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在淋巴母细胞系中表达的免疫球蛋白基因可识别和预测双相情感障碍患者对锂的反应。

Immunoglobulin genes expressed in lymphoblastoid cell lines discern and predict lithium response in bipolar disorder patients.

机构信息

Sagol Department of Neurobiology, Faculty of Natural Sciences, University of Haifa, Haifa, 3498838, Israel.

Laboratory of Genetics, The Salk Institute for Biological Studies, La Jolla, CA, 92037, USA.

出版信息

Mol Psychiatry. 2023 Oct;28(10):4280-4293. doi: 10.1038/s41380-023-02183-z. Epub 2023 Jul 24.

Abstract

Bipolar disorder (BD) is a neuropsychiatric mood disorder manifested by recurrent episodes of mania and depression. More than half of BD patients are non-responsive to lithium, the first-line treatment drug, complicating BD clinical management. Given its unknown etiology, it is pertinent to understand the genetic signatures that lead to variability in lithium response. We discovered a set of differentially expressed genes (DEGs) from the lymphoblastoid cell lines (LCLs) of 10 controls and 19 BD patients belonging mainly to the immunoglobulin gene family that can be used as potential biomarkers to diagnose and treat BD. Importantly, we trained machine learning algorithms on our datasets that predicted the lithium response of BD subtypes with minimal errors, even when used on a different cohort of 24 BD patients acquired by a different laboratory. This proves the scalability of our methodology for predicting lithium response in BD and for a prompt and suitable decision on therapeutic interventions.

摘要

双相情感障碍 (BD) 是一种神经精神疾病,表现为反复发作的躁狂和抑郁。超过一半的 BD 患者对一线治疗药物锂无反应,这使 BD 的临床管理变得复杂。鉴于其病因不明,了解导致锂反应差异的遗传特征至关重要。我们从 10 名对照者和 19 名主要属于免疫球蛋白基因家族的 BD 患者的淋巴母细胞系 (LCL) 中发现了一组差异表达基因 (DEGs),可作为潜在的生物标志物用于诊断和治疗 BD。重要的是,我们在数据集上训练了机器学习算法,即使在使用另一个由不同实验室获得的 24 名 BD 患者的不同队列时,也可以最小的错误预测 BD 亚型的锂反应。这证明了我们预测 BD 锂反应的方法和及时、合适的治疗干预决策具有可扩展性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b501/10827667/55a39d633915/41380_2023_2183_Fig1_HTML.jpg

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