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

• Published in: Nature genetics Vol. 55; no. 12; pp. 2117 - 2128
• Main Authors: Bhattacharya, Arjun, Vo, Daniel D., Jops, Connor, Kim, Minsoo, Wen, Cindy, Hervoso, Jonatan L., Pasaniuc, Bogdan, Gandal, Michael J.
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01.12.2023; Nature Publishing Group
• Subjects: 38/91; 631/208/199; 692/699/476; Agriculture; Animal Genetics and Genomics; Biomedical and Life Sciences; Biomedicine; Brain; Brain - metabolism; Cancer Research; Datasets; Disorders; Gene expression; Gene Function; Gene loci; Genes; Genetic Predisposition to Disease; Genetics; Genome-wide association studies; Genome-Wide Association Study - methods; Genomes; Genomics; Human Genetics; Humans; Hypotheses; Isoforms; Mental disorders; Polymorphism, Single Nucleotide; Protein Isoforms - metabolism; Quantitative Trait Loci - genetics; Schizophrenia; Simulation; Transcriptome - genetics; Transcriptomes; Transcriptomics
• ISSN: 1061-4036; 1546-1718
• DOI: 10.1038/s41588-023-01560-2

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. A multivariate framework for isoform-resolution transcriptome-wide association studies enables modeling of a greater number of genes, with the benefit of identifying isoform-specific associations with psychiatric traits not observed at the gene level.