A transcriptome-wide Mendelian randomization study to uncover tissue-dependent regulatory mechanisms across the human phenome

Developing insight into tissue-specific transcriptional mechanisms can help improve our understanding of how genetic variants exert their effects on complex traits and disease. In this study, we apply the principles of Mendelian randomization to systematically evaluate transcriptome-wide association...

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Veröffentlicht in:Nature communications Jg. 11; H. 1; S. 185 - 11
Hauptverfasser: Richardson, Tom G., Hemani, Gibran, Gaunt, Tom R., Relton, Caroline L., Davey Smith, George
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London Nature Publishing Group UK 10.01.2020
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Aromatase - genetics
Fibrillin-2 - genetics
Gene expression
Gene Expression Regulation
Genetic Association Studies
Genetic diversity
Genetic Predisposition to Disease
Genetic variance
Genetic Variation
Humanities and Social Sciences
Humans
Hydroxymethylglutaryl CoA Reductases - genetics
Mendelian Randomization Analysis
multidisciplinary
Multifactorial Inheritance
Phenomics
Phenotype
Phenotypes
Polymorphism, Single Nucleotide
Quantitative Trait Loci
Randomization
Regulatory mechanisms (biology)
Ribosomal Proteins - genetics
Science
Science (multidisciplinary)
Thyroid Diseases - genetics
Thyroid Diseases - metabolism
Tissues
Transcription
Transcriptome
ISSN:2041-1723, 2041-1723
Online-Zugang:Volltext
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Zusammenfassung:Developing insight into tissue-specific transcriptional mechanisms can help improve our understanding of how genetic variants exert their effects on complex traits and disease. In this study, we apply the principles of Mendelian randomization to systematically evaluate transcriptome-wide associations between gene expression (across 48 different tissue types) and 395 complex traits. Our findings indicate that variants which influence gene expression levels in multiple tissues are more likely to influence multiple complex traits. Moreover, detailed investigations of our results highlight tissue-specific associations, drug validation opportunities, insight into the likely causal pathways for trait-associated variants and also implicate putative associations at loci yet to be implicated in disease susceptibility. Similar evaluations can be conducted at http://mrcieu.mrsoftware.org/Tissue_MR_atlas/ . Gene expression and how genetic variants can influence gene expression are tissue-specific processes with important implications for phenotypes. Here, Richardson et al. use eQTL data from GTEx and the eQTLGen project in a two-sample SMR + HEIDI framework for causal inference of gene expression associations with complex trait.
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ISSN:2041-1723
2041-1723
DOI:10.1038/s41467-019-13921-9