Identification of potential protein biomarkers in a depressed chinese malaysian university student using liquid chromatography-tandem mass spectrometry
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. Curren...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
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Multidisciplinary Digital Publishing Institute
2023
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| Online Access: | http://psasir.upm.edu.my/id/eprint/108249/ https://www.mdpi.com/2673-9992/21/1/10 |
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| Summary: | 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. |
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