北京大学学报(医学版) ›› 2022, Vol. 54 ›› Issue (5): 863-873. doi: 10.19723/j.issn.1671-167X.2022.05.014

• 论著 • 上一篇    下一篇

首发精神分裂症肠道微生物多态性与临床症状及血清代谢组学的关联

王雪萍,张于亚楠,卢天兰,卢喆,康哲维,孙瑶瑶,岳伟华*()   

  1. 北京大学第六医院,北京大学精神卫生研究所,国家卫生健康委员会精神卫生学重点实验室(北京大学),国家精神心理疾病临床医学研究中心(北京大学第六医院),北京 100191
  • 收稿日期:2022-06-22 出版日期:2022-10-18 发布日期:2022-10-14
  • 通讯作者: 岳伟华 E-mail:dryue@bjmu.edu.cn
  • 作者简介:岳伟华,医学博士,北京大学第六医院(精神卫生研究所)教授、研究员、博士生导师,分管科研工作副院(所)长, 国家精神心理疾病临床医学研究中心副主任,北京大学博雅特聘教授,北京大学McGovern研究所研究员,北京脑科学与类脑研究中心“合作研究员”。
      国家杰出青年科学基金(2018)及优秀青年科学基金(2012)获得者,入选教育部新世纪优秀人才和北京市科技新星,获教育部自然科学奖二等奖和中华医学科技奖二等奖。兼任中国神经科学学会学习记忆基础与临床分会副主委,吴阶平医学基金会认知障碍多学科诊疗专业委员会副主委,兼Biological PsychiatryFrontiers in PsychiatryChinese Medical JournalPLoS One、《中华行为医学与脑科学杂志》等学术编辑。
      主要从事临床及生物精神病学研究,主持国家重点研发计划、国家863计划及多项国家自然科学基金项目等。牵头百余家精神科临床研究机构开展精神分裂症和抑郁症多中心临床队列及应用基础研究,取得以下学术成绩:在全基因组水平发现汉族人群精神分裂症新型易感基因,并开展跨种族人群比较分析,进而解析其部分神经生物学功能;利用多组学技术揭示遗传变异影响患者基因转录功能及脑影像学特征,并阐释儿童期城市化成长环境和表观遗传学因素调控个体认知功能的脑影像学机制;在基因组水平发现抗精神病药疗效个体差异的新型靶基因且疗效预测效果良好,推动了精神科精准医学的转化实践应用。上述系列研究为阐释精神分裂症的发病机制和指导合理用药提供了新思路。
      发表SCI收录期刊和中文核心期刊论文200多篇,代表性论著发表在Nature Genetics(2011, 2019)、Lancet PsychiatryCell DiscoveryMolecular PsychiatryNeuropsychopharmacology等期刊,在国际上产生了重要学术影响
  • 基金资助:
    国家重点研发计划项目(2021YFF1201100);国家重点研发计划项目(2016YFC1307000);北京大学医学科技创新平台发展基金(BMU2017PY030);中国医学科学院情感认知障碍综合诊疗关键技术创新单元(2019-I2M-5-006)

Variations in fecal microbiota of first episode schizophrenia associated with clinical assessment and serum metabolomics

Xue-ping WANG,Yu-ya-nan ZHANG,Tian-lan LU,Zhe LU,Zhe-wei KANG,Yao-yao SUN,Wei-hua YUE*()   

  1. Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
  • Received:2022-06-22 Online:2022-10-18 Published:2022-10-14
  • Contact: Wei-hua YUE E-mail:dryue@bjmu.edu.cn
  • Supported by:
    National Key Research and Development Program of China(2021YFF1201100);National Key Research and Development Program of China(2016YFC1307000);Fund for Fostering Young Scholars of Peking University Health Science Center(BMU2017PY030);Academy of Medical Sciences Research Unit(2019-I2M-5-006)

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摘要:

目的: 探索肠道微生物在首发未用药精神分裂症患者与健康对照者间的差异,多维度纵向分析探索抗精神病药物(antipsychotic drugs, APDs)治疗后肠道微生物与临床表型及血清代谢组学的关联。方法: 选择2017年6—12月于北京大学第六医院门诊就诊的28例首发未用药的精神分裂症患者(病例组)及同期性别、年龄、受教育程度相匹配的29例健康志愿者(对照组)为研究对象,其中病例组接受了APDs治疗。研究采集病例组入组基线和治疗6周后的粪便和血清样本,并对粪便样本微生物种类和临床症状及血清代谢物进行了检测和分析。结果: 菌群多样性分析发现,病例组alpha多样性指数(chao1、ACE、goods_coverage)低于对照组,并且组间差异有统计学意义,病例组与对照组在beta多样性方面有明显的区分。菌群组成分析结果显示BacteroidesStreptococcusRomboutsiaEubacterium ruminantium group在病例组患者接受治疗前后发生变化,且差异具有统计学意义,这些菌群可能反映了APDs治疗的影响。病例组与对照组相比,有更多的微生物种属发生变化。LEfSe种群丰度差异分析显示Prevotel-la_9Bacteroides在病例组富集,而BlautiaDialisterRoseburia在对照组富集。肠道微生物与临床症状的关联分析显示,Bifidobacterium在病例组患者中与PANSS (positive and negative syndrome scale)量表中一般精神病理学症状分量表的减分率呈正相关。体重指数的增加与药物治疗前后Clostridium_sensu_stricto_1的变化呈正相关,与基线Bacteroides也呈正相关。进一步的代谢组学分析显示,某些菌属的差异与特定代谢物,如L-甲硫氨酸、L-脯氨酸、高香草酸、N-乙酰血清素和维生素B6的相关性具有统计学意义。结论: 在精神分裂症患者和正常对照之间存在一些微生物群体特征差异且组间差异具有统计学意义,一些菌种与抗精神病药物疗效相关。结合代谢组学结果分析,提示微生物种群可能在抗精神病药物疗效和血清代谢物之间发挥中介作用,为解析抗精神病药物治疗前后肠道微生物对疾病的影响提供了新的证据。

