High Consumption of Ultra-Processed Foods Is Associated with Genome-Wide DNA Methylation Differences in Women: A...

Background/Objectives: The global increase in the consumption of ultra-processed foods (UPFs) parallels the rise in obesity and non-communicable chronic diseases. Although several large-scale studies associate UPF intake with adverse health outcomes, the biological mechanisms remain unclear. Epigenetic alterations, such as changes in DNA methylation, may represent a potential pathway by which diet influences metabolic health. The aim of this study was to investigate whether higher UPF consumption is associated with genome-wide DNA methylation patterns in women. Methods: This was a cross-sectional observational study with exploratory epigenetic analysis. We selected 30 women, who were divided into tertiles based on their UPF consumption (expressed as a percentage of total energy intake) according to the NOVA food classification system. Dietary intake was assessed using a three-day food record. Anthropometric data, body composition and laboratory parameters were evaluated. The analysis of DNA methylation was performed utilizing DNA extracted from peripheral blood leukocytes of participants in the first and third tertiles of UPF consumption. Genome-wide methylation patterns were performed using next-generation sequencing. Results: Participants had a median (IQR) age of 31 years (26.0-36.5) and a BMI of 24.7 (23.6-35.8) kg/m². For the epigenetic analyses, 15 women were included. Of the 30 women initially evaluated, 20 were included as they belonged to the first and third tertile of UPF consumption. Of these, five were excluded due to a low number of reads obtained by NGS. A total of 80 differentially methylated regions were identified between groups, most of which were hypomethylated in the high-UPF-intake group. Conclusions: High UPF consumption was associated with altered DNA methylation patterns, suggesting a potential epigenetic mechanism underlying the negative health effects of UPFs. This pilot study provides a model for future research with larger samples.