16S rRNA sequencing-based evaluation of the protective effects of key gut microbiota on inhaled allergen-induced allergic rhinitis
Allergic rhinitis (AR) is a common respiratory disorder influenced by various factors in its pathogenesis. Recent studies have begun to emphasize the significant role of gut microbiota in immune modulation and its potential association with the development of AR. This research aims to characterize t...
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Published in | Frontiers in microbiology Vol. 15; p. 1497262 |
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Language | English |
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DOI | 10.3389/fmicb.2024.1497262 |
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Abstract | Allergic rhinitis (AR) is a common respiratory disorder influenced by various factors in its pathogenesis. Recent studies have begun to emphasize the significant role of gut microbiota in immune modulation and its potential association with the development of AR. This research aims to characterize the gut microbiota of patients with AR who are sensitized via inhalation, utilizing 16S rRNA sequencing to shed light on the pathogenesis of AR and identify potential therapeutic targets.
To achieve the study's objectives, we compared the microbiota profiles between patients with AR and healthy controls. Microbial diversity was assessed using alpha and beta diversity indices, and differential microbiota populations were identified through Linear discriminant analysis Effect Size (LEfSe) analysis. A Least Absolute Shrinkage and Selection Operator (LASSO) regression model was employed to pinpoint key species. Additionally, PICRUSt2 was utilized to predict the functional pathways associated with these identified species.
The analysis identified a total of 1,122 common species, along with 1,803 species associated with AR and 1,739 species associated with healthy controls. LEfSe analysis revealed 20 significant discrepancies at the genus level. The LASSO regression model identified 8 key genera, including
UCG-004 and
, which exhibited AUC values exceeding 0.7, indicating strong diagnostic potential. Furthermore, functional pathway analysis suggested that these pivotal species are involved in pathways such as L-lysine biosynthesis and photorespiration, potentially contributing to the pathogenesis of AR.
This study identifies critical gut microbiota that could serve as potential biomarkers for allergic rhinitis, providing new insights into its pathogenesis and offering avenues for future therapeutic strategies. Further investigation into these microbiota may lead to enhanced understanding and management of AR. |
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AbstractList | Allergic rhinitis (AR) is a common respiratory disorder influenced by various factors in its pathogenesis. Recent studies have begun to emphasize the significant role of gut microbiota in immune modulation and its potential association with the development of AR. This research aims to characterize the gut microbiota of patients with AR who are sensitized via inhalation, utilizing 16S rRNA sequencing to shed light on the pathogenesis of AR and identify potential therapeutic targets.
To achieve the study's objectives, we compared the microbiota profiles between patients with AR and healthy controls. Microbial diversity was assessed using alpha and beta diversity indices, and differential microbiota populations were identified through Linear discriminant analysis Effect Size (LEfSe) analysis. A Least Absolute Shrinkage and Selection Operator (LASSO) regression model was employed to pinpoint key species. Additionally, PICRUSt2 was utilized to predict the functional pathways associated with these identified species.
The analysis identified a total of 1,122 common species, along with 1,803 species associated with AR and 1,739 species associated with healthy controls. LEfSe analysis revealed 20 significant discrepancies at the genus level. The LASSO regression model identified 8 key genera, including
UCG-004 and
, which exhibited AUC values exceeding 0.7, indicating strong diagnostic potential. Furthermore, functional pathway analysis suggested that these pivotal species are involved in pathways such as L-lysine biosynthesis and photorespiration, potentially contributing to the pathogenesis of AR.
This study identifies critical gut microbiota that could serve as potential biomarkers for allergic rhinitis, providing new insights into its pathogenesis and offering avenues for future therapeutic strategies. Further investigation into these microbiota may lead to enhanced understanding and management of AR. IntroductionAllergic rhinitis (AR) is a common respiratory disorder influenced by various factors in its pathogenesis. Recent studies have begun to emphasize the significant role of gut microbiota in immune modulation and its potential association with the development of AR. This research aims to characterize the gut microbiota of patients with AR who are sensitized via inhalation, utilizing 16S rRNA sequencing to shed light on the pathogenesis of AR and identify potential therapeutic targets.MethodsTo achieve the study’s objectives, we compared the microbiota profiles between patients with AR and healthy controls. Microbial diversity was assessed using alpha and beta diversity indices, and differential microbiota populations were identified through Linear discriminant analysis Effect Size (LEfSe) analysis. A Least Absolute Shrinkage and Selection Operator (LASSO) regression model was employed to pinpoint key species. Additionally, PICRUSt2 was utilized to predict the functional pathways associated with these identified species.ResultsThe analysis identified a total of 1,122 common species, along with 1,803 species associated with AR and 1,739 species associated with healthy controls. LEfSe analysis revealed 20 significant discrepancies at the genus level. The LASSO regression model identified 8 key genera, including Prevotellaceae UCG-004 and Rhodococcus, which exhibited AUC values exceeding 0.7, indicating strong diagnostic potential. Furthermore, functional pathway analysis suggested that these