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Mol Psychiatry ; 14(8): 755-63, 2009 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-19488044


To identify bipolar disorder (BD) genetic susceptibility factors, we conducted two genome-wide association (GWA) studies: one involving a sample of individuals of European ancestry (EA; n=1001 cases; n=1033 controls), and one involving a sample of individuals of African ancestry (AA; n=345 cases; n=670 controls). For the EA sample, single-nucleotide polymorphisms (SNPs) with the strongest statistical evidence for association included rs5907577 in an intergenic region at Xq27.1 (P=1.6 x 10(-6)) and rs10193871 in NAP5 at 2q21.2 (P=9.8 x 10(-6)). For the AA sample, SNPs with the strongest statistical evidence for association included rs2111504 in DPY19L3 at 19q13.11 (P=1.5 x 10(-6)) and rs2769605 in NTRK2 at 9q21.33 (P=4.5 x 10(-5)). We also investigated whether we could provide support for three regions previously associated with BD, and we showed that the ANK3 region replicates in our sample, along with some support for C15Orf53; other evidence implicates BD candidate genes such as SLITRK2. We also tested the hypothesis that BD susceptibility variants exhibit genetic background-dependent effects. SNPs with the strongest statistical evidence for genetic background effects included rs11208285 in ROR1 at 1p31.3 (P=1.4 x 10(-6)), rs4657247 in RGS5 at 1q23.3 (P=4.1 x 10(-6)), and rs7078071 in BTBD16 at 10q26.13 (P=4.5 x 10(-6)). This study is the first to conduct GWA of BD in individuals of AA and suggests that genetic variations that contribute to BD may vary as a function of ancestry.

Afro-Americanos/genética , Transtorno Bipolar/genética , Predisposição Genética para Doença/genética , Estudo de Associação Genômica Ampla , Adolescente , Adulto , Transtorno Bipolar/etnologia , Estudos de Casos e Controles , Estudos de Coortes , Grupo com Ancestrais do Continente Europeu , Feminino , Genoma Humano , Haplótipos , Humanos , Masculino , Pessoa de Meia-Idade , Polimorfismo de Nucleotídeo Único , Valores de Referência , Adulto Jovem
Ann Hum Genet ; 72(Pt 6): 834-47, 2008 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-18702637


Discovering statistical correlation between causal genetic variation and clinical traits through association studies is an important method for identifying the genetic basis of human diseases. Since fully resequencing a cohort is prohibitively costly, genetic association studies take advantage of local correlation structure (or linkage disequilibrium) between single nucleotide polymorphisms (SNPs) by selecting a subset of SNPs to be genotyped (tag SNPs). While many current association studies are performed using commercially available high-throughput genotyping products that define a set of tag SNPs, choosing tag SNPs remains an important problem for both custom follow-up studies as well as designing the high-throughput genotyping products themselves. The most widely used tag SNP selection method optimizes the correlation between SNPs (r(2)). However, tag SNPs chosen based on an r(2) criterion do not necessarily maximize the statistical power of an association study. We propose a study design framework that chooses SNPs to maximize power and efficiently measures the power through empirical simulation. Empirical results based on the HapMap data show that our method gains considerable power over a widely used r(2)-based method, or equivalently reduces the number of tag SNPs required to attain the desired power of a study. Our power-optimized 100k whole genome tag set provides equivalent power to the Affymetrix 500k chip for the CEU population. For the design of custom follow-up studies, our method provides up to twice the power increase using the same number of tag SNPs as r(2)-based methods. Our method is publicly available via web server at

Predisposição Genética para Doença , Técnicas Genéticas , Genoma Humano , Polimorfismo de Nucleotídeo Único , Frequência do Gene , Humanos , Desequilíbrio de Ligação , Modelos Estatísticos