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Personalized Nutrition for MicrobiotaCorrection and Metabolism Restorein Type 2 Diabetes Mellitus Patients


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Tamara Meleshko , Roman Rukavchuk , Olga Levchuk ,

and Nadiya Boyko


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. Bio-

chemical, 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 develop-

ment of personalized diets for patients with

diabetes type 2 demonstrated clinical efficacy

of its implementation.

Keywords

Human microbiota · Metabolism regulation ·

Noncommunicable disease · Personalised diet ·

Prognostic correction


1 Introduction

Type 2 diabetes mellitus (T2D) is a growing

global health problem closely related to the epi-

demic of obesity. It is characterized by

dysregulation of carbohydrate, lipid, and protein

metabolism and results from impaired insulin

secretion, insulin resistance, or a combination of

both (DeFronzo et al. 2015). T2D is one of the

noncommunicable diseases (NCDs) common

among almost all people in the world

(Raychaudhuri 2011) regardless of their age and

region due to the changes in lifestyles, genetics,

and environmental factors, all of which together

influence the disorder (Raj et al. 2018).

Typical clinical markers of type 2 diabetes

include glucose and glycosylated haemoglobin,

increased cholesterol, triglycerides, low-density

lipoprotein, very low-density lipoprotein, and

decreased high-density lipoprotein (Krauss

2004). Metabolic parameters such as urea, uric

acid, creatinine, bilirubin, calcium, magnesium,

sodium, alanine aminotransferase, and others

involved in lipid profile regulation are an addi-

tional source of complete information about the

biochemical status of the human body. Recent

researches have demonstrated that the develop-

ment of low-grade inflammation is a conse-

quence of gut microbiota alteration, which is

closely related to metabolic disorders such as

obesity and T2D (Cani et al. 2012; Minihane

et al. 2015). In particular, in the majority of

patients suffering from diabetes the levels of

Bifidobacterium and Lactobacillus decrease,

which leads to an increase in the levels of

Bacteroides, Prevotella, Peptococcus, Clostrid-

ium, Proteus, Staphylococcus, and Candida.

Importantly, T2D subjects have smaller amounts

of butyrate producing bacteria, such as

Roseburia intestinalis and Faecalibacterium

prausnitzii, and a mucus-degrading bacterium

Аkkermansia muciniphila (Tilg and Moschen

2014).

Studies conducted within the “Human

Microbiome” project (Group et al. 2009)

demonstrated that intestinal microbiome can be

dominated by different ratios of beneficial

microorganisms and still perform identical

functions. Thus, it is not only the species compo-

sition of the microbiome, but also its “function”

that is important. Herewith, it is obvious that the

microbiome of each individual is unique.

Recently, numerous research studies have

been conducted to find a relationship between

nutrition and its impact on human health. Never-

theless, today a balanced diet principle remains

practically unapplied. The reason is, on the one

hand, that people misunderstand (underestimate)

the role of food as a source of essential balanced

nutrients. On the other hand, there are huge

amounts of data on “proper nutrition” (rational

nutrition) available and they are often contradic-

tory, scientifically unsubstantiated, and clinically

unconfirmed. A new modern challenge is the use

of P4 (predictive, preventive, personalised, and

participatory) approaches, in particular

personalized nutrition, in medical practice.

The diet-microbiome interplay is currently the

basis for personalized nutrition introduction and

microbiota composition is the key factor affecting

responsiveness to nutritional interventions that

will soon take into account initial stratification

of individuals on the basis of microbiota (Ercolini

and Fogliano 2018).


The health benefits of adherence to the Medi-

terranean diet, as well as the relationship between

microbiota and its associated metabolome in peo-

ple consuming varied diets ranging from vegan to

omnivorous, are now evidence-based (Shanahan

et al. 2017).

In our opinion, the most promising way of

individual microbiome correction, as well as

prognostic modulation of local immune response,

is the use of complete personalized diets rather

than individual components. The most popular

diets whose positive health effects on the human

body are considered to be established include the

Mediterranean diet, vegetarian/vegan diet, high-

fibre diet, and high-protein diet.


The antioxidant and anti-inflammatory effects

of the Mediterranean diet on the whole as well as

the effects of this diet’s individual components, in

particular olive oil, fruits and vegetables, whole

grains, and fish, have a beneficial impact on

abdominal obesity, lipids levels, glucose metabo-

lism, and blood pressure levels (Kastorini et al.

