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Rhee SJ, Shin D, Shin D, Song Y, Joo EJ, Jung HY, Roh S, Lee SH, Kim H, Bang M, Lee KY, Lee J, Kim J, Kim Y, Kim Y, Ahn YM. Network analysis of plasma proteomes in affective disorders. Transl Psychiatry 2023; 13:195. [PMID: 37296094 DOI: 10.1038/s41398-023-02485-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 05/13/2023] [Accepted: 05/23/2023] [Indexed: 06/12/2023] Open
Abstract
The conventional differentiation of affective disorders into major depressive disorder (MDD) and bipolar disorder (BD) has insufficient biological evidence. Utilizing multiple proteins quantified in plasma may provide critical insight into these limitations. In this study, the plasma proteomes of 299 patients with MDD or BD (aged 19-65 years old) were quantified using multiple reaction monitoring. Based on 420 protein expression levels, a weighted correlation network analysis was performed. Significant clinical traits with protein modules were determined using correlation analysis. Top hub proteins were determined using intermodular connectivity, and significant functional pathways were identified. Weighted correlation network analysis revealed six protein modules. The eigenprotein of a protein module with 68 proteins, including complement components as hub proteins, was associated with the total Childhood Trauma Questionnaire score (r = -0.15, p = 0.009). Another eigenprotein of a protein module of 100 proteins, including apolipoproteins as hub proteins, was associated with the overeating item of the Symptom Checklist-90-Revised (r = 0.16, p = 0.006). Functional analysis revealed immune responses and lipid metabolism as significant pathways for each module, respectively. No significant protein module was associated with the differentiation between MDD and BD. In conclusion, childhood trauma and overeating symptoms were significantly associated with plasma protein networks and should be considered important endophenotypes in affective disorders.
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Affiliation(s)
- Sang Jin Rhee
- Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea
| | - Dongyoon Shin
- Department of Biomedical Science, School of Medicine, CHA University, Seongnam, Republic of Korea
| | - Daun Shin
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Yoojin Song
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Eun-Jeong Joo
- Department of Neuropsychiatry, School of Medicine, Eulji University, Daejeon, Republic of Korea
- Department of Psychiatry, Uijeongbu Eulji Medical Center, Eulji University, Uijeongbu, Republic of Korea
| | - Hee Yeon Jung
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea
- Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea
| | - Sungwon Roh
- Department of Psychiatry, Hanyang University Hospital and Hanyang University College of Medicine, Seoul, Republic of Korea
| | - Sang-Hyuk Lee
- Department of Psychiatry, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Republic of Korea
| | - Hyeyoung Kim
- Department of Psychiatry, Inha University Hospital, Incheon, Republic of Korea
| | - Minji Bang
- Department of Psychiatry, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Republic of Korea
| | - Kyu Young Lee
- Department of Neuropsychiatry, School of Medicine, Eulji University, Daejeon, Republic of Korea
- Department of Psychiatry, Nowon Eulji University Hospital, Seoul, Republic of Korea
| | - Jihyeon Lee
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jaenyeon Kim
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Yeongshin Kim
- Department of Biomedical Science, School of Medicine, CHA University, Seongnam, Republic of Korea
| | - Youngsoo Kim
- Department of Biomedical Science, School of Medicine, CHA University, Seongnam, Republic of Korea.
| | - Yong Min Ahn
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea.
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.
- Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea.
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Shin D, Rhee SJ, Lee J, Yeo I, Do M, Joo EJ, Jung HY, Roh S, Lee SH, Kim H, Bang M, Lee KY, Kwon JS, Ha K, Ahn YM, Kim Y. Quantitative Proteomic Approach for Discriminating Major Depressive Disorder and Bipolar Disorder by Multiple Reaction Monitoring-Mass Spectrometry. J Proteome Res 2021; 20:3188-3203. [PMID: 33960196 DOI: 10.1021/acs.jproteome.1c00058] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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.
