Isoform-level transcriptome-wide association uncovers genetic risk mechanisms for neuropsychiatric disorders in the human brain

Nat Genet. 2023 Dec;55(12):2117-2128. doi: 10.1038/s41588-023-01560-2. Epub 2023 Nov 30.

Abstract

Methods integrating genetics with transcriptomic reference panels prioritize risk genes and mechanisms at only a fraction of trait-associated genetic loci, due in part to an overreliance on total gene expression as a molecular outcome measure. This challenge is particularly relevant for the brain, in which extensive splicing generates multiple distinct transcript-isoforms per gene. Due to complex correlation structures, isoform-level modeling from cis-window variants requires methodological innovation. Here we introduce isoTWAS, a multivariate, stepwise framework integrating genetics, isoform-level expression and phenotypic associations. Compared to gene-level methods, isoTWAS improves both isoform and gene expression prediction, yielding more testable genes, and increased power for discovery of trait associations within genome-wide association study loci across 15 neuropsychiatric traits. We illustrate multiple isoTWAS associations undetectable at the gene-level, prioritizing isoforms of AKT3, CUL3 and HSPD1 in schizophrenia and PCLO with multiple disorders. Results highlight the importance of incorporating isoform-level resolution within integrative approaches to increase discovery of trait associations, especially for brain-relevant traits.

MeSH terms

  • Brain / metabolism
  • Genetic Predisposition to Disease
  • Genome-Wide Association Study* / methods
  • Humans
  • Polymorphism, Single Nucleotide
  • Protein Isoforms / metabolism
  • Quantitative Trait Loci / genetics
  • Transcriptome* / genetics

Substances

  • Protein Isoforms