Pharmacogenomics of HIV Therapy

HIV治疗的药物基因组学

• 批准号: 7559048
• 负责人: David W Haas
• 金额: $ 83.61万
• 依托单位: VANDERBILT UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-07-08 至 2013-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7559048
• 关键词: AIDS clinical trial group; Abbreviations; Acquired Immunodeficiency Syndrome; Adult; Advisory Committees; Affect; Anti-Retroviral Agents; Antiviral Agents; Appendix; Area; Arts; Caring; Charge; Class; Clinical; Clinical Trials; Cohort Analysis; Collaborations; Communicable Diseases; Communities; Complement; Comprehension; Computing Methodologies; Country; DNA; DNA Library; Data; Data Analyses; Disease; Drug toxicity; Fostering; Funding; Gene Frequency; Genes; Genetic; Genetic Polymorphism; Genetic Variation; Genetic screening method; Genomics; Genotype; Goals; Guidelines; HIV; HIV therapy; HIV-1; Health Policy; Health Services Accessibility; Human; Human Genetics; Individual; Infection; Interdisciplinary Study; Knowledge; Leadership; Life; Medicine; Metabolism; Modeling; Morbidity - disease rate; Multi-Drug Resistance; Names; Nature; Outcome; Participant; Persons; Pharmaceutical Preparations; Pharmacogenomics; Policies; Population; Positioning Attribute; Predictive Value; Principal Investigator; Public Health; Randomized; Randomized Clinical Trials; Recording of previous events; Research; Research Personnel; Resources; Single Nucleotide Polymorphism; Site; System; Testing; Therapeutic; Toxic effect; Translating; Treatment Protocols; Treatment outcome; United States; Variant; Viral; Virus; Work; absorption; antiretroviral therapy; base; bench to bedside; cost effectiveness; design; drug metabolism; genetic association; genetic variant; improved; member; mortality; novel strategies; pandemic disease; predictive modeling; prospective; repository; response

DESCRIPTION (provided by applicant): Access to potent antiretroviral drugs markedly reduces acquired immunodeficiency syndrome (AIDS) morbidity and mortality. However, there is considerable interindividual variability in response to human immunodeficiency virus type 1 (HIV-1) therapy regarding both efficacy and toxicity. Variable responses to medications are influenced, at least in part, by frequent human genetic variants that affect drug metabolism and drug disposition. Because suboptimal response can have devastating consequences for individuals and populations, defining the predictive value of human genetics for HIV treatment response has far-reaching implications. The pace of genomic discovery relevant to HIV therapeutics has been relatively slow and fragmented. Efficiently moving HIV pharmacogenomics from bench to bedside to community will be greatly facilitated by an approach that spans antiretroviral drugs and drug classes so that persons affected by HIV worldwide may benefit from the human genomic revolution. The proposed studies will determine the utility of human pharmacogenomic testing for clinical HIV care. The overarching hypothesis is that knowledge of associations between human genetic variants and HIV treatment responses will improve HIV treatment outcomes. This proposal will focus on genes relevant to drug absorption, distribution, metabolism, and elimination (ADME), complemented by selected non-ADME polymorphisms. This will be accomplished through analyses of data and DNA from over 5,000 participants from prospective clinical trials. Predictive models for responses to antiretroviral therapies will be developed based on knowledge of human genetic variants. Results of these analyses may also inform the design of a prospective randomized clinical trial to test whether HIV treatment responses will improve when human genetic testing informs prescribing. This work may ultimately result in better individualized therapy (personalized medicine), and improved antiretroviral treatment guidelines for persons living in resource-limited countries worldwide. To maximize impact and value added, this project will be a platform for collaboration with other investigators. PUBLIC HEALTH RELEVANCE The AIDS pandemic is one of the greatest public health infectious diseases challenges in history. There are approximately 1 million individuals in the US and 40 million worldwide living with HIV/AIDS. Understanding how human genetic differences predict treatment response to HIV medications may help inform public health policy decisions about the safest and most effective use of antiretroviral regimens in the US and worldwide.

描述（由申请人提供）：获得有效的抗逆转录病毒药物可显着降低获得性免疫缺陷综合症（艾滋病）的发病率和死亡率。然而，在疗效和毒性方面，人类免疫缺陷病毒 1 型 (HIV-1) 治疗的反应存在相当大的个体差异。对药物的不同反应至少部分受到影响药物代谢和药物处置的频繁人类遗传变异的影响。由于次优反应可能对个人和人群产生毁灭性后果，因此定义人类遗传学对 HIV 治疗反应的预测价值具有深远的影响。与艾滋病毒治疗相关的基因组发现的步伐相对缓慢且分散。跨越抗逆转录病毒药物和药物类别的方法将极大地促进艾滋病毒药物基因组学从实验室到临床到社区的有效发展，从而使全世界受艾滋病毒影响的人可以从人类基因组革命中受益。拟议的研究将确定人类药物基因组学测试在临床艾滋病毒护理中的效用。总体假设是，了解人类遗传变异与艾滋病毒治疗反应之间的关联将改善艾滋病毒治疗结果。该提案将重点关注与药物吸收、分布、代谢和消除 (ADME) 相关的基因，并辅以选定的非 ADME 多态性。这将通过对来自前瞻性临床试验的 5,000 多名参与者的数据和 DNA 进行分析来完成。将根据人类遗传变异的知识开发抗逆转录病毒疗法反应的预测模型。这些分析的结果还可以为前瞻性随机临床试验的设计提供信息，以测试当人类基因检测为处方提供信息时，艾滋病毒治疗反应是否会改善。这项工作最终可能会为生活在全球资源有限国家的人们带来更好的个体化治疗（个体化医疗）和改进的抗逆转录病毒治疗指南。为了最大限度地提高影响和附加值，该项目将成为与其他研究人员合作的平台。公共卫生相关性 艾滋病大流行是历史上最大的公共卫生传染病挑战之一。美国大约有 100 万人，全世界大约有 4000 万人感染艾滋病毒/艾滋病。了解人类遗传差异如何预测对艾滋病毒药物的治疗反应可能有助于为公共卫生政策决策提供信息，以决定美国和全世界最安全、最有效地使用抗逆转录病毒疗法。