Expression genetics of pharmacogenes

项目总结 我的研究计划的首要目标是全面了解 药物代谢，使药物治疗更有效，毒性更低。细胞色素P450药物- 代谢酶是目前代谢近70%药物的主要酶。 所使用的药物因人而异，需要进行个性化的药物治疗。遗传 影响药物代谢的因素很多，一些dmCyp的变异体被用于临床。 预测代谢物状态的生物标志物。然而，它们变量的基本原理 表达/活动远不清楚。导致氨基酸序列改变的变异已经被研究过了。 广泛存在，但它们未能解释观察到的所有差异。另一方面，技术挑战 到目前为止，对影响dmCyp的mRNA和蛋白表达的因素的研究有限。多数 DmCyp是具有复杂基因组结构和多样化遗传变异的多基因簇。使用 在NIGMS资金的支持下，我们采用了创新的方法，并解剖了建筑群 多基因簇(如CYP3A)的基因组结构和识别的隐藏顺式作用调控 影响基因表达的变体(例如，3A4、3A5和3A43)。我们的结果表明，单一的变种 可以对同一基因座上的两个基因(如3A4和3A43)产生相反的影响，而多个变种 可以以相同或相反的方向(例如，CYP7A1和CYP2D6)调控单个基因，表明 基因簇内复杂的结构域-结构域相互作用和变异体之间的上位性。是这样的 复杂性通常逃脱了基于全基因组关联研究的发现，并需要专门的 这里提出了一种方法。随着对CYP3A集群的成功剖析，我们现在计划扩大和 在接下来的五年里分析其他dmCYP基因簇。此外，我们最近还确定了 无配体雌激素受体α(ESR1)是细胞色素P3A4和其他许多dmCYP基因的主要调节者。 影响以ESR1为中心的调控网络的遗传、表观遗传和非遗传因素可能会影响 DmCYP基因的表达和反式作用机制的酶活性。我们计划使用ESR1基因敲除 IPSC向肝细胞分化以鉴定ESR1为中心的调控网络及其影响因素 调节ESR1和dmCyps的表达。已鉴定的功能顺式和反式作用基因变体和 表观遗传因素，包括非编码RNA，将在人类肝脏样本中进行测试，以确定它们对 DmCYP的mRNA和蛋白表达。已确定的变异的临床意义将被测试。 通过协作进行临床队列研究。以我在药物遗传学生物标记物发现方面的记录， 从研究复杂的多基因簇、新技术的可用性和来自 在生物信息学、蛋白质组学和药物遗传学实施方面拥有专业知识的合作者，我很好 有能力承担拟议的研究。结果将立即进行临床转化，从而导致 更准确的生物标志物，用于指导个性化药物治疗。

PROJECT SUMMARY The overarching goal of my research program is to gain a comprehensive understanding of the variability in drug metabolism to make drug therapies more effective and less toxic. The cytochrome P450 drug- metabolizing enzymes (dmCYPs) are the main enzymes that metabolize nearly 70% of the drugs currently used, which are highly variable from person to person, necessitating personalized drug therapy. Genetic factors significantly affect the drug metabolism, and the variants of some dmCYPs are used as clinical biomarkers to predict the metabolizer status. However, the underlying principles of their variable expression/activity are far from clear. Variants that result in altered amino acid sequences have been studied extensively, but they fail to account for all the differences observed. On the other hand, technical challenges have thus far limited the studies on factors that affect mRNA and protein expression of dmCYPs. Most dmCYPs are multi-gene clusters with complex genomic architecture and diverse genetic variations. With the support of NIGMS funding, we have adopted innovative methodologies and dissected the complex genomic architecture of multiple gene clusters (e. g., CYP3A) and identified hidden cis-acting regulatory variants that affect gene expression (e. g., 3A4, 3A5 and 3A43). Our results demonstrate that a single variant can have opposing effects on two genes in the same locus (e. g, 3A4, and 3A43), while more than one variant can regulate a single gene in the same or opposite direction (e. g., CYP7A1 and CYP2D6) indicating complex domain-domain interactions within the gene cluster and epistasis between variants. Such complexity usually escapes genome wide association study based discovery and warrants a dedicated approach proposed here. With the success of dissecting the CYP3A cluster, we now plan to expand and analyze the other dmCYP gene clusters over the next five years. Furthermore, we have recently identified ligand-free estrogen receptor alpha (ESR1) as a master regulator of CYP3A4 and many other dmCYP genes. Genetic, epigenetic, and non-genetic factors that affect ESR1-centered regulatory network will likely affect dmCYP gene expression and enzyme activity via trans-acting mechanisms. We plan to use ESR1-knockout hepatocytes differentiated from iPSC to characterize ESR1-centered regulatory network and to identify factors regulating ESR1 and dmCYPs expression. The identified functional cis and trans-acting genetic variants and epigenetic factors, including non-coding RNAs, will be tested in human liver samples for their impact on mRNA and protein expression of dmCYPs. The clinical significance of the identified variants will be tested in clinical cohort via collaboration. With my track record of pharmacogenetics biomarker discovery, insights gained from studying complex multi-gene clusters, availability of novel technologies, and support from collaborators with expertise in bioinformatics, proteomics and pharmacogenetics implementation, I am well positioned to undertake the proposed studies. The outcome will have immediate clinical translation leading to more accurate biomarkers for guiding personalized drug therapy.