Antonio González-Chávez

Hyperleptinemia is associated with parameters of low-grade systemic inflammation and metabolic dysfunction in obese human beings

Leptin is an adipose tissue-derived hormone that has been involved in hypothalamic and systemic inflammation, altered food-intake patterns, and metabolic dysfunction in obese mice. However, it remains unclear whether leptin has a relationship with parameters of systemic inflammation and metabolic dysfunction in humans. We thus evaluated in a cross-sectional study the circulating levels of leptin in 40 non-obese and 41 obese Mexican individuals, examining their relationship with tumor necrosis factor alpha (TNF-α), interleukin (IL) 12, IL-10, central obesity, serum glucose and insulin levels, and serum triglyceride and cholesterol concentrations. Circulating levels of leptin, TNF-α, IL-12, IL-10, and insulin were measured by ELISA, while concentrations of glucose, triglyceride, and cholesterol were determined by enzymatic assays. As expected, serum levels of leptin exhibited a significant elevation in obese individuals as compared to non-obese subjects, showing a clear association with increased body mass index (r = 0.4173), central obesity (r = 0.4678), and body fat percentage (r = 0.3583). Furthermore, leptin also showed a strong relationship with serum TNF-α (r = 0.6989), IL-12 (r = 0.3093), and IL-10 (r = −0.5691). Interestingly, leptin was also significantly related with high concentrations of fasting glucose (r = 0.5227) and insulin (r = 0.2229), as well as elevated levels of insulin resistance (r = 0.3611) and circulating triglyceride (r = 0.4135). These results suggest that hyperleptinemia is strongly associated with the occurrence of low-grade systemic inflammation and metabolic alteration in obese subjects. Further clinical research is still needed to determine whether hyperleptinemia may be a potential marker for recognizing the advent of obesity-related metabolic disorders in human beings.

Reduced Systemic Levels of IL-10 Are Associated with the Severity of Obstructive Sleep Apnea and Insulin Resistance in Morbidly Obese Humans

Obstructive sleep apnea (OSA) has been related to elevation of inflammatory cytokines and development of insulin resistance in morbidly obese (MO) subjects. However, it is still unclear whether the systemic concentration of anti-inflammatory mediators is also affected in MO subjects directly related to the severity of OSA and level of insulin resistance. Normal weight and MO subjects were subjected to overnight polysomnography in order to establish the severity of OSA, according to the apnea-hypopnea index (AHI). Blood samples were obtained for estimation of total cholesterol and triglycerides, insulin, glucose, insulin resistance, tumor necrosis factor alpha (TNF-α), interleukin 12 (IL12), and interleukin 10 (IL-10). Serum levels of IL-10 were significantly lower in MO subjects with OSA than in MO and control individuals without OSA. Besides being inversely associated with serum TNF-α and IL-12, decreased IL-10 levels were significantly related to increased AHI, hyperinsulinemia, and insulin resistance. Serum IL-10 is significantly reduced in morbidly obese subjects with severe OSA while also showing a clear relationship with a state of hyperinsulinemia and insulin resistance probably regardless of obesity in the present sample. It may be of potential clinical interest to identify the stimulatory mechanisms of IL-10 in obese individuals with OSA.

Nonalcoholic fatty liver disease can be predicted by retinal vascular changes in patients with obesity without hypertension or diabetes

Objective To evaluate the utility of predicting nonalcoholic fatty liver disease (NAFLD) and obesity by retinal vascular changes (RVC) found in fundoscopy and to determine whether this is related to a low-grade inflammatory process. Methods We carried out a cross-sectional analysis that included 152 (ages 18–45 years) patients divided into four groups: NAFLD and BMI less than 25, absence of NAFLD and BMI less than 25, NAFLD and BMI more than 30, and absence of NAFLD and BMI more than 30. Retinal fundoscopy, hepatic ultrasound, metabolic profile, and cytokine measurement were performed. We calculated odds ratio [95% confidence interval (CI)], performed diagnostic utility tests, and carried out a 2k factorial analysis. Results Obesity was associated with RVC (odds ratio: 21.25; 95% CI: 8.79–51.4) and NAFLD [25 (9.07–72.6)]. NAFLD was associated with RVC [11.24 (4.98–26.48)], and the prediction of NAFLD showed a sensitivity of 75% (95% CI: 68–82) and a specificity of 81% (75–86); when RVC-obesity were combined, sensitivity increased to 90% (88–91.7), with a specificity of 85% (84–85.8). C-reactive protein was associated with the three factors, suggesting an independent contribution. Thin patients with RVC and NAFLD had higher concentrations of interleukin-2, interleukin-6, tumor necrosis factor-&agr;, and interferon-&ggr;. Conclusion NAFLD in patients with obesity without diabetes or hypertension can be predicted by RVC, a noninvasive technique carried out by eye fundoscopy. NAFLD alone can drive inflammatory conditions in the absence of obesity that manifests as RVC.

Family history and obesity in youth, their effect on acylcarnitine/aminoacids metabolomics and non-alcoholic fatty liver disease (NAFLD). Structural equation modeling approach

Background Structural equation modeling (SEM) can help understanding complex functional relationships among obesity, non-alcoholic fatty liver disease (NAFLD), family history of obesity, targeted metabolomics and pro-inflammatory markers. We tested two hypotheses: 1) If obesity precedes an excess of free fatty acids that increase oxidative stress and mitochondrial dysfunction, there would be an increase of serum acylcarnitines, amino acids and cytokines in obese subjects. Acylcarnitines would be related to non-alcoholic fatty disease that will induce insulin resistance. 2) If a positive family history of obesity and type 2 diabetes are the major determinants of the metabolomic profile, there would be higher concentration of amino acids and acylcarnitines in patients with this background that will induce obesity and NAFLD which in turn will induce insulin resistance. Methods/Results 137 normoglycemic subjects, mean age (SD) of 30.61 (8.6) years divided in three groups: BMI<25 with absence of NAFLD (G1), n = 82; BMI>30 with absence of NAFLD (G2), n = 24; and BMI>30 with NAFLD (G3), n = 31. Family history of obesity (any) was present in 53%. Both models were adjusted in SEM. Family history of obesity predicted obesity but could not predict acylcarnitines and amino acid concentrations (effect size <0.2), but did predict obesity phenotype. Conclusion Family history of obesity is the major predictor of obesity, and the metabolic abnormalities on amino acids, acylcarnitines, inflammation, insulin resistance, and NAFLD.

Correction: Family history and obesity in youth, their effect on acylcarnitine/ aminoacids metabolomics and non-alcoholic fatty liver disease (NAFLD). Structural equation modeling approach (PLoS ONE (2018) 13:2 (e0193138) DOI: 10.1371/journal.pone.0193138)

[This corrects the article DOI: 10.1371/journal.pone.0193138.].

Metabolic Syndrome and Cardiovascular Disease: A Health Challenge in Mexico

Metabolic Syndrome (MetS) is a cluster of risk factors that, taken alone or synergically, are independent predictors of type 2 diabetes and cardiovascular disease (CVD), which are both major public health problems that requires urgent containment actions. Current controversies regarding MetS are focused on ascertain the unifying explanation of molecular and pathophysiological mechanisms originating the syndrome, involving insulin resistance and low-grade chronic inflammation. This review aims to present the clinical relevance of MetS and its complications, as well as the hypotheses addressing its etiopathogenic relation with CVD. We conclude that health policies should emphasize basic research promotion, timely detection and early treatment of MetS, which will help to reduce the risk of CVD and their impact on public health and health-care related costs.