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A Diet‐Dependent Microbiota Profile Associated with Incident Type 2 Diabetes: From the CORDIOPREV Study
Author(s) -
Camargo Antonio,
ValsDelgado Cristina,
AlcalaDiaz Juan F.,
VillasantaGonzalez Alejandro,
GomezDelgado Francisco,
Haro Carmen,
LeonAcuña Ana,
Cardelo Magdalena P.,
TorresPeña Jose D.,
Guler Ipek,
Malagon Maria M.,
Ordovas Jose M.,
PerezMartinez Pablo,
DelgadoLista Javier,
LopezMiranda Jose
Publication year - 2020
Publication title -
molecular nutrition and food research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.495
H-Index - 131
eISSN - 1613-4133
pISSN - 1613-4125
DOI - 10.1002/mnfr.202000730
Subject(s) - type 2 diabetes , gammaproteobacteria , gut flora , biology , microbiome , prevotella , feces , diabetes mellitus , mediterranean diet , physiology , medicine , endocrinology , bioinformatics , immunology , microbiology and biotechnology , 16s ribosomal rna , genetics , bacteria
Scope The differences between the baseline gut microbiota of patients who developed type 2 diabetes (T2D) consuming a low‐fat (LF) or a Mediterranean (Med) diet are explored and risk scores are developed to predict the individual risk of developing T2D associated with the consumption of LF or Med diet. Methods and Results All the patients from the CORDIOPREV study without T2D at baseline ( n = 462) whose fecal sample are available, are included. Gut microbiota is analyzed by 16S sequencing and the risk of T2D after a median follow‐up of 60 months assessed by Cox analysis. Linear discriminant analysis effect size (LEfSe) analysis shows a different baseline gut microbiota in patients who developed T2D consuming LF and Med diets. A higher abundance of Paraprevotella , and lower Gammaproteobacteria and B. uniformis are associated with T2D risk when an LF diet is consumed. In contrast, higher abundances of Saccharibacteria , Betaproteobacteria , and Prevotella are associated with T2D risk when a Med diet is consumed. Conclusion The results suggest that different interactions between the microbiome and dietary patterns may partially determine the risk of T2D development, which may be used for selecting personalized dietary models to prevent T2D.