Linkage analysis and association analysis in the presence of linkage using age at onset of COGA alcoholism data

Abstract

Complex disease mapping usually involves a combination of linkage and association techniques. Linkage analysis can scan the entire genome in a few hundred tests. Association tests may involve an even greater number of tests. However, association tests can localize the susceptibility genes more accurately. Using a recently developed combined linkage and association strategy, we analyzed a subset of the Collaborative Study on the Genetics of Alcoholism (COGA) data for the Genetic Analysis Workshop 14 (GAW14). In this analysis, we first employed linkage analysis based on frailty models that take into account age of onset information to establish which regions along the chromosome are likely to harbor disease susceptibility genes for alcohol dependence. Second, we used an association analysis by exploiting linkage disequilibrium to narrow down the peak regions. We also compare the methods with mean identity-by-descent tests and transmission/disequilibrium tests that do not use age of onset information.

Comparison of single-nucleotide polymorphisms and microsatellite markers for linkage analysis in the COGA and simulated data sets for Genetic Analysis Workshop 14: Presentation Groups 1, 2, and 3

“…There was more variation regarding which regions were investigated in the analyses of COGA data. Some participants conducted whole-genome scans with both types of markers Ma et al, 2005;Tayo et al, 2005;Wang et al, 2005;Yang et al, 2005a;Yu et al, 2005;Zhang et al, 2005;Zhong and Zhang, 2005]. Others restricted their analyses to a particular region, chromosome, or chromosomes, with choice of such regions generally based on prior findings.…”

“…In order to reduce heterogeneity, four groups restricted the sample to white, non-Hispanic study participants [Klein et al, 2005;Levinson and Holmans, 2005;Ma et al, 2005;Nsengimana et al, 2005], while one group stratified the sample into nonblack and nonwhite populations [Yang et al, 2005b]. Other groups used the full samples Wang et al, 2005;Zhong and Zhang, 2005]. Among these, some controlled for potential confounding on ethnicity .…”

“…These strategies identified evidence for linkage with initial MS marker scans, and were typically able to refine localizations or identify associations in subsequent analyses with SNPs. Instead of comparing SNPs and MS in parallel linkage scans, Zhong and Zhang [2005] first conducted a linkage scan of age-of-onset information with frailty models using MS markers. They followed this initial scan with an association study based on SNP makers.…”

“…Namkung et al [2005] used ALDX1 and ALDX2 jointly to establish affection status. Tayo et al [2005] used age of onset of alcoholism only, and Zhong and Zhang [2005] analyzed both the age of onset of alcoholism and the qualitative traits. Nsengimana et al [2005] used the qualitative trait and simulated a trait based on ALDX1.…”

“Higher order” addiction molecular genetics: Convergent data from genome-wide association in humans and mice

“…That is, no locus individually appears to contribute a substantial fraction of the vulnerability to any addictive substance. There is a caveat: these data come from subjects that largely have European ethnic/racial backgrounds [25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41]. Nevertheless, as with many complex human disorders in which initial hopes for a tractable underlying genetic architecture supported use of linkage approaches, linkage peaks may be more likely to arise when polygenes that each contribute modest amounts to addiction vulnerability happen to lie near each other on human chromosomes rather than when there is a single gene variant of major effect for addiction vulnerability [42].…”