzarakis, M. N., Fragkiadaki, P., Spandidos, D. A., Baliou, S., Ioannou, P., Hatzidaki, E., Nikitovic, D., Tsatsakis, A., Vasiliadis, E."Telomere length as a predictive biomarker in osteoporosis (Review)". Biomedical Reports 19, no. 5 (2023): 87. https://doi.org/10.3892/br.2023.1669