The challenge of detecting epistasis (G x G interactions): Genetic Analysis Workshop 16.

Interest is increasing in epistasis as a possible source of the unexplained variance missed by genome-wide association studies. The Genetic Analysis Workshop 16 Group 9 participants evaluated a wide variety of classical and novel analytical methods for detecting epistasis, in both the statistical and machine learning paradigms, applied to both real and simulated data. Because the magnitude of epistasis is clearly relative to scale of penetrance, and therefore to some extent, to the choice of model framework, it is not surprising that strong interactions under one model might be minimized or even disappear entirely under a different modeling framework.

Linkage and association analyses of type 2 diabetes/impaired glucose metabolism and adiponectin serum levels in Japanese Americans from Hawaii.

Type 2 diabetes is a common disorder associated with obesity. Lower plasma levels of adiponectin were associated with type 2 diabetes. Candidate regions on chromosomes 1 ( approximately 70 cM) and 14 ( approximately 30 cM) were evaluated for replication of suggestive linkage results for type 2 diabetes/impaired glucose homeostasis in an independent sample of Japanese Americans. Replication of independent linkage evidence for serum levels of adiponectin on chromosome 14 was also evaluated. We investigated 529 subjects from 175 sibships who were originally part of the Honolulu Heart Program. Analyses included nonparametric linkage and association using SAGE (Statistical Analysis for Genetic Epidemiology) and FBAT (family-based test of association) programs and Monte Carlo simulation of Fisher's exact test in SAS. For type 2 diabetes/impaired glucose metabolism, nominal linkage evidence (P < 0.02) followed-up by genotypic association (P = 0.016) was found with marker D14S297 at 31.8 cM; linkage analyses using only diabetes phenotype were also nominally significant at this marker (P < 0.02). Nominal evidence for genotypic association to adiponectin serum level phenotype (P = 0.04) was found with the marker D14S1032 at 23.2 cM. The present study was limited by relatively small sample size. Nevertheless, these results corroborate earlier studies, suggesting that further research is warranted in the candidate region approximately 30 cM on chromosome 14.

Importance sampling method of correction for multiple testing in affected sib-pair linkage analysis.

Using the Genetic Analysis Workshop 13 simulated data set, we compared the technique of importance sampling to several other methods designed to adjust p-values for multiple testing: the Bonferroni correction, the method proposed by Feingold et al., and naïve Monte Carlo simulation. We performed affected sib-pair linkage analysis for each of the 100 replicates for each of five binary traits and adjusted the derived p-values using each of the correction methods. The type I error rates for each correction method and the ability of each of the methods to detect loci known to influence trait values were compared. All of the methods considered were conservative with respect to type I error, especially the Bonferroni method. The ability of these methods to detect trait loci was also low. However, this may be partially due to a limitation inherent in our binary trait definitions.

Different models and single-nucleotide polymorphisms signal the simulated weak gene-gene interaction for a quantitative trait using haplotype-based and mixed models testing.

Knowledge of simulated genetic effects facilitates interpretation of methodological studies. Genetic interactions for common disorders are likely numerous and weak. Using the 200 replicates of the Genetic Analysis Workshop 16 (GAW16) Problem 3 simulated data, we compared the statistical power to detect weak gene-gene interactions using a haplotype-based test in the UNPHASED software with genotypic mixed model (GMM) and additive mixed model (AMM) mixed linear regression model in SAS. We assumed a candidate-gene approach where a single-nucleotide polymorphism (SNP) in one gene is fixed and multiple SNPs are at the second gene. We analyzed the quantitative low-density lipoprotein trait (heritability 0.7%), modulated by simulated interaction of rs4648068 from 4q24 and another gene on 8p22, where we analyzed seven SNPs. We generally observed low power calculated per SNP (

Evidence in an international sample of alcohol-dependent subjects of subgroups with specific symptom patterns of antisocial personality disorder.

BACKGROUND: An earlier latent class analysis (LCA) of the symptoms of antisocial personality disorder in alcohol-dependent subjects enrolled in the Montreal sample of the WHO/ISBRA Study on State and Trait Markers of Alcohol Use and Dependence suggested a three-class qualitative solution. The present analysis of a larger, international WHO/ISBRA sample provides evidence of a four-class solution with expanded symptomatic differentiation. METHODS: An unrestricted LCA of 15 antisocial behaviors expressed after 15 years of age was performed in 465 males with DSM-IV diagnosis of alcohol dependence, from the Montreal center (n = 120, overlapping the previous LCA), Helsinki (n = 80), São Paolo (n = 145), Sapporo (n = 22), and Sydney (n = 98); subjects were of various races, were ascertained from various sources, and showed a wide range of social adjustment. RESULTS: Four latent classes that appeared to differ qualitatively were identified. For descriptive purposes, the classes are termed socially adjusted adults (SAA, n = 197), antisocial work-adjusted adults (AWAA, n = 126), antisocial work-maladjusted adults (AWMA, n = 120), and antisocial aggressive adults (AAA, n = 23). The AAA class had the earliest age of onset for alcohol dependence, which decreased across classes. Proportion of alcohol-dependent first-degree relatives was low in the SAA class (13.6%), moderate in the AWAA and the AWMA classes (20.8% and 18.7% respectively), and high in the AAA class (33.3%). CONCLUSIONS: It is unknown if and to what extent racial, cultural, and ascertainment heterogeneity between collaborating centers might have influenced these analyses. The results presented here show qualitative differences among antisocial alcohol-dependent individuals in job adjustment and aggressive behavior, but only the latter distinction was relevant to familial alcohol dependence. Moreover, both the aggressive class and socially adjusted class differed in familial loading for alcohol dependence from the remaining two antisocial classes. These data provide improved empirical support for qualitative differentiation of aggressive from nonaggressive antisocial alcohol-dependent individuals and might also have nosological implications for antisocial personality disorder.