Cell Specific eQTL Analysis without Sorting Cells

Harm-Jan Westra, Danny Arends, Tõnu Esko, Marjolein J Peters, Claudia Schurmann, Katharina Schramm, Johannes Kettunen, Hanieh Yaghootkar, Benjamin P Fairfax, Anand Kumar Andiappan, Yang Li, Jingyuan Fu, Juha Karjalainen, Mathieu Platteel, Marijn Visschedijk, Rinse K Weersma, Silva Kasela, Lili Milani, Liina Tserel, Pärt Peterson, Eva Reinmaa, Albert Hofman, André G Uitterlinden, Fernando Rivadeneira, Georg Homuth, Astrid Petersmann, Roberto Lorbeer, Holger Prokisch, Thomas Meitinger, Christian Herder, Michael Roden, Harald Grallert, Samuli Ripatti, Markus Perola, Andrew R Wood, David Melzer, Luigi Ferrucci, Andrew B Singleton, Dena G Hernandez, Julian C Knight, Rossella Melchiotti, Bernett Lee, Michael Poidinger, Francesca Zolezzi, Anis Larbi, De Yun Wang, Leonard H van den Berg, Jan H Veldink, Olaf Rotzschke, Seiko Makino, Veikko Salomaa, Konstantin Strauch, Uwe Völker, Joyce B J van Meurs, Andres Metspalu, Cisca Wijmenga, Ritsert C Jansen, Lude Franke

The functional consequences of trait associated SNPs are often investigated using expression quantitative trait locus (eQTL) mapping. While trait-associated variants may operate in a cell-type specific manner, eQTL datasets for such cell-types may not always be available. We performed a genome-environment interaction (GxE) meta-analysis on data from 5,683 samples to infer the cell type specificity of whole blood cis-eQTLs. We demonstrate that this method is able to predict neutrophil and lymphocyte specific cis-eQTLs and replicate these predictions in independent cell-type specific datasets. Finally, we show that SNPs associated with Crohn's disease preferentially affect gene expression within neutrophils, including the archetypal NOD2 locus.