Wang Yi, Xu Dongcao, Liu Xinxin, Cheng Mengchun, Huang Jingsong, Liu Dan, Zhang Xiaozhe, Zhang Lihua
State Key Laboratory of Medical Proteomics, National Chromatographic R. & A. Center, CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China; University of Chinese Academy of Sciences, Beijing 100039, China.
School of Pharmaceutical Sciences, Zhengzhou University, Zhengzhou 450001, China.
J Pharm Biomed Anal. 2025 Feb 15;254:116572. doi: 10.1016/j.jpba.2024.116572. Epub 2024 Nov 19.
The prevalence of major depressive disorder (MDD) is higher in females than males, emphasizing the need to identify gender-specific biomarkers to improve diagnosis accuracy. In this study, a cross-sectional investigation with 258 samples was conducted to evaluate the discriminative power of potential gender-specific biomarkers for MDD. Eighteen MDD-related differential metabolites have been identified, involving pathways of phospholipids, glycerolipids, fatty acids, sphingolipids, cholesterol, vitamin E, and heme. A potential biomarker combination consisting of palmitelaidic acid, gamma carboxyethyl hydroxychroman (gamma-CEHC), and lysoPE(16:0) was confirmed for predicting depression in women using binary logistic regression analysis. To evaluate the panel's specificity, nine generalized anxiety disorder (GAD) samples, which share highly similar clinical symptoms with MDD, were included in the validation set. The discovery and validation sets yielded an area under the receiver operating characteristic curve of 0.86 and 0.83, respectively. All nine female GAD samples were correctly predicted as non-MDD, demonstrating the panel's specificity in diagnosing female MDD. Remarkably, this composite panel achieved a 75 % prediction accuracy in female samples in both the discovery and validation sets, but it did not reach 60 % prediction accuracy in male samples in either set. Our findings highlight the importance of gender-specific molecular diagnostics in developing practical and accurate diagnostic methods for MDD.
重度抑郁症（MDD）在女性中的患病率高于男性，这凸显了识别性别特异性生物标志物以提高诊断准确性的必要性。在本研究中，我们进行了一项包含258个样本的横断面调查，以评估潜在的性别特异性生物标志物对MDD的判别能力。已鉴定出18种与MDD相关的差异代谢物，涉及磷脂、甘油酯、脂肪酸、鞘脂、胆固醇、维生素E和血红素的代谢途径。通过二元逻辑回归分析，确认了由棕榈油酸、γ-羧乙基羟基色满（γ-CEHC）和溶血磷脂酰乙醇胺（16:0）组成的潜在生物标志物组合可用于预测女性的抑郁症。为了评估该指标组合的特异性，我们将9个与MDD临床症状高度相似的广泛性焦虑症（GAD）样本纳入验证集。发现集和验证集的受试者工作特征曲线下面积分别为0.86和0.83。所有9个女性GAD样本均被正确预测为非MDD，证明了该指标组合在诊断女性MDD方面的特异性。值得注意的是，该复合指标组合在发现集和验证集的女性样本中均达到了75%的预测准确率，但在任一集中的男性样本中，其预测准确率均未达到60%。我们的研究结果强调了性别特异性分子诊断在开发实用且准确的MDD诊断方法中的重要性。
