Introduction. Paraoxonase 1 (PON1), lipoprotein lipase (LPL), triaglyceride lipase (LIPC) and alpha-ketoglutarate-dependent dioxygenase (FTO) play key roles in lipid metabolism. Genetic variants PON1 Q192R, LIPC -250G> A, LPL Ser447Ter, FTO A23525T affect the activity of these proteins and the characteristics of metabolic pathways. Description of these polymorphic variants of the PON1, LIPC, LPL, FTO genes and their molecular effect is presented in Table 1.

Table 1 — Characteristics of the loci of the PON1, LPL, LIPC, FTO genes (according to the NCBI database).

Gene localization

Alleles

 

SNP

Protein

Molecular effect of SNP

PON1

7q21.3

T>C

rs662

Gln192Arg

Missense variant in coding position. Decreased gene activity [1]

LIPC

15q21.3 

-250G>A 

rs2070895

-

Intron variant in 5 'UTR

LPL

16p13.3

G>A,C

rs149551759

Ser447Ter

 

Exon 14, stop codon

Ser447Leu

Missense variant

FTO

16q12.2  

23525T˃A

 

rs9939609

-

Intron variant.

Increased gene expression [2]

 

According to the gnomAD browser data, the allele frequencies of these SNPs differ in populations around the world (Table 2).

Table 2 — Population frequency of SNV genes PON1, LIPC, LPL, FTO according to gnomAD browser [3]

Population

rs662

rs2070895

rs149551759*

rs9939609

Africans / African-Americans

0.6733

0.5139

0.000

0.4823

East Asians

0.6568

0.3916

0.000

0.1309

South Asians

0.3824

0.000

0.000

0.000

Latinos / Latino Americans

0.4941

0.5036

0.000

0.2541

Ashkenazi Jews

0.3075

0.2063

0.000

0.5207

Europeans excluding Finns

0.2806

0.2251

0.0006447

0.4216

Finns

0.2771

0.2837

0.0008792

0.3970

General for women

0.3945

0.3332

0.0005114

0.4197

General for men

0.3708

0.3258

0.0002875

0.4134

General

0.3816

0.3290

0.0003899

0.4162

Total number of homozygotes

23 727

2 824

0

2 824

Number of alleles in exomes read

95 101

Not investigated

95

Not investigated

The number of alleles in the genomes read

12 746

13 038

15

13 038

*- for Ser447Leu

 

For rs662, rs2070895, rs149551759, rs9939609, participation in the development of obesity, diabetes, and atherosclerosis in adults for different populations has been shown [4-7]. Taking into account the fact that the clinical manifestations of these diseases are usually noticeable in middle age, the process of atherogenesis is able to start in early childhood [8]. External factors such as diet, lifestyle, hormonal changes affect the phenotypic manifestations of SNP and have to be studied [9, 10].

The aim of the study was to investigate the potential relationship between PON1 Q192R, LIPC-250G> A, LPL Ser447Ter, FTO A23525T and the risk of obesity, atherosclerosis and diabetes in children and adolescents in Europe and the European part of Russia by means of meta-analysis.

Materials and research methods

A systematic search was carried out in the PubMed, eLIBRARY.RU and Google Academia databases to search for full-text studies in English and Russian, published before April 2020. The articles were analyzed using the guidelines for systematic reviews and meta-analyzes (PRISMA) [11]. All included studies had to meet the following criteria: 1. Research focused on the role of gene polymorphisms PON1 Q192R, LIPC -250G> A, LPL Ser447Ter, FTO A23525T and the risk of obesity, atherosclerosis or diabetes in children and adolescents; 2. studies with a case-control design; 3. the age of the participants included in the experiment is no more than 20 years; 4. studies providing detailed frequencies of genotypes and the total number of studied groups for the territory of Europe and the European part of Russia. The exclusion criteria were:

  1. the article is not related to the studied polymorphisms;
  2. review article, editorial articles or meta-analysis;
  3. basic experimental studies or animal studies;
  4. studies without available genotyping data;
  5. data on populations that have been in genetic isolation for a long time (for example, Ashkenazi, Icelanders, etc.).

The search was carried out using the following set of keywords (table 3).

Table 3 — Keywords used for research searches.

