Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits.

Détails

Ressource 1Télécharger: BIB_5BC4DEF5ED27.pdf (986.41 [Ko])
Etat: Public
Version: Final published version
Licence: CC BY 4.0
ID Serval
serval:BIB_5BC4DEF5ED27
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits.
Périodique
Nature communications
Auteur(s)
Porcu E., Rüeger S., Lepik K., Santoni F.A., Reymond A., Kutalik Z.
Collaborateur(s)
eQTLGen Consortium, BIOS Consortium
Contributeur(s)
Agbessi M., Ahsan H., Alves I., Andiappan A., Arindrarto W., Awadalla P., Battle A., Beutner F., Jan Bonder M., Boomsma D., Christiansen M., Claringbould A., Deelen P., Esko T., Favé M.J., Franke L., Frayling T., Gharib S.A., Gibson G., Heijmans B.T., Hemani G., Jansen R., Kähönen M., Kalnapenkis A., Kasela S., Kettunen J., Kim Y., Kirsten H., Kovacs P., Krohn K., Kronberg-Guzman J., Kukushkina V., Lee B., Lehtimäki T., Loeffler M., Marigorta U.M., Mei H., Milani L., Montgomery G.W., Müller-Nurasyid M., Nauck M., Nivard M., Penninx B., Perola M., Pervjakova N., Pierce B.L., Powell J., Prokisch H., Psaty B.M., Raitakari O.T., Ripatti S., Rotzschke O., Saha A., Scholz M., Schramm K., Seppälä I., Slagboom E.P., Stehouwer CDA, Stumvoll M., Sullivan P., 't Hoen PAC, Teumer A., Thiery J., Tong L., Tönjes A., van Dongen J., van Iterson M., van Meurs J., Veldink J.H., Verlouw J., Visscher P.M., Völker U., Võsa U., Westra H.J., Wijmenga C., Yaghootkar H., Yang J., Zeng B., Zhang F., Arindrarto W., Beekman M., Boomsma D.I., Bot J., Deelen J., Deelen P., Franke L., Heijmans B.T., 't Hoen PAC, Hofman B.A., Hottenga J.J., Isaacs A., Bonder M.J., Jhamai P.M., Jansen R., Kielbasa S.M., Lakenberg N., Luijk R., Mei H., Moed M., Nooren I., Pool R., Schalkwijk C.G., Slagboom P.E., Stehouwer CDA, Suchiman HED, Swertz M.A., Tigchelaar E.F., Uitterlinden A.G., van den Berg L.H., van der Breggen R., van der Kallen CJH, van Dijk F., van Dongen J., van Duijn C.M., van Galen M., van Greevenbroek MMJ, van Heemst D., van Iterson M., van Meurs J., van Rooij J., Van't Hof P., van Zwet E.W., Vermaat M., Veldink J.H., Verbiest M., Verkerk M., Wijmenga C., Zhernakova D.V., Zhernakova S.
ISSN
2041-1723 (Electronic)
ISSN-L
2041-1723
Statut éditorial
Publié
Date de publication
24/07/2019
Peer-reviewed
Oui
Volume
10
Numéro
1
Pages
3300
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: epublish
Résumé
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.
Pubmed
Open Access
Oui
Création de la notice
06/08/2019 17:43
Dernière modification de la notice
20/08/2019 15:14
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