Wu Jialin, Ou Guosen, Wang Shiqi, Chen Yaokang, Xu Lu, Deng Li, Xu Huachong, Chen Xiaoyin
School of Traditional Chinese Medicine, Jinan University, Guangzhou, 510632 China.
Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou, 510632 China.
EPMA J. 2024 Sep 20;15(4):587-598. doi: 10.1007/s13167-024-00379-z. eCollection 2024 Dec.
Gut microbiota (GM) is closely associated with the onset of depression, in which inflammation plays an essential role. Identifying specific GM associated with depression and their mechanisms, based on the principles of predictive, preventive, and personalized medicine (PPPM), is a critical step toward achieving targeted prevention and personalized treatment for depression.
We hypothesized that both gut microbiota (GM) and cytokines influence the onset of depression, with cytokines acting as mediators of GM effects on depression. To test this hypothesis, we employed univariate Mendelian Randomization (UVMR) analysis to identify GM taxa associated with depression and cytokines and to determine the potential role of the identified GM taxa on these cytokines. Subsequently, multivariate Mendelian randomization (MVMR) was used to infer the mediating role of cytokines between the identified differential genus of GM and depression. Our results indicate that immune imbalance due to intestinal dysbiosis serves as an early risk indicator for the onset of depression. This provides a basis for utilizing non-invasive stool detection of GM for early screening, timely prevention, and personalized treatment of depression. By combining non-invasive stool detection of GM with existing methods, such as psychological questionnaires, we can jointly predict and assess the risk of developing depression. Additionally, formulating personalized treatment protocols that combine probiotics and medication can help transition depression management from reactive medicine to predictive, preventive, and personalized medicine (PPPM).
UVMR identified 15 GM taxa and 4 cytokines associated with the onset of depression. Specifically, , , , and circulating ADA, IL-18R1 were all inferred to be protective factors against the onset of depression. Conversely, , , , VEGF_A, and TNFSF14 were inferred as risk factors for the onset of depression. Further, MVMR validated the mediating role of some cytokines in the effects of GM on depression.
Our study highlights the influence of alterations in GM on depression, revealing a mediating role of inflammation. By regulating these specific GM, it is hoped that the clinical treatment of depression can be transformed from traditional medicine to PPPM. With the help of mendelian randomization (MR) method, this study provides support for the wide application of non-invasive stool detection of GM for early screening of depression in clinical and carries out precise treatment based on the screening results, targeting the supplementation of specific bacteria, correcting the immune imbalance to prevent depression, and mitigating or blocking the disease process of depression.
The online version contains supplementary material available at 10.1007/s13167-024-00379-z.
肠道微生物群（GM）与抑郁症的发病密切相关，其中炎症起着至关重要的作用。基于预测、预防和个性化医学（PPPM）原则，识别与抑郁症相关的特定GM及其机制，是实现抑郁症靶向预防和个性化治疗的关键一步。
我们假设肠道微生物群（GM）和细胞因子均影响抑郁症的发病，细胞因子作为GM对抑郁症影响的介质。为验证这一假设，我们采用单变量孟德尔随机化（UVMR）分析来识别与抑郁症和细胞因子相关的GM分类群，并确定所识别的GM分类群对这些细胞因子的潜在作用。随后，使用多变量孟德尔随机化（MVMR）来推断细胞因子在已识别的GM差异属与抑郁症之间的中介作用。我们的结果表明，肠道生态失调导致的免疫失衡是抑郁症发病的早期风险指标。这为利用GM的非侵入性粪便检测进行抑郁症的早期筛查、及时预防和个性化治疗提供了依据。通过将GM的非侵入性粪便检测与现有方法（如心理问卷）相结合，我们可以共同预测和评估患抑郁症的风险。此外，制定结合益生菌和药物的个性化治疗方案有助于将抑郁症管理从反应性医学转变为预测、预防和个性化医学（PPPM）。
UVMR识别出15个与抑郁症发病相关的GM分类群和4种细胞因子。具体而言， 、 、 以及循环ADA、IL-18R1均被推断为预防抑郁症发病的保护因素。相反， 、 、 、VEGF_A和TNFSF14被推断为抑郁症发病的风险因素。此外，MVMR验证了某些细胞因子在GM对抑郁症影响中的中介作用。
我们的研究突出了GM改变对抑郁症的影响，揭示了炎症的中介作用。通过调节这些特定的GM，有望将抑郁症的临床治疗从传统医学转变为PPPM。借助孟德尔随机化（MR）方法，本研究为GM的非侵入性粪便检测在临床抑郁症早期筛查中的广泛应用提供了支持，并基于筛查结果进行精准治疗，针对性地补充特定细菌，纠正免疫失衡以预防抑郁症，减轻或阻断抑郁症的疾病进程。
在线版本包含可在10.1007/s13167-024-00379-z获取的补充材料。
