What it is
Transcriptome-wide association studies (TWAS) are widely used to identify genes involved in complex traits and to infer the direction of a gene's effect on a trait, whether more of the gene's expression raises or lowers it. Despite their popularity, how accurately TWAS recover the true direction of effect has remained unclear. The authors estimate the false sign rate of TWAS for plasma proteins, using the expectation that increased expression of a gene should generally increase expression of its protein, and extend the framework to complex traits, where loss-of-function burden tests provide the expected direction of effect. Both analyses show high discordance with expectations: TWAS have a false sign rate of 23% for plasma proteins and 33% for complex traits. The authors propose that much of the discordance arises when expression quantitative trait loci in tissues that are not relevant to the trait tag haplotypes associated with the trait in genome-wide association studies through distinct, tightly linked regulatory variants, yielding spurious TWAS associations with the correct genes but an unreliable direction of effect. They conclude that TWAS-based direction-of-effect estimates should be interpreted with caution, and raise concerns about the reliability of TWAS more broadly.
Why it matters
TWAS, widely used to infer whether a gene raises or lowers a trait, had estimated false sign rates of 23% for plasma proteins and 33% for complex traits. How accurately these transcriptome-wide association studies recover the direction of a gene's effect had been unclear. The authors checked plasma-protein results against the expectation that more expression of a gene generally means more of its protein, and complex-trait results against loss-of-function burden tests. They propose that much of the discordance comes from expression signals in tissues not relevant to the trait tagging trait-associated haplotypes through distinct, tightly linked regulatory variants, so TWAS can find the correct gene with an unreliable direction. They urge caution with TWAS direction-of-effect estimates.
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Filed underGenetic Associations and Epidemiology, Bioinformatics and Genomic Networks, Genetic Mapping and Diversity in Plants and Animals
