Mental Health Research Institute, Tomsk National Research Medical Center, Russian Academy of Sciences, Tomsk 634014, Russia.
Skolkovo Institute of Science and Technology, Moscow 121205, Russia.
Int J Mol Sci. 2023 Oct 17;24(20):15250. doi: 10.3390/ijms242015250.
The prevalence of bipolar disorder (BD) in modern society is growing rapidly, but due to the lack of paraclinical criteria, its differential diagnosis with other mental disorders is somewhat challenging. In this regard, the relevance of proteomic studies is increasing due to the development of methods for processing large data arrays; this contributes to the discovery of protein patterns of pathological processes and the creation of new methods of diagnosis and treatment. It seems promising to search for proteins involved in the pathogenesis of BD in an easily accessible material-blood serum. Sera from BD patients and healthy individuals were purified via affinity chromatography to isolate 14 major proteins and separated using 1D SDS-PAGE. After trypsinolysis, the proteins in the samples were identified via HPLC/mass spectrometry. Mass spectrometric data were processed using the OMSSA and X!Tandem search algorithms using the UniProtKB database, and the results were analyzed using PeptideShaker. Differences in proteomes were assessed via an unlabeled NSAF-based analysis using a two-tailed Bonferroni-adjusted -test. When comparing the blood serum proteomes of BD patients and healthy individuals, 10 proteins showed significant differences in NSAF values. Of these, four proteins were predominantly present in BD patients with the maximum NSAF value: 14-3-3 protein zeta/delta; ectonucleoside triphosphate diphosphohydrolase 7; transforming growth factor-beta-induced protein ig-h3; and B-cell CLL/lymphoma 9 protein. Further exploration of the role of these proteins in BD is warranted; conducting such studies will help develop new paraclinical criteria and discover new targets for BD drug therapy.
双相情感障碍 (BD) 在现代社会中的患病率正在迅速上升，但由于缺乏临床辅助标准，其与其他精神障碍的鉴别诊断存在一定的挑战性。在这方面，由于处理大数据数组方法的发展，蛋白质组学研究的相关性正在增加；这有助于发现病理过程的蛋白质模式，并创建新的诊断和治疗方法。在易于获取的物质——血清中寻找参与 BD 发病机制的蛋白质似乎很有前景。通过亲和层析从 BD 患者和健康个体的血清中纯化出 14 种主要蛋白质，并使用 1D SDS-PAGE 进行分离。在胰蛋白酶水解后，通过 HPLC/质谱法鉴定样品中的蛋白质。使用 OMSSA 和 X!Tandem 搜索算法处理质谱数据，并使用 UniProtKB 数据库，使用 PeptideShaker 对结果进行分析。通过使用非标记 NSAF 基于分析的双侧 Bonferroni 调整 -检验评估蛋白质组的差异。在比较 BD 患者和健康个体的血清蛋白质组时，10 种蛋白质的 NSAF 值存在显著差异。其中，四种蛋白质主要存在于 NSAF 值最大的 BD 患者中：14-3-3 蛋白 zeta/delta；核苷酸三磷酸二磷酸水解酶 7；转化生长因子-β诱导蛋白 ig-h3；和 B 细胞 CLL/淋巴瘤 9 蛋白。有必要进一步探索这些蛋白质在 BD 中的作用；进行此类研究将有助于开发新的临床辅助标准，并发现 BD 药物治疗的新靶点。
