Background

Lithium remains the first-line treatment for bipolar disorder (BD), but patients respond to it variably. While a myriad of studies have attributed many genes and signaling pathways to lithium responsiveness, a comprehensive study with an integrated conclusion is still lacking.

Objective

We aim to present an integrated mechanism for the therapeutic actions of lithium in BD.

Methods

First, a list of lithium responsiveness-associated genes (LRAGs) was collected by searching in the literature. Thereafter, gene set enrichment analysis together with gene–gene interaction network analysis was performed, in order to find the cellular and molecular events related to the LRAGs.

Results

Gene set enrichment analyses showed that the chromosomal regions 3p26, 4p21, 5q34 and 7p13 could be novel associated loci for lithium responsiveness in BD. Also, expression pattern analysis of the LRAGs showed their enrichment in adulthood stages and different cell lineages of brain, blood and immune system. Most of the LRAGs exhibited enriched expression in central parts of human brain, suggesting major contribution of these parts in lithium responsiveness. Beside the prediction of several biological processes and signaling pathways related to lithium responsiveness, an interaction network between these processes was constructed that was found to be regulated by a set of microRNAs. Proteins of the network were mainly classified as transcription factors and kinases, which also highlighted the crucial role of glycogen synthase kinase 3β (GSK3β) in lithium responsiveness.

Conclusions

The predicted cellular and molecular events in this study could be considered as mechanisms and also determinants of lithium responsiveness in BD.

中文翻译：

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锂在治疗双相情感障碍中的预测细胞和分子作用：一项计算机研究。

背景

锂仍然是双相情感障碍 (BD) 的一线治疗方法，但患者对它的反应各不相同。尽管大量研究已将许多基因和信号通路归因于锂反应性，但仍缺乏具有综合结论的综合研究。

客观的

我们的目标是提出锂在 BD 中的治疗作用的综合机制。

方法

首先，通过在文献中搜索收集了锂反应相关基因 (LRAG) 的列表。此后，进行基因集富集分析和基因-基因相互作用网络分析，以发现与 LRAGs 相关的细胞和分子事件。

结果

基因集富集分析表明，染色体区域3p26 , 4p21 , 5q34和7p13可能是 BD 中锂反应性的新相关位点。此外，LRAGs 的表达模式分析显示它们在成年阶段和大脑、血液和免疫系统的不同细胞谱系中富集。大多数 LRAG 在人脑的中央部分表现出丰富的表达，表明这些部分对锂反应性的主要贡献。除了预测与锂反应性相关的几种生物过程和信号通路外，还构建了这些过程之间的相互作用网络，发现该网络受一组 microRNA 的调控。该网络的蛋白质主要分为转录因子和激酶，这也突出了糖原合酶激酶 3β ( GSK3β ) 在锂反应中的关键作用。

结论

本研究中预测的细胞和分子事件可被视为 BD 中锂反应性的机制和决定因素。