T. Meleshko et al.

2011). Gut microbiota in individuals following

the Mediterranean diet is characterized by high

levels of Lactobacillus spp., Bifidobacterium

spp., and Prevotella spp. and low levels of Clos-

tridium spp., which relates to weight loss,

improvement of the lipid profile, and decreased

inflammation (Singh et al. 2017).

For vegetarians and vegans, the most relevant

risk factors for chronic disease, such as body

mass index (BMI), lipid variables, and fasting

glucose, are significantly lower. People following

a plant-based dietary pattern demonstrate signifi-

cantly lower levels of BMI, total cholesterol,

LDL-cholesterol, triglycerides, and blood glucose

when vegetarians were compared to

nonvegetarians, and lower levels of BMI, total

cholesterol, and LDL-cholesterol when vegans

were compared to nonvegans (Dinu et al. 2017).

People following vegan and vegetarian diets rich

in fermentable plant-based foods were reported to

have a microbiota characterized by a lower abun-

dance of Bacteroides spp. and Bifidobacterium

spp. (Wu et al. 2016).

High fibre intake is associated with lower serum

cholesterol concentrations, lower risk of coronary

heart disease, reduced blood pressure, enhanced

weight control, better glycaemic control, reduced

risk of certain forms of cancer, and improved

gastrointestinal function (Anderson et al. 2009).


One study revealed that three diets containing dif-

ferent fibre-rich whole grains (barley, brown rice,

or a combination of both) increased microbial

diversity, the Firmicutes/Bacteroidetes ratio, and

the abundance of the genus Blautia in faecal

samples (Oriach et al. 2016).

High-protein diet decreases weight, fasting

glucose, and insulin concentrations as well as

total and abdominal fat. In addition, this diet

significantly decreases LDL cholesterol

concentrations (Parker et al. 2002). Dietary pro-

tein intake in humans has been associated with the

Bacteroides enterotype (Oriach et al. 2016).

In previous studies, we obtained data

demonstrating that extracts of certain edible

plants rich in biologically active substances

(BAS) specifically stimulate the immune

response and have anti-inflammatory properties.

We also proved that these extracts are able to

specifically modulate intestinal microbiota (Bati

and Boyko 2013).

In our previous studies involving different

mouse models, we showed the molecular mecha-

nism by which different gut commensal

representatives modulate local immune response

at mucosal sites in a strain- or species-specific

manner. We were able to analyse in vitro the

effects of individual commensal bacteria on

human monocyte-derived dendritic cells

(moDCs)-mediated inflammation and effector

T-lymphocyte priming conditions mimicking

unique intestinal microenvironment. Human

moDCs expressing peroxisome proliferator-

activated receptor gamma (PPARγ) also regulate

cell surface expression of type I and II CD1

glycoprotein receptors as well as mucosa-

associated CD103 protein differently in the

absence or presence of all-trans-retinoic acid

(ATRA), when ATRA provides a tolerogenic

effect. In other words, this makes the pro- and

anti-inflammatory reprogramming of this popula-

tion of immune cells possible (Bene et al. 2017).

However, applying all these observations in

practice taking into consideration patients’

microbiome uniqueness is a challenge.

Additionally, it is known that the geographical

location of plant food ingredients’ growth affects

the quantitative and qualitative composition of

their BAS. Also, geographical location

determines people’s lifestyles, their habits and

traditions, and diets.

Previously, within the BaSeFood project, we

conducted a study of priority dishes in the Black

Sea region, including Ukrainian ones. We deter-

mined the nutritional value and composition of

food products, which formed the basis for the

creation of the First National Composite Database

of Food (Costa et al. 2013). One of the tasks of

this work was to investigate the fundamental pos-

sibility of creating or developing personalized

(individual) approaches (diet plans) using tradi-

tional dishes (based on traditional dishes) of our

region as a source of BAS selected for their

known biological effects on the microbiome and

local immune response and that could be used to

treat T2D in a controlled diet study (Danesi et al.

2013; Pallah et al. 2019).


Personalized Nutrition for Microbiota Correction and Metabolism Restore in...

