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Several genomewide screens indicated that chromosome 7q was linked to autistic disorder. FOXP2, located on 7q31, is a putative transcription factor containing a polyglutamine tract and a forkhead DNA binding domain. It is one member of the forkhead family who are known to be key regulators of embryogenesis. A point mutation at a highly conserved residue within the forkhead domain co-segregated with affected status in the KE family who was a unique three generation pedigree with a severe speech and language disorder and FOXP2 was directly disrupted by a translocation in an individual who had similar deficits as those of the KE family. Several studies have investigated the role of FOXP2 polymorphisms in autism and none of them found positive association. We performed a family-based association study of three single nucleotide polymorphisms (SNPs) of FOXP2 in 181 Chinese Han trios using the analyses of transmission/disequilibrium test (TDT) and haplotype. We found a significant association between autistic disorder and one SNP, as well as with specific haplotypes formed by this SNP with two other SNPs we investigated. Our findings suggest that the FOXP2 gene may be involved in the pathogenesis of autism in Chinese population.

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Frizzled 3 (FZD3) gene is located on chromosome 8p21, a region that has been implicated in schizophrenia in genetic linkage studies. The FZD3 is a transmembrane receptor required for Wnt signal transduction cascades that have been thought to be involved in producing the cytoarchitectural defects observed in schizophrenia. Previous work has showed a strong association between FZD3 locus and schizophrenia in family-based study. To confirm this issue further, we investigated a genetic association between four single nucleotide polymorphisms (SNPs) located in the FZD3 gene and schizophrenia by case-control study using polymerase chain reaction (PCR)-based restriction fragment length polymorphism (RFLP) in the Chinese Han population. Our studies showed the SNPs rs2323019 and rs880481 have significant differences in both genotype and allele frequencies between control subjects and schizophrenic patients (rs2323019: Allele A > G, chi2 = 6.7277, df = 1, P = 0.0095; Genotype, chi2 = 10.6583, df = 2, P = 0.0049; rs880481: Allele A > G, chi2 = 10.3945, df = 1, P = 0.0013; Genotype, chi2 = 16.8049, df = 2, P = 0.0002). In addition, we constructed three-locus haplotypes to test their association with schizophrenia. The globe chi-squared test for haplotype analysis showed a significant association (chi2 = 66.38, df = 7, P < 0.000001). These results suggested that the FZD3 gene might be involved in the predisposition to schizophrenia.

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The genetic basis of complex diseases is expected to be highly heterogeneous, with many disease genes, where each gene by itself has only a small effect. Based on the nonlinear contributions of disease genes across the genome to complex diseases, we introduce the concept of single nucleotide polymorphism (SNP) synergistic blocks. A two-stage approach is applied to detect the genetic association of synergistic blocks with a disease. In the first stage, synergistic blocks associated with a complex disease are identified by clustering SNP patterns and choosing blocks within a cluster that minimize a diversity criterion. In the second stage, a logistic regression model is given for a synergistic block. Using simulated case-control data, we demonstrate that our method has reasonable power to identify gene-gene interactions. To further evaluate the performance of our method, we apply our method to 17 loci of four candidate genes for paranoid schizophrenia in a Chinese population. Five synergistic blocks are found to be associated with schizophrenia, three of which are negatively associated (odds ratio, OR \ 0.3, P \ 0.05), while the others are positively associated (OR [ 2.0, P \ 0.05). The mathematical models of these five synergistic blocks are presented. The results suggest that there may be interactive effects for schizophrenia among variants of the genes neuregulin 1 (NRG1, 8p22-p11), G72 (13q34), the regulator of G-protein signaling-4 (RGS4, 1q21-q22) and frizzled 3 (FZD3, 8p21). Using synergistic blocks, we can reduce the dimensionality in a multi-locus association analysis, and evaluate the sizes of interactive effects among multiple disease genes on complex phenotypes.