Deep inside the body, a silent and slow-growing problem can start.
In about 1 in 5 older adults, a small group of mutated blood cells can begin to grow in the bone marrow without any warning signs.
This hidden condition, called clonal hematopoiesis of indeterminate potential, or CHIP, can increase the risk of serious health problems like leukemia and heart disease.
CHIP starts when a blood stem cell in the bone marrow develops a mutation in a gene linked to blood cancer. This mutated cell then creates a cluster of abnormal blood cells that grow slowly over time.
Even though people with CHIP may feel perfectly healthy, their risk of leukemia goes up by more than 10 times, and their chance of developing heart disease is four times higher than normal.
The challenge is that CHIP usually doesn’t cause any symptoms, so it often goes unnoticed for years. But if doctors could detect it early, they might be able to offer better monitoring or even preventive care.
To help with this, researchers at the Mayo Clinic have developed a powerful artificial intelligence (AI) tool called UNISOM. This tool helps scientists and doctors find CHIP mutations in common genetic data. In the past, finding these mutations required advanced and costly sequencing tests, which were not widely available.
UNISOM was created by Dr. Shulan Tian and her team, with support from Dr. Eric Klee, a leader in research and innovation at the Mayo Clinic. The tool uses machine learning to search through genetic information and spot the small mutations linked to CHIP.
In a recent study published in the journal Genomics, Proteomics & Bioinformatics, UNISOM showed impressive results. It was able to detect about 80% of CHIP mutations using a method called whole-exome sequencing, which looks at the parts of DNA that code for proteins.
The tool also worked well on whole-genome sequencing data, which covers almost all of a person’s genetic code. It even found mutations that were present in less than 5% of a person’s blood cells—changes that are usually too small to notice with standard methods.
Dr. Klee explained that tools like UNISOM are a big step forward in medicine because they help find diseases at the earliest stages, when treatment might be most effective. Dr. Tian added that their goal is to turn genetic discoveries into real tools that doctors can use to make better decisions and offer more personalized care.
The Mayo Clinic team now plans to use UNISOM on larger and more diverse groups of patients to see how well it works across different populations. They hope that by expanding its use, the tool can one day help catch CHIP early in many more people, giving them a better chance to protect their health.
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The study is published in Genomics, Proteomics & Bioinformatics.
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