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...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Nature communications Ročník 11; číslo 1; s. 185 - 11
Hlavní autori:	Richardson, Tom G., Hemani, Gibran, Gaunt, Tom R., Relton, Caroline L., Davey Smith, George
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Nature Publishing Group UK 10.01.2020 Nature Publishing Group Nature Portfolio
Predmet:	45/43 631/208/199 631/208/205 631/208/480 692/308 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
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Popis
Shrnutí:	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.
Bibliografia:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
ISSN:	2041-1723 2041-1723
DOI:	10.1038/s41467-019-13921-9