NIH Unveils Biomarker Score to Track Ultra-Processed Food Intake

Key Takeaways:

• NIH researchers developed a metabolite-based score to objectively measure ultra-processed food intake.
• The study highlights metabolomics as a more accurate alternative to self-reported dietary data.
• Future research will assess how these scores relate to chronic diseases such as cancer and diabetes.

Researchers at the National Institutes of Health (NIH) have identified distinct patterns of blood and urine metabolites that can objectively measure a person’s intake of ultra-processed foods. Published on May 20, 2025, in PLOS Medicine, the study marks a major step toward reducing reliance on self-reported dietary data in large-scale nutrition studies. Metabolites, which are byproducts of metabolism, were used to develop a poly-metabolite score—a composite biomarker that reflects ultra-processed food consumption.

Also read: Mass Spectrometry in Biomarker Discovery for Early Disease Detection

“Limitations of self-reported diet are well known. Metabolomics provides an exciting opportunity to not only improve our methods for objectively measuring complex exposures like diet and intake of ultra-processed foods, but also to understand the mechanisms by which diet might be impacting health,” said lead investigator Erikka Loftfield, Ph.D., M.P.H., of NIH’s National Cancer Institute.

The study combined observational data from 718 older adults and clinical trial data from 20 participants who followed alternating diets of ultra-processed and unprocessed foods Using machine learning, scientists identified hundreds of metabolites associated with processed food intake and developed scores that could clearly distinguish between the two diet phases.

The study validates metabolomics as a powerful tool to measure dietary intake and explore its impact on health more accurately than traditional self-report methods. Researchers emphasize the need to refine and test the poly-metabolite scores in diverse populations and further investigate links to diseases like cancer and type 2 diabetes.