Fifteen potential drug targets for Alzheimer's disease (AD) were identified, with six considered the highest-confidence targets.
Six targets (PILRA, GRN, ACE, TIMD3, TREM2) were validated as the most reliable options for further research.
IDUA may lower AD risk by influencing Aβ42 and p-tau levels in cerebrospinal fluid.
Siglec-7/9 could increase AD risk through effects on p-tau in cerebrospinal fluid.
Single-cell analysis suggested key roles for specific microglial and astrocyte targets.
Protein interaction network analysis showed connections between seven drug targets and four existing AD treatments.
Seven potential therapeutics were identified through druggability assessment.
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BACKGROUND: The development of effective disease-modifying therapies for Alzheimer's disease (AD) remains a critical unmet need. While (MR) has been leveraged to identify genetic variants to accelerate AD target discovery, previous studies have been limited by narrow phenotypic coverage, insufficient multiomics validation, and inadequate mechanistic exploration. This study aims to overcome these limitations via comprehensive MR to identify robust therapeutic targets.
METHODS: We performed an integrative multiomics MR analysis leveraging over 50 genome-wide association study (GWAS) datasets spanning AD, cerebrospinal fluid (CSF) biomarkers (Aβ42, p-tau), neuroimaging endophenotypes, cognitive traits, and risk factors. Blood/CSF/brain protein quantitative trait loci (pQTLs) from large-scale proteomics studies were analyzed to identify druggable targets. A rigorous validation cascade was subsequently performed: Bayesian colocalization was performed to assess whether the same variants are associated with the protein and other traits; summary-data-based MR was performed to distinguish pleiotropy from linkage; mediation analysis was performed to quantify biomarker-driven causal pathways; integrated analysis of multiomics (single-cell RNA-seq and proteome) data was performed to resolve cellular specificity, and (PPI) interaction networks were generated; phenome-wide MR (Phe-MR) was performed across 679 traits to evaluate on-target side effects; and structure-based druggability screening was conducted.
RESULTS: Proteome-wide MR analysis revealed 15 potential drug targets for AD; six of these targets (PILRA, GRN, ACE, TIMD3, TREM2) were validated as Tier 1 (highest-confidence targets with external validation and causal consistency). Mediation analysis revealed that IDUA reduced the risk of AD through Aβ42 and p-tau in the CSF, whereas Siglec-7/9 increased the risk of AD through p-tau in the CSF. Additional targets revealed associations with AD biomarkers, neuroimaging, and cognitive function. Single-cell analysis highlighted the enrichment of key microglial and astrocyte targets. PPI network analysis revealed interaction pathways between seven drug targets and four AD therapeutics, and druggability assessment revealed seven potential therapeutics.
CONCLUSIONS: This study established a comprehensive AD target atlas, revealing mechanism-anchored targets that were validated across multiomics analyses and a clinically actionable framework integrating efficacy, biology, and safety profiling. Overall, these results advance AD drug discovery by revealing prioritized targets with causal biological support and providing a validated development roadmap.
Key numbers
15
Potential Drug Targets Identified
Total drug targets identified for Alzheimer's disease.
6
Tier 1 Drug Targets
High-confidence targets validated through external datasets.
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