Leveraging Longitudinal Data and Informatics Technology to Understand the Role of Bilingualism in Cognitive Resilience, Aging and Dementia

利用纵向数据和信息学技术了解双语在认知弹性、衰老和痴呆中的作用

• 批准号: 10583170
• 负责人: HUA XU
• 金额: $ 141.18万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-15 至 2028-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10583170
• 关键词: Address; Adult; Affect; Age; Age of Onset; Age-associated memory impairment; Aging; Algorithms; Alzheimer' s disease related dementia; American; Behavioral; Boston; California; Characteristics; Clinical; Cognition; Cognitive; Complex; Computing Methodologies; Confounding Factors (Epidemiology); Data; Dementia; Discipline; Education; Elderly; Electronic Health Record; Electronics; Environment; Face; Future; Generations; Geography; Health; Health Care Costs; Health Sciences; Health Services Research; Health system; Healthcare Systems; Immigrant; Impaired cognition; Individual; Informatics; Institution; Intervention; Investigation; Knowledge; Language; Life; Life Style; Longitudinal Surveys; Machine Learning; Maps; Measures; Methods; Morbidity - disease rate; Natural Language Processing; Nature; Needs Assessment; Neurologic; Neurology; Neuropsychology; Outcome; Pathway interactions; Patient Recruitments; Patients; Phenotype; Physical activity; Population; Population Heterogeneity; Prevention; Process; Prospective Studies; Prospective, cohort study; Psychiatry; Psychology; Quality of life; Registries; Reproducibility; Research; Research Support; Role; Sample Size; Site; Social support; Standardization; Stress; Surveys; Technology; Testing; Texas; Text; Time; Translating; US State; Universities; Work; age related; age related cognitive change; age related neurodegeneration; aging population; bilingualism; brain health; case finding; cognitive change; cognitive enhancement; cognitive function; cognitive process; cognitive reserve; cohort; comorbidity; coping; cost; design; disability; disorder prevention; electronic health record system; electronic structure; ethnic diversity; experience; health care delivery; improved; innovation; insight; instrument; interdisciplinary approach; machine learning algorithm; neural; novel; novel therapeutic intervention; observational cohort study; primary outcome; protective factors; psychologic; racial diversity; recruit; resilience; screening; social; social health determinants; statistics; theories; time use; tool

Project Summary Alzheimer’s Disease and Related Dementias (ADRD) along with other age-related neurodegenerative diseases contribute to significant morbidity and costs for the aging population worldwide. Advances in this field have uncovered that bilingualism is a protective factor that delays onset of ADRD and may enhance cognitive reserve. Still, little is clearly known about the direct impact of bilingualism on cognitive reserve and ADRD progression; multiple, entangled confounding variables, such as lifestyle and psychological resilience, complicate the relationship between bilingualism and cognition and warrant further investigation. Other major shortcomings in previous studies include small sample size, lack of population diversity and insufficient data on relevant covariates. We aim to address these critical gaps via the following specific aims. In Aim 1, we will leverage advanced informatics and longitudinal electronic health records (EHRs) from millions of patients across three geographically and demographically diverse sites (i.e., MGB [Boston, MA], UTHealth [Houston, TX], and UC Davis [Sacramento, CA]). We will develop robust algorithms to identify potential monolingual and bilingual cohorts and their phenotypes. We will disseminate reproducible informatics methods to support research cross-institutionally. In Aim 2, we will conduct a prospective cohort study to evaluate the dynamic cognitive changes in monolingual and bilingual older adults. We will explore potential pathways by which bilingualism impacts cognitive decline over time using comprehensive instruments and surveys to repeatedly measure cognitive resilience, cognitive reserve, and related factors, including social support, psychological resilience, and physical activity. In Aim 3, we will develop and validate machine learning algorithms to identify onset of age-related cognitive decline and dementia using EHR data. We will apply the validated language classifier for all participating EHR systems to examine the role of bilingualism in relation to the progression of cognitive decline and the effect of other factors recorded in EHR data. By integrating multiple disciplines to explore the influence of bilingualism on cognitive reserve, this proposed design will address major gaps and challenges in this field. Such research has the potential to transform the current understanding of neural and behavioral pathways in relation to language, culture, and environment. Furthermore, the knowledge gained may translate to improvements in existing interventions and novel therapeutic approaches for ADRD.

项目总结