Following to numerous in vitro studies (Pallah

et al. 2019; Bati and Boyko 2016, 2017) and

based on in vivo experiments data about main

influences of various plant originated compounds

and defined beneficial lactic acid bacteria (LAB)

strains on gut microbiota, mucosal immune

response and lipid metabolism of tested mice

and rats (Bati and Boyko 2016; Meleshko et al.

2020) the selection procedure of most promising

ethnical foods had been performed.

Thus, the aim of this study was to investigate

the possibility of correction of lipid metabolism

of patients with T2D using a personalised diet

based on the most important microbial, biochem-

ical, and immunological biomarkers of chronic

inflammation.

To achieve this goal, we focused on lipid

metabolism, immune, and microbiome

biomarkers as a whole, as well as patients’ indi-

vidual characteristics (differences), to be able to

regulate those indices that are considered major

evidence-based determinants of T2D.

2 Materials and Methods

Patients of the Mukachevo Central District Hos-

pital, Therapy Department, took part in the con-

trolled clinical trial; all participants gave written

informed consent.

Women aged 39–68 years with T2D were

selected according to the criteria typical of this

nosology (DeFronzo et al. 2015). Exclusionary

criteria involved smoking, alcohol or drug

abuse, pregnancy, and unstable medical status.


No participants had clinically significant cardio-

vascular, renal or liver disease, a history of cancer

or any other comorbidities. Patients who

participated in the study did not take any other

drugs.

Eligibility requirements were fulfilled and

enrolment procedures were performed in accor-

dance with the EU Clinical Trials Regulation

(Regulation (EU) No 536/2014). The study pro-

tocol was approved by the Uzhhorod National


University, Research Ethics Committee.

To confirm the effectiveness of personalized

diet plans, a randomized controlled trial was

conducted in two parallel groups. Group I (exper-

imental one) included patients who followed an

18-day personalized diet, which included individ-

ually selected products rich in BAS and yogurts

with unique microbial starters. Group II (control

one) involved patients who, for 18 days, ate

berries and yogurt prepared without microbial

starters in the morning. Patients were not

instructed to do additional physical exercise.

The experimental group consisted of 35 patients

and the control one of 21 patients. The study

lasted for roughly a month. Before and after the

diet course we measured five groups of

parameters (total 62 parameters): (1) patients’

biochemical status; (2) gut microbiota; (3) oral

microbiota; (4) immune status; and (5) physical

parameters of patients (measurement of body

weight, circumference of waist, thighs, and

upper thighs). Gut and oral microbiota studies

were performed in dynamics on days 1, 7,

11 and 18 of the experiment.

In order to conduct measurements, that is to

determine the condition (severity and course of

the disease), for each individual we identified

typical to this disease diagnostic markers for the

detection of T2D, such as blood glucose, lipid

profile (cholesterol, LDL, HDL, VLDL,

triglycerides, and atherogenicity levels),

glycosylated haemoglobin, total protein, and bili-

rubin levels, as well as typical diagnostic

enzymes (amylase, alkaline phosphatase, aspar-

tate aminotransferase, alanine aminotransferase,

lactate dehydrogenase, gamma-glutamyl transfer-

ase, and total creatine kinase), thymol test, and

indicators measuring the state of the excretory

system (albumin, urea and uric acid, and total

creatinine) and micro- (iron) and macronutrient

(potassium, magnesium, calcium, sodium) blood

composition, as an evidence of existing metabolic

disorders. Regarding immune parameters, we

limited ourselves to the well-known indicators

of inflammatory processes, that is markers of

inflammation and their agonists (IL-1β, Il-10,

TNF-α). However, we also considered previously

identified (selected) local inflammation markers,

such as levels of total and secretory immunoglob-

ulin A in serum (IgA, SIgA. During the study of

intestinal and oral microbiome we focused on

T. Meleshko et al.

such target groups of microorganisms as (1) typi-

cal intestinal commensals and the so-called bene-

ficial microorganisms (Enterobacteriaceae family,

genera Staphylococcus, Streptococcus, Lactoba-

cillus, Candida, Clostridium spp.); (2) opportunis-

tic microorganisms - Pseudomonas aeruginosa,

E. faecalis, Staphylococcus spp., Enterobac-

teriaceae; (3) markers of metabolic disorders that

we identified earlier (E. coli lac+, E. coli lac-,

Bifidobacterium spp., Enterococcus spp.) (Petrov

and Boyko 2014).

