Network signatures link hepatic effects of anti-diabetic interventions with systemic disease parameters

Nutrient-epigenome interactions: Implications for personalized nutrition against aging-associated diseases

Aging is a multifaceted process involving genetic and environmental interactions often resulting in epigenetic changes, potentially leading to aging-related diseases. Various strategies, like dietary interventions and calorie restrictions, have been employed to modify these epigenetic landscapes. A burgeoning field of interest focuses on the role of microbiota in human health, emphasizing system biology and computational approaches. These methods help decipher the intricate interplay between diet and gut microbiota, facilitating the creation of personalized nutrition strategies. In this review, we analysed the mechanisms related to nutritional interventions while highlighting the influence of dietary strategies, like calorie restriction and intermittent fasting, on microbial composition and function. We explore how gut microbiota affects the efficacy of interventions using tools like multi-omics data integration, network analysis, and machine learning. These tools enable us to pinpoint critical regulatory elements and generate individualized models for dietary responses. Lastly, we emphasize the need for a deeper comprehension of nutrient-epigenome interactions and the potential of personalized nutrition informed by individual genetic and epigenetic profiles. As knowledge and technology advance, dietary epigenetics stands on the cusp of reshaping our strategy against aging and related diseases.

Candidate genes associated with the effect of rosiglitazone on glycemic control and cardiovascular system in the treatment of type 2 diabetes mellitus

In the present study, candidate genes affected by rosiglitazone to exert glycemic control in the treatment of type 2 diabetes mellitus (T2DM) and associated with its adverse cardiovascular effects were identified using a bioinformatics analysis. The gene expression profiles of the dataset GSE36875 from the Gene Expression Omnibus database, including heart samples from 5 non-diabetic control mice (NC), 5 untreated diabetic mice (NH) and 5 rosiglitazone-treated diabetic mice (TH), were used to identify differentially expressed genes (DEGs) in the NC vs. NH, NC vs. TH and TH vs. NH groups. Subsequently, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enriched by the DEGs were determined. Furthermore, genes associated with the action of rosiglitazone were identified using Short Time-series Expression Miner, which were then subjected to enrichment analysis in gene ontology (GO) terms in the category biological process (BP), and networks of the GO terms, KEGG pathways and genes associated with the action of rosiglitazone were constructed. Finally, biological abnormalities associated with these genes were identified using WebGestalt. A set of 791 DEGs in three groups (NC vs. NH, NC vs. TH and NH vs. TH) were identified. Subsequently, 72 DEGs [e.g., apolipoprotein (Apo)A1, ApoA5, cytochrome P450 (Cyp)2c37, Cyp2J5, Cyp2b9 and Cyp2b10] were identified as genes associated with the action of rosiglitazone. In addition, a network of 13 GO terms in the category BP, 6 KEGG pathways and 41 genes associated with the action of rosiglitazone was constructed, with major terms/pathways including oxidation/reduction, lipid transport, peroxisome proliferator-activated receptor signaling pathway and metabolism of xenobiotics by Cyp. Finally, 15 biological abnormalities (including abnormal triglyceride levels, abnormal cholesterol homeostasis, abnormal lipid homeostasis) associated with these genes were identified. ApoA1, ApoA5, Cyp2c37, Cyp2J5, Cyp2b9 and Cyp2b10 were differently expressed after rosiglitazone treatment, which may be accountable for affecting cardiovascular outcomes and glycemic control in T2DM. The present results may expand the current understanding of the mechanism of action of rosiglitazone to exert glycemic control in T2DM, as well as its effects on the cardiovascular system.

Propelling the paradigm shift from reductionism to systems nutrition

The complex physiology of living organisms represents a challenge for mechanistic understanding of the action of dietary bioactives in the human body and of their possible role in health and disease. Animal, cell, and microbial models have been extensively used to address questions that could not be pursued experimentally in humans, posing an additional level of complexity in translation of the results to healthy and diseased metabolism. The past few decades have witnessed a surge in development of increasingly sensitive molecular techniques and bioinformatic tools for storing, managing, and analyzing increasingly large datasets. Application of such powerful means to molecular nutrition research led to a major leap in study designs and experimental approaches yielding experimental data connecting dietary components to human health. Scientific journals bear major responsibilities in the advancement of science. As primary actors of dissemination to the scientific community, journals can impose rigid criteria for publishing only sound, reliable, and reproducible data. Journal policies are meant to guide potential authors to adopt the most updated standardization guidelines and shared best practices. Such policies evolve in parallel with the evolution of novel approaches and emerging challenges and therefore require constant updating. We highlight in this manuscript the major scientific issues that led to formulating new, updated journal policies for Genes & Nutrition, a journal which targets the growing field of nutritional systems biology interfacing personalized nutrition and preventive medicine, with the ultimate goal of promoting health and preventing or treating disease. We focus here on relevant issues requiring standardization in nutrition research. We also introduce new sections on human genetic variation and nutritional bioinformatics which follow the evolution of nutritional science into the twenty-first century.

Jiang Tang Xiao Ke Granule, a Classic Chinese Herbal Formula, Improves the Effect of Metformin on Lipid and Glucose Metabolism in Diabetic Mice

In the present study, the hypoglycemic, hypolipidemic, and antioxidative effects of metformin (MET) combined with Jiang Tang Xiao Ke (JTXK) granule derived from the “Di Huang Tang” were evaluated in mice with type 2 diabetes mellitus (DM) induced by high-fat diet/streptozotocin. DM mice were orally treated with MET (0.19 g/kg) either alone or combined with different doses (1.75, 3.5, or 7 g/kg) of JTXK for 4 weeks. Results showed that the serum and hepatic glucose, lipids, and oxidative stress levels were elevated in DM mice, when compared with the normal mice. MET treatment decreased FBG and serum glucagon levels of DM mice. Combination treatment with MET and JTXK 3.5 g/kg increased the hypoglycemia and insulin sensitivity at 4 weeks when compared with the DM mice treated with MET alone. However, neither MET nor MET/JTXK treatment could completely reverse the hyperglycemia in DM mice. JTXK enhanced the serum triglyceride (TG) and hepatic lipid-lowering effect of MET in a dose-dependent manner in DM mice. JTXK 1.75 and 3.5 g/kg improved the hepatoprotective effect of MET in DM mice. Synergistic effect of combination treatment with MET and JTXK on antioxidant stress was also found in DM mice compared with MET alone.

Systems biology approaches to study the molecular effects of caloric restriction and polyphenols on aging processes

Worldwide population is aging, and a large part of the growing burden associated with age-related conditions can be prevented or delayed by promoting healthy lifestyle and normalizing metabolic risk factors. However, a better understanding of the pleiotropic effects of available nutritional interventions and their influence on the multiple processes affected by aging is needed to select and implement the most promising actions. New methods of analysis are required to tackle the complexity of the interplay between nutritional interventions and aging, and to make sense of a growing amount of -omics data being produced for this purpose. In this paper, we review how various systems biology-inspired methods of analysis can be applied to the study of the molecular basis of nutritional interventions promoting healthy aging, notably caloric restriction and polyphenol supplementation. We specifically focus on the role that different versions of network analysis, molecular signature identification and multi-omics data integration are playing in elucidating the complex mechanisms underlying nutrition, and provide some examples on how to extend the application of these methods using available microarray data.