The associations between gut microbiota and fecal metabolites with intelligence quotient in preschoolers.


Journal

BMC microbiology
ISSN: 1471-2180
Titre abrégé: BMC Microbiol
Pays: England
ID NLM: 100966981

Informations de publication

Date de publication:
25 Oct 2024
Historique:
received: 12 06 2024
accepted: 10 10 2024
medline: 26 10 2024
pubmed: 26 10 2024
entrez: 25 10 2024
Statut: epublish

Résumé

The awareness of the association between the gut microbiota and human intelligence levels is increasing, but the findings are inconsistent. Furthermore, few research have explored the potential role of gut microbial metabolites in this association. This study aimed to investigate the associations of the gut microbiota and fecal metabolome with intelligence quotient (IQ) in preschoolers. The 16 S rRNA sequencing and widely targeted metabolomics were applied to analyze the gut microbiota and fecal metabolites of 150 children aged 3-6 years. The Wechsler Preschool and Primary Scale of Intelligence, Fourth Edition (WPPSI-IV) was used to assess the cognitive competence. The observed species index, gut microbiome health index, and microbial dysbiosis index presented significant differences between children with full-scale IQ (FSIQ) below the borderline (G1) and those with average or above-average (all P < 0.05). The abundance of Acinetobacter, Blautia, Faecalibacterium, Prevotella_9, Subdoligranulum, Collinsella, Dialister, Holdemanella, and Methanobrevibacter was significantly associated with preschooler's WPPSI-IV scores (P < 0.05). In all, 87 differential metabolites were identified, mainly including amino acid and its metabolites, fatty acyl, and benzene and substituted derivatives. The differential fecal metabolites carnitine C20:1-OH, 4-hydroxydebrisoquine, pantothenol, creatine, N,N-bis(2-hydroxyethyl) dodecanamide, FFA(20:5), zerumbone, (R)-(-)-2-phenylpropionic acid, M-toluene acetic acid, trans-cinnamaldehyde, isonicotinic acid, val-arg, traumatin, and 3-methyl-4-hydroxybenzaldehyde were significantly associated with the preschooler's WPPSI-IV scores (P < 0.05). The combination of Acinetobacter, Isonicotinic acid, and 3-methyl-4-hydroxybenzaldehydenine may demonstrate increased discriminatory power for preschoolers in G1. This study reveals a potential association between gut microbiome and metabolites with IQ in preschoolers, providing new directions for future research and practical applications. However, due to limitations such as the small sample size, unclear causality, and the complexity of metabolites, more validation studies are still needed to further elucidate the mechanisms and stability of these associations.

Sections du résumé

BACKGROUND BACKGROUND
The awareness of the association between the gut microbiota and human intelligence levels is increasing, but the findings are inconsistent. Furthermore, few research have explored the potential role of gut microbial metabolites in this association. This study aimed to investigate the associations of the gut microbiota and fecal metabolome with intelligence quotient (IQ) in preschoolers.
METHODS METHODS
The 16 S rRNA sequencing and widely targeted metabolomics were applied to analyze the gut microbiota and fecal metabolites of 150 children aged 3-6 years. The Wechsler Preschool and Primary Scale of Intelligence, Fourth Edition (WPPSI-IV) was used to assess the cognitive competence.
RESULTS RESULTS
The observed species index, gut microbiome health index, and microbial dysbiosis index presented significant differences between children with full-scale IQ (FSIQ) below the borderline (G1) and those with average or above-average (all P < 0.05). The abundance of Acinetobacter, Blautia, Faecalibacterium, Prevotella_9, Subdoligranulum, Collinsella, Dialister, Holdemanella, and Methanobrevibacter was significantly associated with preschooler's WPPSI-IV scores (P < 0.05). In all, 87 differential metabolites were identified, mainly including amino acid and its metabolites, fatty acyl, and benzene and substituted derivatives. The differential fecal metabolites carnitine C20:1-OH, 4-hydroxydebrisoquine, pantothenol, creatine, N,N-bis(2-hydroxyethyl) dodecanamide, FFA(20:5), zerumbone, (R)-(-)-2-phenylpropionic acid, M-toluene acetic acid, trans-cinnamaldehyde, isonicotinic acid, val-arg, traumatin, and 3-methyl-4-hydroxybenzaldehyde were significantly associated with the preschooler's WPPSI-IV scores (P < 0.05). The combination of Acinetobacter, Isonicotinic acid, and 3-methyl-4-hydroxybenzaldehydenine may demonstrate increased discriminatory power for preschoolers in G1.
CONCLUSION CONCLUSIONS
This study reveals a potential association between gut microbiome and metabolites with IQ in preschoolers, providing new directions for future research and practical applications. However, due to limitations such as the small sample size, unclear causality, and the complexity of metabolites, more validation studies are still needed to further elucidate the mechanisms and stability of these associations.

Identifiants

pubmed: 39455934
doi: 10.1186/s12866-024-03579-9
pii: 10.1186/s12866-024-03579-9
doi:

Substances chimiques

RNA, Ribosomal, 16S 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

431

Subventions

Organisme : National Natural Science Foundation of China
ID : 22366007
Organisme : Guangxi Key Research and Development Program
ID : AB17195012

Informations de copyright

© 2024. The Author(s).

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Auteurs

Jinghua Long (J)

Department of Prevention and Healthcare, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530021, China.

Jiehua Chen (J)

Department of Microbiology, School of Preclinical Medicine, Guangxi Medical University, Nanning, Guangxi, 530021, China.

Huishen Huang (H)

Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, 530021, China.

Jun Liang (J)

Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, 530021, China.

Lixiang Pang (L)

Department of Sanitary Chemistry, School of Public Health, Guangxi Medical University, Nanning, Guangxi, 530021, China.

Kaiqi Yang (K)

Department of Sanitary Chemistry, School of Public Health, Guangxi Medical University, Nanning, Guangxi, 530021, China.

Huanni Wei (H)

Liuzhou People's Hospital Affiliated to Guangxi Medical University, Liuzhou, Guangxi, 545006, China.

Qian Liao (Q)

Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, 530021, China.

Junwang Gu (J)

Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, 530021, China.

Xiaoyun Zeng (X)

Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, 530021, China.

Dongping Huang (D)

Department of Sanitary Chemistry, School of Public Health, Guangxi Medical University, Nanning, Guangxi, 530021, China. dongpinghuang@gxmu.edu.cn.

Xiaoqiang Qiu (X)

Department of Epidemiology and Health Statistics, School of Public Health, Guangxi Medical University, Nanning, Guangxi, 530021, China. xqqiu9999@163.com.

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