Blood formula (red and white blood cells,

monocytes, lymphocytes, platelet assay, and

eosinophils) was identified using Mythic

22 Orphee S.A. (Switzerland) Haematology sys-

tem. Erythrocyte sedimentation rate (ESR) was

measured using the Westergren method.

Haemoglobin was identified calorimetrically. All

biochemical parameters were assayed using

Cobas c 311 (Roche/Hitachi) Switzerland.

Intestinal and oral microbes were studied

according to our own method using the following

nutrient media: Mitis Salivarius Agar, Bile

Esculin Agar, Mannitol Salt Agar, Endo Agar,

Bismuth Sulphite Agar, HiCrome Clostridial

Agar, Sabouraud Dextrose Agar, Lactobacillus

MRS Agar, Bifidobacterium Agar, Bacteroides

bile esculin agar, Propionibacter Isolation Agar,

L.D. Esculin HiVegTM Agar (manufactured by

HiMedia Laboratories, India), UriSelectTM

4 Medium (Bio-Rad Laboratories, Inc., USA),

and Blaurock semi-liquid modified hepatic

medium (manufactured by Liofilchem, Italy).

Identification of isolated microorganisms was

performed using biochemical test systems

ANAERO-23, ENTERO-24, NEFERM-test,

Candida-23, STAPHY-16, and STREPTO test

24 (Erba Lachema s.r.o., Czech Republic).

Microbiome studies were also performed using

real-time polymerase chain reaction (qPCR).

Immune parameters were measured using indica-

tor immunosorbent systems Vector-Best (Russian

Federation); results were read at a wavelength of

450 nm using a plate immunosorbent assay

BioTek Elx800.

With the help of the developed information

system and created an algorithm based on linear

programming approaches, which allows selecting

food for any individual (patient) in accordance

with the state of her gut microbiota and immune

and biochemical parameters, a personalized diet

was developed for each participant of the experi-

ment. Developed diets included products that

contain functioning groups of biologically active

substances such as polyphenols, anthocyanins,

and flavonoids as well as unique microbial

starters for fermentation. Sequenced strains of

Lactobacillus casei IMB B-7412, Lactobacillus

plantarum IMB B-7414, and Lactobacillus

plantarum IMB B-7413 were used to prepare

yogurts. The selection of food products was

tak-ing into account individual wishes and contrain-

dications, as well as when determining the portion

size - individual characteristics of patients such as

the level of physical activity, body mass

index, etc.

Statistical analyses were performed using the

statistical program GraphPad Prism version 3.00

(GraphPad Software, USA). All data are

presented as the mean SD or mean SE. For

normally distributed data, checked used Shapiro-

Wilk test, comparisons were tested using


ANOVA. The two-tailed Mann-Whitney U-test

was used for comparisons between the groups. P

values <0.05 were considered statistically

significant.

3 Results

On the first day of the experiment, in all patients

diagnosed with type 2 diabetes there was an

increase in the level of biochemical parameters

observed: glucose (the real average value is

8 times higher than the allowed excess of the

average value of the norm), LDH (the real aver-

age value is 5 times higher than the allowed

excess of the average value of the norm),

HbA1C (the real average value is 1,5 times higher

than the allowed excess of the average value of

the norm), and immunological indicator IL-10

(the real average value is 2 times higher than the

allowed excess of the average value of the norm),

as well as physical parameters such as BMI (the real average value is 5,5 times higher than the

allowed excess of the average value of the norm).

Also, a decrease in HDL levels was observed: the

real average value is 1.5 times lower than the

allowed decrease in the average value of the

norm (see Table 1, Fig. 1).

