BRIDGE-AD reveals Alzheimer's disease effectors through interpretable large-scale omics integration

Authors

Cerneckis, J., Baltusyte, G., Convey, H., Sun, G., Abela, Z. C. E., Ramirez, M., Wang, D., Sun, G., Zhou, T., Spring, D., Saeb-Parsy, K., Han, N., Shi, Y.

Abstract

The growing landscape of Alzheimer's disease (AD) datasets creates opportunities to integrate heterogeneous evidence and systematically discover disease effectors. We present BRIDGE-AD, an interpretable network medicine framework that transforms multimodal data into a unified, disease-specific gene representation for AD effector prioritisation. We integrated more than 30 datasets and curated resources spanning omics, functional, genetic and prior disease knowledge layers. BRIDGE-AD outperformed recently published pretrained and modality-specific gene embeddings in recovering AD-associated genes and produced a genome-wide resource of candidate AD effectors. Established and newly prioritised effectors formed 19 functional clusters, revealing a global molecular landscape of AD biology. BRIDGE-AD supported an SPP1-centred cross-compartment hypothesis and nominated SCARB2, a poorly characterised candidate, for functional validation. SCARB2 rewired lysosomal, lipid-handling and autophagic programmes in microglia, whereas disrupted SCARB2 glycosylation in AD implicated altered SCARB2 processing and function. The accompanying website, explore-bridgead.com, enables users to trace the curated evidence and generate mechanistic hypotheses.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 21 Sep 2026.

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