Atherosclerosis

Diabetes

Obesity

PON1 / LIPC/ LPL/ FTO young subjects atherosclerosis

PON1 / LIPC/ LPL/ FTO young subjects diabetes

PON1 / LIPC/ LPL/ FTO young subjects overweight obesity

PON1 / LIPC/ LPL/ FTO atherosclerosis children adolescents

PON1 / LIPC/ LPL/ FTO diabetes children adolescents

PON1 / LIPC/ LPL/ FTO obesity children adolescents

rs662/ rs2070895/ rs149551759/ rs9939609  atherosclerosis children adolescents

rs662/ rs2070895/ rs149551759/ rs9939609  diabetes children adolescents

rs662/ rs2070895/ rs149551759/ rs9939609  obesity children adolescents

Gln192Arg/ -250G>A/ Ser447Ter/ A23525T atherosclerosis children adolescents

Gln192Arg/ -250G>A/ Ser447Ter/ A23525T diabetes children adolescents

Gln192Arg/ -250G>A/ Ser447Ter/ A23525T obesity children adolescents

PON1 / LIPC/ LPL/ FTO atherosclerosis in children and adolescents

PON1 / LIPC/ LPL/ FTO diabetes children adolescents

PON1 / LIPC/ LPL/ FTO obesity children adolescents

rs662/ rs2070895/ rs149551759/ rs9939609 atherosclerosis in children and adolescents

rs662/ rs2070895/ rs149551759/ rs9939609 diabetes children adolescents

rs662/ rs2070895/ rs149551759/ rs9939609 obesity children adolescents

 

 

 

Gln192Arg/ -250G>A/ Ser447Ter/ A23525T  atherosclerosis in children and adolescents

Gln192Arg/ -250G>A/ Ser447Ter/ A23525T  diabetes children adolescents

Gln192Arg/ -250G>A/ Ser447Ter/ A23525T  obesity children adolescents

 

An initial search in electronic databases yielded 2,549 studies in accordance with the above comprehensive search strategy. A detailed outline of the research selection process is shown in Figure 1. In total, more than 2,500 publications were excluded after careful reading of the titles, abstracts, or full text of the article. Following this procedure, 9 case-control studies were identified that met our criteria. In total, 3,603 people were included in the meta-analysis, divided into groups: children and adolescents with obesity or overweight (BMI) — 1,877 people and children and adolescents who made up the control group, with normal weight or underweight — 1,726 people.

 

Figure 1. Description of the procedure for searching for publications.


Statistical processing of results

The correspondence of the frequency distribution of genotypes to the Hardy-Weinberg equilibrium and the χ2 criterion were calculated using the Hardy-Weinberg equilibrium calculator [12]. The odds ratio (OR) was calculated using the SciStat.com program [13]. Differences were regarded as statistically significant at p < 0.05. If the authors did not provide detailed data in the article, HWE and OR were additionally calculated. The combined odds ratios were calculated for the dominant and recessive models, since, to the best of author’s knowledge, the data on the type of inheritance of the studied polymorphisms has not been found.

 

Results and discussion

Analysis of data on polymorphisms rs662, rs2070895, rs149551759, rs9939609 in the development of obesity in children and adolescents.

1627 articles have been found and analyzed by keywords (Table 3) in the PubMed, eLIBRARY.RU and Google Academia databases. Of these, 31 publications were devoted to a case-control study of rs662 and rs9939609 in the development of obesity in children and adolescents. Data on these studies are presented in Table 4. No such studies were found for the gene variants LIPC-250G> A and LPL Ser447Ter.

The results of a meta-analysis of the association of the rs662 polymorphism of the PON1 gene are presented in the study by Ferré N. et al (Table 5). There were no statistically significant differences for the two groups of children. The authors mention that the presence of the rs662 polymorphic alley of the PON1 gene in the genotype cannot be considered as a direct cause-and-effect relationship with the development of obesity. However, the authors note a decrease in plasma PON1 activity in obese children. In the respective publication, it is concluded that PON1 may play a role in the occurrence and development of metabolic changes in childhood obesity, which leads to diabetes and cardiovascular diseases at a later age [14].

