Genetically predicted protein concentrations in association with Alzheimer's disease risk: Insights from nonlinear protein modeling
Our study underscores the importance of accounting for nonlinear relationships in uncovering important gene products associated with AD. Our method could improve the understanding of AD pathogenesis and inform future therapeutic and preventive strategies to reduce AD burden.
Authors
- Unhee Lim (ORCID: https://orcid.org/0000-0001-6221-7190)
- Xueqiu Jian (ORCID: https://orcid.org/0000-0002-0313-6494)
- Ben Dai (ORCID: https://orcid.org/0000-0002-1620-1021)
- Jingjing Zhu
- Chong Wu (ORCID: https://orcid.org/0000-0002-9593-293X)
- Keenan A. Walker (ORCID: https://orcid.org/0000-0002-5989-9853)
- Quan Long (ORCID: https://orcid.org/0000-0003-3795-1873)
- Youping Deng
- Lang Wu
- Zhongming Zhao
Institutions
- University of Hawaiʻi at Mānoa (US)
- National Institutes of Health (US)
- University of Hawaii System (US)
- The University of Texas MD Anderson Cancer Center (US)
- The University of Texas at San Antonio Health Science Center (US)
- University of Calgary (CA)
- Chinese University of Hong Kong (HK)
- Cancer Center of Hawaii (US)
- The University of Texas Health Science Center at Houston (US)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1002/alz70856_099503
- Primary Topic
- Genetic Associations and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 0.00