Researchers have just developed a new tool that is able to analyze the microbiome in stool samples, which allows it to detect chronic liver disease in over 90% of the patients.
According to the World Health Organization (WHO), chronic liver disease affects about 844 million people worldwide and is one of the leading causes of death in many rich countries.
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While alcohol, obesity, overweight, and lack of vaccination have been identified as major factors in chronic liver disease, the difficulty of diagnosing these diseases is also a cause of concern. Biopsies are invasive and painful and are not always reliable in detecting liver damage. MRIs are expensive and often difficult to perform in rural areas.
To improve the detection of these silent and insidious diseases, a team of researchers from the University of San Diego and the Salt Lake Institute has created a new microbiome-based diagnostic tool that can detect fibrosis and liver cirrhosis with 90% reliability. Their work has just been published in the journal Cell Metabolism.
Universal gut microbiome-derived signature
“The microbiome is a living, dynamic sensor for small changes in the health and disease of the body and as such provides an accurate reading of the health of the body,” says Professor Ronald Evans, co-author of the book.
Cost-effective and non-invasive, this new diagnostic method is based on an algorithm for analyzing stool samples from patients that could be widely used, especially in the many areas where there is a lack of specialized clinics and physicians. It could simply be a change in the game, with global implications.
Based on a “microbiome-derived signature” of the disease, the test is able to detect up to 19 bacteria in the stool that cause chronic liver disease, including cirrhosis and fibrosis. A total of 163 samples from healthy and sick volunteers were tested. The microbiome-derived signature was associated with a 94% accuracy in the diagnosis of cirrhosis and enabled the exact identification of cirrhosis in over 90% of the patients.
The microbiome-derived signature could also determine the stage of liver fibrosis, allowing physicians to classify patients and improve treatment strategies.
“These results show that it is possible to use algorithms to identify a universal signature that can be used to make an accurate diagnosis of a disease such as liver cirrhosis,” said Tae Gyu Oh, lead author of the paper. The models we have found reflect the complexity of the microbiome and show how intestinal health is likely to be affected by the disease.
Further research is planned to investigate the causal relationship between the microbiome and liver disease, and to find out whether restoring parts of the microbiome will lead to a regression of the disease or whether removing certain bacteria will make the disease worse. The researchers also hope that this approach can be used to diagnose other diseases, such as inflammatory bowel disease, colon cancer, Alzheimer’s disease, and other diseases that have been shown to be affected by a deregulated microbiome.