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Open Journal of Clinical and
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Research Article - Open Access, Volume 3

UCP2 45bp Ins/Del gene polymorphism in association with
overweight and obesity: A meta-analysis

Bin Ni1; Wei Zhang1; Xiaoqing Zhang1; Bo Liang1; Yan Shu2*

1Department of General Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China.

2Health Management Center, The Second Hospital of Nanchang University, Nanchang, China.

*Corresponding Author: Yan Shu
Health Management Center, The Second Hospital of Nanchang University, No. 1 MinDe Road, Nanchang 330006, China.
Email: 1150055027@qq.com

Received : Mar 20, 2023

Accepted : Apr 25, 2023

Published : Apr 28, 2023

Archived : www.jclinmedimages.org

Copyright : © Shu Y (2023).

Abstract

Uncoupling protein (UCP) is a mitochondrial inner-membrane protein that is involved in energy homeostasis. In human tissues, UCP2 is widely expressed, acts as an uncoupling agent for oxidative phosphorylation, and is involved in the regulation of metabolism and ATP production. The association between UCP2 45bp Ins/Del gene polymorphism and the risk of overweight and obesity remains controversial and requires further evaluation. A meta-analysis of 12,224 subjects in 20 articles from PubMed, Embase, and China National Knowledge Infrastructure was performed to assess the association of UCP2 45bp Ins/Del gene polymorphism with the risk of overweight and obesity. The results of the meta-analysis showed that the UCP2 45bp Ins/Del gene polymorphism was significantly associated with genetic susceptibility to overweight and obesity only in the recessive model (odds ratio [OR]=1.24, 95% confidence interval [CI]=1.07-1.43, P=0.004), while the rest of the models did not show an association (P﹥0.05). However, the subgroup analysis of ethnicity showed that, in Asian populations, UCP2 45bp Ins/Del gene polymorphism was associated with genetic susceptibility to overweight and obesity in the allelic (OR=1.18, 95%CI=1.02-1.36, P=0.027), dominant (OR=1.20, 95%CI=1.02-1.41, P=0.030), and heterozygote (OR=1.19, 95%CI=1.01-1.41, P=0.043) models, respectively. No significant associations were found in the Caucasian population (P﹥0.05), and there was significant heterogeneity between the studies. We also performed subgroup analysis according to whether the subjects were adults and found significant associations only in the recessive (OR=1.19, 95% CI=1.01-1.41, P=0.011) and homozygote (OR=1.24, 95% CI=1.04-1.48, P=0.017) models in the adult group, while no significant associations were found in the other groups (P﹥0.05). UCP2 45bp Ins/Del gene polymorphism, which is significantly associated with genetic susceptibility to overweight and obesity in Asian populations, is not significantly associated with genetic susceptibility to obesity in Caucasian populations.

Keywords: Uncoupling proteins(UCPs); Gene polymorphism; Overweight; Obesity; Meta-analysis.

Citation: Ni B, Zhang W, Zhang X, Liang B, Shu Y. UCP2 45bp Ins/Del gene polymorphism in association with overweight and obesity: A meta-analysis. Open J Clin Med Images. 2023; 3(1): 1109.

Introduction

With economic development, people’s lifestyles have gradually changed, and the number of overweight and obese individuals has increased annually. Since the 1970s, obesity has become prevalent in developed countries, and the number of obese individuals worldwide has increased more than six times in the past 40 years, totaling more than 600 million individuals. Since 1975 and in the next 39 years, the global obesity rate (body mass index ≥ 30 kg/m2) increased from 3.2% to 10.8% and from 6.4% to 14.9% in women. If the trend continues, it is expected that, by 2025, 18% of men and 21% of women worldwide will be obese [1]. Overweight and obesity are not only important risk factors for metabolic and cardiovascular diseases but are also significantly associated with the risk of certain types of cancer (e.g., liver, kidney, prostate, colon, ovarian, breast), depression, and Alzheimer’s disease. Moreover, the death and disability caused by obesity significantly increase the national economic burden, and the problems it poses have become a major challenge worldwide [2,3]. Being overweight and obese are equally important in child and adolescent populations. In the past 30 years, the global situation of obesity in children and adolescents has become critical, with obesity detection rates increasing in many European and American countries and some Asian countries [1]. Overweight and obesity are mainly due to the fact that energy intake is greater than consumption, energy is stored in the body in the form of fat, and many factors can affect the body’s energy metabolism, among which genes are a well-known cause.

