The translation of the growing increase of findings emerging from basic nutritional science into meaningful and clinically relevant dietary advices represents nowadays one of the main challenges of clinical nutrition. From nutrigenomics to deep phenotyping, many factors need to be taken into account in designing personalized and unbiased nutritional solutions for individuals or population sub-groups. Likewise, a concerted effort among basic, clinical scientists and health professionals will be needed to establish a comprehensive framework allowing the implementation of these new findings at the population level. In a world characterized by an overwhelming increase in the prevalence of obesity and associated metabolic disturbances, such as type 2 diabetes and cardiovascular diseases, tailored nutrition prescription represents a promising approach for both the prevention and management of metabolic syndrome. This review aims to discuss recent works in the field of precision nutrition analyzing most relevant aspects affecting an individual response to lifestyle/nutritional interventions. Latest advances in the analysis and monitoring of dietary habits, food behaviors, physical activity/exercise and deep phenotyping will be discussed, as well as the relevance of novel applications of nutrigenomics, metabolomics and microbiota profiling. Recent findings in the development of precision nutrition are highlighted. Finally, results from published studies providing examples of new avenues to successfully implement innovative precision nutrition approaches will be reviewed.
Consumption of red raspberries has been reported to exert acute beneficial effects on postprandial glycemia, insulinemia, triglyceridemia, and cytokine levels in metabolically disturbed subjects. In a two-arm parallel-group, randomized, controlled trial, 59 subjects with overweight or abdominal obesity and with slight hyperinsulinemia or hypertriglyceridemia were randomized to consume 280 g/day of frozen raspberries or to maintain their usual diet for 8 weeks. Primary analyses measured metabolic differences between the groups. Secondary analyses performed with omics tools in the intervention group assessed blood gene expression and plasma metabolomic changes following the raspberry supplementation. The intervention did not significantly affect plasma insulin, glucose, inflammatory marker concentrations, nor blood pressure. Following the supplementation, 43 genes were differentially expressed, and several functional pathways were enriched, a major portion of which were involved in the regulation of cytotoxicity, immune cell trafficking, protein signal transduction, and interleukin production. In addition, 10 serum metabolites were found significantly altered, among which β-alanine, trimethylamine N-oxide, and bioactive lipids. Although the supplementation had no meaningful metabolic effects, these results highlight the impact of a diet rich in raspberry on the immune function and phospholipid metabolism, thus providing novel insights into potential immune-metabolic pathways influenced by regular raspberry consumption.
Objectives Altered enteroendocrine cell (EEC) function in obesity and type 2 diabetes is not fully understood. Understanding the transcriptional program that controls EEC differentiation is important because some EEC types harbor significant therapeutic potential for type 2 diabetes. Methods EEC isolation from jejunum of obese individuals with (ObD) or without (Ob) type 2 diabetes was obtained with a new method of cell sorting. EEC transcriptional profiles were established by RNA-sequencing in a first group of 14 Ob and 13 ObD individuals. EEC lineage and densities were studied in the jejunum of a second independent group of 37 Ob, 21 ObD and 22 non obese (NOb) individuals. Results The RNA seq analysis revealed a distinctive transcriptomic signature and a decreased differentiation program in isolated EEC from ObD compared to Ob individuals. In the second independent group of ObD, Ob and NOb individuals a decreased GLP-1 cell lineage and GLP-1 maturation from proglucagon, were observed in ObD compared to Ob individuals. Furthermore, jejunal density of GLP-1-positive cells was significantly reduced in ObD compared to Ob individuals. Conclusions These results highlight that the transcriptomic signature of EEC discriminate obese subjects according to their diabetic status. Furthermore, type 2 diabetes is associated with reduced GLP-1 cell differentiation and proglucagon maturation leading to low GLP-1-cell density in human obesity. These mechanisms could account for the decrease plasma GLP-1 observed in metabolic diseases.
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