 

Table 4 — Characteristics of studies investigating the role of rs662 and rs9939609 in the development of obesity in children and adolescents

First author, year

A country

Ethnicity

Diagnosis

Age in years

Sample size, absolute

Inclusion / exclusion criteria in meta-analysis

Weight deficit / average physical development

Obesity / body mass index

PON1

Ferré N., 2013 [14]

Spain

Spaniards

Obesity

12±3

36

110

Meets all criteria

FTO

Hallman D. M., 2005 [15]

USA, Texas, Louisiana

Non-hispanic whites

-

8-18

1081

Population is of no interest

African American

478

Grant SFA, 2008 [16]

USA, Philadelphia

Caucasians

Obesity

2-18

2270

418

Population is of no interest

African American

1424

578

Jacobsson J.A., 2008 [17]

Sweden

Swedes

Obesity

6-21

512

450

Meets all criteria

Müller T. D., 2008 [18]

Germany

Germans

Obesity / body mass index

10,71±3,1

178

519

The average age of the participants included in the control group is 24.58 ± 2.56 years

Xi B., 2010 [19]

China

Chinese

Obesity

6-18

2274

1229

Population is of no interest

Bollepalli S, 2010 [20]

USA, Ohio

Non-hispanic whites

-

14.26 ± 2.21

561

Population is of no interest

African American

14.21 ± 2.15

497

Okuda M., 2011 [21]

Japan

Japanese

Overweight, including obesity

10-13

133

133

Population is of no interest

Riffo B., 2011 [22]

Chile

American Indians Chile

Obesity

6-11

136

238

Population is of no interest

Zavattari P., 2011 [23]

Italy

Italians

Obesity

10.5±3.3

543

912

The average age of the participants included in the control group is 34 ± -7.1 years

Mangge H., 2011 [24]

Austria

Austrians

Obesity

12,5±3,1

103

268

Meets all criteria

Moleres A., 2012 [25]

Spain

Spaniards

Obesity

6-18

146

208

Meets all criteria

Luczynski W, 2012 [26]

Poland

Poles

Obesity

14.01±3.24

634

199

Meets all criteria

Dwivedi O.P., 2012 [9]

India

Hindus

Obesity / body mass index

11-17

2230

896

Population is of no interest

Pyrzak B., 2012 [27]

Poland

Poles

Obesity

12 - 18

24

136

Meets all criteria

Olza J., 2013 [28]

Spain

Spaniards

Obesity

6-15

241

290

Meets all criteria

Vasan S. K., 2013 [29]

India

Indians of southern India

Obesity

17.1 ± 1.9

1036

181

Population is of no interest

Ibba A., 2013 [30]

Italy

Sardinians

Obesity

4-20

543

412

Meets all criteria

Yang M., 2014 [31]

China

Chinese, cities of Beijing, Tianjin, Chongqing, Hangzhou, Shanghai and Nanning

Obesity

7-18

2600

1400

Population is of no interest

Lazopoulou N., 2015 [32]

Greece

Greeks

Obesity / body mass index

11.08±2.23

151

153

Insufficient data to analyze

Reuter C.P., 2016 [33]

Brazil

Brazilians

Obesity / body mass index

7-17

266

140

Population is of no interest

Zhang M.X., 2017 [34]

China

Han Chinese

Obesity

6-11

531

246

Population is of no interest

Abdelmajed S.S., 2017 [35]

Egypt

Egyptians

Obesity

9.93±3.06

100

100

Population is of no interest

Fu L.W., 2017 [36]

China

Chinese

Obesity

pupils

2306

1196

Population is of no interest

González‐Herrera L., 2018 [37]

Mexico

Mexicans

Obesity / body mass index

6-12

303

318

Population is of no interest

Yang Y, 2019 [38]

China

Chinese people of the northwestern part of the country

Obesity

pupils

170

200

Population is of no interest

Bondareva, E.A., 2013 [39]

Russia

The population of the city of Arkhangelsk and the Arkhangelsk region

body mass index

10 -17

66

25

Meets all criteria

Zavyalova L.G., 2011 [40]

Russia

Russians, population of Novosibirsk

Overweight

14-17

530

56

Meets all criteria

Shakirova A.T., 2017 [41]

Russia

Population of the Republic of Tatarstan

body mass index

7-17

81

114

Meets all criteria

Lebedeva E.N., 2019 [42]

 

Russia

Population of the Orenburg region

body mass index

adolescents

50

50

Insufficient data to analyze

Ubaidullayeva S.A., 2019 [43]

Uzbekistan

Uzbeks

Obesity

No data

54

41

Population is of no interest, insufficient data to analyze

 

 

Table 5 — Results of meta-analysis of the association of rs662 polymorphism of the PON1 gene

Genotype

Obesity, absolute

The control, absolute

 р

OR (95%CI)

Ferré N., 2013 (Spain, Spanish)

