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Transcriptome-wide and stratified genomic structural equation modeling identify neurobiological pathways shared across diverse cognitive traits

Author

Listed:
  • Andrew D. Grotzinger

    (University of Colorado at Boulder
    University of Colorado at Boulder)

  • Javier de la Fuente

    (University of Texas at Austin
    University of Texas at Austin)

  • Gail Davies

    (University of Edinburgh
    University of Edinburgh)

  • Michel G. Nivard

    (VU University Amsterdam)

  • Elliot M. Tucker-Drob

    (University of Texas at Austin
    University of Texas at Austin)

Abstract

Functional genomic methods are needed that consider multiple genetically correlated traits. Here we develop and validate Transcriptome-wide Structural Equation Modeling (T-SEM), a multivariate method for studying the effects of tissue-specific gene expression across genetically overlapping traits. T-SEM allows for modeling effects on broad dimensions spanning constellations of traits, while safeguarding against false positives that can arise when effects of gene expression are specific to a subset of traits. We apply T-SEM to investigate the biological mechanisms shared across seven distinct cognitive traits (N = 11,263–331,679), as indexed by a general dimension of genetic sharing (g). We identify 184 genes whose tissue-specific expression is associated with g, including 10 genes not identified in univariate analysis for the individual cognitive traits for any tissue type, and three genes whose expression explained a significant portion of the genetic sharing across g and different subclusters of psychiatric disorders. We go on to apply Stratified Genomic SEM to identify enrichment for g within 28 functional categories. This includes categories indexing the intersection of protein-truncating variant intolerant (PI) genes and specific neuronal cell types, which we also find to be enriched for the genetic covariance between g and a psychotic disorders factor.

Suggested Citation

  • Andrew D. Grotzinger & Javier de la Fuente & Gail Davies & Michel G. Nivard & Elliot M. Tucker-Drob, 2022. "Transcriptome-wide and stratified genomic structural equation modeling identify neurobiological pathways shared across diverse cognitive traits," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-33724-9
    DOI: 10.1038/s41467-022-33724-9
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    References listed on IDEAS

    as
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