血液环状RNA或可预测SSRI抗抑郁药反应

一个长期存在的临床难题

重度抑郁症的药物治疗常从试错开始。SSRI（选择性5-羟色胺再摄取抑制剂）是常用的一线药物，但报道指出，不到一半的患者在第一种抗抑郁药后症状缓解。患者往往要花数月换药，才能找到适合自己的方案。目前医生缺少能提前判断某种药是否有效的生物学检测——现有基因检测只能提示代谢速度，无法预测药物是否真能改善抑郁症状。

CDR1as：从大脑泄漏到血液的分子

研究聚焦一种叫CDR1as的环状RNA。环状RNA是闭合环状的遗传分子，没有暴露的末端，因此不易被体内降解酶分解，寿命比普通线性RNA长。这类分子在大脑中浓度很高，参与调节神经元的连接与通讯，其中一些能穿过血脑屏障进入血液，使研究者可以通过普通抽血检测到来自大脑的信号。

CDR1as在大脑中含量丰富，在其他人体组织中却很少见，这使它成为一个有吸引力的候选标志物。研究团队由Circular Genomics的Grigorios Papageorgiou、Eleni T. Tzavara、Nikolaos Mellios，以及德克萨斯大学西南医学中心的Madhukar H. Trivedi等人领导，分析了两个独立临床试验中即将开始服用舍曲林的患者基线血样。

预测的是药物，而非泛泛的好转

结果显示，治疗八周后对舍曲林无反应的患者，基线CDR1as水平明显更高；症状缓解者基线水平较低，未患病的对照者也较低。用药后，反应良好者的CDR1as水平上升，无反应者则没有这种上升。

为排除“只是预测一般性好转”的可能，研究者检查了其他治疗组：基线CDR1as水平既不能预测安慰剂组的改善，也不能预测换用安非他酮后的缓解。研究者还分析了服用氟西汀、西替利嗪、艾司西酞普兰等SSRI的患者血样，发现该标志物在这些药物中同样能识别反应良好者；而在其他类别抗抑郁药中则没有预测作用。这提示该分子与SSRI这一类药物的作用机制存在特定联系。

机制线索与明确的局限

为理解这一分子的产生过程，团队在小鼠身上做了实验：阻断5-HT2A型5-羟色胺受体后，小鼠三个脑区的Cdr1as水平下降；阻断多巴胺或谷氨酸受体则没有类似变化。在实验室培养的人与小鼠神经细胞中，抑制脑源性神经营养因子的受体也会减少该环状RNA的生成。这些实验为“5-羟色胺系统活动—CDR1as生成”之间提供了一条机制线索。

研究者也指出了检测的边界：在有躁狂家族史的抑郁患者中（常提示未被诊断的双相障碍），该检测表现较差；排除这些患者后，预测准确性有所提高。严重头部外伤或中风等可能破坏血脑屏障的事件，也可能人为改变血液中该分子的含量，未来需要验证。此外，高基线水平与快感缺失、社交退缩等症状相关，而这些症状常见于历史上较难用SSRI治疗的抑郁亚型，二者如何重叠仍待研究。

Major depressive disorder is often treated through trial and error, but a blood test may soon help doctors choose the right medication on the first try. Researchers have identified a circular RNA molecule in the blood that predicts whether a patient will respond to a common class of antidepressants. The findings were published in Molecular Psychiatry.

Millions of people globally experience major depressive disorder. Doctors frequently prescribe selective serotonin reuptake inhibitors, commonly known as SSRIs, as a first line of medical defense. These drugs block the reabsorption of serotonin in the brain, leaving more of the chemical available to help transmit messages between nerve cells.

Less than half of patients experience relief from their symptoms after trying their first prescribed antidepressant. This forces patients to spend months trying different medications before finding one that works. The prolonged wait imposes a heavy burden on individuals and adds substantial costs to the healthcare system.

Medical professionals currently lack biological tests to predict which drug will work for a specific person. Genetic tests exist to show how fast a person’s body might metabolize a drug. They cannot, however, forecast if the drug will actually relieve depression symptoms.

To find a better biological indicator, a team of researchers investigated circular RNAs. These are stable, loop-shaped genetic molecules that influence how other genes operate. Because they lack exposed ends, they resist degrading enzymes in the body, giving them a much longer lifespan than standard linear RNA molecules.

Circular RNAs are highly concentrated in the brain and help regulate how neurons connect and communicate. Some of these molecules can pass through the blood-brain barrier, the semi-permeable membrane that separates circulating blood from brain fluid. Because they leak into the bloodstream in a stable form, researchers can detect brain-derived circular RNAs using a standard blood draw.

