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Single-cell gene networks nominate IKZF1 as an Alzheimer's microglial regulator
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Abstract
BackgroundMicroglia drive neuroinflammation in Alzheimers disease (AD), yet no approved therapy targets this compartment. Human genome-wide association studies consistently implicate innate immune loci in AD risk, establishing microglial transcriptional programs as therapeutically relevant but pharmacologically underexploited targets. ObjectiveWe sought to identify transcription factors (TFs) governing microglial state transitions computationally and to nominate structurally tractable drug repurposing candidates. MethodsWe applied trajectory inference (PAGA), pseudobulk DESeq2, pySCENIC gene regulatory network (GRN) inference, CellChat, and virtual screening of 1,962 approved compounds to 236,002 microglial nuclei from 84 donors (SEA-AD atlas). ResultsIKZF1 was the sole target TF retained under cisTarget v10 motif constraints, with peak regulon activity in LateAD-DAM (pseudotime {rho} = +0.309) and replication in an independent bulk cohort (GSE95587; adjusted P value =.004). CellChat identified SLIT2[->]ROBO2 from multiple neuron subtypes (predominantly inhibitory interneurons) as the top predicted pathway to microglia. Tafamidis ([->]IRF8) and diflunisal ([->]PPARG) were top virtual screening hits; all evaluated compounds failed the pre-specified selectivity threshold. ConclusionsIKZF1 is prioritised as a candidate late-disease microglial TF, supported by six convergent evidence dimensions including independent bulk replication. Tafamidis and diflunisal are low-confidence repurposing hypotheses requiring experimental validation.
- organism: human
- assay: scRNA-seq
- research focus: gene regulatory network inference
- research focus: drug response / drug discovery
- approach: statistical model
- approach: machine learning (classical)
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