Nowadays, obesity is one of the most prevalent human health problems. Research from the last 30 years has clarified the role of the imbalance between energy intake and expenditure, unhealthy lifestyle, and genetic variability in the development of obesity. More recently, the composition and metabolic functions of gut microbiota have been proposed as being able to affect obesity development. Here, we will report the current knowledge on the definition, composition, and functions of intestinal microbiota. We have performed an extensive review of the literature, searching for the following keywords: metabolism, gut microbiota, dysbiosis, obesity. There is evidence for the association between gut bacteria and obesity both in infancy and in adults. There are several genetic, metabolic, and inflammatory pathophysiological mechanisms involved in the interplay between gut microbes and obesity. Microbial changes in the human gut can be considered a factor involved in obesity development in humans. The modulation of the bacterial strains in the digestive tract can help to reshape the metabolic profile in the human obese host as suggested by several data from animal and human studies. Thus, a deep revision of the evidence pertaining to the use probiotics, prebiotics, and antibiotics in obese patients is conceivable

Modern biotechnologies often result in high-dimensional data sets with many more variables than observations (n≪p). These data sets pose new challenges to statistical analysis: Variable selection becomes one of the most important tasks in this setting. Similar challenges arise if in modern data sets from observational studies, e.g., in ecology, where flexible, non-linear models are fitted to high-dimensional data. We assess the recently proposed flexible framework for variable selection called stability selection. By the use of resampling procedures, stability selection adds a finite sample error control to high-dimensional variable selection procedures such as Lasso or boosting. We consider the combination of boosting and stability selection and present results from a detailed simulation study that provide insights into the usefulness of this combination. The interpretation of the used error bounds is elaborated and insights for practical data analysis are given. Stability selection with boosting was able to detect influential predictors in high-dimensional settings while controlling the given error bound in various simulation scenarios. The dependence on various parameters such as the sample size, the number of truly influential variables or tuning parameters of the algorithm was investigated. The results were applied to investigate phenotype measurements in patients with autism spectrum disorders using a log-linear interaction model which was fitted by boosting. Stability selection identified five differentially expressed amino acid pathways. Stability selection is implemented in the freely available R package stabs (http://CRAN.R-project.org/package=stabs). It proved to work well in high-dimensional settings with more predictors than observations for both, linear and additive models. The original version of stability selection, which controls the per-family error rate, is quite conservative, though, this is much less the case for its improvement, complementary pairs stability selection. Nevertheless, care should be taken to appropriately specify the error bound.

Mosaicism is increasingly recognized as a cause of developmental disorders with the advent of next-generation sequencing (NGS). Mosaic mutations of PIK3CA have been associated with the widest spectrum of phenotypes associated with overgrowth and vascular malformations. We performed targeted NGS using 2 independent deep-coverage methods that utilize molecular inversion probes and amplicon sequencing in a cohort of 241 samples from 181 individuals with brain and/or body overgrowth. We identified PIK3CA mutations in 60 individuals. Several other individuals ( n = 12) were identified separately to have mutations in PIK3CA by clinical targeted-panel testing ( n = 6), whole-exome sequencing ( n = 5), or Sanger sequencing ( n = 1). Based on the clinical and molecular features, this cohort segregated into three distinct groups: (a) severe focal overgrowth due to low-level but highly activating (hotspot) mutations, (b) predominantly brain overgrowth and less severe somatic overgrowth due to less-activating mutations, and (c) intermediate phenotypes (capillary malformations with overgrowth) with intermediately activating mutations. Sixteen of 29 PIK3CA mutations were novel. We also identified constitutional PIK3CA mutations in 10 patients. Our molecular data, combined with review of the literature, show that PIK3CA -related overgrowth disorders comprise a discontinuous spectrum of disorders that correlate with the severity and distribution of mutations.

Background: Autism spectrum disorders (ASDs) are relatively common neurodevelopmental conditions whose biological basis has been incompletely determined. Several biochemical markers have been associated with ASDs, but there is still no laboratory test for these conditions. Methods: We analyzed the metabolic profile of lymphoblastoid cell lines from 137 patients with neurodevelopmental disorders with or without ASDs and 78 normal individuals, using Biolog Phenotype MicroArrays. Results: Metabolic profiling of lymphoblastoid cells revealed that the 87 patients with ASD as a clinical feature, as compared to the 78 controls, exhibited on average reduced generation of NADH when tryptophan was the sole energy source. The results correlated with the behavioral traits associated with either syndromal or non-syndromal autism, independent of the genetic background of the individual. The low level of NADH generation in the presence of tryptophan was not observed in cell lines from non-ASD patients with intellectual disability, schizophrenia or conditions exhibiting several similarities with syndromal autism except for the behavioral traits. Analysis of a previous small gene expression study found abnormal levels for some genes involved in tryptophan metabolic pathways in 10 patients. Conclusions: Tryptophan is a precursor of important compounds, such as serotonin, quinolinic acid, and kynurenic acid, which are involved in neurodevelopment and synaptogenesis. In addition, quinolinic acid is the structural precursor of NAD⁺, a critical energy carrier in mitochondria. Also, the serotonin branch of the tryptophan metabolic pathway generates NADH. Lastly, the levels of quinolinic and kynurenic acid are strongly influenced by the activity of the immune system. Therefore, decreased tryptophan metabolism may alter brain development, neuroimmune activity and mitochondrial function. Our finding of decreased tryptophan metabolism appears to provide a unifying biochemical basis for ASDs and perhaps an initial step in the development of a diagnostic assay for ASDs.

Non-alcoholic fatty liver disease (NAFLD), which is emerging as a major public health issue worldwide, is characterized by a wide spectrum of liver disorders, ranging from simple fat accumulation in hepatocytes, also known as steatosis, to non-alcoholic steatohepatitis (NASH) and cirrhosis. At present, the pharmacological treatment of NAFLD is still debated and dietary strategies for the prevention and the treatment of this condition are strongly considered. Polyphenols are a group of plant-derived compounds whose anti-inflammatory and antioxidant properties are associated with a low prevalence of metabolic diseases, including obesity, hypertension, and insulin resistance. Since inflammation and oxidative stress are the main risk factors involved in the pathogenesis of NAFLD, recent studies suggest that the consumption of polyphenol-rich diets is involved in the prevention and treatment of NAFLD. However, few clinical trials are available on human subjects with NAFLD. Here, we reviewed the emerging existing evidence on the potential use of polyphenols to treat NAFLD. After introducing the physiopathology of NAFLD, we focused on the most investigated phenolic compounds in the setting of NAFLD and described their potential benefits, starting from basic science studies to animal models and human trials.

Lifestyle interventions remain the first-line treatment for non-alcoholic fatty liver disease (NAFLD), even if the optimal alimentary regimen is still controversial. The interest in antioxidants has increased over time, and literature reports an inverse association between nutrients rich in antioxidants and the risk of mortality due to non-communicable diseases, including NAFLD. Mediterranean diet (MD) is a model characterized by main consumption of plant-based foods and fish and reduced consumption of meat and dairy products. MD represents the gold standard in preventive medicine, probably due to the harmonic combination of many foods with antioxidant and anti-inflammatory properties. This regimen contributes substantially to the reduction of the onset of many chronic diseases as cardiovascular diseases, hypertension, type 2 diabetes mellitus, obesity, cancer, and NAFLD. The present review aims to clarify the intake of antioxidants typical of the MD and evaluate their effect on NAFLD.