The treatment landscape for Alzheimer's disease (AD) faces challenges such as prolonged drug development, high costs, and limited FDA-approved therapies. Given the pathological similarities between Early-Onset AD (EOAD) and Late-Onset AD (LOAD), repurposing existing drugs offers a promising strategy to expedite therapeutic development. In this study, weighted gene coexpression network analysis (WGCNA) was applied to identify AD-associated gene modules, followed by network pharmacology to screen candidate compounds. Parthenolide was selected based on blood-brain barrier permeability and disease relevance. Its effects were evaluated using LPS-stimulated BV2 microglia, N2a-sw and HT22 neuronal models, and transgenic AD mouse models. Transcriptomic integration, transcription factor enrichment, pharmacological inhibition, and in vivo behavioral and pathological analyses were employed to elucidate underlying mechanisms. Our findings reveal that parthenolide markedly suppressed microglial activation and reduced pro-inflammatory mediators via modulation of the HIF1α/NF-κB signaling axis. Bioinformatics analysis identified HIF1α as a key hub gene, which was experimentally validated using the selective inhibitor YC-1. Parthenolide attenuated inflammation-induced amyloidogenesis by downregulating amyloid β precursor protein (APP) expression and the γ-secretase component Aph-1A γ-Secretase Subunit (APH1α). In vivo, parthenolide administration significantly improved cognitive performance, reduced microglial activation, decreased β-amyloid plaque burden, and suppressed HIF1α/NF-κB-dependent inflammatory signaling in 5 × FAD mouse models. In conclusion, this study demonstrates that parthenolide exerts multitarget therapeutic effects in AD by concurrently suppressing neuroinflammation and amyloidogenic processing. Targeting the HIF1α/NF-κB axis may represent a promising strategy for modulating inflammatory-metabolic-amyloid networks in AD.