Multiomics Patterns and Alzheimer’s Disease Risk
This study demonstrates the utility of multiomics integration for uncovering biologically relevant patterns in AD and its potential application disease risk stratification. Future research should focus on validating these patterns in larger, independent cohorts and exploring their utility in clinical applications.
Authors
- James D. Doecke (ORCID: https://orcid.org/0000-0003-2863-0293)
- Michael A. Vacher (ORCID: https://orcid.org/0000-0003-0375-8370)
- Elizabeth Asque
- Magdalena Rogozinska
- Fedik Rahimov (ORCID: https://orcid.org/0000-0001-6519-7404)
- Eleanor K. O’Brien (ORCID: https://orcid.org/0000-0001-5145-7340)
- Lidija Milicic (ORCID: https://orcid.org/0000-0002-2104-1413)
- Ameya Kulkarni (ORCID: https://orcid.org/0000-0003-4495-8838)
- Sara Ishak
- Jeffrey F. Waring (ORCID: https://orcid.org/0000-0002-7769-0367)
- Aparna Vasanthakumar (ORCID: https://orcid.org/0000-0003-3857-8812)
- Keysury Curro
- Milcent Tsvangiray
- Vinny Vijayakumar
- Claire Konefal
- Annita Martin
- Simon M. Laws
- Tenielle Porter
- Erin Murphy
Institutions
- Edith Cowan University (AU)
- Commonwealth Scientific and Industrial Research Organisation (AU)
- AbbVie (United States) (US)
- Australian e-Health Research Centre (AU)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1002/alz70861_108392
- Primary Topic
- Alzheimer's disease research and treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00