Citation
Abstract
Depression is a serious psychological disorder with high prevalence rates, especially among university students. Serum proteins related to the immune system and oxygen and lipid transfer could have contributing roles in the development of depression and could act as biomarkers for depression. Currently, there is a lack of accurate biological methods that can be used to diagnose depression. Biomarkers could be an inexpensive and convenient way to predict depression and understand its pathophysiology. This study aimed to screen the serum proteome profile of a depressed student for the identification of potential depression biomarkers. A Malaysian private university student who was recruited from the pre-test study (n = 10) was further analyzed for serum proteome due to the fact that he was depressed, with scores of 15 out of 27 on the Patient Health Questionnaire (PHQ-9). After depleting the high-abundance proteins from the serum sample, liquid chromatography-tandem mass spectrometry (LC-MS/MS) was performed to identify the expressed proteins. A total of 224 proteins were identified. Globins, globulins, apolipoproteins and glycoproteins were most commonly detected. Here, we show the potential biomarkers that can be used to identify depression vulnerable individuals. These findings may be relevant to the development of new diagnostic and treatment strategies. However, further studies with larger sample sizes and healthy controls are needed to confirm the role of these candidate biomarkers for the prediction and diagnosis of depression.
Download File
Full text not available from this repository.
Official URL or Download Paper: https://www.mdpi.com/2673-9992/21/1/10
|
Additional Metadata
Item Type: | Article |
---|---|
Divisions: | Faculty of Medicine and Health Science |
DOI Number: | https://doi.org/10.3390/ecb2023-14089 |
Publisher: | Multidisciplinary Digital Publishing Institute |
Keywords: | Protein markers; Depressed; Chinese; Malaysian; University students |
Depositing User: | Ms. Zaimah Saiful Yazan |
Date Deposited: | 11 Sep 2024 03:21 |
Last Modified: | 11 Sep 2024 03:21 |
Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3390/ecb2023-14089 |
URI: | http://psasir.upm.edu.my/id/eprint/108249 |
Statistic Details: | View Download Statistic |
Actions (login required)
View Item |