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

项目总结 暴露组的特征可能是阿尔茨海默病和相关痴呆(ADRD)病因学的关键， 对ADRD的跨国曝光研究在这一领域有着巨大的前景。跨国协调 老龄化队列研究，如美国健康和退休研究(HRS)国际合作伙伴研究和 其嵌入式协调认知评估协议(HCAP)是 Exposome-ADRD研究。这些队列包括适当年龄的基于人口的研究样本。 ADRD发病率范围，并有丰富的访谈、身体、认知和生物标记物评估 以及行政和地理数据链接。国际覆盖和协调设计 HCAP的研究允许对不同国家背景下的暴露数据进行新颖的三角测量。HCAP 数据在加强因果推断和扩大全球证据基础方面具有巨大潜力，其特点是 它可能影响ADRD的机制的暴露和多样性。然而，Exposome HCAP网络中的研究是有限的，这是因为在关于衰老的队列研究中存在共同的偏见，这种偏见没有得到解决 迄今为止的研究努力：在研究基线之前发生在目标人群中的选择性存活。这 偏见很难量化，因为大多数研究缺乏关于人口成员的信息 有资格参加这项研究，但在入学前死亡。在美国，20%-30%的死亡率不是 这在老龄化研究中并不常见，对于跨人群三角关联数据的努力至关重要， 不同年龄段的死亡率在全国范围内差异很大。曝光体的许多特征与 生存，使这种形式的选择偏见成为对EXPLOME-ADRD有效性的显著威胁，但研究不足 研究。事实上，我们的初步数据表明，在HCAP中存在相当大的选择偏见 学习。我们目前的目标是通过创新性地量化看似合理的预付费程度来解决这种偏见 使用HCAP网络数据进行的EXPLOME-ADRD研究中的基线选择偏差，并开发一个用户- 友好的基于网络的应用程序，将允许其他研究人员了解他们自己的生存偏见的影响 与ADRD相关的曝光组研究。我们将首先进行针对特定国家的模拟研究，使用 关于特定年龄死亡率的生命表数据和来自协调HCAP评分的认知数据，以生成 对可能影响曝光组结果的基线前选择偏差大小的可信估计 HCAP网络中的ADRD分析。我们将对三个关键暴露因素进行模拟，认为 突出ADRD，与HCAP国家的死亡率有看似不同的联系：主要寿命 职业技能水平，晚年暴露于空气污染，晚年暴露于II型糖尿病。我们会 然后构建一个用户友好的、全面的基于Web的选择偏差分析工具，该工具将托管在 全球老龄化门户网站，这将是一个重要的研究资源，以帮助阐明 暴露了整个HCAP研究网络的ADRD结果和差异。

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.