Associations between olfactory pathway gene methylation marks, obesity features and dietary intakes

Abstract Background Olfaction is an important sense influencing food preferences, appetite, and eating behaviors. This hypothesis-driven study aimed to assess associations between olfactory pathway gene methylation signatures, obesity features, and dietary intakes. Methods A nutriepigenomic analysis was conducted in 474 adults from the Methyl Epigenome Network Association (MENA) project. Anthropometric measurements, clinical data, and serum metabolic profiles of the study population were obtained from structured databases of the MENA cohorts. Habitual dietary intake was assessed using a validated semiquantitative food frequency questionnaire. DNA methylation was measured in circulating white blood cells by microarray (Infinium Human Methylation 450 K BeadChips). FDR values (p < 0.0001) were used to select those CpGs that showed the best correlation with body mass index (BMI) and waist circumference (WC). Pathway analyses involving the characterization of genes involved in the olfactory transduction system were performed using KEGG and pathDIP reference databases. Results Overall, 15 CpG sites at olfactory pathway genes were associated with BMI (p < 0.0001) and WC (p < 0.0001) after adjustments for potential confounding factors. Together, methylation levels at the15 CpG sites accounted for 22% and 20% of the variability in BMI and WC (r 2 = 0.219, p < 0.001, and r 2 = 0.204, p < 0.001, respectively). These genes encompassed olfactory receptors (OR4D2, OR51A7, OR2T34, and OR2Y1) and several downstream signaling molecules (SLC8A1, ANO2, PDE2A, CALML3, GNG7, CALML6, PRKG1, and CAMK2D), which significantly regulated odor detection and signal transduction processes within the complete olfactory cascade, as revealed by pathway enrichment analyses (p = 1.94 × 10–10). Moreover, OR4D2 and OR2Y1 gene methylation patterns strongly correlated with daily intakes of total energy (p < 0.0001), carbohydrates (p < 0.0001), protein (p < 0.0001), and fat (p < 0.0001). Conclusions The results of this study suggest novel relationships between olfactory pathway gene methylation signatures, obesity indices, and dietary intakes

Guide for Current Nutrigenetic, Nutrigenomic, and Nutriepigenetic Approaches for Precision Nutrition Involving the Prevention and Management of Chronic Diseases Associated with Obesity

Chronic diseases, including obesity, are major causes of morbidity and mortality in most countries. The adverse impacts of obesity and associated comorbidities on health remain a major concern due to the lack of effective interventions for prevention and management. Precision nutrition is an emerging therapeutic approach that takes into account an individual's genetic and epigenetic information, as well as age, gender, or particular physiopathological status. Advances in genomic sciences are contributing to a better understanding of the role of genetic variants and epigenetic signatures as well as gene expression patterns in the development of diverse chronic conditions, and how they may modify therapeutic responses. This knowledge has led to the search for genetic and epigenetic biomarkers to predict the risk of developing chronic diseases and personalizing their prevention and treatment. Additionally, original nutritional interventions based on nutrients and bioactive dietary compounds that can modify epigenetic marks and gene expression have been implemented. Although caution must be exercised, these scientific insights are paving the way for the design of innovative strategies for the control of chronic diseases accompanying obesity. This document provides a number of examples of the huge potential of understanding nutrigenetic, nutrigenomic, and nutriepigenetic roles in precision nutrition

Recombinant adenoviral vectors turn on the type I interferon system without inhibition of transgene expression and viral replication

Recombinant adenovirus administration gives rise to transgene-independent effects caused by the ability of the vector to activate innate immunity mechanisms. We show that recombinant adenoviruses encoding reporter genes trigger IFN-alpha and IFN-beta transcription from both plasmacytoid and myeloid mouse dendritic cells. Interestingly, IFN-beta and IFN-alpha5 are the predominant transcribed type I IFN genes both in vitro and in vivo. In human peripheral blood leukocytes type I IFNs are induced by adenoviral vectors, with a preponderance of IFN-beta together with IFN-alpha1 and IFN-alpha5 subtypes. Accordingly, functional type I IFN is readily detected in serum samples from human cancer patients who have been treated intratumorally with a recombinant adenovirus encoding thymidine kinase. Despite inducing functional IFN-alpha release in both mice and humans, gene transfer by recombinant adenoviruses is not interfered with by type I IFNs either in vitro or in vivo. Moreover, IFN-alpha does not impair replication of wild-type adenovirus. As a consequence, cancer gene therapy strategies with defective or replicative-competent adenoviruses are not expected to be hampered by the effect of the type I IFNs induced by the vector itself. However, type I IFN might modulate antitumor and antiadenoviral immune responses and thus influence the outcome of gene immunotherapy

Gut Microbiota Differences According to Ultra-Processed Food Consumption in a Spanish Population

Ultra-processed foods (UPFs) consumption could affect gut microbiota diversity and profile. We aimed to evaluate the effects of UPFs on microbiota, considering the role of sex. The consumption of UPFs (using NOVA criteria) was assessed with a validated 137-item food-frequency questionnaire. Participants (n = 359) were classified into less than three servings per day (n = 96) of UPFs and more than five (n = 90). Women and men were subclassified following the same criteria. 16S rRNA sequencing was performed from DNA fecal samples, and differences in microbiota were analyzed using EdgeR. The relationship between UPFs and bacteria was assessed by Spearman correlation and comparison of tertiles of consumption. Women who consumed more than five servings/day of UPFs presented an increase in Acidaminococcus, Butyrivibrio, Gemmiger, Shigella, Anaerofilum, Parabacteroides, Bifidobacterium, Enterobacteriales, Bifidobacteriales and Actinobacteria and a decrease in Melainabacter and Lachnospira. Bifidobacterium, Bifidobacteriales and Actinobacteria was positively associated with pizza and Actinobacteria with industrially processed dairy in women. Men who consumed more than five servings/day presented an increase of Granulicatella, Blautia, Carnobacteriaceae, Bacteroidaceae, Peptostreptococcaceae, Bacteroidia and Bacteroidetes and a decrease of Anaerostipes and Clostridiaceae. Bacteroidia and Bacteroidetes correlated positively with industrially processed meat. This study suggests that UPFs may affect microbiota composition differently in women and men

