New Stool Test May Make Painful Colonoscopies Less Necessary

🔴 BREAKING: Published 3 hours ago
Israeli scientists at Hebrew University developed a new stool test for inflammatory bowel disease, potentially reducing painful colonoscopies for millions.

Jerusalem, 6 May, 2026 (TPS-IL) — Israeli scientists have developed a new way to monitor inflammatory bowel disease using a simple stool test, a breakthrough That Could reduce the need for repeated colonoscopies for millions of patients worldwide, Hebrew University of Jerusalem announced.

Inflammatory bowel disease, or IBD, affects an estimated 6 to 8 million people globally. The condition includes Crohn’s disease and ulcerative colitis, chronic illnesses in which the immune system attacks the digestive tract, causing pain, diarrhea, bleeding and other complications.

There is no cure for IBD; the condition is typically managed through dietary changes and medication, with surgery reserved for severe complications. If untreated, patients may require emergency surgery, hospitalization or removal of part of the intestine or colon.

Doctors currently rely on colonoscopies and laboratory markers to monitor inflammation and determine whether treatments are working. Colonoscopies — in which a thin, flexible tube with a camera is inserted into the rectum to examine the inside of the colon — are invasive, costly and uncomfortable.

However, a study led by Hebrew University Professors Moran Yassour, Eyal Shteyer and Yuval Dor, and including researchers from Jerusalem’s Shaare Zedek Medical Center, found that human DNA in stool samples can provide a detailed picture of intestinal inflammation.

The findings were published in the peer-reviewed journal Microbiome.

Biological ‘Noise’ or an Overlooked Marker?

The researchers discovered that DNA shed into stool by immune cells called neutrophils closely mirrors the severity of inflammation in the gut. Neutrophils are a type of white blood cell that serves as one of the body’s first lines of defense against infection and inflammation.

“For too long, the human DNA found in stool samples was treated as biological ‘noise’ that we filtered out to focus on microbial data,” Yassour said. “Our findings show that this DNA contains valuable, unappreciated information, reflecting the immune system’s activity in real time.”

The scientists used methylation profiling, a method that identifies the tissue origin of DNA fragments, to determine where the genetic material came from. They discovered that neutrophil DNA dominates stool samples from IBD patients, overturning previous assumptions that most human DNA in fecal matter originated from cells lining the colon.

According to the study, neutrophil DNA levels strongly correlated with fecal calprotectin, an established marker used to detect intestinal inflammation.

The researchers said methylation profiling may offer advantages because calprotectin testing can become less effective in severe cases.

The team also developed a new measurement called the Neutrophil-to-Epithelial Ratio, or NER, which they said more accurately distinguishes between active disease and remission.

Researchers combined the human DNA findings with microbiome analysis — the study of bacteria and other microorganisms living in the digestive system. Using machine learning models, they were able to identify patients with IBD and distinguish between Crohn’s disease and ulcerative colitis.

The findings were consistent among both Israeli children and adult patients in the Netherlands, suggesting the approach may work across different age groups and populations.

“By analyzing both the human and microbial components together, we can gain a much clearer picture of what is happening in the gut,” Yassour said.

The researchers said the dual approach could eventually allow doctors to monitor flare-ups and treatment responses through routine stool testing instead of repeated invasive procedures. Moreover, a DNA-based signal could provide a more continuous and nuanced readout of inflammation, helping detect flare-ups earlier and confirm when a patient is truly in remission.

The study also demonstrates that machine learning models can distinguish Crohn’s disease from ulcerative colitis and predict disease activity, which could help doctors tailor therapies more quickly and accurately.