Identification of Bacterial Lipopolysaccharide-Associated Genes and Molecular Subtypes in Autism Spectrum Disorder

Yuanxia He,1,2,* Yun He,2,* Boli Cheng1,2 1Department of Clinical Medicine, North Sichuan Medical College, Nanchong, Sichuan, 637000, People’s Republic of China; 2Department of Pediatrics, Affiliated Hospital, North Sichuan Medical College, Nanchong, Sichuan, 637000, People’s Republi...

Full description

Saved in:
Bibliographic Details
Main Authors: He Y, Cheng B
Format: Article
Language:English
Published: Dove Medical Press 2025-01-01
Series:Pharmacogenomics and Personalized Medicine
Subjects:
Online Access:https://www.dovepress.com/identification-of-bacterial-lipopolysaccharide-associated-genes-and-mo-peer-reviewed-fulltext-article-PGPM
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832594288056205312
author He Y
He Y
Cheng B
author_facet He Y
He Y
Cheng B
author_sort He Y
collection DOAJ
description Yuanxia He,1,2,* Yun He,2,* Boli Cheng1,2 1Department of Clinical Medicine, North Sichuan Medical College, Nanchong, Sichuan, 637000, People’s Republic of China; 2Department of Pediatrics, Affiliated Hospital, North Sichuan Medical College, Nanchong, Sichuan, 637000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yun He; Boli Cheng, Department of Pediatrics, Affiliated Hospital, North Sichuan Medical College, Nanchong, 637000, Sichuan, People’s Republic of China, Email heyun02409@aliyun.comBackground: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition marked by diverse symptoms affecting social interaction, communication, and behavior. This research aims to explore bacterial lipopolysaccharide (LPS)- and immune-related (BLI) molecular subgroups in ASD to enhance understanding of the disorder.Methods: We analyzed 89 control samples and 157 ASD samples from the GEO database, identifying BLI signatures using least absolute shrinkage and selection operator regression (LASSO) and logistic regression machine learning algorithms. A nomogram prediction model was developed based on these signatures, and we performed Gene Set Enrichment Analysis (GSEA), Gene Set Variation Analysis (GSVA), and immune cell infiltration analysis to assess the impact of BLI subtypes and their underlying mechanisms.Results: Our findings revealed 17 differentially expressed BLI genes in children with ASD, with BLNK, MAPK8, PRKCQ, and TNFSF12 identified as potential biomarkers. The nomogram demonstrated high diagnostic accuracy for ASD. We delineated two distinct molecular subtypes (Cluster 1 and Cluster 2), with GSVA indicating that Cluster 2 showed upregulation of immune- and inflammation-related pathways. This cluster exhibited increased levels of antimicrobial agents, chemokines, cytokines, and TNF family cytokines, alongside activation of bacterial lipoprotein-related pathways. A significant correlation was found between these pathways and distinct immune cell subtypes, suggesting a potential mechanism for neuroinflammation and immune cell infiltration in ASD.Conclusion: Our research highlights the role of BLI-associated genes in the immune responses of individuals with ASD, indicating their contribution to the disorder’s typification. The interplay between bacterial components, genetic predisposition, and immune dysregulation offers new insights for understanding ASD and developing personalized interventions.Keywords: autism, bacterial metabolites, immune cell infiltration, GEO, molecular subtypes, immune responses
format Article
id doaj-art-6e795123a0004f7e9841d0a1214893a7
institution Kabale University
issn 1178-7066
language English
publishDate 2025-01-01
publisher Dove Medical Press
record_format Article
series Pharmacogenomics and Personalized Medicine
