Serum Carboxylated and Undercarboxylated Osteocalcin association with Coronary Atherosclerosis Disease and Cardiovascular Risk Markers in: Analysis of a Syrian Male Cohort

Hosam Eddin Shahrour^1,2*, Sahar Al Fahom^1,2,3, Ghassan Al Massarani^4,5, Kenda Jawich¹, Ahmad Rasheed AlSaadi⁶

¹Department of Biochemistry and Microbiology, Faculty of Pharmacy, Damascus University, Damascus, Syria.

²Al Rasheed International Private University for Science and Technology, Damascus, Syria.

³University of Kalamoon, Damascus, Syria.

⁴Department Radiation Medicine, Pharmacological Studies Division, Atomic Energy Commission of Syria (AECS), Damascus, Syria.

⁵International University of Science and Technology (IUST), Damascus, Syria.

⁶Department of Internal Medicine, Cardiovascular Disease Section, Faculty of Medicine Damascus University, Damascus, Syria.

*Corresponding Author E-mail: hosam.shahrour@damascusuniversity.edu.sy.

ABSTRACT:

Background: New assumption concerning association of osteocalcin and Vascular calcification has emerged in reaction to observations that the mechanism of vascular calcification resembles that of bone mineralization, thus linking bone and the vasculature. However, studies reported contrasting results about the association between osteocalcin and atherosclerosis. This study was designed to evaluate capacity relationships among different forms of circulating osteocalcin and cardiovascular risk markers in male with coronary atherosclerosis.
Methods: A cross-sectional study was conducted on 58 male patients, divided into two groups according to the severity of coronary artery disease (CAD), as determined by coronary angiography assessment: Early coronary atherosclerosis (ECA), n=20, patients with mild CAD (<50% stenosis in any major epicardial arteries), and late coronary atherosclerosis (LCA), n=38, patients with severe, multivessel CAD (>50% stenosis in at least one or more major epicardial arteries). The healthy control (HC) group included 26 healthy male subjects. Carboxylated (cOC) and ucOC were measured using ELISA technique. Results: We observed significantly lower ucOC levels in both stages of cardiovascular disease (CVD) (ECA and LCA) compared to the HC group (2.34±2.23 and 2.48±1.60 vs 6.65±1.78ng/mL, P<0.01). ucOC was inversely correlated with an increasing number of cardiovascular risk factors (CVRFs). Moreover, ucOC levels were markedly reduced in high-fasting plasma glucose (FPG) groups (IFG and T2DM-threshold level), compared to the normal FPG group (NG). cOC levels were higher in the IFG group, compared to the normal FPG group (8.50±4.76 vs 7.13±3.13ng/mL, p=0.008) possibly predicting such condition. Conclusions: In the present study, patients with coronary atherosclerosis, regardless of the onset of stenosis, showed lower ucOC levels which were inversely correlated with an increasing number of CVRFs. Moreover, ucOC levels were markedly reduced in high-FPG groups. Serum ucOC may be considered as a potential biomarker for coronary atherosclerosis disease and therefore its measurement may help to establish preventive and therapeutic approaches. Moreover, cOC may be associated with a high alert for diabetes at the IFG stage, but not when the disease progresses to diabetes.

KEYWORDS: Coronary atherosclerosis disease, atherosclerosis, biomarker, osteocalcin, undercarboxylated osteocalcin, carboxylated osteocalcin, cardiovascular risk factors, fasting plasma glucose, diabetes.

INTRODUCTION:

Atherosclerosis is a complicated disease caused by multifactorial disorder^1-5, multiple genotypes⁶, and several mechanism^7-9. Vascular calcification has been considered to be a passive pathological process associated with aging. However, in the last years, vascular calcification proved to be an active cell-mediated process, similar to bone mineralization¹⁰, in which different bone-related proteins are involved¹¹. Moreover, the association between osteoporosis and cardiovascular disease (CVD), found in most epidemiological and pathophysiological studies, suggests with increasing evidence the involvement of the skeleton in the regulation and process of atherosclerotic vascular disease (ASCVD)¹⁰. The skeleton is nowadays recognized as an endocrine organ^12-14 involved in several metabolic processes^15,16. Previous studies showed an extended biological function for the osteoblast that is focused on the actions of osteocalcin^17-19. Osteocalcin is an osteoblast-derived vitamin K-dependent protein that exists in the circulation in two forms, carboxylated (cOC) and undercarboxylated (ucOC)^20-22. Through the secretion of osteocalcin, the skeleton regulates several functions, including glucose homeostasis^14,18 and male reproductive functions²³. Clinical studies suggest a more complex role for osteocalcin in human metabolism, which led to investigating its association with ASCVD^24-27, and clarification of the role of osteocalcin as a vital mediator or a nonparticipant observer in energy metabolism²⁸.

