Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits
Porcu, Eleonora; Rueger, Sina; Lepik, Kaido; Agbessi, Mawusse; Ahsan, Habibul; Alves, Isabel; Andiappan, Anand; Arindrarto, Wibowo; Awadalla, Philip; Battle, Alexis; Beutner, Frank; Bonder, Marc Jan; Boomsma, Dorret; Christiansen, Mark; Claringbould, Annique; Deelen, Patrick; Esko, Tonu; Fave, Marie-Julie; Franke, Lude; Frayling, Timothy; Gharib, Sina A.; Gibson, Gregory; Heijmans, Bastiaan T.; Hemani, Gibran; Jansen, Rick; Kahonen, Mika; Kalnapenkis, Anette; Kasela, Silva; Kettunen, Johannes; Kim, Yungil; Kirsten, Holger; Kovacs, Peter; Krohn, Knut; Kronberg-Guzman, Jaanika; Kukushkina, Viktorija; Lee, Bernett; Lehtimaki, Terho; Loeffler, Markus; Marigorta, Urko M.; Mei, Hailang; Milani, Lili; Montgomery, Grant W.; Mueler-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; Seppala, Ilkka; Slagboom, Eline P.; Stehouwer, Coen D. A.; Stumvoll, Michael; Sullivan, Patrick; Teumer, Alexander; Thiery, Joachim; Tong, Lin; Tonjes, Anke; van Dongen, Jenny; van Iterson, Maarten; van Meurs, Joyce; Veldink, Jan H.; Verlouw, Joost; Visscher, Peter M.; Volker, Uwe; Vosa, Urmo; Westra, Harm-Jan; Wijmenga, Cisca; Yaghootkar, Hanieh; Yang, Jian; Zeng, Biao; Zhang, Futao; Arindrarto, Wibowo; Beekman, Marian; Boomsma, Dorret I.; Bot, Jan; Deelen, Joris; Deelen, Patrick; Franke, Lude; Heijmans, Bastiaan T.; Hofman, Bert A.; Hottenga, Jouke J.; Isaacs, Aaron; Bonder, Marc Jan; Jhamai, P. Mila; Jansen, Rick; Kielbasa, Szymon M.; Lakenberg, Nico; Luijk, Rene; Mei, Hailiang; Moed, Matthijs; Nooren, Irene; Pool, Rene; Schalkwijk, Casper G.; Slagboom, P. Eline; Stehouwer, Coen D. A.; Suchiman, H. Eka D.; Swertz, Morris A.; Tigchelaar, Ettje F.; Uitterlinden, Andre 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, Zoltan (2019-07-24)
Porcu, E., Rüeger, S., Lepik, K. et al. Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits. Nat Commun 10, 3300 (2019). https://doi.org/10.1038/s41467-019-10936-0
© The Author(s) 2019. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
https://creativecommons.org/licenses/by/4.0/
https://urn.fi/URN:NBN:fi-fe202003117859
Tiivistelmä
Abstract
Genome-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.
Kokoelmat
- Avoin saatavuus [34343]
