1. Identification of serum N-glycoproteins as a biological correlate underlying chronic stress response in mice.
- Author
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Mahmoud ME, Rehan IF, El-Dawy Ahmed K, Abdelrahman A, Mohammadi S, Abou-Elnaga AF, Youssef M, Diab HM, Salman D, Elnagar A, Mohammed HH, Shanab O, Ibrahim RM, Ahmed EKH, Hesham AE, and Gupta A
- Subjects
- Animals, Biomarkers blood, Depression blood, Disease Models, Animal, Female, Glycoproteins analysis, Glycoproteins blood, Glycosylation, Mice, Mice, Inbred BALB C, Polysaccharides blood, Polysaccharides metabolism, Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization methods, Depression metabolism, Polysaccharides analysis, Stress, Physiological physiology
- Abstract
Glycosylation is a post-translational protein modification in eukaryotes and plays an important role in controlling several diseases. N-glycan structure is emerging as a new paradigm for biomarker discovery of neuropsychiatric disorders. However, the relationship between N-glycosylation pattern and depression is not well elucidated to date. This study aimed to explore whether serum N-glycan structures are altered in depressive-like behavior using a stress based mouse model. We used two groups of BALB/c mice; (i) treated group exposed to chronic unpredictable mild stress (CUMS) as a model of depression, and (ii) control group. Behavioral tests in mice (e.g., sucrose preference test, forced swimming test, and fear conditioning test) were used to evaluate the threshold level to which mice displayed a depressive-like phenotype. Serum N-glycans were analyzed carefully using glycoblotting followed by Matrix-assisted laser desorption ionization-time of flight/mass spectrometry (MALDI-TOF/MS) to exhibit N-glycan expression levels and to illustrate the changes in the N-glycome profile. N-glycan expression levels were commonly altered in the depressive-like model and correlated well with the behavioral data. Our results indicated that sialylated N-glycan was identified as a biomarker associated with depressive symptoms, which may have utility as a candidate biomarker for the clinical diagnosis and monitoring of depression.
- Published
- 2019
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