This study is aimed to evaluate the association of serum cOC and ucOC levels with cardiovascular risk markers in a cohort of male patients with different severity of coronary atherosclerosis, as determined by coronary angiography assessment.

Study design and participants:

A cross-sectional study was conducted on 58 male patients, divided into two groups according to the severity of coronary artery disease (CAD), determined by coronary angiography assessment: Early coronary atherosclerosis (ECA), 20 patients, aged (55.1±10.8 years), defined as patients with mild CAD (<50% stenosis in any major epicardial arteries), and late coronary atherosclerosis (LCA), 38 patients, aged (59.0± 9.5 years), defined as patients with severe, multivessel CAD (>50% stenosis in at least one or more major epicardial arteries). The healthy control (HC) group included 26 healthy male subjects, aged (38.6±7.7 years). Patients were hospitalized at the cardiac catheterization department in Alassad University hospital. Clinical and demographic data were used following hospital regulations and written consent was obtained from each patient. Patients were stratified according to having one or more of the following cardiovascular risk factors (CVRFs): 1. history of hypertension: systolic blood pressure ≧140mmHg, diastolic blood pressure ≧90mmHg; 2. history of type 2 diabetes mellitus (T2DM): hemoglobin A1c ≧6.5%, fasting plasma glucose (FPG) ≧126mg/dL; 3. history of hypercholesterolemia: total cholesterol (TC) ≧200 mg/dL, LDL-C ≧100mg/dL; 4. previous/current smoking; 5. obesity, body mass index ≧30kg/m2; and 6. family history of premature CAD: CAD in first-degree relatives <55 years (male) or <65 years (female). Concomitant medications are summarized in Supplemental Table 1. Patients with impaired renal function, paralysis, depletion, two weeks of bed rest, had previous hormonal or metabolic disorders or taking medications known to influence bone or calcium metabolism, such as vitamin D, bisphosphonates, calcitonin, estrogen, corticosteroids, or warfarin were excluded. This study was approved by Human Research Ethics Committee, Faculty of Pharmacy, Damascus University (HRECPHARMDU).

Biochemical measurements:

Enzyme immunoassay was used to measure concentrations of ucOC (Glu-OC MK118, Takara Bio Inc.) and cOC (Gla-OC MK111, Takara Bio Inc.) in serum samples from venous blood. Lipid profile and fasting plasma glucose (FPG) were measured according to standard automated clinical procedures.

Statistical analysis:

Data were analyzed using the Statistical Package for the Social Sciences v26 (SPSS, Inc., Chicago, Illinois). The Kolmogorov-Smirnov test was performed to assess the sample cumulative distribution. Quantitative continuous variables were presented as mean±SD or median and interquartile range. Normally distributed variables were analyzed using the two independent samples t-test. To analyze non-normally distributed data the Mann-Whitney U test was performed. Kruskal Wallis test was used to compare the mean ranks of ucOC and cOC among different groups. Spearman correlation coefficient was used to assess the strength of the association between ucOC, cOC, and CVRFs. Statistical significance was set at p<0.05.

