Skip to main content
  • Original Research Article
  • Open access
  • Published:

An exploratory cohort study of serum estradiol, testosterone, osteoprotegerin, interleukin-6, calcium, and magnesium as potential biomarkers of cervical spondylosis

Abstract

Background

Exploration of biomarkers for debilitating diseases such as cervical spondylosis is important to revolutionize clinical diagnosis and management of such conditions. The study aimed to determine the correlation between neck pain and disability and serum levels of interleukin-6 (IL-6), osteoprotegerin (OPG), estradiol (E2), testosterone (TES), calcium (Ca), and magnesium (Mg) among individuals with symptomatic cervical spondylosis.

Methods

This study was a cohort design. The participants were new referrals to two Nigerian physical therapy clinics. Participants’ neck pain intensity (PI), neck disability index (NDI), IL-6, OPG, E2, TES, Ca, and Mg were measured at baseline and after 13 weeks of follow-up. Data were analyzed using descriptive statistics, independent samples t test, Pearson’s correlation, and multiple linear regression.

Results

Forty individuals aged 52.40 ± 8.60 years participated in the study. Women had significantly higher levels of IL-6 (t =  − 2.392, p = 0.026), OPG (t =  − 3.235, p = 0.005), E2 (t =  − 6.841, p = 0.001), but lower TES (t = 17.776, p = 0.001). There were no significant sex differences in PI and NDI. There were significant correlations between PI and OPG (r = 0.385, p < 0.001), NDI and OPG (r = 0.402, p < 0.001), and IL-6 (r = 0.235, p = 0.036). Significant predictors of PI were OPG (β = 0.442, p < 0.001) and E2 (β =  − 0.285, p = 0.011), and NDI were OPG (β = 0.453, p < 0.001), E2 (β =  − 0.292, p = 0.005), and IL-6 (β = 0.225, p = 0.024).

Conclusion

High serum levels of IL-6 and OPG were associated with cervical spondylosis severity. However, high serum levels of E2 and TES correlated with lesser severity. Moreover, TES inversely correlated with the proinflammatory cytokines.

Introduction

Research into the biomolecular basis of diseases is gaining interest in physical therapy. Identifying biomarkers associated with the pathogenesis of common diseases will help in developing prophylaxis and improving interventions for such diseases. It will also help explain the biomolecular mechanism of action of physical therapy modalities of known efficacy. A biomarker is a measurable characteristic whose values indicate normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention [1]. Recent integrative approaches to chronic pain management focus on neuroinflammation and the roles of chemical mediators such as osteoprotegerin (OPG) and interleukins [2], yet there is a paucity of studies on the role of these biomarkers in prevalent musculoskeletal conditions such as cervical spondylosis [3].

Cervical spondylosis is a common age-related degenerative disease leading to significant neck pain, stiffness, discomfort, disability, and economic burden and it hampers the quality of life among adults globally [4]. Characteristically, cervical spondylosis can begin with cervical facet joint arthritis and a feature of gradual degenerative cervical disc changes, which can lead to the formation of osteophytes around the edges of the vertebrae body [5]. Severe cases may lead to axial joint dysfunction due to ligament, articular cartilage, and facet joint involvement as well as compression of a nerve root or spinal cord causing cervical radiculopathy or myelopathy [5, 6].

Cervical spondylosis contributes significantly to years lived with disability (YLD), and 85% of individuals, 60 years and older, show evidence of cervical spondylosis on radiographic imaging [7]. The prevalence of cervical spondylosis in southwestern Nigeria was 10.7% [8]. A sedentary lifestyle, smoking, use of technological devices involving prolonged neck bending (computer and phones), manual handling jobs, menopause, older age, and its associated biophysical decline predisposes individuals to cervical spondylosis [9, 10]. Therefore, countries experiencing increased longevity and civilization are faced with an increased incidence of symptomatic cervical spondylosis and its burden. For instance, the UK spends approximately 681.6 million pounds on residual disability and other complications from cervical spondylosis despite the initial cost of primary interventions [11]. Some of these cost goes into physical therapy in which modalities and procedures such as transcutaneous electrical nerve stimulation, infrared therapy, and cervical traction have been found promising.

