Unraveling the polygenic architecture of complex traits using blood eQTL meta-analysis

Vosa, U.; Claringbould, A.; Westra, H.-J.; Bonder, M. J.; Deelen, P.; Zeng, B.; Kirsten, H.; Saha, A.; Kreuzhuber, R.; Kasela, S.; Pervjakova, N.; Alvaes, I.; Fave, M.-J.; Agbessi, M.; Christiansen, M.; Jansen, R.; Seppälä, I.; Tong, L.; Teumer, A.; Schramm, K.; Hemani, G.; Verlouw, J.; Yaghootkar, H.; Sönmez, R.; Andrew, A. A.; Kukushkina, V.; Kalnapenkis, A.; Rüeger, S.; Porcu, E.; Kronberg-Guzman, J.; Kettunen, J.; Powell, J.; Lee, B.; Zhang, F.; Arindrarto, W.; Beutner, F.; BIOS Consortium,; Brugge, H.; i2QTL Consortium,; Dmitrieva, J.; Elansary, M.; Fairfax, B. P.; Georges, M.; He

doi:10.1101/447367

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bioRxiv · 10.1101/447367

Unraveling the polygenic architecture of complex traits using blood eQTL meta-analysis

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Abstract

SummaryWhile many disease-associated variants have been identified through genome-wide association studies, their downstream molecular consequences remain unclear.\n\nTo identify these effects, we performed cis- and trans-expression quantitative trait locus (eQTL) analysis in blood from 31,684 individuals through the eQTLGen Consortium.\n\nWe observed that cis-eQTLs can be detected for 88% of the studied genes, but that they have a different genetic architecture compared to disease-associated variants, limiting our ability to use cis-eQTLs to pinpoint causal genes within susceptibility loci.\n\nIn contrast, trans-eQTLs (detected for 37% of 10,317 studied trait-associated variants) were more informative. Multiple unlinked variants, associated to the same complex trait, often converged on trans-genes that are known to play central roles in disease etiology.\n\nWe observed the same when ascertaining the effect of polygenic scores calculated for 1,263 genome-wide association study (GWAS) traits. Expression levels of 13% of the studied genes correlated with polygenic scores, and many resulting genes are known to drive these traits.

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Vosa, U., Claringbould, A., Westra, H.-J., Bonder, M. J., Deelen, P., Zeng, B., Kirsten, H., Saha, A., Kreuzhuber, R., Kasela, S., Pervjakova, N., Alvaes, I., Fave, M.-J., Agbessi, M., Christiansen, M., Jansen, R., Seppälä, I., Tong, L., Teumer, A., Schramm, K., Hemani, G., Verlouw, J., Yaghootkar, H., Sönmez, R., Andrew, A. A., Kukushkina, V., Kalnapenkis, A., Rüeger, S., Porcu, E., Kronberg-Guzman, J., Kettunen, J., Powell, J., Lee, B., Zhang, F., Arindrarto, W., Beutner, F., BIOS Consortium,, Brugge, H., i2QTL Consortium,, Dmitrieva, J., Elansary, M., Fairfax, B. P., Georges, M., He. 2018-10-19. Unraveling the polygenic architecture of complex traits using blood eQTL meta-analysis. https://doi.org/10.1101/447367

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