Marc Jan Bonder

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 characterizes proteome variation across 202 human iPSC lines, identifies 700 pQTLs, and links pQTLs to disease-associated GWAS variants.

This paper identifies DNA methylation sites associated with aggression through a meta-analysis of epigenome-wide studies across different age groups and tissues.

The paper examines how structural variants and short tandem repeats affect gene expression and complex traits, identifying high-impact variants associated with multiple genes and GWAS traits.

The paper discovers and genotypes a comprehensive set of structural variants and short tandem repeats using multiple algorithms and replicates, creating a well-characterized map of these variants.

The paper uses single-cell RNA-seq of differentiating iPS cells from 125 donors to identify expression quantitative trait loci influencing gene expression during endoderm differentiation.

This study systematically analyzes the MHC region to uncover genetic associations between HLA types, gene expression, and disease, revealing novel insights into disease mechanisms.

This study shows that ageing increases transcriptional heterogeneity and DNA methylation drift in muscle stem cells, disrupting transcriptional networks and stem cell function.

The paper screens for genes affecting epigenetic age acceleration in humans and identifies NSD1 as a key regulator of the epigenetic ageing clock.

This paper introduces TWMR, a Mendelian Randomization method that identifies gene-trait associations by integrating GWAS and eQTL data, revealing 3,913 novel associations across 43 human phenotypes.

The paper uses single-cell profiling of expression and DNA methylation to study splicing regulation and heterogeneity in human induced pluripotent stem cells.

Cardelino integrates whole exomes and single-cell transcriptomes to identify clone-of-origin and reveal phenotypic impacts of somatic variants in human fibroblasts.

This paper introduces StructLMM, a linear mixed model for analyzing multivariate gene-environment interactions, demonstrating its effectiveness in detecting GxE signals in BMI and eQTL data.

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

This study identifies 139 common and 4 rare genetic variants associated with type 2 diabetes through GWAS and integrates gene expression and epigenomic data to highlight potential functional genes and regulatory mechanisms.

The paper identifies gene targets for brain-related traits using transcriptomic and methylomic data from blood, finding strong correlations between genetic effects in brain and blood tissues.

The paper develops a DNA methylation age predictor for mice, showing it accurately measures biological age and responds to interventions like ovariectomy and diet.

This study investigates the association between CpG methylation and educational attainment, finding limited significant associations that may be influenced by confounding factors.

The paper identifies trans-meQTLs linking disease variants to methylation changes at transcription factor binding sites, revealing eight-fold more downstream effects than trans-eQTLs.

The paper identifies context-dependent eQTLs in peripheral blood RNA-seq data from Dutch individuals using a hypothesis-free approach, revealing gene expression influenced by cell type and signaling pathways.

The paper identifies genetic variants affecting gene expression using genotypes derived from public RNA-seq data, finding cis-eQTLs for 8,034 genes and strong ASE effects for 34 rare pathogenic variants.