Based on the literature, the following biomarkers may correlate with cervical spondylosis severity: interleukin-6 (IL-6) [12, 13], OPG [14], sex hormones (estradiol [E2] and testosterone [TES]), calcium (Ca), and magnesium (Mg) [15,16,17,18,19,20,21]. Henceforth, in this study, the term biomarkers represent IL-6, OPG, E2, TES, Ca, and Mg. Briefly, OPG and IL-6 are pro-inflammatory cytokines. OPG is a soluble member of the tumor necrosis factor receptor superfamily with pleiotropic effects on bone metabolism and endocrine function [22]. It can downregulate osteoclastogenesis by regulating nuclear transcription factor kappa B (NFKB) [23]. However, IL-6 can inhibit OPG and facilitate receptor activators of nuclear factor kappa B ligand (RANKL) mRNA activity, thus disrupting the RANKL/OPG ratio and resulting in higher bone damage [24]. Nonetheless, TES and E2 moderate osteoclastogenesis by regulating OPG and IL-6 [25,26,27]. The complex interaction between the inflammatory cytokines and sex hormones affects the serum levels of Ca and Mg via their osteoclastic activities [27, 28]. Figure 1 is a theoretical framework for the correlation between the biomarkers under study, neck pain, and disability.

Fig. 1
figure 1

Theoretical interactions between the biomarkers and primary outcomes. Models 1–7: correlation between neck pain and (1) neck disability, (2) serum calcium and magnesium, (3) serum estradiol and testosterone, (4) serum osteoprotegerin and interleukin-6; the correlation between neck disability and (5) serum calcium and magnesium, (6) serum estradiol and testosterone, and (7) serum osteoprotegerin and interleukin-6

This study aimed to explore the correlation between serum levels of IL-6, OPG, E2, TES, Ca, and Mg with the pain intensity (PI) and neck disability index (NDI) and to identify biomarkers and sociodemographic variables that could predict PI and NDI among the cohort. The study hypothesized that there would be no significant (a) correlation between the biomarkers, PI, and NDI, and (b) association between the biomarkers, sociodemographic factors, and each of PI and NDI.

Methods

Study design

This paper is a secondary analysis of a cohort study involving forty gender-matched participants who were diagnosed with cervical spondylosis and referred for physical therapy follow-up. The protocol was approved by the Health Research and Ethics Committee of the Health Research and Ethics Committee of the National Orthopaedic Hospital Enugu (NOHE), Nigeria (IRB/HEC Protocol No: S.313/IV/985). Each participant signed a written informed consent before study entry. The study was conducted following the guidelines of the revised Declaration of Helsinki 2013 and reported in adherence to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist for cohort studies [29].

Cohort description

The cohort were participants of a cross-over cohort study, designed to assess the effect of biomarkers, infrared radiation, and cervical traction therapies on neck pain intensity and disability among people with cervical spondylosis [30, 31]. The study involved adult male and female patients (n = 20, each), aged between 30 and 64 years, who were diagnosed with cervical spondylosis with radiculopathy and referred for physical therapy in NOHE and Saint Mary Hospital Enugu (SMHE), Southeast Nigeria. Cervical spondylosis was diagnosed by the consultant orthopedic doctors at NOHE and SMHE using the medical history such as neck pain characteristics and duration, physical examination, and the presence of symptomatic degenerative changes in a magnetic resonance image of the cervical spine [30]. All the patients with positive diagnoses were informed about the study, and patients that provided signed informed consent notes and passed the inclusion criteria were recruited into the study. The study was conducted at the Department of Physiotherapy in both hospitals between 31 March 2016 and 7 March 2018.

Participant eligibility criteria

Participants were included in the study if they were aged between 30 and 65 years, diagnosed with cervical spondylosis, and had at least 1-month history of neck pain with radiculopathy due to cervical spondylosis. Pregnant women, patients with low bone density, ankylosing spondylitis, rheumatoid arthritis, kyphosis, scoliosis, cervical instability, tumor, trauma or fracture, severe hypertension, diabetes, active infection, and any other systemic diseases were excluded.

Sample size determination

A post hoc sample size was calculated using a moderate effect size of 0.25, with an alpha error probability of 0.05, and a power of 0.95. The output showed that 74 samples would have ample power for a fixed model multiple linear regression (G*Power 3.1.9.4 software). However, the pooled data (baseline and follow-up) were 80 samples used for the final analysis.

Sampling and bias

To avoid sampling bias, the authors conducted purposive simultaneous participant recruitment and data collection at NOHE and SMHE [32]. Though we aimed to counterbalance gender in our recruitment, there were more women participants, and we could only achieve a gender-matched cohort when four eligible women from SMHE declined participation for personal reasons.

Variables

Participants’ sociodemographic variables were sex (women = 0, men = 1), age (years), and duration since pain onset (months), extracted from the hospital records. Physical measures obtained were weight (kg), height (cm), and body mass index (BMI = height squared/weight [m2/kg]). Primary outcomes were PI (0 to 10 score) and NDI (0 to 50 score). Secondary outcomes were serum concentration of bone minerals (Ca2 and Mg [mmol/L]), biomarkers of inflammation (OPG and IL-6 [pg/ml]), and hormones (E2 [pg/ml] and TES [ng/ml]). Apart from sex (dichotomous variable), all other variables were continuous/scale.

