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The global prevalence of obesity is continuously increasing, with about 19.5% of the adult population currently considered obese. Multiple metabolic and molecular imbalances are associated with obesity, such as insulin resistance, hyperlipidemia, hypertension, and impaired cell signaling. These perturbations cause the early onset of various chronic diseases in obese individuals.

Study: Epigenome-wide meta-analysis of BMI in nine cohorts: Examining the utility of epigenetically predicted BMI. Image Credit: Maya Kruchankova / Shutterstock.com

Background

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As compared to those without obesity, obese individuals are at a high risk of developing type 2 diabetes and cardiovascular disease. Since obesity is increasing globally, it is imperative to identify molecular mechanisms that are impaired by obesity. This would not only help determine early markers of disease progression but also aid in the development of novel therapeutic targets.

Epigenetic mechanisms are associated with molecules that mediate changes in gene function without changing the DNA sequence. DNA methylation, a well-studied epigenetic mechanism, occurs when a methyl group attaches to the cytosine in a cytosine-guanine nucleotide (CpG) pair.

DNA methylation influences gene expression by inhibiting transcription factors and employing chromatin remodelers. Research on DNA methylation offers a better understanding of therapeutic targets, which could be pivotal for developing treatments. Notably, DNA methylation has become an important biomarker for monitoring health status. 

An individual’s age can be accurately estimated using the methylation status of a representative set of CpG sites. However, if an individual’s epigenetically predicted age is higher than their actual age, they are at a greater risk of developing cardiovascular disease, cancer, and diabetes.

Several studies have documented the association between DNA methylation and body mass index (BMI), which is commonly used to determine obesity. These studies have linked obesity with differential DNA methylation.

Interestingly, Mendelian randomization analyses have indicated that certain CpG sites are associated with obesity. More sites could likely be detected in large-scale studies, as DNA methylation differences are very subtle.

About the study

A recent study published in The American Journal of Human Genetics hypothesized that DNA methylation-based estimates of obesity measures could provide important metrics of metabolic health. This large-scale epigenome-wide association study (EWAS) meta-analysis of BMI utilized nine population-based cohort studies to detect previously unidentified CpG sites associated with obesity. 

Notably, the determination of novel sites can identify important molecular signatures of various BMI phenotypes that can be used to improve BMI predictions. The authors examined whether individuals whose BMI was poorly predicted by DNA methylation had different metabolic health statuses.

A total of 17,034 participants from six EWASs based on nine cohorts were included in the final analysis. All participants belonged to Europe, Africa, or South Asia. Participants were excluded if the BMI and blood samples for DNA methylation were not analyzed within the same year.

Study findings

The current study involved a large meta-EWAS of BMI and determined distinct methylome signatures of BMI. About 99% of CpG sites identified in this study were replicated in the Women’s Health Initiative (WHI) and associated with genes encoding several metabolic and inflammatory pathways. A low level of inflammation is the hallmark of obesity, which can cause significant metabolic impairment.

A total of 1,238 CpG sites were significantly associated with BMI in various racial or ethnic groups. Moreover, five CpG sites were differentially associated with BMI between African Americans and Hispanic White individuals.

Among these, TNFRSF13B and LGALS3BP were linked with nuclear factor kB (NFkB) signal regulation, which could be upregulated with obesity. A positive association was observed between BMI and DNA methylation in cg25212453 and a less negative association in cg08122652.

The authors developed a score based on 398 CpG sites, which have the realistic predictive ability for BMI. These were also associated with many cardiometabolic risk factors.

Based on DNA methylation predictions, an individual was considered to be in poor metabolic health when the measured BMI was higher than predicted estimates. These individuals had higher triglycerides and blood glucose levels, as well as lower HDL cholesterol, as compared to individuals whose BMIs were accurately predicted.

Individuals with high epigenetic BMI or those whose BMI was overpredicted by the epigenetic markers exhibited poorer cardiometabolic markers as compared to individuals with accurately predicted BMI. Additionally, LDL cholesterol was inconsistent with other cardiometabolic markers.

Conclusions

The current study revealed that DNA methylation is an accurate predictor of current BMI and a poor predictor of future BMI. Novel CpG sites, which were associated with BMI, were also identified. Furthermore, unique molecular profiles associated with obesity in individuals of African descent were revealed.

More research is needed to understand whether differential BMI-associated DNA methylation affects metabolic health status.

Journal reference:
  • Do, L. W., Sun, D., Meeks, K., et al. (2023) Epigenome-wide meta-analysis of BMI in nine cohorts: Examining the utility of epigenetically predicted BMI. The American Journal of Human Genetics. doi:10.1016/j.ajhg.2022.12.014

Posted in: Men's Health News | Medical Science News | Medical Research News | Medical Condition News | Women's Health News

Tags: Biomarker, Blood, Body Mass Index, Body Mass Index (BMI), Cancer, Cardiometabolic, Cardiovascular Disease, Cell, Cell Signaling, Cholesterol, Chromatin, Chronic, CpG, Cytosine, Diabetes, DNA, DNA Methylation, Gene, Gene Expression, Genes, Genetics, Glucose, Guanine, Hyperlipidemia, Inflammation, Insulin, Insulin Resistance, Nucleotide, Obesity, Research, Transcription, Transcription Factors, Type 2 Diabetes

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Written by

Dr. Priyom Bose

Priyom holds a Ph.D. in Plant Biology and Biotechnology from the University of Madras, India. She is an active researcher and an experienced science writer. Priyom has also co-authored several original research articles that have been published in reputed peer-reviewed journals. She is also an avid reader and an amateur photographer.

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