关键词: 肠道菌群, 精神分裂症, 首发未用药, 血清代谢组学

Abstract:

Objective: To explore the role of the microbiota in drug naïve first-onset schizophrenia patients and to seek evidence from multidimensional longitudinal analyses of the intestinal microbiome and clinical phenotype with antipsychotic drugs (APDs) therapy. Methods: In this study, 28 drug naïve first onset schizophrenia patients and age-, gender- and education-matched 29 healthy controls were included, and the patients were treated with APDs. We collected fecal and serum samples at baseline and after 6 weeks of treatment to identify the different microbiota strains and analyse their correlation with clinical symptoms and serum metabolites. The 16S rRNA genes of the gut microbiota were sequenced, and the diversity and relative abundance at the phylum and genus levels were analyzsed in detail. The PANSS score, BMI changed value, and serum metabolome were included in the data analyses. Results: A multiomics study found a potential connection among the clinical phenotype, microbiota and metabolome. The species diversity analyses revealed that the alpha diversity index (chao1, ACE, and goods_coverage) in the schizophrenia APDs group was significantly lower than that in the control group, and the schizophrenia group had clear demarcation from the control group. The microbiota composition analysis results showed that the relative abundance of the genera of Bacteroides, Streptococcus, Romboutsia, and Eubacterium ruminantium group significantly changed after APDs treatment in the schizophrenia patients. These strains could reflect the APDs treatment effect. More genera had differences between the patient and control groups. The LEfSe analysis showed that Prevotella_9 and Bacteroides were enriched in schizophrenia, while Blautia, Dialister, and Roseburia were enriched in the control group. The correlation analysis between microbiota and clinical symptoms showed that Bifidobacterium in schizophrenia was positively correlated with the PANSS reduction rate of the general psychopathology scale. The BMI changed value was positively correlated with the alteration of Clostridium_sensu_stricto_1 during treatment and the baseline abundance of Bacteroides. Moreover, metabolomic data analysis revealed a significant correlation between specific genera and metabolites, such as L-methionine, L-proline, homovanillic acid, N-acetylserotonin, and vitamin B6. Conclusion: Our study found some microbiota features in schizophrenia patients and healthy controls, and several strains were correlated with APDs effects. Furthermore, the multiomics analysis implies the intermediate role of microbiota between antipsychotic effects and serum metabolites and provides new evidence to interpret the difference from multiple levels in the pathogenesis and pharmacological mechanism of schizophrenia.

Key words: Gut microbiota, Schizophrenia, Drug naïve, Serum metabolomics

中图分类号: 

  • R749.3

表1

对病例组28例精神分裂症患者基线值和对照组29例志愿者的人口学等指标统计"

Index Patients
(n=28)
Controls
(n=29)
P
Age at study entry/years 21.0±5.9 23.5±2.8 0.015
Gender, n (M/F) 15/13 13/16
Height/cm 169.5±7.7 168.2±9.7 0.587
Weight/kg 60.5±10.3 61.3±11.3 0.790
BMI/(kg/m2) 20.9±2.6 21.5±2.3 0.375

表2

不同组别间菌群alpha多样性指标分析"

Parameter S1 S2 Control P
S1 vs.control S2 vs.control S1 vs. S2
observed_species 430.64±28.67 424.24±32.39 450.50±105.18 0.708 0.950 0.170
shannon 5.73±0.58 5.76±0.68 5.69±0.59 0.695 0.675 0.840
simpson 0.93±0.06 0.93±0.06 0.94±0.04 0.510 1.000 0.737
chao1 496.69±42.12 483.71±36.44 547.35±135.45 0.219 0.044 0.221
ACE 499.28±39.13 489.89±35.05 557.44±134.00 0.098 0.027 0.397
goods_coverage 99.78±0.04 99.80±0.02 99.71±0.10 0.001 0.000 0.180
PD_whole_tree 24.43±1.54 24.59±1.75 28.31±8.24 0.059 0.069 0.638

图1

3组样本微生物组主坐标分析及不同组别在门水平的微生物组成分析"

图2

病例组APDs治疗前后与对照组的差异菌群"

图3

精神分裂症基线组(S1)与对照组的LEfSe分析"

表3

APDs治疗6周前后28例病例的临床指标统计"

Index Baseline (S1) Endpoint (S2) Reduction rate/%
Weight/kg 60.5±10.3 66.5±10.1 10.4±7.8
Waistline/cm 77.2±7.3 83.1±7.3 8.0±7.0
BMI/(kg/m2) 21.0±2.6 23.1±2.6 10.4±7.8
Clinical PANSS assessments
PANSS total score 83.4±14.2 61.0±11.8 40.1±21.6
Positive scale 24.6±7.0 13.7±4.4 38.7±83.4
Negative scale 22.6±8.0 18.5±6.7 17.9±40.4
General Psychopathology scale 36.2±7.1 28.8±6.8 34.5±34.3

图4

APDs治疗临床指标与肠道菌群的相关性分析"

图5

精神分裂症病例基线组(S1)与对照组,以及S1与S2组的血清代谢组及菌群丰度变化的相关性热图"

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