Procedures and instruments

All the outcomes were measured at baseline and during the 13-week follow-up.

Physical measures

Participants’ weight and height were measured to the nearest 0.1 kg and 0.1 cm, respectively, using a standard BMI apparatus (RGZ-120, made in China; weight/[height]2 = BMI) and protocol [33].

Subjective measures

The Numeric Pain Rating Scale (NPRS) was used to measure the participants’ PI on an 11-point scale (0–no pain to 10–worst pain imaginable). NPRS is a reliable, valid, and responsive measure of PI among individuals with neck pain [34]. The NDI was used to estimate the participant’s neck disability level. The NDI comprised ten items: (seven) related to the activity of daily living, (two) related to pain, and (one) related to concentration. Each item is scored from 0 to 5, the total expected score is 0 to 50; higher scores indicate greater disability. The NDI has good psychometric properties (validity and reliability) in patients with neck pain [34].

Laboratory analysis

In anticipation of their potential impacts on the biomarkers, participants were instructed to refrain from the consumption of any drug, caffeine, alcohol, and exercise for at least 48 h before the data collection [35]. Moreover, serum samples for Ca and Mg were collected under overnight fasting conditions because they can be easily affected by diet [36]. The serum concentrations of the biomarkers were analyzed using participants’ 5 mil blood samples, drawn through an antecubital venepuncture between 8:00 AM and 10:00 AM by a phlebotomist [35]. Each participant’s sample was shared into three different sample bottles appropriate for the tests. All samples were correctly labeled and transported in a cold box from NOHE and SMHE to the Spectrum Biomedical Laboratory (SBL), Enugu, Nigeria (about 10-min drive). Assays were performed in triplicate of thawed samples, and the median scores were reported.

The ethylenediamine tetraacetic acid (EDTA) bottles (Caremax Co., Ltd; Made in China©) were used to collect the sample for serum OPG and IL-6 analyses. The blood samples were centrifuged using a bucket centrifuge (Jenalab-model 800D; made in England) at 3000 rpm for 10 min at 4o C, and the supernatant (serum) was collected using a micropipette and stored frozen at − 20o C until they were required for analysis. The laboratory analysis was completed using a commercial human enzyme-linked immunosorbent assay (ELISA) kit (BIOTANG; Made in the USA©). The absorbance was read at 450 nm using a microwell plate reader (Diagnostic Automation- DAR 800; Made in the USA©). The laboratory reference range of IL-6 for healthy adults was 0 to 43.5 pg/ml.

The serum Ca and Mg were analyzed from blood samples collected from the antecubital vein without the tourniquet. The sample was discharged into a lithium heparin bottle and transported immediately to the laboratory; the fresh sample was centrifuged at 3000 rpm. The serum was harvested and analyzed with an automated chemistry analyzer (Roche Diagnostics Ltd., Model: Cobas c 111; Made in Germany©). The laboratory reference ranges for adult human serum Mg were 0.66 mmol/L to 1.07 mmol/L, and serum Ca was 2.2 to 2.7 mmol/L.

The serum E2 and TES (ng/ml) were analyzed from participants’ blood samples, collected, and allowed to coagulate in a plain sample bottle for 20 min, and the supernatant was collected using a micropipette and analyzed with an automated immunology analyzer (Roche Diagnostics Ltd., Model: Cobas e 411; Made in Germany©). The laboratory reference ranges for E2 were 30 to 400 pg/mL for premenopausal women and 10 to 50 pg/mL for men. Reference values for TES were 2.50 to 9.50 ng/mL for adult males and 0.10 to 0.90 ng/mL for adult females.

Statistical analysis

The data collected from the study were analyzed with SPSS 26 software (SPSS, Chicago, IL, USA). Baseline data characteristics were analyzed using mean ± standard deviation. The dataset was assessed and fixed for assumptions of parametric statistics: independent samples t test, Pearson’s correlation, and multiple linear regression [37]. There were issues of missing variables, univariate and multivariate outliers, normality, linearity, or multicollinearity. Therefore, sex differences in participants’ baseline characteristics were determined using an independent samples t test. For the correlation and regression analyses, the baseline and post-follow-up data were pooled and analyzed. The pooled data met all five assumptions of comparability: same participants, sampling, instrument, outcomes, and context [38]. Pearson’s correlation coefficient was used to analyze the correlation between the biomarkers, PI, and NDI. Multiple linear regressions were completed to determine any of the biomarkers (OPG, IL-6, E2, TES, Ca2, and Mg), sociodemographic and anthropometric variables that could significantly predict PI and NDI.

