EVALUATING NEW GENETIC EFFECTS ON HEALTH AND AGING FROM LONGITUDINAL DATA

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，人口统计学和行为因素对表征人类衰老过程的“系统”变量的年龄轨迹的动态相互作用的影响，成人和老年人健康障碍的发展和进展风险，寿命和无疾病寿命，使用新阐述的统计方法。这些方法基于衰老、健康和长寿的数学和计算机模型，这些模型能够描述具有和不具有遗传信息的纵向样本，并估计发病率和死亡率风险的年龄模式，以及表征年龄依赖性生理“规范”、适应适应率、累积适应负荷水平、抗逆性下降率、适应能力和随机性的新“系统”变量。在存在人口和行为因素的情况下，以及相关的发病率、总体和特定原因死亡率的风险。由于在弗雷明汉心脏（FHS）和后代（FHSO）研究中收集的独特信息，这种全面的评估是可能的。这些数据的独特优势是结合了遗传和非遗传因素、生理变化的详细纵向信息、主要慢性疾病的风险和死亡风险。将讨论以下具体目标：1)评价选定的基因多态性对发病率和死亡率年龄模式的影响。2)评估各自发病率/死亡率年龄模式的时间趋势，并估计其对选定多态性的改变。3)评价选择的遗传多态性对生理指标和新的“系统”变量的年龄轨迹的影响。4)考察所选生理指标和遗传性状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。这项研究与公共卫生直接相关，因为它集中在美国成年人和老年人的样本上，并提出了衰老生物体与遗传信息联系起来的最重要特征的评估。这些特点对制定针对老年人的疾病预防和医疗干预措施具有重要意义。

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.