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Circulating osteoprotegerin is correlated with lipid profile, insulin sensitivity, adiponectin and sex steroids in an ageing male population
Author(s) -
GannagéYared MarieHélène,
Fares Florence,
Semaan Michelle,
Khalife Simon,
Jambart Selim
Publication year - 2006
Publication title -
clinical endocrinology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.055
H-Index - 147
eISSN - 1365-2265
pISSN - 0300-0664
DOI - 10.1111/j.1365-2265.2006.02522.x
Subject(s) - medicine , endocrinology , adiponectin , body mass index , blood pressure , osteoprotegerin , insulin , population , waist , triglyceride , quantitative insulin sensitivity check index , leptin , metabolic syndrome , sex hormone binding globulin , cholesterol , insulin resistance , androgen , diabetes mellitus , hormone , obesity , insulin sensitivity , receptor , environmental health , activator (genetics)
Summary Objective  The relationship between osteoprotegerin (OPG) and lipid profile, insulin sensitivity, adipocytokines and sex steroids has been poorly studied and subject to controversy. The purpose of this study was to look at the correlates of OPG in an elderly male population. Design  One hundred and fifty‐one nondiabetic, elderly Lebanese men (age range 50–83) were recruited in this cross‐sectional study based on voluntary enrolment. Measurements  In all the subjects, serum OPG levels were measured and related to clinical parameters (age, waist, body mass index (BMI), systolic and diastolic blood pressure), as well as to metabolic and hormonal parameters. The following fasting laboratory measurements were performed: plasma glucose and insulin levels, total cholesterol, triglycerides and HDL cholesterol, adiponectin, leptin, as well as sex steroids (testosterone, SHBG, free androgen index, ooestradiol, DHEAS), GH and IGF‐1. QUICKI index was calculated as a measure of insulin sensitivity. Results  OPG levels were significantly correlated with age ( r  = 0·28, P  < 0·0001) but not with BMI, waist, systolic or diastolic blood pressure. There was a trend towards higher OPG levels in subjects without, compared to subjects with the metabolic syndrome (3·58 ± 1·28 vs. 3·26 ± 1·04 pmol/l, P  = 0·09). OPG was negatively correlated with fasting glucose and triglyceride levels ( r  =  – 0·18, P  = 0·031 and r  = −0·19, P  = 0·02, respectively) and positively correlated with the QUICKI index ( r  = 0·17, P  = 0·033), HDL cholesterol ( r  = 0·21, P  = 0·009) and adiponectin levels ( r  = 0·27, P  = 0·001). No significant correlations were reported with total or LDL cholesterol levels and with leptin levels. After adjustment for age, OPG is still correlated with triglycerides ( r  =  – 0·19, P  = 0·02), glucose ( r  =  – 0·21, P  = 0·011) and adiponectin ( r  = 0·19, P  = 0·02). Finally, OPG was positively associated with SHBG ( r  = 0·31, P  < 0·001) and negatively associated with free androgen index ( r  = – 0·346, P  < 0·001); both correlations persisted after adjustment for age ( r  = 0·21, P  = 0·009 and r  = −0·23, P  = 0·005, respectively). No significant correlation was found between OPG and oestradiol levels while a weak negative correlation was demonstrated with DHEAS ( r  =  – 0·18, P  = 0·025). Also, no significant correlation was found between OPG and GH or IGF‐1 values. In a multiple regression analysis with a stepwise model, the main determinants of OPG were free androgen index and adiponectin ( P <  0·0001 and P  = 0·015, respectively). Conclusion  Our results show that circulating OPG levels are favourably associated with some components of the metabolic syndrome. Also, for the first time, an association between OPG and adiponectin is described. Finally, the negative correlation we found between OPG and free androgen index may suggest a potential role of OPG in the increase in cardiovascular disease related to ageing and sex steroid deficiency.

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