Results

The participants were 40 individuals (20 men and 20 women) aged (mean ± SD) 52.40 ± 8.60 years and presented with moderate neck pain (PI = 6.90 ± 2.20) and disability (NDI = 21.40 ± 8.84) and medical history of 24.66 ± 27.00 months. There were significant sex differences (p < 0.05) in height, BMI, OPG, IL-6, E2, and TES among the participants. The males were taller and had more TES, while females were heavier relative to their heights, and secreted more E2, OPG, and IL-6. Table 1 shows participants’ sociodemographic, anthropometric, and clinical characteristics. While the baseline data (n = 40) was used to compute the sociodemographic panel (Table 1), pooled data (baseline plus the 13-week follow-up, n = 80) was used for correlation and regression analyses (Fig. 2).

Table 1 Sex differences in participants’ baseline characteristics
Fig. 2
figure 2

The study flowchart

Pearson’s correlation test (Table 2) showed a strong positive correlation between PI and NDI (r = 0.896, p < 0.001). Serum OPG correlated with PI (r = 0.385, p < 0.001) and NDI (r = 0.402, p < 0.001), while IL-6 correlated with NDI (r = 0.235, p = 0.036) only. There was no significant correlation between the rest of the biomarkers and the measures of cervical spondylosis severity. However, there were significant negative correlations between IL-6 and TES (r =  − 0.295, p = 0.008), and Ca (r =  − 0.239, p = 0.033); OPG and TES (r =  − 0.451, p =  < 0.001); and E2 and TES (r =  − 0.701, p < 0.001). There was a positive correlation between OPG and E2 (r = 0.241, p = 0.032). Due to the hormonal sex differences observed in Table 1, there was a negative correlation between TES (male hormone) and each of E2, OPG, and IL-6 (perceived to be higher in females).

Table 2 Correlation between PI, NDI, and the biomarkers (n = 80)

Multiple linear regression models were completed to determine sets of biomarkers, sociodemographic, and anthropometric characteristics that could significantly predict PI and NDI, respectively (Table 3). The forward stepwise approach showed that only OPG (β = 0.450, p < 0.001) and E2 (β =  − 0.271, p = 0.011) could significantly predict the PI. The model was well fit (F [2, 77] = 10.675, p < 0.001). However, only 20% of the total variance could be explained by the model (adjusted R2 = 0.20). The neck disability index could be significantly predicted by OPG (β = 0.453, p < 0.001), E2 (β =  − 0.292, p = 0.005), and (β = 0.225, p = 0.024). The model was well fit (F [3, 76] = 9.958, p < 0.001), and 25% of the total variance was explained (adjusted R2 = 0.25).

Table 3 Forward stepwise multiple linear regression showing (biomarkers) predictors of neck pain and disability

Discussion

Formerly, cervical spondylosis defined the processes of cervical disc degeneration; however, the term has been broadened to incorporate vertebral osteophytic changes, osteoarthritis of the Luschka and facet joints, and inflammatory reactions characterized by debilitating neck pain and disability [5]. Studies have identified lifestyle, habitual and occupational posture, menopause, and age-related degenerative changes among the predisposing factors of cervical spondylosis [6, 9, 10]. Although the biomolecular mechanisms of these degenerative changes and the inflammatory responses have not been fully understood, the by-products of this degenerative process such as osteophytes and ruptured disc materials may compress neural structure in their canals resulting in cervical radiculopathy, myelopathy, and axial neck pain which are the clinical syndromes of cervical spondylosis [39].

There are prospects for biomarkers in advancing the diagnosis and prognosis of spinal diseases [3, 40]. In this study, serum levels of estradiol, testosterone, osteoprotegerin, interleukin-6, calcium, and magnesium were investigated as potential biomarkers of cervical spondylosis severity. The most common complaints of people with cervical spondylosis are neck pain and disability [30]; therefore, we used NPRS and NDI to estimate the disease severity among the cohort. While older pain theories such as the pain gait theory informed structural pathology-based models, recent theories gave insights into the inflammatory basis of spinogenic pain transmission and remission via biomolecular responses [35, 41]. Studies have shown a potential link between cervical degenerative disc diseases and bloodborne mediators of inflammation such as IL-6 [12, 13] and OPG [14]. Although there is a paucity of research that directly linked biomarkers of bone turnover such as sex hormones (E2 and TES), Ca, and Mg with cervical spondylosis [17, 19], some studies have reported an association between bone turnover and cervical spondylosis [16, 18, 21, 42]. Therefore, the conceptual framework in Fig. 1 is plausible. Khan et al. [3] stated that articulating diagnostic and prognostic biomarkers for spinal diseases will be of great clinical relevance.

