Statistical, population genetics and genetic epidemiology

统计、群体遗传学和遗传流行病学

• 批准号: 7968195
• 负责人: dmitri v zaykin
• 金额: $ 32.24万
• 依托单位: NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7968195
• 关键词: Accounting; Acute; Address; Adverse effects; Alleles; Bypass; Chromosome Mapping; Chromosomes; Collaborations; Control Groups; Data; Data Set; Development; Diagnostic tests; Disease; Disease susceptibility; Distant; Drowning; Environmental Exposure; Family; Frequencies; Gene Frequency; Genetic; Genetic Polymorphism; Genetic Variation; Genome; Genome Scan; Haplotypes; Human; Human Genetics; Individual; Individual Differences; Investigation; Joints; Lead; Linkage Disequilibrium; Maps; Medicine; Methodology; Methods; Morphine; Opiates; Opioid; Opioid Analgesics; Pain; Parkinson Disease; Partner in relationship; Pharmaceutical Preparations; Phase; Population; Population Genetics; Public Health; Reaction; Research; Risk; Sampling; Signal Transduction; Statistical Methods; Stimulus; Stratification; Sum; Testing; Variant; base; case control; chronic pain; design; disorder prevention; genetic association; genetic epidemiology; genetic variant; genome wide association study; health related quality of life; improved; insight; mu opioid receptors; novel; novel strategies; receptor; response; trait

The main theme of this research is on haplotype, multilocus and general genetic association methods. We have been developing haplotype association mapping approach that relax population assumptions, such as random mating, and bypass estimation of the haplotype phase. Compared to competitors, the approach gains substantial power under low linkage disequilibrium and when there is non-independence of haplotypic effects. The approach is based on estimation of joint frequencies of alleles at multiple genetic loci. The difference between traditional approaches and this approach lies in that the traditional approaches consider joint frequencies of alleles that reside on the same haplotype, whereas we consider the sum of joint frequencies that reside on the same as well as on two different haplotypes within individuals. This allows to capture direct haplotypic effects as well as joint effects of alleles that reside on two different haplotypes within an individuals, which reflect the diplotypic effects. The approach is applicable for testing interactions between distant genetic loci. For example, it can be applied to sets of SNPs that span separate haplotype blocks, and it is also useful for detecting interactions between genetic loci that reside on different chromosomes. While the method is powerful in detecting direct haplotypic effects, it is also capable of capturing epistatic effects due to interactions between two haplotypes in a diplotype. Covariates, such as environmental exposures, can be readily incorporated with this approach. The main development has been around the case-control and random population sampling designs. There are straightforward extensions to family-based association mapping designs. These extensions make the approach robust against confounding due to population stratification. We have applied the method in study concerned with discovery of novel functional variants in the mu-opioid receptor, which is the principal receptor target for both endogenous and exogenous opioid analgesics. There are substantial individual differences in human responses to painful stimuli and to opiate drugs that are attributed to genetic variations in the mu-opioid receptor. Opioid drugs are widely used to treat both acute and chronic pain, but the benefits are undermined due to individual variation in side effects and the degree of response. Our approach helped to identify novel genetic variants that offer insight into individual responses to morphine. This may lead to development of a new class of opioids and to diagnostic tests for prediction of individual risk for inadequate or adverse response. In an ongoing collaboration with Dr. Honglei Chen this method is being applied to Parkinson's disease genome scan data. Other ongoing research include development of statistical approaches to address multiplicity issues in whole genome scans. This research includes investigation of novel approaches aimed to improve ranks of true positives in whole genome scans (in collaboration with Dr. Jack Taylor), and development of new tests for the shared control design, where a common control group of individuals is contrasted against several independent case groups that may have the same, different, or related diseases.

本研究的主题是单倍型，多位点和一般的遗传关联方法。我们一直在开发单倍型关联映射方法，放宽人口假设，如随机交配，并绕过估计的单倍型阶段。与竞争者相比，该方法在低连锁不平衡和单倍型效应不独立的情况下获得了很大的优势。该方法是基于多个遗传位点的等位基因的联合频率的估计。传统方法和这种方法之间的区别在于，传统方法考虑的是位于同一单倍型上的等位基因的联合频率，而我们考虑的是个体内位于同一单倍型以及两个不同单倍型上的联合频率之和。这允许捕获直接单倍型效应以及个体内存在于两个不同单倍型上的等位基因的联合效应，其反映了双倍型效应。该方法适用于检测远缘遗传位点之间的相互作用。例如，它可以应用于跨越单独的单倍型块的SNP组，并且它也可用于检测位于不同染色体上的遗传基因座之间的相互作用。虽然该方法在检测直接单倍型效应方面是强大的，但它也能够捕获由于双倍型中两个单倍型之间的相互作用而引起的上位效应。协变量，如环境暴露，可以很容易地与这种方法相结合。主要的发展是围绕病例对照和随机人口抽样设计。基于家族的关联映射设计有一些简单的扩展。这些扩展使得该方法对由于人口分层而引起的混淆具有鲁棒性。我们已经将该方法应用于有关发现μ阿片受体中的新功能变体的研究中，μ阿片受体是内源性和外源性阿片类镇痛剂的主要受体靶点。人类对疼痛刺激和阿片类药物的反应存在很大的个体差异，这归因于μ阿片受体的遗传变异。阿片类药物被广泛用于治疗急性和慢性疼痛，但由于副作用和反应程度的个体差异，其益处受到破坏。 我们的方法有助于识别新的遗传变异，从而深入了解个体对吗啡的反应。这可能会导致开发新的阿片类药物，并进行诊断测试，以预测个人的风险不足或不良反应。在与Honglei Chen博士的持续合作中，这种方法正在应用于帕金森病基因组扫描数据。 其他正在进行的研究包括开发统计方法，以解决全基因组扫描中的多重性问题。这项研究包括调查旨在提高全基因组扫描中真阳性率的新方法（与Jack Taylor博士合作），以及开发用于共享控制设计的新测试，其中一个共同的对照组与几个独立的病例组进行对比，这些病例组可能具有相同，不同或相关的疾病。