Author
Listed:
- Bingxin Zhao
(University of North Carolina at Chapel Hill)
- Yue Shan
(University of North Carolina at Chapel Hill)
- Yue Yang
(University of North Carolina at Chapel Hill)
- Zhaolong Yu
(Yale University)
- Tengfei Li
(University of North Carolina at Chapel Hill
University of North Carolina at Chapel Hill)
- Xifeng Wang
(University of North Carolina at Chapel Hill)
- Tianyou Luo
(University of North Carolina at Chapel Hill)
- Ziliang Zhu
(University of North Carolina at Chapel Hill)
- Patrick Sullivan
(University of North Carolina at Chapel Hill)
- Hongyu Zhao
(Yale University
Yale University)
- Yun Li
(University of North Carolina at Chapel Hill
University of North Carolina at Chapel Hill
University of North Carolina at Chapel Hill)
- Hongtu Zhu
(University of North Carolina at Chapel Hill
University of North Carolina at Chapel Hill)
Abstract
Structural variations of the human brain are heritable and highly polygenic traits, with hundreds of associated genes identified in recent genome-wide association studies (GWAS). Transcriptome-wide association studies (TWAS) can both prioritize these GWAS findings and also identify additional gene-trait associations. Here we perform cross-tissue TWAS analysis of 211 structural neuroimaging and discover 278 associated genes exceeding Bonferroni significance threshold of 1.04 × 10−8. The TWAS-significant genes for brain structures have been linked to a wide range of complex traits in different domains. Through TWAS gene-based polygenic risk scores (PRS) prediction, we find that TWAS PRS gains substantial power in association analysis compared to conventional variant-based GWAS PRS, and up to 6.97% of phenotypic variance (p-value = 7.56 × 10−31) can be explained in independent testing data sets. In conclusion, our study illustrates that TWAS can be a powerful supplement to traditional GWAS in imaging genetics studies for gene discovery-validation, genetic co-architecture analysis, and polygenic risk prediction.
Suggested Citation
Bingxin Zhao & Yue Shan & Yue Yang & Zhaolong Yu & Tengfei Li & Xifeng Wang & Tianyou Luo & Ziliang Zhu & Patrick Sullivan & Hongyu Zhao & Yun Li & Hongtu Zhu, 2021.
"Transcriptome-wide association analysis of brain structures yields insights into pleiotropy with complex neuropsychiatric traits,"
Nature Communications, Nature, vol. 12(1), pages 1-11, December.
Handle:
RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-23130-y
DOI: 10.1038/s41467-021-23130-y
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