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Analysis of lifestyle and metabolic predictors of visceral obesity with Bayesian Networks.

ABSTRACT: BACKGROUND: The aim of this study was to provide a framework for the analysis of visceral obesity and its determinants in women, where complex inter-relationships are observed among lifestyle, nutritional and metabolic predictors. Thirty-four predictors related to lifestyle, adiposity, body fat distribution, blood lipids and adipocyte sizes have been considered as potential correlates of visceral obesity in women. To properly address the difficulties in managing such interactions given our limited sample of 150 women, bootstrapped Bayesian networks were constructed based on novel constraint-based learning methods that appeared recently in the statistical learning community. Statistical significance of edge strengths was evaluated and the less reliable edges were pruned to increase the network robustness. To allow accessible interpretation and integrate biological knowledge into the final network, several undirected edges were afterwards directed with physiological expertise according to relevant literature. RESULTS: Extensive experiments on synthetic data sampled from a known Bayesian network show that the algorithm, called Recursive Hybrid Parents and Children (RHPC), outperforms state-of-the-art algorithms that appeared in the recent literature. Regarding biological plausibility, we found that the inference results obtained with the proposed method were in excellent agreement with biological knowledge. For example, these analyses indicated that visceral adipose tissue accumulation is strongly related to blood lipid alterations independent of overall obesity level. CONCLUSIONS: Bayesian Networks are a useful tool for investigating and summarizing evidence when complex relationships exist among predictors, in particular, as in the case of multifactorial conditions like visceral obesity, when there is a concurrent incidence for several variables, interacting in a complex manner. The source code and the data sets used for the empirical tests are available at http://www710.univ-lyon1.fr/~aaussem/Software.html.

SUBMITTER: Aussem A

PROVIDER: S-EPMC2955704 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

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Analysis of lifestyle and metabolic predictors of visceral obesity with Bayesian Networks.

Aussem Alex A Tchernof André A de Morais Sérgio Rodrigues SR Rome Sophie S

BMC bioinformatics 20100928

<h4>Background</h4>The aim of this study was to provide a framework for the analysis of visceral obesity and its determinants in women, where complex inter-relationships are observed among lifestyle, nutritional and metabolic predictors. Thirty-four predictors related to lifestyle, adiposity, body fat distribution, blood lipids and adipocyte sizes have been considered as potential correlates of visceral obesity in women. To properly address the difficulties in managing such interactions given ou ...[more]

PMID: 20920208

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Project description:Maternal obesity is linked with increased adverse outcomes for mother and fetus. However, the metabolic impact of excessive fat accumulation within the altered hormonal context of pregnancy is not well understood. We used a murine model of obesity, the high fat diet-fed C57BL/6J mouse to determine adipose tissue-mediated molecular mechanisms driving metabolic dysfunction throughout pregnancy. Remarkably, obese mice exhibited a normalization of visceral fat accumulation at late-stage pregnancy (-53%, P<0.001 E18.5) to achieve levels comparable in mass (per gram of body weight) to that of non pregnant, control diet fed mice. Moreover, whilst obese pregnant mice showed a marked glucose intolerance and apparent insulin resistance at mid-stage pregnancy (E14.5), glucose homeostasis converged with that of lean pregnant mice at late-stage pregnancy, suggesting an unexpected amelioration of the worsening metabolic dysfunction in obese pregnant mice. Transcriptomic analysis of the late-stage visceral fat indicated reduced de novo lipogenic drive (Me1, Fasn, Scd1, Dgat2), retinol metabolism (Rdh11, Rbp4) and inflammation (Mcp1, Tnfα) in obese pregnant mice that was confirmed functionally by their lower adipose proinflammatory macrophage density. Elevated expression of estrogen receptor a (ERα) in visceral adipose tissue was identified as potential unifying mechanism for the transcriptional changes and reduced adiposity of late stage obese pregnancy. Support for a role for ERα was provided by experiments showing that the ERα selective agonist PPT suppressed lipogenesis in primary mouse adipocytes and suppressed Me1, Fasn, SCD1 and Dgat2 mRNA levels in mature female human ChubS7 clonal fat cells. Our data reveal a novel role for elevated visceral adipocyte estrogen signaling as a protective mechanism against visceral fat hypertrophy and inflammation in late pregnancy. Pregnant high fat, pregnant control fat, non pregnant high fat, non pregnant control fat. Five biologial replictes each (20 samples).

Dataset Information

Analysis of lifestyle and metabolic predictors of visceral obesity with Bayesian Networks.

Publications

Analysis of lifestyle and metabolic predictors of visceral obesity with Bayesian Networks.

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