The VETSA Longitudinal Twin Study of Cognition and Aging (VETSA 3)

 描述（由申请人提供）：风险因素的早期识别和治疗方面的进展可能是对抗阿尔茨海默病（AD）和年龄相关性认知下降的主要武器，就像他们对心血管疾病和癌症一样。对于AD，研究人员最近才得出结论，治疗无效的一个可能原因是疾病过程在痴呆症发作前几十年就已经开始了。AD从1990年的第32位疾病跃升至2010年的第9位（任何疾病中增幅最大），并且从第17位跃升至第12位，与心血管疾病或癌症的显著改善形成对比，这些疾病强调早期识别和治疗风险因素。有了这些令人担忧的趋势，难怪现在越来越强烈地推动早期识别AD和认知障碍。因此，我们的重点是轻度认知障碍（MCI），这可能是AD的前兆。在痴呆症之前几十年开始的疾病过程也需要关注中年和从中年到老年早期的过渡。然而，这一年龄段的研究仍显不足。 我们建议在越南时代老龄化双胞胎研究（VETSA）中收集第三波数据。VETSA有一个狭窄的10岁年龄组来评估人内差异。平均年龄55岁和61岁的数据加上67岁时的第3波数据将提供12年的随访，以早期识别MCI。目的1是使用基于纵向一致性、转化为MCI和恢复正常的人群比例以及与生物标志物的关联的最先进方法构建最有效的MCI定义。我们将纳入3类具有筛查大人群潜力的生物标志物：基于血液的（ApoE、外泌体p-tau、clusterin、APOE、NT-proBNP、CRP、游离睾酮）;外部验证的AD和认知障碍多基因风险评分;生理学（瞳孔测量、光反射、勃起功能障碍、代谢综合征）。前两个类别是本提案的新类别。利用VETSA 1储存的血浆，我们将检查VETSA 1和3的血液生物标志物。目的2是开发第一个专门针对MCI的风险指数，该指数基于生物标志物和传统风险因素的组合，最大限度地提高灵敏度和特异性。目的3是阐明连续测量的认知功能和认知变化的异质性，并确定预测因素和相关因素。在这样做的时候，我们将确定不同的变化分组 模式，以及认知变化对特定环境背景的敏感性差异，这取决于遗传因素。目标4是确定认知弹性的预测因素（多基因或血液风险因素高，但没有认知障碍），以便我们能够提供有关成功认知老化以及衰退的信息。 我们将有1261对双胞胎与波3数据。完成后，我们将公开数据供研究使用。我们独特的功能组合使VETSA在获得有关早期识别和可改变的风险因素的知识方面处于领先地位，这些风险因素可能会对公共卫生产生深远的影响。

 DESCRIPTION (provided by applicant): Advances in early identification and treatment of risk factors are likely to be major weapons in the battle against Alzheimer's disease (AD) and age-related cognitive decline, just as they are for cardiovascular disease and cancer. For AD, it is only relatively recently that researchers concluded that a likely reason for treatment ineffectiveness is the fact that the disease process unfolds decades before dementia onset. AD jumped from the 32nd ranked disease for years of life lost in 1990 to 9th in 2010 (largest increase of any disease), and from 17th to 12th for years lived with disability, in contrast to substantial improvements in cardiovascular disease or cancer where early identification and treatment of risk factors are emphasized. With these alarming trends, it is no wonder that there is now an ever stronger push for earlier identification of AD and cognitive impairment. Therefore, our focus is on mild cognitive impairment (MCI), which can be a precursor to AD. A disease process beginning decades before dementia also calls for a focus on midlife and the transition from middle age to early old age. However, this age period remains notably understudied. We propose to collect a third wave of data in the Vietnam Era Twin Study of Aging (VETSA). VETSA has a narrow 10-year age cohort for assessing within-person differences. Data from mean ages 55 and 61 plus wave 3 data at age 67 will provide a 12-year follow-up for early identification of MCI. Aim 1 is to construct a maximally valid MCI definition using a state-of-the-art approach based on longitudinal consistency, proportion of people converting to MCI and reverting to normal, and associations with biomarkers. We will include 3 categories of biomarkers with potential for screening large populations: blood-based (Aß, exosomal p-tau, clusterin, APOE, NT-proBNP, CRP, free testosterone); externally-validated polygenic risk scores for AD and cognitive impairment; and physiological (pupillometry, light reflex, erectile dysfunction, metabolic syndrome). The first 2 categories are new to this proposal. Capitalizing on plasma stored from VETSA 1, we will examine blood-based biomarkers from VETSA 1 and 3. Aim 2 is to develop the first risk index specifically for MCI based on the combination of biomarkers and traditional risk factors that maximizes sensitivity and specificity. Aim 3 is to elucidate the heterogeneity of continuously measured cognitive function and cognitive change, and identify predictors and correlates. In doing so, we will identify different subgroups of change patterns, and differential sensitivity of cognitive change to particular environmental contexts depending on genetic factors. Aim 4 is to determine predictors of cognitive resilience (being high on polygenic or blood-based risk factors but having no cognitive impairment), so that we can be informative about successful cognitive aging as well as decline. We will have 1261 twins with wave 3 data. After completion, we will make the data publicly available for research. Our unique combination of features puts VETSA ahead of curve with respect to its ability to gain knowledge about early identification and modifiable risk factors that can have a profound public health impact.