ABSTRACT
BACKGROUND: Obesity configures a pathophysiological profile that predisposes the development of metabolic and cardiovascular diseases, critically impacting public health. The chronic dysregulation of immuno-metabolic components triggered by pediatric obesity is a common but scarcely understood aspect of the disease. Peroxisome proliferator-activated receptors (PPARs) are a group of transcription factors essential for energy and immune homeostasis of different tissues. Besides, the glucagon-like peptide-1 receptor (GLP-1R) activation influences insulin secretion, but also regulates the cytokine profile possibly mediated through a PPAR isotype. However, the role of PPARs and GLP-1R in leukocytes from obese pediatric patients remains unclear. Therefore, we examined the expression of PPARs isotypes and GLP-1R in leukocytes, and its correlation with metabolic, hormonal, inflammatory, and anthropometric markers in an obese pediatric population. RESULTS: Obese children and adolescents presented a significant increase in anthropometric and body composition parameters, TG, VLDL, TG/HDL, android fat (%)/gynoid fat (%) (A/G%) index, and HOMA score when compared with the control group. Obese participants exhibited a pro-inflammatory profile with an augment of IL-8 (p = 0,0081), IL-6 (p = 0,0005), TNF-α (p = 0,0004), IFN-γ (p = 0,0110), MCP-1 (p = 0,0452), and adipsin (p = 0,0397), whereas displayed a reduction of adiponectin (p = 0,0452). The expression of PPARα and GLP-1R was lower in the leukocytes from obese participants than in lean subjects. Furthermore, PPARα correlates negatively with TNF-α (p = 0,0383), while GLP-1R did not show correlation with any inflammatory variable. However, both receptors correlate negatively with the abdominal skinfold. Although PPARß/δ expression was similar between groups, it was negatively associated with IL-8 levels (p = 0,0085). CONCLUSIONS: PPARα and PPARß/δ expression are negatively correlated with the proinflammatory markers TNF-α and IL-8, respectively, suggesting participation in the regulation of inflammation which was observed to be altered in pediatric obesity. Furthermore, PPARα and GLP-1R are downregulated in leukocytes from obese participants. The low expression of both receptors is correlated with an increase in abdominal skinfold, suggesting a role in fat distribution that could indirectly affect cytokine secretion from different immune and adipose cells, likely triggering an inflammatory profile as a consequence of obesity. Altogether, these findings may impact the understanding and implementation of PPARα or GLP-1R agonists in the clinic.
ABSTRACT
OBJECTIVE: The overall appearance of an aged skin is characterized by a combination of several attributes such as wrinkles, brown spots and sagging. Our objective was to develop and validate a statistical framework to assess the overall anti-ageing benefits of products/procedures. METHOD: Different skin attributes were evaluated by a clinical grader and combined using a Principal Component Analysis (PCA). The Skin Ageing Index was defined as the normalized projection of the clinical grading values on the first PCA axis. Several Skin Indexes were built by grouping specific parameters related to a skin condition such as overall ageing, wrinkles and sagging. The method was validated following two steps. Firstly, a clinical study was performed on 173 Caucasian women and the correlation between the Skin Indexes and the volunteers' real and perceived age was estimated. Secondly, a double-blinded placebo-controlled randomized study was performed on 87 Caucasian women to assess the efficacy of an anti-wrinkle cream containing retinol, hyaluronic acid and dihydroxymethylchromone. Facial wrinkles were clinically evaluated and a Wrinkle Index was built. RESULTS: All indexes were highly correlated with the real and the perceived age (0.57 ≤ Pearson R ≤ 0.92, P-value ≤ 0.05). Finally, the Wrinkle Index provides documented evidence that the tested product significantly reduced the appearance of wrinkles versus the placebo and the baseline assessment (-23.53% after 4 weeks, -27.83% after 8 weeks). CONCLUSION: Skin ageing Indexes capture information relevant to the visual transformation of facial skin with age, while providing documented product benefits. These tools may enable a simpler and more consistent comparison of anti-ageing products/procedures.