Gene- and evidence-based candidate gene selection for schizophrenia and gene feature analysis

Abstract

Objective: Schizophrenia is a chronic psychiatric disorder that affects about 1% of the population globally. A tremendous amount of effort has been expended in the past decade, including more than 2400 association studies, to identify genes influencing susceptibility to the disorder. However, few genes or markers have been reliably replicated. The wealth of this information calls for an integration of gene association data, evidence-based gene ranking, and follow-up replication in large sample. The objective of this study is to develop and evaluate evidence-based gene ranking methods and to examine the features of top-ranking candidate genes for schizophrenia.

Methods: We proposed a gene-based approach for selecting and prioritizing candidate genes by combining odds ratios (ORs) of multiple markers in each association study and then combining ORs in multiple studies of a gene. We named it combination-combination OR method (CCOR). CCOR is similar to our recently published method, which first selects the largest OR of the markers in each study and then combines these ORs in multiple studies (i.e., selection-combination OR method, SCOR), but differs in selecting representative OR in each study. Features of top-ranking genes were examined by Gene Ontology terms and gene expression in tissues.

Results: Our evaluation suggested that the SCOR method overall outperforms the CCOR method. Using the SCOR, a list of 75 top-ranking genes was selected for schizophrenia candidate genes (SZGenes). We found that SZGenes had strong correlation with neuro-related functional terms and were highly expressed in brain-related tissues.

Conclusion: The scientific landscape for schizophrenia genetics and other complex disease studies is expected to change dramatically in the next a few years, thus, the gene-based combined OR method is useful in candidate gene selection for follow-up association studies and in further artificial intelligence in medicine. This method for prioritization of candidate genes can be applied to other complex diseases such as depression, anxiety, nicotine dependence, alcohol dependence, and cardiovascular diseases.

Figure 1

Genotypes and allele frequencies in cases and controls and calculation of odds ratio.

Figure 2

Flowchart of the gene-based combined odds ratio (OR) methods for weighting evidence for schizophrenia candidate gene selection. OR is the ratio of allele carriers to non-carriers in cases compared with that in controls. In the figure, there are two alternative approaches to selecting representative OR of a study: selection (the largest OR value of all the markers being selected, step one in the SCOR method) and combination (the OR values of all markers being combined by the “meta” analysis, step one in the CCOR method).

Figure 3

Proportion difference (%) of gene expression in the 47 tissues between schizophrenia candidate genes and non-disease genes. The x-axis represents gene expression difference (%) between schizophrenia candidate genes and non-disease genes. The corresponding tissues are shown in the right panel.