RESULTS:

Patients Characteristics:

The demographic, clinical, and biochemical characteristics of the study subjects are displayed in Table 1. HC subjects were younger than ECA and LCA patients (38.6±7.7 vs 55.1±10.8, 59.0±9.5 years, p<0.01). BMI was higher in ECA and LCA than in HC group (29.56±3.72, 28.34±4.00 vs 23.60±2.41kg/m², P<0.01). The prevalence of smoking was similar in all groups. FPG was significantly different between HC (91.15±11.48mg/dL) and both ECA (155.45±92.58 mg/dL) and LCA (161.71±83.75mg/dL) groups (both p<0.01). No significant difference in FPG was found between ECA and LCA. There was a significant difference in the lipid profile between groups. TC and LDL-C were lower in the ECA and LCA groups, compared to HC group (TC: 155.4±53.54, 142.13±36.67 vs 185.88±27.81 mg/dL, P<0.01; LDL-C: 84.65±30.07, 80.61±25.01 vs 108.23±27.27 mg/dL, P<0.01), which is consistent with statin treatment in 65% of the patients in the ECA and LCA groups (Supplemental Table 1). HDL-C was lower in ECA and LCA groups than in HC group (31.5±9.58, 26±5.82mg/dL vs 42±9.86, P<0.01). TG was higher in HC group than ECA group only (171.27±54.78 vs 135.25±87.17mg/dL, P=0.006) (Table 1).

Serum ucOC and cOC levels and coronary atherosclerosis severity:

Levels of ucOC were not different between ECA and LCA groups, whereas it showed significantly lower levels in both groups compared to HC group (2.34±2.23, 2.48±1.60 vs 6.65±1.78 ng/mL, P<0.01) (Table 2). Such difference is independent of age (Table 3). There was no significant difference in cOC levels between CVD groups (Table 2).

Table 1. Demographic, anthropometric, and biochemical parameters.

Variables	HC (n=26)	ECA (n=20)	LCA (n=38)	P-value Kruskal Wallis	P-value	Post-hoc	Bonferroni test
Age (yr)	38.6±7.7	55.1± 10.8	59.0± 9.5	<0.01	1.0*	<0.01**	<0.01#
BMI (kg/m²)	23.60±2.41	29.56±3.72	28.34±4.00	<0.01	0.75*	<0.01**	<0.01#
Smoking n (%)	7(26.9)	12(36.4)	17(33.3)	0.739	_	_	_
HDL-C (mg/dL)	42±9.86	31.5±9.58	26±5.82	<0.01	0.179*	<0.01**	<0.01#
LDL-C*** (mg/dL)	108.23±27.27	84.65±30.07	80.61±25.01	<0.01	1.0*	<0.01**	0.01#
TC*** (mg/dL)	185.88±27.81	155.4±53.54	142.13±36.67	<0.01	1.0*	<0.01**	0.02#
TG*** (mg/dL)	171.27±54.78	135.25±87.17	151.29±81.45	0.008	0.199*	0.279**	0.006#
FPG (mg/dL)	91.15±11.48	155.45±92.58	161.71±83.75	<0.01	1.0*	<0.01**	<0.01#

Results are expressed as mean±SD; SD: Standard Deviation. HC: healthy controls; ECA: early coronary atherosclerosis; LCA: late coronary atherosclerosis; BMI: body mass index; TC: total cholesterol; LDL-C: cholesterol bound to low-density lipoproteins; HDL-C: cholesterol bound to high density lipoproteins; TG: triglycerides; FPG: fasting plasma glucose. *LCA vs ECA. **LCA vs HC # ECA vs HC. *** 65% of patients was taking statins.

Table 2. ucOC and cOC levels according to study groups

Variables

HC (n=26)

ECA (n=20)

LCA (n=38)

P-value

Kruskal Wallis

P-value

Post-hoc

Bonferroni test

ucOC (ng/mL)

6.65±1.78

2.34±2.23

2.48±1.60

<0.01

1.0*

<0.01**

<0.01#

cOC (ng/mL)

7.29±3.267

8.81±4.21

8.57±4.31

0.35

Results are expressed as mean±SD; SD: Standard Deviation, or median and interquartile range HC: healthy controls; ECA: early coronary atherosclerosis; LCA: late coronary atherosclerosis; ucOC: undercarboxylated osteocalcin; cOC: carboxylated osteocalcin. *LCA vs ECA; **LCA vs HC; # ECA vs HC.

