Statistical Models of Maternal and Offspring Genetic Effects For Risk of Disease
母亲和后代遗传效应对疾病风险的统计模型
基本信息
- 批准号:7849557
- 负责人:
- 金额:$ 1.22万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2009
- 资助国家:美国
- 起止时间:2009-07-01 至 2010-09-06
- 项目状态:已结题
- 来源:
- 关键词:AffectAllelesBiologicalBlood typing procedureCandidate Disease GeneCodeCommunitiesComplexComputer softwareDevelopmentDiseaseEnvironmentEnvironmental ExposureExtended FamilyFamilyFetusGenerationsGenesGeneticGenotypeJointsKnowledgeLifeMacaca mulattaMentorsMethodologyMethodsModelingMothersNuclear FamilyOutcomeParentsPopulationPredispositionProblem SolvingProcessPublic HealthRelative RisksResearchResearch PersonnelRheumatoid ArthritisRiskRisk FactorsSchizophreniaSiblingsStatistical MethodsStatistical ModelsSusceptibility GeneTestingWorkbaseblood groupdesigndisorder riskfamily structurefetalgenetic analysisgenetic risk factorhuman leukocyte antigen geneoffspringpublic health relevancesexsoftware developmenttrait
项目摘要
DESCRIPTION (provided by applicant): The development of statistical methods to detect complex biological or genetic mechanisms is very important to the furthering of our knowledge of the etymology of complex diseases. One example where genes operate through complex biological mechanisms to increase disease risk is through an interaction between maternal and offspring genes termed maternal-fetal genotype (MFC) incompatibility. MFC incompatibility arises from maternal-fetal genotype combinations that predispose for maternal immunological processes that adversely affect the developing fetus, and thereby increase susceptibility to disease. Although the adverse environment takes place early in life, the effects of it can be studied decades later because of its genetic origins. Using population designs that collect only offspring and their mothers, interactions between mothers and offspring gene effects are confounded with the effects of a susceptibility risk allele in the offspring or the mother. To solve this problem, my research group developed the original MFG test to estimate MFC interaction effects by adapting the log-linear method for estimating genotypic relative risks for trios (parents and affected offspring). However, there are still some fundamental limitations to the current version of the MFG test that must be overcome. The current test is limited to 2-generation families, it can not handle all forms of MFG incompatibility and it can not be used with quantitative outcomes. This proposed work will expand upon existing statistical methodology (the MFG Test) that estimates disease relative risk for MFG incompatible offspring. Specifically this research will (1) Develop an extended MFG test (EMFG Test) to accommodate arbitrary family structures, (2) Generalize the EMFG test so that one statistical method can be used to fit a variety of MFG incompatibility models, (3) Allow for interactions between specific covariates and MFG incompatibility in the arbitrary family setting, (4) Extend the EMFG test for use with quantitative traits. PUBLIC HEALTH RELEVANCE: This proposed work is relevant to public health because it will provide new statistical methods that can be used by others to test for the joint effects of maternal and offspring genes in a wide range of diseases. Ultimately it will help the scientific community better understand the mechanisms by which environmental and genetic risk factors interact to increase risk to disease.
描述(由申请人提供):统计方法的发展,以检测复杂的生物或遗传机制是非常重要的,以促进我们的复杂疾病的词源学知识。基因通过复杂的生物学机制增加疾病风险的一个例子是通过母体和后代基因之间的相互作用,称为母胎基因型(MFC)不相容性。MFC不相容性由母体-胎儿基因型组合引起,其倾向于不利地影响发育中的胎儿的母体免疫过程,从而增加对疾病的易感性。虽然不利的环境发生在生命的早期,但由于其遗传起源,它的影响可以在几十年后进行研究。使用仅收集后代及其母亲的群体设计,母亲和后代基因效应之间的相互作用与后代或母亲中易感性风险等位基因的效应混淆。为了解决这个问题,我的研究小组开发了原始的MFG测试,通过调整对数线性方法来估计三人组(父母和受影响的后代)的基因型相对风险,以估计MFC的相互作用效应。然而,目前版本的MFG测试仍然存在一些必须克服的基本限制。目前的测试仅限于2代家庭,它不能处理所有形式的MFG不相容性,也不能用于定量结果。这项拟议的工作将扩大现有的统计方法(MFG测试),估计疾病的相对风险MFG不兼容的后代。具体来说,本研究将(1)开发一个扩展的MFG测试(EMFG测试),以适应任意的家庭结构,(2)推广EMFG测试,使一种统计方法可以用来拟合各种MFG不相容性模型,(3)允许特定的协变量和MFG不相容性之间的相互作用,在任意的家庭设置,(4)扩展EMFG测试用于数量性状。公共卫生相关性:这项拟议中的工作与公共卫生有关,因为它将提供新的统计方法,其他人可以使用这些方法来测试母体和后代基因在广泛疾病中的联合作用。最终,它将帮助科学界更好地了解环境和遗传风险因素相互作用增加疾病风险的机制。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
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