Differential Association of Glycation Products with Bone Mineral Density and Fat Mass in Healthy and Diabetes Type 2 Subjects from Mexican Southeastern: A Cross Sectional Study.

Background: Glycation products have been linked to decreased bone mineral density (BMD) in a number of clinical settings. This study examined the correlation between early glycation products (HbA1c and glycated albumin (ALB-g)) and advanced glycation end products (pentosidine (PTD)) with BMD in two groups of participants: those with type 2 diabetes mellitus (DM2) and those without diabetes or any other comorbidities (noDM). All of the participants had resided in southeastern Mexico for a minimum of 10 years. Material and Methods: This study included 204 participants: 112 (55%) with DM2 and 92 (45%) healthy subjects. We utilized dual X-ray absorptiometry (DXA) to measure both the total and segment-specific BMD and adipose mass. In addition, the fasting blood glucose, HbA1c, PTD, and ALB-g parameters were measured. Correlation and logistic regression analyses were conducted. Results: There was an inverse correlation between PTD and BMD in all anatomical regions among postmenopausal women (PMW) in the DM2 group, whereas in non-PMW, only the waist-to-height ratio was statistically significant. A negative correlation was observed between HbA1c levels and BMD in the arms and legs of DM2 individuals. However, in the noDM group, a negative correlation was found between HbA1c levels and BMD in the pelvis, while a positive association was observed between HbA1c and indicators of adipose tissue. ALB-g, demonstrated a negative correlation with fat mass. After performing binary logistic regressions, the following odds ratios (OR) for osteopenia/osteoporosis risk were determined: PTD OR 1.1 (p = 0.047) for DM2 PMW, HbA1c OR 1.4 (p = 0.048), and fat mass content OR 1.011 (p = 0.023) for the entire sample. Conclusions: Glycation products are associated with BMD differentially depending on the analyzed anatomical segment, but PTD, HbA1c, and fat mass are significant predictors of low bone mass. In prospective studies, this association could be determined using other techniques involving three-dimensional analysis of bone architecture to evaluate bone architecture.

Smoking index, lifestyle factors, and genomic instability assessed by single-cell gel electrophoresis: a cross-sectional study in subjects from Yucatan, Mexico.

BACKGROUND: It is widely accepted that genomic instability is associated with several mechanisms involving oxidative stress, which can increase the rate of DNA breaks. Such factors include smoking, impairments in body composition, an unhealthy lifestyle, and a hereditary history of cancer. The aim was to evaluate the degree of association of genomic instability in smokers and non-smokers, and how the risk could change depending on the lifestyle and other causes. For this purpose, a survey of tobacco consumption, dietary patterns, physical activity, antecedents of cancer, and body composition assessment was carried out. Genomic instability was evaluated through a single-cell gel electrophoresis using peripheral blood mononuclear cells in three different conditions of oxidative stress. The analysis of genomic damage degree was performed through a dimension reduction procedure (principal component analysis) from 16 parameters per treatment (adding up 48 parameters of genomic damage per subject) and a binary logistic regression model for DNA fragmentation risk. RESULTS: The sample consisted of 82 participants, divided into three age groups: young adults (18-35 years), adults (36-59 years), and older adults (60-95 years). As expected, the results showed a significant positive correlation of age with genomic damage rates, represented by 2 PCA groups (p = 0.027, p = 0.004). There were consistent significant positive associations of genomic damage rates with smoking index and three PCA groups (p = 0.007, p = 0.004, p = 0.009). The smoking status and age group analysis revealed that there were significant differences for adult smokers with the same aforementioned PCA groups (p = 0.002, p = 0.001, p = 0.010). In addition, higher DNA damage rates were found in subjects with incorrect diet patterns, long sitting hours, and previous exposure to radiation. The analysis with binary logistic regression displayed two models in which lifestyles (age, diet, and/or sedentarism) did not change the significance of smoking index for DNA fragmentation risk; however, when physical activity was present in the model, the smoking index was not a significant factor for DNA damage risk. CONCLUSIONS: Although it is well known that smoking affects human health in different ways, DNA fragmentation can be analyzed by a damage phenotypic analysis and integrate a risk analysis reshaped by diet and lifestyle in general.