We found a significant association between OPG and E2 with pain intensity and OPG, E2, and IL-6 with neck disability. However, there was no significant association between other biomarkers, sociodemographic, and anthropometric variables with neck pain intensity and disability via stepwise multiple linear regression. Weber et al. [43] found that serum IL-6 was significantly higher in patients with degenerative disc disease and spinal stenosis than in their counterparts with disc herniation only. Similar to the present study, Du et al. [12] reported that higher IL-6 and OPG were significant predictors of higher pain intensity and disability index. Previous studies have reported that the proinflammatory cytokines (IL-6 and OPG) were mediators of nociception in disc degeneration processes [3, 44]. Apart from the pain-mediating activities of the cytokines, OPG helps to reduce systemic inflammatory bone degeneration and osteoporosis via the inhibition of osteoclastogenesis [28]. The interplay between OPG, E2, and serum Ca2 and Mg improves bone mineral density [45]. Since, osteoporosis has a negative impact on cervical spondylosis [15, 16, 18, 21, 42, 46], higher serum levels of IL-6 might signify a worsening inflammatory process, which may necessitate higher OPG secretion as a protective response.

Pearson’s correlation test showed a strong positive correlation between neck pain intensity and disability index, this outcome is expected as the convergent criterion validity of NPRS and NDI is well known [34]. While OPG correlated with neck pain intensity and disability, IL-6 correlated with neck disability only. There was no significant correlation between the rest of the biomarkers and the measure of cervical spondylosis severity. This outcome agrees with the finding of [12] who reported a positive correlation between IL-6 levels and symptom severity, in a rat model of degenerative cervical myelopathy. As already established in medical research, the present study reported sex differences in E2 and TES levels, such that women had higher E2 and lower TES and vice versa. There was a significant inverse relationship between E2 and TES with PI and NDI. Testosterone levels had a negative correlation with proinflammatory cytokines (IL-6 and OPG) and measures of cervical spondylosis severity. Conversely, E2 had a positive correlation with the cytokines. This implies that women may have more disease severity. Concurringly, Lv et al. [9] reported that cervical spondylosis prevalence was higher in women than in men (16.51 vs 10.49%). With the moderating roles sex home plays in bone metabolism and inflammation, post-menopausal women might have more cervical spondylosis severity than men of similar age.

While serum Mg had no significant correlation with PI, NDI, and the rest of the biomarkers, Ca had a significant inverse correlation with IL-6 levels. The impact of blood levels of calcium and magnesium and their influence via the parathyroid calcium sensory receptor has been found to indirectly downregulate the IL-6 osteoclastic and inflammatory activities [47]. Contrarily, Omoigui [41] suggested that higher serum calcium could be associated with higher IL-6 levels, bone pain, osteoclastic activities, degeneration, and disability. Zhao et al. [48] reported that serum Ca correlated with the degree of disk degeneration, suggesting that serum Ca be used as an indicator of intervertebral disk degeneration prognosis. Understanding the osteoclastic and osteoblastic activities and their biomarkers is crucial to the comprehension of normal bone turnover and could be implicated in metabolic and degenerative bone diseases.

Study significance and strength

The previous paper [30] reported the efficacy of concurrent infrared and cervical traction for cervical spondylosis, the present paper has shown a correlation between cervical spondylosis and some of the biomarkers. The next paper will explore the mechanism of action of infrared therapy and cervical traction via their effects on the biomarkers. This study highlighted some salient points necessary for conducting a successful laboratory assay of biomarkers, and this resource will be helpful to physiotherapists planning biomarker studies. The major strength of this paper is the pooled baseline and follow-up data which improved the statistical power. However, a segregated baseline and follow-up analysis also yielded similar results. Moreover, the paper has provided basics for future exploration of some of these biomarkers that were lacking in the literature with reference to cervical spondylosis and physical therapy interventions.

Limitation

Although the participants were gender-matched, non-probability sampling techniques are prone to sampling bias which may affect the generalisability of this study.

Conclusion

Higher levels of serum interleukin-6 and osteoprotegerin may predict higher cervical spondylosis severity, measured as neck pain intensity and disability. Increased levels of sex hormones (estradiol and testosterone) were inversely correlated with disease severity. Specifically, increasing endogenous estradiol was a significant predictor of milder disease even when we controlled for age and sex. Moreover, serum testosterone levels were inversely correlated with the proinflammatory cytokines. Although the present study could not establish an association between the serum level of bone minerals (calcium and magnesium) and the severity of the disease, there are indications from the literature that higher serum calcium correlates with cervical spondylosis severity.

Availability of data and materials

The dataset analyzed during the current study is available at the Zenodo repository https://doi.org/10.5281/zenodo.4337859 [31].

