Differentially methylated regions (DMRs) in PON3 gene between responders and non-responders to a weight loss dietary intervention: a new tool for precision management of obesity

Implication of DNA methylation during lifestyle mediated weight loss

Over the past 50 years, the number of overweight/obese people increased significantly, making obesity a global public health challenge. Apart from rare monogenic forms, obesity is a multifactorial disease, most likely resulting from a concerted interaction of genetic, epigenetic and environmental factors. Although recent studies opened new avenues in elucidating the complex genetics behind obesity, the biological mechanisms contributing to individual's risk to become obese are not yet fully understood. Non-genetic factors such as eating behaviour or physical activity are strong contributing factors for the onset of obesity. These factors may interact with genetic predispositions most likely via epigenetic mechanisms. Epigenome-wide association studies or methylome-wide association studies are measuring DNA methylation at single CpGs across thousands of genes and capture associations to obesity phenotypes such as BMI. However, they only represent a snapshot in the complex biological network and cannot distinguish between causes and consequences. Intervention studies are therefore a suitable method to control for confounding factors and to avoid possible sources of bias. In particular, intervention studies documenting changes in obesity-associated epigenetic markers during lifestyle driven weight loss, make an important contribution to a better understanding of epigenetic reprogramming in obesity. To investigate the impact of lifestyle in obesity state specific DNA methylation, especially concerning the development of new strategies for prevention and individual therapy, we reviewed 19 most recent human intervention studies. In summary, this review highlights the huge potential of targeted interventions to alter disease-associated epigenetic patterns. However, there is an urgent need for further robust and larger studies to identify the specific DNA methylation biomarkers which influence obesity.

Crosstalk between Gut Microbiota and Epigenetic Markers in Obesity Development: Relationship between Ruminococcus, BMI, and MACROD2/SEL1L2 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.

Near transfer to an unrelated N-back task mediates the effect of N-back working memory training on matrix reasoning

The extent to which working memory training improves performance on untrained tasks is highly controversial. Here we address this controversy by testing the hypothesis that far transfer may depend on near transfer using mediation models in three separate randomized controlled trials (RCTs). In all three RCTs, totalling 460 individuals, performance on untrained N-back tasks (near transfer) mediated transfer to Matrix Reasoning (representing far transfer) despite the lack of an intervention effect in RCTs 2 and 3. Untrained N-back performance also mediated transfer to a working memory composite, which showed a significant intervention effect (RCT 3). These findings support a model of N-back training in which transfer to untrained N-back tasks gates further transfer (at least in the case of working memory at the construct level) and Matrix Reasoning. This model can help adjudicate between the many studies and meta-analyses of working memory training that have provided mixed results but have not examined the relationship between near and far transfer on an individual-differences level.

DNA methylome in visceral adipose tissue can discriminate patients with and without colorectal cancer

Adipose tissue dysfunction, particularly the visceral (VAT) compartment, has been proposed to play a relevant role in colorectal cancer (CRC) development and progression. Epigenetic mechanisms could be involved in this association. The current study aimed to evaluate if specific epigenetic marks in VAT are associated with colorectal cancer (CRC) to identify epigenetic hallmarks of adipose tissue-related CRC. Epigenome-wide DNA methylation was evaluated in VAT from 25 healthy participants and 29 CRC patients, using the Infinium HumanMethylation450K BeadChip. The epigenome-wide methylation analysis identified 170,184 sites able to perfectly separate the CRC and healthy samples. The differentially methylated CpG sites (DMCpGs) showed a global trend for increased methylated levels in CRC with respect to healthy group. Most of the genes encoded by the DMCpGs belonged to metabolic pathways and cell cycle, insulin resistance, and adipocytokine signalling, as well as tumoural transformation processes. In gene-specific analyses, involved genes biologically relevant for the development of CRC include PTPRN2, MAD1L1, TNXB, DIP2C, INPP5A, HDCA4, PRDM16, RPTOR, ATP11A, TBCD, PABPC3, and IER2. The methylation level of some of them showed a discriminatory capacity for detecting CRC higher than 90%, showing IER2 to have the highest capacity. This study reveals that a specific methylation pattern of VAT is associated with CRC. Some of the epigenetic marks identified could provide useful tools for the prediction and personalized treatment of CRC connected to excess adiposity.

Precision nutrition based on phenotypical traits and the (epi)genotype: nutrigenetic and nutrigenomic approaches for obesity care

PURPOSE OF REVIEW

The purpose of this article is to rationally review and critically appraise the current knowledge in the most relevant nongenetic and genetic factors influencing obesity predisposition. This information may be translated into the implementation of personalized nutrition approaches involving precision nutrigenetic and nutrigenomic strategies for obesity monitoring and weight management.

RECENT FINDINGS

The importance and influence of several nongenetic contributors to obesity onset and individual responses to weight-loss interventions have been highlighted including the role of age, sex or perinatal feeding and others related to an individual's lifestyle and modifiable. Nutrigenetic studies have analysed potential interactions between polymorphisms influencing energy homeostasis/body composition and dietary factors in relation to adiposity phenotypes and therapy responsiveness. A second approach comprises the Nutrigenomic analysis of gene expression modifications in response to the consumption of specific nutrients or dietary bioactive compounds, which may involve epigenetic mechanisms including deoxyribonucleic acid methylation and micro-ribonucleic acid expression profiles.

SUMMARY

Taken together, these findings encompass the importance of taking into account up-to-date advances in Nutrigenetic and Nutrigenomic hallmarks, globally analysing the risk of weight gain and related outcomes after following nutrition counselling, this contributing to improve obesity care considering phenotypical traits and the genetic make-up for precision obesity care.