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Peer-reviewedCC BYNature Genetics

High false sign rates in transcriptome-wide association studies

  • P. Gerlach1
  • Nikhil Milind2
  • Jeffrey P. Spence3,4
  • Jonathan K. Pritchard5,6
6 affiliations
  1. 1Department of Genetics, Stanford University, Stanford, CA, USA. [email protected]
  2. 2Department of Genetics, Stanford University, Stanford, CA, USA. [email protected]
  3. 3Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA. [email protected]
  4. 4Institute for Human Genetics, University of California, San Francisco, CA, USA. [email protected]
  5. 5Department of Biology, Stanford University, Stanford, CA, USA. [email protected]
  6. 6Department of Genetics, Stanford University, Stanford, CA, USA. [email protected]
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Abstract

Transcriptome-wide association studies (TWAS) are widely used to identify genes involved in complex traits and to infer the direction of gene effects on traits. However, despite their popularity, it remains unclear how accurately TWAS recover the true direction of a gene’s effect on a trait. Here we estimate the false sign rate of TWAS for plasma proteins, leveraging the expectation that increased gene expression should generally increase protein expression. We then extend this framework to complex traits, where loss-of-function burden tests provide the expected direction of effect. In both analyses, we observe high discordance with expectations, with TWAS showing a false sign rate of 23% for plasma proteins and 33% for complex traits. We propose that much of the sign discordance arises when expression quantitative trait loci in non-trait-relevant tissues tag haplotypes associated with traits in genome-wide association studies via distinct, tightly linked regulatory variants, yielding spurious TWAS associations with the correct genes but with unreliable direction of effect. These findings show that TWAS-based direction-of-effect estimates should be interpreted with caution and raise concerns about the reliability of TWAS more broadly.

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Cite

BibTeXRIS
BibTeX
@article{gerlach2026high,
  title = {{High false sign rates in transcriptome-wide association studies}},
  author = {P. Gerlach and Nikhil Milind and Jeffrey P. Spence and Jonathan K. Pritchard},
  journal = {Nature Genetics},
  year = {2026},
  month = oct,
  doi = {10.1038/s41588-026-02796-4},
  url = {https://doi.org/10.1038/s41588-026-02796-4},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - High false sign rates in transcriptome-wide association studies
AU  - P. Gerlach
AU  - Nikhil Milind
AU  - Jeffrey P. Spence
AU  - Jonathan K. Pritchard
PY  - 2026
DA  - 2026/10/22
JO  - Nature Genetics
DO  - 10.1038/s41588-026-02796-4
UR  - https://doi.org/10.1038/s41588-026-02796-4
AB  - Transcriptome-wide association studies (TWAS) are widely used to identify genes involved in complex traits and to infer the direction of gene effects on traits. However, despite their popularity, it remains unclear how accurately TWAS recover the true direction of a gene’s effect on a trait. Here we estimate the false sign rate of TWAS for plasma proteins, leveraging the expectation that increased gene expression should generally increase protein expression. We then extend this framework to complex traits, where loss-of-function burden tests provide the expected direction of effect. In both analyses, we observe high discordance with expectations, with TWAS showing a false sign rate of 23% for plasma proteins and 33% for complex traits. We propose that much of the sign discordance arises when expression quantitative trait loci in non-trait-relevant tissues tag haplotypes associated with traits in genome-wide association studies via distinct, tightly linked regulatory variants, yielding spurious TWAS associations with the correct genes but with unreliable direction of effect. These findings show that TWAS-based direction-of-effect estimates should be interpreted with caution and raise concerns about the reliability of TWAS more broadly.
SN  - 1061-4036
SN  - 1546-1718
ER  -