Integrative Resource to Develop Translational Strategies to Promote Longevity

 描述(申请人提供)：人类的长寿是可遗传的，已经确定了与人类长寿和年龄相关特征的统计学和生物学上令人信服的遗传关联。将这些遗传关联转化为能够导致旨在促进健康老龄化的药物干预的洞察力，需要一种整合了许多信息来源和科学专业知识的方法和基础设施。事实上，以前无法将来自基因关联的见解转化为促进长寿的干预措施，至少部分原因是缺乏在所有相关领域都具有专业知识的整合良好和组织齐全的研究团队。我们建议创建一个整合基因组和相关数据源的资源和基础设施，使我们的多样化科学团队能够制定策略，根据遗传关联确定药物干预的目标，从而影响寿命。这一基础设施将包括来自具有全基因组基因和测序数据的纵向队列研究的信息、注释遗传变异的计算方法、来自特定组织的表达数量性状基因座(EQTL)研究的信息，以及与蛋白质靶标相关联的小分子化合物的化学性质的数据集。我们的科学团队包括人类和模型生物衰老、衰老遗传流行病学、统计遗传学、化学信息学和药物开发方面的专家。我们还将组建一个研究规划委员会，该委员会将每年举行会议，评估我们统计分析的证据，并为试点项目制定计划，以推动将我们的发现转化为促进健康的疗法。我们提案中的一个中心主题是基于根植于涉及长寿的遗传相关研究的假设，开发与分子和生理因素相关的洞察力，这些因素可以通过药物作用于健康衰老。我们将通过对已发表的关于长寿和年龄相关性状的全基因组关联研究(GWAS)的荟萃分析结果，以及通过寻找对衰老相关性状具有多效性效应的遗传变异的证据，来确定用于深入分析的候选遗传变异。可能受候选遗传变异调控的基因将使用基因组功能注释资源，如组织特异性基因组功能元件和eQTL来识别。对于每个识别的基因，将从eQTL数据集中识别与例如该基因的表达相关的等位基因变异系列，并且将测试从等位基因序列构建的遗传风险分数与包括偶发残疾、偶发疾病和慢性病以及身体和认知功能变化在内的衰老的纵向测量的关联，这可以为寻找可能模仿所选遗传变体的集体效应的小分子化合物奠定基础。通过根据基因功能与健康衰老相关的治疗假说识别小分子，可以开发出有效的翻译研究策略，并将其传播给研究界。

 DESCRIPTION (provided by applicant): Human longevity is heritable, and statistically and biologically compelling genetic associations with longevity and age-related traits in humans have been identified. The translation of these genetic associations into insights that can lead to pharmacological interventions designed to promote healthy aging requires an approach and infrastructure that integrates many sources of information and scientific expertise. In fact, a previous inability to translate insights from genetic associations to longevity-promoting interventions is due, at least in part, to a lack of well-integrated and assembled research teams with expertise in all areas of relevance. We propose the creation of a resource and infrastructure that integrates genomic and related data sources that enable our diverse scientific team to develop strategies for identifying targets for pharmacological intervention that will impact longevity based on genetic associations. This infrastructure will include information from longitudinal cohort studies with genome-wide genotype and sequencing data, computational methods for annotating genetic variants, information from tissue-specific studies of expression quantitative trait loci (eQTL), and datasets of chemical properties of small molecule compounds linked to protein targets. Our scientific team includes experts in human and model organism aging, genetic epidemiology of aging, statistical genetics, chemical informatics, and pharmaceutical development. We will also assemble a research planning committee that will meet annually to evaluate the evidence from our statistical analyses and to develop plans for pilot projects to advance the translation of our findings into health-promoting therapeutics. A central theme in our proposal is to develop insights relating molecular and physiologic factors that can be manipulated pharmacologically to healthy aging based on hypothesis rooted in genetic associated studies involving longevity. We will identify candidate genetic variants for in-depth analysis by meta-analyzing results from published genome-wide association studies (GWAS) of longevity and age-related traits and by searching for evidence of genetic variants with pleiotropic effects on aging-related traits. Genes likely to be modulated by candidate genetic variants will be identified using genomic functional annotation resources such as tissue-specific genomic functional elements and eQTLs. For each identified gene, an allelic series of genetic variants associated with, e.g., the expression of that gene, will be identified from eQTL data sets, and a genetic risk score constructed from the allelic series will be tested for its association with longitudinal measures of aging, including incident disability, incident disease and chronic conditions, and change in physical and cognitive function, which can build the foundation for the search for small molecule compounds that might mimic the collective effect of selected genetic variants. By identifying small molecules based on therapeutic hypotheses relating genetic function to healthy aging, effective translational research strategies can be developed and disseminated to the research community.