The composition of the intestinal microbiota

on day 1 of the experiment demonstrated a pre-

dominance of enterococci and lactobacilli with a

significant variety of commensal and opportunis-

tic microorganisms, namely enterobacteria,

pseudomonads, streptococci, staphylococci,

bacilli, and candida. We observed an increase

level of E. faecalis (the real average value is

2 times higher than the allowed excess of the

average value of the norm), a decrease in levels

of E. coli (lac+) (the real average value is more

than 8 times lower than the allowed decrease in

the average value of the norm), E. coli (lac) (the

real average value is 4 times lower than the

allowed decrease in the average value of the

norm) and Lactobacillus spp. (the real average

value is more than 1,5 times lower than the

allowed decrease in the average value of the

norm) (see Figs. 2 and 3). The oral microbiota

was characterized by a predominance of

lactobacilli, enterococci, and streptococci, as

well as a number of other bacteria, such as

E. coli (lac+), Citrobacter spp., E. cloacae,

P. aeruginosa, S. epidermidis, Bacillus spp., and

Candida spp. We observed an increased level of

E. faecalis (the real average value is 4 times

higher than the allowed excess of the average

value of the norm), Lactobacillus spp. (the real

average value is 7,5 times higher than the allowed

excess of the average value of the norm),

P. aeruginosa and Candida spp. (the real average

value is 2 times higher than the allowed excess of

the average value of the norm) (see Figs. 2 and 4).

On the first day of the experiment, no statistically

significant difference was observed between the

control and experimental groups.


After 18 days of the experiment, no statisti-

cally significant changes in parameters were

observed in the control group, but there were

changes in blood and physical parameters and

microbiota composition in the experimental

group. According to the data obtained, there was

a decrease in the levels of such biochemical


parameters as glucose, bilirubin, thymol test, cho-

lesterol, HDL, LDL, VLDL, iron, gamma-

glutamyl transferase, total protein, urea, creati-

nine, LDH, HbA1C, and triglycerides as well as


changes in all immune and physical parameters.


Also, an increase in amylase, alkaline phospha-

tase, calcium, creatine kinase, aspartate transfer-

ase, alanine aminotransferase, uric acid, sodium,

magnesium, albumin, and atherogenicity levels

was observed. Herewith, on day 18 of the experi-

ment all indicators were almost unchanged in the

control group (see Table 1).

After adherence to a personalized diet, in the

experimental group patients there was a statisti-

cally significant reduction in the following

parameters: glucose, thymol test, VLDL, urea,

creatinine, sIgA, and TNF-a, as well as all physical

parameters. There was a statistically significant

increase in such biochemical parameters as uric

acid, sodium, and magnesium. Regarding intesti-

nal microbiota indicators, there was a decrease in

the levels of all microbiota members except

lactobacilli. Statistically significant changes were

observed in Enterococcus faecalis, Escherichia

coli (lac+), Escherichia coli (lac), Lactobacillus

spp., and Candida spp. The oral microbiota was

characterized by a decrease in the number of all

representatives except lactobacilli. Such

microorganisms as E. faecalis, Lactobacillus

spp., P. aeruginosa, and Candida spp.

demonstrated statistically significant changes.

Statistically significant changes in the concen-

tration of microorganisms (in dynamics) were

observed in both the intestinal microbiota

(E. faecalis, E. coli (lac+), E. coli (lac), Lacto-

bacillus spp., and Candida spp.) and oral

microbiota (E. faecalis, Lactobacillus spp.,

P. aeruginosa, and Candida spp.) (see Figs. 5

and 6). Dynamic intestinal microbiota changes

in the experimental group (see Fig. 4) demon-

strate that the average concentration of

E. faecalis remained unchanged until day

11 while a statistically significant ifference com-

pared to the first day appeared on day 11 and the

tendency to a decrease remained on day 18 of the

experiment. E. coli (lac+) is characterized by a

decrease in concentration throughout the


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observation period, but a statistically significant

difference appeared on day 11 compared to day

1. A statistically significant difference in the

concentration of E. coli (lac) was also observed

on day 7 of the experiment and then an increase

was observed on day 11, with a further decrease

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on day 18. The concentration of Lactobacillus

spp. did not change statistically significantly

until day 11; there was a sharp increase in con-

centration on day 18. For Candida spp., on the

contrary, there was a statistically significant

decrease on day 7 with the absence of statistically

significant changes in subsequent days (see

Fig. 5).

The oral microbiota is characterized by a sharp

decrease in the concentration of E. faecalis on day

7 of the experiment followed by a slight decrease

in concentration. Lactobacillus spp. demonstrated

a statistically significant decrease in concentration

on day 7 with further growth dynamics. The

concentration of P. aeruginosa decreased during

the experiment and a statistically significant

difference was observed on day 11 compared to

day 1. Candida spp. is characterized by a slight

increase in concentration on day 7 and a further

decrease until day 18 of the experiment while a

statistically significant change was observed on

days 7–11 and 7–18 (see Fig. 6).


