Meta-Analysis Reveals the Association of Common Variants in the Uncoupling Protein (UCP) 1–3 Genes with Body Mass Index Variability

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Abstract

Background

The relationship between uncoupling protein ( UCP) 1–3 polymorphisms and susceptibility to obesity has been investigated in several genetic studies. However, the impact of these polymorphisms on obesity is still under debate, with contradictory results being reported. Until this date, no meta-analysis evaluated the association of UCP polymorphisms with body mass index (BMI) variability. Thus, this paper describe a meta-analysis conducted to evaluate if the -3826A/G ( UCP1); -866G/A, Ala55Val and Ins/Del ( UCP2) and -55C/T ( UCP3) polymorphisms are associated with BMI changes.

Methods

A literature search was run to identify all studies that investigated associations between UCP1-3 polymorphisms and BMI. Weighted mean differences (WMD) were calculated for different inheritance models.

Results

Fifty-six studies were eligible for inclusion in the meta-analysis. Meta-analysis results showed that UCP2 55Val/Val genotype was associated with increased BMI in Europeans [Random Effect Model (REM) WMD 0.81, 95% CI 0.20, 1.41]. Moreover, the UCP2 Ins allele and UCP3-55T/T genotype were associated with increased BMI in Asians [REM WMD 0.46, 95% CI 0.09, 0.83 and Fixed Effect Model (FEM) WMD 1.63, 95% CI 0.25, 3.01]. However, a decreased BMI mean was observed for the UCP2-866 A allele in Europeans under a dominant model of inheritance (REM WMD −0.18, 95% CI −0.35, −0.01). There was no significant association of the UCP1-3826A/G polymorphism with BMI mean differences.

Conclusions

The meta-analysis detected a significant association between the UCP2-866G/A, Ins/Del, Ala55Val and UCP3-55C/T polymorphisms and BMI mean differences.

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Most cited references 74

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Obesity: overview of an epidemic.

Nia Mitchell, Victoria A Catenacci, Holly Wyatt … (2011)

The obesity epidemic in the United States has proven difficult to reverse. We have not been successful in helping people sustain the eating and physical activity patterns that are needed to maintain a healthy body weight. There is growing recognition that we will not be able to sustain healthy lifestyles until we are able to address the environment and culture that currently support unhealthy lifestyles. Addressing obesity requires an understanding of energy balance. From an energy balance approach it should be easier to prevent obesity than to reverse it. Further, from an energy balance point of view, it may not be possible to solve the problem by focusing on food alone. Currently, energy requirements of much of the population may be below the level of energy intake than can reasonably be maintained over time. Many initiatives are underway to revise how we build our communities, the ways we produce and market our foods, and the ways we inadvertently promote sedentary behavior. Efforts are underway to prevent obesity in schools, worksites, and communities. It is probably too early to evaluate these efforts, but there have been no large-scale successes in preventing obesity to date. There is reason to be optimistic about dealing with obesity. We have successfully addressed many previous threats to public health. It was probably inconceivable in the 1950s to think that major public health initiatives could have such a dramatic effect on reducing the prevalence of smoking in the United States. Yet, this serious problem was addressed via a combination of strategies involving public health, economics, political advocacy, behavioral change, and environmental change. Similarly, Americans have been persuaded to use seat belts and recycle, addressing two other challenges to public health. But, there is also reason to be pessimistic. Certainly, we can learn from our previous efforts for social change, but we must realize that our challenge with obesity may be greater. In the other examples cited, we had clear goals in mind. Our goals were to stop smoking, increase the use of seatbelts, and increase recycling. The difficulty of achieving these goals should not be minimized, but they were clear and simple goals. In the case of obesity, there is no clear agreement about goals. Moreover, experts do not agree on which strategies should be implemented on a widespread basis to achieve the behavioral changes in the population needed to reverse the high prevalence rates of obesity. We need a successful model that will help us understand what to do to address obesity. A good example is the recent HEALTHY study. This comprehensive intervention was implemented in several schools and aimed to reduce obesity by concentrating on behavior and environment. This intervention delivered most of the strategies we believe to be effective in schools. Although the program produced a reduction in obesity, this reduction was not greater than the reduction seen in the control schools that did not receive the intervention. This does not mean we should not be intervening in schools, but rather that it may require concerted efforts across behavioral settings to reduce obesity. Although we need successful models, there is a great deal of urgency in responding to the obesity epidemic. An excellent example is the effort to get menu labeling in restaurants, which is moving rapidly toward being national policy. The evaluation of this strategy is still ongoing, and it is not clear what impact it will have on obesity rates. We should be encouraging efforts like this, but we must evaluate them rigorously. Once we become serious about addressing obesity, it will likely take decades to reverse obesity rates to levels seen 30 years ago. Meanwhile, the prevalence of overweight and obesity remains high and quite likely will continue to increase.

