Of 449 independent intervals that contained the best genome-wide association signals, 9 intervals overlapped with the 66 target genes of GO:0022843. INRICH ( Lee et al., 2012), another gene-set tool, implements a permutation-based algorithm to correct for possible biases induced by marker density, linkage disequilibrium (LD) structure and gene size. We ran four analyses, and for each option the voltage-gated cation channel activity gene-set (GO:0022843) showed a highly significant enrichment score, with FDR corrected P values ranging between P FDR = 1 × 10 -8 and 4 × 10 -8. Importantly, GSA-SNP offers the option to set the k th ( k = 2, 3, 4 or 5) best P value as proxy for the respective gene instead of using only the best P value. GSA-SNP is a gene-set tool that uses SNP P values as input and identifies pathways in a competitive way ( Nam et al., 2010). To assess whether the identified gene set is detected independently of the algorithm used, we used different gene-set analysis tools in the combined discovery and replication samples ( n = 1’651), for which the identical cognitive task served as phenotype. Transport of inorganic cations anions and amino acids oligopeptidesĬell surface interactions at the vascular Wall Transmembrane receptor protein kinase activity Metal ion transmembrane transporter activityĪrrhythmogenic right ventricular cardiomyopathy Transport of glucose and other sugars, bile salts and organic acids, metal ions and amine compounds In addition, this gene-set is associated to WM-related activity in brain regions known for their involvement in psychiatric disease.
We show that the voltage-gated cation channel activity gene-set, consisting of genes related to neuronal excitability, is robustly linked to WM performance across ages, and to schizophrenia. In a large case-control sample we also performed genome-wide gene-set enrichment analyses of the risk for schizophrenia. We performed genome-wide gene-set enrichment analyses of WM performance in multiple independent data sets of young and aged cognitively healthy subjects.
However, the methodological heterogeneity of different pathway analytical tools makes it necessary to demonstrate the methodological invariance and replicability of the results (for reviews see ( Holmans et al., 2009 Wang et al., 2010 Wang et al., 2011)). As shown recently in studies on autism ( Voineagu et al., 2011), bipolar disorder ( Holmans et al., 2009 Sklar et al., 2011), ADHD ( Stergiakouli et al., 2012) and schizophrenia ( O’Dushlaine et al., 2011), such approaches can identify convergent molecular pathways relevant to neuropsychiatry and provide initial evidence, which can serve as starting point for testable hypotheses addressing functionality within the indicated pathways. By taking into account prior biological knowledge, gene-set-based approaches examine whether test statistics for a group of related genes have consistent deviation from chance ( Wang et al., 2010). These methods aim at identifying biologically meaningful sets of genes associated with a certain trait, rather than focusing on a single GWAS gene locus ( Wang et al., 2010). Triggered by statistical approaches for the analysis of gene expression and protein-protein interaction, gene-set-based analytical methods have recently become available. It is, however, widely accepted that single-marker-based analyses have limited power to identify the genetic basis of a given trait, as for example, many loci will fail to reach stringent genome-wide significance threshold, despite the fact that they may be genuinely associated with the trait. Genome-wide association studies (GWAS) employing single-marker statistics have been successful in identifying cognitive trait-associated single-gene loci ( Papassotiropoulos and de Quervain, 2011). Deficits in WM are a key component of psychiatric disorders such as schizophrenia ( Barch, 2005), bipolar disorder ( Balanza-Martinez et al., 2008) and attention deficit hyperactivity disorder (ADHD) ( Doyle, 2006). Working memory (WM), which represents a limited-capacity neural network capable of actively maintaining task-relevant information during the execution of a cognitive task ( Shah and Miyake, 1999), is a key cognitive trait well amenable to behavioral genetic studies: WM is heritable ( Karlsgodt et al., 2011), can be assessed in a valid and reliable manner, and has well-defined neural correlates as shown in functional brain imaging studies ( D’Esposito, 2007). The study of the genetic underpinnings of human cognition, emotion and personality impacts substantially on the understanding of physiological and pathophysiological processes relevant to mental health and psychiatric disease.
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