Researchers led by Johan Auwerx, PhD, at the École Polytechnique Fédérale de Lausanne (EPFL) report that they have addressed the metabolic syndrome (MetS) health condition by developing a metabolic health score (MHS) based on clinical parameters using a type of mice called “BXD” as genetic reference population. These mice are genetically diverse, much like humans, making them suitable for studying how genetics influence health.
Having developed the MHS, they used it to explore its genetic underpinnings in the mice, validating their findings in human data from the UK Biobank. The study “Systems genetics of metabolic health in the BXD mouse genetic reference population” is published in Cell Systems.
MetS is characterized by a group of risk factors: high blood pressure, high blood sugar, unhealthy cholesterol levels, and abdominal fat. These factors increase the risk of heart disease, type 2 diabetes, and other serious health problems.
Five key health indicators
The researchers fed 49 different strains of the BXD mice either a standard diet or a high-fat diet from the age of eight weeks to 29 weeks. Then they measured five key health indicators: body fat percentage, fasting blood sugar, triglycerides, total cholesterol, and fasting insulin levels. From these measurements, they created a metabolic health score (MHS), where a higher score indicates better metabolic health.
Next, they used advanced genetic mapping techniques (quantitative trait locus mapping) to find specific areas in the mice’s DNA that were associated with the MHS. Additionally, they analyzed liver gene expression and plasma lipid profiles to uncover molecular signatures linked to MHS.
Finally, they looked at gene activity in the mouse livers and analyzed their blood to see how their metabolism was working on a molecular level.
The study also revealed two significant genetic regions on chromosomes 7 and 8 that were linked to metabolic health in a diet-dependent manner. These findings were consistent even when tested in different groups of mice, reinforcing the genetic influence on metabolic health. The study pinpointed two candidate genes, TNKS and MCPH1, which were also associated with metabolic traits in human datasets from the UK Biobank and other cohorts.
The team also found that good metabolic health is associated with better management of cholesterol and fatty acids, as well as lower activity in certain cell stress responses and fat storage processes.
Specifically, better metabolic health (a higher MHS score) is linked to lower cholesterol and fatty acid metabolism, reduced mTORC1 signaling (mTORC1 is a protein complex that regulates cell growth and metabolism by responding to nutrients and energy levels), diminished unfolded protein response (a cell stress response that ensures proteins are properly folded and functional), and adipogenesis (making fat cells) in the liver.
The findings highlight potential pathways that could be targeted for therapeutic interventions and underscore the importance of genetics in metabolic health. The study provides a model for studying gene-environment interactions, while the identification of TNKS and MCPH1 as key regulators offers new avenues for understanding and potentially mitigating metabolic diseases.
“Our findings provide insights into the molecular mechanisms sustaining metabolic health across species and uncover likely regulators,” write the researchers.
By translating these findings from mice to humans, the study paves the way for personalized approaches to managing and preventing MetS.
However, the scientists did point out that its study still has some limitations: first, metabolic health is a complex biological phenotype, and there is no precise standard to evaluate it in mice.
“In our study, we used the percentage of fat mass, glucose, triglycerides, total cholesterol, and fasting insulin to evaluate the global health of mice and also confirmed that it is related to metabolic disorders and their biomarkers in two mouse populations and human UKBB, but we still lack a method to measure the accuracy of this MHS,” they continued.
“Furthermore, because the BXD originated from the C57BL/6J and DBA/2J strains, the genetic variants are limited to those present in the parental strains and cannot fully reflect the massive genetic diversity in humans. Inclusion of additional mouse data is likely to highlight additional candidate genes that may be involved in the etiology of MHS. Additional human data could also provide greater power to confirm which of these genes are also important for metabolic health in humans and provide potential therapeutic targets or markers for personalized medicine.