Abstract
There is growing recognition that co-morbidity and co-occurrence of disease traits are often determined by shared genetic and molecular mechanisms. In most cases, however, the specific mechanisms that lead to such trait-trait relationships are yet unknown. Here we present an analysis of a broad spectrum of behavioral and physiological traits together with gene-expression measurements across genetically diverse mouse strains. We develop an unbiased methodology that constructs potentially overlapping groups of traits and resolves their underlying combination of genetic loci and molecular mechanisms. For example, our method predicts that genetic variation in the Klf7 gene may influence gene transcripts in bone marrow-derived myeloid cells, which in turn affect 17 behavioral traits following morphine injection; this predicted effect of Klf7 is consistent with an in vitro perturbation of Klf7 in bone marrow cells. Our analysis demonstrates the utility of studying hidden causative mechanisms that lead to relationships between complex traits.
Highlights
Epidemiological and clinical research has identified a profusion of correlated physiological traits, as well as a remarkably high incidence of co-occurrence and comorbidity among disorders
Various studies have shown that such connections among diseases are typically attributable to a common underlying genetic or molecular mechanism (Rzhetsky et al, 2007; Oti et al, 2008; Barabasi et al, 2011; Cotsapas et al, 2011; Lee et al, 2012; Cross-Disorder Group of the Psychiatric Genomics Consortium, 2013)
Our simulations showed that GEMOT is superior to these methods in identifying trait groups that share the same underlying transcripts (Figure 5—figure supplement 5B)
Summary
Epidemiological and clinical research has identified a profusion of correlated physiological traits, as well as a remarkably high incidence of co-occurrence and comorbidity among disorders. A common way to improve predictions is by integrating relationships between genes and traits, using gene–trait correlations, associations, or causal mutations (Rzhetsky et al, 2007; Cotsapas et al, 2011; Baker et al, 2012; Hwang et al, 2012; Gat-Viks et al, 2013) Such pairwise gene–trait connections were used to construct two-layer clusters (‘biclusters’) consisting of groups of traits linked to the same group of genes. Such ‘gene-based’ approaches provide a list of putative non-environmental mechanisms, their utilization has two major
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