Strengthening Causal Inference for Complex Disease Using Molecular Quantitative Trait Loci.

Abstract:

:Large genome-wide association studies (GWAS) have identified loci that are associated with complex traits and diseases, but index variants are often not causal and reside in non-coding regions of the genome. To gain a better understanding of the relevant biological mechanisms, intermediate traits such as gene expression and protein levels are increasingly being investigated because these are likely mediators between genetic variants and disease outcome. Genetic variants associated with intermediate traits, termed molecular quantitative trait loci (molQTLs), can then be used as instrumental variables in a Mendelian randomization (MR) approach to identify the causal features and mechanisms of complex traits. Challenges such as pleiotropy and the non-specificity of molQTLs remain, and further approaches and methods need to be developed.

journal_name

Trends Mol Med

authors

Neumeyer S,Hemani G,Zeggini E

doi

10.1016/j.molmed.2019.10.004

subject

Has Abstract

pub_date

2020-02-01 00:00:00

pages

232-241

issue

2

eissn

1471-4914

issn

1471-499X

pii

S1471-4914(19)30266-7

journal_volume

26

pub_type

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