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GUT MICROBIOTA AND TYPE 2 DIABETES ASSOCIATIONS: A META-ANALYSIS OF 16S STUDIES AND THEIR METHODOLOGICAL CHALLENGES
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Fundação Oswaldo Cruz. Instituto René Rachou. Grupo de Genomica e Informatica de Biosistemas. Belo Horizonte, MG, Brasil / Universidade Federal de Minas Gerais. Programa de Pós-Graduação em Bioinformática. Belo Horizonte, MG, Brasil.
Kiel University and University Medical Center Schleswig-Holstein. Institute of Experimental Medicine. Kiel, Germany.
Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Bioquímica e Imunologia. Belo Horizonte, MG, Brasil / Universidade Federal de Minas Gerais. Programa de Pós-Graduação em Bioquímica e Imunologia. Belo Horizonte, MG, Brasil.
Fundação Oswaldo Cruz. Instituto René Rachou. Grupo de Genomica e Informatica de Biosistemas. Belo Horizonte, MG, Brasil
Kiel University and University Medical Center Schleswig-Holstein. Institute of Experimental Medicine. Kiel, Germany.
Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Departamento de Bioquímica e Imunologia. Belo Horizonte, MG, Brasil / Universidade Federal de Minas Gerais. Programa de Pós-Graduação em Bioquímica e Imunologia. Belo Horizonte, MG, Brasil.
Fundação Oswaldo Cruz. Instituto René Rachou. Grupo de Genomica e Informatica de Biosistemas. Belo Horizonte, MG, Brasil
Abstract
Diabetes mellitus is a prevalent chronic non-communicable disease, and recent studies have explored the link between gut microbiota and its development. Despite some evidence suggesting an association, the influence of gut microbiota on type 2 diabetes DM2 remains unclear. A systematic search of PubMed Janeiro 2016– 10 December 2023 using the keywords “16S” and “diabetes” or “DM2” and “gut microbiota” and “diabetes” or “DM2”. The studies included compared gut microbiome diversity between diabetic and non-diabetic adults using 16S rRNA sequencing, excluding children, interventions, and type 1 diabetes. Alpha diversity indices and bacterial mean abundance were analyzed, with statistical assessments using a random-effects model and I² for heterogeneity. Thirteen studies met the criteria, with the Shannon index being the most commonly used measure. Results showed significant heterogeneity I² > 75% and no notable differences between diabetic and non-diabetic groups. Other indices, such as Chao1 and phylogenetic whole tree, similarly showed no consistent differences. Taxonomic analysis also failed to find phyla consistently correlated with DM2, with variability across studies. The relationship between gut microbiota and diabetes remains uncertain due to technical and biological factors that are often overlooked. The inconsistencies across studies highlight the low reproducibility common in microbiota research.
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