Development and validation of diagnostic models for immunoglobulin A nephropathy based on gut microbes
BackgroundImmunoglobulin A nephropathy (IgAN) is a highly prevalent glomerular disease. The diagnosis potential of the gut microbiome in IgAN has not been fully evaluated. Gut microbiota, serum metabolites, and clinical phenotype help to further deepen the understanding of IgAN.Patients and methodsC...
| Main Authors: | , , , , , |
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| Format: | Article |
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Frontiers Media S.A.
2022-12-01
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| Series: | Frontiers in Cellular and Infection Microbiology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fcimb.2022.1059692/full |
| _version_ | 1811301089324040192 |
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| author | Yijun Dong Yijun Dong Jiaojiao Chen Jiaojiao Chen Yiding Zhang Yiding Zhang Zhihui Wang Zhihui Wang Jin Shang Jin Shang Jin Shang Zhanzheng Zhao Zhanzheng Zhao Zhanzheng Zhao |
| author_facet | Yijun Dong Yijun Dong Jiaojiao Chen Jiaojiao Chen Yiding Zhang Yiding Zhang Zhihui Wang Zhihui Wang Jin Shang Jin Shang Jin Shang Zhanzheng Zhao Zhanzheng Zhao Zhanzheng Zhao |
| author_sort | Yijun Dong |
| collection | DOAJ |
| description | BackgroundImmunoglobulin A nephropathy (IgAN) is a highly prevalent glomerular disease. The diagnosis potential of the gut microbiome in IgAN has not been fully evaluated. Gut microbiota, serum metabolites, and clinical phenotype help to further deepen the understanding of IgAN.Patients and methodsCohort studies were conducted in healthy controls (HC), patients of IgA nephropathy (IgAN) and non-IgA nephropathy (n_IgAN). We used 16S rRNA to measure bacterial flora and non-targeted analysis methods to measure metabolomics; we then compared the differences in the gut microbiota between each group. The random forest method was used to explore the non-invasive diagnostic value of the gut microbiome in IgAN. We also compared serum metabolites and analyzed their correlation with the gut microbiome.ResultsThe richness and diversity of gut microbiota were significantly different among IgAN, n_IgAN and HC patients. Using a random approach, we constructed the diagnosis model and analysed the differentiation between IgAN and n_IgAN based on gut microbiota. The area under the receiver operating characteristic curve for the diagnosis was 0.9899. The metabolic analysis showed that IgAN patients had significant metabolic differences compared with HCs. In IgAN, catechol, l-tryptophan, (1H-Indol-3-yl)-N-methylmethanamine, and pimelic acid were found to be enriched. In the correlation analysis, l-tryptophan, blood urea nitrogen and Eubacterium coprostanoligenes were positively correlated with each other.ConclusionOur study demonstrated changes in the gut microbiota and established models for the non-invasive diagnosis of IgAN from HC and n_IgAN. We further demonstrated a close correlation between the gut flora, metabolites, and clinical phenotypes of IgAN. These findings provide further directions and clues in the study of the mechanism of IgAN. |
| first_indexed | 2024-04-13T07:02:34Z |
| format | Article |
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| institution | Directory Open Access Journal |
| issn | 2235-2988 |
| language | English |
| last_indexed | 2024-04-13T07:02:34Z |
| publishDate | 2022-12-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Cellular and Infection Microbiology |
| spelling | doaj.art-cd21b40aca3244319ae16cf64e8cf0af2022-12-22T02:57:05ZengFrontiers Media S.A.Frontiers in Cellular and Infection Microbiology2235-29882022-12-011210.3389/fcimb.2022.10596921059692Development and validation of diagnostic models for immunoglobulin A nephropathy based on gut microbesYijun Dong0Yijun Dong1Jiaojiao Chen2Jiaojiao Chen3Yiding Zhang4Yiding Zhang5Zhihui Wang6Zhihui Wang7Jin Shang8Jin Shang9Jin Shang10Zhanzheng Zhao11Zhanzheng Zhao12Zhanzheng Zhao13Department of Nephrology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaSchool of Medicine, Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Nephrology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaSchool of