Transcriptome wide association studies: general framework and methods

Abstract

Background: Genome-wide association studies (GWAS) have succeeded in identifying tens of thousands of genetic variants associated with complex human traits during the past decade, however, they are still hampered by limited statistical power and difficulties in biological interpretation. With the recent progress in expression quantitative trait loci (eQTL) studies, transcriptome-wide association studies (TWAS) provide a framework to test for gene-trait associations by integrating information from GWAS and eQTL studies.

Results: In this review, we will introduce the general framework of TWAS, the relevant resources, and the computational tools. Extensions of the original TWAS methods will also be discussed. Furthermore, we will briefly introduce methods that are closely related to TWAS, including MR-based methods and colocalization approaches. Connection and difference between these approaches will be discussed.

Conclusion: Finally, we will summarize strengths, limitations, and potential directions for TWAS.

Author summary

Transcriptome-wide association studies (TWAS) provide an important framework to test for gene-trait associations by integrating information from GWAS and eQTL studies. In this review, we systematically review the general framework and methods of transcriptome-wide association studies, and discuss their strengths, limitations, and potential future directions.

Graphical abstract

Keywords

TWAS / gene imputation / gene-trait association test / eQTL studies / GWAS

References

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SUPPLEMENTARY MATERIALS

The supplementary materials can be found online with this article at https://10.15302/J-QB-020-0228.

ACKNOWLEDGEMENTS

We thank Zhaolong Yu for suggestions and Michael Farruggia for English language polishing. L. H. acknowledges the following fundings: the National Natural Science Foundation of China (No. 11601259) and Shanghai Municipal Science and Technology Major Project (No. 2017SHZDZX01). Y. X. and N. S. were supported in part by the China Scholarship Council, and H. Z. was supported in part by NIH grant R01GM122078, NSF grants DMS 1713120 and DMS 1902903.

COMPLIANCE WITH ETHICS GUIDELINES

The authors Yuhan Xie, Nayang Shan, Hongyu Zhao and Lin Hou declare that they have no conflict of interests.

This article is a review article and does not contain any studies with human or animal subjects performed by any of the authors.

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