Integrated genomic meta-analysis identifies cell-type-specific signatures and targets in early Alzheimer’s disease
Year: 2026
Type: preprint
Abstract: Cellular mechanisms in early Alzheimer’s disease (AD) remain poorly understood despite generation of extensive observational multiomic data. Weighted integration across diverse datasets can prioritise convergent mechanisms and targets. We conducted a systematic review to identify datasets profiling cell-type-specific changes in early AD. We integrated multiomic findings using Meta-Analysis by Information Content (MAIC), a computational method which combines genomic data from diverse experimental sources. Electron transport chain dysfunction in mitochondria emerged as a shared pathway in neurons, microglia, and astrocytes, and Wnt signalling was a prominent astrocyte-specific signature. Pathological neuro-glial signalling mechanisms included APP-CD74, APOE-SORL1, and WNT-FZD/LRP6. Integration with pharmacological data identified therapeutics already under investigation in AD, such as guanfacine, and candidates not previously prioritised, such as eltrombopag and encorafenib. We present a systematic analysis of cell-type-specific changes in early AD to prioritise pathways for investigation and therapeutics for repurposing.
Source: medRxiv
Language: English
Subfield: Cellular and Molecular Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
Awards: G1109727603, G1147936081, G1925463342, G2409359785, G2759079240, G3487910343, G5799633523, G6456837005, G6690987417, G6783509755, G7267735475, The Edinburgh Molecular Mechanisms Cluster, G862200495, G8765071762, Translational genomics in critical care medicine., Translational genomics in critical care medicine., G931666629
OpenAlex ID: W7214108114
