[3P] Poster

[3P-364] Integrating spatial transcriptomics and machine learning analysis of amyloid-β pathology reveals microglial environments and plaque-associated genes in Alzheimer’s disease

*Okiru Komine¹, Ryosaku Ota², Yuichiro Yada², Akira Sobue¹, Yasuyoshi Oka³, Fumito Endo¹, Mayuko Shimada³, Jun-ichi Takeda⁴, Yuko Saito⁵, Shigeo Murayama^5,6, Tomoo Ogi³, Takashi Saito⁷, Naoki Honda^2,8, Koji Yamanaka¹ (1. Dept Neurosci Pathobiol, Res Inst Env Med, Nagoya Univ, Nagoya, Japan, 2. Grad Sch Med, Nagoya Univ, Nagoya, Japan, 3. Dept Genet, Res Inst Env Med, Nagoya Univ, Nagoya, Japan, 4. COMIT, Inst Adv Stu, Gifu Univ, Gifu, Japan, 5. Brain Bank Aging Res, Tokyo Met Geria Hosp Inst Geront, Tokyo, Japan, 6. Brain Bank Neurodev, Neurolo, Psychiat Dis, Unit Grad Sch Chil Dev, Univ of Osaka, Osaka, Japan, 7. Inst Brain Sci, Grad Sch Med, Nagoya City Univ, Nagoya, Japan, 8. Grad Sch Int Sci Life, Hiroshima Univ, Hiroshima, Japan)

Keywords:

Alzheimer's disease,Spatial Transcriptomics,Machine Learning,Microglia

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