Personalized Nutrition for Microbiota Correction and Metabolism Restore in Type 2 Diabetes Mellitus Patients.

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.

Genome diversity in Ukraine.

BACKGROUND: The main goal of this collaborative effort is to provide genome-wide data for the previously underrepresented population in Eastern Europe, and to provide cross-validation of the data from genome sequences and genotypes of the same individuals acquired by different technologies. We collected 97 genome-grade DNA samples from consented individuals representing major regions of Ukraine that were consented for public data release. BGISEQ-500 sequence data and genotypes by an Illumina GWAS chip were cross-validated on multiple samples and additionally referenced to 1 sample that has been resequenced by Illumina NovaSeq6000 S4 at high coverage. RESULTS: The genome data have been searched for genomic variation represented in this population, and a number of variants have been reported: large structural variants, indels, copy number variations, single-nucletide polymorphisms, and microsatellites. To our knowledge, this study provides the largest to-date survey of genetic variation in Ukraine, creating a public reference resource aiming to provide data for medical research in a large understudied population. CONCLUSIONS: Our results indicate that the genetic diversity of the Ukrainian population is uniquely shaped by evolutionary and demographic forces and cannot be ignored in future genetic and biomedical studies. These data will contribute a wealth of new information bringing forth a wealth of novel, endemic and medically related alleles.