Reading tea leaves? No, reading stools

Research by UC San Diego, Human Longevity and JCVI finds stool microbes predict advanced liver disease

Lori Lesko
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SAN DIEGO—A proof-of-concept study by the University of California, San Diego (UC San Diego), Human Longevity Inc. and the J. Craig Venter Institute (JCVI) suggests a noninvasive test for specific microbial population patterns could be used to detect advanced nonalcoholic fatty liver disease (NAFLD), a condition that can lead to liver cirrhosis and cancer. Because the symptoms are similar to other maladies, NAFLD isn’t typically detected until it has advanced considerably, and the diagnosis requires an invasive liver biopsy.
 
One solution to this medical dilemma may soon be provided by researchers led by first author Dr. Rohit Loomba, professor of medicine in the Division of Gastroenterology, director of the NAFLD Research Center and a faculty member in the Center for Microbiome Innovation at UC San Diego. The team found a way to diagnose NAFLD with a non-invasive procedure—a simple stool sample.
 
Conducting a proof-of-concept study involving 135 participants, the research team found that the unique microbial makeup of a patient’s stool sample, or gut microbiome, can be used to predict advanced NAFLD with an 88- to 94-percent accuracy. The study was published May 2 in Cell Metabolism.
 
“We estimate that as many as 100 million adults and children in the U.S. may have NAFLD. Determining exactly who has or is at risk for the disease is a critical unmet medical need,” Loomba says. “There are about 50 new NAFLD drugs in the pipeline, including about five that will likely be approved for use in the next two years. If we are better able to diagnose this condition, we will be better at enrolling the right types of patients in these trials, and ultimately will be better equipped to prevent and treat it.”
 
The precise cause of NAFLD is unknown, but diet and genetics play substantial roles, with up to 50 percent of obese people believed to have NAFLD. As mounting evidence continues to suggest that the makeup of a person’s gut microbiome may influence his or her risk for obesity, Loomba began to wonder if the gut microbiome might also be linked to obesity-associated liver disease. If so, he hypothesized that a stool-based “readout” of what’s living in a person’s gut might provide insight into whether he or she is at risk for NAFLD.
 
“Researchers are now looking into a larger validation cohort study to validate these findings,” Loomba says. “In addition, we are currently analyzing if twins with or without NAFLD could be differentiated using a gut microbiome-derived signature.”
 
To conduct the study, Loomba and team examined two different patient groups. The first group included 86 patients with NAFLD, as diagnosed by biopsy. Of these, 72 had mild/moderate NAFLD and 14 had advanced disease. Collaborators at Human Longevity sequenced the microbial genes extracted from each participant’s stool sample and used that information to determine which species were living where and the relative abundance of each.
 
The researchers found 37 bacterial species that distinguished mild/moderate NAFLD from advanced disease, allowing them to predict which patients had advanced disease with 93.6-percent accuracy, according to the study.
 
The team validated this finding with a second study group that included 16 patients with advanced NAFLD and 33 healthy people as controls. In this case, they found nine bacterial species whose relative numbers allowed them to distinguish NAFLD patients from the healthy volunteers, with 88-percent accuracy, the study states. Seven of these bacterial species overlapped with the signature 37 used in the previous group.
 
The four main types of bacteria found in the human gut are: Firmicutes, Proteobacteria, Bacteroidetes and Actinobacteria. The Cell Metabolism article reports that Loomba and his team found patients with advanced NAFLD tend to have more Proteobacteria and fewer Firmicutes in their stool than those with early-stage NAFLD. At the species level, one major difference the researchers found was in the abundance of E. coli—these bacteria were threefold more common in advanced NAFLD patients than early-stage patients.
 
However, the researchers reported in the article that they were surprised that E. coli was discovered at all in the early stages of NAFLD.
 
“We believe our study sets the stage for a potential stool-based test to detect advanced liver fibrosis based simply on microbial patterns, or at least help us minimize the number of patients who have to undergo liver biopsies,” states senior author Karen E. Nelson, president of JCVI.
 
One drawback is expense. Loomba estimates that a stool-based microbiome diagnostic test might cost $1,500 if it were on the market today; however, over the next five years, advances in genomic sequencing and analysis technologies could lower the cost to less than $400 per test.
 
However, so far this new diagnostic approach has only been tested in a relatively small patient group at a single, highly specialized medical center.
 
To collect more data to prove or disprove their theory, the team is now applying for grant funding to expand their study in a larger cohort across multiple sites, Loomba says. Even if successful, a stool-based test for NAFLD wouldn’t be available to patients for at least five years.
 
“We are looking forward to further studies to assess the role, if any, these microbial species play in gut permeability, liver inflammation and cross-talk with other factors to induce liver injury and ultimately influence disease progression in NAFLD,” states study co-author Dr. David A. Brenner, vice chancellor of UC San Diego Health Sciences and dean of the UC San Diego School of Medicine.
 
Study co-author J. Craig Venter, co-founder and executive chairman of Human Longevity—as well as the namesake of the JCVI—adds, “Understanding the microbiome, just as sequencing the human genome, is one part of the puzzle on human health and disease. New technologies, such as machine learning, are allowing for tremendous advances to interpret these data.”

Lori Lesko

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