Kadir Kizilkaya

Effects of postmenopausal hormone replacement therapy on body fat composition

Aim. To evaluate the effects of different types, regimens and administration routes of hormone replacement therapy (HRT) on body fat composition indices in postmenopausal women at increased risk of anthropometry-related cardiovascular disease (CVD). Methods. Fifty-nine postmenopausal women (aged 41–57 years, mean ± standard deviation: 49.9 ± 3.8 years) with body mass index (BMI) ≥25 kg/m2 participated in this 6-month, prospective, randomized single-blind study. Subjects were assigned into three groups and received transdermal estradiol (E2)/norethisterone acetate (NETA) (50 μg E2 daily for 14 days followed by 50 μg E2/0.25 μg NETA daily for 14 days; transdermal group, n = 19), transdermal continuous E2/oral medroxyprogesterone acetate (MPA) (50 μg E2/5 mg MPA daily; transdermal/oral group, n = 19) or oral continuous E2/NETA (1 mg E2/0.5 mg NETA daily; oral group, n = 21). Anthropometric indices (body weight, height, and hip and waist circumferences) were measured, and BMI and waist-to-hip ratio (WHR) were calculated, before and after treatment. Also, the thickness of subcutaneous abdominal fat was measured by ultrasound. Depending on waist circumference (WC), the subjects were divided into two risk groups: increased-risk group with WC <88 cm (n = 32) and high-risk group with WC ≥88 cm (n = 27). Also, the effects of HRT were evaluated separately in subjects with median subcutaneous fat of <33 mm (n = 29) and those with median subcutaneous fat of ≥33 mm (n = 30). Results. Overall, all three types of HRT caused a significant decrease in both WC and subcutaneous fat (p < 0.001), and also in WHR (p < 0.05). There was no significant difference in baseline (p > 0.05) and final values (p > 0.05) between HRT groups. In each group, all types of HRT significantly decreased WC and subcutaneous fat (transdermal group: p < 0.001 and p < 0.05; transdermal/oral group: p < 0.001 and p < 0.01; oral group: p < 0.001 and p < 0.001, respectively), while body weight, BMI and WHR changed only insignificantly (p > 0.05). In the increased-risk group, body weight increased significantly (p < 0.05) while WC and subcutaneous fat decreased significantly (p < 0.001 and p < 0.001). As for the high-risk group, there was a significant decrease in WC and subcutaneous fat (p < 0.001, p < 0.001) while the remaining parameters did not change significantly. However, BMI showed a tendency to increase in the increased-risk group, while there was a decrease in all measurements in the high-risk group. Regardless of the drugs used and baseline subcutaneous fat, WC and subcutaneous fat decreased significantly at the end of the treatment (subcutaneous fat <33 mm: p < 0.001 and p < 0.01; subcutaneous fat ≥33 mm: p < 0.001 and p < 0.001, respectively). Conclusions. The three different types of HRT have comparable effects on central fat tissue in women at increased risk of anthropometry-related CVD. Indeed, the three combinations of HRT reduced fat tissue in the central part of the body. However, the overall effect of HRT was more marked in women with WC ≥88 cm and subcutaneous fat ≥33 cm. Whether HRT increases body weight depends on the body composition indices of individuals before treatment.

Morphological and microsatellite DNA diversity of Nigerian indigenous sheep

BackgroundSheep is important in the socio-economic lives of people around the world. It is estimated that more than half of our once common livestock breeds are now endangered. Since genetic characterization of Nigerian sheep is still lacking, we analyzed ten morphological traits on 402 animals and 15 microsatellite DNA markers in 384 animals of the 4 Nigerian sheep breeds to better understand genetic diversity for breeding management and germplasm conservation.ResultsMorphological traits of Uda and Balami were significantly (P < 0.05) higher than Yankasa, which were both higher than West African Dwarf (WAD) sheep. Stepwise discriminant analysis showed tail length, rump height, chest girth, ear length and chest depth as the most discriminating variables for classification. Mahalanobis distances show the least differentiation between Uda and Balami and the largest between WAD and Balami sheep. While 93.3% of WAD sheep were correctly assigned to their source genetic group, 63.9% of Yankasa, 61.2% of Balami and 45.2% of Uda were classified correctly by nearest neighbour discriminant analysis. The overall high Polymorphism Information Content (PIC) of all microsatellite markers ranged from 0.751 to 0.927 supporting their use in genetic characterization. Expected heterozygosity was high for all loci (0.783 to 0.93). Mean heterozygote deficiency across all populations (0.171 to 0.534) possibly indicate significant inbreeding (P < 0.05). Mean values for FST, FIT and FIS statistics across all loci were 0.088, 0.394 and 0.336 respectively. Yankasa and Balami are the most closely related breeds (DA = 0.184) while WAD and Balami are the farthest apart breeds (DA = 0.665), which is coincident with distance based on morphological analysis and population structure assessed by STRUCTURE.ConclusionsThese results suggest that within-breed genetic variation in Nigerian sheep is higher than between-breeds and may be a valuable tool for genetic improvement and conservation. The higher genetic variability in Yankasa suggests the presence of unique ancestral alleles reflecting the presence of certain functional genes which may result in better adaptability in more agro-ecological zones of Nigeria. These genetic characteristics are potentially useful in planning improvement and conservation strategies in Nigerian indigenous sheep.

