Ignite Creation Date:
2024-10-26 @ 3:41 PM
Last Modification Date:
2024-10-26 @ 3:41 PM
Study NCT ID:
NCT06618430
Status:
ACTIVE_NOT_RECRUITING
Last Update Posted:
None
First Post:
2024-09-23
Brief Title:
Evaluation Of DNA Methylation Pattern In Healthy Sarcopenic Obese And Sarcopenic Obese Older Women A Cross-Sectional Study
Sponsor:
None
Organization:
None
Study Overview
Official Title:
Evaluation Of DNA Methylation Pattern In Healthy Sarcopenic Obese And Sarcopenic Obese Older Women A Cross-Sectional Study
Status:
ACTIVE_NOT_RECRUITING
Status Verified Date:
2024-09
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
No
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
INTRODUCTION Sarcopenic obesity SO a functional and clinical condition is characterized by the coexistence of obesity marked by excess fat mass and sarcopenia characterized by reduced strength and muscle mass SO is associated with a greater risk of health-related adverse clinical outcomes than older adults with obesity and sarcopenia alone Aging is accompanied by numerous changes epigenetic These aging-associated epigenetic changes include DNA methylation histone modification chromatin remodeling non-coding RNA ncRNA regulation and RNA modification DNA methylation occurs at cytosines in CpG dinucleotides in the genome and undergoes changes with age in various human tissues Furthermore many genes can be hypermethylated or hypomethylated on CpG islands with the aging process Soon a broad exploration of candidate genes may provide insights into the pathogenesis of Sarcopenic obesity Therefore understanding how aging specifically sarcopenia obesity and Sarcopenic obesity is regulated by epigenetic factors favors the development of new treatment therapies Thus the objective will be to evaluate the epigenetic influence on sarcopenic obesity in older women METHODS This cross-sectional study will include 32 older women who will be classified as healthy with sarcopenia obesity and sarcopenic obesity living in the city of Ribeirão Preto - SP The older adults will perform total and regional body scan using iDXA anthropometric assessment functional capacity tests peripheral blood collection for analysis of biochemical markers and epigenetics For statistical analysis will be used t test ANOVA linear regression models and Pearson correlation Analyzes of the complete methylome will be performed using bioinformatics tools including specific software EXPECTED RESULTS It is expected that there will be differences in the patterns of methylation and gene expression in the diseases analyzed In addition it is expected to clarify how epigenetic changes occur throughout this process
Detailed Description:
The sample size was calculated a priori considering DNA methylation as the primary outcome on an exploratory basis The analyses were conducted using R software httpswwwr-projectorg For the calculation an effect size of 065 alpha 005 and statistical power of 080 were used Thus a total of 32 participants will be included in the study n 8 in each group The degree of methylation will be determined by measuring the amount of marker incorporated for each probe The image intensities will be extracted using the Illumina Genome Studio 20111 Methylation module 190 software The methylation score will be represented as a beta value β according to the fluorescence intensity ratio Beta values can assume any value between 0 unmethylated and 1 completely methylated Subsequently the image intensities will be extracted from the raw data IDATS using the Champ package for R Statistical Computing VIE Austria All genome-wide methylation data will be analyzed by t-test within groups followed by the Benjamini Hochberg test Pathway enrichment analysis will be performed using WEBGestalt and Reactome The normality of data distribution will be verified by the Shapiro Wilk test and descriptive statistics will consist of mean and standard deviation values ANOVA will be used to compare groups Pearson correlations will be used to assess the correlation of DNA methylation patterns with phenotypic variables Linear regression models will be applied to analyze the prediction of methylation pattern and selected variables The multinomial logistic regression model will be used in the groups for association with telomere length adjusted for BMI age ALST Statistical significance will be set at 5 and all analyses will be performed using the Statistical Package for Social Sciences software SPSS version 170 Inc Chicago IL
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None