EVALUATING NEW GENETIC EFFECTS ON HEALTH AND AGING FROM LONGITUDINAL DATA

描述（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的动态相互作用对表征人类衰老过程的“系统”变量的年龄轨迹的影响，成年人和老年人健康障碍的发展和进展风险，寿命和无病寿命，使用新的统计方法。这些方法基于衰老、健康和寿命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“标准”的新的“系统”变量、非稳态适应率、累积非稳态负荷水平、抗应激能力下降率、适应能力、和随机性，沿着相关的发病风险，总体和原因特异性死亡率，在存在人口统计学和行为因素的情况下。由于FHS和FHSO研究中收集的独特信息，因此可以进行这种全面评价。这些数据的独特优势是综合了遗传和非遗传因素、关于生理变化、主要慢性病风险和死亡风险的详细纵向信息。本研究的具体目标如下：1）评价选定的遗传多态性对发病率和死亡率年龄模式的影响。2)评价相应发病率/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)评估选定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)检验所选生理指标和遗传特性的加性叠加和非线性相互作用的影响。5)评估遗传因素对新的“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，因为它侧重于美国成年人和老年人的样本，并建议评估衰老生物体与遗传信息相关的最重要特征。这些特征对老年人疾病预防和医学干预的靶向治疗具有重要意义。

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.