Over the past 2 decades there has been increasing evidence supporting an important contribution from food-derived advanced glycation end products (AG

The human intestine is home to a diverse range of bacterial and fungal species, forming an ecological community that contributes to normal physiology and disease susceptibility. Here, the fungal microbiota (mycobiome) in obese and non-obese subjects was characterized using Internal Transcribed Spacer (ITS)-based sequencing. The results demonstrate that obese patients could be discriminated by their specific fungal composition, which also distinguished metabolically “healthy” from “unhealthy” obesity. Clusters according to genus abundance co-segregated with body fatness, fasting triglycerides and HDL-cholesterol. A preliminary link to metabolites such as hexadecanedioic acid, caproic acid and N-acetyl-L-glutamic acid was also found.Mucor racemosusandM. fuscuswere the species more represented in non-obese subjects compared to obese counterparts. Interestingly, the decreased relative abundance of theMucorgenus in obese subjects was reversible upon weight loss. Collectively, these findings suggest that manipulation of gut mycobiome communities might be a novel target in the treatment of obesity.

Neurons in the mature human central nervous system (CNS) perform a wide range of motor, sensory, regulatory, behavioral, and cognitive functions. Such diverse functional output requires a great diversity of CNS neuronal and non-neuronal populations. Metabolomics encompasses the study of the complete set of metabolites/low-molecular-weight intermediates (metabolome), which are context-dependent and vary according to the physiology, developmental state, or pathologic state of the cell, tissue, organ, or organism. Therefore, the use of metabolomics can help to unravel the diversity-and to disclose the specificity-of metabolic traits and their alterations in the brain and in fluids such as cerebrospinal fluid and plasma, thus helping to uncover potential biomarkers of aging and neurodegenerative diseases. Here, we review the current applications of metabolomics in studies of CNS aging and certain age-related neurodegenerative diseases such as Alzheimer disease, Parkinson disease, and amyotrophic lateral sclerosis. Neurometabolomics will increase knowledge of the physiologic and pathologic functions of neural cells and will place the concept of selective neuronal vulnerability in a metabolic context.

Gut microbiota has been suggested to affect lipid metabolism. The objective of this study was to characterize the faecal microbiota signature and both short chain fatty acids (SCFAs) and bile acids (BA) profile of hypercholesterolemic subjects. Microbiota composition, SCFAs, BA and blood lipid profile from male volunteers with hypercholesterolemia (HC) and normocholesterolemia (NC) were determined by 16S rDNA sequencing, HPLC, GC and NMR, respectively. HC subjects were characterized by having lower relative abundance of Anaeroplasma (0.002% vs 0.219%, p-value = 0.026) and Haemophilus (0.041% vs 0.078%, p-value = 0.049), and higher of Odoribacter (0.51% vs 0.16%; p-value = 0.044). Correlation analysis revealed that Anaeroplasma and Haemophilus were associated to an unfavourable lipid profile: they correlated negatively to cholesterol and triglycerides related biomarkers and the ratio total to high density lipoprotein (HDL) cholesterol, and positively to HDL size. Odoribacter displayed an opposite behaviour. Faecal SCFAs profile revealed higher abundance of isobutyric (2.76% vs 0.82%, p-value = 0.049) and isovaleric acid (1.32% vs 0.06%, p-value = 0.016) in HC. Isobutyric acid correlated positively with Odoribacter and lipid parameters indicative of an unfavourable profile. BA profile did not show differences between groups. It was concluded that HC subjects showed a particular faecal bacterial signature and SCFAs profile associated with their lipid profile.