4 Discussion

The issue of treatment of type 2 diabetes is still

relevant. Emergence of a number of new markers

greatly simplifies and increases the accuracy of

the disease diagnosis, but medical personnel still

mostly uses long-tested, “classic” markers of dia-

betes, in particular because of their availability for

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analysis (DeFronzo et al. 2015). In our work, we

used a classic set of such markers as well as a

number of other indicators, including intestinal

and oral microbiota as recent publications empha-

size its significant role in the development of type

2 diabetes and human health in general (Gurung

et al. 2020; Sharma and Tripathi 2019).

According to the results of indicators’ change

during the experiment, there are improvements

in a number of markers, such as VLDL, glucose,

creatinine, urea, magnesium, sodium, thymol test,

and uric acid.

VLDL involves pre-beta-lipoproteins that are

formed in the liver and are the main transport

form of endogenous triglycerides. They are clas-

sified as highly atherogenic lipoproteins involved

in the formation of atherosclerotic plaques.

Hance, a decrease in VLDL indicates an improve-

ment in lipid metabolism, reducing the risk of

atherosclerosis and coronary heart disease devel-

oping (Xie et al. 2017). Elevated glucose levels

are one of the main diagnostic markers of T2D,

and, therefore, a decrease in its level indicates that

our proposed diet has a therapeutic effect.


In addition, we noticed a statistically signifi-

cant decrease in creatinine and urea levels was

observed in all patients in the experimental group.

This change resulted from an increase in the con-

sumption of vegetables and fruits, as well as a

decrease in the consumption of meat products.

According to the analysis of literature data, a

decrease in the levels of these biochemical

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parameters within normal limits may be indica-

tive of normalization of the renal excretory func-

tion (Gowda et al. 2010).


According to previous research, diabetes

mellitus is one of the diseases with increased

frequency of electrolyte abnormalities given that

the impaired renal function, malabsorption

syndromes, and acid-base disorders are often

present in diabetic patients (Liamis et al. 2014).


Magnesium deficiency may relate to the develop-

ment of atherosclerosis, coronary heart disease,


and cardiac arrhythmias while low blood magne-

sium is associated with the development of insu-

lin resistance (Kostov 2019). According to


experimental data obtained, we observed an

increase in the concentration of magnesium in


experimental group patients compared to the con-

trol group which demonstrated a tendency to an

increase in the concentration of this indicator.


It should be noted that hyponatremia is

associated with increased plasma glucose

concentrations (Liamis et al. 2015). As a result

of adherence to the personalized diet, patients in

the experimental group demonstrated an increase

in the concentration of another microelement,

sodium, compared to the control group, in which

this indicator remained almost unchanged

throughout the study. Sufficient sodium concen-

tration is extremely important for proper function-

ing of membrane transport, muscle contraction,

nerve impulse transmission, and many other vital

functions (Constantin and Alexandru 2011), and

therefore, normalization of this indicator indicates

the effectiveness of the proposed diet.

A statistically significant decrease in thymol

test levels within normal limits can indicate

improvement of liver function (Djiambou-

Nganjeu 2019). A statistically significant increase

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in uric acid levels within normal limits can be

explained by the increase in the consumption of

foods containing fructose, such as apples,

persimmons, blueberries, pears and dried fruits.

Another important result is a change in the

microbiota of the experimental group patients.

The study demonstrated a statistically significant

decrease in enterococci, E. coli, and Candida spp.

concentration, as well as an increase in

lactobacilli concentration. This indicates the nor-

malization of intestinal microbiota, which, in

turn, leads to metabolism improvement, including

glucose and cholesterol metabolism (Ma et al.

2019).


All the above-mentioned changes in biochem-

ical and immunological parameters, as well as

normalization of patients’ gut and oral

microbiota, cause changes in patients’ physical

parameters, namely a statistically significant

decrease in body weight and the circumference

of waist, hips, and upper thighs in all patients of

the experimental group.