Uncoupling Proteins (UCPs) are thought to be involved in regulating glucose/lipid metabolism and energy homeostasis processes and are essentially a group of mitochondrial anion carrier proteins located in the inner mitochondrial membrane. As a candidate gene for obesity, Fleury et al. were the first to investigate the UCP2 gene. The Homo sapiens UCP2 gene is located on chromosome 11q13 and consists of 8 exons and 7 introns, with a length of 8174. UCP2 is widely expressed in human tissues and is an uncoupling agent for oxidative phosphorylation, which is involved in the regulation of lipid metabolism and ATP production, and disruption of UCP2 expression in the adipose tissue can lead to overweight and obesity [4,5]. UCP2 gene polymorphisms (Aal55Val, 45bp insertion/deletion, and -866G/A) have been extensively studied in relation to overweight and obesity, but showed conflicting results. Among these, information on the biological effects of UCP2 45bp Ins/Del gene polymorphism is still limited. Therefore, this meta-analysis aimed to assess the effects of UCP2 45bp Ins/Del gene polymorphism on the risk of overweight and obesity.

Methods

Search strategy

The following three databases were searched: PubMed, Embase, and China National Knowledge Infrastructure (CNKI). The search terms included “uncoupling protein 2,” “UCP2,” “polymorphism,” “genotype,” “alleles,” “obesity,” “overweight,” and “BMI.” The deadline for the search was September 3, 2021, for Chinese and English literature published as electronic papers, and reference back was used to find additional literature for inclusion in the study.

Inclusion and exclusion criteria

Studies meeting the following criteria were included in the meta-analysis: (1) case-control, cohort, or cross-sectional studies assessed the association between UCP2 45bp Ins/Del gene polymorphism and overweight and obesity; (2) sufficient information was provided in the text to calculate the frequency distribution of the genotype of interest or that of the allele of interest; (3) subjects were recruited from the same race during the same period; (4) if data were reported repeatedly, the most complete datasets were included; and (5) the genotype distribution of controls obeyed the Hardy–Weinberg equilibrium. Duplicate literature, reviews, abstracts, correspondence, animal studies, non-case-control studies, and non-UCP2 45bp Ins/Del gene polymorphisms in relation to genetic susceptibility to overweight and obesity were excluded from this study.

Quality assessment of included studies

The Newcastle-Ottawa Scale was used to assess the quality of each included study. Scores ≥ 7 were considered high quality.

Data extraction

The articles were evaluated, and data were independently extracted by two authors. Disagreements were resolved by consensus through discussion. The information extracted included the following in order: name of the first author, year of publication, country and ethnicity, number of cases and controls, frequency of cases and control genotypes, and whether the study population consisted of children and adolescents.

Statistical analysis

The Hardy–Weinberg equilibrium of the UCP2 45bp Ins/Del genotype distribution in the control group was tested using the Pearson chi-square test, and a P-value < 0.05 was considered to deviate from the Hardy–Weinberg equilibrium. Literature deviating from the Hardy–Weinberg equilibrium was excluded from the study. A combined odds ratio (OR) with 95% confidence interval (CI) was calculated to assess the association between the UCP2 45bp Ins/Del gene polymorphism and the risk of genetic susceptibility to overweight and obesity in five models (allelic, dominant, recessive, heterozygote, and homozygote models). The significance of the combined OR was determined using the Z-test. I2 was used to assess the heterogeneity between studies. When a random-effects model was used as the combined method, heterogeneity was considered significant if I2>50%; otherwise, heterogeneity was considered not significantly different, and a fixed-effects model was used. Subgroup analyses were performed for race in each of the five genetic models. A Begg’s funnel plot was used to identify publication bias. All statistical analyses were performed using Stata 16.0 (StataCorp LLC, College Station, TX, USA). P-values < 0.05 were considered statistically significant (two-tailed).

Results

Search results

A total of 459 articles were obtained by searching PubMed, Embase, and CNKI databases. After excluding 52 duplicate articles, 407 articles were obtained. A total of 378 articles that were reviews, letters, laboratory studies, or not related to the current study were excluded. Based on the abovementioned inclusion and exclusion criteria, nine full-text articles were excluded. Twenty eligible articles were included in the meta-analysis [6-25] (Figure 1).

Study demographics

A total of 20 relevant papers were included in the meta-analysis, covering 12 countries, including 5750 cases and 6474 controls, and of these 20 papers, five were studies on Asian populations, and 15 were studies on Caucasian populations, with studies published between 1999 and 2020 (Table 1).

