Ordered subsets linkage analysis of antisocial behavior in substance use disorder among participants in the Collaborative Study on the Genetics of Alcoholism

Confirmation of prior evidence of genetic susceptibility to alcoholism in a genome-wide association study of comorbid alcoholism and bipolar disorder

OBJECTIVES

Alcoholism and affective disorders are both strongly comorbid and heritable. We have investigated the genetic comorbidity between bipolar affective disorder and alcoholism.

METHODS

A genome-wide allelic association study of 506 patients from the University College London bipolar disorder case-control sample and 510 ancestrally matched supernormal controls. One hundred forty-three of the bipolar patients fulfilled the Research Diagnostic Criteria diagnosis of alcoholism. A total of 372 193 single nucleotide polymorphisms (SNPs) were genotyped. Genes previously shown to be associated with alcoholism and addiction phenotypes were then tested for association in the bipolar alcoholic sample using gene-wise permutation tests of all SNPs genotyped within a 50-kb region flanking each gene.

RESULTS

Several central nervous system genes showed significant (P<0.05) gene-wise evidence of association with bipolar alcoholism. The genes implicated, which replicated genes previously shown to be associated with alcoholism were: cadherin 11, collagen type 11 α2, neuromedin U receptor 2, exportin7, and semaphorin-associated protein 5A. The SNPs most strongly implicated in bipolar alcoholism, but, which did not meet conventional genome-wide significance criteria were the insulin-like growth factor-binding protein 7, carboxypeptidase O, cerebellin 2, and the cadherin 12 genes.

CONCLUSION

We have confirmed the role of some genes previously shown to be associated with alcoholism in the comorbid bipolar alcoholism subgroup. In this subgroup, bipolar disorder may lower the threshold for the phenotypic expression of these alcoholism susceptibility genes. We also show that some genes may independently increase susceptibility to affective disorder and alcoholism.

Ordered subset analysis for case-control studies

Genetic heterogeneity, which may manifest on a population level as different frequencies of a specific disease susceptibility allele in different subsets of patients, is a common problem for candidate gene and genome-wide association studies of complex human diseases. The ordered subset analysis (OSA) was originally developed as a method to reduce genetic heterogeneity in the context of family-based linkage studies. Here, we have extended a previously proposed method (OSACC) for applying the OSA methodology to case-control datasets. We have evaluated the type I error and power of different OSACC permutation tests with an extensive simulation study. Case-control datasets were generated under two different models by which continuous clinical or environmental covariates may influence the relationship between susceptibility genotypes and disease risk. Our results demonstrate that OSACC is more powerful under some disease models than the commonly used trend test and a previously proposed joint test of main genetic and gene-environment interaction effects. An additional unique benefit of OSACC is its ability to identify a more informative subset of cases that may be subjected to more detailed molecular analysis, such as DNA sequencing of selected genomic regions to detect functional variants in linkage disequilibrium with the associated polymorphism. The OSACC-identified covariate threshold may also improve the power of an additional dataset to replicate previously reported associations that may only be detectable in a fraction of the original and replication datasets. In summary, we have demonstrated that OSACC is a useful method for improving SNP association signals in genetically heterogeneous datasets.

The multidimensionality of schizotypy in nonpsychotic relatives of patients with schizophrenia and its applications in ordered subsets linkage analysis of schizophrenia

This study aimed to examine the multidimensionality of schizotypy and validate the structure using ordered subset linkage analyses on information from both relatives' schizotypy and probands' schizophrenia symptoms. A total of 203 and 1,310 nonpsychotic first-degree relatives from simplex and multiplex schizophrenia families, respectively, were interviewed with the Diagnostic Interview for Genetic Studies, which contains a modified Structured Interview for Schizotypy. Using Mplus program with categorical factor indicators, a four-factor model (Negative Schizotypy, Positive Schizotypy, Interpersonal Sensitivity, and Social Isolation/Introversion) was extracted by exploratory factor analysis from relatives of simplex families and was confirmed in relatives of multiplex families. The validity of each factor was supported by distinct linkage findings resulting from ordered subset analysis based on different combinations of schizophrenia-schizotypy factors. Six chromosomal regions with significant increase in nonparametric linkage z score (NPL-Z) were found as follows: 15q21.1 (NPL-Z = 3.60) for Negative Schizophrenia-Negative Schizotypy, 10q22.3 (NPL-Z = 3.83) and 15q21.3 (NPL-Z = 3.36) for Negative Schizophrenia-Social Isolation/Introversion, 5q14.2 (NPL-Z = 3.20) and 11q23.3 (NPL-Z = 3.31) for Positive Schizophrenia-Positive Schizotypy, and 4q32.1 (NPL-Z = 3.31) for Positive Schizophrenia-Interpersonal Sensitivity. The greatest NPL-Z of 3.83 on 10q22.3 in the subset was significantly higher than the greatest one of 2.88 in the whole sample (empirical P-value = 0.04). We concluded that a consistent four-factor model of schizotypy could be derived in nonpsychotic relatives across families of patients with different genetic loadings in schizophrenia. Their differential relations to linkage signals have etiological implications and provide further evidence for their validity.