Fecal microbiome analysis in patients with metabolic syndrome and type 2 diabetes
Background Metabolic syndrome (MS) and type 2 diabetes (T2D) are metabolically related diseases with rising global prevalence and increasingly evident links to the intestinal microbiota. Research suggests that imbalances in microbiota composition may play a crucial role in their pathogenesis. Specif...
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2025-06-01
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| author | Laura Isabel Sinisterra Loaiza Diego Fernández-Edreira Jose Liñares-Blanco Alberto Cepeda Alejandra Cardelle-Cobas Carlos Fernandez-Lozano |
| author_facet | Laura Isabel Sinisterra Loaiza Diego Fernández-Edreira Jose Liñares-Blanco Alberto Cepeda Alejandra Cardelle-Cobas Carlos Fernandez-Lozano |
| author_sort | Laura Isabel Sinisterra Loaiza |
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| description | Background Metabolic syndrome (MS) and type 2 diabetes (T2D) are metabolically related diseases with rising global prevalence and increasingly evident links to the intestinal microbiota. Research suggests that imbalances in microbiota composition may play a crucial role in their pathogenesis. Specific population cohorts, such as the one in Galicia, Spain, offer the opportunity to analyze microbiota patterns within a distinct geographical and genetic context. This study was performed to investigate the relationship between the intestinal microbiota and MS and T2D. Methods A cohort of 79 volunteers was analyzed over a 2-year study period. Recruitment posed significant challenges because of strict inclusion criteria (918PTE0540; PCI2018-093284), which required participants to be free from chronic medications and have a moderate to high risk of developing T2D. Volunteers were classified based on their serum glucose levels, body mass index, and the presence or absence of MS. To analyze the microbiota composition, amplicon sequencing of 16S rRNA genes was performed on stool samples. Alpha diversity was assessed using the Chao and Shannon indices, while beta diversity was evaluated using permutational analysis of variance with Bray–Curtis and Chao distances. Differential abundance analysis was conducted using the LinDA method. Results In patients with MS, we observed a higher Firmicutes/Bacteroidetes ratio and an increased prevalence of Blautia compared to healthy patients. than in healthy individuals. Other enriched taxa in patients with MS included Tyzerella, Streptococcus, and Ruminococcus callidus. In patients with T2D, we observed a higher Bacteroidetes/Firmicutes ratio and a decrease in the phylum Actinobacteria compared with healthy individuals. Taxa such as Dorea, Prevotella, Dialister invisus, Fusicatenibacter, and Coprococcus were associated with T2D, while beneficial taxa such as Eubacterium, Ligilactobacillus, and Acidaminococcus were more prevalent in healthy or prediabetic individuals. Conclusions This study reveals notable differences in the intestinal microbiota composition among patients with MS and T2D. Changes in microbial composition, particularly the Firmicutes/Bacteroidetes ratio, may serve as indicators of underlying pathology. At more specific taxonomic levels, several enriched taxa were identified in patients with MS, including Blautia, Tyzzerella, Dorea, Streptococcus, and Ruminococcus callidus. Additionally, species such as Dorea longicatena and Dialister invisus were enriched in prediabetic and diabetic patients, whereas beneficial genera (Eubacterium, Acidaminococcus, Bifidobacterium, and Ligilactobacillus) were more prevalent in healthy and prediabetic individuals than in those with T2D. |
| format | Article |
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| institution | Kabale University |
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| spelling | doaj-art-bb29c313d6424b8ea09067adcd827de62025-08-20T03:47:12ZengPeerJ Inc.PeerJ2167-83592025-06-0113e1910810.7717/peerj.19108Fecal microbiome analysis in patients with metabolic syndrome and type 2 diabetesLaura Isabel Sinisterra Loaiza0Diego Fernández-Edreira1Jose Liñares-Blanco2Alberto Cepeda3Alejandra Cardelle-Cobas4Carlos Fernandez-Lozano5Department of Analytical Chemistry, Nutrition and Bromatology, Faculty of Veterinary Medicine, Universidade de Santiago de Compostela, Campus de Lugo, Lugo, SpainMachine Learning in Life Sciences Laboratory, Department of Computer Science and Information Technologies, Universidade da Coruña (CITIC), A Coruña, SpainMachine Learning in Life Sciences