Abbreviations

Ca:

Calcium

E2:

Estradiol

IL-6:

Interleukin-6

Mg:

Magnesium

NOHE:

National Orthopedic Hospital, Enugu

NPRS:

Numerical Pain Rating Scale

OPG:

Osteoprotegerin

PI:

Pain intensity

SMHE:

St. Mary’s Hospital Enugu

TES:

Testosterone

References

  1. Chen XH, Huang S, Kerr D. Biomarkers in clinical medicine. IARC Sci Publ. 2011;163:303–22.

    Google Scholar 

  2. Ellis A, Bennett DLH. Neuroinflammation and the generation of neuropathic pain. Br J Anaesth. 2013;111(1):26–37.

    CAS  PubMed  Google Scholar 

  3. Khan AN, Jacobsen HE, Khan J, Filippi CG, Levine M, Lehman RA Jr, et al. Inflammatory biomarkers of low back pain and disc degeneration: a review. Ann N Y Acad Sci. 2017;1410(1):68–84.

    PubMed  PubMed Central  Google Scholar 

  4. Voorhies RM. Cervical spondylosis: recognition, differential diagnosis, and management. Ochsner J. 2001;3(2):78–84.

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Shedid D, Benzel EC. Cervical spondylosis anatomy: pathophysiology and biomechanics. Neurosurgery. 2007;60(suppl1):S7–13.

    PubMed  Google Scholar 

  6. Iheukwumere N, Okoye E. Prevalence of symptomatic cervical spondylosis in a Nigerian tertiary health institution. Trop J Med Res. 2014;17(1):25–7.

    Google Scholar 

  7. Hurwitz EL, Randhawa K, Yu H, Côté P, Haldeman S. The global spine care initiative: a summary of the global burden of low back and neck pain studies. Eur Spine J. 2018;27(Suppl 6):796–801.

    PubMed  Google Scholar 

  8. Oguntona SA. Cervical spondylosis in South West Nigerian farmers and female traders. Ann Afr Med. 2014;13(2):61–4.

    CAS  PubMed  Google Scholar 

  9. Lv Y, Tian W, Chen D, Liu Y, Wang L, Duan F. The prevalence and associated factors of symptomatic cervical spondylosis in Chinese adults: a community-based cross-sectional study. BMC Musculoskelet Disord. 2018;19(1):325.

    PubMed  PubMed Central  Google Scholar 

  10. McLean SM, May S, Klaber-Moffett J, Sharp DM, Gardiner E. Risk factors for the onset of non-specific neck pain: a systematic review. J Epidemiol Community Health. 2010;64(7):565–72.

    PubMed  Google Scholar 

  11. Davies BM, Phillips R, Clarke D, Furlan JC, Demetriades AK, Milligan J, et al. Establishing the socio-economic impact of degenerative cervical myelopathy is fundamental to improving outcomes. Global Spine J. 2022;12(Suppl 1):122s-s129.

    PubMed  PubMed Central  Google Scholar 

  12. Du S, Sun Y, Zhao B. Interleukin-6 serum levels are elevated in individuals with degenerative cervical myelopathy and are correlated with symptom severity. Med Sci Monit. 2018;24:7405–13.

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Hu W, Ma X-L, Yuan J-J, Zhang R-Z, Peng B, Zhang X-L. Expression of interleukin-1 beta, interleukin-6 and cyclooxygenase 2 in cervical intervertebral disc of cervical spondylosis patients with different clinical symptoms. Chinese J Tissue Eng Res. 2016;20(35):5270.

    Google Scholar 

  14. Yu HM, Chen XL, Wei W, Yao XD, Sun JQ, Su XT, et al. Effect of osteoprotegerin gene polymorphisms on the risk of cervical spondylotic myelopathy in a Chinese population. Clin Neurol Neurosurg. 2018;175:149–54.

    PubMed  Google Scholar 

  15. Dinizo M, Buckland A. History, physical exam, and differential diagnosis of vertebral compression fracture. In: Razi A, Hershman S, editors. Vertebral compression fractures in osteoporotic and pathologic bone: A Clinical Guide to Diagnosis and Management. Switzerland: Springer; 2020. p. 69-74.

  16. Ebeling PR. Androgens and osteoporosis. Curr Opin Endocrinol Diabetes Obes. 2010;17(3):284–92.

    CAS  PubMed  Google Scholar 

  17. Jin LY, Lv ZD, Wang K, Qian L, Song XX, Li XF, et al. Estradiol alleviates intervertebral disc degeneration through modulating the antioxidant enzymes and inhibiting autophagy in the model of menopause rats. Oxid Med Cell Longev. 2018;2018:7890291.

    PubMed  PubMed Central  Google Scholar 

  18. Harada A, Okuizumi H, Miyagi N, Genda E. Correlation between bone mineral density and intervertebral disc degeneration. Spine. 1998;23(8):857–61.

