To date, several studies have integrated genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) data from bulk tissues to identify novel Alzheimer's disease (AD) genetic variants and susceptibility genes. However, there is highly cell-type-specific nature in different bulk eQTL data. Until now, eQTL data from different brain single cells have been reported. Therefore, integrating eQTL data from different brain single-cell types along with AD GWAS data makes biological sense for studying the potential biological explanations of AD. Here, we utilized the summary-data-based Mendelian randomization (SMR) method to integrate AD GWAS data with eQTL data from eight brain single-cell types. We identified a larger number of significant genes compared to previous SMR study based on bulk eQTL. Notably, microglia exhibited the highest number of significant genes. Moreover, we conducted validation-phase SMR analysis, single-cell analysis, protein-protein interaction (PPI), druggability evaluation, functional enrichment analyses, and colocalization analysis of the top 20 SMR significant genes in microglia. We found that most genes passed the validation and were significantly enriched in microglia. PPI analysis uncovered interactions among PICALM, BIN1, RIN3, CD2AP, CASS4, and MS4A6E. Five most significant SMR genes were further validated through colocalization analysis. RIN3 is the only significant gene across all mentioned analyses and is a novel AD susceptibility gene at the genome-wide significance level. Druggability evaluation identified KCNQ3, HLA-DQB1, and RABEP1 as known genes previously targeted for drug development in neurological disorders, suggesting their potential therapeutic relevance in AD.image