Table 3. Linear regression of the association between ucOC and age across the whole study population (HC+ECA+LCA)

	Model 1		Model 2
Variable	β-coefficient	p-value	β-coefficient	p-value
age	n/a	n/a	-0.062	0.002
HC+ECA+LCA	2.278	<0.001	1.721	<0.001

After adjustment by age in model 2, the difference of ucOC levels among HC and ECA/LCA groups is still significant, suggesting that such difference is independent of age.

Table 4. Correlation of ucOC and cOC levels (whole study cohort) with specific cardiovascular risk factors

	Age	BMI	HDL	LDL	TC	TG	FPG
ucOC	-0.459^**	-0.522^**	0.465^**	0.285^**	0.292^**	0.089	-0.586^**
cOC	0.125	-0.216^*	0.040	0.149	0.131	-0.064	-0.068

Correlations were determined using Spearman correlation coefficients. *p < 0.05; ** p < 0.01. ucOC: undercarboxylated osteocalcin; cOC: carboxylated osteocalcin; BMI: body mass index; TC: Total cholesterol; LDL: Cholesterol bound to low-density lipoproteins; HDL: Cholesterol bound to high density lipoproteins; TG: Triglycerides; FPG: Fasting Plasma Glucose; ECA: Early Coronary Atherosclerosis. LCA: Late Coronary Atherosclerosis.

Compared to the NG group, levels of ucOC significantly (p<0.01) decreased in both IFG and T2DM-threshold groups (2.89±1.4, 1.80±1.64 vs 5.70±2.37ng/mL), without significant differences between the latter (Table 5). On the contrary, cOC levels were greater in the IFG group, compared to the NG group (8.50±4.76 vs 7.13±3.13ng/mL), but did not differ between NG and T2DM-threshold groups (Table 5).

According to Receiver operating characteristics (ROC) curve analyses (cOC: area-under-the-curve [AUC]= 0.720, P=0.002), cOC levels appear to be an associated risk predictor for IFG. (Figure 2)

DISCUSSION:

Atherosclerosis has been associated with circulating osteocalcin changes; however, data about this association are often conflicting and unclear^29,30. In the present study, we observed significantly lower ucOC levels in both CVD (ECA and LCA) groups than in HC. We also found that ucOC level was inversely correlated with increasing number of CVRFs. Moreover, ucOC levels were markedly reduced in high-FPG groups (IFG and T2DM-threshold level), compared to normal FPG group. cOC was higher in the IFG group and according to ROC analysis possibly predicting such condition.

According to our findings, serum ucOC level may be relevant as a biomarker of CVD risk and/or presence of clinical/subclinical CVD. More specifically, reduced ucOC levels may be regarded as an indicator of early CVD risk, since significantly lower ucOC was already found in the ECA group with less severe/subclinical CVD, in addition to the LCA group with more severe CVD, as well as when even just 1 (trend, p=0.061) or 2 (p=0.001) CVRFs were present.

As far as we know, this appears to be the first study reporting such association of lower ucOC with early atherosclerosis.

No significant difference was found between ECA or LCA, possibly suggesting that ucOC has no role in the progression of the disease after it has been initiated. However, ucOC levels were found to be progressively reduced according to the increasing number of CVRFs, although ucOC levels observed with 4 CVRFs were not significantly lower than with 3 CVRFs.

ucOC was negatively correlated with age and with BMI, also according to previous reports^31-33.

The findings of this study suggest that ucOC may be a prognostic factor for the possibility of occurrence of coronary atherosclerosis in apparently healthy subjects³². In this regard, one may propose future studies on the influence of regulatory agents and vitamin D³⁴ on the expression of osteocalcin gene (BGLAP). No difference was found in cOC levels between all CVD groups.

When considering FPG separately from the other CVRFs, ucOC levels were found to be markedly reduced in high-FPG groups (IFG and T2DM-threshold level), compared to normal FPG group.

cOC significantly increased in IFG group, that is a high alert for diabetes, although decreased in the diabetes group. This appears to be the first report indicating cOC as an early prognostic marker for IFG.

