Evidence mapPaperPMID 39891268Full record

ArticleNutrition journal2025

Association of ultra-processed food-related metabolites with selected biochemical markers in the UK Biobank.

Anthony Kityo, Byeonggeun Choi, Jung-Eun Lee, Chulho Kim, Sang-Ah Lee

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Article in Nutrition journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Anthony KityoDepartment of Preventive Medicine, School of Medicine, Kangwon National University, 1 Gangwondeahakgil, Chuncheon, Gangwon, 24341, Republic of Korea.
Byeonggeun ChoiInterdisciplinary Graduate Program in Medical Bigdata Convergence, Kangwon National University, Chuncheon, Gangwon, 24341, Republic of Korea.
Jung-Eun LeeInterdisciplinary Graduate Program in Medical Bigdata Convergence, Kangwon National University, Chuncheon, Gangwon, 24341, Republic of Korea.
Chulho KimDepartment of Neurology, Chuncheon Sacred Heart Hospital, Chuncheon, Gangwon, 24341, Republic of Korea.
Sang-Ah LeeDepartment of Preventive Medicine, School of Medicine, Kangwon National University, 1 Gangwondeahakgil, Chuncheon, Gangwon, 24341, Republic of Korea. sangahlee@kangwon.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUltra-processed food (UPF) intake is positively associated with multiple adverse health outcomes. However, the underlying biological mechanisms remain unclear. Serum metabolites may elucidate these mechanisms. We investigated serum metabolites correlated with UPF and un/minimally processed food (UNPF) intake and evaluated their association with selected biochemical markers.

methodsCross-sectional study within the UK biobank, including a total of 72,817 participants with 24-hour recall dietary data and 134 nuclear magnetic resonance metabolites. UPF and UNPF intakes were evaluated using the NOVA classification, and related metabolites were identified using elastic net penalized regression. A UPF metabolomic signature was computed as a weighted sum of UPF-related metabolites, using elastic net coefficients as weights. Associations between UPF and UNPF-related metabolites, and serum C-reactive protein (CRP), insulin-like growth factor-1(IGF-1), sex hormone-binding globulin (SHBG), and testosterone were examined using multiple quantile regression.

resultsElastic net model identified 17 and 15 metabolites uniquely related to UPF and UNPF intake, respectively. Acetoacetate, acetone, high-density lipoprotein (HDL) diameter, docosahexaenoic acid, linoleic acid, ω-3 fatty acids (FA), total lipids in large HDL cholesterol, and valine levels were decreased, but free cholesterol in extremely small very low-density lipoproteins (LDL), glutamine, glycine, glycoprotein acetyls, lactate, saturated FA, sphingomyelins, triglycerides in large LDL, and triglycerides in medium HDL levels were increased with high UPF intake. Opposite relationships were observed for UNPF intake. Heterogeneous associations were observed between UPF-related metabolites and CRP, IGF-1, SHBG, and testosterone levels. A UPF metabolomic signature was positively associated with CRP (regression coefficient per standard deviation, 1.45, 95% confidence interval, 1.385, 1.515) and negatively associated with IGF-1 (-3.16, -4.493, -1.827) and SHBG (-13.878, -15.291, -12.465).

conclusionA UPF metabolomic profile, including VLDL free cholesterol, saturated FA, triglycerides, glutamine, glycine, and glycoprotein acetyl was associated with inflammatory, insulin signalling, and reproductive biomarkers. This metabolomic profile should be explored as a potential mediators of UPF-disease associations, and as an objective marker of UPF intake.

Indexed as

BiomarkersDietFast FoodsFood HandlingAdultAgedBiological Specimen BanksC-Reactive ProteinCross-Sectional StudiesFemaleFood, ProcessedHumansInsulin-Like Growth Factor IMaleMetabolomeMiddle AgedBiomarkersC-Reactive ProteinInsulin-Like Growth Factor ISex Hormone-Binding GlobulinTestosteroneC-reactive proteinInsulin-like growth factor-1MetabolitesSex hormone-binding globulinUK BiobankUltra-processed food

Identifiers

PMID39891268
PMCPMC11786352

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.