EVALUATING NEW GENETIC EFFECTS ON HEALTH AND AGING FROM LONGITUDINAL DATA

从纵向数据评估新的遗传对健康和衰老的影响

• 批准号: 7497878
• 负责人: ANATOLIY I YASHIN
• 金额: $ 58.21万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-30 至 2012-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7497878
• 关键词: ADRB2 gene; Address; Adrenergic Receptor; Adult; Adverse reactions; Affect; Age; Aging; Aging-Related Process; Alcohol consumption; Alleles; Apolipoprotein E; Area; Behavioral; Blood Glucose; Blood Pressure; Body mass index; Cardiovascular Diseases; Characteristics; Cholesterol; Chronic; Chronic Disease; Clinical; Cognitive; Cohort Studies; Complement; Computer Simulation; Condition; Consensus; Data; Degenerative Disorder; Demographic Factors; Dependence; Development; Diabetes Mellitus; Disease; Education; Elderly; Employment; Environment; Evaluation; Genes; Genetic; Genetic Polymorphism; Genotype; Hazard Models; Health; Heart; Hematocrit procedure; Human; Hypertension; Individual; Intervention; Joints; Life; Likelihood Functions; Link; Literature; Longevity; Malignant Neoplasms; Marital Status; Measurement; Medical; Methodology; Methods; Modeling; Morbidity - disease rate; National Research Council; Organism; Pattern; Peptidyl-Dipeptidase A; Personal Satisfaction; Physical activity; Physiological; Procedures; Public Health; Pulse Pressure; Pulse Rates; Rate; Recommendation; Research; Research Personnel; Resistance; Risk; Sampling; Science; Sensory; Series; Serum; Simulate; Smoking; Smoking Status; Statistical Methods; Statistical Models; Stochastic Processes; Stress; Stroke; Supervision; System; Time; United States National Institutes of Health; age related; allostasis; allostatic load; base; concept; disorder prevention; follow-up; indexing; innovation; mortality; programs; senescence; sex; theories; tool; trend

DESCRIPTION (provided by applicant): The broad, long-term objective of the proposed research is to evaluate the effects of dynamic interplay of genetic, physiological, demographic, and behavioral factors on the age-trajectories of the "systemic" variables characterizing aging process in humans, risks of development and progression of health disorders in adult and elderly individuals, life span, and free-of-disease life span, using newly elaborated statistical methods. These methods are based on mathematical and computer models of aging, health, and longevity capable of describing longitudinal samples with and without genetic information and estimating age patterns of morbidity and mortality risks, as well as new "systemic" variables characterizing age-dependent physiological "norm", rate of allostatic adaptation, levels of accumulated allostatic load, rates of decline in stress resistance, adaptive capacity, and stochasticity, along with the associated risks of morbidity, overall and cause-specific mortality, in the presence of demographic and behavioral factors. Such comprehensive evaluation is possible due to unique information collected in the Framingham Heart (FHS) and Offspring (FHSO) Studies. The unique advantage of these data is a combination of genetic and non-genetic factors, detailed longitudinal information on physiological changes, risks of major chronic diseases and mortality risk. The following specific aims will be addressed: 1) Evaluate the effects of selected genetic polymorphisms on age patterns of morbidity and mortality rates. 2) Evaluate time trends in the respective morbidity/mortality age patterns and estimate their alteration for the selected polymorphisms. 3) Evaluate the effects of selected genetic polymorphisms on the age-trajectories of physiological indices and new "systemic" variables. 4) Examine the effects of additive superposition and nonlinear interaction of the selected physiological indices and genetic characteristics. 5) Evaluate the effect of genetic factors on trends in the new "systemic" variables and morbidity and mortality age patterns. This research is directly relevant to public health, as it focuses on a sample of the U.S. adult and elderly individuals and proposes evaluation of the most important characteristics of aging organisms linking them with genetic information. These characteristics are of great importance for developing targeted approach in disease prevention and medical intervention for aging individuals.

描述（由申请人提供）：拟议研究的广泛、长期目标是评估遗传、生理、人口和行为因素的动态相互作用对表征衰老过程的“系统”变量的年龄轨迹的影响使用新制定的统计方法，对人类、成人和老年人健康疾病发生和进展的风险、寿命和无病寿命进行了研究。这些方法基于衰老、健康和长寿的数学和计算机模型，能够描述有或没有遗传信息的纵向样本，并估计发病和死亡风险的年龄模式，以及表征与年龄相关的生理特征的新“系统”变量。标准”，在人口存在的情况下，非稳态适应率、累积的非稳态负荷水平、抗应激能力下降率、适应能力和随机性，以及发病率、总体死亡率和特定原因死亡率的相关风险和行为因素。由于弗雷明汉心脏 (FHS) 和后代 (FHSO) 研究中收集的独特信息，这种综合评估成为可能。这些数据的独特优势是遗传和非遗传因素的结合，详细的纵向信息的生理变化、主要慢性疾病的风险和死亡风险。将解决以下具体目标： 1）评估选定的遗传多态性对发病率和死亡率年龄模式的影响。 2) 评估各自发病/死亡年龄模式的时间趋势，并估计所选多态性的变化。 3) 评估选定的遗传多态性对生理指标和新“系统”变量的年龄轨迹的影响。 4) 检查所选生理指标和遗传特征的加性叠加和非线性相互作用的影响。 5) 评估遗传因素对新“系统”变量趋势以及发病率和死亡率年龄模式的影响。这项研究与公共健康直接相关，因为它重点关注美国成年人和老年人的样本，并提出评估将衰老有机体与遗传信息联系起来的最重要特征。这些特征对于制定针对老年人的疾病预防和医疗干预的针对性方法具有重要意义。