PLoS ONE (Jan 2024)

The race-based stress reduction intervention (RiSE) study on African American women in NYC and Chicago: Design and methods for complex genomic analysis.

  • Jacquelyn Y Taylor,
  • Alexandria Jones-Patten,
  • Laura Prescott,
  • Stephanie Potts-Thompson,
  • Cara Joyce,
  • Bamidele Tayo,
  • Karen Saban

DOI
https://doi.org/10.1371/journal.pone.0295293
Journal volume & issue
Vol. 19, no. 4
p. e0295293

Abstract

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RiSE study aims to evaluate a race-based stress-reduction intervention as an effective strategy to improve coping and decrease stress-related symptoms, inflammatory burden, and modify DNA methylation of stress response-related genes in older AA women. This article will describe genomic analytic methods to be utilized in this longitudinal, randomized clinical trial of older adult AA women in Chicago and NYC that examines the effect of the RiSE intervention on DNAm pre- and post-intervention, and its overall influence on inflammatory burden. Salivary DNAm will be measured at baseline and 6 months following the intervention, using the Oragene-DNA kit. Measures of perceived stress, depressive symptoms, fatigue, sleep, inflammatory burden, and coping strategies will be assessed at 4 time points including at baseline, 4 weeks, 8 weeks, and 6 months. Genomic data analysis will include the use of pre-processed and quality-controlled methylation data expressed as beta (β) values. Association analyses will be performed to detect differentially methylated sites on the targeted candidate genes between the intervention and non-intervention groups using the Δβ (changes in methylation) with adjustment for age, health behaviors, early life adversity, hybridization batch, and top principal components of the probes as covariates. To account for multiple testing, we will use FDR adjustment with a corrected p-value of <0.05 regarded as statistically significant. To assess the relationship between inflammatory burden and Δβ among the study samples, we will repeat association analyses with the inclusion of individual inflammation protein measures. ANCOVA will be used because it is more statistically powerful to detect differences.