ArticleAdvances in experimental medicine and biology2022
Personalized Nutrition for Microbiota Correction and Metabolism Restore in Type 2 Diabetes Mellitus Patients.
Article in Advances in experimental medicine and biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.
- Dietary intervention improves metabolic levels in patients with type 2 diabetes through the gut microbiota: a systematic review and meta-analysis.Frontiers in nutrition · 2023Pooled it
- From Inclusion Complexes to Metabolic Signaling: The Emerging Role of γ-Cyclodextrin in Gut Microbiota and Metabolic Regulation.Molecules (Basel, Switzerland) · 2026Review
- Oral Microbiota and Type 2 Diabetes: Interactions, Potential Mechanisms, and Preventive Strategies.Microorganisms · 2026Review
- Impact of Ketogenic and Mediterranean Diets on Gut Microbiota Profile and Clinical Outcomes in Drug-Naïve Patients with Diabesity: A 12-Month Pilot Study.Metabolites · 2025Article
- The Effects of Diet Intervention on the Gut Microbiota in Type 2 Diabetes Mellitus: A Systematic Review.Cureus · 2024Review
- Impact of HbA1c control and type 2 diabetes mellitus exposure on the oral microbiome profile in the elderly population.Journal of oral microbiology · 2024Article
- The roles of personalized nutrition in obesity and diabetes management: a review.Journal of diabetes and metabolic disorders · 2022Review
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Type 2 diabetes is one of the most common noncommunicable diseases in the world. Recent studies suggest a link between type 2 diabetes and microbiota, as well as the ability to treat and prevent it using personalized approaches to nutrition. In this work, we conducted clinical studies on the effects of a personalized diet on 56 female patients. Biochemical, physical, and immunological parameters were measured by standard methods on days 1 and 18 of the experiment. Gut and oral microbiota studies were performed in dynamics on days 1, 7, 11, and 18 using real-time polymerase chain reaction. With the help of the developed information system, a personalized diet was developed for each participant of the experiment. In the group of patients following personalized diets a statistically significant decreasing levels of glucose, thymol test, creatinine, very low-density lipoprotein, urea, secretory IgA, and tumour necrosis factor-α, and improvement in all physical parameters were observed. There was a statistically significant increase in uric acid, sodium, and magnesium. Statistically significant changes in gut microbiota were observed in Enterococcus faecalis, Escherichia coli (lac+, lac-), Lactobacillus spp., and Candida spp. Such microorganisms of oral microbiota as E. faecalis, Lactobacillus spp., Pseudomonas aeruginosa, and Candida spp. demonstrated statistically significant changes. All these changes indicate an improvement in the patients' condition in the experimental group compared to the control group. Our algorithm used for the development of personalized diets for patients with diabetes type 2 demonstrated clinical efficacy of its implementation.
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