Department of Anesthesiology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, 201204 Shanghai, PR China; Shanghai Key Laboratory of Maternal Fetal Medicine, Clinical and Translational Research Center, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, 201204 Shanghai, PR China.
Department of Anesthesiology and Perioperative Medicine, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, 200081 Shanghai, PR China; Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration of Ministry of Education, Orthopedic Department, Tongji Hospital, School of Medicine, Tongji University, 200065 Shanghai, PR China.
J Affect Disord. 2023 Dec 1;342:177-181. doi: 10.1016/j.jad.2023.09.021. Epub 2023 Sep 18.
Postpartum depression (PPD), the depressive episodes following delivery, is a serious and frequent psychiatric disorder. While numerous screening tools existed for depressive episodes, e.g., the Edinburgh Postnatal Depression Scale (EPDS), there are no objective biological measures for predicting PPD. Despite several studies done to identify biomarkers in PPD, there has been limited exploration into cerebrospinal fluid (CSF) which directly interfaces with the brain. Consequently, novel potential biomarkers of CSF are required to predict PPD, so as to target specific preventive interventions.
Seventy-five parturients undergoing caesarean delivery were enrolled for CSF collection at delivery. Of the twenty-eight subjects who didn't meet any exclusion criteria, the number of the healthy parturients whose score of EPDS 6-weeks postpartum (6-wpp) < 5 and PPD patients whose EPDS 6-wpp ≥ 13 was ten respectively. Gas chromatography-mass spectrometry (GC-MS) analysis of CSF was used for metabolomic assessments.
We found that capric acid, dodecanoic acid, arachidic acid and behenic acid in CSF were significantly negatively correlated with PPD symptoms, meanwhile L-tryptophan had an obvious positive correlation. Moreover, these five biomarkers can be used as effective predictive biomarkers for PPD.
The main limitations are the inclusion of only parturients who underwent caesarean sections and a small sample size.
This study innovatively investigated potential predictive biomarkers of PPD before the onset through intrapartum maternal CSF metabolomics, which offered a more objective approach to predict and diagnose PPD, leading to help identify high-risk parturients for early initiation of secondary prevention to reduce global PPD burden.
产后抑郁症(PPD)是一种严重且常见的产后精神障碍。尽管有许多用于筛查产后抑郁发作的工具,如爱丁堡产后抑郁量表(EPDS),但目前尚无预测 PPD 的客观生物学指标。尽管已经进行了多项研究来识别 PPD 中的生物标志物,但对与大脑直接接触的脑脊液(CSF)的探索有限。因此,需要新的潜在 CSF 生物标志物来预测 PPD,以便针对特定的预防干预措施。
对 75 名行剖宫产的产妇进行分娩时的 CSF 采集。在 28 名未满足任何排除标准的受试者中,10 名 EPDS 产后 6 周(6-wpp)评分<5 的健康产妇和 EPDS 6-wpp≥13 的 PPD 患者。CSF 的气相色谱-质谱分析(GC-MS)用于代谢组学评估。
我们发现 CSF 中的癸酸、十二烷酸、花生四烯酸和山嵛酸与 PPD 症状呈显著负相关,而 L-色氨酸则呈明显正相关。此外,这五种生物标志物可以作为预测 PPD 的有效生物标志物。
主要局限性是仅纳入了接受剖宫产的产妇,且样本量较小。
本研究通过分娩时的母体 CSF 代谢组学创新性地研究了 PPD 的潜在预测生物标志物,为预测和诊断 PPD 提供了更客观的方法,有助于识别高危产妇,以便尽早开始二级预防,从而降低全球 PPD 负担。