The human microbiome can provide information on the risk of nonalcoholic fatty liver disease. This was discovered by an international team led by the Leibniz Institute for Natural Product Research and Infection Biology – Hans Knöll Institute. Researchers developed a model that can predict the possible course of the disease based on the microbial composition in the gut. The study is published in Science Translational Medicine.
Up to 25% of the world’s population has non-alcoholic fatty liver disease (NAFLD), in which more fat cells are formed in the liver. It is the most common chronic liver disease in industrialized countries of the world and, unlike alcoholic fatty liver disease, it is not caused by high alcohol consumption. In some people, undetected NAFLD can lead to liver scarring, liver cancer, or liver failure.
In a long-term study, an international research team led by Gianni Panagiotou, leader of the research group for systems biology and bioinformatics at Leibniz HKI, analyzed stool and blood samples from 1,200 people who were initially NAFLD-free. “Microorganisms in the human gut have already been shown to contribute to the development of NAFLD. We wanted to find out whether a healthy person’s microbiome could predict whether or not they will develop NAFLD in the future,” explains Panagiotou. When the subjects were re-examined four years later, it was revealed that 90 of them had developed NAFLD by then. Samples from those affected were compared to a control group of 90 people who did not have NAFLD at baseline or at the follow-up visit. “Using different methods, we were able to find very subtle differences in the samples taken four years earlier,” explains first author Howell Leung of the Panagiotou group at Leibniz HKI. “With this data, we were able to develop a model that can predict who will develop NAFLD in the future based on the microbiome with 80% certainty.” Currently, there are clinical models that use biochemical parameters in the blood to make a prediction with an accuracy of 60%. “The model we developed combines easily measurable information from the blood with data from the microbiome and can therefore enormously increase reliability,” says Panagiotou.
Disease prediction through machine learning
The research team developed a so-called machine learning model, a computer model trained to recognize certain patterns in a set of data. The model can then use these models to analyze new datasets and, in this case, predict possible nonalcoholic fatty liver disease. “The whole process of developing our model took more than three years due to the complexity of the data. However, we were ultimately successful and were able to create a useful tool for predicting NAFLD,” says Panagiotou.
Late stage nonalcoholic fatty liver disease is irreversible and can even lead to liver cancer in the worst cases. People who already suffer from a precursor or are particularly at risk must therefore be identified early in order to be able to fight the disease. “NAFLD is a silent disease. This means that in most cases it is asymptomatic and is usually only detected by chance,” explains Gianni Panagiotou. The number of Germans with NAFLD is estimated at around 12 million. People with pre-existing conditions such as type 2 diabetes, obesity, high blood pressure or dyslipidemia are particularly affected by fatty liver.
Possible applications and next steps
Using their machine learning model, the researchers have already been able to compare and then validate their findings with patient data from the United States and Europe. In the next phase, Panagiotou plans to conduct the study globally and use artificial intelligence to integrate even larger data sets into the study.
“I see microbiome-based diagnostics as something that will reach clinical practice and have great potential in the next decade,” says Panagiotou. Early treatment of risk factors for nonalcoholic fatty liver disease, such as type 2 diabetes, hypertension and obesity, could stop the development of the disease. Therefore, early prognosis is the only way to prevent the disease.
Reference: Leung H, Long X, Ni Y, et al. Risk assessment with gut microbiome and metabolite markers in the development of NAFLD. Trans Med ski. 2022; 14 (648): eabk0855. doi: 10.1126 / scitranslmed.abk0855
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