Immunoglobulin genes expressed in lymphoblastoid cell lines discern and predict lithium response in bipolar disorder patients.
Immunoglobulin genes expressed in lymphoblastoid cell lines discern and predict lithium response in bipolar disorder patients.
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DOI：
10.1038/s41380-023-02183-z
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发表时间：
2023-10
影响因子：
11
通讯作者：
Stern, Shani
中科院分区：
文献类型：
--
作者：
Mizrahi, Liron;Choudhary, Ashwani;Ofer, Polina;Goldberg, Gabriela;Milanesi, Elena;Kelsoe, John R.;Gurwitz, David;Alda, Martin;Gage, Fred H.;Stern, Shani
双相情感障碍（BD）是一种神经精神性心境障碍，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，使BD临床管理复杂化。鉴于其病因不明，了解导致锂反应变异的遗传特征是有意义的。我们从10名对照和19名BD患者的淋巴母细胞系（LCL）中发现了一组差异表达基因（DEG），这些基因主要属于免疫球蛋白基因家族，可用作诊断和治疗BD的潜在生物标志物。重要的是，我们在我们的数据集上训练机器学习算法，预测BD亚型的锂反应，误差最小，即使在不同实验室获得的24例BD患者的不同队列中使用时也是如此。这证明了我们预测BD锂反应的方法的可扩展性，以及对治疗干预的及时和适当决策。
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.
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