Transcriptome-wide and Stratified Genomic Structural Equation Modeling Identify Neurobiological Pathways Underlying General and Specific Cognitive Functions

Abstract

Spearmans observation in 1904 that distinct cognitive functions--such as reasoning, processing speed, and episodic memory--are positively intercorrelated has given rise to over a century of speculation and investigation into their common and domain-specific mechanisms of variation. Here we develop and validate Transcriptome-wide Structural Equation Modeling (T-SEM), a novel method for studying the effects of tissue-specific gene expression within multivariate space. We apply T-SEM to investigate the shared and unique functional genomic characteristics of seven, distinct cognitive traits (N = 11,263-331,679). We identify 184 genes associated with general cognitive function (g), including 10 novel genes not identified in univariate analysis for the individual cognitive traits. We go on to apply Stratified Genomic SEM to identify enrichment for g within 29 functional genomic 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.