Meta-analysis

The results of the meta-analysis showed that the UCP2 45bp Ins/Del gene polymorphism was significantly associated with genetic susceptibility to overweight and obesity only in the recessive model (OR=1.24, 95%CI=1.07-1.43, P=0.004; Figure 2), while the other models did not show an association (P﹥0.05). However, the subgroup analysis of ethnicity showed that, in Asian populations, UCP2 45bp Ins/Del gene polymorphism was allelic (OR=1.18, 95%CI=1.02-1.36, P=0.027; Figure 3), dominant (OR=1.20, 95%CI=1.02-1.41, P=0.030; Figure 4), and heterozygote (OR=1.19, 95%CI=1.01-1.41, P=0.043; Fig.5), respectively, which were significantly associated with genetic susceptibility to overweight and obesity in the model. No significant associations were found in the Caucasian population (P﹥0.05), and there was significant heterogeneity between studies. We also performed subgroup analysis according to whether the subjects were adults and found significant associations only in the recessive (OR=1.19, 95% CI=1.01-1.41, P=0.011; Figure 6) and homozygote (OR=1.24, 95% CI=1.04-1.48, P=0.017; Figure 7) models in the adult group, while no significant associations were found in the other groups (P﹥0.05) (Table 2).

Influence analysis

To assess the stability of the study results, we performed sensitivity analyses, excluding one study at a time and combining the remaining studies. The results showed that, under all mentioned genetic models, no single study had an excess effect on any pooled effect.

Publication bias evaluation

After excluding the key factors of heterogeneity between studies, no publication bias regarding the association between polymorphisms and overweight and obesity was detected in any of the abovementioned genetic models using funnel plots (Figure 8).

Table 1: Relevant features of the studies included in the meta-analysis.
Study Country Year Ethnicity Age Case Control NOS score
DD DI II DD DI II
Dalgaard et al.[6] Denmark 1999 Caucasian adults 371 293 80 432 364 76 8
Evans et al.[7] Germany 2000 Caucasian adults 145 130 30 286 198 24 6
Esterbauer et al [8] Austria 2001 Caucasian adults 179 132 29 117 115 24 8
Nieters et al.[9] Germany 2002 Caucasian adults 88 58 8 78 57 16 8
Maestrini et al.[10] Italy 2003 Caucasian adults 211 124 25 51 42 10 7
Feng et al.[11] China 2004 Asian adults 75 27 1 138 31 2 7
Marti et al.[12] Spain 2004 Caucasian adults 83 63 11 92 52 6 7
Berentzen et al.[13] Denmark 2005 Caucasian adults 277 227 64 356 294 67 8
Hong et al.[14] China 2005 Asian children 165 35 1 190 36 4 8
Ochoa et al.[15] Spain 2007 Caucasian children 103 71 18 79 76 11 7
Kring et al.[16] Denmark 2008 Caucasian adults 104 94 24 166 127 21 8
Liu et al.[17] China 2012 Asian adults 463 141 12 696 199 15 7
Papazoglou et al.[18] Greece 2012 Caucasian adults 96 55 7 60 27 4 8
Csernus et al.[19] Hungary 2013 Caucasian children 338 303 68 339 251 47 7
Oguzkan et al.[20] turkey 2013 Caucasian children 46 31 23 65 30 5 7
Say et al.[21] Malaysia 2014 Asian adults 181 77 7 505 145 11 7
Gul et al.[22] Turkey 2017 Caucasian children 151 96 21 93 68 24 7
Kaabi et al.[23] Saudi Arabia 2018 Caucasian adults 58 23 5 30 32 3 7
Surniyantoro et al.[24] Indonesia 2018 Asian adults 68 25 7 68 29 3 7
Verdi et al.[25] Turkey 2020 Caucasian children 72 29 1 53 29 5 6

OR: Odds Ratio; CI: Confidence Interval; FEM: Fixed-Effects Model; REM: Random-Effects Model.