Effects of oral continuous 17β-estradiol plus norethisterone acetate replacement therapy on abdominal subcutaneous fat, serum leptin levels and body composition

Aim. To evaluate the effects of oral continuous 17β-estradiol plus norethisterone acetate (E2/NETA) replacement therapy on abdominal subcutaneous fat, serum leptin level (SLL) and body composition in postmenopausal women. Materials and methods. A 6-month, prospective, randomized, double-blind and placebo-controlled study was conducted. Forty-three healthy naturally postmenopausal women aged 43–65 years were randomly assigned to receive E2/NETA (2 mg E2 plus 1 mg NETA, n = 22) or placebo (n = 21). Fasting SLL by enzyme-linked immunosorbent assay, subcutaneous abdominal fat thickness (STh) by ultrasound and the anthropometric indices of body weight (BW), body mass index (BMI), waist and hip circumference (WC, HC) and waist-to-hip ratio (WHR) were recorded at the beginning and the end of the study. Results. After 6 months of therapy, BW and SLL increased in the placebo group (p = 0.043 and 0.033, respectively). WC, HC and STh decreased significantly in the E2/NETA group (p = 0.002, 0.006 and 0.000, respectively) and they were also significantly lower in women receiving E2/NETA than in women taking placebo (p = 0.000, 0.034 and 0.000, respectively). At baseline, SLL and STh were positively correlated with all anthropometric indices except WHR. Conclusion. Oral continuous combined regimen of E2/NETA significantly reduced central fat accumulation as assessed by WC and STh, and attenuated the increase in SLL. The observed changes in SLL were highly and positively related to changes in STh. The oral continuous combined E2/NETA regimen appears to have protective effects on cardiovascular function and probably on metabolic diseases by its slimming effect upon WC in postmenopausal women.

Comparison of growth characteristics of chukar partridges (Alectoris chukar) raised in captivity.

Abstract Balcioğlu, M.S., Rizilkaya, K., Karabağ, K., Alkan, S., Yolcu, H.İ. and Şahin, E.2009. Comparison of growth characteristics of chukar partridges (Alectoris chukar) raised in captivity. J. Appl. Anim. Res., 35: 21–24. This study was carried out to estimate growth curve of chukar partridges and to compare the parameter estimates based on Gompertz, Bertalanffy and Logistic models. The growth curve functions were fitted to the observed data individually by using non-linear regression procedure with Marquart algorithm of SAS, NLIN procedure. Gompertz model (with highest determination coefficient and the lowest residual variance) was found to be the best to determine the growth pattern. Sex had significant effect on the estimates of parameter A and weight and age at inflection point within each model.

Genomic Prediction from Multiple-Trait Bayesian Regression Methods Using Mixture Priors

Bayesian multiple-regression methods incorporating different mixture priors for marker effects are used widely in genomic prediction. Improvement in prediction accuracies from using those methods, such as BayesB, BayesC, and BayesCπ, have been shown in single-trait analyses with both simulated and real data. These methods have been extended to multi-trait analyses, but only under the restrictive assumption that a locus simultaneously affects all the traits or none of them. This assumption is not biologically meaningful, especially in multi-trait analyses involving many traits. In this paper, we develop and implement a more general multi-trait BayesCΠ and BayesB methods allowing a broader range of mixture priors. Our methods allow a locus to affect any combination of traits, e.g., in a 5-trait analysis, the “restrictive” model only allows two situations, whereas ours allow all 32 situations. Further, we compare our methods to single-trait methods and the “restrictive” multi-trait formulation using real and simulated data. In the real data analysis, higher prediction accuracies were observed from both our new broad-based multi-trait methods and the “restrictive” formulation. The broad-based and restrictive multi-trait methods showed similar prediction accuracies. In the simulated data analysis, higher prediction accuracies to the “restrictive” method were observed from our general multi-trait methods for intermediate training population size. The software tool JWAS offers open-source routines to perform these analyses.

Multiple-trait Bayesian Regression Methods with Mixture Priors for Genomic Prediction

Bayesian multiple-regression methods incorporating different mixture priors for marker effects are widely used in genomic prediction. Improvement in prediction accuracies from using those methods, such as BayesB, BayesC and BayesCπ, have been shown in single-trait analyses with both simulated data and real data. These methods have been extended to multi-trait analyses, but only under a specific limited circumstance that assumes a locus affects all the traits or none of them. In this paper, we develop and implement the most general multi-trait BayesCΠ and BayesB methods allowing a broader range of mixture priors. Further, we compare them to single-trait methods and the “restricted” multi-trait formulation using real data. In those data analyses, significant higher prediction accuracies were sometimes observed from these new broad-based multi-trait Bayesian multiple-regression methods. The software tool JWAS offers routines to perform the analyses.