Plasma proteomic analysis identifies proteins and pathways related to Alzheimer's risk

Abstract

Introduction: We investigated associations of plasma proteins with blood-based amyloid/tau/neurodegeneration/inflammation (A/T/N/I) biomarkers for Alzheimer's disease (AD). Methods: Plasma proteomics and clinical data from the Indiana AD Research Center (N = 498) were used. Association analysis of plasma proteins with blood A/T/N/I biomarkers as well as diagnosis was performed, followed by replication in an independent cohort (N = 323), network analysis, pathway enrichment, and machine learning classification to identify proteins and pathways related to AD risk. Results: We identified 35 proteins associated with AD, 20 of which were replicated in the independent cohort. We identified 150, 448, and 219 proteins associated with T/N/I biomarkers, respectively, revealing biomarker-specific pathways. Network analysis identified two modules associated with T/N/I biomarkers, preserved in cerebrospinal fluid (CSF), and their enriched pathways. The classification model of proteins effectively differentiated AD (area under the curve [AUC] = 0.930). Conclusion: Our findings suggest dysregulated plasma proteins and pathways in AD, enhancing our understanding of molecular mechanisms and diagnostic strategies for AD. Highlights: Plasma proteins were identified as being associated with Alzheimer's disease (AD) and plasma biomarkers. The identified proteins were replicated in both plasma and cerebrospinal fluid (CSF) proteomics. The identified proteins were associated with AD biomarker-specific pathways. The identified proteins improved the performance of the AD classification. Protein network analysis identified network modules and their enriched pathways.