{"title":"与血糖控制和 1 型糖尿病有关的肠道微生物群、血清代谢物和血脂。","authors":"Zhaohe Gu, Lanxin Pan, Huiling Tan, Xulin Wang, Jing Wang, Xueying Zheng, Jianping Weng, Sihui Luo, Tong Yue, Yu Ding","doi":"10.1111/1753-0407.70021","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>The composition and function of gut microbiota, lipids, and metabolites in patients with type 1 diabetes (T1D) or its association with glycemic control remains unknown. We aimed to use multi-omics sequencing technology and machine learning (ML) approaches to investigate potential function and relationships among the gut microbiota, lipids, and metabolites in T1D patients at varied glycemic levels.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>We conducted a multi-omics analysis of the gut microbiome from fecal samples, metabolites, and lipids obtained from serum samples, collected from a cohort of 72 T1D patients. The patients were divided into two groups based on their hemoglobin A1c (HbA1c) levels. 16S rRNA sequencing, and metabolomics methods were applied to analyze changes in composition and function of gut microbiota, metabolites, and lipids.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>The linear discriminant analysis, Shapley additive explanations (SHAP) algorithm, and ML algorithms revealed the enrichment of <i>Bacteroides_nordii, Bacteroides_cellulosilyticus</i> in the glycemic control (GC) group, while <i>Bacteroides_coprocola</i> and <i>Sutterella_wadsworthensis</i> were enriched in the poor glycemic control (PGC) group. Several metabolic enrichment sets like fatty acid biosynthesis and glycerol phosphate shuttle metabolism were different between two groups. <i>Bacteroides_nordii</i> exhibited a negative association with D-fructose, a component involved in the starch and sucrose metabolism pathway, as well as with monoglycerides (16:0) involved in the glycerolipid metabolism pathway.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>We identified distinct characteristics of gut microbiota, metabolites, and lipids in T1D patients exhibiting different levels of glycemic control. Through comprehensive analysis, microbiota (<i>Bacteroides_nordii</i>, <i>Bacteroides_coprocola</i>), metabolites (D-fructose), and lipids (Monoglycerides) may serve as potential mediators that communicated the interaction between the gut, circulatory systems, and glucose fluctuations in T1D patients.</p>\n \n <div>\n <figure>\n <div><picture>\n <source></source></picture><p></p>\n </div>\n </figure>\n </div>\n </section>\n </div>","PeriodicalId":189,"journal":{"name":"Journal of Diabetes","volume":"16 10","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2024-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70021","citationCount":"0","resultStr":"{\"title\":\"Gut microbiota, serum metabolites, and lipids related to blood glucose control and type 1 diabetes\",\"authors\":\"Zhaohe Gu, Lanxin Pan, Huiling Tan, Xulin Wang, Jing Wang, Xueying Zheng, Jianping Weng, Sihui Luo, Tong Yue, Yu Ding\",\"doi\":\"10.1111/1753-0407.70021\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>The composition and function of gut microbiota, lipids, and metabolites in patients with type 1 diabetes (T1D) or its association with glycemic control remains unknown. We aimed to use multi-omics sequencing technology and machine learning (ML) approaches to investigate potential function and relationships among the gut microbiota, lipids, and metabolites in T1D patients at varied glycemic levels.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>We conducted a multi-omics analysis of the gut microbiome from fecal samples, metabolites, and lipids obtained from serum samples, collected from a cohort of 72 T1D patients. The patients were divided into two groups based on their hemoglobin A1c (HbA1c) levels. 16S rRNA sequencing, and metabolomics methods were applied to analyze changes in composition and function of gut microbiota, metabolites, and lipids.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>The linear discriminant analysis, Shapley additive explanations (SHAP) algorithm, and ML algorithms revealed the enrichment of <i>Bacteroides_nordii, Bacteroides_cellulosilyticus</i> in the glycemic control (GC) group, while <i>Bacteroides_coprocola</i> and <i>Sutterella_wadsworthensis</i> were enriched in the poor glycemic control (PGC) group. Several metabolic enrichment sets like fatty acid biosynthesis and glycerol phosphate shuttle metabolism were different between two groups. <i>Bacteroides_nordii</i> exhibited a negative association with D-fructose, a component involved in the starch and sucrose metabolism pathway, as well as with monoglycerides (16:0) involved in the glycerolipid metabolism pathway.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusions</h3>\\n \\n <p>We identified distinct characteristics of gut microbiota, metabolites, and lipids in T1D patients exhibiting different levels of glycemic control. Through comprehensive analysis, microbiota (<i>Bacteroides_nordii</i>, <i>Bacteroides_coprocola</i>), metabolites (D-fructose), and lipids (Monoglycerides) may serve as potential mediators that communicated the interaction between the gut, circulatory systems, and glucose fluctuations in T1D patients.</p>\\n \\n <div>\\n <figure>\\n <div><picture>\\n <source></source></picture><p></p>\\n </div>\\n </figure>\\n </div>\\n </section>\\n </div>\",\"PeriodicalId\":189,\"journal\":{\"name\":\"Journal of Diabetes\",\"volume\":\"16 10\",\"pages\":\"\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-10-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1753-0407.70021\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Diabetes\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/1753-0407.70021\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Diabetes","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/1753-0407.70021","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
Gut microbiota, serum metabolites, and lipids related to blood glucose control and type 1 diabetes
Background
The composition and function of gut microbiota, lipids, and metabolites in patients with type 1 diabetes (T1D) or its association with glycemic control remains unknown. We aimed to use multi-omics sequencing technology and machine learning (ML) approaches to investigate potential function and relationships among the gut microbiota, lipids, and metabolites in T1D patients at varied glycemic levels.
Methods
We conducted a multi-omics analysis of the gut microbiome from fecal samples, metabolites, and lipids obtained from serum samples, collected from a cohort of 72 T1D patients. The patients were divided into two groups based on their hemoglobin A1c (HbA1c) levels. 16S rRNA sequencing, and metabolomics methods were applied to analyze changes in composition and function of gut microbiota, metabolites, and lipids.
Results
The linear discriminant analysis, Shapley additive explanations (SHAP) algorithm, and ML algorithms revealed the enrichment of Bacteroides_nordii, Bacteroides_cellulosilyticus in the glycemic control (GC) group, while Bacteroides_coprocola and Sutterella_wadsworthensis were enriched in the poor glycemic control (PGC) group. Several metabolic enrichment sets like fatty acid biosynthesis and glycerol phosphate shuttle metabolism were different between two groups. Bacteroides_nordii exhibited a negative association with D-fructose, a component involved in the starch and sucrose metabolism pathway, as well as with monoglycerides (16:0) involved in the glycerolipid metabolism pathway.
Conclusions
We identified distinct characteristics of gut microbiota, metabolites, and lipids in T1D patients exhibiting different levels of glycemic control. Through comprehensive analysis, microbiota (Bacteroides_nordii, Bacteroides_coprocola), metabolites (D-fructose), and lipids (Monoglycerides) may serve as potential mediators that communicated the interaction between the gut, circulatory systems, and glucose fluctuations in T1D patients.
期刊介绍：
Journal of Diabetes (JDB) devotes itself to diabetes research, therapeutics, and education. It aims to involve researchers and practitioners in a dialogue between East and West via all aspects of epidemiology, etiology, pathogenesis, management, complications and prevention of diabetes, including the molecular, biochemical, and physiological aspects of diabetes. The Editorial team is international with a unique mix of Asian and Western participation.
The Editors welcome submissions in form of original research articles, images, novel case reports and correspondence, and will solicit reviews, point-counterpoint, commentaries, editorials, news highlights, and educational content.
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