Introduction: The decrease in lean mass is directly related to the loss of independence, muscle strength, and worse quality of life over the years. Although the genetic determinants of muscle mass were well recognized, recent literature has been uncovering new epigenetic factors affecting the state of muscular tissue. This study aimed to verify differences in the DNA methylation profile among Brazilian postmenopausal women aged 50–70 years according to the lean mass evaluation.Methods: A cross-sectional study comprised 40 women aged 50–70 years. After K-means cluster analysis the 40 participants were divided into two groups, the Lower Lean Mass group with 20 participants (61.1 ± 4.6 years) and the Higher Lean Mass group with 20 participants (60.7 ± 3.2 years). Lean mass was measured by dual-energy X-ray emission densitometry (DEXA). The participants' DNA was extracted using the Salting Out technique and subsequently, the Illumina 850k EPIC Infinium Methylation BeadChip was performed to obtain methylation data.Results: We obtained 1,913 differentially methylated sites (p ≤ 0.005 of β > 5% and β < −5%) in a total of 979 genes between groups (p ≤ 0.005; −5% > β > 5%). In addition, the PI3K-Akt pathway had the greatest power of significance with an FDR of 4.6 × 10–3.Conclusion: Our results demonstrate a differentiation between specific sites of different genes, which have essential functions in body composition and energy metabolism, supporting future studies that aim to relate lean mass with epigenetics.
People living with HIV (PWH) experience an accelerated reduction in bone mineral content (BMC), and a high risk of osteopenia and osteoporosis. Anthropometry is an accurate and low-cost method that can be used to monitor changes in body composition in PWH. To date, no studies have used anthropometry to estimate BMC in PWH. To propose and validate sex-specific anthropometric models to predict BMC in PWH. This cross-sectional study enrolled 104 PWH (64 males) aged >18 years at a local university hospital. BMC was measured using dual energy X-ray absorptiometry (DXA). Anthropometric measures were collected. We used linear regression analysis to generate the models. Cross-validations were conducted using the “leave one out”, from the predicted residual error sum of squares (PRESS) method. Bland–Altman plots were used to explore distributions of errors. We proposed models with high coefficient of determination and reduced standard error of estimate for males (r2 = 0.70; SEE = 199.97 g; Q2PRESS = 0.67; SEEPRESS = 208.65 g) and females (r2 = 0.65; SEE = 220.96 g; Q2PRESS = 0.62; SEEPRESS = 221.90 g). Our anthropometric predictive models for BMC are valid, practical, and a low-cost alternative to monitoring bone health in PWH.
The increase in lean mass is directly related to the loss of independence, muscle strength, and worse quality of life over the years. Studies in epigenetics can provide accurate answers about lean mass, demonstrating changes in DNA methylation patterns and possible changes in gene expression. The objective of this study was to verify whether there is a difference in the methylation profile among Brazilian women aged 50 to 70 years with greater or lesser lean mass. A cross-sectional study comprised 22 women aged 50 to 70 years, with 2 groups of 11 participants (Low Lean Mass and More Lean Mass). Lean mass was measured by dual-energy X-ray emission densitometry (DEXA). Blood DNA was collected for methylation assays using the Illumina 850k EPIC Infinium Methylation BeadChip, analyzing data from the Bioconductor chAMP data package medium in RStudio software. We obtained 1,913 differentially methylated (p ≤ 0.005 of delta β > 5% and delta β < -5 %) with a total of 979 genes with different methylation sites between groups (p ≤ 0.005; -5% > delta β > 5%). In addition, the pathway with the greatest power of significance was PI3K-Akt, presenting an FDR of 4.6 x 10-3. Thus, our results demonstrate a differentiation between specific sites of different genes, which have essential functions in body composition and energy metabolism, supporting future studies that aim to relate lean mass with epigenetics.
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