This finding is supported by meta-analyses reporting that TOC and ucOC are similarly and negatively correlated with FPG, and glycated hemoglobin (HbA1c) in humans¹⁶. Additionally, we found ucOC negatively correlated with FPG, that is consistent with previous studies reporting an inverse correlation between serum ucOC levels and insulin resistance and FPG^35-37.

ucOC significantly decreased in the IFG group and decreased again in the diabetes group. The decrease of both cOC in the diabetes group and ucOC in the IFG and diabetes groups could be due to chronic exposure to high concentrations of glucose. possibly leading to a decrease in OCN gene transcription in osteoblast-like cell lines³⁸. This assumption was demonstrated by the administration of ucOC in mice¹⁵, suggesting that ucOC may be targeted as a future therapeutic approach for metabolic diseases³⁹.

ucOC levels were found to be positively correlated with TC, LDL-C, and HDL-C. The correlation of ucOC with HDL-C may suggest that a low ucOC is linked to an atherogenic dyslipidemic profile that would increase cardiovascular risk. This is in agreement with several previous studies^{25,40, 41}. Regarding TC and LDL-C, since 65% of the patients in the ECA/LCA groups were taking statins, such a relationship may be difficult to interpret, also in consideration of the potential impact of such (and other) treatment on cOC and ucOC levels. In this regard, the available data in the literature is not conclusive. Thus, this important issue needs to be addressed in larger studies.

CONCLUSIONS:

This study concluded that low ucOC seems linked to greater risk/presence of coronary atherosclerotic disease, with apparent better sensitivity for early disease. Moreover, cOC may be associated with a high alert for diabetes at the IFG stage, but not when the disease progresses to diabetes. Serum ucOC is a potential biomarker for cardiovascular coronary atherosclerosis disease to establish preventive and therapeutic approaches. In addition to a potential biomarker for early atherosclerosis risk, whether ucOC may also be a protective factor, relevant to the improvement of metabolic profile, and reduction of CVD risk, remains to be established^42,43.

CONFLICT OF INTERESTS:

The authors declare that there is no conflict of interest regarding the publication of this paper.

REFERENCE:

1. Kaur S. A Descriptive Study to Assess the Prevalence of Cardiovascular risk factors among Adolescents in Selected Schools of Banga, District Shaheed Bhagat Singh Nagar, Punjab. Asian J. Nur. Edu. and Research, 2016. 6(3): p. 361-370. DOI: 10.5958/2349-2996.2016.00068.9.

2. Mounika S. and D. Gopinath. Periodontitis as a Risk Factor of Atherosclerosis. Research J. Pharm. and Tech, 2016. 9(11): p. 2017-2019. DOI.

3. Katakami N. H. Kaneto, and I. Shimomura. Carotid ultrasonography: A potent tool for better clinical practice in diagnosis of atherosclerosis in diabetic patients. Journal of Diabetes Investigation, 2014. 5. DOI: 10.1111/jdi.12106.

4. Prabha J.L. and M. Sankar. Role of Il-1 in Atherosclerosis. Research J. Pharm. and Tech, 2018. 11(7): p. 3163-3166. DOI: 10.5958/0974-360X.2018.00581.4.

5. Jadhav K.L., et al. Genetic Insights of Cholesterol and Atherosclerosis: Complex Biology. Asian J. Pharm. Res., 2018. 8(3): p. 175-184. DOI.

6. Jadhav K.L., et al. Genetic Insights of Cholesterol and Atherosclerosis: Complex Biology. Asian J. Pharm. Res. 2018. 175-184(3). DOI.

7. Baragetti A., et al. Effect of Lipids and Lipoproteins on Hematopoietic Cell Metabolism and Commitment in Atherosclerosis. Immunometabolism, 2021. 3(2): p. e210014. DOI: 10.20900/immunometab20210014.

8. Dib S. and R. Makhous. Research J. Pharm. and Tech. 13(5): p. 2329-2334. DOI.

9. Wihastuti T.A., et al. Polysaccharide Peptide (PsP) of Ganoderma lucidum as vasa vasorum anti-Angiogenesis agent in Dyslipidemic state by Measuring Lp-PLA2 and H2O2 Levels. Research J. Pharm. and Tech., 2020. 13(7): p. 3241-3245. DOI.

10. Laroche M., et al. Osteoporosis and ischemic cardiovascular disease. Joint Bone Spine, 2016. 84. DOI: 10.1016/j.jbspin.2016.09.022.