General inheritance model

QQ

47

18

 

1

QR

51

16

0.6

1.22 [0.56 – 2.66]

RR

12

2

0.3

2.23 [0.47 - 11.29]

p=0.31

 

 

Dominant inheritance model

QQ

47

18

0.45

1

QR+ RR

63

18

1.34 [0.63 – 2.85]

Recessive inheritance model

QQ+ QR

98

34

0.35

1

RR

12

2

2.08 [0.44 – 9.77]

 

The study by Huen K. et al was not included in the meta-analysis based on population criteria and the absence of a case-control study design. The study itself has been carried out twice on a cohort of 373 children: at the age of 2 and 5 years, anthropometric measurements were carried out, blood was taken for analysis of the activity of enzymes — participants in lipid metabolism. Genotyping was performed for rs662 of the PON1 gene. The direct link between genetic origin and obesity parameters was also examined. It was found that African roots were not significantly associated with higher BMI scores. These findings provide additional evidence that it is important to consider parentage in genetic studies of obesity. Interestingly, the associations observed at ages 2 and 5 were vastly different. For example, the association between rs662 and obesity was stronger and the effect of genetic origin was more pronounced at age 2 years compared with age 5 years [44]. These data are well supported by data from studies of twins and adopted children, demonstrating that the influence of heredity on the development of obesity is lowest at 5 years, when the influence of general environmental factors is strongest [45].

The data of studies for which the frequencies of genotypes and odds ratios for the rs9939609 polymorphism of the FTO gene were calculated are presented in tables (6-8) (general, dominant and recessive inheritance patterns) and in Figure 2. For data in publications by Luczynski W. et al, Pyrzak B. et al and Zavyalova L.G. with colleagues [26, 27, 40] for the genetic variant 23525T˃A of the FTO gene, when calculating the distribution of allele and genotype frequencies, a correspondence to the Hardy-Weinberg equilibrium of one of the studied groups has not been found. Therefore, these data were not included in the pooled sample.

Table 6 — Results of meta-analysis of the association of rs9939609 polymorphism of the FTO gene

First author, year

Genotype

Obesity / BMI, abs.

Control, abs.

р

OR (95%CI)

Jacobsson, J. A., 2008 [17]

TT

133

174

 

1

TA

206

244

0.5

1.105 [0.825-1.479]

AA

111

92

 

1.58 [1.105-2.255]

p=0.01638

 

 

Mangge, H., 2011 [24]

TT

75

31

 

1

TA

118

56

0.6

0.87 [0.515-1.473]

AA

75

16

0.055

1.9 [0.979-3.836]

p=0.08425

 

 

Moleres, A., 2012 [25]

TT

53

49

 

1

TA

106

76

0.3

1.29 [0.792-2.100]

AA

49

21

0.01799

2.16 [1.135-4.099]

p=0.02076

 

 

Ibba A., 2013 [30]

TT

84

183

 

1

TA

193

254

0.00188

1.65 [1.203-2.277]

AA

135

106

<0.0001

2.775 [1.931-3.987]

p=<0.0001

 

 

Olza, J., 2013 [28]

TT

72

90

 

1

TA

149

118

0.02246

1.58 [1.066-2.338]

AA

69

33

0.00023

2.6 [1.557-4.387]

p=0.00019

 

 

Bondareva, E.A. [39], 2013

TT

4

24

 

1

TA

13

32

0.15

2.45 [0.706-8.418]

AA

8

10

0.023

4.8 [1.173-19.637]

p=0.02408

 

 

Shakirova A.T., 2017 [41]

TT

30

34

 

1

TA

58

37

0.078

1.78 [0.936-3.373]

AA

26

10

0.01424

2.95 [1.223-7.098]

p=0.0104

 

 

Pooled data

TT

451

585

 

1

TA

843

817

0.00025

1.34 [1.145-1.564]

AA

473

288

<0.0001

2.13 [1.760-2.579]

p=<0.0001

 

 

Zavyalova L.G., 2011 [40]

TT

15

177

РХВ for the control group p=0.0067

TA

23

321

AA

18

92

Luczynski W, 2012 [26]

TT

51

187

For comparison group РХВ p=0.001326

TA

76

313

AA

72

134

Pyrzak, B., 2012 [27]

 

TT

35

5

РХВ for the control group p=0.032089

TA

67

6

AA

34

13

 

Statistically significant differences for the overweight or obese and normal weight groups of children were found for all studies included in the meta-analysis. In the pooled sample, the risk of developing obesity for homozygotes for allele A is doubled (p <0.0001). These data are consistent with the data of other researchers obtained for the populations of children in China, Japan, Europe and Africa, Brazil [18, 19, 21, 32, 35, 36, 38, 46, 47].

