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Lilit Egshatyan
Lilit Egshatyan
‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation
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Daria Kashtanova
Daria Kashtanova
‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation
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Anna Popenko
Anna Popenko
‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation
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Olga Tkacheva
Olga Tkacheva
‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation
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Alexander Tyakht
Alexander Tyakht
‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation
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Dmitry Alexeev
Dmitry Alexeev
‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation
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Natalia Karamnova
Natalia Karamnova
‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation
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Elena Kostryukova
Elena Kostryukova
‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation
‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation
‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation
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‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation
‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation
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Vladislav Babenko
Vladislav Babenko
‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation
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Maria Vakhitova
Maria Vakhitova
‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation
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Sergey Boytsov
Sergey Boytsov
‘Research of Age and Age-Associated Conditions’ Department, Laboratory of Bioinformatics, The ‘Russian Clinical Research Center for Gerontology’, ‘Chronic Noncommunicable Diseases Primary Prevention in the Healthcare System’ Department, Moscow Institute of Physics and Technology, National Research Centre for Preventive Medicine, National Research Centre for Preventive Medicine, Building 10, Petroverigskiy Lane, Moscow RF 101000, Russian Federation
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Type 2 diabetes (T2D) is a serious disease. The gut microbiota (GM) has recently been identified as a new potential risk factor in addition to well-known diabetes risk factors. To investigate the GM composition in association with the dietary patterns in patients with different glucose tolerance, we analyzed 92 patients: with normal glucose tolerance (n=48), prediabetes (preD, n=24), and T2D (n=20). Metagenomic analysis was performed using 16S rRNA sequencing. The diet has been studied by a frequency method with a quantitative evaluation of food intake using a computer program. Microbiota in the samples was predominantly represented by Firmicutes, in a less degree by Bacteroidetes. Blautia was a dominant genus in all samples. The representation of Blautia, Serratia was lower in preD than in T2D patients, and even lower in those with normal glucose tolerance. After the clustering of the samples into groups according to the percentage of protein, fat, carbohydrates in the diet, the representation of the Bacteroides turned to be lower and Prevotella abundance turned to be higher in carbohydrate cluster. There were more patients with insulin resistance, T2D in the fat–protein cluster. Using the Calinski–Harabasz index identified the samples with more similar diets. It was discovered that half of the patients with a high-fat diet had normal tolerance, the others had T2D. The regression analysis showed that these T2D patients also had a higher representation of Blautia. Our study provides the further evidence concerning the structural modulation of the GM in the T2DM pathogenesis depending on the dietary patterns.
