Updated FTP location. Background/Aims: The discovery of predictive biomarker for Alzheimer’s disease (AD) from urine would be highly beneficial for preventative approach of the disease, but the information about biological and pathophysiological changes observed in the molecular composition of urine of AD patient is limited. This study aimed to explore the comprehensive profile and molecular network relations of urinary proteins in the urine of AD patients. Methods: Urine samples collected from 18 AD patients and 18 age- and sex- matched cognitively normal controls were analyzed by mass spectrometry and semi-quantified by normalized spectral index method. Bioinformatics analyses were performed on the proteins which significantly increased more than two-fold or decreased less than 0.5-fold compared to the control (p< 0.05) using DAVID bioinformatics resources and KeyMolnet software. Results: 109 proteins were significantly increased or decreased in AD urine compared to control. Among those differentially expressed proteins, annotation clusters related to lysosome, complement activation, and gluconeogenesis were significantly enriched. The molecular relation network calculated from those proteins were mainly associated to pathways of lipoprotein metabolism, heat shock protein 90 signaling, matrix metalloproteinase signaling, and redox regulation by thioredoxin. Conclusion: The study suggested that the change of urinary proteome reflect the systemic change related to AD pathophysiology.