Identifying serum lipidomic signatures related to prognosis in first-episode schizophrenia.

IF 3.4 2区医学 Q2 PSYCHIATRY

BMC Psychiatry Pub Date : 2025-05-08 DOI:10.1186/s12888-025-06802-7

Mengyi Luo, Suzhen Zhang, Jingxin Xue, Tianhao Gao, Xuan Li, Zhaolin Zhai, Chang Lu, Yuke Dong, Kaiming Zhuo, Qiong Xiang, Qing Kang, Shunying Yu, Chunhong Shao, Dengtang Liu

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引用次数: 0

Abstract

Background: Antipsychotic medications are crucial for alleviating symptoms of schizophrenia (SCZ). However, treatment responses vary across individuals, and few reliable biomarkers currently exist to predict the clinical outcome. Therefore, we aim to identify potential lipid markers for treatment outcomes in patients with first-episode SCZ.

Methods: Pre-treatment serum samples were obtained from 95 participants who underwent an 8-week treatment regimen with antipsychotic drugs. Untargeted liquid chromatography-mass spectrometry (LC-MS) was used to acquire serum lipidomic profiles, correlating them with treatment responses at 8 weeks to identify potential lipid signatures. The antipsychotic treatment response was quantified using the percentage change on the Positive and Negative Syndrome Scale (PANSS) scale.

Results: By combining LASSO regression and Random Forest regression, we identified 8 positively associated and 2 negatively associated baseline lipids related to the PANSS reduction rate. In the further analysis of logistic regression, we identified three candidate lipids, PC (18:2e_19:0), PE (53:7), and TG (16:2e_19:0_20:5), which could together distinguish poor and good responders, with an AUC of 0.805 (95% CI, 0.715-0.894).

Conclusions: Our findings suggest that this set of lipid biomarkers may have the potential to predict the outcome of antipsychotic drug treatment. Further validation and larger studies are needed to evaluate their potential for clinical applications.

Clinical trial number: Not applicable.

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鉴定与首发精神分裂症预后相关的血清脂质组学特征。

背景：抗精神病药物是缓解精神分裂症（SCZ）症状的关键。然而，治疗反应因个体而异，目前很少有可靠的生物标志物来预测临床结果。因此，我们的目标是确定首发SCZ患者治疗结果的潜在脂质标志物。方法：从95名接受8周抗精神病药物治疗方案的参与者中获得治疗前血清样本。使用非靶向液相色谱-质谱法（LC-MS）获得血清脂质组学特征，并将其与8周时的治疗反应相关联，以确定潜在的脂质特征。使用阳性和阴性症状量表（PANSS）量表的百分比变化来量化抗精神病治疗反应。结果：通过LASSO回归和随机森林回归相结合，我们确定了8种与PANSS降低率呈正相关的基线脂质和2种负相关的基线脂质。在进一步的逻辑回归分析中，我们确定了三种候选脂质，PC (18:20 e_19:0)， PE（53:7）和TG (16:20 e_19:0_20:5)，它们可以共同区分不良和良好的反应，AUC为0.805 （95% CI, 0.715-0.894）。结论：我们的研究结果表明，这组脂质生物标志物可能具有预测抗精神病药物治疗结果的潜力。需要进一步的验证和更大规模的研究来评估它们的临床应用潜力。临床试验号：不适用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

BMC Psychiatry 医学-精神病学

CiteScore

5.90

自引率

4.50%

发文量

716

审稿时长

3-6 weeks

期刊介绍： BMC Psychiatry is an open access, peer-reviewed journal that considers articles on all aspects of the prevention, diagnosis and management of psychiatric disorders, as well as related molecular genetics, pathophysiology, and epidemiology.