Molecular Network Analysis of the Urinary Proteome of Alzheimer’s Disease Patients

Abstract

Background/Aims: The identification of predictive biomarkers for Alzheimer’s disease (AD) from urine would aid in screening for the disease, but information about biological and pathophysiological changes in the urine of AD patients is limited. This study aimed to explore the comprehensive profile and molecular network relations of urinary proteins in 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 semiquantified with the normalized spectral index method. Bioinformatics analyses were performed on proteins which significantly increased by more than 2-fold or decreased by less than 0.5-fold compared to the control (p < 0.05) using DAVID bioinformatics resources and KeyMolnet software. Results: The levels of 109 proteins significantly differed between AD patients and controls. Among these, annotation clusters related to lysosomes, complement activation, and gluconeogenesis were significantly enriched. The molecular relation networks derived from these proteins were mainly associated with pathways of lipoprotein metabolism, heat shock protein 90 signaling, matrix metalloproteinase signaling, and redox regulation by thioredoxin. Conclusion: Our findings suggest that changes in the urinary proteome of AD patients reflect systemic changes related to AD pathophysiology.

Quantitative proteomics of synaptosome S‐nitrosylation in Alzheimer’s disease

“…GOT1 is localized in the cytoplasm and acts as a scavenger of glutamate in brain neuroprotection. To our knowledge, there is only scarce data on its specific functions in neurons or synapses, but GOT1 activity was found to be increased in CSF (D’Aniello et al ) and urine (Watanabe et al ) of patients with Alzheimer disease compared to controls. The SNO site described in this study on position 46 of the human sequence has been previously found in a technical setting (Forrester et al ).…”

Urinary Biomarkers for Neurodegenerative Diseases

“…However, to designate a specific substance as a biomarker, a high-throughput method or an educated guess is necessary. Therefore, despite its cost, MS-based proteomic analysis and metabolic profiling of urine from patients with a specific disease is gaining prominence to identify a novel disease-specific biomarker [14][15][16]. If the target material is nucleic acid, next generation sequencing or small RNA sequencing can be a tool for a high-throughput screening method [17].…”

Gene Ontology: A Resource for Analysis and Interpretation of Alzheimer’s Disease Data

“…Lipoprotein metabolism, heat shock protein 90 signaling pathway, and matrix metalloproteinase signaling pathway as well as redox regulation by thioredoxin were among the molecular pathways with the highest enrichment scores, providing evidence for impairment of vascular processes key to the development of dementia (66). In addition, Watanabe et al (66) also supplemented their functional GO and KEGG analyses with an interrelation network analysis to determine, which of the proteins differentially expressed in the Alzheimer' s urine samples interact with each other (either directly or via an intermediate). This network analysis of molecular relationships enabled these researchers to further elucidate which GO biological processes and KEGG pathways should be prioritized in future studies and whether they correlate with and confirm other findings.…”

“…GO term enrichment analysis has also been implemented in pilot studies aiming to identify biomarkers associated with dementia, which can be detected using noninvasive methods in easily accessible bodily fluids, such as blood (65) and urine (66). For instance, Chouliaras et al (65) used GO enrichment together with KEGG pathway analysis to demonstrate the relationships between the identified blood biomarkers with neurological processes and neuronal components.…”

“…Similarly, Watanabe et al (66) used GO term enrichment and KEGG pathway analyses to delineate the roles of proteins differentially expressed in urine of Alzheimer' s patients relative to healthy controls to identify a urine biomarker signature, which could be used for noninvasive diagnostic purposes. Lipoprotein metabolism, heat shock protein 90 signaling pathway, and matrix metalloproteinase signaling pathway as well as redox regulation by thioredoxin were among the molecular pathways with the highest enrichment scores, providing evidence for impairment of vascular processes key to the development of dementia (66). In addition, Watanabe et al (66) also supplemented their functional GO and KEGG analyses with an interrelation network analysis to determine, which of the proteins differentially expressed in the Alzheimer' s urine samples interact with each other (either directly or via an intermediate).…”