Tkachev Anna, Stekolshchikova Elena, Golubova Anastasia, Serkina Anna, Morozova Anna, Zorkina Yana, Riabinina Daria, Golubeva Elizaveta, Ochneva Aleksandra, Savenkova Valeria, Petrova Daria, Andreyuk Denis, Goncharova Anna, Alekseenko Irina, Kostyuk Georgiy, Khaitovich Philipp
Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, 121205, Russia; LLC NeurOmix, Moscow, 119571, Russia.
Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow, 121205, Russia.
EBioMedicine. 2024 Dec;110:105455. doi: 10.1016/j.ebiom.2024.105455. Epub 2024 Nov 20.
Anxiety and depression significantly contribute to the overall burden of mental disorders, with depression being one of the leading causes of disability. Despite this, no biochemical test has been implemented for the diagnosis of these mental disorders, while recent studies have highlighted lipids as potential biomarkers.
Using a streamlined high-throughput lipidome analysis method, direct-infusion mass spectrometry, we evaluated blood plasma lipid levels in 604 individuals from a general urban population and analysed their association with self-reported anxiety and depression symptoms. We also assessed lipidome profiles in 32 patients with clinical depression, matched to 21 healthy controls.
We found a significant correlation between lipid abundances and the severity of self-reported depression symptoms. Moreover, lipid alterations detected in high scoring volunteers mirrored the lipidome profiles identified in patients with clinical depression included in our study. Based on these findings, we developed a lipid-based predictive model distinguishing individuals reporting severe depressive symptoms from non-depressed subjects with high accuracy.
This study demonstrates the possibility of generalizing lipid alterations from a clinical cohort to the general population and underscores the potential of lipid-based biomarkers in assessing depressive states.
This study was sponsored by the Moscow Center for Innovative Technologies in Healthcare, №2707-2, №2102-11.
焦虑和抑郁显著加重了精神障碍的总体负担，抑郁症是导致残疾的主要原因之一。尽管如此，目前尚无用于诊断这些精神障碍的生化检测方法，而近期研究已将脂质作为潜在的生物标志物。
我们采用一种简化的高通量脂质组分析方法——直接进样质谱分析法，评估了来自城市普通人群的604名个体的血浆脂质水平，并分析了其与自我报告的焦虑和抑郁症状之间的关联。我们还评估了32例临床抑郁症患者以及与之匹配的21名健康对照者的脂质组谱。
我们发现脂质丰度与自我报告的抑郁症状严重程度之间存在显著相关性。此外，在高分志愿者中检测到的脂质变化反映了我们研究中临床抑郁症患者的脂质组谱。基于这些发现，我们开发了一种基于脂质的预测模型，能够高度准确地区分报告有严重抑郁症状的个体与未患抑郁症的个体。
本研究证明了将脂质变化从临床队列推广至普通人群的可能性，并强调了基于脂质的生物标志物在评估抑郁状态方面的潜力。
本研究由莫斯科医疗创新技术中心资助，项目编号为2707 - 2、2102 - 11。