    CAS  PubMed  Google Scholar 

  19. Liu S, Yang SD, Huo XW, Yang DL, Ma L, Ding WY. 17β-estradiol inhibits intervertebral disc degeneration by down-regulating MMP-3 and MMP-13 and up-regulating type II collagen in a rat model. Artif Cells Nanomed Biotechnol. 2018;46(sup2):182–91.

    CAS  PubMed  Google Scholar 

  20. Miyahara M, Hillier SL, Pridham L, Nakagawa S. Task-oriented interventions for children with developmental co-ordination disorder. Cochrane Database Syst Rev. 2017;7(7):CD010914.

    PubMed  Google Scholar 

  21. Muraki S, Yamamoto S, Ishibashi H, Horiuchi T, Hosoi T, Orimo H, et al. Impact of degenerative spinal diseases on bone mineral density of the lumbar spine in elderly women. Osteoporos Int. 2004;15(9):724–8.

    PubMed  Google Scholar 

  22. Kudlacek S, Schneider B, Woloszczuk W, Pietschmann P, Willvonseder R. Serum levels of osteoprotegerin increase with age in a healthy adult population. Bone. 2003;32(6):681–6.

    CAS  PubMed  Google Scholar 

  23. Fili S, Karalaki M, Schaller B. Therapeutic implications of osteoprotegerin. Cancer Cell Int. 2009;9:26.

    PubMed  PubMed Central  Google Scholar 

  24. Harmer D, Falank C, Reagan MR. Interleukin-6 interweaves the bone marrow microenvironment, bone loss, and multiple myeloma. Front Endocrinol. 2018;9:788.

    Google Scholar 

  25. Bellido T, Jilka RL, Boyce BF, Girasole G, Broxmeyer H, Dalrymple SA, et al. Regulation of interleukin-6, osteoclastogenesis, and bone mass by androgens. The role of the androgen receptor. J Clin Invest. 1995;95(6):2886–95.

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Michael H, Härkönen PL, Väänänen HK, Hentunen TA. Estrogen and testosterone use different cellular pathways to inhibit osteoclastogenesis and bone resorption. J Bone Miner Res. 2005;20(12):2224–32.

    CAS  PubMed  Google Scholar 

  27. Streicher C, Heyny A, Andrukhova O, Haigl B, Slavic S, Schüler C, et al. Estrogen regulates bone turnover by targeting RANKL expression in bone lining cells. Sci Rep. 2017;7(1):6460.

    PubMed  PubMed Central  Google Scholar 

  28. Schett G, Redlich K, Smolen JS. The role of osteoprotegerin in arthritis. Arthritis Res Ther. 2003;5(5):239–45.

    CAS  PubMed  PubMed Central  Google Scholar 

  29. von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet. 2007;370(9596):1453–7.

    Google Scholar 

  30. Igwe AA, Onyeso OK, Ezema CI, Eyichukwu GO, Ejim EC, Egwuonwu VA, et al. Effects of cervical traction and infrared therapy on pain intensity and neck disability index among people with cervical spondylosis: a cross-over cohort study. J Musculoskelet Res. 2022;25:2250023.

    Google Scholar 

  31. Igwe AA, Ezema CI, Onyeso OK, Eyichukwu GO, Ejim EC, Egwuonwu VA, et al. Effects of cervical traction, infrared therapy, and selected biomarkers on neck disability indexes among people with cervical spondylosis: a sequential clinical trial. Zenodo. 2020. https://doi.org/10.5281/zenodo.4337859.

  32. Ekediegwu EC, Akpaenyi CE, Nwosu IB, Onyeso OK. Demographic and disease characteristics associated with pain intensity, kinesiophobia, balance, and fall self-efficacy among people with osteoarthritis: a cross-sectional study. BMC Musculoskelet Disord. 2022;23(1):544.

    PubMed  PubMed Central  Google Scholar 

  33. Anyachukwu CC, Onyeso OKK, Ezema CI. Age, body mass and physical activity determinants of facial acne severity among southern Nigerian adolescents and young adults. W Indian Med J. 2018;5(2):66–71.

    Google Scholar 

  34. Cleland JA, Childs JD, Whitman JM. Psychometric properties of the neck disability index and numeric pain rating scale in patients with mechanical neck pain. Arch Phys Med Rehabil. 2008;89(1):69–74.

    PubMed  Google Scholar 

  35. Ezema CI, Onyeso OK, Nna EO, Awosoga OA, Odole AC, Kalu ME, et al. Transcutaneous electrical nerve stimulation effects on pain-intensity and endogenous opioids levels among chronic low-back pain patients: a randomised controlled trial. J Back Musculoskelet Rehabil. 2022;35(5):1053–64.

