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Hypothesis-driven candidate genes for schizophrenia compared to genome-wide association results.

ABSTRACT: 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).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).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.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.

SUBMITTER: Collins AL

PROVIDER: S-EPMC4188923 | biostudies-literature | 2012 Mar

REPOSITORIES: biostudies-literature

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Hypothesis-driven candidate genes for schizophrenia compared to genome-wide association results.

Collins A L AL Kim Y Y Sklar P P O'Donovan M C MC Sullivan P F PF

Psychological medicine 20110819 3

<h4>Background</h4>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).<h4>Method</h4>We describe the characteristics of hypothesis-driven candidate gene studies from the SZGene database, and use pathway analysis to compare h ...[more]

PMID: 21854684

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Project description:Mitochondria are the main source of energy for neurons and have a role in many vital neuronal functions. Mitochondrial dysfunction has been described in schizophrenia, and antipsychotics such as clozapine and olanzapine have been associated with differences in gene expression in mitochondria. We investigated the hypothesis that nuclear-encoded mitochondrial genes, particularly those involved in oxidative phosphorylation or involved in oxidative stress, mitochondrial biogenesis, inflammation, and apoptosis, would be associated with antipsychotic-induced weight gain (AIWG). In total, we selected 28 genes and analyzed 60 SNPs (50 are functional), in 283 schizophrenia subjects, treated with atypical medications for up to 14 weeks. Association between AIWG (as measured by the % of weight gain from baseline) and SNP genotypes were tested using linear regression with treatment duration, baseline body weight, and medication type as covariates. We observed a significant association between rs6435326 in the NDUFS1 gene and AIWG in the subset of European patients (N=150, Pcorrected=0.02). The haplotype carrying the risk alleles of rs6435326 and two other SNPs (rs1053517 and rs1801318) in NDUFS1 was also nominally associated with percentage of weight gain (T-C-G vs A-T-A, P=0.005). In addition, stepwise linear regression was performed to select important variables predictive of the outcome, and a gene-gene interaction analysis was carried out. We observed a significant interaction between the TT risk genotype of rs6435326 in NDUFS1 and AG genotype of rs3762883 in COX18 (Pcorrected=0.001). A permutation-based test of all 60 SNPs jointly showed significant association with weight gain (P=0.02). Finally, our replication study of rs6435326, rs1053517 and rs1801318 in NDUFS1 using samples from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) showed that rs1801318 was significantly associated with AIWG (N=200, Pcorrected=0.04), and the three SNPs were collectively associated with AIWG (P=0.04). In conclusion, our findings suggest an association between NDUFS1 and AIWG in schizophrenia subjects. To the best of our knowledge, this is the first study to explore genetic variation in the mitochondrial genes in the context of AIWG.

Project description:Integrating evidence from multiple domains is useful in prioritizing disease candidate genes for subsequent testing. We ranked all known human genes (n=3819) under linkage peaks in the Irish Study of High-Density Schizophrenia Families using three different evidence domains: 1) a meta-analysis of microarray gene expression results using the Stanley Brain collection, 2) a schizophrenia protein-protein interaction network, and 3) a systematic literature search. Each gene was assigned a domain-specific p-value and ranked after evaluating the evidence within each domain. For comparison to this ranking process, a large-scale candidate gene hypothesis was also tested by including genes with Gene Ontology terms related to neurodevelopment. Subsequently, genotypes of 3725 SNPs in 167 genes from a custom Illumina iSelect array were used to evaluate the top ranked vs. hypothesis selected genes. Seventy-three genes were both highly ranked and involved in neurodevelopment (category 1) while 42 and 52 genes were exclusive to neurodevelopment (category 2) or highly ranked (category 3), respectively. The most significant associations were observed in genes PRKG1, PRKCE, and CNTN4 but no individual SNPs were significant after correction for multiple testing. Comparison of the approaches showed an excess of significant tests using the hypothesis-driven neurodevelopment category. Random selection of similar sized genes from two independent genome-wide association studies (GWAS) of schizophrenia showed the excess was unlikely by chance. In a further meta-analysis of three GWAS datasets, four candidate SNPs reached nominal significance. Although gene ranking using integrated sources of prior information did not enrich for significant results in the current experiment, gene selection using an a priori hypothesis (neurodevelopment) was superior to random selection. As such, further development of gene ranking strategies using more carefully selected sources of information is warranted.

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Hypothesis-driven candidate genes for schizophrenia compared to genome-wide association results.

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Hypothesis-driven candidate genes for schizophrenia compared to genome-wide association results.

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