An inherited duplication at the gene p21 Protein-Activated Kinase 7 (PAK7) is a risk factor for psychosis

Identifying rare, highly penetrant risk mutations may be an important step in dissecting the molecular etiology of schizophrenia. We conducted a gene-based analysis of large (>100 kb), rare copy-number variants (CNVs) in the Wellcome Trust Case Control Consortium 2 (WTCCC2) schizophrenia sample of 1564 cases and 1748 controls all from Ireland, and further extended the analysis to include an additional 5196 UK controls. We found association with duplications at chr20p12.2 (P = 0.007) and evidence of replication in large independent European schizophrenia (P = 0.052) and UK bipolar disorder case-control cohorts (P = 0.047). A combined analysis of Irish/UK subjects including additional psychosis cases (schizophrenia and bipolar disorder) identified 22 carriers in 11 707 cases and 10 carriers in 21 204 controls [meta-analysis Cochran–Mantel–Haenszel P-value = 2 × 10−4; odds ratio (OR) = 11.3, 95% CI = 3.7, ∞]. Nineteen of the 22 cases and 8 of the 10 controls carried duplications starting at 9.68 Mb with similar breakpoints across samples. By haplotype analysis and sequencing, we identified a tandem ∼149 kb duplication overlapping the gene p21 Protein-Activated Kinase 7 (PAK7, also called PAK5) which was in linkage disequilibrium with local haplotypes (P = 2.5 × 10−21), indicative of a single ancestral duplication event. We confirmed the breakpoints in 8/8 carriers tested and found co-segregation of the duplication with illness in two additional family members of one of the affected probands. We demonstrate that PAK7 is developmentally co-expressed with another known psychosis risk gene (DISC1) suggesting a potential molecular mechanism involving aberrant synapse development and plasticity

Pharmacogenetics of the g protein-coupled receptors

Pharmacogenetics investigates the influence of genetic variants on physiological phenotypes related to drug response and disease, while pharmacogenomics takes a genome-wide approach to advancing this knowledge. Both play an important role in identifying responders and nonresponders to medication, avoiding adverse drug reactions, and optimizing drug dose for the individual. G protein-coupled receptors (GPCRs) are the primary target of therapeutic drugs and have been the focus of these studies. With the advance of genomic technologies, there has been a substantial increase in the inventory of naturally occurring rare and common GPCR variants. These variants include single-nucleotide polymorphisms and insertion or deletions that have potential to alter GPCR expression of function. In vivo and in vitro studies have determined functional roles for many GPCR variants, but genetic association studies that define the physiological impact of the majority of these common variants are still limited. Despite the breadth of pharmacogenetic data available, GPCR variants have not been included in drug labeling and are only occasionally considered in optimizing clinical use of GPCR-targeted agents. In this chapter, pharmacogenetic and genomic studies on GPCR variants are reviewed with respect to a subset of GPCR systems, including the adrenergic, calcium sensing, cysteinyl leukotriene, cannabinoid CB1 and CB2 receptors, and the de-orphanized receptors such as GPR55. The nature of the disruption to receptor function is discussed with respect to regulation of gene expression, expression on the cell surface (affected by receptor trafficking, dimerization, desensitization/downregulation), or perturbation of receptor function (altered ligand binding, G protein coupling, constitutive activity). The large body of experimental data generated on structure and function relationships and receptor-ligand interactions are being harnessed for the in silico functional prediction of naturally occurring GPCR variants. We provide information on online resources dedicated to GPCRs and present applications of publically available computational tools for pharmacogenetic studies of GPCRs. As the breadth of GPCR pharmacogenomic data becomes clearer, the opportunity for routine assessment of GPCR variants to predict disease risk, drug response, and potential adverse drug effects will become possible