Gemma Llauradó, Lídia Cedó, Elisenda Climent, Joan Badia, Gemma Rojo-Martínez, Juana Flores-Le Roux, Oscar Yanes, Maria Vinaixa, Minerva Granado-Casas, Didac Mauricio, Sonia Fernández-Veledo, Joan Vendrell
{"title":"循环短链脂肪酸和地中海食物模式。预测2型糖尿病风险的潜在作用:Di@bet.es研究。","authors":"Gemma Llauradó, Lídia Cedó, Elisenda Climent, Joan Badia, Gemma Rojo-Martínez, Juana Flores-Le Roux, Oscar Yanes, Maria Vinaixa, Minerva Granado-Casas, Didac Mauricio, Sonia Fernández-Veledo, Joan Vendrell","doi":"10.1186/s12916-025-04186-9","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Identifying nutritional patterns associated with developing type 2 diabetes (T2D) can facilitate more effective and personalized dietary interventions. Short-chain fatty acids (SCFAs), key metabolites derived from gut microbiota, are produced through the anaerobic fermentation of dietary fibers. This study aimed to evaluate whether circulating concentrations of SCFAs are associated with specific food consumption patterns and to assess their association with T2D development in at-risk subjects within a prospective cohort (The Di@bet.es Study).</p><p><strong>Methods: </strong>The Di@bet.es study is a prospective, population-based study utilizing random cluster sampling from the Spanish population aged over 18 years (n = 5,072). Among these participants, 4,347 were free of T2D at baseline. Follow-up losses were approximately 45%, resulting in a final re-screened sample of 2,408 subjects. A qualitative food frequency questionnaire evaluated Mediterranean diet (MedDiet) adherence and high-fiber food consumption. The risk of developing T2D was assessed using the FINDRISK. Metabolomics-driven analyses of SCFAs were conducted using gas chromatography-mass spectrometry.</p><p><strong>Results: </strong>Subjects who developed T2D after a median follow-up of seven years had higher baseline circulating concentrations of butyrate and isobutyrate. Circulating concentrations of SCFAs were associated with high-fiber food consumption at baseline. In multivariate analysis, baseline circulating concentrations of butyrate and isobutyrate were independently associated with incident T2D after adjusting for traditional clinical factors. The C-statistics for predicting T2D were 0.847 (95%CI:0.816-0.877) for butyrate and 0.843 (95%CI:0.812-0.875) for isobutyrate in adjusted models, similar to the reference model based on traditional clinical factors (0.840 [95%CI: 0.807-0.873]). Both models improved risk prediction compared to FINDRISK. Dietary patterns did not add predictive value. Sensitivity analysis excluding subjects with prediabetes at baseline confirmed these results. In addition, an association between baseline consumption of high-fiber foods with incident T2D emerged, suggesting a different behaviour between healthy and prediabetic subjects.</p><p><strong>Conclusions: </strong>Baseline circulating concentrations of SCFAs are associated with high-fiber food consumption and independently predict the development of T2D over seven years of follow-up. However, they offer limited improvement in risk prediction compared to traditional risk factors, though they enhance risk prediction as assessed by FINDRISK. Further studies are necessary to evaluate the impact of dietary interventions on SCFA.</p>","PeriodicalId":9188,"journal":{"name":"BMC Medicine","volume":"23 1","pages":"337"},"PeriodicalIF":7.0000,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12143092/pdf/","citationCount":"0","resultStr":"{\"title\":\"Circulating short-chain fatty acids and Mediterranean food patterns. A potential role for the prediction of type 2 diabetes risk: The Di@bet.es Study.\",\"authors\":\"Gemma Llauradó, Lídia Cedó, Elisenda Climent, Joan Badia, Gemma Rojo-Martínez, Juana Flores-Le Roux, Oscar Yanes, Maria Vinaixa, Minerva Granado-Casas, Didac Mauricio, Sonia Fernández-Veledo, Joan Vendrell\",\"doi\":\"10.1186/s12916-025-04186-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Identifying nutritional patterns associated with developing type 2 diabetes (T2D) can facilitate more effective and personalized dietary interventions. Short-chain fatty acids (SCFAs), key metabolites derived from gut microbiota, are produced through the anaerobic fermentation of dietary fibers. This study aimed to evaluate whether circulating concentrations of SCFAs are associated with specific food consumption patterns and to assess their association with T2D development in at-risk subjects within a prospective cohort (The Di@bet.es Study).</p><p><strong>Methods: </strong>The Di@bet.es study is a prospective, population-based study utilizing random cluster sampling from the Spanish population aged over 18 years (n = 5,072). Among these participants, 4,347 were free of T2D at baseline. Follow-up losses were approximately 45%, resulting in a final re-screened sample of 2,408 subjects. A qualitative food frequency questionnaire evaluated Mediterranean diet (MedDiet) adherence and high-fiber food consumption. The risk of developing T2D was assessed using the FINDRISK. Metabolomics-driven analyses of SCFAs were conducted using gas chromatography-mass spectrometry.