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Transcriptome-wide association analysis of brain structures yields insights into pleiotropy with complex neuropsychiatric traits.
Zhao, Bingxin; Shan, Yue; Yang, Yue; Yu, Zhaolong; Li, Tengfei; Wang, Xifeng; Luo, Tianyou; Zhu, Ziliang; Sullivan, Patrick; Zhao, Hongyu; Li, Yun; Zhu, Hongtu.
Afiliação
  • Zhao B; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Shan Y; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Yang Y; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Yu Z; Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA.
  • Li T; Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Wang X; Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Luo T; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Zhu Z; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Sullivan P; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Zhao H; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Li Y; Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA.
  • Zhu H; Department of Biostatistics, Yale University, New Haven, CT, USA.
Nat Commun ; 12(1): 2878, 2021 05 17.
Article em En | MEDLINE | ID: mdl-34001886
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Encéfalo / Herança Multifatorial / Perfilação da Expressão Gênica / Estudo de Associação Genômica Ampla / Pleiotropia Genética Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Encéfalo / Herança Multifatorial / Perfilação da Expressão Gênica / Estudo de Associação Genômica Ampla / Pleiotropia Genética Idioma: En Ano de publicação: 2021 Tipo de documento: Article