The Genetic and Life Style Determinants of Bone Mass of Young Greek Males

Overview

The genetic bases of peak bone mass in males, as determinants of an individual's risk of developing osteoporotic fractures in old age and their interaction with dietary and lifestyle factors are still poorly understood. Our objective was to examine the relative contribution of genetic and environmental variables to the regulation of peak bone mass in a population-based cohort of young healthy men, focusing on the BsmI polymorphism of vitamin D receptor (VDR)gene and the AluI polymorphism of calcitonin receptor (CTR)gene.

Material and Methods Subjects In this cross-sectional study, 301 Greek healthy young men, aged 16-35 were selected during gradational examinations for the Greek Armed forces. Men who were treated with corticosteroids, anticonvulsants, or anticoagulants or who suffered from hypogonadism, kidney, liver, thyroid and gastrointestinal disease or diabetes mellitus were excluded from the study. Approval by the hospital ethics committee and informed consent were obtained. Height and body weight were measured with the subjects in sportswear, standing barefoot on a fixed stadiometer and on a standard clinical balance. Height was recorded in centimetres and weight in kilograms. The stadiometer and scale were routinely monitored for accuracy and precision. Body mass index (BMI) was calculated as weight/height 2 . Dietary Evaluation Current dietary factors (calcium, proteins, alcohol, coffee and tea intake), were assessed using a food frequency questionnaire validated in the MEDOS study, and completed with an interview. Calcium intake was estimated considering milk, yogurt and cheese consumption. Protein intake was estimated by taking into account the consumption of meat and fish per week. Tea and coffee consumption was also taken into account. Nondieter factors were investigated using a questionnaire Physical was quantified as hours of sports activities per week (defined as taking part in organized sport for at least 12 months). Smoking behaviour was coded as 'yes' (daily smoking) or 'no', and sunlight exposure when there was exposure in places abroad during the previous 3 months. Duration of immobilizations was also coded as 'less' or 'more than 1 month' (in majority, due to fractures caused by high energy trauma). Genetic analyses Genomic DNA was extracted from peripheral blood leukocytes with a DNA extraction kit (Puregene DNA isolation kit, Gentra Systems Inc., Munich, Germany). Polymorphisms in the CTR and VDR genes were determined by polymerase chain reaction (PCR) as previously described using Taq DNA polymerase (Takara, Tokyo, Japan), and thermal cycler (PCR Primus 96 plus-MWG AG BIOTECH). 4μl of CTR-PCR product were digested with AluI (New England Biolabs, UK) and 2 μl of VDR-PCR product were digested with BsmI (New England Biolabs, UK) according to manufacturer’s instructions. AluI restriction digest yielded DNA fragments of 120/108-bp (TT), 228/120/108-bp (TC) and 228-bp (CC) and BsmI restriction digest yielded DNA fragments of 1200/650-bp (bb), 1850/1200/650-bp (Bb) and 1850-bp (BB), which were visualized using a 3% and 1% agarose gel respectively stained with ethidium bromide. BMD Measurements Distal BMC (dBMC), distal BMD (dBMD) and ultradistal BMD (udBMD) at the radius were measured by single X-ray absorptiometry (Osteometer DTX-100, Denmark). Additionally, there were assessments of the corresponding geometrical areas, such as radial area (RadAr), ulnar area (UlnAr) and ultradistal area (udAr). BMD is expressed as grams/cm2; BMC is expressed in grams and Area as cm2 The in vivo precision for the BMD and BMC measurements in our laboratory was 1-5%. Statistical Analysis Descriptive statistics were determined for all variables. All variables are sufficiently represented using the mean value (mean) and standard deviation (SD). Univariate analysis was performed using the two-sample Student's test or Welch-test (in a case of unequal SDs) and the model of one-way analysis of variance with no repeated measurements (pairwise multiple comparisons were analysed using the Tukey test). Analysis of covariance (ANCOVA) used the bone values (BMC, BMD, Area) as dependent variables, the VDR and CTR polymorphisms as factors and age, weight and height as covariates. Furthermore, multiple stepwise regression analysis was used to determine significant predictors of BMD. All tests are two sided; P\<0, 05 was defined as significant. All data analysis was performed using the Statistical Package for Social Sciences (version 10.0) software (SPSS Inc., Chicago, IL).

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