The predicative values of vascular and metabolic disorders for risk of incident mild cognitive impairment and dementia

血管和代谢紊乱对发生轻度认知障碍和痴呆风险的预测价值

• 批准号: 10661996
• 负责人: Longjian Liu
• 金额: $ 18.96万
• 依托单位: DREXEL UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10661996
• 关键词: Address; Adult; Affect; Age; Aging; Algorithms; Alleles; Alzheimer' s Disease; Alzheimer' s disease diagnosis; Alzheimer' s disease related dementia; Alzheimer' s disease risk; Amyloid beta-Protein; Apolipoprotein E; Biological Markers; Blood; Blood Vessels; Brain; Chronic; Cognitive; Cohort Studies; Data; Dementia; Development; Diabetes Mellitus; Diagnosis; Dimensions; Disease; Dyslipidemias; Early Diagnosis; Elderly; Encephalitis; Functional disorder; Genes; Genetic; Hyperglycemia; Impairment; Individual; Inflammation; Inflammatory; Ionizing radiation; Journals; Judgment; Late Onset Alzheimer Disease; Literature; Longevity; Machine Learning; Magnetic Resonance Imaging; Measures; Memory; Metabolic; Metabolic Diseases; Metabolic syndrome; Methods; Modeling; Modification; Neurosciences; Outcome; Outcome Study; Participant; Pathology; Patients; Population; Population Study; Predictive Factor; Predictive Value; Predictive Value of Tests; Prevention; Prevention Measures; Primary Health Care; Proteins; Public Health; Publishing; Questionnaires; Reporting; Research; Research Design; Risk; Risk Factors; Sample Size; Sampling Studies; Secondary to; Short-Term Memory; Signal Transduction; Special Equipment; Testing; Thinking; Time; Vascular Diseases; Woman; Women' s Health; aged; aging population; cohort; dementia risk; disorder risk; experience; fluorodeoxyglucose positron emission tomography; genetic risk factor; hazard; health care settings; high risk; human old age (65+); indexing; innovation; insight; meetings; men; mental state; middle age; mild cognitive impairment; neuroimaging; normal aging; novel; older women; predictive modeling; risk prediction; risk prediction model; sex; tau Proteins; tool; vascular risk factor; volunteer

Project Summary/Abstract Dementia is a condition affecting thinking, judgment, memory and other cognitive domains to the degree that interferes with performing everyday activities. Alzheimer’s disease (AD) is the most common type of dementia. In 2021, an estimated 6.2 million adults in the US aged ≥65 have dementia, and the number is projected to be nearly 14 million by 2060. Women a have significantly higher risk of AD than men. About two thirds of patients with dementia are women. Mild cognitive impairment (MCI), representing the early stage of the disease, refers to a state in which the patient experiences a decline in short-term memory, or other cognitive domain, but with no significant impairment in everyday functioning. Though dementia mostly affects older adults, it is not a part of normal aging. Given that taking prevention at the early stage of MCI delays the development of the disease. It is of tremendous important to detect MCI during the early pre- symptomatic stage. Several studies observed that vascular, metabolic disorders, and inflammation are associated with risk of MCI, AD and AD related dementia (AD/ADRD). However, research gaps remain: (1) inconsistent findings were observed from the previous studies. (2) Large-scale population-based studies for AD and dementia risk are limited. (3) Although it is known that the risk of MCI and dementia are associated with changes in risk exposures, few studies tested the association between time-varying exposures and risk of outcomes. In the application, we aim at filling these gaps by using a rigorous study design to test the predictive values of vascular and metabolic disorders, inflammation, as well as genetic factors for the risk of incident MCI and dementia, and then develop a novel cumulative (combined) prediction index. We have 2 specific aims. Aim 1: To examine the association of vascular, metabolic and inflammatory biomarkers with risk of incident MCI and dementia in older women. Hypothesis: vascular, metabolic and inflammatory biomarkers, with time-varying measures significantly predict the risk of incident MCI and dementia in women aged 65-79, and these associations are modified by APOE gene (ε4 versus the other alleles). Aim 2: To develop a machine learning (ML)-enabled algorithm to predict individuals who are at high risk of incident MCI and dementia. Hypothesis: A novel and advanced risk prediction model (e.g., a multi-dimensional risk model using ML) that integrates predictive values of multiple risk factors and key covariates, will enhance the degree of the prediction for the risk of incident MCI and dementia. The proposed study addresses a significant public health challenge facing an aging population. The proposed study is innovative, characterized by (1) focusing on sex-specific study in older women; (2) addressing time-varying risk factors that may have significant predictive effects on the study outcomes. (3) We will test whether there are potential modification effects of APOE on the association between the study of exposures and outcomes. The scientifically promising aspects of the study are the fact that it is able to test the natural development of MCI and dementia using data from an unique large-scale population-based study, the Women’s Health Initiative Memory Study. Findings of the study will be disseminated through scientific meetings and research articles published in high impact journals, and add new insights into the prevention and control of MCI and dementia.

项目总结/摘要 痴呆是一种影响思维、判断、记忆和其他认知领域的疾病，其程度 妨碍日常活动的物质。阿尔茨海默病（AD）是一种最常见的 痴呆2021年，估计美国有620万≥65岁的成年人患有痴呆，这一数字为 预计到2060年将接近1400万人。女性患AD的风险明显高于男性。关于 三分之二的痴呆症患者是女性。轻度认知功能障碍（MCI），代表早期 疾病的阶段是指患者经历短期记忆减退的状态，或 其他认知领域，但日常功能无明显损害。虽然痴呆症大部分 影响老年人，它不是正常衰老的一部分。鉴于在MCI早期采取预防措施 延缓了疾病的发展。早期发现MCI对早期诊断MCI具有重要意义。 症状阶段。几项研究观察到血管、代谢紊乱和炎症 与MCI、AD和AD相关性痴呆（AD/ADRD）的风险相关。然而，研究的空白仍然存在：（1） 从以前的研究中观察到不一致的结果。(2)大规模人群研究 AD和痴呆风险有限。(3)虽然已知MCI和痴呆的风险相关 随着风险暴露的变化，很少有研究检验时间变化的暴露与风险之间的关系 结果。在应用程序中，我们的目标是通过使用严格的研究设计来测试 血管和代谢紊乱、炎症以及遗传因素对 MCI和痴呆的发病率，然后开发新的累积（组合）预测指数。We have 2 明确的目标。目的1：研究血管、代谢和炎症生物标志物的相关性 老年妇女有发生MCI和痴呆危险。假设：血管、代谢和 炎性生物标志物与时变指标显著预测MCI的发病风险， 65-79岁的女性痴呆患者中，APOE基因改变了这些关联（ε4与其他 等位基因）。目标2：开发一种支持机器学习（ML）的算法，用于预测 发生MCI和痴呆的风险很高。假设：一种新颖和先进的风险预测模型（例如， 使用ML的多维风险模型），该模型综合了多个风险因素和关键 协变量，将提高对MCI和痴呆发病风险的预测程度。 这项拟议的研究解决了人口老龄化所面临的重大公共卫生挑战。的 该研究具有创新性，其特点是：（1）侧重于老年女性的性别特异性研究;（2） 解决了可能对研究结果具有显著预测作用的时变风险因素。（三） 我们将检验APOE是否对研究中的相关性有潜在的修饰作用。 风险和结果。这项研究在科学上有希望的方面是它能够 使用来自一个独特的基于大规模人群的数据来测试MCI和痴呆的自然发展 女性健康倡议记忆研究。研究结果将透过 在高影响力期刊上发表的科学会议和研究文章，并为 用于MCI和痴呆的预防和控制。