</p><p><strong>Results: </strong>Subjects who developed T2D after a median follow-up of seven years had higher baseline circulating concentrations of butyrate and isobutyrate. Circulating concentrations of SCFAs were associated with high-fiber food consumption at baseline. In multivariate analysis, baseline circulating concentrations of butyrate and isobutyrate were independently associated with incident T2D after adjusting for traditional clinical factors. The C-statistics for predicting T2D were 0.847 (95%CI:0.816-0.877) for butyrate and 0.843 (95%CI:0.812-0.875) for isobutyrate in adjusted models, similar to the reference model based on traditional clinical factors (0.840 [95%CI: 0.807-0.873]). Both models improved risk prediction compared to FINDRISK. Dietary patterns did not add predictive value. Sensitivity analysis excluding subjects with prediabetes at baseline confirmed these results. In addition, an association between baseline consumption of high-fiber foods with incident T2D emerged, suggesting a different behaviour between healthy and prediabetic subjects.</p><p><strong>Conclusions: </strong>Baseline circulating concentrations of SCFAs are associated with high-fiber food consumption and independently predict the development of T2D over seven years of follow-up. However, they offer limited improvement in risk prediction compared to traditional risk factors, though they enhance risk prediction as assessed by FINDRISK. 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Circulating short-chain fatty acids and Mediterranean food patterns. A potential role for the prediction of type 2 diabetes risk: The Di@bet.es Study.
Background: Identifying nutritional patterns associated with developing type 2 diabetes (T2D) can facilitate more effective and personalized dietary interventions. Short-chain fatty acids (SCFAs), key metabolites derived from gut microbiota, are produced through the anaerobic fermentation of dietary fibers. This study aimed to evaluate whether circulating concentrations of SCFAs are associated with specific food consumption patterns and to assess their association with T2D development in at-risk subjects within a prospective cohort (The Di@bet.es Study).
Methods: The Di@bet.es study is a prospective, population-based study utilizing random cluster sampling from the Spanish population aged over 18 years (n = 5,072). Among these participants, 4,347 were free of T2D at baseline. Follow-up losses were approximately 45%, resulting in a final re-screened sample of 2,408 subjects. A qualitative food frequency questionnaire evaluated Mediterranean diet (MedDiet) adherence and high-fiber food consumption. The risk of developing T2D was assessed using the FINDRISK. Metabolomics-driven analyses of SCFAs were conducted using gas chromatography-mass spectrometry.
Results: Subjects who developed T2D after a median follow-up of seven years had higher baseline circulating concentrations of butyrate and isobutyrate. Circulating concentrations of SCFAs were associated with high-fiber food consumption at baseline. In multivariate analysis, baseline circulating concentrations of butyrate and isobutyrate were independently associated with incident T2D after adjusting for traditional clinical factors. The C-statistics for predicting T2D were 0.847 (95%CI:0.816-0.877) for butyrate and 0.843 (95%CI:0.812-0.875) for isobutyrate in adjusted models, similar to the reference model based on traditional clinical factors (0.840 [95%CI: 0.807-0.873]). Both models improved risk prediction compared to FINDRISK. Dietary patterns did not add predictive value. Sensitivity analysis excluding subjects with prediabetes at baseline confirmed these results. In addition, an association between baseline consumption of high-fiber foods with incident T2D emerged, suggesting a different behaviour between healthy and prediabetic subjects.
Conclusions: Baseline circulating concentrations of SCFAs are associated with high-fiber food consumption and independently predict the development of T2D over seven years of follow-up. However, they offer limited improvement in risk prediction compared to traditional risk factors, though they enhance risk prediction as assessed by FINDRISK. Further studies are necessary to evaluate the impact of dietary interventions on SCFA.
期刊介绍:
BMC Medicine is an open access, transparent peer-reviewed general medical journal. It is the flagship journal of the BMC series and publishes outstanding and influential research in various areas including clinical practice, translational medicine, medical and health advances, public health, global health, policy, and general topics of interest to the biomedical and sociomedical professional communities. In addition to research articles, the journal also publishes stimulating debates, reviews, unique forum articles, and concise tutorials. All articles published in BMC Medicine are included in various databases such as Biological Abstracts, BIOSIS, CAS, Citebase, Current contents, DOAJ, Embase, MEDLINE, PubMed, Science Citation Index Expanded, OAIster, SCImago, Scopus, SOCOLAR, and Zetoc.