11. Johnson R.C. J.A. Leopold, and J. Loscalzo. Vascular calcification: pathobiological mechanisms and clinical implications. Circ Res, 2006. 99(10): p. 1044-59. DOI: 10.1161/01.res.0000249379.55535.21.

12. Lee N.K., et al. Endocrine regulation of energy metabolism by the skeleton. Cell, 2007. 130(3): p. 456-69. DOI: 10.1016/j.cell.2007.05.047.

13. Riddle R.C. and T.L. Clemens. Bone Cell Bioenergetics and Skeletal Energy Homeostasis. Physiological Reviews, 2017. 97(2): p. 667-698. DOI: 10.1152/physrev.00022.2016.

14. Liu J.M., et al. Regulation of Glucose Handling by the Skeleton: Insights From Mouse and Human Studies. Diabetes, 2016. 65(11): p. 3225-3232. DOI: 10.2337/db16-0053.

15. Ferron M., et al. Intermittent injections of osteocalcin improve glucose metabolism and prevent type 2 diabetes in mice. Bone, 2012. 50(2): p. 568-75. DOI: 10.1016/j.bone.2011.04.017.

16. Liu D.M., et al. Association between osteocalcin and glucose metabolism: a meta-analysis. Osteoporos Int, 2015. 26(12): p. 2823-33. DOI: 10.1007/s00198-015-3197-8.

17. Ducy P. The role of osteocalcin in the endocrine cross-talk between bone remodelling and energy metabolism. Diabetologia, 2011. 54(6): p. 1291-7. DOI: 10.1007/s00125-011-2155-z.

18. Zoch M.L. T.L. Clemens, and R.C. Riddle. New insights into the biology of osteocalcin. Bone, 2016. 82: p. 42-9. DOI: 10.1016/j.bone.2015.05.046.

19. Kumar M.P.S. and T. Nandhini. Mechanism of action of Bone Morphogenic Protein 3 in the maintenance of Tissue Homeostasis. Research J. Pharm. and Tech, 2018. 11(3): p. 1270-1274. DOI.

20. Hauschka P.V., et al. Osteocalcin and matrix Gla protein: vitamin K-dependent proteins in bone. Physiol Rev, 1989. 69(3): p. 990-1047. DOI.

21. Gundberg C.M., et al. Vitamin K status and bone health: an analysis of methods for determination of undercarboxylated osteocalcin. J Clin Endocrinol Metab, 1998. 83(9): p. 3258-66. DOI: 10.1210/jcem.83.9.5126.

22. Shao J., et al. Bone Regulates Glucose Metabolism as an Endocrine Organ through Osteocalcin. International journal of endocrinology, 2015. 2015: p. 967673. DOI: 10.1155/2015/967673.

23. Karsenty G. and F. Oury. Regulation of male fertility by the bone-derived hormone osteocalcin. Molecular and cellular endocrinology, 2014. 382(1): p. 521-526. DOI: 10.1016/j.mce.2013.10.008.

24. Millar S., et al. Osteocalcin, Vascular Calcification, and Atherosclerosis: A Systematic Review and Meta-analysis. Frontiers in Endocrinology, 2017. 8: p. 183. DOI: 10.3389/fendo.2017.00183.

25. Sanchez-Enriquez S., et al. Serum levels of undercarboxylated osteocalcin are related to cardiovascular risk factors in patients with type 2 diabetes mellitus and healthy subjects. World journal of diabetes, 2017. 8(1): p. 11-17. DOI: 10.4239/wjd.v8.i1.11.

26. Magni P., et al. Osteocalcin as a potential risk biomarker for cardiovascular and metabolic diseases. Clinical chemistry and laboratory medicine, 2016. 54. DOI: 10.1515/cclm-2015-0953.

27. Zhang M., et al. Undercarboxylated osteocalcin as a biomarker of subclinical atherosclerosis in non-dialysis patients with chronic kidney disease. J Biomed Sci, 2015. 22: p. 75. DOI: 10.1186/s12929-015-0183-6.