Laboratory, Department of Computer Science and Information Technologies, Universidade da Coruña (CITIC), A Coruña, SpainDepartment of Analytical Chemistry, Nutrition and Bromatology, Faculty of Veterinary Medicine, Universidade de Santiago de Compostela, Campus de Lugo, Lugo, SpainDepartment of Analytical Chemistry, Nutrition and Bromatology, Faculty of Veterinary Medicine, Universidade de Santiago de Compostela, Campus de Lugo, Lugo, SpainMachine Learning in Life Sciences Laboratory, Department of Computer Science and Information Technologies, Universidade da Coruña (CITIC), A Coruña, SpainBackground Metabolic syndrome (MS) and type 2 diabetes (T2D) are metabolically related diseases with rising global prevalence and increasingly evident links to the intestinal microbiota. Research suggests that imbalances in microbiota composition may play a crucial role in their pathogenesis. Specific population cohorts, such as the one in Galicia, Spain, offer the opportunity to analyze microbiota patterns within a distinct geographical and genetic context. This study was performed to investigate the relationship between the intestinal microbiota and MS and T2D. Methods A cohort of 79 volunteers was analyzed over a 2-year study period. Recruitment posed significant challenges because of strict inclusion criteria (918PTE0540; PCI2018-093284), which required participants to be free from chronic medications and have a moderate to high risk of developing T2D. Volunteers were classified based on their serum glucose levels, body mass index, and the presence or absence of MS. To analyze the microbiota composition, amplicon sequencing of 16S rRNA genes was performed on stool samples. Alpha diversity was assessed using the Chao and Shannon indices, while beta diversity was evaluated using permutational analysis of variance with Bray–Curtis and Chao distances. Differential abundance analysis was conducted using the LinDA method. Results In patients with MS, we observed a higher Firmicutes/Bacteroidetes ratio and an increased prevalence of Blautia compared to healthy patients. than in healthy individuals. Other enriched taxa in patients with MS included Tyzerella, Streptococcus, and Ruminococcus callidus. In patients with T2D, we observed a higher Bacteroidetes/Firmicutes ratio and a decrease in the phylum Actinobacteria compared with healthy individuals. Taxa such as Dorea, Prevotella, Dialister invisus, Fusicatenibacter, and Coprococcus were associated with T2D, while beneficial taxa such as Eubacterium, Ligilactobacillus, and Acidaminococcus were more prevalent in healthy or prediabetic individuals. Conclusions This study reveals notable differences in the intestinal microbiota composition among patients with MS and T2D. Changes in microbial composition, particularly the Firmicutes/Bacteroidetes ratio, may serve as indicators of underlying pathology. At more specific taxonomic levels, several enriched taxa were identified in patients with MS, including Blautia, Tyzzerella, Dorea, Streptococcus, and Ruminococcus callidus. Additionally, species such as Dorea longicatena and Dialister invisus were enriched in prediabetic and diabetic patients, whereas beneficial genera (Eubacterium, Acidaminococcus, Bifidobacterium, and Ligilactobacillus) were more prevalent in healthy and prediabetic individuals than in those with T2D.https://peerj.com/articles/19108.pdfBioinformaticsMicrobiomeType 2 diabetesMetabolic syndromeBiomarkers |
| spellingShingle | Laura Isabel Sinisterra Loaiza Diego Fernández-Edreira Jose Liñares-Blanco Alberto Cepeda Alejandra Cardelle-Cobas Carlos Fernandez-Lozano Fecal microbiome analysis in patients with metabolic syndrome and type 2 diabetes PeerJ Bioinformatics Microbiome Type 2 diabetes Metabolic syndrome Biomarkers |
| title | Fecal microbiome analysis in patients with metabolic syndrome and type 2 diabetes |
| title_full | Fecal microbiome analysis in patients with metabolic syndrome and type 2 diabetes |
| title_fullStr | Fecal microbiome analysis in patients with metabolic syndrome and type 2 diabetes |
| title_full_unstemmed | Fecal microbiome analysis in patients with metabolic syndrome and type 2 diabetes |
| title_short | Fecal microbiome analysis in patients with metabolic syndrome and type 2 diabetes |
| title_sort | fecal microbiome analysis in patients with metabolic syndrome and type 2 diabetes |
| topic | Bioinformatics Microbiome Type 2 diabetes Metabolic syndrome Biomarkers |
| url | https://peerj.com/articles/19108.pdf |
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