title: Hypothesis-driven candidate genes for schizophrenia compared to genome-wide association results.
abstract: BACKGROUND
  Candidate gene studies have been a key approach to the genetics of schizophrenia (SCZ). However, the results of these studies are confusing and no genes have been unequivocally implicated. The hypothesis-driven candidate gene literature can be appraised by comparison with the results of genome-wide association studies (GWAS).
  
  
  METHODS
  We describe the characteristics of hypothesis-driven candidate gene studies from the SZGene database, and use pathway analysis to compare hypothesis-driven candidate genes with GWAS results from the International Schizophrenia Consortium (ISC).
  
  
  RESULTS
  SZGene contained 732 autosomal genes evaluated in 1374 studies. These genes had poor statistical power to detect genetic effects typical for human diseases, assessed only 3.7% of genes in the genome, and had low marker densities per gene. Most genes were assessed once or twice (76.9%), providing minimal ability to evaluate consensus across studies. The ISC studies had 89% power to detect a genetic effect typical for common human diseases and assessed 79% of known autosomal common genetic variation. Pathway analyses did not reveal enrichment of smaller ISC p values in hypothesis-driven candidate genes, nor did a comprehensive evaluation of meta-hypotheses driving candidate gene selection (SCZ as a disease of the synapse or neurodevelopment). The most studied hypothesis-driven candidate genes (COMT, DRD3, DRD2, HTR2A, NRG1, BDNF, DTNBP1 and SLC6A4) had no notable ISC results.
  
  
  CONCLUSIONS
  We did not find support for the idea that the hypothesis-driven candidate genes studied in the literature are enriched for the common genetic variation involved in the etiology of SCZ. Larger samples are required to evaluate this conclusion definitively.
authors.affiliation: Department of Genetics, University of North Carolina at Chapel Hill, NC 27599-7264, USA. collin@med.unc.edu
authors.forename: A L
authors.initials: AL
authors.lastname: Collins
authors.forename: Y
authors.initials: Y
authors.lastname: Kim
authors.forename: P
authors.initials: P
authors.lastname: Sklar
authors.forename: M C
authors.initials: MC
authors.lastname: O'Donovan
authors.forename: P F
authors.initials: PF
authors.lastname: Sullivan
mesh_terms: D000465:Algorithms; D016022:Case-Control Studies; D003627:Data Interpretation, Statistical; D030541:Databases, Genetic / Q000706:statistics & numerical data; D056726:Genetic Association Studies / Q000706:statistics & numerical data*; D056426:Genetic Loci; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D014644:Genetic Variation / Q000235:genetics*; D055106:Genome-Wide Association Study / Q000706:statistics & numerical data; D023281:Genomics / Q000379:methods* / Q000639:trends; D005838:Genotype; D006801:Humans; D016015:Logistic Models; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D012559:Schizophrenia / Q000235:genetics*