Exploring the characteristics of gut microbiome in patients of Southern Fujian with hypocitraturia urolithiasis and constructing clinical diagnostic models

Purpose Hypocitraturia is an important cause of urolithiasis. Exploring the characteristics of the gut microbiome (GMB) of hypocitriuria urolithiasis (HCU) patients can provide new ideas for the treatment and prevention of urolithiasis. Methods The 24 h urinary citric acid excretion of 19 urolithias...

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Veröffentlicht in:International urology and nephrology 2023-08, Vol.55 (8), p.1917-1929
Hauptverfasser: Wang, Jialiang, Chen, Guofeng, Chen, Heyi, Chen, Jiabi, Su, Qingfu, Zhuang, Wei
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container_issue 8
container_start_page 1917
container_title International urology and nephrology
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creator Wang, Jialiang
Chen, Guofeng
Chen, Heyi
Chen, Jiabi
Su, Qingfu
Zhuang, Wei
description Purpose Hypocitraturia is an important cause of urolithiasis. Exploring the characteristics of the gut microbiome (GMB) of hypocitriuria urolithiasis (HCU) patients can provide new ideas for the treatment and prevention of urolithiasis. Methods The 24 h urinary citric acid excretion of 19 urolithiasis patients was measured, and patients were divided into the HCU group and the normal citrate urolithiasis (NCU) group. The 16 s ribosomal RNA (rRNA) was used to detect GMB composition differences and construct operational taxonomic units (OTUs) coexistence networks. The key bacterial community was determined by Lefse analysis, Metastats analysis and RandomForest analysis. Redundancy analysis (RDA) and Pearson correlation analysis visualized the correlation between key OTUs and clinical features and then established the disease diagnosis model of microbial-clinical indicators. Finally, PICRUSt2 was used to explore the metabolic pathway of related GMB in HCU patients. Results The alpha diversity of GMB in HCU group was increased and Beta diversity analysis suggested significant differences between HCU and NCU groups, which was related to renal function damage and urinary tract infection. Ruminococcaceae_ge and Turicibacter are the characteristic bacterial groups of HCU. Correlation analysis showed that the characteristic bacterial groups were significantly associated with various clinical features. Based on this, the diagnostic models of microbiome-clinical indicators in HCU patients were constructed with the areas under the curve (AUC) of 0.923 and 0.897, respectively. Genetic and metabolic processes of HCU are affected by changes in GMB abundance. Conclusion GMB disorder may be involved in the occurrence and clinical characteristics of HCU by influencing genetic and metabolic pathways. The new microbiome-clinical indicator diagnostic model is effective.
doi_str_mv 10.1007/s11255-023-03662-6
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Exploring the characteristics of the gut microbiome (GMB) of hypocitriuria urolithiasis (HCU) patients can provide new ideas for the treatment and prevention of urolithiasis. Methods The 24 h urinary citric acid excretion of 19 urolithiasis patients was measured, and patients were divided into the HCU group and the normal citrate urolithiasis (NCU) group. The 16 s ribosomal RNA (rRNA) was used to detect GMB composition differences and construct operational taxonomic units (OTUs) coexistence networks. The key bacterial community was determined by Lefse analysis, Metastats analysis and RandomForest analysis. Redundancy analysis (RDA) and Pearson correlation analysis visualized the correlation between key OTUs and clinical features and then established the disease diagnosis model of microbial-clinical indicators. Finally, PICRUSt2 was used to explore the metabolic pathway of related GMB in HCU patients. Results The alpha diversity of GMB in HCU group was increased and Beta diversity analysis suggested significant differences between HCU and NCU groups, which was related to renal function damage and urinary tract infection. Ruminococcaceae_ge and Turicibacter are the characteristic bacterial groups of HCU. Correlation analysis showed that the characteristic bacterial groups were significantly associated with various clinical features. Based on this, the diagnostic models of microbiome-clinical indicators in HCU patients were constructed with the areas under the curve (AUC) of 0.923 and 0.897, respectively. Genetic and metabolic processes of HCU are affected by changes in GMB abundance. Conclusion GMB disorder may be involved in the occurrence and clinical characteristics of HCU by influencing genetic and metabolic pathways. The new microbiome-clinical indicator diagnostic model is effective.