Table 2: Pooled measures for the associations of the UCP2 45bp Ins/Del gene polymorphism with overweight and obesity.
Population Inherited model Numbers of cases/controls Pooled OR (95% CI) I2(%)
FEM P value REM P value
Overall Allele 11500/12948 1.08 (1.02, 1.15) 0.011 1.06 (0.95, 1.19) 0.296 67.5
Dominant 5750/6474 1.07 (0.99, 1.15) 0.096 1.05 (0.92, 1.19) 0.484 59.1
Recessive 5750/6474 1.24 (1.07, 1.43) 0.004 1.21 (0.97, 1.53) 0.098 46.3
Heterozygote 5308/6096 1.03 (0.96, 1.12) 0.397 1.02 (0.91, 1.15) 0.704 45.4
Homozygote 3716/4272 1.24 (1.06, 1.43) 0.005 1.20 (0.93, 1.56) 0.161 54.9
Asian Allele 2570/4144 1.18 (1.02, 1.36) 0.027 1.18 (1.02, 1.37) 0.025 0
Dominant 1285/2072 1.20 (1.02, 1.41) 0.03 1.20 (1.01, 1.43) 0.035 6.4
Recessive 1285/2072 1.27 (0.76, 2.11) 0.358 1.30 (0.77, 2.19) 0.32 0
Heterozygote 1257/2037 1.19 (1.01, 1.41) 0.043 1.20 (0.99, 1.45) 0.059 12.6
Homozygote 980/1632 1.31 (0.78, 2.18) 0.303 1.35 (0.80, 2.27) 0.261 0
Caucasian Allele 8930/8334 1.06 (0.99, 1.14) 0.072 1.03 (0.89, 1.18) 0.706 73.5
Dominant 4465/4402 1.03 (0.95, 1.12) 0.448 1.00 (0.85, 1.16) 0.971 64.6
Recessive 4465/4402 1.23 (1.06, 1.43) 0.007 1.20 (0.92, 1.56) 0.171 56.7
Heterozygote 4051/4059 1.00 (0.91, 1.09) 0.914 0.97 (0.85, 1.11) 0.672 47.8
Homozygote 2736/2640 1.23 (1.05, 1.44) 0.009 1.18 (0.88, 1.59) 0.275 64.1
Adults Allele 8356/10138 1.08 (1.01, 1.16) 0.03 1.07 (0.95, 1.21) 0.248 59.7
Dominant 4178/5069 1.06 (0.97, 1.16) 0.164 1.06 (0.91, 1.22) 0.461 58
Recessive 4178/5069 1.25 (1.02, 1.48) 0.011 1.24 (1.02, 1.52) 0.031 14.7
Heterozygote 3868/4787 1.03 (0.94, 1.13) 0.51 1.03 (0.89, 1.19) 0.691 52.1
Homozygote 2709/3357 1.24 (1.04, 1.48) 0.017 1.23 (0.96, 1.57) 0.1 34.6
Children Allele 3144/2810 1.08 (0.96, 1.22) 0.189 1.04 (0.76, 1.42) 0.795 81
Dominant 1572/1405 1.07 (0.92, 1.24) 0.358 1.02 (0.76, 1.37) 0.897 67.6
Recessive 1572/1405 1.20 (0.92, 1.58) 0.181 1.09 (0.53, 2.23) 0.81 75.1
Heterozygote 1440/1309 1.05 (0.89, 1.22) 0.582 1.00 (0.81, 1.25) 0.979 34.9
Homozygote 1007/915 1.23 (0.93, 1.63) 0.152 1.06 (0.49, 2.30) 0.874 77.5
Figure 1:

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Figure 7:

Discussion

UCP2 plays an important role in the development and treatment of overweight and obesity, as an obesity candidate gene involved in the regulation of glucose/lipid metabolism and energy homeostasis. UCP2 affects the susceptibility to obesity and obesity-related diseases by decreasing the activity or expression of these UCPs, thereby increasing oxidative phosphorylation coupling to reduce energy expenditure. Thus, the expression/activity levels of UCP2 influence the relationship between UCP2 gene polymorphisms and obesity [26]. The 3'UTR region of the UCP2 Ins/Del polymorphic gene, which is only 158 bp away from the transcription termination codon, may function by participating in mRNA processing or transcriptional stability, and lower transcript stability may result in lower UCP2 protein translocation [11]. These three polymorphisms are currently the most studied in the UCP2 gene: 45bp Ins/Del in exon 8, missense variant in exon 4 (rs660339, Ala55Val, C/T), and one in the promoter region (rs659366, 866G/A) [12]. The association of one of these 45bp Ins/Del polymorphisms with overweight and obesity remains highly controversial. Therefore, we systematically summarized 20 eligible case-control studies using the largest sample size available for this meta-analysis to assess the association between UCP2 45bp Ins/Del with genetic susceptibility and overweight and obesity and guide future studies.

The analysis showed that the UCP2 45bp Ins/Del gene polymorphism was significantly associated with genetic susceptibility to overweight and obesity only in the recessive model (OR=1.24, 95%CI=1.07-1.43, P=0.004), but race-specific subgroup analysis showed that the UCP2 45bp Ins/Del gene polymorphism was significantly associated with genetic susceptibility to overweight and obesity in Asian populations in the allelic (OR=1.18, 95%CI=1.02-1.36, P=0.027), dominant (OR=1.20, 95%CI=1.02-1.41, P=0.030), and heterozygote (OR=1.19, 95%CI=1.01-1.41, P=0.043) models, and no significant association was found in Caucasian populations.

