Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits
Authors: Porcu Eleonora , Rüeger Sina , Lepik Kaido ,   eQTLGen Consortium, Agbessi Mawussé , Ahsan Habibul , Alves Isabel , Andiappan Anand , Arindrarto Wibowo , Awadalla Philip , Battle Alexis , Beutner Frank , Jan Bonder Marc , Boomsma Dorret , Christiansen Mark , Claringbould Annique , Deelen Patrick , Esko Tõnu , Favé Marie-Julie , Franke Lude , Frayling Timothy , Gharib Sina A. , Gibson Gregory , Heijmans Bastiaan T. , Hemani Gibran , Jansen Rick , Kähönen Mika , Kalnapenkis Anette , Kasela Silva , Kettunen Johannes , Kim Yungil , Kirsten Holger , Kovacs Peter , Krohn Knut , Kronberg-Guzman Jaanika , Kukushkina Viktorija , Lee Bernett , Lehtimäki Terho , Loeffler Markus , Marigorta Urko M. , Mei Hailang , Milani Lili , Montgomery Grant W. , Müller-Nurasyid Martina , Nauck Matthias , Nivard Michel , Penninx Brenda , Perola Markus , Pervjakova Natalia , Pierce Brandon L. , Powell Joseph , Prokisch Holger , Psaty Bruce M. , Raitakari Olli T. , Ripatti Samuli , Rotzschke Olaf , Saha Ashis , Scholz Markus , Schramm Katharina , Seppälä Ilkka , Slagboom Eline P. , Stehouwer Coen D. A. , Stumvoll Michael , Sullivan Patrick , ‘t Hoen Peter A. C. , Teumer Alexander , Thiery Joachim , Tong Lin , Tönjes Anke , van Dongen Jenny , van Iterson Maarten , van Meurs Joyce , Veldink Jan H. , Verlouw Joost , Visscher Peter M. , Völker Uwe , Võsa Urmo , Westra Harm-Jan , Wijmenga Cisca , Yaghootkar Hanieh , Yang Jian , Zeng Biao , Zhang Futao ,   BIOS Consortium, Arindrarto Wibowo , Beekman Marian , Boomsma Dorret I. , Bot Jan , Deelen Joris , Deelen Patrick , Franke Lude , Heijmans Bastiaan T. , ’t Hoen Peter A. C. , Hofman Bert A. , Hottenga Jouke J. , Isaacs Aaron , Bonder Marc Jan , Jhamai P. Mila , Jansen Rick , Kielbasa Szymon M. , Lakenberg Nico , Luijk René , Mei Hailiang , Moed Matthijs , Nooren Irene , Pool René , Schalkwijk Casper G. , Slagboom P. Eline , Stehouwer Coen D. A. , Suchiman H. Eka D. , Swertz Morris A. , Tigchelaar Ettje F. , Uitterlinden André G. , van den Berg Leonard H. , van der Breggen Ruud , van der Kallen Carla J. H. , van Dijk Freerk , van Dongen Jenny , van Duijn Cornelia M. , van Galen Michiel , van Greevenbroek Marleen M. J. , van Heemst Diana , van Iterson Maarten , van Meurs Joyce , van Rooij Jeroen , van’t Hof Peter , van Zwet Erik. W. , Vermaat Martijn , Veldink Jan H. , Verbiest Michael , Verkerk Marijn , Wijmenga Cisca , Zhernakova Dasha V. , Zhernakova Sasha , Santoni Federico A. , Reymond Alexandre , Kutalik Zoltán 
Published: July 2019

AbstractGenome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, but their biological interpretation often remains unclear. Most of these variants overlap with expression QTLs, indicating their potential involvement in regulation of gene expression. Here, we propose a transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) that uses multiple SNPs as instruments and multiple gene expression traits as exposures, simultaneously. Applied to 43 human phenotypes, it uncovers 3,913 putatively causal gene–trait associations, 36% of which have no genome-wide significant SNP nearby in previous GWAS. Using independent association summary statistics, we find that the majority of these loci were missed by GWAS due to power issues. Noteworthy among these links is educational attainment-associated BSCL2, known to carry mutations leading to a Mendelian form of encephalopathy. We also find pleiotropic causal effects suggestive of mechanistic connections. TWMR better accounts for pleiotropy and has the potential to identify biological mechanisms underlying complex traits.