R01AG075775

An automated machine learning approach to language changes in Alzheimer's disease and frontotemporal dementia across Latino and English-speaking populations - project summary.

Alzheimer's disease (AD) and frontotemporal dementia (FTD) are highly prevalent in Latinos, the largest and fastest-growing minority in the United States (US). Yet, due to financial and cultural inequities, this group is challenged to afford standard diagnostic and monitoring procedures. Also, research on Latinos lacks scalable, culturally valid tests and it rarely examines whether potential markers are robust across socio-biological profiles.

Such issues can be tackled with low-cost automated speech and language analyses (ASLA). Participants are asked to produce natural speech, generating multiple acoustic (sound wave) and linguistic (e.g., semantic) data that can be digitally extracted and analyzed to identify diseases or predict neurocognitive disruptions. Yet, ASLA findings are minimal in Latinos. Also, most ASLA studies are small and very few have differentiated between AD and FTD variants, compared ASLA with standard measures, accounted for socio-biological factors (e.g., sex, race, brain profile, bilingualism) or tested for validity across languages and dialects.

This project will develop a novel ASLA framework to jointly address such challenges. To capture socio-biological diversity and meet requisites for robust machine and deep learning analyses, we will leverage 2740 participants. These encompass Spanish speakers from five Latin American countries (700 AD, 700 FTD, 800 controls), English speakers from the US (140 AD, 140 FTD, 160 controls), and US-based Latinos (30 AD, 30 FTD, 40 controls), including the main variants of each disease. This is possible due to a strategic partnership between UCSF and the Consortium to Expand Dementia Research in Latin America, a multi-funded network bringing a fully harmonized environment and a large, growing cohort. The Global Brain Health Institute, a dementia training hub at UCSF, hosts expert clinicians in all sites.

Speech and language data will be gleaned through our new toolkit to examine lifelike language, a HIPAA-compliant app for speech collection, storage, and visualization, supported by a language battery and survey. Enrollees are characterized with demographic, clinical, cognitive, and social determinants of health measures, alongside MRI and fMRI.

Our ASLA approach comprises top predicted markers for each syndrome, added fine-grained features, and embedding features. Novel machine and deep learning algorithms for high-dimensional settings will be used to pursue three aims. In Aim 1, we will employ machine and deep learning to reveal the ASLA markers that best identify AD and FTD syndromes; compare them with cognitive and imaging measures; and test them for generalizability from Spanish onto English (a typologically different language). In Aim 2, via linear regressions, we will use optimal ASLA markers to capture syndrome-specific patterns of cognitive dysfunction, brain atrophy, and connectivity. In Aim 3, using high-dimensional machine learning, we will test such markers for validity across diverse socio-biological profiles, dialects, and bilingual skills (null, low, high).

We will forge an affordable, scalable approach to assist AD and FTD diagnosis in Latinos, at a time when disease-modifying therapies may emerge.

San Francisco Regents Of The University Of California

TO ENCOURAGE BIOMEDICAL, SOCIAL, AND BEHAVIORAL RESEARCH AND RESEARCH TRAINING DIRECTED TOWARD GREATER UNDERSTANDING OF THE AGING PROCESS AND THE DISEASES, SPECIAL PROBLEMS, AND NEEDS OF PEOPLE AS THEY AGE. THE NATIONAL INSTITUTE ON AGING HAS ESTABLISHED PROGRAMS TO PURSUE THESE GOALS. THE DIVISION OF AGING BIOLOGY EMPHASIZES UNDERSTANDING THE BASIC BIOLOGICAL PROCESSES OF AGING. THE DIVISION OF GERIATRICS AND CLINICAL GERONTOLOGY SUPPORTS RESEARCH TO IMPROVE THE ABILITIES OF HEALTH CARE PRACTITIONERS TO RESPOND TO THE DISEASES AND OTHER CLINICAL PROBLEMS OF OLDER PEOPLE. THE DIVISION OF BEHAVIORAL AND SOCIAL RESEARCH SUPPORTS RESEARCH THAT WILL LEAD TO GREATER UNDERSTANDING OF THE SOCIAL, CULTURAL, ECONOMIC AND PSYCHOLOGICAL FACTORS THAT AFFECT BOTH THE PROCESS OF GROWING OLD AND THE PLACE OF OLDER PEOPLE IN SOCIETY. THE DIVISION OF NEUROSCIENCE FOSTERS RESEARCH CONCERNED WITH THE AGE-RELATED CHANGES IN THE NERVOUS SYSTEM AS WELL AS THE RELATED SENSORY, PERCEPTUAL, AND COGNITIVE PROCESSES ASSOCIATED WITH AGING AND HAS A SPECIAL EMPHASIS ON ALZHEIMER'S DISEASE. SMALL BUSINESS INNOVATION RESEARCH (SBIR) PROGRAM: TO EXPAND AND IMPROVE THE SBIR PROGRAM, TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, TO INCREASE SMALL BUSINESS PARTICIPATION IN FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION. SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAM: TO STIMULATE AND FOSTER SCIENTIFIC AND TECHNOLOGICAL INNOVATION THROUGH COOPERATIVE RESEARCH DEVELOPMENT CARRIED OUT BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO FOSTER TECHNOLOGY TRANSFER BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION.

93.866 - Aging Research

National Institute on Aging (NIA) [HHS - NIH]

San Francisco, California 94143 United States

Single Zip Code

Research on Current Topics in Alzheimer's Disease and Its Related Dementias (R01 Clinical Trial Optional) (PAR-22-093)

Amendment Since initial award the total obligations have increased 208% from $1,773,132 to $5,455,529.