 

Table 7 — Results of meta-analysis of the association of rs9939609 polymorphism of the FTO gene for the dominant model

First author, year

Genotype

Obesity / BMI, abs.

Control, abs.

р

OR (95%CI)

Jacobsson, J. A., Danielsson, P., 2008

TT

133

174

0.13

1

TA+AA

317

336

1.23 [0.94 - 1.62]

Mangge, H., 2011

TT

75

31

0.69

1

TA+AA

193

72

1.1 [0.67 - 1.82]

Moleres, A., 2012

TT

53

49

0.1

 

TA+AA

155

97

1.48 [0.93 - 2.35]

Ibba A., 2013

TT

84

183

<0.0001

1

TA+AA

328

360

1.98 [1.47 - 2.67]

Olza, J., 2013

TT

72

90

0.0019

1

TA+AA

218

151

1.8 [1.24 - 2.62]

Bondareva, E.A., 2013

TT

4

24

0.07

1

TA+AA

21

42

3 [0.92 - 9.77]

Shakirova A.T., 2017

TT

30

34

0.0227

1

TA+AA

84

47

2.025 [1.10 - 3.72]

Pooled data

TT

451

585

< 0.0001

1

TA+AA

1316

1105

1.54 [1.33 - 1.79]

 

Table 8 — Results of a meta-analysis of the association of the rs9939609 polymorphism of the FTO gene for the recessive model

First author, year

Genotype

Obesity / BMI, abs.

Control, abs.

р

OR (95%CI)

Jacobsson, J. A., 2008

TT+TA

339

418

0.0124

1

AA

111

92

1.49 [1.09 - 2.03]

Mangge, H., 2011

TT+TA

193

87

0.0139

1

AA

75

16

2.11 [1.16 - 3.83]

Moleres, A., 2012

TT+TA

159

125

0.0345

1

AA

49

21

1.83 [1.04 - 3.22]

Ibba A., 2013

TT+TA

277

437

<0.0001

1

AA

135

106

2 [1.49 - 2.70]

Olza, J., 2013

TT+TA

221

208

0.0036

1

AA

69

33

1.97 [1.25 - 3.10]

Bondareva, E.A., 2013

TT+TA

17

56

0.08

1

AA

8

10

2.63 [0.898 - 7.73]

Shakirova A.T., 2017

TT+TA

88

71

0.07

1

AA

26

10

2.1 [0.95 - 4.64]

Pooled data

TT+TA

1294

1402

<0.0001

1

AA

473

288

1.78 [1.51 - 2.098]

 

According to calculations for the dominant model of inheritance, statistically significant differences for the two groups of children were revealed for the studies of Ibba A. et al, Olza J. et al, Shakirova A.T. For a sample common for all studies, the odds ratio for homo- and heterozygous genotypes for the polymorphic allele was 1.54 (p <0.0001) (Table 7).

The risk of developing obesity is increased for the homozygous genotype for allele A according to calculations for the general data (p <0.0001). For the recessive model of inheritance, statistically significant differences were not revealed only for the data of E. A. Bondareva (2013) with colleagues and A. T. Shakirova (2017) with colleagues. According to calculations in the other studies, the risk of obesity is increased by 1.5-2 times for the A23525A genotype (Table 8). These data are consistent with the data obtained for children of the Italian population [23] and the population of children in Uzbekistan [43]. The authors of [43] note that this genotype is 2.5 times more common in the group of obese children than in the control group. At the same time, the T allele, with a low level of relative risk and a high level of reliability, may indicate a protective value. Lebedeva E.N. (2019) [42] and co-authors found that allele A is a risk factor for the development of obesity for both the A23525A genotype and the T23525A genotype in the population of children and adolescents in the Orenburg region [42]. For the population of Chilean American Indian children, there are data indicating a relationship between the A allele of the FTO gene and insulin resistance [22].

In the population of adults in St. Petersburg, it was shown that the T23525T genotype of the FTO gene is more common in metabolically healthy people with obesity. The likelihood of metabolic health decreased in the presence of the A allele rs9939609 [7].

