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Alzheimer9s disease (AD) is a multifactorial pathology responsible for most cases of dementia worldwide. Only a small percentage of AD cases are due to autosomal dominant mutations, while the vast majority have a sporadic presentation. Yet, preclinical research studies relied for decades on animal models that overexpress human genes found in AD autosomal dominant patients. Thus, one could argue that these models do not recapitulate sporadic AD. To avoid human gene overexpression artifacts, knock-in (KI) models have been developed, such as the novel hAβ-KI mouse model, which are still in early phases of characterization. We hypothesize that comparisons at the transcriptomic level may elucidate critical similarities and differences between transgenic/KI models and AD patients. Thus, we aimed at comparing the hippocampal transcriptomic profiling of overexpression (5xFAD and APP/PS1) and KI (hAβ-KI) mouse models with early- (EOAD) and late- (LOAD) onset AD patients. We first evaluated differentially expressed genes (DEGs) and Gene Ontology biological processes (GOBP) overlapping cross-species. After, we explored a network-based strategy to identify master regulators (MR) and the similarities of such elements among models and AD subtypes. A multiple sclerosis (MS) dataset was included to test the molecular specificity of the mouse models to AD. Our analysis revealed that all three mouse models presented more DEGs, GOBP terms and enriched signaling pathways in common with LOAD than with EOAD subjects. Furthermore, semantic similarity of enriched GOBP terms showed mouse model-specific biological alterations, and protein-protein interaction analysis of DEGs identified clusters of genes exclusively shared between hAβ-KI mice and LOAD. Furthermore, we identified 17 transcription factor candidates potentially acting as MR of AD in all three models. Finally, though all mouse models showed transcriptomic similarities to LOAD, hAβ-KI mice presented a remarkable specificity to this AD subtype, which might support the use of the novel hAβ-KI mouse model to advance our understanding of sporadic LOAD.