TY - JOUR T1 - Disease variants alter transcription factor levels and methylation of their binding sites JF - bioRxiv DO - 10.1101/033084 SP - 033084 AU - Marc Jan Bonder AU - René Luijk AU - Daria V. Zhernakova AU - Matthijs Moed AU - Patrick Deelen AU - Martijn Vermaat AU - Maarten van Iterson AU - Freerk van Dijk AU - Michiel van Galen AU - Jan Bot AU - Roderick C. Slieker AU - P. Mila Jhamai AU - Michael Verbiest AU - H. Eka D. Suchiman AU - Marijn Verkerk AU - Ruud van der Breggen AU - Jeroen van Rooij AU - Nico Lakenberg AU - Wibowo Arindrarto AU - Szymon M. Kielbasa AU - Iris Jonkers AU - Peter van ’t Hof AU - Irene Nooren AU - Marian Beekman AU - Joris Deelen AU - Diana van Heemst AU - Alexandra Zhernakova AU - Ettje F. Tigchelaar AU - Morris A. Swertz AU - Albert Hofman AU - André G. Uitterlinden AU - René Pool AU - Jenny van Dongen AU - Jouke J. Hottenga AU - Coen D.A. Stehouwer AU - Carla J.H. van der Kallen AU - Casper G. Schalkwijk AU - Leonard H. van den Berg AU - Erik. W van Zwet AU - Hailiang Mei AU - Yang Li AU - Mathieu Lemire AU - Thomas J. Hudson AU - the BIOS Consortium AU - P. Eline Slagboom AU - Cisca Wijmenga AU - Jan H. Veldink AU - Marleen M.J. van Greevenbroek AU - Cornelia M. van Duijn AU - Dorret I. Boomsma AU - Aaron Isaacs AU - Rick Jansen AU - Joyce B.J. van Meurs AU - Peter A.C. ’t Hoen AU - Lude Franke AU - Bastiaan T. Heijmans Y1 - 2015/01/01 UR - http://biorxiv.org/content/early/2015/12/01/033084.1.abstract N2 - Most disease associated genetic risk factors are non-coding, 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 downstream effects of disease variants but the large majority remains unexplained.3,4. The analysis of DNA methylation, a key component of the epigenome5, offers highly complementary data on the regulatory potential of genomic regions6,7. However, a large-scale, combined analysis of methylome and transcriptome data to infer downstream effects of disease variants is lacking. Here, we show that disease variants have wide-spread effects on DNA methylation in trans that likely reflect the downstream effects on binding sites of cis-regulated transcription factors. Using data on 3,841 Dutch samples, we detected 272,037 independent cis-meQTLs (FDR < 0.05) and identified 1,907 trait-associated SNPs that affect methylation levels of 10,141 different CpG sites in trans (FDR < 0.05), an eight-fold increase in the number of downstream effects that was known from trans-eQTL studies3,8,9. Trans-meQTL CpG sites are enriched for active regulatory regions, being correlated with gene expression and overlap with Hi-C determined interchromosomal contacts10,11. We detected many trans-meQTL SNPs that affect expression levels of nearby transcription factors (including NFKB1, CTCF and NKX2–3), while the corresponding trans-meQTL CpG sites frequently coincide with its respective binding site. Trans-meQTL mapping therefore provides a strategy for identifying and better understanding downstream functional effects of many disease-associated variants. ER -