The literature contains data on different risks for rs9939609 for different populations of children and adolescents. Different risks of obesity for different genetic variants of the FTO gene have been identified for Caucasians and African Americans in Ohio, USA [20]. In his work, Grant SFA. et al. performed genotyping for 11 SNPs of the FTO gene. An association of different SNPs and haplotypes with the risk of obesity in the groups of Caucasians and African American children was revealed. The researchers argue that the association observed in children is almost identical to that of adults [16]. According to Hallman D. M. et al. the A / A rs9939609 genotype in the FTO gene is associated with a higher body mass index in non-Hispanic whites compared to African Americans in samples from Louisiana and Texas. The association can change with age, with the A / A genotype associated with a larger difference in body mass index in late adolescence than in childhood [15].

For children and adolescents of the Indian population for rs9939609, the findings are controversive. According to some data, the FTO gene is not associated with general obesity, but a correlation was found with the waist-hip ratio [29]. According to other authors, genetic variants of FTO influence the risk of obesity to a greater extent in children than in adults [9].

Endocrinological changes in adolescents can act as external factors influencing the development of obesity. It has been shown that the presence of the A allele of the FTO gene in the genotype is associated with a higher body mass index, fat mass index, and leptin concentrations in the blood in children aged 12 years, at the same time, there is a decrease in the association between the ages of 13-14 and its strengthening at the age of 17 [10].

Figure 2. Overall assessment of the odds ratio for dominant and recessive models for the rs9939609 polymorphism of the FTO gene

Jacobsson J. A. et al. and Zavyalova L.G. with colleagues [17, 40] presented data on genotypes for boys and girls for children with obesity and normal weight. Data on odds ratios for general, dominant and recessive inheritance models are presented in Tables 9-11 and in Figure 3. For the group of girls in the study by LG Zavyalova with colleagues, the correspondence with the Hardy-Weinberg equilibrium for the control group was not found, therefore, the genotype data of girls from this study were not included in the pooled sample.

 

Table 9 — The results of a meta-analysis of the association of the rs9939609 polymorphism of the FTO gene for boys and girls.

Group

Genotype

Obesity / BMI, abs.

Control, abs.

р

OR (95%CI)

Jacobsson J. A., 2008 (Sweden)

TT

62

94

 

1

TA

106

122

0.19

1.32 [0.872-1.991]

AA

59

44

0.00563

2.033 [1.227-3.369]

p=0.00625

 

 

TT

67

80

 

1

TA

92

122

0.62

0.9 [0.590-1.374]

AA

47

48

0.55

1.17 [0.697-1.960]

p=0.64797

 

 

Zavyalova L.G., 2011 (Russia)

TT

5

101

 

1

TA

10

174

0.79

1.16 [0.386-3.492]

AA

7

58

0.13

2.45 [0.740-8.031]

p=0.14413

 

 

TT

10

76

РХВ control group p=0.004935

TA

13

147

AA

11

34

Pooled data

TT

67

195

 

1

TA

116

296

0.46

1.14 [0.803-1.620]

AA

66

102

0.00268

1.88 [1.243-2.854]

p=0.004

 

 

TT

77

156

 

1

TA

105

269

0.19

0.79 [0.555-1.127]

AA

58

82

0.103

1.43 [0.929-2.210]

p=0.22

 

 

 

For the general inheritance model, statistically significant differences were found for groups of girls with obesity and normal weight (OR = 1.88, p = 0.00268). These data are consistent with the data of studies of Mexican and Polish populations of children and adolescents [26, 37].

Table 10 — The results of the meta-analysis of the association of the rs9939609 polymorphism of the FTO gene for boys and girls for the dominant model

Group

Genotype

Obesity / BMI, abs.

Control, abs.

р

OR (95%CI)

Jacobsson J. A., 2008 (Sweden)

TT

62

94

0.0375

1

TA+ AA

165

166

1.51 [1.02 - 2.22]

TT

67

80

0.905

1

TA+ AA

139

170

0.98 [0.66 - 1.45]

Zavyalova L.G., 2011 (Russia)

TT

5

101

0.45

1

TA+ AA

17

232

1.48 [0.53 - 4.12]

Pooled data

TT

67

195

0.09

1

TA+ AA

182

398

1.33 [0.96 - 1.85]

TT

77

156

0.72

1

TA+AA

163

351

0.94 [0.68 - 1.31]

 

Table 11 — The results of the meta-analysis of the association of the rs9939609 polymorphism of the FTO gene for boys and girls for a recessive model

Group

Genotype

Obesity / BMI, abs.

