Accounting for pre-baseline selective survival in cross-national studies of the exposome in Alzheimer’s disease and related dementias: a novel bias assessment tool

项目摘要 该基因组的特征可能是阿尔茨海默病和相关痴呆症（ADRD）病因学的关键， ADRD的跨国研究在这一领域具有巨大的前景。跨国协调 老龄化的队列研究，如美国健康与退休研究（HRS）国际合作伙伴研究， 其嵌入式协调认知评估协议（HCAP）是主要的潜在数据资源， ADRD研究。这些队列包括适当年龄的基于人群的研究样本 ADRD发病率范围，并有丰富的访谈、体格、认知和生物标志物评估 以及行政和地理数据链接。国际覆盖面和统一设计 HCAP研究允许对不同国家背景下的麻烦数据进行新的三角测量。HCAP 数据有很大的潜力，以加强因果推理和扩大全球证据基础的特点， 它可能影响ADRD的机制的复杂性和多样性。然而， HCAP网络中的研究是有限的，因为在老龄化的队列研究中存在一个共同的偏见， 迄今为止的研究工作：研究基线前目标人群的选择性生存率。这 偏见很难量化，因为大多数研究缺乏人口成员的信息， 符合研究条件，但在入组前死亡。在美国，20-30%的死亡率并不是 这在老龄化研究中并不常见，而且对于在人群中进行三角关联数据的努力至关重要， 年龄别死亡率在各国之间差别很大。麻烦的许多特征都与 生存，使这种形式的选择偏见的一个显着的，但研究不足的威胁，有效性的麻烦，ADRD research.事实上，我们的初步数据表明，相当大的选择偏见是不同的HCAP 问题研究我们目前的目标是通过创新性地量化预测的合理幅度来解决这种偏差。 使用HCAP网络数据进行ADRD研究的基线选择偏差，并开发用户- 一个友好的基于网络的应用程序，将允许其他研究人员了解生存偏见的影响，在他们自己的 研究与ADRD相关的问题。我们将首先进行针对具体国家的模拟研究， 年龄特异性死亡率的生命表数据和来自我们的统一HCAP评分的认知数据， 可能影响麻烦结果的基线前选择偏倚幅度的合理估计- HCAP网络中的ADRD分析。我们将对三个关键的麻烦因素进行模拟， 对ADRD很重要，在HCAP国家与死亡率之间存在明显差异：主要寿命 职业技能水平，晚年暴露于空气污染，以及晚年暴露于II型糖尿病。我们将 然后建立一个用户友好和全面的基于网络的选择偏差分析工具， 全球老龄化门户网站，这将是一个重要的研究资源，有助于阐明 ADRD结局令人困扰，HCAP研究网络存在差异。

PROJECT SUMMARY Features of the exposome are likely key to the etiology of Alzheimer’s disease and related dementias (ADRD), and cross-national exposome studies of ADRD have huge promise in this area. Cross-nationally harmonized cohort studies of aging such as the US Health and Retirement Study (HRS) International Partner Studies and their embedded Harmonized Cognitive Assessment Protocols (HCAPs) are prime potential data resources for exposome-ADRD research. These cohorts include population-based study samples of the appropriate age range for ADRD incidence, and have a wealth of interview, physical, cognitive, and biomarker assessments alongside administrative and geographic data linkages. The international coverage and harmonized design of the HCAP studies allow for novel triangulation of exposome data across diverse country contexts. The HCAP data have great potential to strengthen causal inference and broaden the global evidence base on features of the exposome and diversity in the mechanisms through which it may impact ADRD. However, exposome research in the HCAP network is limited due to a common bias in cohort studies of aging that is unresolved by research efforts to date: selective survival in the target population that occurs prior to the study baseline. This bias is difficult to quantify, as most studies lack information on population members who would have been eligible for the study, but who died prior to enrollment. In the United States, mortality rates of 20-30% are not uncommon in studies of aging, and, crucially for efforts to triangulate associational data across populations, age-specific mortality varies widely cross-nationally. Many features of the exposome are associated with survival, making this form of selection bias a salient yet under-studied threat to the validity of exposome-ADRD research. Indeed, our preliminary data indicate considerable selection bias that is differential across HCAP studies. Our current objective is to address this bias by innovatively quantifying plausible magnitudes of pre- baseline selection bias in exposome-ADRD research using the HCAP network data, and to develop a user- friendly web-based app that will allow other researchers to understand the impacts of survival bias in their own research on the exposome in relation to ADRD. We will first conduct country-specific simulation studies using life table data on age-specific mortality and cognitive data from our harmonized HCAP scores to generate plausible estimates for the magnitudes of pre-baseline selection bias that could affect results of exposome- ADRD analyses in the HCAP network. We will conduct simulations for three key exposome factors thought to be salient to ADRD, with plausibly differential associations with mortality across HCAP countries: main lifetime occupational skill level, later-life exposure to air pollution, and later-life exposure to type II diabetes. We will then build a user-friendly and comprehensive web-based selection bias analysis tool to be hosted on the Gateway to Global Aging website, which will be an important research resource to help elucidate the role of the exposome in ADRD outcomes and disparities across the HCAP network of studies.