| Title: | Proteome-wide association study identifies novel Alzheimer's disease-associated proteins. |
| Journal: | Journal of Alzheimer's Disease |
| Published: | 29 Dec 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41460672/ |
| DOI: | https://doi.org/10.1177/13872877251409352 |
Publication 16961
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Abstract
BackgroundAlzheimer's disease (AD) is a progressive neurodegenerative disease with limited prevention and treatment options.ObjectiveWe aimed to identify proteins with genetically regulated plasma levels associated with AD and its related phenotypes.MethodsWe conducted a proteome-wide association study (PWAS) using Olink-based plasma proteomes (N = 45,540) from the UK Biobank Pharma Proteomics Project (UKB-PPP) and a large-scale genome-wide association study for AD (N case = 85,934, N control = 401,577). To validate and expand these findings, we conducted longitudinal analyses of AD and mild cognitive disorder (MCD) over a 13.7-year follow-up, along with genetic-based PWAS analyses and cross-sectional studies on hippocampal volume. Protein-protein interaction networks were constructed to explore mechanistic association.ResultsWe identified 30 AD-associated plasma proteins by PWAS, including 17 previously reported and 13 novel candidates (including FES, LRP11, and HDGF). Longitudinal cohort studies supported the role of PILRB and FES in AD and/or MCD. Additionally, the genetically determined higher levels of LRP11 were found to be associated with an increased hippocampal volume, including its subdivisions, along with a reduced risk of AD. In contrast, higher plasma levels of HDGF were linked to a decreased hippocampal volume, accompanied by an increased risk of AD. Protein-protein interaction analysis linked PILRA, PILRB, FES, and LRP11 to several pathological proteins associated with AD, including BIN1, ABCA7, and SORL1.ConclusionsThis study identified 13 novel candidates, with potential roles in hippocampal volume and AD risk, providing insights into disease mechanisms.</p>
11 Authors
- Lingyun Sun
- Guikang Wei
- Feiyang Ji
- Yihong Ding
- Jiayao Fan
- Yue Xu
- Chunfeng He
- Yuan Zhou
- Zuyun Liu
- Zeyu Sun
- Dan Zhou
1 Application
| Application ID | Title |
|---|---|
| 102158 | Causal gene mapping for complex traits by leveraging genomics and proteomics data |
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