Erik W. van Zwet

The paper investigates how blood cell counts influence epigenetic age metrics, finding strong links with DNAmAge but weaker associations with AgeAccel, particularly for neutrophils in second-generation clocks.

The paper develops interpretable neural networks for multi-omics data to predict smoking status, age, and LDL levels, showing improved performance and generalizability across cohorts.

This study shows that oleic acid pre-exposure rewires CD4+ T cell metabolism, promoting pro-inflammatory differentiation upon activation.

The paper identifies age-related increases in DNA methylation variability on the inactive X chromosome in females and males, with aVMCs accumulating in XCI regions and showing replication in purified cell types.

The paper identifies 818 genes influencing DNA methylation in blood using genetic anchors and causal inference, revealing both transcription factors and non-DNA-binding proteins with regulatory roles.

The paper identifies 49 gene drivers of downstream transcriptional changes using population genomics data and RNA-sequencing from 3,072 individuals.

The paper argues that mediation analysis is more appropriate than Mendelian randomization for studying the link between prenatal famine exposure and adult metabolic traits via DNA methylation.

This paper develops a method to control bias and inflation in epigenome- and transcriptome-wide association studies using an empirical null distribution estimated via Bayesian statistics, showing improved power and false positive rate control.