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Metabolome and the genome, weight and BMI

A surprising finding was that genetics did not correlate nearly as closely as expected, differences in genetics between obese and non-obese populations did not show patterns that were distinct enough to be predictive

Researchers from the US and Switzerland have reported the outcomes from a large study examining new ways to measure obesity. The study looked at both the metabolome and the genome, and their relationship to BMI, and who is at an elevated risk of developing obesity-related complications.

In the current study, the investigators used data from TwinsUK, a multiyear study examining the genetic and environmental influences on human health and aging. They analysed body and metabolic measures from nearly 2,000 adult twins that had been collected at three time points over an average of 13 years. They also used data from a single time point for 427 volunteers. They found that about one-third of the metabolites included in the study were associated with changes in BMI. The paper, 'Profound perturbation of the metabolome in obesity associates with health risk', was published in Cell Metabolism.

"We are attempting to identify the heterogeneity in what we currently call obesity. There's a need for more precise ways of measuring," said senior author, Dr Amalio Telenti, a genomics professor at Scripps Research Institute, La Jolla, CA. "Although it's clear that obesity is linked to certain diseases, not everybody who is obese will have these consequences. Also surprising, you may not look obese but still have the problems of someone who is."

The metabolome is the sum of all the small-molecule chemicals found in a biological sample, often the blood plasma. These chemicals include fatty acids, amino acids, sugars, and vitamins, to name a few. The metabolome changes in response to interactions between the genome and the environment.

"For most people, we found the metabolome is tied very closely to weight and BMI," he explained. "Every time someone gains or loses a pound, their metabolome changes. It's almost linear. Correlating well is not the same as correlating perfectly, and that's where this work became very interesting."

A surprising finding was that genetics did not correlate nearly as closely as expected. Differences in genetics between obese and non-obese populations did not show patterns that were distinct enough to be predictive. The exception was with a few particular genes known to be connected with extreme obesity, such as mutations in MC4R. This gene is known to play a critical role in regulating food intake and energy balance.

This graphical abstract shows that the metabolome captures clinically relevant phenotypes of obesity and is a better health predictor than genetic risk (Credit: Cirulli et al/Cell Metabolism

"There have been studies before of individuals whose BMI doesn't match their metabolic health, but this is a new way of defining who is metabolically healthy," added first author, Liz Cirulli, a research scientist at Human Longevity, San Diego, CA. "All across the weight spectrum, we found people who were heavier or lighter than expected based on their metabolome."

These differences were found in a range of metabolites linked to various diseases.

Telenti stresses that the metabolome tests developed for this paper are still an academic development, and much more research is needed before they can be validated and established for clinical use. But eventually, the hope is that it will be possible for someone to get a comprehensive analysis of all the metabolites in their body with one blood test, rather than the battery of tests that's currently part of a standard physical exam.

Cirulli stated that future work will look at defining metabolic signatures for other traits, including blood pressure and android/gynoid ratios - a measure of different types of body fat, adding: "It's important to collect additional longitudinal data in bigger cohorts to see what the long-term health consequences of different metabolic states are."

To access this paper, please click here

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