Poster Presentations
Day 2, June 11（Thu.） Room P (5F 501+502)
- 2P-11
Integrated Proteomic and Metabolomic Profiling of Urinary Extracellular Vesicles Reveals Early Biomarkers of Sepsis-Induced Acute Kidney Injury
(1TMU Biochemistry, 2TMU, College of Pharmacy, 3TMU, Medical Sciences, 4NTU, Graduate Institute of Forensic Medicine, 5TMU, College of Medicine, 6TMU Hospital, Internal Medicine, 7TMU-RCUK, 8TMU, Shuang Ho Hospital, 9TMU, School of Pharmacy, 10TMU, Core Lab Neoantigen, 11UBC, Pathology & Lab Medicine, 12UVic, Division of Medical Sciences)
oTanyu Chang1,2, I-Lin Tsai1,2,3, Guan-Yuan Chen4, Te-I Weng4, San-Yuan Wang2, Yueh-Chu Sio5,6,7, Ching-Yi Chen5,6,7, Li-Yee Hong5,7,8, I-Jen Chiu5,7,8, Yen-Chung Lin5,6,7, Hsi-Hsien Chen5,6,7, Wei-Chiao Chang2,9,10, Mai-Szu Wu5,7,8, Michael X. Chen11,12, Chih-Chin Kao5,6,7
Background
Acute kidney injury (AKI) is a common and life-threatening complication of sepsis, yet current diagnostic tools lack sensitivity for early detection. Extracellular vesicles (EVs) have emerged as important mediators in sepsis-induced AKI (S-AKI), but their potential as a source of early biomarkers remains underexplored.
Methods
In this prospective longitudinal study, 52 patients with sepsis (29 with S-AKI and 23 without) were enrolled. Urine samples were collected at diagnosis and during follow-up, and urinary EVs were subjected to comprehensive proteomic and metabolomic profiling. Differential expression and longitudinal analyses were performed to identify candidate biomarkers associated with S-AKI progression.
Results
We identified multiple differentially expressed proteins across time points, among which five proteins—FABP4, MYOC, LYZ, PFN1, and CFD—were consistently upregulated. Notably, FABP4, LYZ, and CFD were also associated with patient survival, suggesting their potential to predict both AKI development and clinical outcomes. Expression of FABP4 and LYZ was further validated by ELISA.
Conclusions
These findings highlight urinary EV-based multi-omics profiling as a promising strategy for early S-AKI biomarker discovery and provide new insights into disease pathogenesis.
Keywords: acute kidney injury (AKI), sepsis, extracellular vesicles (EVs), proteomics, metabolomics, biomarker