HepatO’Twin: a digital twin to investigate the effects of food contaminants on the hepatic metabolism

Background and challenge

The observed global increase in the incidence of obesity and metabolic disorders cannot be attributed solely to genetic factors and lifestyle. It is now widely acknowledged that other environmental factors play a non-negligible role in these disorders, with a high probability that numerous chemicals (bisphenols, pesticides, phthalates, metals and perfluorinated compounds) act on the body, encouraging changes to the metabolism that may ultimately lead to disorders such as obesity, diabetes and fatty liver disease.

The list of these chemicals, known as metabolism disrupting compounds (MDCs), is growing. They are thought to alter metabolic pathways and, in the longer term, disrupt the body’s metabolic balance and contribute to its progression towards a pathological state. The disruption caused by the compounds may also affect the body’s ability to adapt to physiological stressors such as an unbalanced diet, thus increasing the likelihood of the development of metabolic diseases such as diabetes and obesity. Exposure to the chemical compounds can interact with nutritional stress in differing ways:

• First, by binding to nuclear receptors, chemicals can modify the expression of metabolic genes, disrupting the metabolism and leaving it unable to respond adequately to nutritional stress;
• Second, the detoxification and biotransformation mechanisms activated by such chemicals may compete with endogenous metabolic pathways, given that all these mechanisms are strongly interconnected.

The interactions between exposure to chemicals and nutritional stressors and the development of metabolic diseases are currently poorly understood. They are also hard to study, not only because they are multifactorial but also because their temporal evolution is variable, with adverse effects often taking a considerable time to emerge.

The HepatO’twin project will draw on the concept of the Digital Twin to investigate this major health concern for society.

Goals and methodology

The goal of HepatO’twin is to put the digital twin concept to practical use in establishing whether and how changes in the hepatic metabolism brought about by exposure to food contaminants can increase the likelihood of developing a metabolic disease under nutritionally unbalanced conditions.

HepatO’twin is conceived as a new tool that combines the production of continuous real-time metabolomic data, modelling of the hepatic metabolism, and the application of a feedback action on the nutritional environment of the system.

In silico simulations of nutritional stress (the project calls these simulations ‘nutritional challenges’) linked with machine-learning strategies will allow us to predict whether the observed metabolic modulations will produce a ‘disturbed’ metabolic response to nutritional stress, thereby revealing progression towards a pathological state.

Feedback action, which in this instance takes the form of decision making, will be applied to the system to test out different nutritional challenge scenarios at the specific time when metabolic disruption, likely to alter the system’s response to the challenge, is predicted to occur. This feedback action has the particular advantage of enabling nutritional challenges to be introduced at the optimal exposure time point in an experiment.

This original and innovative system will remove constraints that currently hamper in vitro experiments and open up new perspectives for the understanding of the interactions between exposure to food contaminants and the development of metabolic diseases.

Units involved and partners

INRAE participating units

Partners