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Asian Cohort for Alzheimer's Disease (ACAD) Pilot Study on Genetic and Non-Genetic AD Risk Factors among Asian Americans and Canadians

Li-San Wang, University of Pennsylvania, Philadelphia, PA
Pei-Chuan Ho, University of Pennsylvania, Philadelphia, United States
Wai Haung Yu, Centre for Addiction and Mental Health, Toronto, Canada
Boon Lead Tee, University of California San Francisco, San Francisco, United States
Clara Li, Icahn School of Medicine at Mount Sinai, New York, United States
Guerry Peavy, University of California San Diego, La Jolla, United States
Haeok Lee, New York University, New York, United States
Howard Feldman, University of California San Diego, La Jolla, United States
Richard Mayeux, Columbia University, New York, United States
Gyungah Jun, Boston University, Boston, United States
Van Ta Park, University of California San Francisco, San Francisco, United States
Tiffany Chow, University of Pennsylvania, Philadelphia, United States


Objective:

Alzheimer’s Disease affects 5.8 million people in the US and 50 million worldwide and is an immense burden on our economy, patients and caregivers.  AD research literature has a strong bias towards European ancestry. Although Asians are the fastest growing population in the US, AD genetics research in Asian Americans is limited.  To this end, we formed Asian Cohort for Alzheimer’s Disease (ACAD) to examine genetic and non-genetic risk factors for AD in Asian populations in the US and Canada, which share similar life experiences, immigration histories, and genetic backgrounds.

Participants and Methods:

The ACAD started fully recruiting in October 2021 with one coordination, eight recruitment, and two analysis sites. The team consisted of scientists, clinicians, and community partners with experience in AD clinical research, genetics, and Asian community outreach.  ACAD developed site-specific community-based participatory research (CBPR) strategies for outreach and recruitment, an extensive data collection packet, and a centralized data management system.

Results:

ACAD data collection is based on the NACC Uniform Data Set (UDS) and contains a total of 17 sections with >200 questions on participant demographics; family, medical and lifestyle across lifespan; cognitive assessments using validated instruments; Functional Assessment Scale (FAS) and neurological assessment. Assessments including pre-screening, consenting, instructions for biosample collection, and cognitive and neurological assessments were conducted in person or by videoconferencing.  The English data collection packet has been translated into Chinese, Korean, and Vietnamese, accompanied by training materials, sample collection instructions, and recruitment scripts.  As of May 2023, ACAD has recruited 713 participants with additional 1,167 expressing interest in enrollment since program inception. 315 have saliva and 198 blood for DNA and blood-based biomarker assays.

Conclusions:

ACAD is the first study of Asians in the US and Canada to comprehensively investigate genetic contributions to AD and interactions with non-genetic risk factors, and establish resources to expand knowledge about these communities and their needs. ACAD pilot data demonstrates feasibility of our recruitment strategy. Ultimately, ACAD will enhance clinical trial readiness by identifying Asian-specific biomarker criteria and promoting AD education to raise awareness and reduce stigma, allowing for greater participation in other studies, provide comprehensive understanding to AD pathophysiology and offer perspectives in dementia prevention strategies. This presentation will introduce the Asian Cohort for Alzheimer’s Disease Study with the rationale, study design considerations, protocols, progress, and lessons learned.  The audience will gain new insights on the challenges and strategies in recruiting underrepresented Asian American and Canadian populations for Alzheimer’s disease research and learn about the latest advances in this area.

Category: Neurodegenerative Disorders

Keyword 1: dementia - Alzheimer's disease
Keyword 2: diversity
Keyword 3: inclusion