Ryan C. Smith

The paper shows that blood DNA methylation can predict gene expression based on regulatory mode and enhancer architecture, with lineage genes being more predictable than stimulus-responsive genes.

This study uses BEWAS to identify DNA methylation changes in brain-enriched genes after ketamine and MDMA treatment, revealing shared epigenetic mechanisms linked to neuroplasticity.

The paper examines age-related DNA methylation changes in IL-11 and IL-11RA genes, finding inverse U-shaped patterns that suggest non-linear regulation of IL-11 expression and sensitivity across life stages.

The paper develops EpiVision, a panel of 21 epigenetic predictors linking skin DNA methylation to facial aging traits, revealing shared and trait-specific biological pathways.

The paper identifies age-associated Th2-like CD8 memory T cells in human blood and links their accumulation to health conditions like asthma and diabetes.

The paper identifies non-linear DNA methylation patterns with aging, showing peaks or troughs in middle age and linking them to disease onset.

This study evaluates a natural ingredients intervention's impact on DNA methylation, showing reduced biological age and improved health metrics in participants over 12 months.

The paper develops a custom Infinium DNA methylation array for the human imprintome and validates its performance against WGBS and EPIC arrays.

The paper develops OMICmAge, a multi-omics biomarker of biological age, and shows it outperforms existing markers in predicting chronic diseases and mortality.

This paper uses DNA methylation data to analyze immune cell fractions across 25,629 blood samples, identifying associations with age, sex, health outcomes, and lifestyle factors.

This study compares DNA methylation and mRNA responses to lower- versus higher-load resistance exercise in trained men, finding similar gene expression and methylation patterns despite differences in exercise intensity.