Dataset Information

Plasma proteomic data in bipolar II disorders and major depressive disorders.

ABSTRACT: The proteomics data included in this article supplement the research article titled "Predictive protein markers for the severity of depression in mood disorders: A preliminary trans-diagnostic approach study (manuscript ID: JPSYCHIATRES-D-20-00437)." Plasma protein was analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). This data article included 370 plasma protein profiles expressed in patients with bipolar II disorder (BD-II) and major depressive disorder (MDD). The tables present the comparison of protein expressions between BD-II and MDD, and the relationship between the severity of the depressive symptoms and protein expression. In addition, details of results adjusting the use of each psychotropic medication (antipsychotics, mood stabilizers, and antidepressants) for 20 proteins that showed a significant relationship with the severity of the depressive symptom were presented in the table. Results of the bioinformatics analysis of proteins, which were significantly related to the severity of depressive symptom, are presented. The blood protein profiles and the results of the analyses presented in this data article provide detailed information on the proteins associated with mood disorders, and could be used as the basis for further mass spectrometry studies in psychiatric disorders.

SUBMITTER: Lee H

PROVIDER: S-EPMC8605259 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Plasma proteomic data in bipolar II disorders and major depressive disorders.

Lee Hyunju H Rhee Sang Jin SJ Kim Jayoun J Lee Yunna Y Kim Hyeyoung H Lee Junhee J Lee Kangeun K Shin Hyunsuk H Kim Hyeyoon H Lee Tae Young TY Kim Minah M Kim Eun Young EY Kim Se Hyun SH Ahn Yong Min YM Kwon Jun Soo JS Han Dohyun D Ha Kyooseob K

Data in brief 20211017

The proteomics data included in this article supplement the research article titled "Predictive protein markers for the severity of depression in mood disorders: A preliminary trans-diagnostic approach study (manuscript ID: JPSYCHIATRES-D-20-00437)." Plasma protein was analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). This data article included 370 plasma protein profiles expressed in patients with bipolar II disorder (BD-II) and major depressive disorder (MDD). The table ...[more]

PMID: 34825021

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Project description:Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are classified as major mental disorders and together account for the second-highest global disease burden, and half of these patients experience symptom onset in adolescence. Several studies have reported both similar and unique features regarding the risk factors and clinical symptoms of these three disorders. However, it is still unclear whether these disorders have similar or unique metabolic characteristics in adolescents. We conducted a metabolomics analysis of plasma samples from adolescent healthy controls (HCs) and patients with MDD, BD, and SCZ. We identified differentially expressed metabolites between patients and HCs. Based on the differentially expressed metabolites, correlation analysis, metabolic pathway analysis, and potential diagnostic biomarker identification were conducted for disorders and HCs. Our results showed significant changes in plasma metabolism between patients with these mental disorders and HCs; the most distinct changes were observed in SCZ patients. Moreover, the metabolic differences in BD patients shared features with those in both MDD and SCZ, although the BD metabolic profile was closer to that of MDD than to SCZ. Additionally, we identified the metabolites responsible for the similar and unique metabolic characteristics in multiple metabolic pathways. The similar significant differences among the three disorders were found in fatty acid, steroid-hormone, purine, nicotinate, glutamate, tryptophan, arginine, and proline metabolism. Interestingly, we found unique characteristics of significantly altered glycolysis, glycerophospholipid, and sphingolipid metabolism in SCZ; lysine, cysteine, and methionine metabolism in MDD and BD; and phenylalanine, tyrosine, and aspartate metabolism in SCZ and BD. Finally, we identified five panels of potential diagnostic biomarkers for MDD-HC, BD-HC, SCZ-HC, MDD-SCZ, and BD-SCZ comparisons. Our findings suggest that metabolic characteristics in plasma vary across psychiatric disorders and that critical metabolites provide new clues regarding molecular mechanisms in these three psychiatric disorders.

Dataset Information

Plasma proteomic data in bipolar II disorders and major depressive disorders.

Publications

Plasma proteomic data in bipolar II disorders and major depressive disorders.

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