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Network analysis of plasma proteomes in affective disorders
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 29...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10256808/ https://www.ncbi.nlm.nih.gov/pubmed/37296094 http://dx.doi.org/10.1038/s41398-023-02485-4 |
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author | Rhee, Sang Jin Shin, Dongyoon Shin, Daun Song, Yoojin Joo, Eun-Jeong Jung, Hee Yeon Roh, Sungwon Lee, Sang-Hyuk Kim, Hyeyoung Bang, Minji Lee, Kyu Young Lee, Jihyeon Kim, Jaenyeon Kim, Yeongshin Kim, Youngsoo Ahn, Yong Min |
author_facet | Rhee, Sang Jin Shin, Dongyoon Shin, Daun Song, Yoojin Joo, Eun-Jeong Jung, Hee Yeon Roh, Sungwon Lee, Sang-Hyuk Kim, Hyeyoung Bang, Minji Lee, Kyu Young Lee, Jihyeon Kim, Jaenyeon Kim, Yeongshin Kim, Youngsoo Ahn, Yong Min |
author_sort | Rhee, Sang Jin |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10256808 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-102568082023-06-11 Network analysis of plasma proteomes in affective disorders Rhee, Sang Jin Shin, Dongyoon Shin, Daun Song, Yoojin Joo, Eun-Jeong Jung, Hee Yeon Roh, Sungwon Lee, Sang-Hyuk Kim, Hyeyoung Bang, Minji Lee, Kyu Young Lee, Jihyeon Kim, Jaenyeon Kim, Yeongshin Kim, Youngsoo Ahn, Yong Min Transl Psychiatry Article 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. Nature Publishing Group UK 2023-06-09 /pmc/articles/PMC10256808/ /pubmed/37296094 http://dx.doi.org/10.1038/s41398-023-02485-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Rhee, Sang Jin Shin, Dongyoon Shin, Daun Song, Yoojin Joo, Eun-Jeong Jung, Hee Yeon Roh, Sungwon Lee, Sang-Hyuk Kim, Hyeyoung Bang, Minji Lee, Kyu Young Lee, Jihyeon Kim, Jaenyeon Kim, Yeongshin Kim, Youngsoo Ahn, Yong Min Network analysis of plasma proteomes in affective disorders |
title | Network analysis of plasma proteomes in affective disorders |
title_full | Network analysis of plasma proteomes in affective disorders |
title_fullStr | Network analysis of plasma proteomes in affective disorders |
title_full_unstemmed | Network analysis of plasma proteomes in affective disorders |
title_short | Network analysis of plasma proteomes in affective disorders |
title_sort | network analysis of plasma proteomes in affective disorders |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10256808/ https://www.ncbi.nlm.nih.gov/pubmed/37296094 http://dx.doi.org/10.1038/s41398-023-02485-4 |
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