pivotal species are involved in pathways such as L-lysine biosynthesis and photorespiration, potentially contributing to the pathogenesis of AR.DiscussionThis study identifies critical gut microbiota that could serve as potential biomarkers for allergic rhinitis, providing new insights into its pathogenesis and offering avenues for future therapeutic strategies. Further investigation into these microbiota may lead to enhanced understanding and management of AR. Allergic rhinitis (AR) is a common respiratory disorder influenced by various factors in its pathogenesis. Recent studies have begun to emphasize the significant role of gut microbiota in immune modulation and its potential association with the development of AR. This research aims to characterize the gut microbiota of patients with AR who are sensitized via inhalation, utilizing 16S rRNA sequencing to shed light on the pathogenesis of AR and identify potential therapeutic targets.IntroductionAllergic rhinitis (AR) is a common respiratory disorder influenced by various factors in its pathogenesis. Recent studies have begun to emphasize the significant role of gut microbiota in immune modulation and its potential association with the development of AR. This research aims to characterize the gut microbiota of patients with AR who are sensitized via inhalation, utilizing 16S rRNA sequencing to shed light on the pathogenesis of AR and identify potential therapeutic targets.To achieve the study's objectives, we compared the microbiota profiles between patients with AR and healthy controls. Microbial diversity was assessed using alpha and beta diversity indices, and differential microbiota populations were identified through Linear discriminant analysis Effect Size (LEfSe) analysis. A Least Absolute Shrinkage and Selection Operator (LASSO) regression model was employed to pinpoint key species. Additionally, PICRUSt2 was utilized to predict the functional pathways associated with these identified species.MethodsTo achieve the study's objectives, we compared the microbiota profiles between patients with AR and healthy controls. Microbial diversity was assessed using alpha and beta diversity indices, and differential microbiota populations were identified through Linear discriminant analysis Effect Size (LEfSe) analysis. A Least Absolute Shrinkage and Selection Operator (LASSO) regression model was employed to pinpoint key species. Additionally, PICRUSt2 was utilized to predict the functional pathways associated with these identified species.The analysis identified a total of 1,122 common species, along with 1,803 species associated with AR and 1,739 species associated with healthy controls. LEfSe analysis revealed 20 significant discrepancies at the genus level. The LASSO regression model identified 8 key genera, including Prevotellaceae UCG-004 and Rhodococcus, which exhibited AUC values exceeding 0.7, indicating strong diagnostic potential. Furthermore, functional pathway analysis suggested that these pivotal species are involved in pathways such as L-lysine biosynthesis and photorespiration, potentially contributing to the pathogenesis of AR.ResultsThe analysis identified a total of 1,122 common species, along with 1,803 species associated with AR and 1,739 species associated with healthy controls. LEfSe analysis revealed 20 significant discrepancies at the genus level. The LASSO regression model identified 8 key genera, including Prevotellaceae UCG-004 and Rhodococcus, which exhibited AUC values exceeding 0.7, indicating strong diagnostic potential. Furthermore, functional pathway analysis suggested that these pivotal species are involved in pathways such as L-lysine biosynthesis and photorespiration, potentially contributing to the pathogenesis of AR.This study identifies critical gut microbiota that could serve as potential biomarkers for allergic rhinitis, providing new insights into its pathogenesis and offering avenues for future therapeutic strategies. Further investigation into these microbiota may lead to enhanced understanding and management of AR.DiscussionThis study identifies critical gut microbiota that could serve as potential biomarkers for allergic rhinitis, providing new insights into its pathogenesis and offering avenues for future therapeutic strategies. Further investigation into these microbiota may lead to enhanced understanding and management of AR. |
Author | Chen, Danping Zhou, Yibo Liu, Zhai Xie, Dan She, Yongchuan Tang, Yi |
AuthorAffiliation | Changsha Hospital of Traditional Chinese Medicine (Changsha Eighth Hospital) , Changsha , China |
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Cites_doi | 10.1016/j.jaci.2019.06.049 10.1038/s41564-022-01301-x 10.1098/rstb.1994.0091 10.1111/all.14586 10.1016/j.chom.2019.07.008 10.1159/000510536 10.1038/nmeth.3869 10.1038/nbt.2676 10.5217/ir.2019.00108 10.1159/000515352 10.3390/molecules26164871 10.1016/j.envres.2021.112472 10.3390/ijms20081835 10.1097/mib.0000000000000382 10.1186/1471-2105-12-77 10.1136/bmjopen-2019-031339 10.1002/alr.23090 10.1038/cti.2016.29 10.1128/mSystems.00013-15 10.3389/fmicb.2022.978940 10.1080/09168451.2019.1654847 10.1128/spectrum.01676-22 10.1016/j.alit.2017.06.008 10.1186/gb-2011-12-6-r60 10.3390/nu14204328 10.1038/s41572-020-00227-0 10.3389/fimmu.2018.01584 |
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Keywords | microbiota diagnosis fresh feces allergic rhinitis 16S rRNA sequencing |
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Snippet | Allergic rhinitis (AR) is a common respiratory disorder influenced by various factors in its pathogenesis. Recent studies have begun to emphasize the... IntroductionAllergic rhinitis (AR) is a common respiratory disorder influenced by various factors in its pathogenesis. Recent studies have begun to emphasize... |
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SubjectTerms | 16S rRNA sequencing allergic rhinitis diagnosis fresh feces Microbiology microbiota |
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Title | 16S rRNA sequencing-based evaluation of the protective effects of key gut microbiota on inhaled allergen-induced allergic rhinitis |
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