Control, abs.

р

OR (95%CI)

Jacobsson, J. A., 2008 (Sweden)

TT+ TA

168

216

0.0151

1

AA

59

44

1.72 [1.11 - 2.67]

TT+TA

159

202

0.34

1

AA

47

48

1.24 [0.79 - 1.96]

Zavyalova L.G., 2011 (Russia)

TT+ TA

15

275

0.098

1

AA

7

58

2.21 [0.86 - 5.67]

Pooled data

 

TT+ TA

183

491

0.0022

1

AA

66

102

1.74 [1.23 - 2.47]

TT+TA

182

425

0.0094

1

AA

58

82

1.65 [1.13 - 2.41]

 

Statistically significant differences both in the group of boys and in the group of girls were revealed for the recessive inheritance model in the pooled sample. The odds ratios for the A23525A genotype were 1.74 (p = 0.0022) and 1.65 (p = 0.0094) for girls and boys with obesity and normal weight, respectively. There were no statistically significant differences for the pooled sample for the dominant model.

Figure 3. Overall assessment of the odds ratio for the dominant and recessive models for the rs9939609 polymorphism of the FTO gene.

Analysis of data on polymorphisms rs662, rs2070895, rs149551759, rs9939609 in the development of diabetes in children and adolescents.

On this topic, we analyzed 578 articles, of which only 3 articles were devoted to the study of type I diabetes in children for rs662 and rs9939609. The data from these studies are presented in Table 12.

For genes of lipoprotein lipase and triacylglyceride lipase, data on the carriage of genetic variants rs2070895, rs149551759 and the development of diabetes in children were not found.

For the PON1 gene, 2 publications were found that met the required criteria, except for the territorial one [48, 49]. In a study by Fekih O. et al. conclude that the L55M and Q192R PON1 gene polymorphisms can be genetic markers of diabetic nephropathy in type I diabetes, as well as the LMQQ and MMQQ haplotypes [48]. Gallego P. H. et al. analyzed genotypes for PON1 gene polymorphisms Leu54Me and Gln192Arg. According to their studies, it can be argued that these SNPs are involved in the development of complications in type I diabetes. Researchers emphasize the relationship between the Leu54Met variants and the increase in plantar fascia thickness, which indicates the involvement of PON1 in the pathogenesis of collagen in diabetes [49]. In their study, Luczyński W. et al. showed that the carriage of the A allele of the rs9939609 variant of the FTO gene is associated with increased body weight in children with type I diabetes, especially in girls [50]. This article was not included in the meta-analysis due to a different study design.

 

Table 12 — Data from studies on the development of type I diabetes in children and adolescents for rs662 and rs9939609

First author, year

A country

Ethnicity

Age in years

Sample size, abs.

The control

Type I diabetes

PON1

Fekih O, 2017 [48]

Tunisia

Not specified

12.59 ± 5.38

91

116

Gallego P.H., 2008 [49]

Australia

Caucasians

15.4 ±1.9

172

159

FTO

Luczyński W., 2014 [50]

Poland

Poles

13.39±3.42

-

1119

 

Association between genetic variants rs662, rs2070895, rs149551759, rs9939609 and the risk of atherosclerosis in children and adolescents.

314 articles have been analyzed by keywords: "atherosclerosis in children and adolescents PON1 FTO LPL LIPC", "atherosclerosis children teens PON1 / LPL / FTO / LIPC", "PON1 / LPL / FTO / LIPC atherosclerosis in children" in the PubMed databases, Google Academia, eLIBRARY.RU. (table 3). There were no articles on the analysis of the rs662, rs2070895, rs149551759, rs9939609 polymorphisms in the development of atherosclerosis in children and adolescents. Research has focused on the study of atherosclerosis in adults and the elderly.

2 articles were devoted to the search for candidate genes for lipid metabolism disorders in children and adolescents [51, 52] Montali, A. et al studied 283 children of the Italian population 2-18 years old for LPL gene polymorphisms rs1801177, rs268, rs118204078, rs328, p.Ser45Asn and predisposition to the development of atherogenic dyslipidemia. Based on the results obtained, the authors of the article conclude that the presence of these polymorphisms may contribute to the development of hypertriglyceridemic traits in the subgroup of children with atherogenic dyslipidemia [51]. Agirbasli, M. et al conducted a study among 365 Turkish schoolchildren 12-15 years old to search for candidate genes for lipid levels. The analyzed genes included LPL (rs328) and LIPC (rs1800588). The children were divided into groups with high and low levels of lipoprotein cholesterol and triglycerides. No statistically significant differences were found for these polymorphisms for these groups [52].

