Transcriptome-wide association studies: a view from Mendelian randomization

Abstract

Background: Genome-wide association studies (GWASs) have identified thousands of genetic variants that are associated with many complex traits. However, their biological mechanisms remain largely unknown. Transcriptome-wide association studies (TWAS) have been recently proposed as an invaluable tool for investigating the potential gene regulatory mechanisms underlying variant-trait associations. Specifically, TWAS integrate GWAS with expression mapping studies based on a common set of variants and aim to identify genes whose GReX is associated with the phenotype. Various methods have been developed for performing TWAS and/or similar integrative analysis. Each such method has a different modeling assumption and many were initially developed to answer different biological questions. Consequently, it is not straightforward to understand their modeling property from a theoretical perspective.

Results: We present a technical review on thirteen TWAS methods. Importantly, we show that these methods can all be viewed as two-sample Mendelian randomization (MR) analysis, which has been widely applied in GWASs for examining the causal effects of exposure on outcome. Viewing different TWAS methods from an MR perspective provides us a unique angle for understanding their benefits and pitfalls. We systematically introduce the MR analysis framework, explain how features of the GWAS and expression data influence the adaptation of MR for TWAS, and re-interpret the modeling assumptions made in different TWAS methods from an MR angle. We finally describe future directions for TWAS methodology development.

Conclusions: We hope that this review would serve as a useful reference for both methodologists who develop TWAS methods and practitioners who perform TWAS analysis.

Author summary

Transcriptome wide association studies (TWAS) integrate expression mapping studies and GWAS studies and aim to identify candidate genes whose genetically regulated expression is associated with trait of interest. We present a comprehensive review on a broad category of recently developed and commonly used TWAS methods. Our review covers different modeling assumptions, different inference procedures, modeling of horizontal pleiotropic effects, and extensions of TWAS towards multivariate MR analysis and summary statistics. Our review also aims to provide a unified view of various TWAS methods from the perspective of Mendelian randomization (MR).

Graphical abstract

Keywords

transcriptome-wide association studies / genome-wide association studies / expression mapping studies

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ACKNOWLEDGEMENTS

This study was supported by the National Institutes of Health (NIH) Grants R01HG009124 and the National Science Foundation (NSF) Grant DMS1712933.

COMPLIANCE WITH ETHICS GUIDELINES

The authors Huanhuan Zhu and Xiang Zhou declare that they have no conflict of interests. ƒAll procedures performed in studies were in accordance with the ethical standards of the institution.

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