Prediction of Blood Lipid Phenotypes Using Obesity-Related Genetic Polymorphisms and Lifestyle Data in Subjects with Excessive Body Weight

Background and Aim. Individual lipid phenotypes including circulating total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), high-density lipoprotein cholesterol (HDL-c), and triglycerides (TG) determinations are influenced by gene-environment interactions. The aim of this study was to predict blood lipid level (TC, LDL-c, HDL-c, and TG) variability using genetic and lifestyle data in subjects with excessive body weight-for-height. Methods. This cross-sectional study enrolled 304 unrelated overweight/obese adults of self-reported European ancestry. A total of 95 single nucleotide polymorphisms (SNPs) related to obesity and weight loss were analyzed by a targeted next-generation sequencing system. Relevant genotypes of each SNP were coded as 0 (nonrisk) and 1 (risk). Four genetic risk scores (GRS) for each lipid phenotype were calculated by adding the risk genotypes. Information concerning lifestyle (diet, physical activity, alcohol drinking, and smoking) was obtained using validated questionnaires. Total body fat (TFAT) and visceral fat (VFAT) were determined by dual-energy X-ray absorptiometry. Results. Overall, 45 obesity-related genetic variants were associated with some of the studied blood lipids. In addition to conventional factors (age, sex, dietary intakes, and alcohol consumption), the calculated GRS significantly contributed to explain their corresponding plasma lipid trait. Thus, HDL-c, TG, TC, and LDL-c serum concentrations were predicted by approximately 28% (optimism-corrected adj. R2=0.28), 25% (optimism-corrected adj. R2=0.25), 24% (optimism-corrected adj. R2=0.24), and 21% (optimism-corrected adj. R2=0.21), respectively. Interestingly, GRS were the greatest contributors to TC (squared partial correlation (PC2) = 0.18) and LDL-c (PC2 = 0.18) features. Likewise, VFAT and GRS had a higher impact on HDL-c (PC2 = 0.09 and PC2 = 0.06, respectively) and TG levels (PC2 = 0.20 and PC2 = 0.07, respectively) than the rest of variables. Conclusions. Besides known lifestyle influences, some obesity-related genetic variants could help to predict blood lipid phenotypes

Crosstalk between Gut Microbiota and Epigenetic Markers in Obesity Development: Relationship between <i>Ruminococcus</i>, BMI, and <i>MACROD2</i>/<i>SEL1L2</i> Methylation

Changes in gut microbiota composition and in epigenetic mechanisms have been proposed to play important roles in energy homeostasis, and the onset and development of obesity. However, the crosstalk between epigenetic markers and the gut microbiome in obesity remains unclear. The main objective of this study was to establish a link between the gut microbiota and DNA methylation patterns in subjects with obesity by identifying differentially methylated DNA regions (DMRs) that could be potentially regulated by the gut microbiota. DNA methylation and bacterial DNA sequencing analysis were performed on 342 subjects with a BMI between 18 and 40 kg/m2. DNA methylation analyses identified a total of 2648 DMRs associated with BMI, while ten bacterial genera were associated with BMI. Interestingly, only the abundance of Ruminococcus was associated with one BMI-related DMR, which is located between the MACROD2/SEL1L2 genes. The Ruminococcus abundance negatively correlated with BMI, while the hypermethylated DMR was associated with reduced MACROD2 protein levels in serum. Additionally, the mediation test showed that 19% of the effect of Ruminococcus abundance on BMI is mediated by the methylation of the MACROD2/SEL1L2 DMR. These findings support the hypothesis that a crosstalk between gut microbiota and epigenetic markers may be contributing to obesity development

Interaction between an ADCY3 Genetic Variant and Two Weight-Lowering Diets Affecting Body Fatness and Body Composition Outcomes Depending on Macronutrient Distribution: A Randomized Trial

The adenylate cyclase 3 (ADCY3) gene is involved in the regulation of several metabolic processes including the development and function of adipose tissue. The effects of the ADCY3 rs10182181 genetic variant on changes in body composition depending on the macronutrient distribution intake after 16 weeks of the dietary intervention were tested. The ADCY3 genetic variant was genotyped in 147 overweight or obese subjects, who were randomly assigned to one of the two diets varying in macronutrient content: a moderately-high-protein diet and a low-fat diet. Anthropometric and body composition measurements (DEXA scan) were recorded. Significant interactions between the ADCY3 genotype and dietary intervention on changes in weight, waist circumference, and body composition were found after adjustment for covariates. Thus, in the moderately-high-protein diet group, the G allele was associated with a lower decrease of fat mass, trunk and android fat, and a greater decrease in lean mass. Conversely, in the low-fat diet group carrying the G allele was associated with a greater decrease in trunk, android, gynoid, and visceral fat. Subjects carrying the G allele of the rs10182181 polymorphism may benefit more in terms of weight loss and improvement of body composition measurements when undertaking a hypocaloric low-fat diet as compared to a moderately-high-protein diet