Biology subjects

van Zwet, E. W.

Publications and source records attributed to van Zwet, E. W..

4 recordsLinked to original sources

bioRxiv2024

Oleic acid triggers CD4+ T cells to be metabolically rewired and poised to differentiate into proinflammatory T cell subsets upon activation

T cells are the most common immune cells in atherosclerotic plaques and the function of T cells can be altered by fatty acids. Here, we show that pre-exposure of CD4+ T cells to oleic acid, an abundant fatty acid linked to cardiovascular events, results in a preferential differentiation into pro-inflammatory subsets upon activation by upregulating core metabolic pathways. RNA-sequencing of non-activated CD4+ T cells revealed that oleic acid upregulates genes encoding enzymes responsible for cholesterol and fatty acid biosynthesis. Transcription footprint analysis linked this rewiring to the differentiation of pro-inflammatory subsets. Indeed, spectral flow cytometry showed that pre-exposure to oleic acid results in a skew toward IL-9, IL-17A, IL-5 and IL-13 producing T cells upon activation. Importantly, inhibition of either cholesterol or fatty acid biosynthesis abolishes this effect, suggesting a beneficial role for statins beyond cholesterol lowering. Taken together, fatty acids may affect inflammatory diseases by influencing T cell metabolism.

genomics↗

bioRxiv2019

Genome-wide identification of genes regulating DNA methylation using genetic anchors for causal inference

DNA methylation is a key epigenetic modification in human development and disease, yet there is limited understanding of its highly coordinated regulation. Here, we identified 818 genes that influence DNA methylation patterns in blood using large-scale population genomics data. By employing genetic instruments as causal anchors, we identified directed associations between gene expression and distant DNA methylation levels, whilst ensuring specificity of the associations by correcting for linkage disequilibrium and pleiotropy among neighboring genes. We found that DNA methylation patterns are commonly shaped by transcription factors that consistently increase or decrease DNA methylation levels. However, we also observed genes encoding proteins without DNA binding activity with widespread effects on DNA methylation (e.g. NFKBIE, CDCA7(L) and NLRC5) and we suggest plausible mechanisms underlying these findings. Many of the reported genes were unknown to influence DNA methylation, resulting in a comprehensive resource providing insights in the principles underlying epigenetic regulation.

genomics↗

bioRxiv2018

Why mediation analysis trumps Mendelian randomization in population epigenomics studies of the Dutch Famine

Our recent analysis of genome-wide DNA methylation data in men and women exposed to the Dutch Famine met passionate criticism by several researchers active on Twitter. It also prompted a more reasoned letter by Richmond and colleagues. At the core of the debate is the proper interpretation of findings from a mediation analysis. We used this method to identify specific DNA methylation changes that statistically provide a link between prenatal exposure to famine and adult metabolic traits. Our critics first argue that our results do not suggest mediation but reverse-causation, where famine-induced metabolic traits drive changes in DNA methylation. We rebut this scenario in a simulation study showing that our test of mediation was unlikely to become statistically significant in the case of reverse-causation. Some critics then argue that Mendelian randomization provides the sole path to correct inference. This belief misses a crucial point: DNA methylation, especially when measured in peripheral blood, is not likely to be a causal mediator from a biological point of view. It could however be a proxy of epigenetic regulation changes in specific tissues, for example at the level of transcription factor binding. If so, a Mendelian randomization approach using genetic variants affecting local DNA methylation in blood will be disconnected from the underlying biological mechanism and is bound to yield false-negative results. Our new simulation studies strengthen the original reasoning that the relationship between prenatal famine and metabolic traits is statistically mediated by specific DNA methylation changes while the specific molecular mechanism awaits elucidation.

genomics↗

bioRxiv2017

Genome-wide identification of directed gene networks using large-scale population genomics data

Identification of causal drivers behind regulatory gene networks is crucial in understanding gene function. We developed a method for the large-scale inference of gene-gene interactions in observational population genomics data that are both directed (using local genetic instruments as causal anchors, akin to Mendelian Randomization) and specific (by controlling for linkage disequilibrium and pleiotropy). The analysis of genotype and whole-blood RNA-sequencing data from 3,072 individuals identified 49 genes as drivers of downstream transcriptional changes (P < 7 x 10-10), among which transcription factors were overrepresented (P = 3.3 x 10-7). Our analysis suggests new gene functions and targets including for SENP7 (zinc-finger genes involved in retroviral repression) and BCL2A1 (novel target genes possibly involved in auditory dysfunction). Our work highlights the utility of population genomics data in deriving directed gene expression networks. A resource of trans-effects for all 6,600 genes with a genetic instrument can be explored individually using a web-based browser.

genomics↗