RESUMO
The discordance in results of independent genome-wide association studies (GWAS) indicates the potential for Type I and Type II errors. We assessed the repeatibility of current Affymetrix technologies that support GWAS. Reasonable reproducibility was observed for both raw intensity and the genotypes/copy number variants. We also assessed consistencies between different SNP arrays and between genotype calling algorithms. We observed that the inconsistency in genotypes was generally small at the specimen level. To further examine whether the differences from genotyping and genotype calling are possible sources of variation in GWAS results, an association analysis was applied to compare the associated SNPs. We observed that the inconsistency in genotypes not only propagated to the association analysis, but was amplified in the associated SNPs. Our studies show that inconsistencies between SNP arrays and between genotype calling algorithms are potential sources for the lack of reproducibility in GWAS results.
Assuntos
Estudo de Associação Genômica Ampla/estatística & dados numéricos , Genótipo , Haplótipos/genética , Algoritmos , DNA/genética , Interpretação Estatística de Dados , Dosagem de Genes , Humanos , Análise de Sequência com Séries de Oligonucleotídeos/métodos , Polimorfismo de Nucleotídeo Único , Reprodutibilidade dos TestesRESUMO
Summary This molecular epidemiology study integrated questionnaire and genotype information to examine a disease susceptibility hypothesis. The study was based on a previously reported association demonstrated between a single nucleotide polymorphism (SNP) identified as A-564G within the promoter of the proteinase-3 gene (PRTN3) and the autoimmune disease Wegener's granulomatosis (WG). To further examine the strength of this association, we employed a family-based design in which the inheritance of alternate alleles could be ascertained from the parents of affected and unaffected progeny. Genotype information for the study participants was derived from DNA samples from participants who collected buccal cells using a harvesting method that was non-invasive and self-administered. A brief questionnaire captured demographic data on the participants, the family relationships between participants, and the prevalence of autoimmune disease among family members. Samples were obtained on 132 individuals representing 43 WG cases and 89 unaffected controls. Thirty-four nuclear families containing at least one unaffected sibling or parent of a WG case were represented in this sample. We found no evidence for an association between A-564G and the likelihood of a WG diagnosis. We examined five additional SNPs and a sixth SNP haplotype within the PRTN3 promoter region in a family-based association analysis and found no evidence that mutations within PRTN3 are associated with WG diagnosis.
Assuntos
Granulomatose com Poliangiite/genética , Doenças Autoimunes/epidemiologia , Estudos de Casos e Controles , Demografia , Feminino , Frequência do Gene/genética , Marcadores Genéticos/genética , Predisposição Genética para Doença/genética , Granulomatose com Poliangiite/diagnóstico , Haplótipos/genética , Humanos , Masculino , Mieloblastina , Polimorfismo de Nucleotídeo Único/genética , Prevalência , Regiões Promotoras Genéticas/genética , Serina Endopeptidases/genética , Inquéritos e QuestionáriosRESUMO
The simulated sequence data for the Genetic Analysis Workshop 12 were analyzed using data mining techniques provided by SAS ENTERPRISE MINER Release 4.0 in addition to traditional statistical tests for linkage and association of genetic markers with disease status. We examined two ways of combining these approaches to make use of the covariate data along with the genotypic data. The result of incorporating data mining techniques with more classical methods is an improvement in the analysis, both by correctly classifying the affection status of more individuals and by locating more single nucleotide polymorphisms related to the disease, relative to analyses that use classical methods alone.
