Molecular Neurobiology Branch, National Institutes of Health Intramural Research Program, National Institute on Drug Abuse, Baltimore, Maryland, United States of America.
PLoS One. 2010 Jan 21;5(1):e8832. doi: 10.1371/journal.pone.0008832.
Vulnerabilities to dependence on addictive substances are substantially heritable complex disorders whose underlying genetic architecture is likely to be polygenic, with modest contributions from variants in many individual genes. "Nontemplate" genome wide association (GWA) approaches can identity groups of chromosomal regions and genes that, taken together, are much more likely to contain allelic variants that alter vulnerability to substance dependence than expected by chance.
METHODOLOGY/PRINCIPAL FINDINGS: We report pooled "nontemplate" genome-wide association studies of two independent samples of substance dependent vs control research volunteers (n = 1620), one European-American and the other African-American using 1 million SNP (single nucleotide polymorphism) Affymetrix genotyping arrays. We assess convergence between results from these two samples using two related methods that seek clustering of nominally-positive results and assess significance levels with Monte Carlo and permutation approaches. Both "converge then cluster" and "cluster then converge" analyses document convergence between the results obtained from these two independent datasets in ways that are virtually never found by chance. The genes identified in this fashion are also identified by individually-genotyped dbGAP data that compare allele frequencies in cocaine dependent vs control individuals.
CONCLUSIONS/SIGNIFICANCE: These overlapping results identify small chromosomal regions that are also identified by genome wide data from studies of other relevant samples to extents much greater than chance. These chromosomal regions contain more genes related to "cell adhesion" processes than expected by chance. They also contain a number of genes that encode potential targets for anti-addiction pharmacotherapeutics. "Nontemplate" GWA approaches that seek chromosomal regions in which nominally-positive associations are found in multiple independent samples are likely to complement classical, "template" GWA approaches in which "genome wide" levels of significance are sought for SNP data from single case vs control comparisons.
对成瘾物质的依赖易感性是一种具有重要遗传基础的复杂疾病，其遗传结构可能是多基因的，少量个体基因的变异也可能发挥作用。“非模板”全基因组关联（GWA）方法可以识别出染色体区域和基因群体，这些区域和基因群体共同包含的等位基因变异更有可能改变对物质依赖的易感性，而不是随机发生的。
方法/主要发现：我们报告了两个独立的物质依赖与对照研究志愿者样本（n = 1620）的“非模板”全基因组关联研究 pooled 的结果，一个是欧洲裔美国人，另一个是非洲裔美国人，使用了 100 万个 SNP（单核苷酸多态性）Affymetrix 基因分型阵列。我们使用两种相关的方法评估这两个样本结果之间的一致性，这两种方法旨在寻找名义上阳性结果的聚类，并使用蒙特卡罗和置换方法评估显著性水平。“先聚类后一致”和“先一致后聚类”分析都记录了这两个独立数据集的结果之间的一致性，这种一致性几乎不可能是偶然发现的。以这种方式识别出的基因也可以通过单独基因分型的 dbGAP 数据来识别，这些数据比较了可卡因依赖个体与对照个体的等位基因频率。
结论/意义：这些重叠的结果确定了小的染色体区域，这些区域也可以通过来自其他相关样本的全基因组数据来识别，其程度远远超过了随机发现的程度。这些染色体区域包含了更多与“细胞黏附”过程相关的基因，比随机发现的要多。它们还包含了一些编码潜在抗成瘾药物治疗靶点的基因。寻找在多个独立样本中发现名义上阳性关联的染色体区域的“非模板”GWA 方法可能会补充经典的“模板”GWA 方法，后者寻求 SNP 数据从单个病例与对照比较中获得“全基因组”水平的显著性。
