Abstract
Brain Commun. 2026 Mar 22;8(2):fcag105. doi: 10.1093/braincomms/fcag105. eCollection 2026.
ABSTRACT
Changes to the relative abundance of amyloid-beta (Aβ) peptides are hallmarks of Alzheimer's disease. Induced pluripotent stem cell (iPSC)-derived neurons offer a physiological model of Aβ production. We employed unbiased, data-driven analyses to investigate combinations of Aβ peptides as Alzheimer's disease biomarkers and the relative contribution of peptides to Alzheimer's disease pathogenesis. We measured Aβ37, Aβ38, Aβ40, Aβ42 and Aβ43 in 10 iPSC-neuronal cultures from PSEN1 mutation carriers. We combined these data with published cell model data and used linear weighted combinations to (i) distinguish Alzheimer's disease from controls, and (ii) predict age-at-onset for PSEN1 mutations. Data-driven approaches distinguished Aβ42 and Aβ43 from shorter peptides, providing unbiased evidence for a greater association of Aβ42 and Aβ43 to disease pathogenesis, compared with shorter peptides (Aβ37, Aβ38 and Aβ40). Weighted linear combinations of Aβ peptides outperform Aβ42/40 and provide insights into relative peptide contribution as biomarkers. A representative weighted composite value ratio (wCVR) derived from all data, balancing both disease classification and age-at-onset prediction, was ( 21 ⋅ A β 37 + 10 ⋅ A β 38 + 69 ⋅ A β 40 ) / ( 94 ⋅ A β 42 + 6 ⋅ A β 43 ) . This work suggests a practical non-parametric harmonization approach to employing Aβ ratios as biomarkers for Alzheimer's disease, from multiple sites and assays. Building on this foundation, we applied a new model using weighted composite value ratios, which outperform existing biomarkers across all tasks. This underscores the value of integrating multiple peptides and assigning optimized weightings. The study confirms the association of Aβ42 and Aβ43 with Alzheimer's disease pathogenesis in a data-driven manner. Peptide weights further provide mechanistic insights into the relative contribution of each peptide to disease, such as a greater contribution of Aβ37 compared to Aβ38. The algorithm used herein can be further refined to improve biomarkers for Alzheimer's disease.
PMID:42022292 | PMC:PMC13096935 | DOI:10.1093/braincomms/fcag105
UK DRI Authors