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Synthesis of genetic association studies for pertinent gene-disease associations requires appropriate methodological and statistical approaches.

Joseph Lau, Elias Zintzaras (2008)

The aim of the study was to consider statistical and methodological issues affecting the results of meta-analysis of genetic association studies for pertinent gene-disease associations. Although the basic statistical issues for performing meta-analysis are well described in the literature, there are remaining methodological issues. An analysis of our database and a literature review were performed to assess issues such as departure of Hardy-Weinberg equilibrium, genetic contrasts, sources of bias (replication validity, early extreme contradictory results, differential magnitude of effect in large versus small studies, and "racial" diversity), utility of cumulative and recursive cumulative meta-analyses. Gene-gene-environment interactions and methodological challenges of genome-wide association studies are discussed. Departures from Hardy-Weinberg equilibrium can be handled using sensitivity analysis or correction procedures. A spectrum of genetic models should be investigated in the absence of biological justification. Cumulative and recursive cumulative meta-analyses are useful to explore heterogeneity in risk effect in time. Exploration of bias leading to heterogeneity provides insight to postulated genetic effects. In the presence of bias, results should be interpreted with caution. Meta-analysis provides a robust tool to investigate contradictory results in genetic association studies by estimating population-wide effects of genetic risk factors in diseases and explaining sources of bias and heterogeneity.

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Meta-Analysis of Genetic Association Studies

Young-Ho Lee (2015)

The object of this review is to help readers to understand meta-analysis of genetic association study. Genetic association studies are a powerful approach to identify susceptibility genes for common diseases. However, the results of these studies are not consistently reproducible. In order to overcome the limitations of individual studies, larger sample sizes or meta-analysis is required. Meta-analysis is a statistical tool for combining results of different studies on the same topic, thus increasing statistical strength and precision. Meta-analysis of genetic association studies combines the results from independent studies, explores the sources of heterogeneity, and identifies subgroups associated with the factor of interest. Meta-analysis of genetic association studies is an effective tool for garnering a greater understanding of complex diseases and potentially provides new insights into gene-disease associations.

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Author and article information

Contributors

Zane Andrews: Role: Editor

Journal

Journal ID (nlm-ta): PLoS One

Journal ID (iso-abbrev): PLoS ONE

Journal ID (publisher-id): plos

Journal ID (pmc): plosone

Title: PLoS ONE

Publisher: Public Library of Science (San Francisco, USA )

ISSN (Electronic): 1932-6203

Publication date Collection: 2014

Publication date (Electronic): 7 May 2014

Volume: 9

Issue: 5

Electronic Location Identifier: e96411

Affiliations

[1 ]Endocrinology Division, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil

[2 ]Postgraduate Program in Medical Sciences, Endocrinology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil

Monash University, Australia

Author notes

* E-mail: dcmoreira@ 123456hcpa.ufrgs.br

Competing Interests: The authors have declared that no competing interests exist.

Conceived and designed the experiments: LAB DC. Analyzed the data: LAB TSA BMS APB. Wrote the paper: LAB LHC DC.

Article

Publisher ID: PONE-D-14-05487

DOI: 10.1371/journal.pone.0096411

PMC ID: 4013025

PubMed ID: 24804925

SO-VID: 1c9422aa-d5f2-4617-a72a-5d93db3a05e9

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

History

Date received : 5 February 2014

Date accepted : 5 April 2014

Page count

Pages: 10

Funding

This study was partially supported by grants from the Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (FAPERGS), the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), the Fundo de Incentivo à Pesquisa e Eventos (FIPE) at the Hospital de Clínicas de Porto Alegre and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Meta-Analysis Reveals the Association of Common Variants in the Uncoupling Protein (UCP) 1–3 Genes with Body Mass Index Variability

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Most cited references 74

Obesity: overview of an epidemic.

Synthesis of genetic association studies for pertinent gene-disease associations requires appropriate methodological and statistical approaches.

Meta-Analysis of Genetic Association Studies

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