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<p>Allergic rhinitis (AR) affects 20–30% of India’s population and significantly impacts quality of life. Recent research has revealed connections between AR and the human microbiome, yet direct studies on nasal microbiome in Indian AR patients remain scarce. The relationship between AR severity and microbiome profiles has not been previously investigated. To investigate the nasal microbiome profile of AR patients compared to healthy individuals and analyze correlations between AR severity according to ARIA criteria and microbiome composition. A case-control study was conducted at AIIMS Bhubaneswar involving 22 participants (AR patients and healthy controls). Nasal swab samples were collected from the middle turbinate using DNA-free flocked swabs. DNA extraction was performed using a modified DNeasy PowerLyzer PowerSoil Kit, followed by 16&#xa0;S rRNA gene sequencing targeting the V3-V4 hypervariable region on Illumina MiSeq platform. Taxonomic classification used Kraken2 with NCBI RefSeq database. Alpha and beta diversity analyses were conducted, and correlations between microbial taxa and clinical parameters were assessed using Spearman rank correlation. Microbiome analysis revealed 24 operational taxonomic units (OTUs) at phylum level and 53 OTUs at species level after filtration. *Acinetobacter johnsonii* emerged as the most abundant species in AR patients (~ 40% relative abundance) compared to controls (~ 30%). AR patients showed higher levels of *Haemophilus influenzae*, *Staphylococcus epidermidis*, and *Acinetobacter guillouiae*, while controls exhibited greater abundance of *Alloiococcus otitis*, *Propionibacterium acnes*, and *Pseudomonas stutzeri*. Alpha diversity measures were significantly higher in healthy controls compared to AR patients. Within ARIA classifications, greater disease severity and persistence correlated with lower microbial diversity and evenness. Gender-specific differences were observed, with *Lysinbacillus boronitolerans* more abundant in females (<i>p</i> = 0.043) and *Pseudomonas alcaligenes* in males (<i>p</i> = 0.046). Medication history significantly influenced beta diversity patterns. This study demonstrates significant differences in nasal bacterial composition between AR patients and healthy controls, with microbial diversity inversely correlating with disease severity. The findings highlight the importance of demographic and treatment factors in shaping microbial communities, providing valuable insights for potential biomarkers and personalized therapeutic approaches in AR management. This represents the first comprehensive analysis of nasal microbiome impact on AR severity using ARIA criteria in an Indian population.</p>

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Comprehensive Analysis of Nasal Microbiome in Allergic Rhinitis Patients: An In-depth Exploration in a Tertiary Care Centre in India

  • 期刊论文

  • 发表日期：

    2025年11月1日

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  • Lucky Dash,
  • Priyanka Mishra,
  • Saurav Sarkar,
  • Pankaj Ranjan Mohapatra,
  • Giriprasad Venugopal,
  • Mukund Namdev Sable,
  • Pradipta Ku Parida,
  • Balamurugan Ramadass

摘要

Allergic rhinitis (AR) affects 20–30% of India’s population and significantly impacts quality of life. Recent research has revealed connections between AR and the human microbiome, yet direct studies on nasal microbiome in Indian AR patients remain scarce. The relationship between AR severity and microbiome profiles has not been previously investigated. To investigate the nasal microbiome profile of AR patients compared to healthy individuals and analyze correlations between AR severity according to ARIA criteria and microbiome composition. A case-control study was conducted at AIIMS Bhubaneswar involving 22 participants (AR patients and healthy controls). Nasal swab samples were collected from the middle turbinate using DNA-free flocked swabs. DNA extraction was performed using a modified DNeasy PowerLyzer PowerSoil Kit, followed by 16 S rRNA gene sequencing targeting the V3-V4 hypervariable region on Illumina MiSeq platform. Taxonomic classification used Kraken2 with NCBI RefSeq database. Alpha and beta diversity analyses were conducted, and correlations between microbial taxa and clinical parameters were assessed using Spearman rank correlation. Microbiome analysis revealed 24 operational taxonomic units (OTUs) at phylum level and 53 OTUs at species level after filtration. *Acinetobacter johnsonii* emerged as the most abundant species in AR patients (~ 40% relative abundance) compared to controls (~ 30%). AR patients showed higher levels of *Haemophilus influenzae*, *Staphylococcus epidermidis*, and *Acinetobacter guillouiae*, while controls exhibited greater abundance of *Alloiococcus otitis*, *Propionibacterium acnes*, and *Pseudomonas stutzeri*. Alpha diversity measures were significantly higher in healthy controls compared to AR patients. Within ARIA classifications, greater disease severity and persistence correlated with lower microbial diversity and evenness. Gender-specific differences were observed, with *Lysinbacillus boronitolerans* more abundant in females (p = 0.043) and *Pseudomonas alcaligenes* in males (p = 0.046). Medication history significantly influenced beta diversity patterns. This study demonstrates significant differences in nasal bacterial composition between AR patients and healthy controls, with microbial diversity inversely correlating with disease severity. The findings highlight the importance of demographic and treatment factors in shaping microbial communities, providing valuable insights for potential biomarkers and personalized therapeutic approaches in AR management. This represents the first comprehensive analysis of nasal microbiome impact on AR severity using ARIA criteria in an Indian population.