Peter 't Hoen, Lude Franke, Bastiaan Heijmans and colleagues present a combined analysis of methylome and transcriptome data from a large collection of whole-blood samples to infer the downstream effects of disease-associated variants. They identify a large number of trait-associated SNPs influencing methylation of CpG sites in trans, providing insights into the downstream functional effects of many disease-associated variants. Most disease-associated genetic variants are noncoding, making it challenging to design experiments to understand their functional consequences1,2. Identification of expression quantitative trait loci (eQTLs) has been a powerful approach to infer the downstream effects of disease-associated variants, but most of these variants remain unexplained3,4. The analysis of DNA methylation, a key component of the epigenome5,6, offers highly complementary data on the regulatory potential of genomic regions7,8. Here we show that disease-associated variants have widespread effects on DNA methylation in trans that likely reflect differential occupancy of trans binding sites by cis-regulated transcription factors. Using multiple omics data sets from 3,841 Dutch individuals, we identified 1,907 established trait-associated SNPs that affect the methylation levels of 10,141 different CpG sites in trans (false discovery rate (FDR) < 0.05). These included SNPs that affect both the expression of a nearby transcription factor (such as NFKB1, CTCF and NKX2-3) and methylation of its respective binding site across the genome. Trans methylation QTLs effectively expose the downstream effects of disease-associated variants.