The predictive, preventive, and personalized medicine of depression: gut microbiota and inflammation.

IF 5.9 Q1 MEDICINE, RESEARCH & EXPERIMENTAL
The EPMA journal Pub Date : 2024-09-20 eCollection Date: 2024-12-01 DOI:10.1007/s13167-024-00379-z
Jialin Wu, Guosen Ou, Shiqi Wang, Yaokang Chen, Lu Xu, Li Deng, Huachong Xu, Xiaoyin Chen
{"title":"The predictive, preventive, and personalized medicine of depression: gut microbiota and inflammation.","authors":"Jialin Wu, Guosen Ou, Shiqi Wang, Yaokang Chen, Lu Xu, Li Deng, Huachong Xu, Xiaoyin Chen","doi":"10.1007/s13167-024-00379-z","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Working hypothesis and methodology: </strong>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).</p><p><strong>Results: </strong>UVMR identified 15 GM taxa and 4 cytokines associated with the onset of depression. Specifically, <i>Romboutsia</i>, <i>Intestinimonas</i>, <i>Ruminococcaceae UCG011</i>, and circulating ADA, IL-18R1 were all inferred to be protective factors against the onset of depression. Conversely, <i>Lachnospiraceae FCS020 group</i>, <i>Streptococcus</i>, <i>Marvinbryantia</i>, 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.</p><p><strong>Conclusions: </strong>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.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s13167-024-00379-z.</p>","PeriodicalId":94358,"journal":{"name":"The EPMA journal","volume":"15 4","pages":"587-598"},"PeriodicalIF":5.9000,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11612071/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The EPMA journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s13167-024-00379-z","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0

Abstract

Background: 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.

Working hypothesis and methodology: 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).

Results: UVMR identified 15 GM taxa and 4 cytokines associated with the onset of depression. Specifically, Romboutsia, Intestinimonas, Ruminococcaceae UCG011, and circulating ADA, IL-18R1 were all inferred to be protective factors against the onset of depression. Conversely, Lachnospiraceae FCS020 group, Streptococcus, Marvinbryantia, 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.

Conclusions: 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.

Supplementary information: The online version contains supplementary material available at 10.1007/s13167-024-00379-z.

抑郁症的预测、预防和个性化药物:肠道微生物群和炎症。
背景: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。基于预测性、预防性和个性化医学(PPPM)的原则,确定与抑郁症相关的特定基因及其机制,是实现抑郁症针对性预防和个性化治疗的关键一步。工作假设和方法:我们假设肠道微生物群(GM)和细胞因子都影响抑郁症的发病,细胞因子作为GM对抑郁症作用的介质。为了验证这一假设,我们采用单变量孟德尔随机化(UVMR)分析来鉴定与抑郁和细胞因子相关的转基因分类群,并确定鉴定的转基因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)来推断细胞因子在鉴定的GM差异属与抑郁症之间的中介作用。我们的研究结果表明,肠道生态失调引起的免疫失衡是抑郁症发病的早期风险指标。这为利用GM无创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。将无创粪便基因检测与现有的心理问卷等方法相结合,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可以帮助抑郁症管理从反应性药物过渡到预测性、预防性和个性化药物(PPPM)。结果:UVMR鉴定出15个GM分类群和4个与抑郁症发病相关的细胞因子。具体而言,Romboutsia、肠子单胞菌、Ruminococcaceae UCG011以及循环ADA、IL-18R1均被推断为抑郁症发病的保护因素。相反,Lachnospiraceae FCS020组、Streptococcus、Marvinbryantia、VEGF_A和TNFSF14被推断为抑郁症发病的危险因素。此外,MVMR验证了一些细胞因子在GM对抑郁症的影响中的中介作用。结论:我们的研究强调了GM改变对抑郁症的影响,揭示了炎症的中介作用。通过调控这些特异性基因,希望临床治疗抑郁症能从传统医学转向PPPM。本研究借助孟德尔随机化(mendelian randomization, MR)方法,为GM无创伤粪便检测在临床抑郁症早期筛查中的广泛应用提供支持,并根据筛查结果进行精准治疗,针对性地补充特定细菌,纠正免疫失衡预防抑郁症,缓解或阻断抑郁症的发病过程。补充信息:在线版本包含补充资料,提供地址为10.1007/s13167-024-00379-z。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
12.50
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信