利用多重反应监测-质谱法评估基于非贫化血浆多蛋白的精神疾病鉴别模型:概念验证研究

IF 3.6 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Dongyoon Shin, Jihyeon Lee, Yeongshin Kim, Junho Park, Daun Shin, Yoojin Song, Eun-Jeong Joo, Sungwon Roh, Kyu Young Lee, Sanghoon Oh, Yong Min Ahn, Sang Jin Rhee* and Youngsoo Kim*, 
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引用次数: 0

摘要

精神病评估依赖于主观症状和行为观察,有时会导致误诊。尽管以前曾尝试利用血浆蛋白作为客观标记物,但耗损法耗时较长。因此,本研究旨在改进以往的定量方法,并利用未耗尽的血浆构建主要精神疾病的客观判别模型。研究人员开发了多反应监测-质谱(MRM-MS)检测方法,用于定量检测来自 132 名患者(35 名重度抑郁障碍(MDD)患者、47 名双相情感障碍(BD)患者、23 名精神分裂症(SCZ)患者和 27 名健康对照(HC)患者)的未耗竭血浆中的 453 种肽段。通过机器学习方法构建了针对 MDD、BD 和 SCZ 的配对判别模型,以及患者和 HC 之间的判别模型。此外,还将基于非耗竭血浆的判别模型中的蛋白质与之前开发的基于耗竭血浆的判别模型进行了比较。用11至13个蛋白质构建了MDD与BD、BD与SCZ、MDD与SCZ以及患者与HC的判别模型,并显示出合理的性能(AUROC = 0.890-0.955)。未耗竭血浆模型和耗竭血浆模型中的大多数共有蛋白具有一致的表达水平方向,并且与神经信号、炎症和脂质代谢途径相关。这些结果表明,非耗竭血浆中的多蛋白标记物在精神病学评估中具有潜在的作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Evaluation of a Nondepleted Plasma Multiprotein-Based Model for Discriminating Psychiatric Disorders Using Multiple Reaction Monitoring-Mass Spectrometry: Proof-of-Concept Study

Evaluation of a Nondepleted Plasma Multiprotein-Based Model for Discriminating Psychiatric Disorders Using Multiple Reaction Monitoring-Mass Spectrometry: Proof-of-Concept Study

Evaluation of a Nondepleted Plasma Multiprotein-Based Model for Discriminating Psychiatric Disorders Using Multiple Reaction Monitoring-Mass Spectrometry: Proof-of-Concept Study

Psychiatric evaluation relies on subjective symptoms and behavioral observation, which sometimes leads to misdiagnosis. Despite previous efforts to utilize plasma proteins as objective markers, the depletion method is time-consuming. Therefore, this study aimed to enhance previous quantification methods and construct objective discriminative models for major psychiatric disorders using nondepleted plasma. Multiple reaction monitoring-mass spectrometry (MRM-MS) assays for quantifying 453 peptides in nondepleted plasma from 132 individuals [35 major depressive disorder (MDD), 47 bipolar disorder (BD), 23 schizophrenia (SCZ) patients, and 27 healthy controls (HC)] were developed. Pairwise discriminative models for MDD, BD, and SCZ, and a discriminative model between patients and HC were constructed by machine learning approaches. In addition, the proteins from nondepleted plasma-based discriminative models were compared with previously developed depleted plasma-based discriminative models. Discriminative models for MDD versus BD, BD versus SCZ, MDD versus SCZ, and patients versus HC were constructed with 11 to 13 proteins and showed reasonable performances (AUROC = 0.890–0.955). Most of the shared proteins between nondepleted and depleted plasma models had consistent directions of expression levels and were associated with neural signaling, inflammatory, and lipid metabolism pathways. These results suggest that multiprotein markers from nondepleted plasma have a potential role in psychiatric evaluation.

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来源期刊
Journal of Proteome Research
Journal of Proteome Research 生物-生化研究方法
CiteScore
9.00
自引率
4.50%
发文量
251
审稿时长
3 months
期刊介绍: Journal of Proteome Research publishes content encompassing all aspects of global protein analysis and function, including the dynamic aspects of genomics, spatio-temporal proteomics, metabonomics and metabolomics, clinical and agricultural proteomics, as well as advances in methodology including bioinformatics. The theme and emphasis is on a multidisciplinary approach to the life sciences through the synergy between the different types of "omics".
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