In a groundbreaking advancement poised to reshape nutritional epidemiology, researchers have identified specific molecular signatures in blood and urine that correlate strongly with the consumption of ultra-processed foods (UPFs). Published on May 20th in the open-access journal PLOS Medicine, this pioneering study led by Erikka Loftfield of the National Cancer Institute (NCI), USA, unveils novel biochemical markers capable of objectively measuring an individual’s UPF intake. This development marks a crucial step toward overcoming the long-standing challenges of self-reported dietary data, which have historically hampered efforts to accurately assess the health impacts of ultra-processed diets.
Ultra-processed foods—those industrial formulations typically high in sugars, fats, salts, and additives—constitute more than half the caloric intake for the average American. Despite their ubiquity, the precise health consequences of UPFs remain elusive, in large part due to the difficulty of reliably quantifying their consumption in free-living populations. Traditional dietary recall tools are plagued by inaccuracies, biases, and underreporting, complicating attempts to link UPF intake to chronic disease outcomes. The identification of objective biomarkers thus represents a watershed moment, offering a potential biochemical lens through which dietary intake can be more accurately assessed.
The study harnessed a large dataset composed of blood and urine samples from 718 older adults, meticulously matched with extensive dietary recall information. Using sophisticated metabolomic profiling techniques, the research team detected hundreds of metabolites—small molecules reflecting various biochemical processes—associated with the proportion of dietary energy derived from ultra-processed foods. These metabolites span numerous chemical classes, reflecting the intricate physiological interplay triggered by UPF consumption.
From the vast metabolomic landscape, researchers distilled poly-metabolite scores based on 28 serum metabolites and 33 urinary metabolites. These composite scores integrate signals from multiple metabolites to create robust biomarkers that correlate with the percentage of calories participants received from UPFs. The poly-metabolite scores were statistically predictive of self-reported UPF intake, thereby validating their potential as objective proxies for dietary assessment. This multidimensional approach transcends the limitations inherent to single biomarker strategies, offering enhanced sensitivity and specificity.
Crucially, the robustness of these findings was corroborated through a post-hoc randomized controlled crossover-feeding trial involving 20 inpatients at the NIH Clinical Center. Within this tightly controlled setting, participants consumed diets either high in UPFs or entirely free of them, enabling direct comparison of metabolite profiles under known dietary conditions. The poly-metabolite scores reliably discriminated between the high-UPF and no-UPF diets on an individual level, underscoring their validity and potential translational relevance for clinical and population research.
The implications of these validated poly-metabolite scores are far-reaching. They offer an unprecedented opportunity to complement or even supplant self-reported data in large epidemiological studies investigating UPF-related health outcomes. By providing objective biochemical metrics, these scores could help clarify the mechanistic pathways linking UPFs to chronic diseases such as obesity, cardiovascular disease, diabetes, and certain cancers, which observational studies have thus far struggled to elucidate due to measurement inaccuracies.
Moreover, these molecular signatures could catalyze a new era of personalized nutrition, enabling more precise dietary monitoring and intervention tailoring. Researchers envision iterative improvements and refinements of the poly-metabolite scores across diverse populations with varying dietary patterns and cultural contexts. Such refinement would ensure the biomarkers’ generalizability and robustness, enhancing their utility in global nutritional surveillance and public health initiatives.
The study’s meticulous design, combining observational metabolomics with a highly controlled crossover feeding study, strengthens the confidence in these biomarkers. Metabolomics, which quantitatively captures the multitude of small molecules present in biological samples, provides a snapshot of both dietary exposures and endogenous metabolic responses. This integrative approach captures both the direct ingestion of UPF-derived chemicals and the host’s metabolic adaptations, creating a comprehensive assessment tool.
While the authors caution that further work is needed to enhance and validate these scores across broader demographics, the current findings lay a transformative foundation. Such biomarkers, once fully optimized, could revolutionize dietary assessment methods, shedding light on the complex interface between diet and human health. This would be particularly valuable in tackling the global surge in ultra-processed food consumption and its attendant health consequences.
Furthermore, these insights carry profound implications for regulatory policies and public health strategies. Objective biomarker data could inform more targeted dietary guidelines, enable robust monitoring of population-level dietary shifts, and foster accountability among food producers. In an era where nutrition misinformation thrives, scientific tools such as these biomarkers provide robust evidence to underpin health-promoting interventions.
The research was supported by the NIH Intramural Research Program at both the National Cancer Institute and the National Institute of Diabetes and Digestive and Kidney Diseases, with additional funding from Brazil’s Fundação de Amparo à Pesquisa do Estado de São Paulo. The multi-institutional collaboration spanning the United States and Brazil exemplifies a concerted international effort to address the pressing public health challenges linked to ultra-processed foods.
As ultra-processed foods continue to pervade global diets, accounting for an ever-growing proportion of daily caloric intake, the need for objective, reliable measurement tools becomes increasingly urgent. This study’s identification and validation of poly-metabolite scores stand as a monumental leap forward, providing the scientific community with tangible molecular tools to unravel the complexities of UPF consumption and its health ramifications.
Linking metabolite profiles with diet enables researchers to peer into the biochemical consequences of food choices in real time, bridging gaps between nutritional science, epidemiology, and clinical practice. This holds promise not only for individual health optimization but also for crafting deeply informed, population-wide strategies to combat diet-related diseases on a global scale.
The report, titled “Identification and validation of poly-metabolite scores for diets high in ultra-processed food: An observational study and post-hoc randomized controlled crossover-feeding trial,” invites a reconceptualization of how dietary intake is measured and understood. It transforms the metaphorical ‘black box’ of ultra-processed food consumption into a quantifiable, observable phenomenon, unlocking unprecedented opportunities for science-driven health promotion.
Subject of Research: People
Article Title: Identification and validation of poly-metabolite scores for diets high in ultra-processed food: An observational study and post-hoc randomized controlled crossover-feeding trial
News Publication Date: May 20, 2025
Web References: http://dx.doi.org/10.1371/journal.pmed.1004560
References: Abar L, Steele EM, Lee SK, Kahle L, Moore SC, Watts E, et al. (2025) Identification and validation of poly-metabolite scores for diets high in ultra-processed food: An observational study and post-hoc randomized controlled crossover-feeding trial. PLOS Med 22(5): e1004560.
Image Credits: Randy Fath, Unsplash (CC0)
Keywords: ultra-processed food, biomarkers, metabolomics, dietary assessment, poly-metabolite scores, nutritional epidemiology, controlled feeding trial