 For PON1, it was shown that a decrease in its activity in serum is accompanied by an increase in oxidative stress and the risk of atherosclerosis [53].

 

Conclusion

Thus, based on the results of the meta-analysis, it can be concluded that the 23525T˃A polymorphism of the FTO gene is involved in metabolic pathways disorders in children and adolescents in Europe and the European part of Russia. The risk of developing obesity for homozygotes for allele A is doubled (p <0.0001). Statistically significant differences for children and adolescents with obesity and normal weight were found for dominant and recessive inheritance patterns (p <0.0001).

An analysis of genotype frequencies for boys and girls revealed statistically significant differences only for homozygotes for allele A in the girls group (p = 0.00268). Statistically significant differences both in the group of boys and in the group of girls were found for the recessive inheritance model. The odds ratios for the A23525A genotype were 1.74 (p = 0.0022) and 1.65 (p = 0.0094) for girls and boys with obesity and normal weight, respectively.

Based on the data of one publication for rs662 of the PON1 gene, no significant differences in the allele frequencies of genotypes for groups of children and adolescents with and without obesity were found.

To the best of authors knowledge, there are no studies of genetic variants rs662, rs2070895, rs149551759, rs9939609 in children and adolescents in Europe and the European part of Russia and the risk of atherosclerosis and diabetes.

Various genetic factors have an additive effect on changes in body mass index and obesity status in children. An individual who carries more risk alleles in genes associated with obesity has an increased risk of developing obesity [34, 38, 46]. It is likely that many of the individual polymorphisms have only a moderate effect on the risk of obesity, diabetes, or atherosclerosis, but their effects are enhanced in synergism with other genetic and environmental factors [54]. For example, it was shown that the effects of the rs9939609 FTO gene are more expressed among children with insufficient level of vitamin D [55]. It is also necessary to take into account the hormonal background of children and adolescents that affect metabolic pathways. In this regard, independent studies of children and adolescents of different age groups are possible [10, 54]. Studies of hereditary factors in the association of obesity with gene polymorphisms associated with the risk of its development among members of the same family is also important. It has been shown that the rs9939609 association of the FTO gene is higher if the student has a mother or a paternal or maternal grandmother is obese [33].

For the LPL gene, it was revealed that epigenetic disturbances in the intergenic LPL region in the placenta were associated with birth weight, fetal growth, and fat accumulation in childhood, which can lead to metabolic dysfunctions in later life [56].

The genome accumulates different genetic variants over generations. Epigenetic profiles determine which parts of it will be transcribed. Depending on the post-transcriptional regulators, various mature RNAs are formed from the original messenger RNA. Diet has been shown to affect DNA sequence variants, epigenetic profiles, and post-transcriptional regulation [31]. The influence of food products on the translation process leads to a final set of functional proteins, activated pathways and subsequent metabolites, which constitute the functional gene product. According to nutrigenetics, positive or negative phenotypic effects depend on food and lifestyle (Figure 4). Taste preferences and lifestyle are determined by culturally inherited customs and habits. In addition, diseases of metabolic disorders have been hidden for a long period of time due to food shortages and forced lifestyle. The masking effect is also associated with the Mediterranean diet, which has recently been increasingly mentioned in the literature. Modern living conditions and dietary habits lead to the activation of hidden genes [57]. However, the relationship of specific SNPs affecting metabolism for different ethnic groups needs further study [44, 57].

Figure 4. Impact of diet from genotype to phenotype [57].

This study was funded by the Ministry of Science and Higher Education of the Russian Federation №0852-2020-0028.

Conflicts of interest

No conflict of interests.

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Библиографическая ссылка

Мараховская Т. А., Алаа Хашим Абд Али, Амелина М. А., Лянгасова О.В., Александрова А. А., Машкина Е. В., Метаанализ ассоциации полиморфных вариантов генов FTO, LPL, LIPC, PON1 с риском развития ожирения у детей и подростков // «Живые и биокосные системы». – 2021. – № 36; URL: https://jbks.ru/archive/issue-36/article-5/. DOI: 10.18522/2308-9709-2021-36-5