The investigation was led by scientists Grigorios Papageorgiou, Eleni T. Tzavara, and Nikolaos Mellios of Circular Genomics and various research institutes in the United States and France, along with Madhukar H. Trivedi at the University of Texas Southwestern Medical Center. They focused on a specific circular RNA called CDR1as. This molecule is highly abundant in the brain but rarely found in other human tissues.

The researchers first analyzed baseline blood samples from patients enrolled in two independent clinical trials. They extracted RNA from the blood of patients diagnosed with major depressive disorder who were about to begin taking the SSRI sertraline. Using a technique that amplifies genetic material, the team measured the starting levels of CDR1as for each patient.

The team found that patients who did not respond to sertraline after eight weeks of treatment had notably higher baseline levels of CDR1as in their blood. Patients who experienced symptom relief had lower starting levels of the molecule. The researchers observed that unaffected control subjects also showed lower baseline levels of the molecule.

Taking advantage of the clinical trial design, the researchers also measured the patients’ blood at different intervals after they started taking sertraline. They discovered that patients who responded well to the drug experienced an increase in CDR1as levels after treatment began. Patients who did not respond to the medication saw no such increase in the molecule’s concentration.

To test if this molecule simply predicts general improvement rather than specific drug responses, the researchers looked at other treatment groups. They measured baseline blood levels in patients who were given a placebo pill. They also evaluated patients who failed to respond to sertraline and were subsequently switched to bupropion, a different type of antidepressant.

Baseline levels of CDR1as did not predict whether a patient would feel better on a placebo. The molecule also failed to predict if a patient would go on to experience remission while taking bupropion. This suggested the biomarker is specifically tied to the mechanisms of sertraline.

The research team then wanted to know if this predictive power applied to the entire SSRI drug class. They examined blood samples from patients in other clinical programs who were taking fluoxetine, citalopram, or escitalopram. They also analyzed samples from a small study of patients taking alternative medications like serotonin and norepinephrine reuptake inhibitors.

The researchers observed that CDR1as levels successfully identified patients who were faring well on various SSRIs, not just sertraline. When evaluating patients taking other classes of antidepressants, the molecule’s levels did not predict symptom relief. This pointed to a specific relationship between the circular RNA and SSRI medications as a whole.

To understand exactly how the brain produces this circular RNA, the team conducted experiments on mice. They administered different chemical compounds to the animals to block specific brain receptors. They then extracted brain tissue to measure changes in Cdr1as, the mouse equivalent of the human molecule.

When the researchers blocked the serotonin 5-HT2A receptor, levels of the circular RNA dropped across three different regions of the mouse brain. Blocking dopamine or glutamate receptors did not produce a similar drop in the molecule. This established a direct link between serotonin system activity and the production of the circular RNA.

The investigators conducted a final set of experiments on lab-grown human and mouse nerve cells. They treated the cells with chemicals that inhibit brain-derived neurotrophic factor, a protein that promotes the survival and growth of neurons. Inhibiting this protein’s receptors caused the cells to produce less of the circular RNA.

The researchers noted that certain medical conditions could interfere with the accuracy of this blood test. For instance, the test performed poorly in depressed patients who had a family history of mania, which is often a sign of undiagnosed bipolar disorder. When the researchers excluded these patients from their analysis, the test’s predictive accuracy improved.

Medical events that disrupt the blood-brain barrier might also artificially alter the amount of circular RNA in the bloodstream. Severe head trauma or strokes could potentially cause these brain molecules to leak into the blood at abnormal rates. Future research will need to verify how such physical injuries influence the test results.

The study authors noted that high baseline levels of the molecule correlated with specific depression symptoms like anhedonia and social withdrawal. These symptoms are often associated with a subtype of depression that is historically harder to treat with SSRIs. Further studies will need to explore exactly how this biological marker overlaps with different clinical subtypes of the disorder.

The study, “A brain-enriched circRNA blood biomarker can predict response to SSRI antidepressants,” was authored by Grigorios Papageorgiou, El Chérif Ibrahim, Victor Gorgievski, Gabriella Maxson, Evelyn Lozano, Eric Gordon, Antoine Lefrere, Marie-Julie Toupet, Philippe Courtet, Raoul Belzeaux, Jane Foster, Thomas Carmody, Roy H. Perlis, Madhukar H. Trivedi, Eleni T. Tzavara, and Nikolaos Mellios.