28. Razzaque M.S. Osteocalcin: a pivotal mediator or an innocent bystander in energy metabolism? Nephrol Dial Transplant, 2011. 26(1): p. 42-5. DOI: 10.1093/ndt/gfq721.

29. Tacey A., et al. Potential Role for Osteocalcin in the Development of Atherosclerosis and Blood Vessel Disease. Nutrients, 2018. 10(10): p. 1426. DOI: 10.3390/nu10101426.

30. Millar S.A., et al. Osteocalcin, Vascular Calcification, and Atherosclerosis: A Systematic Review and Meta-analysis. Frontiers in Endocrinology, 2017. 8(183). DOI: 10.3389/fendo.2017.00183.

31. Polgreen L.E., et al. Association of Osteocalcin With Obesity, Insulin Resistance, and Cardiovascular Risk Factors in Young Adults. Obesity, 2012. 20(11): p. 2194-2201. DOI: https://doi.org/10.1038/oby.2012.108.

32. Razny U., et al. Carboxylated and undercarboxylated osteocalcin in metabolic complications of human obesity and prediabetes. Diabetes Metab Res Rev, 2017. 33(3). DOI: 10.1002/dmrr.2862.

33. Ingram R.T., et al. Age- and gender-related changes in the distribution of osteocalcin in the extracellular matrix of normal male and female bone. Possible involvement of osteocalcin in bone remodeling. The Journal of clinical investigation, 1994. 93(3): p. 989-997. DOI: 10.1172/JCI117106.

34. Sofihussein H.Q., et al. Effect of Vitamin D supplement on the risks of Cardiovascular disease in patients with type 2 diabetes in the Kurdistan Region of Iraq. Research J. Pharm. and Tech, 2020. 13: p. 4125-4129. DOI: 10.5958/0974-360X.2020.00728.3.

35. Ferron M., et al. Osteocalcin differentially regulates beta cell and adipocyte gene expression and affects the development of metabolic diseases in wild-type mice. Proc Natl Acad Sci U S A, 2008. 105(13): p. 5266-70. DOI: 10.1073/pnas.0711119105.

36. Gössl M., et al. Coronary endothelial dysfunction in humans is associated with coronary retention of osteogenic endothelial progenitor cells. European heart journal, 2010. 31: p. 2909-14. DOI: 10.1093/eurheartj/ehq373.

37. Kanazawa I., et al. Serum osteocalcin level is associated with glucose metabolism and atherosclerosis parameters in type 2 diabetes mellitus. J Clin Endocrinol Metab, 2009. 94(1): p. 45-9. DOI: 10.1210/jc.2008-1455.

38. Bilotta F.L., et al. Insulin and osteocalcin: further evidence for a mutual cross-talk. 2018. 59(3): p. 622-632. DOI: 10.1007/s12020-017-1396-0.

39. Tacey A., et al. Osteocalcin and vascular function: is there a cross-talk? Molecular Metabolism, 2021. 49: p. 101205. DOI: https://doi.org/10.1016/j.molmet.2021.101205.

40. De Pergola G., et al. Independent Relationship of Osteocalcin Circulating Levels with Obesity, Type 2 Diabetes, Hypertension, and HDL Cholesterol. Endocr Metab Immune Disord Drug Targets, 2016. 16(4): p. 270-275. DOI: 10.2174/1871530317666170106150756.

41. Lee N.K., et al. Endocrine regulation of energy metabolism by the skeleton. Cell, 2007. 130(3): p. 456-469. DOI: 10.1016/j.cell.2007.05.047.

42. Pollock N.K., et al. Lower uncarboxylated osteocalcin concentrations in children with prediabetes is associated with beta-cell function. J Clin Endocrinol Metab, 2011. 96(7): p. E1092-9. DOI: 10.1210/jc.2010-2731.

43. Prats-Puig A., et al. Carboxylation of osteocalcin affects its association with metabolic parameters in healthy children. Diabetes Care, 2010. 33(3): p. 661-3. DOI: 10.2337/dc09-1837.

Received on 14.09.2021 Modified on 29.11.2021

Research J. Pharm. and Tech 2022; 15(9):3987-3992.

DOI: 10.52711/0974-360X.2022.00668