Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits
Many genetic variants identified in genome-wide association studies are associated with gene expression. Here, Porcu et al. propose a transcriptome-wide summary statistics-based Mendelian randomization approach (TWMR) that, applied to 43 human traits, uncovers hundreds of previously unreported gene–...
Main Authors: | Eleonora Porcu, Sina Rüeger, Kaido Lepik, eQTLGen Consortium, BIOS Consortium, Federico A. Santoni, Alexandre Reymond, Zoltán Kutalik |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Publishing Group
2019-07-01
|
Series: | Nature Communications |
Online Access: | https://doi.org/10.1038/s41467-019-10936-0 |
Similar Items
-
Mendelian randomization integrating GWAS and eQTL data revealed genes pleiotropically associated with major depressive disorder
by: Huarong Yang, et al.
Published: (2021-04-01) -
Impact of admixture and ancestry on eQTL analysis and GWAS colocalization in GTEx
by: Nicole R. Gay, et al.
Published: (2020-09-01) -
Integrate GWAS, eQTL, and mQTL Data to Identify Alzheimer’s Disease-Related Genes
by: Tianyi Zhao, et al.
Published: (2019-10-01) -
C-reactive protein upregulates the whole blood expression of CD59 - an integrative analysis.
by: Kaido Lepik, et al.
Published: (2017-09-01) -
Identifying Thyroid Carcinoma-Related Genes by Integrating GWAS and eQTL Data
by: Fei Shen, et al.
Published: (2021-02-01)