spelling doaj-art-6e795123a0004f7e9841d0a1214893a72025-01-19T16:42:59ZengDove Medical PressPharmacogenomics and Personalized Medicine1178-70662025-01-01Volume 1811899334Identification of Bacterial Lipopolysaccharide-Associated Genes and Molecular Subtypes in Autism Spectrum DisorderHe YHe YCheng BYuanxia He,1,2,* Yun He,2,* Boli Cheng1,2 1Department of Clinical Medicine, North Sichuan Medical College, Nanchong, Sichuan, 637000, People’s Republic of China; 2Department of Pediatrics, Affiliated Hospital, North Sichuan Medical College, Nanchong, Sichuan, 637000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yun He; Boli Cheng, Department of Pediatrics, Affiliated Hospital, North Sichuan Medical College, Nanchong, 637000, Sichuan, People’s Republic of China, Email heyun02409@aliyun.comBackground: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition marked by diverse symptoms affecting social interaction, communication, and behavior. This research aims to explore bacterial lipopolysaccharide (LPS)- and immune-related (BLI) molecular subgroups in ASD to enhance understanding of the disorder.Methods: We analyzed 89 control samples and 157 ASD samples from the GEO database, identifying BLI signatures using least absolute shrinkage and selection operator regression (LASSO) and logistic regression machine learning algorithms. A nomogram prediction model was developed based on these signatures, and we performed Gene Set Enrichment Analysis (GSEA), Gene Set Variation Analysis (GSVA), and immune cell infiltration analysis to assess the impact of BLI subtypes and their underlying mechanisms.Results: Our findings revealed 17 differentially expressed BLI genes in children with ASD, with BLNK, MAPK8, PRKCQ, and TNFSF12 identified as potential biomarkers. The nomogram demonstrated high diagnostic accuracy for ASD. We delineated two distinct molecular subtypes (Cluster 1 and Cluster 2), with GSVA indicating that Cluster 2 showed upregulation of immune- and inflammation-related pathways. This cluster exhibited increased levels of antimicrobial agents, chemokines, cytokines, and TNF family cytokines, alongside activation of bacterial lipoprotein-related pathways. A significant correlation was found between these pathways and distinct immune cell subtypes, suggesting a potential mechanism for neuroinflammation and immune cell infiltration in ASD.Conclusion: Our research highlights the role of BLI-associated genes in the immune responses of individuals with ASD, indicating their contribution to the disorder’s typification. The interplay between bacterial components, genetic predisposition, and immune dysregulation offers new insights for understanding ASD and developing personalized interventions.Keywords: autism, bacterial metabolites, immune cell infiltration, GEO, molecular subtypes, immune responseshttps://www.dovepress.com/identification-of-bacterial-lipopolysaccharide-associated-genes-and-mo-peer-reviewed-fulltext-article-PGPMautismbacterial metabolitesimmune cell infiltrationgeomolecular subtypesimmune responses.
spellingShingle He Y
He Y
Cheng B
Identification of Bacterial Lipopolysaccharide-Associated Genes and Molecular Subtypes in Autism Spectrum Disorder
Pharmacogenomics and Personalized Medicine
autism
bacterial metabolites
immune cell infiltration
geo
molecular subtypes
immune responses.
title Identification of Bacterial Lipopolysaccharide-Associated Genes and Molecular Subtypes in Autism Spectrum Disorder
title_full Identification of Bacterial Lipopolysaccharide-Associated Genes and Molecular Subtypes in Autism Spectrum Disorder
title_fullStr Identification of Bacterial Lipopolysaccharide-Associated Genes and Molecular Subtypes in Autism Spectrum Disorder
title_full_unstemmed Identification of Bacterial Lipopolysaccharide-Associated Genes and Molecular Subtypes in Autism Spectrum Disorder
title_short Identification of Bacterial Lipopolysaccharide-Associated Genes and Molecular Subtypes in Autism Spectrum Disorder
title_sort identification of bacterial lipopolysaccharide associated genes and molecular subtypes in autism spectrum disorder
topic autism
bacterial metabolites
immune cell infiltration
geo
molecular subtypes
immune responses.
url https://www.dovepress.com/identification-of-bacterial-lipopolysaccharide-associated-genes-and-mo-peer-reviewed-fulltext-article-PGPM
work_keys_str_mv AT hey identificationofbacteriallipopolysaccharideassociatedgenesandmolecularsubtypesinautismspectrumdisorder
AT hey identificationofbacteriallipopolysaccharideassociatedgenesandmolecularsubtypesinautismspectrumdisorder
AT chengb identificationofbacteriallipopolysaccharideassociatedgenesandmolecularsubtypesinautismspectrumdisorder