Literature DB >> 33960196

Quantitative Proteomic Approach for Discriminating Major Depressive Disorder and Bipolar Disorder by Multiple Reaction Monitoring-Mass Spectrometry.

Dongyoon Shin, Sang Jin Rhee1,2, Jihyeon Lee, Injoon Yeo, Misol Do, Eun-Jeong Joo3,4, Hee Yeon Jung1,5,6, Sungwon Roh7,8, Sang-Hyuk Lee9, Hyeyoung Kim10, Minji Bang9, Kyu Young Lee3,4, Jun Soo Kwon1,2,6, Kyooseob Ha1,2,6, Yong Min Ahn1,2,6, Youngsoo Kim.   

Abstract

Because major depressive disorder (MDD) and bipolar disorder (BD) manifest with similar symptoms, misdiagnosis is a persistent issue, necessitating their differentiation through objective methods. This study was aimed to differentiate between these disorders using a targeted proteomic approach. Multiple reaction monitoring-mass spectrometry (MRM-MS) analysis was performed to quantify protein targets regarding the two disorders in plasma samples of 270 individuals (90 MDD, 90 BD, and 90 healthy controls (HCs)). In the training set (72 MDD and 72 BD), a generalizable model comprising nine proteins was developed. The model was evaluated in the test set (18 MDD and 18 BD). The model demonstrated a good performance (area under the curve (AUC) >0.8) in discriminating MDD from BD in the training (AUC = 0.84) and test sets (AUC = 0.81) and in distinguishing MDD from BD without current hypomanic/manic/mixed symptoms (90 MDD and 75 BD) (AUC = 0.83). Subsequently, the model demonstrated excellent performance for drug-free MDD versus BD (11 MDD and 10 BD) (AUC = 0.96) and good performance for MDD versus HC (AUC = 0.87) and BD versus HC (AUC = 0.86). Furthermore, the nine proteins were associated with neuro, oxidative/nitrosative stress, and immunity/inflammation-related biological functions. This proof-of-concept study introduces a potential model for distinguishing between the two disorders.

Entities:  

Keywords:  bipolar disorder (BD); generalizable model; major depressive disorder (MDD); multiple reaction monitoring-mass spectrometry (MRM-MS); quantitative targeted proteomics

Year:  2021        PMID: 33960196     DOI: 10.1021/acs.jproteome.1c00058

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  2 in total

1.  Integrating proteomic and clinical data to discriminate major psychiatric disorders: Applications for major depressive disorder, bipolar disorder, and schizophrenia.

Authors:  Dongyoon Shin; Sang Jin Rhee; Daun Shin; Eun-Jeong Joo; Hee Yeon Jung; Sungwon Roh; Sang-Hyuk Lee; Hyeyoung Kim; Minji Bang; Kyu Young Lee; Se Hyun Kim; Jihyeon Lee; Yoseop Kim; Injoon Yeo; Yeongshin Kim; Jaenyeon Kim; Jun Soo Kwon; Kyooseob Ha; Yong Min Ahn; Youngsoo Kim
Journal:  Clin Transl Med       Date:  2022-06

2.  Alterations in blood proteins in the prodromal stage of bipolar II disorders.

Authors:  Hyunju Lee; Dohyun Han; Sang Jin Rhee; Jayoun Kim; Yunna Lee; Eun Young Kim; Dong Yeon Park; Sungwon Roh; Myungjae Baik; Hee Yeon Jung; Junhee Lee; Tae Young Lee; Minah Kim; Hyunsuk Shin; Hyeyoon Kim; Se Hyun Kim; Jun Soo Kwon; Yong Min Ahn; Kyooseob Ha
Journal:  Sci Rep       Date:  2022-02-24       Impact factor: 4.379

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.