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Affiliation(s)
| | - Sang Jin Rhee
- Department of Psychiatry, Seoul National University College of Medicine, Seoul 03080, Republic of Korea.,Department of Neuropsychiatry, Seoul National University Hospital, Seoul 03080, Republic of Korea
| | | | | | | | - Eun-Jeong Joo
- Department of Neuropsychiatry, School of Medicine, Eulji University, Daejeon 34824, Republic of Korea.,Department of Psychiatry, Nowon Eulji Medical Center, Eulji University, Seoul 01830, Republic of Korea
| | - Hee Yeon Jung
- Department of Psychiatry, Seoul National University College of Medicine, Seoul 03080, Republic of Korea.,Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul 07061, Republic of Korea.,Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, 101 Daehakro, Seoul 30380, Republic of Korea
| | - Sungwon Roh
- Department of Psychiatry, Hanyang University Hospital, Seoul 04763, Republic of Korea.,Department of Psychiatry, Hanyang University College of Medicine, Seoul 04763, Republic of Korea
| | - Sang-Hyuk Lee
- Department of Psychiatry, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam 13496, Republic of Korea
| | - Hyeyoung Kim
- Department of Psychiatry, Inha University Hospital, Incheon 22332, Republic of Korea
| | - Minji Bang
- Department of Psychiatry, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam 13496, Republic of Korea
| | - Kyu Young Lee
- Department of Neuropsychiatry, School of Medicine, Eulji University, Daejeon 34824, Republic of Korea.,Department of Psychiatry, Nowon Eulji Medical Center, Eulji University, Seoul 01830, Republic of Korea
| | - Jun Soo Kwon
- Department of Psychiatry, Seoul National University College of Medicine, Seoul 03080, Republic of Korea.,Department of Neuropsychiatry, Seoul National University Hospital, Seoul 03080, Republic of Korea.,Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, 101 Daehakro, Seoul 30380, Republic of Korea
| | - Kyooseob Ha
- Department of Psychiatry, Seoul National University College of Medicine, Seoul 03080, Republic of Korea.,Department of Neuropsychiatry, Seoul National University Hospital, Seoul 03080, Republic of Korea.,Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, 101 Daehakro, Seoul 30380, Republic of Korea
| | - Yong Min Ahn
- Department of Psychiatry, Seoul National University College of Medicine, Seoul 03080, Republic of Korea.,Department of Neuropsychiatry, Seoul National University Hospital, Seoul 03080, Republic of Korea.,Institute of Human Behavioral Medicine, Seoul National University Medical Research Center, 101 Daehakro, Seoul 30380, Republic of Korea
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Prodan Žitnik I, Černe D, Mancini I, Simi L, Pazzagli M, Di Resta C, Podgornik H, Repič Lampret B, Trebušak Podkrajšek K, Sipeky C, van Schaik R, Brandslund I, Vermeersch P, Schwab M, Marc J. Personalized laboratory medicine: a patient-centered future approach. Clin Chem Lab Med 2019; 56:1981-1991. [PMID: 29990304 DOI: 10.1515/cclm-2018-0181] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2018] [Accepted: 05/11/2018] [Indexed: 12/12/2022]
Abstract
In contrast to population-based medical decision making, which emphasizes the use of evidence-based treatment strategies for groups of patients, personalized medicine is based on optimizing treatment at the level of the individual patient. The creation of molecular profiles of individual patients was made possible by the advent of "omics" technologies, based on high throughput instrumental techniques in combination with biostatistics tools and artificial intelligence. The goal of personalized laboratory medicine is to use advanced technologies in the process of preventive, curative or palliative patient management. Personalized medicine does not rely on changes in concentration of a single molecular marker to make a therapeutic decision, but rather on changes of a profile of markers characterizing an individual patient's status, taking into account not only the expected response to treatment of the disease but also the expected response of the patient. Such medical approach promises a more effective diagnostics with more effective and safer treatment, as well as faster recovery and restoration of health and improved cost effectiveness. The laboratory medicine profession is aware of its key role in personalized medicine, but to empower the laboratories, at least an enhancement in cooperation between disciplines within laboratory medicine will be necessary.
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Affiliation(s)
| | - Darko Černe
- Faculty of Pharmacy, University of Ljubljana, Ljubljana, Slovenia
| | - Irene Mancini
- Department of Biomedical, Experimental and Clinical Sciences, University of Florence, Florence, Italy
| | - Lisa Simi
- Department of Biomedical, Experimental and Clinical Sciences, University of Florence, Florence, Italy
| | - Mario Pazzagli
- Department of Biomedical, Experimental and Clinical Sciences, University of Florence, Florence, Italy
| | - Chiara Di Resta
- Vita-Salute San Raffaele University and Division of Genetics and Cell Biology, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Helena Podgornik
- Department of Hematology, University Medical Centre Ljubljana, Ljubljana, Slovenia
| | - Barbka Repič Lampret
- Unit for Special Laboratory Diagnostics, University Children's Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
| | - Katarina Trebušak Podkrajšek
- Unit for Special Laboratory Diagnostics, University Children's Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia.,Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Csilla Sipeky
- Institute of Biomedicine, University of Turku, Turku, Finland
| | - Ron van Schaik
- Department of Clinical Chemistry, Erasmus Medical Center, Rotterdam, TheNetherlands
| | - Ivan Brandslund
- Biochemistry Department, University of Southern Denmark and Vejle Hospital, Vejle, Denmark
| | | | - Matthias Schwab
- Department of Clinical Pharmacology, University Hospital Tuebingen, Tuebingen, Germany.,Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany.,Department of Pharmacy and Biochemistry, University of Tuebingen, Tuebingen, Germany
| | - Janja Marc
- Faculty of Pharmacy, University of Ljubljana, Ljubljana, Slovenia
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