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Cerebrospinal fluid proteome evaluation in major depressive disorder by mass spectrometry
BACKGROUND: Depression affects approximately 7.1% of the United States population every year and has an annual economic burden of over $210 billion dollars. Several recent studies have sought to investigate the pathophysiology of depression utilizing focused cerebrospinal fluid (CSF) and serum analy...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7528485/ https://www.ncbi.nlm.nih.gov/pubmed/32998701 http://dx.doi.org/10.1186/s12888-020-02874-9 |
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author | Franzen, Avery D. Lam, Tukiet T. Williams, Kenneth R. Nairn, Angus C. Duman, Ronald S. Sathyanesan, Monica Kumar, Vikas Carpenter, Linda L. Newton, Samuel S. |
author_facet | Franzen, Avery D. Lam, Tukiet T. Williams, Kenneth R. Nairn, Angus C. Duman, Ronald S. Sathyanesan, Monica Kumar, Vikas Carpenter, Linda L. Newton, Samuel S. |
author_sort | Franzen, Avery D. |
collection | PubMed |
description | BACKGROUND: Depression affects approximately 7.1% of the United States population every year and has an annual economic burden of over $210 billion dollars. Several recent studies have sought to investigate the pathophysiology of depression utilizing focused cerebrospinal fluid (CSF) and serum analysis. Inflammation and metabolic dysfunction have emerged as potential etiological factors from these studies. A dysregulation in the levels of inflammatory proteins such as IL-12, TNF, IL-6 and IFN-γ have been found to be significantly correlated with depression. METHODS: CSF samples were obtained from 15 patients, seven with major depressive disorder and eight age- and gender-matched non-psychiatric controls. CSF protein profiles were obtained using quantitative mass spectrometry. The data were analyzed by Progenesis QI proteomics software to identify significantly dysregulated proteins. The results were subjected to bioinformatics analysis using the Ingenuity Pathway Analysis suite to obtain unbiased mechanistic insight into biologically relevant interactions and pathways. RESULTS: Several dysregulated proteins were identified. Bioinformatics analysis indicated that the potential disorder/disease pathways include inflammatory response, metabolic disease and organismal injury. Molecular and cellular functions that were affected include cellular compromise, cell-to-cell signaling & interaction, cellular movement, protein synthesis, and cellular development. The major canonical pathway that was upregulated was acute phase response signaling. Endogenous upstream regulators that may influence dysregulation of proinflammatory molecules associated with depression are interleukin-6 (IL-6), signal transducer and activator of transcription 3 (STAT3), oncostatin M, PR domain zinc finger protein 1 (PRDM1), and peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PPARGC1A). CONCLUSIONS: The proteome profiling data in this report identifies several potential biological functions that may be involved in the pathophysiology of major depressive disorder. Future research into how the differential expression of these proteins is involved in the etiology and severity of depression will be important. |
format | Online Article Text |
id | pubmed-7528485 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-75284852020-10-02 Cerebrospinal fluid proteome evaluation in major depressive disorder by mass spectrometry Franzen, Avery D. Lam, Tukiet T. Williams, Kenneth R. Nairn, Angus C. Duman, Ronald S. Sathyanesan, Monica Kumar, Vikas Carpenter, Linda L. Newton, Samuel S. BMC Psychiatry Research Article BACKGROUND: Depression affects approximately 7.1% of the United States population every year and has an annual economic burden of over $210 billion dollars. Several recent studies have sought to investigate the pathophysiology of depression utilizing focused cerebrospinal fluid (CSF) and serum analysis. Inflammation and metabolic dysfunction have emerged as potential etiological factors from these studies. A dysregulation in the levels of inflammatory proteins such as IL-12, TNF, IL-6 and IFN-γ have been found to be significantly correlated with depression. METHODS: CSF samples were obtained from 15 patients, seven with major depressive disorder and eight age- and gender-matched non-psychiatric controls. CSF protein profiles were obtained using quantitative mass spectrometry. The data were analyzed by Progenesis QI proteomics software to identify significantly dysregulated proteins. The results were subjected to bioinformatics analysis using the Ingenuity Pathway Analysis suite to obtain unbiased mechanistic insight into biologically relevant interactions and pathways. RESULTS: Several dysregulated proteins were identified. Bioinformatics analysis indicated that the potential disorder/disease pathways include inflammatory response, metabolic disease and organismal injury. Molecular and cellular functions that were affected include cellular compromise, cell-to-cell signaling & interaction, cellular movement, protein synthesis, and cellular development. The major canonical pathway that was upregulated was acute phase response signaling. Endogenous upstream regulators that may influence dysregulation of proinflammatory molecules associated with depression are interleukin-6 (IL-6), signal transducer and activator of transcription 3 (STAT3), oncostatin M, PR domain zinc finger protein 1 (PRDM1), and peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PPARGC1A). CONCLUSIONS: The proteome profiling data in this report identifies several potential biological functions that may be involved in the pathophysiology of major depressive disorder. Future research into how the differential expression of these proteins is involved in the etiology and severity of depression will be important. BioMed Central 2020-10-01 /pmc/articles/PMC7528485/ /pubmed/32998701 http://dx.doi.org/10.1186/s12888-020-02874-9 Text en © The Author(s) 2020 Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Franzen, Avery D. Lam, Tukiet T. Williams, Kenneth R. Nairn, Angus C. Duman, Ronald S. Sathyanesan, Monica Kumar, Vikas Carpenter, Linda L. Newton, Samuel S. Cerebrospinal fluid proteome evaluation in major depressive disorder by mass spectrometry |
title | Cerebrospinal fluid proteome evaluation in major depressive disorder by mass spectrometry |
title_full | Cerebrospinal fluid proteome evaluation in major depressive disorder by mass spectrometry |
title_fullStr | Cerebrospinal fluid proteome evaluation in major depressive disorder by mass spectrometry |
title_full_unstemmed | Cerebrospinal fluid proteome evaluation in major depressive disorder by mass spectrometry |
title_short | Cerebrospinal fluid proteome evaluation in major depressive disorder by mass spectrometry |
title_sort | cerebrospinal fluid proteome evaluation in major depressive disorder by mass spectrometry |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7528485/ https://www.ncbi.nlm.nih.gov/pubmed/32998701 http://dx.doi.org/10.1186/s12888-020-02874-9 |
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