Brondani's study showed similar findings to this study that polymorphism is significantly associated with increased BMI in Asian populations [27]. However, in a study on Caucasian populations, the findings of Brondani et al. contradicted our findings by suggesting that the UCP2 45bp Ins/Del gene polymorphism was significantly associated with obesity in Caucasian populations [28]. Comparative results from other studies have shown that individuals carrying the II genotype and Ins allele are at higher risk of obesity than those carrying the DD genotype compared to other genotypes or alleles [17,21,29]. Moreover, Ins allele carriers have a higher BMI in some populations [30]. Conversely, Zhang et al. and Surniyantoro et al. showed that 45bp Ins/Del gene polymorphism is not a risk factor for overweight and obesity [24,31]. The nutritional characteristics of populations may influence the relationship between genetic variation and obesity, and food and cultural habits and environmental factors differ for each race, which may influence the association between UCP polymorphisms and obesity [24,32]. Therefore, future studies on obesity gene polymorphisms should consider environmental factors and dietary habits. Moreover, there are numerous genes associated with obesity [33], and each population has different genetic variants in its gene pool; these factors may also play a role in obesity. Kring et al. concluded that there is a lack of significant correlation between genetic variants and BMI because obesity is a mixed phenotype, and several other proxies for overweight and obesity are available, such as waist circumference, waist circumference for a given BMI, sagittal abdominal diameter, and waist-to-hip ratio [15], which should be considered in future studies. Some researchers have suggested that the effect of insertion polymorphisms may be age-related and associated with late-onset obesity [8]. Therefore, we conducted a subgroup analysis of the study population divided into child and adult groups for age and only found significant associations in the recessive (OR=1.19, 95% CI=1.01-1.41, P=0.011) and homozygote (OR=1.24, 95% CI=1.04-1.48, P=0.017) models in the adult group, while the other groups did not show significant associations. A study by Gul et al. concluded that UCP2 exon 8 Ins/Del had no significant effect on the risk of obesity in adolescents, which is similar to our findings, and that low HDL cholesterolemia may be associated with the Ins allele [12]. Gender-stratified UCP2 45bp Ins/Del gene polymorphism analysis by Surniyantoro et al. and Papazoglou et al. showed that gene polymorphisms had opposite effects on male and female populations, with the II genotype and I allele leading to reduced UCP2 expression and increased body weight in the male population. Conversely, in the female population, the UCP2 45bp Ins/Del gene polymorphism is recessively associated with obesity [22,24].

Heterogeneity between studies is a matter of concern, and high heterogeneity was observed in all our analyses of genetic models of the association of the UCP2 45bp Ins/Del gene polymorphism with overweight and obesity. After stratifying the analysis by ethnicity, heterogeneity was significantly lower in the analysis of Asian populations; however, significant heterogeneity remained in the analysis of Caucasian populations, suggesting some other confounding factors in the study on Caucasian populations. The sources of heterogeneity were worth exploring; therefore, a regression analysis was implemented, including covariates such as age, sex, and sample size. However, none of these covariates individually or jointly explained the observed heterogeneity. Study quality, general characteristics of participants, representation of participants, gene-environment interactions, and genotyping methods may contribute to heterogeneity. Without additional information on the metabolic and clinical characteristics of the articles analyzed, the role of these factors in the sources of heterogeneity is difficult to describe accurately.

Therefore, the results of the current meta-analysis should be interpreted with caution. First, the definition of cases is not uniform across studies; in some studies, cases are defined as obese populations, morbidly obese populations, or mixed populations of overweight and obesity. Moreover, in some relevant studies, the threshold values of overweight or obesity were different. Second, due to technical limitations, we only retrieved studies published in English and Chinese, which may lead to certain omissions. Lastly, our analysis revealed significant heterogeneity among studies on Caucasian populations.

Conclusion

Our study showed a significant association between UCP2 45bp Ins/Del gene polymorphism and genetic susceptibility to overweight and obesity in Asian populations but not in Caucasian populations. Factors such as age, sex, environmental factors, and dietary habits may influence the accuracy of this association. To obtain strong evidence, a larger sample size and more adequate information are needed to conduct more detailed analytical studies.

Declarations

Acknowledgment: This research was funded by grants from the National Natural Science Foundation of China (No. 82160578), Natural Science Foundation of Jiangxi Province, China (No. 20212BCJ23024 and 20202BAB216029), Health Department of Jiangxi Province, China (No. 20198020), and Education Department of Jiangxi Province, China (No. GJJ190019).

Conflict of interest: The authors have no conflict of interests.

Date availability statement: The data that support the findings of this study are available from the corresponding author upon reasonable request.

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