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、人口和行为因素的动态相互作用对表征人类衰老过程、成人和老年人健康障碍的发展和进展的风险、寿命和无病寿命的“系统性”变量的年龄轨迹的影响，使用新制定的统计方法。这些方法基于数学和计算机模型，这些模型能够描述有和没有遗传信息的纵向样本，并估计发病率和死亡风险的年龄模式，以及在存在人口和行为因素的情况下，表征与年龄相关的生理“正常”、变态适应速率、累积的变态负荷水平、应激抵抗力、适应能力和随机性的速率以及相关的发病率、总死亡率和特定原因死亡率的新的“系统”变量。由于弗雷明翰心脏(FHS)和后代(FHSO)研究中收集的独特信息，这样的综合评估是可能的。这些数据的独特优势是遗传和非遗传因素的结合，关于生理变化、重大慢性病风险和死亡风险的详细纵向信息。将讨论以下具体目标：1)评估选定的遗传多态对发病率和死亡率年龄模式的影响。2)评估各自发病率/死亡率年龄模式中的时间趋势，并估计所选多态的变化。3)评估选定的遗传多态对生理指标和新的“系统”变量的年龄轨迹的影响。4)考察所选生理指标与遗传性状的加性叠加效应和非线性互作效应。5)评估遗传因素对新的“系统性”变量的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，因为它专注于美国成年人和老年人的样本，并建议评估将他们与遗传信息联系起来的衰老生物的最重要特征。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.