Data on the immune status of the experimental

group patients demonstrated that there is a statis-

tically significant decrease in the levels of secre-

tory IgA and proinflammatory cytokine TNF-α

compared to the control group demonstrating a

tendency to a decrease in these indicators (see

Table 1). Literature analysis shows that TNF-α

is considered one of the many risk factors in the

development of type 2 diabetes. With regard to

type 2 diabetes, it affects glucose metabolism,

sensitivity of peripheral tissues to insulin, and

renin-angiotensin system, and is involved in the

development of oxidative stress. It possesses

cytotoxic activity, promotes endothelial dysfunc-

tion, and is able to induce apoptosis of insulin

producing cells (Dombrovska 2017). Thus, we

Fig. 6 Dynamic of oral microbiota changes in experimental group. All data represented on the figure are significantly

different between 1 and 18 days

Personalized Nutrition for Microbiota Correction and Metabolism Restore in...

can conclude that a decrease in TNF-α level

confirms the effectiveness of the proposed diet.

All this confirms the hypothesis of the possi-

bility of personalized diet use for treatment of

type 2 diabetes. In general, diets are often used

in type 2 diabetes treatment. The Mediterranean

diet is known to be one of the most studied diets

and its positive effect on health has been proved

(Trichopoulou et al. 2005). In addition, this diet is

claimed to be effective in prevention and treat-

ment of type 2 diabetes (Pérez-Jiménez et al.

2002). Research (Shai et al. 2008; Esposito et al.

2009) showed that the use of the Mediterranean

diet leads to a statistically significant decrease in

glucose and glycosylated haemoglobin in blood,

as well as a decrease in weight and body mass

index. Herewith, in our work we did not observe

statistically significant changes in glycosylated

haemoglobin in patients of the experimental

group. This may be due to the short duration of

the proposed diet (18 days), as this biochemical

blood indicator reflects the average content of

glucose in blood over a long period of time

(3–4 months).


It should be noted that literature does not pro-

vide data on the changes in such biochemical

indicators as urea, thymol test, uric acid, creati-

nine, sodium, and magnesium under the influence

of diet in patients with diabetes mellitus. The

reason may be that only classic markers of diabe-

tes, such as glucose, glycosylated haemoglobin,

cholesterol, triglycerides, low-density lipopro-

tein, very low-density lipoprotein, and high-

density lipoprotein, are usually studied. However,

most diets used in type 2 diabetes treatment do

not consider the patient’s condition and are not

personalized. The most valuable in this regard is

the known approach to adjusting body state in

type 2 diabetes based on the glycaemic index

(Zeevi et al. 2015). The study demonstrated the

ability to predict the glycaemic response to the

use of certain foods, which resulted in the possi-

bility of making plans for personalized nutrition

and adjusting intestinal microbiota. They used

blood parameters, dietary habits, anthro-

pometrics, physical activity, and gut microbiota

measured to predict personalized postprandial

glycaemic responses to daily consumed meals.

The results of cohort study suggest that

personalized diets may consistently alter gut

microbiota configuration and successfully modify

elevated postprandial blood glucose and its meta-

bolic consequences. However, this approach is

difficult to implement and it is not based on the

use of BAS, which are extremely promising in

terms of correction of not only body condition in

type 2 diabetes, but also a number of other

diseases.


5 Conclusions


A personalized diet based on the use of individu-

ally selected BAS and probiotic microorganisms

is one of the possible ways to improve the condi-

tion of patients with type 2 diabetes. Its use in the

experimental group of 35 patients led to the

improvement in a number of biochemical (glu-

cose, thymol test, VLDL, urea, uric acid, creati-

nine, sodium, and magnesium), immunological

(sIgA, TNF-a), and all physical parameters. The

intestinal and oral microbiota condition also

normalized. Reduction in E. faecalis, E. coli,

P. aeruginosa, and Candida spp., as well as an

increase in the number of lactobacilli, was

observed. Statistically significant changes were

observed in only a small number of the studied

62 markers, so it is important to identify a narrow

range of priority biomarkers. The results obtained

can be used for further treatment of patients with

type 2 diabetes and introduction of personalized

medicine in Ukraine.

Conflict of Interest The authors declare no conflicts of

interest in relation to this article.


Funding This work was supported by Ministry of Edu-

cation and Science, Topic: “The introduction of new

approaches to the creation and use of modern

pharmabiotics” Registration number 0117 U000379.


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