Department of Psychiatry, Indiana University School of Medicine, Indianapolis, Indiana, USA.
Am J Med Genet B Neuropsychiatr Genet. 2010 Jun 5;153B(4):850-77. doi: 10.1002/ajmg.b.31087.
We previously proposed and provided proof of principle for the use of a complementary approach, convergent functional genomics (CFG), combining gene expression and genetic data, from human and animal model studies, as a way of mining the existing GWAS datasets for signals that are there already, but did not reach significance using a genetics-only approach [Le-Niculescu et al., 2009b]. CFG provides a fit-to-disease prioritization of genes that leads to generalizability in independent cohorts, and counterbalances the fit-to-cohort prioritization inherent in classic genetic-only approaches, which have been plagued by poor reproducibility across cohorts. We have now extended our previous work to include more datasets of GWAS, and more recent evidence from other lines of work. In essence our analysis is the most comprehensive integration of genetics and functional genomics to date in the field of bipolar disorder. Biological pathway analyses identified top canonical pathways, and epistatic interaction testing inside these pathways has identified genes that merit future follow-up as direct interactors (intra-pathway epistasis, INPEP). Moreover, we have put together a panel of best P-value single nucleotide polymorphisms (SNPs), based on the top candidate genes we identified. We have developed a genetic risk prediction score (GRPS) based on our panel, and demonstrate how in two independent test cohorts the GRPS differentiates between subjects with bipolar disorder and normal controls, in both European-American and African-American populations. Lastly, we describe a prototype of how such testing could be used to categorize disease risk in individuals and aid personalized medicine approaches, in psychiatry and beyond.
我们之前提出并提供了使用互补方法的原理证明，即收敛功能基因组学（CFG），结合人类和动物模型研究中的基因表达和遗传数据，作为挖掘现有 GWAS 数据集信号的一种方法，这些信号已经存在，但仅使用遗传方法无法达到显著水平[Le-Niculescu 等人，2009b]。CFG 为与疾病相关的基因进行了优先排序，使其在独立队列中具有可推广性，并平衡了经典遗传方法固有的与队列相关的优先排序，经典遗传方法在队列之间的可重复性一直存在问题。我们现在已经将我们之前的工作扩展到包括更多的 GWAS 数据集，以及来自其他工作的最新证据。本质上，我们的分析是迄今为止在双相情感障碍领域对遗传学和功能基因组学进行的最全面整合。生物途径分析确定了顶级经典途径，并且这些途径内的上位相互作用测试确定了值得进一步关注的作为直接相互作用物的基因（途径内上位相互作用，INPEP）。此外，我们根据我们确定的顶级候选基因，组合了一组最佳 P 值单核苷酸多态性（SNP）。我们基于我们的面板开发了一个遗传风险预测评分（GRPS），并证明了在两个独立的测试队列中，GRPS 如何区分双相情感障碍患者和正常对照者，包括欧洲裔和非裔美国人。最后，我们描述了如何使用这种测试来对个体的疾病风险进行分类并辅助精神病学和其他领域的个性化医疗方法的原型。
