NIH

NIH biomarker score predicts ultra-processed food intake

May 23, 2025

NIH researchers developed a novel biomarker-based tool to objectively assess dietary intake of ultra-processed foods (UPFs), addressing long-standing limitations of self-reported dietary data. Using metabolomic analysis of blood and urine samples, scientists identified hundreds of metabolites linked to UPF consumption. These were used to create a "poly-metabolite score" that accurately reflects the percentage of dietary energy derived from UPFs.

The study combined data from a 12-month observational cohort of 718 older adults and a controlled clinical trial involving 20 participants who alternated between high-UPF (80% energy) and no-UPF (0% energy) diets. Machine learning techniques helped pinpoint metabolic patterns associated with UPF intake, enabling the development of separate scores for blood and urine samples. This biomarker score offers a promising, objective alternative to dietary questionnaires, enhancing the precision of nutritional epidemiology and potentially improving our understanding of how UPFs contribute to chronic diseases.

Source:

(2025, May 20). NIH. NIH researchers develop biomarker score for predicting diets high in ultra-processed foods. https://www.nih.gov/news-events/news-releases/nih-researchers-develop-biomarker-score-predicting-diets-high-ultra-processed-foods