Abstract
Adipocyte size (AS) shows asymmetric distribution related to current metabolic state, e.g., adipogenesis or lipolysis. We profiled AS distribution using different statistical approaches in offspring (F1) of control (C) and obese (MO) mothers (F0) with and without F0 or F1 exercise. Offspring from F0 exercise were designated CF0ex and MOF0ex. Exercised F1 of sedentary mothers were designated CF1ex and MOF1ex. F1 retroperitoneal fat cross-sectional AS was measured by median, cumulative distributions, data dispersion and extreme values based on gamma distribution modeling. F1 metabolic parameters: body weight, retroperitoneal fat, adiposity index (AI), serum leptin, triglycerides (TG) and insulin resistance index (IRI) were measured. Male and female F1 AS showed different cumulative distribution between C and MO (p < 0.0001) therefore comparisons were performed among C, CF0ex and CF1ex groups and MO, MOF0ex and MOF1ex groups. MO AI was higher than C (p < 0.05) and male MOF1ex AI lower than MO (p < 0.05). Median AS was higher in male and female MO vs. C (p < 0.05). Male and female MOF0ex and MOF1ex reduced median AS (p < 0.05). Lower AS dispersion was observed in male CF1ex and MOF1ex vs. CF0ex and MOF0ex, respectively. MO reduced small and increased large adipocyte proportions vs. C (p < 0.05); MOF0ex increased small and MOF1ex the proportion of large adipocytes vs. MO (p < 0.05). MOF0ex reduced male IRI and female TG vs. MO (p < 0.05). MOF1ex reduced male and female leptin (p < 0.05); CF1ex reduced male leptin (p < 0.05). Conclusions: several factors, diet, physical activity and gender modify AS distribution. Conventional AS distribution methods normally do not include analyzes of extreme, large and small adipocytes, which characterize different phenotypes. Maternal high fat diet affects F1 AS distribution, which was programmed during development. F0ex and F1ex have gender specific F1 beneficial effects. AS distribution characterization helps explain adipose tissue metabolic changes in different physiological conditions and will aid design of efficacious interventions to prevent and/or recuperate adverse developmental programming outcomes. Finally, precise identification of effects of specific interventions as exercise of F0 and/or F1 are needed to improve outcomes in obese women and their obesity prone offspring.
Highlights
We (Zambrano et al, 2010, 2016; Rodriguez et al, 2012; Santos et al, 2015; Vega et al, 2015; Bautista et al, 2017) and others (Sen and Simmons, 2010; Elshenawy and Simmons, 2016; Lecoutre et al, 2016; Wankhade et al, 2016) have studied the rat as an experimental animal model of the metabolic consequences of maternal (F0) obesity (MO) in offspring (F1)
The results show that F0 and F1 exercise result in different beneficial metabolic profiles and several dissimilar adipocyte size (AS) distribution patterns
Very small AS is associated with preadipocyte differentiation into new adipocytes, whilst large sizes are related to fat accumulation in mature adipocytes (Welte, 2015)
Summary
We (Zambrano et al, 2010, 2016; Rodriguez et al, 2012; Santos et al, 2015; Vega et al, 2015; Bautista et al, 2017) and others (Sen and Simmons, 2010; Elshenawy and Simmons, 2016; Lecoutre et al, 2016; Wankhade et al, 2016) have studied the rat as an experimental animal model of the metabolic consequences of maternal (F0) obesity (MO) in offspring (F1). Variable physiological conditions can profoundly either reduce or increase adipose tissue lipid storage capacity by up to 15-fold (Berry et al, 2013). Adipocytes isolated by collagenase digestion can be accurately analyzed by Coulter counting or flow cytometry (Hirsch and Gallian, 1968; McLaughlin et al, 2014; Fang et al, 2015). This approach has many disadvantages due to the potential cell damage by protease activity, incomplete cell separation and lack of specificity of automatic particle detection. AS obtained from isolated adipocytes is often reported as multimodal histograms (Bradshaw et al, 2003), whose statistical distribution is frequently empirically modeled by sophisticated differential equations (Jo et al, 2009, 2010, 2013), which potentially discourage their generalized use
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