Blood Transcriptomic Markers in Patients with Late-Onset Major Depressive Disorder.
Blood Transcriptomic Markers in Patients with Late-Onset Major Depressive Disorder.
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DOI：
10.1371/journal.pone.0150262
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发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
Mikuni M
中科院分区：
文献类型：
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作者：
Miyata S;Kurachi M;Okano Y;Sakurai N;Kobayashi A;Harada K;Yamagata H;Matsuo K;Takahashi K;Narita K;Fukuda M;Ishizaki Y;Mikuni M
我们从血细胞中表达的基因中研究了晚发性重性抑郁障碍（LOD;首次抑郁发作的发病年龄≥ 50岁）的转录组标志物，并确定了这些患者的状态依赖性转录组标志物。我们通过微阵列评估了血细胞中表达的基因，发现3，066个探针的表达水平在LOD患者的血细胞中呈状态依赖性变化。为了从这些探针中选择潜在的候选者，我们通过微阵列评估了抑郁症动物模型（暴露于慢性超轻度应激的卵巢切除雌性小鼠）血液中表达的基因，并将患者和模型小鼠之间的差异表达基因进行交叉匹配。我们确定了14个差异表达的基因，这些基因在患者和模型小鼠中的变化相似。通过使用实时定量PCR（RT-qPCR）评估统计学显著性，选择以下4个基因作为候选基因：细胞死亡诱导DFFA样效应子c（CIDEC）、核糖核酸酶1（RNASE 1）、溶质载体家族36成员-1（SLC 36 A1）和丝氨酸/苏氨酸/酪氨酸相互作用样1（STYXL 1）。这4个候选基因的区分能力在一个独立的队列中进行了评估，并进行了验证。其中，CIDEC的判别效度最高（敏感性91.3%，特异性87.5%）。因此，这4种生物标志物应有助于正确诊断LOD。
We investigated transcriptomic markers of late-onset major depressive disorder (LOD; onset age of first depressive episode ≥ 50 years) from the genes expressed in blood cells and identified state-dependent transcriptomic markers in these patients. We assessed the genes expressed in blood cells by microarray and found that the expression levels of 3,066 probes were state-dependently changed in the blood cells of patients with LOD. To select potential candidates from those probes, we assessed the genes expressed in the blood of an animal model of depression, ovariectomized female mice exposed to chronic ultra-mild stress, by microarray and cross-matched the differentially expressed genes between the patients and the model mice. We identified 14 differentially expressed genes that were similarly changed in both patients and the model mice. By assessing statistical significance using real-time quantitative PCR (RT-qPCR), the following 4 genes were selected as candidates: cell death-inducing DFFA-like effector c (CIDEC), ribonuclease 1 (RNASE1), solute carrier family 36 member-1 (SLC36A1), and serine/threonine/tyrosine interacting-like 1 (STYXL1). The discriminating ability of these 4 candidate genes was evaluated in an independent cohort that was validated. Among them, CIDEC showed the greatest discriminant validity (sensitivity 91.3% and specificity 87.5%). Thus, these 4 biomarkers should be helpful for properly diagnosing LOD.