</description><identifier>ISSN: 1573-2584</identifier><identifier>ISSN: 0301-1623</identifier><identifier>EISSN: 1573-2584</identifier><identifier>DOI: 10.1007/s11255-023-03662-6</identifier><identifier>PMID: 37294502</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Bacteria ; Bacteria - genetics ; Citrates ; Citric Acid ; Coexistence ; Correlation analysis ; Digestive system ; Gastrointestinal Microbiome - genetics ; Humans ; Intestinal microflora ; Lithiasis ; Medicine ; Medicine &amp; Public Health ; Metabolic pathways ; Metabolism ; Microbiomes ; Microbiota ; Nephrology ; Patients ; Renal function ; rRNA ; Urinary tract ; Urinary tract diseases ; Urinary Tract Infections - complications ; Urolithiasis - complications ; Urology ; Urology - Original Paper</subject><ispartof>International urology and nephrology, 2023-08, Vol.55 (8), p.1917-1929</ispartof><rights>The Author(s), under exclusive licence to Springer Nature B.V. 2023. 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Exploring the characteristics of the gut microbiome (GMB) of hypocitriuria urolithiasis (HCU) patients can provide new ideas for the treatment and prevention of urolithiasis. Methods The 24 h urinary citric acid excretion of 19 urolithiasis patients was measured, and patients were divided into the HCU group and the normal citrate urolithiasis (NCU) group. The 16 s ribosomal RNA (rRNA) was used to detect GMB composition differences and construct operational taxonomic units (OTUs) coexistence networks. The key bacterial community was determined by Lefse analysis, Metastats analysis and RandomForest analysis. Redundancy analysis (RDA) and Pearson correlation analysis visualized the correlation between key OTUs and clinical features and then established the disease diagnosis model of microbial-clinical indicators. Finally, PICRUSt2 was used to explore the metabolic pathway of related GMB in HCU patients. Results The alpha diversity of GMB in HCU group was increased and Beta diversity analysis suggested significant differences between HCU and NCU groups, which was related to renal function damage and urinary tract infection. Ruminococcaceae_ge and Turicibacter are the characteristic bacterial groups of HCU. Correlation analysis showed that the characteristic bacterial groups were significantly associated with various clinical features. Based on this, the diagnostic models of microbiome-clinical indicators in HCU patients were constructed with the areas under the curve (AUC) of 0.923 and 0.897, respectively. Genetic and metabolic processes of HCU are affected by changes in GMB abundance. Conclusion GMB disorder may be involved in the occurrence and clinical characteristics of HCU by influencing genetic and metabolic pathways. 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Exploring the characteristics of the gut microbiome (GMB) of hypocitriuria urolithiasis (HCU) patients can provide new ideas for the treatment and prevention of urolithiasis. Methods The 24 h urinary citric acid excretion of 19 urolithiasis patients was measured, and patients were divided into the HCU group and the normal citrate urolithiasis (NCU) group. The 16 s ribosomal RNA (rRNA) was used to detect GMB composition differences and construct operational taxonomic units (OTUs) coexistence networks. The key bacterial community was determined by Lefse analysis, Metastats analysis and RandomForest analysis. Redundancy analysis (RDA) and Pearson correlation analysis visualized the correlation between key OTUs and clinical features and then established the disease diagnosis model of microbial-clinical indicators. Finally, PICRUSt2 was used to explore the metabolic pathway of related GMB in HCU patients. Results The alpha diversity of GMB in HCU group was increased and Beta diversity analysis suggested significant differences between HCU and NCU groups, which was related to renal function damage and urinary tract infection. Ruminococcaceae_ge and Turicibacter are the characteristic bacterial groups of HCU. Correlation analysis showed that the characteristic bacterial groups were significantly associated with various clinical features. Based on this, the diagnostic models of microbiome-clinical indicators in HCU patients were constructed with the areas under the curve (AUC) of 0.923 and 0.897, respectively. Genetic and metabolic processes of HCU are affected by changes in GMB abundance. Conclusion GMB disorder may be involved in the occurrence and clinical characteristics of HCU by influencing genetic and metabolic pathways. The new microbiome-clinical indicator diagnostic model is effective.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><pmid>37294502</pmid><doi>10.1007/s11255-023-03662-6</doi><tpages>13</tpages><orcidid>https://orcid.org/0009-0008-9907-1576</orcidid></addata></record>
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subjects Bacteria
Bacteria - genetics
Citrates
Citric Acid
Coexistence
Correlation analysis
Digestive system
Gastrointestinal Microbiome - genetics
Humans
Intestinal microflora
Lithiasis
Medicine
Medicine & Public Health
Metabolic pathways
Metabolism
Microbiomes
Microbiota
Nephrology
Patients
Renal function
rRNA
Urinary tract
Urinary tract diseases
Urinary Tract Infections - complications
Urolithiasis - complications
Urology
Urology - Original Paper
title Exploring the characteristics of gut microbiome in patients of Southern Fujian with hypocitraturia urolithiasis and constructing clinical diagnostic models
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