Integrative multi‐omics approaches identify molecular pathways and improve Alzheimer's disease risk prediction
Identified novel contributions to Alzheimer's disease (AD) from a multi-omics perspective. Integrated genome-wide association studies (GWAS), transcriptome-wide association studies (TWAS), and proteome-wide association studies (PWAS) in a unified association study framework. Developed a method for predicting heritable risk of late-onset AD. Demonstrated that ancestry-aware modeling improves AD risk prediction accuracy.
Authors
- Rasika Venkatesh (ORCID: https://orcid.org/0009-0003-4471-4291)
- Jason H. Moore (ORCID: https://orcid.org/0000-0002-5015-1099)
- Anni Moore (ORCID: https://orcid.org/0000-0003-1953-6449)
- Rachit Kumar (ORCID: https://orcid.org/0000-0002-7736-3307)
- Li Shen (ORCID: https://orcid.org/0000-0001-6520-1418)
- Marylyn DeRiggi Ritchie (ORCID: https://orcid.org/0000-0002-1208-1720)
- Katie M. Cardone
- Dokyoon Kim
- Yuki Bradford
Institutions
- Cedars-Sinai Medical Center (US)
- University of Pennsylvania (US)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2025-11-01
- DOI
- https://doi.org/10.1002/alz.70886
- Citations
- 3
- Primary Topic
- Genetic Associations and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 5.45
Funders
- National Institutes of Health
- National Heart, Lung, and Blood Institute