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

  • bioRxiv. 2026 Sep 24:2026.09.14.750802. doi: 10.64898/2026.09.14.750802.
Greta Baltusyte ,  Jonas Cerneckis ,  Harry Convey ,  Guoqiang Sun ,  Zyrille C E Abela ,  Miguel Ramirez ,  Daniel Wang ,  Guihua Sun ,  Tao Zhou ,  David Spring ,  Kourosh Saeb-Parsy ,  Yanhong Shi ,  Namshik Han
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, https://explore-bridgead.com, enables users to trace the curated evidence and generate mechanistic hypotheses.

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