{"title":"Identification of Bacterial Lipopolysaccharide-Associated Genes and Molecular Subtypes in Autism Spectrum Disorder.","authors":"Yuanxia He, Yun He, Boli Cheng","doi":"10.2147/PGPM.S494126","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":56015,"journal":{"name":"Pharmacogenomics & Personalized Medicine","volume":"18 ","pages":"1-18"},"PeriodicalIF":1.8000,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11750731/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pharmacogenomics & Personalized Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/PGPM.S494126","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: 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.
期刊介绍:
Pharmacogenomics and Personalized Medicine is an international, peer-reviewed, open-access journal characterizing the influence of genotype on pharmacology leading to the development of personalized treatment programs and individualized drug selection for improved safety, efficacy and sustainability.
In particular, emphasis will be given to:
Genomic and proteomic profiling
Genetics and drug metabolism
Targeted drug identification and discovery
Optimizing drug selection & dosage based on patient''s genetic profile
Drug related morbidity & mortality intervention
Advanced disease screening and targeted therapeutic intervention
Genetic based vaccine development
Patient satisfaction and preference
Health economic evaluations
Practical and organizational issues in the development and implementation of personalized medicine programs.