42: Application of the STAAR Framework in Detecting Rare Variant Associations with Alzheimer's Disease and Related Dementias: Insights and Implications

Nancy Heard-Costa Co-Author
Department of Medicine, Boston University School of Medicine;NHLBI Framingham Heart Study
 
Andy Rampersaud Co-Author
Research Computing Services, Information Services & Technology, Boston University
 
Eden Martin Co-Author
University of Miami-Miami Institute of Human Genomics
 
Adam Naj Co-Author
Department of Biostatistics, Epidemiology, and Informatics, Department of Pathology and Laboratory
 
Bilcag Akgun Co-Author
John P Hussman Institute for Human Genomics
 
Brian Kunkle Co-Author
John P Hussman Institute for Human Genomics; John T Macdonald Department of Human Genetics
 
Gina Peloso Co-Author
 
Anita DeStefano Co-Author
Department of Biostatistics, Boston University School of Public Health
 
Xihao Li Co-Author
University of North Carolina at Chapel Hill
 
Seung Hoan Choi Co-Author
Department of Biostatistics, Boston University School of Public Health
 
Dongyu Wang First Author
Department of Biostatistics, Boston University School of Public Health
 
Dongyu Wang Presenting Author
Department of Biostatistics, Boston University School of Public Health
 
Tuesday, Aug 5: 2:00 PM - 3:50 PM
1340 
Contributed Posters 
Music City Center 
Introduction: Rare genetic variation is considered a potential source of heritability in individuals with sporadic Alzheimer's Disease and related dementias (ADRD). The STAAR framework leverages multiple functional annotations of genetic variants and combines association statistics from multiple variant aggregation-based methods, including burden, SKAT, and ACAT-V, into a single measure of significance.

Method: Using whole genome sequencing data from the Alzheimer's Disease Sequencing Project (ADSP), we comprehensively examined the association of rare genetic variation with ADRD in 23,455 individuals (37% ADRD cases) and with cognitively healthy elder status in 13,292 individuals (13% cognitively healthy elders) from diverse populations via the STAAR framework.

Results: We identified several genes significantly associated with ADRD or cognitively healthy status. However, our analysis revealed several limitations within the STAAR framework incorporating ultra-rare variants with dichotomous outcomes. To enhance the robustness of the framework, we proposed several computational refinements, including creating a burden of ultra-rare variants and employing more precise annotations to match with expected mechanism. After implementing the proposed modifications, the association with ADRD for ZNF200 was no longer statistically significant (α=1x10-7), while TBX19, PLXNB2, CARD11, and LINC01880 remained significantly associated with cognitively healthy status.

Conclusion: We identified and addressed the computational limitations in the STAAR framework that could lead to potential spurious results for ultra-rare variant aggregates with an extremely low cumulative minor allele count. Our proposed refinements produced more robust results for associations with rare variants in the context of dichotomous outcomes.

Keywords

Rare varaint analysis

STAAR framework

Alzheimer's disease 

Main Sponsor

Section on Statistics in Genomics and Genetics