Medicine, Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Nephrology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaSchool of Medicine, Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Nephrology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaSchool of Medicine, Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Nephrology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaNephrology Laboratory, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaLaboratory Animal Platform of Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, ChinaDepartment of Nephrology, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaNephrology Laboratory, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, ChinaLaboratory Animal Platform of Academy of Medical Sciences, Zhengzhou University, Zhengzhou, Henan, ChinaBackgroundImmunoglobulin A nephropathy (IgAN) is a highly prevalent glomerular disease. The diagnosis potential of the gut microbiome in IgAN has not been fully evaluated. Gut microbiota, serum metabolites, and clinical phenotype help to further deepen the understanding of IgAN.Patients and methodsCohort studies were conducted in healthy controls (HC), patients of IgA nephropathy (IgAN) and non-IgA nephropathy (n_IgAN). We used 16S rRNA to measure bacterial flora and non-targeted analysis methods to measure metabolomics; we then compared the differences in the gut microbiota between each group. The random forest method was used to explore the non-invasive diagnostic value of the gut microbiome in IgAN. We also compared serum metabolites and analyzed their correlation with the gut microbiome.ResultsThe richness and diversity of gut microbiota were significantly different among IgAN, n_IgAN and HC patients. Using a random approach, we constructed the diagnosis model and analysed the differentiation between IgAN and n_IgAN based on gut microbiota. The area under the receiver operating characteristic curve for the diagnosis was 0.9899. The metabolic analysis showed that IgAN patients had significant metabolic differences compared with HCs. In IgAN, catechol, l-tryptophan, (1H-Indol-3-yl)-N-methylmethanamine, and pimelic acid were found to be enriched. In the correlation analysis, l-tryptophan, blood urea nitrogen and Eubacterium coprostanoligenes were positively correlated with each other.ConclusionOur study demonstrated changes in the gut microbiota and established models for the non-invasive diagnosis of IgAN from HC and n_IgAN. We further demonstrated a close correlation between the gut flora, metabolites, and clinical phenotypes of IgAN. These findings provide further directions and clues in the study of the mechanism of IgAN.https://www.frontiersin.org/articles/10.3389/fcimb.2022.1059692/fullglomerulonephritisIgAchronic kidney diseasegut microbiomenon‐invasive diagnostic toolsmetabolic networks |
| spellingShingle | Yijun Dong Yijun Dong Jiaojiao Chen Jiaojiao Chen Yiding Zhang Yiding Zhang Zhihui Wang Zhihui Wang Jin Shang Jin Shang Jin Shang Zhanzheng Zhao Zhanzheng Zhao Zhanzheng Zhao Development and validation of diagnostic models for immunoglobulin A nephropathy based on gut microbes Frontiers in Cellular and Infection Microbiology glomerulonephritis IgA chronic kidney disease gut microbiome non‐invasive diagnostic tools metabolic networks |
| title | Development and validation of diagnostic models for immunoglobulin A nephropathy based on gut microbes |
| title_full | Development and validation of diagnostic models for immunoglobulin A nephropathy based on gut microbes |
| title_fullStr | Development and validation of diagnostic models for immunoglobulin A nephropathy based on gut microbes |
| title_full_unstemmed | Development and validation of diagnostic models for immunoglobulin A nephropathy based on gut microbes |
| title_short | Development and validation of diagnostic models for immunoglobulin A nephropathy based on gut microbes |
| title_sort | development and validation of diagnostic models for immunoglobulin a nephropathy based on gut microbes |
| topic | glomerulonephritis IgA chronic kidney disease gut microbiome non‐invasive diagnostic tools metabolic networks |
| url | https://www.frontiersin.org/articles/10.3389/fcimb.2022.1059692/full |
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