    PubMed  Google Scholar 

  36. Delmas PD, Eastell R, Garnero P, Seibel MJ, Stepan J. The use of biochemical markers of bone turnover in osteoporosis. Committee of scientific advisors of the international osteoporosis foundation. Osteoporos Int. 2000;11(Suppl 6):S2–17.

    PubMed  Google Scholar 

  37. Garson GD. Testing statistical assumptions. Asheboro: Statistical Associates Publishing; 2012.

    Google Scholar 

  38. Schenker N, Raghunathan TE. Combining information from multiple surveys to enhance estimation of measures of health. Stat Med. 2007;26(8):1802–11.

    PubMed  Google Scholar 

  39. Kuo DT, Tadi P. Cervical spondylosis. Treasure Island: StatPearls Publishing; 2022.

    Google Scholar 

  40. Reveille JD. Biomarkers for diagnosis, monitoring of progression, and treatment responses in ankylosing spondylitis and axial spondyloarthritis. Clin Rheumatol. 2015;34(6):1009–18.

    PubMed  PubMed Central  Google Scholar 

  41. Omoigui S. The biochemical origin of pain--proposing a new law of pain: The origin of all pain is inflammation and the inflammatory response. Part 1 of 3--a unifying law of pain. Med Hypotheses. 2007;69(1):70–82.

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Miyakoshi N, Itoi E, Murai H, Wakabayashi I, Ito H, Minato T. Inverse relation between osteoporosis and spondylosis in postmenopausal women as evaluated by bone mineral density and semiquantitative scoring of spinal degeneration. Spine. 2003;28(5):492–5.

    PubMed  Google Scholar 

  43. Weber KT, Alipui DO, Sison CP, Bloom O, Quraishi S, Overby MC, et al. Serum levels of the proinflammatory cytokine interleukin-6 vary based on diagnoses in individuals with lumbar intervertebral disc diseases. Arthritis Res Ther. 2016;18:3.

    PubMed  PubMed Central  Google Scholar 

  44. Zu B, Pan H, Zhang XJ, Yin ZS. Serum levels of the inflammatory cytokines in patients with lumbar radicular pain due to disc herniation. Asian Spine J. 2016;10(5):843–9.

    PubMed  PubMed Central  Google Scholar 

  45. Piri F, Khosravi A, Moayeri A, Moradipour A, Derakhshan S. The effects of dietary supplements of calcium, vitamin D and estrogen hormone on serum levels of OPG and RANKL cytokines and their relationship with increased bone density in rats. J Clin Diagn Res. 2016;10(9):AF01-AF4.

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Wáng YXJ. Senile osteoporosis is associated with disc degeneration. Quant Imaging Med Surg. 2018;8(6):551–6.

    PubMed  PubMed Central  Google Scholar 

  47. Klein GL. The role of calcium in inflammation-associated bone resorption. Biomolecules. 2018;8(3):69.

    PubMed  PubMed Central  Google Scholar 

  48. Zhao B, Wang K, Zhao J, Luo Y. Serum calcium concentration as an indicator of intervertebral disk degeneration prognosis. Biol Trace Elem Res. 2013;154(3):333–7.

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors thank the staff and management of the Physiotherapy Departments of the National Orthopaedic Hospital, Enugu, and St. Mary’s Hospital, Enugu, where this study was conducted for approving and/or participating in this study. We also appreciate the staff of the Spectrum Biomedical Laboratory, Enugu, and all the volunteers who participated in the study.

Funding

There was no external funding for this study.

Author information

Authors and Affiliations

Authors

Contributions

AAI, CIE, GCO, and OKO contributed to the conception of this study. All authors made substantial contributions to the design and acquisition of the data. OKO and OOA performed the statistical analysis. OKO, AI, KMO, and CCA were responsible for drafting the article. AAI, CIE, OOA, and GCO contributed to its critical revision. The authors approved the final manuscript for publication.

Corresponding author

Correspondence to Ogochukwu Kelechi Onyeso.

Ethics declarations

Ethics approval and consent to participate

The authors obtained ethical approval to conduct this study from the Health Research and Ethics Committee of the Health Research and Ethics Committee of the National Orthopaedic Hospital Enugu (NOHE), Nigeria (IRB/HEC Protocol No: S.313/IV/985). The objectives, protocols, benefits, and potential harms of the study were clearly explained to the participants. Each participant signed a written informed consent before participating in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Igwe, A.A., Onyeso, O.K., Adandom, I. et al. An exploratory cohort study of serum estradiol, testosterone, osteoprotegerin, interleukin-6, calcium, and magnesium as potential biomarkers of cervical spondylosis. Bull Fac Phys Ther 28, 29 (2023). https://doi.org/10.1186/s43161-023-00141-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s43161-023-00141-y

Keywords