The role of genetics in the etiology of schizophrenia

Abstract

Schizophrenia is a complex genetic disorder manifesting combined environmental and genetic causation. Recently, genome-wide association experiments yielded remarkable new experimental evidence that is leading to a better understanding of the genetic models and the biological risk factors involved in schizophrenia. These studies have discovered uncommon copy number variations (mainly deletions) and common single nucleotide polymorphisms with alleles associated with schizophrenia. The aggregate data provide support for polygenic inheritance and for genetic overlap of schizophrenia with autism and with bipolar disorder. It is anticipated that the application of a myriad of tools from systems biology, in combination with biological functional experiments, will lead to a delineation of biological pathways involved in the pathophysiology of schizophrenia, and eventually to new therapies.

Copyright 2010 Elsevier Inc. All rights reserved.

Figures

Figure 1

Quantile-quantile plot of observed vs. expected p-values for tag SNPs for fourteen schizophrenia candidate genes. Open circles represent the relationship between the expected (X-axis) and observed (Y-axis) p-values for pointwise nominal Armitage trend tests for the 433 SNPs that represent tags (at r2>0.8) for common SNPs in each of 14 tested genes (RGS4, DISC1, DTNBP1, STX7, TAAR6, PPP3CC, NRG1, DRD2, HTR2A, DAOA, AKT1, CHRNA7, COMT, and ARVCF). The solid line represents the null expectation. The observed distribution is within the 95% confidence interval of the null expectation, consistent with a lack of evidence in the tested sample for association with schizophrenia in the tested candidate genes. The lowest p-values are slightly below the line (less significant than expected), but still within the confidence interval. Reprinted with permission .

Figure 2

The combined p-values of three datasets (MGS, ISC, and SGENE) at the MHC region (~26~33Mb). The positions of the three histone gene clusters and NOTCH4 are indicated in the RefSeq track (top of the graph). The relative location of the maximum peak in each data set is indicated by a line below the p-value peaks. Cis-eQTL (with LOD >5) are shown below the graph with association −log p-values.