Genome-wide expression profiling of human lymphoblastoid cell lines identifies CHL1 as a putative SSRI antidepressant response biomarker
Genome-wide expression profiling of human lymphoblastoid cell lines identifies CHL1 as a putative SSRI antidepressant response biomarker
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DOI：
10.2217/pgs.10.185
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发表时间：
2011-02-01
期刊：
影响因子：
2.1
通讯作者：
Gurwitz, David
中科院分区：
文献类型：
--
作者：
Morag, Ayelet;Pasmanik-Chor, Metsada;Gurwitz, David
目的：选择性5-羟色胺再摄取抑制剂（SSRIs）是治疗抑郁症最常用的一类抗抑郁药。然而，大约30%的患者对一线抗抑郁药物治疗反应不充分，需要替代治疗。迄今为止，寻找SSRI反应DNA生物标志物的全基因组研究或候选人降钙素相关基因的研究都给出了不确定或矛盾的结果。在这里，我们提出了一种替代的基于转录组的全基因组方法，通过使用人类淋巴母细胞系（LCL）中的药物效应表型来搜索抗抑郁药药物反应生物标志物。材料与方法：我们筛选了80例来自健康成年女性个体的LCL，用于帕罗西汀生长抑制。选择对帕罗西汀具有可再现的高和低敏感性的总共14个LCL（每个表型组7个），用商业微阵列进行全基因组表达谱分析。结果如下：显示高与低帕罗西汀敏感性的LCL之间最显着的全基因组转录组差异是CHL 1的基础表达低6.3倍（p = 0.0000256），CHL 1是一种编码神经元细胞粘附蛋白的基因，与正确的丘脑皮质回路、精神分裂症和自闭症有关。实时PCR证实了微阵列结果（帕罗西汀高敏感性组中CHL 1表达水平低36倍）。与突触发生或精神障碍有关的几个其他基因，包括ARRB 1、CCL 5、DDX 60、DDX 60 L、ENDOD 1、ENPP 2、FLT 1、GABRA 4、GAP 43、MCTP 2和SPRY 2，在两个帕罗西汀敏感性组之间也相差超过1.5倍，p值小于0.005，如通过实时PCR实验所证实的。结论：体外表型LCL的全基因组转录谱鉴定了CHL 1和参与突触发生和脑回路的其他基因，作为推定的SSRI反应生物标志物。该方法可用作寻找潜在抑郁症治疗生物标志物的初步工具。
Aims: Selective serotonin reuptake inhibitors (SSRIs) are the most commonly used class of antidepressants for treating major depression. However, approximately 30% of patients do not respond sufficiently to first-line antidepressant drug treatment and require alternative therapeutics. Genome-wide studies searching for SSRI response DNA biomarkers or studies of candidate serotonin-related genes so far have given inconclusive or contradictory results. Here, we present an alternative transcriptome-based genome-wide approach for searching antidepressant drug-response biomarkers by using drug-effect phenotypes in human lymphoblastoid cell lines (LCLs). Materials & methods: We screened 80 LCLs from healthy adult female individuals for growth inhibition by paroxetine. A total of 14 LCLs with reproducible high and low sensitivities to paroxetine (seven from each phenotypic group) were chosen for genome-wide expression profiling with commercial microarrays. Results: The most notable genome-wide transcriptome difference between LCLs displaying high versus low paroxetine sensitivities was a 6.3-fold lower (p = 0.0000256) basal expression of CHL1, a gene coding for a neuronal cell adhesion protein implicated in correct thalamocortical circuitry, schizophrenia and autism. The microarray findings were confirmed by real-time PCR (36-fold lower CHL1 expression levels in the high paroxetine sensitivity group). Several additional genes implicated in synaptogenesis or in psychiatric disorders, including ARRB1, CCL5, DDX60, DDX60L, ENDOD1, ENPP2, FLT1, GABRA4, GAP43, MCTP2 and SPRY2, also differed by more than 1.5-fold and a p-value of less than 0.005 between the two paroxetine sensitivity groups, as confirmed by real-time PCR experiments. Conclusion: Genome-wide transcriptional profiling of in vitro phenotyped LCLs identified CHL1 and additional genes implicated in synaptogenesis and brain circuitry as putative SSRI response biomarkers. This method might be used as a preliminary tool for searching for potential depression treatment biomarkers.