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Journal of Peking University (Health Sciences) ›› 2022, Vol. 54 ›› Issue (5): 863-873. doi: 10.19723/j.issn.1671-167X.2022.05.014

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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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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

CLC Number: 

  • R749.3

Table 1

Demographic and clinical characteristics of 28 patients and 29 controls at baseline"

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

Table 2

Alpha diversity index among different groups"

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

Figure 1

Principal coordinates analysis (PCoA) plot and microbial composition of different group at phylum level A, the unweighted UniFrac PCoA plot camparing sample distribution between the schizophrenia patients before APDs treatment (S1 group) and after treatment (S2 group), and healthy controls (control), red and green dots represent baseline and posttreatment schizophrenia patients, respectively, black dots represent healthy controls. PC1 and PC2 are the top 2 principal component; B and C, show the microbial composition of different group at phylum level; B, the top 4 phyla with the highest abundance were shown; C, the proportion of phyla ranked 5-10 in abundance was enlarged."

Figure 2

The histogram of the microbiota of schizophrenia before and after APDs treatment and the control group A, the genera that have relative abundance of genera higher in schizophrenia than control group; B, the genera that have relative abundance lower in schizophrenia than control group; C, the genera that had different relative abundance between S1 and S2 group, which reflect the APDs treatment effect. The relative abundance more than 1% total amount of microbiota at genus level which have significant differences (P < 0.05) were shown as $\bar x \pm s$. *P < 0.05, #P < 0.01，★ P < 0.001."

Figure 3

Linear discriminant analysis effect size (LEfSe) analysis between schizophrenia baseline group (S1) and the control group A, LEfSe cladogram reveal the different taxa between two groups; B, bar plot showed the taxa that meeting linear discriminant analysis (LDA) score>4."

Table 3

Demographic and clinical characteristics of 28 patients before and after 6-week APDs treatment"

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

Figure 4

The correlation between therapeutic effect and intestinal microbiota A, the reduction score of general psychopathology scale was positive correlated with Bifidobacterium; B, the change of Clostridium_sensu_stricto_1 before and after antipsychotic drugs (APDs) treatment were correlated with body mass index (BMI) changed values; C, the baseline of Bacteroides in schizophrenia (S1) was correlated with BMI changed values. PANSS, positive and negative syndrome scale."

Figure 5

Heatmap of correlation of serum metabolomic difference and alterant microbiota abundances between S1 and control group, and the difference between S1 and S2 group A and B, the genera that have significant change between S1 and Control are shown in the heatmap; C and D, heatmap of correlation of serum metabolomic difference and alterant microbiota abundances between S1 and S2 group are shown in the heatmap. A and C are the anion metabolite; B and D are the positive ion metabolite. UDP, uridine diphosphate; PC, phosphatidylcholine; TXB2, thromboxane B2; PGF1α, prostaglandin F1α; MG, monoacylglycerol; DG, diacylglycerol; UMP, uridine monophosphate; PE, phosphatidyl ethanolamine."

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