超加工食品摂取を予測するバイオマーカースコアの開発(NIH researchers develop biomarker score for predicting diets high in ultra-processed foods)

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2025-05-20 アメリカ国立衛生研究所(NIH)

 

米国国立衛生研究所(NIH)の研究チームは、血液と尿中の代謝物を基に、超加工食品(UPF)の摂取量を客観的に評価する「ポリメタボライトスコア」を開発した。718人の高齢者のサンプルを分析し、UPF摂取と関連する多数の代謝物を特定。さらに、20人の成人を対象とした食事介入試験でスコアの有効性を確認した。このスコアは、自己申告に頼らずに食事の質を評価でき、UPF摂取と肥満や糖尿病、がんなどの慢性疾患リスクとの関係を解明する研究に役立つと期待されている。

<関連情報>

超加工食品を多く含む食事のポリ代謝物スコアの同定と検証: 観察研究と事後無作為化クロスオーバー給餌対照試験 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

Leila Abar,Eurídice Martínez Steele,Sang Kyu Lee,Lisa Kahle,Steven C. Moore,Eleanor Watts,Caitlin P. O’Connell,Charles E. Matthews,Kirsten A. Herrick,Kevin D. Hall,Lauren E. O’Connor,Neal D. Freedman,Rashmi Sinha,Hyokyoung G. Hong,Erikka Loftfield
PLOS Medicine  Published: May 20, 2025
DOI:https://doi.org/10.1371/journal.pmed.1004560

超加工食品摂取を予測するバイオマーカースコアの開発(NIH researchers develop biomarker score for predicting diets high in ultra-processed foods)

Abstract

Background

Ultra-processed food (UPF) accounts for a majority of calories consumed in the United States, but the impact on human health remains unclear. We aimed to identify poly-metabolite scores in blood and urine that are predictive of UPF intake.

Methods and findings

Of the 1,082 Interactive Diet and Activity Tracking in AARP (IDATA) Study (clinicaltrials.gov ID NCT03268577) participants, aged 50-74 years, who provided biospecimen consent, n = 718 with serially collected blood and urine and one to six 24-h dietary recalls (ASA-24s), collected over 12-months, met eligibility criteria and were included in the metabolomics analysis. Ultra-high performance liquid chromatography with tandem mass spectrometry was used to measure >1,000 serum and urine metabolites. Average daily UPF intake was estimated as percentage energy according to the Nova system. Partial Spearman correlations and Least Absolute Shrinkage and Selection Operator (LASSO) regression were used to estimate UPF-metabolite correlations and build poly-metabolite scores of UPF intake, respectively. Scores were tested in a post-hoc analysis of a previously conducted randomized, controlled, crossover-feeding trial (clinicaltrials.gov ID NCT03407053) of 20 subjects who were admitted to the NIH Clinical Center and randomized to consume ad libitum diets that were 80% or 0% energy from UPF for 2 weeks immediately followed by the alternate diet for 2 weeks; eligible subjects were between 18-50 years old with a body mass index of >18.5 kg/m2 and weight-stable. IDATA participants were 51% female, and 97% completed ≥4 ASA-24s. Mean intake was 50% energy from UPF. UPF intake was correlated with 191 (of 952) serum and 293 (of 1,044) 24-h urine metabolites (FDR-corrected P-value < 0.01), including lipid (n = 56 serum, n = 22 24-h urine), amino acid (n = 33, 61), carbohydrate (n = 4, 8), xenobiotic (n = 33, 70), cofactor and vitamin (n = 9, 12), peptide (n = 7, 6), and nucleotide (n = 7, 10) metabolites. Using LASSO regression, 28 serum and 33 24-h urine metabolites were selected as predictors of UPF intake; biospecimen-specific scores were calculated as a linear combination of selected metabolites. Overlapping metabolites included (S)C(S)S-S-Methylcysteine sulfoxide (rs = -0.23, -0.19), N2,N5-diacetylornithine (rs = -0.27 for serum, -0.26 for 24-h urine), pentoic acid (rs = -0.30, -0.32), and N6-carboxymethyllysine (rs = 0.15, 0.20). Within the cross-over feeding trial, the poly-metabolite scores differed, within individual, between UPF diet phases (P-value for paired t test < 0.001). IDATA Study participants were older US adults whose diets may not be reflective of other populations.

Conclusions

Poly-metabolite scores, developed in IDATA participants with varying diets, are predictive of UPF intake and could advance epidemiological research on UPF and health. Poly-metabolite scores should be evaluated and iteratively improved in populations with a wide range of UPF intake.

Abstract

Why was this study done?
  • Global production and availability of UPF is high, but accurately measuring UPF consumption is challenging.
  • Objectively measured metabolites in blood and urine that derive from the diet or response to dietary intake may be useful for studying UPF intake in epidemiologic studies.
  • Complementary observational and experimental human studies provide a unique opportunity to develop and evaluate potential dietary biomarkers.
What did the researchers do and find?
  • Using a discovery metabolomics approach, we identified hundreds of serum and urine metabolites were correlated with percentage energy from UPF intake in 718 free-living adults with diverse dietary intakes who participated in the IDATA Study.
  • We developed and tested poly-metabolite scores that are predictive of UPF intake for blood and urine.
  • Using metabolomics data generated previously in a randomized, controlled, crossover-feeding trial of two diets, one high in and the other void of UPF, we evaluated the IDATA poly-metabolite scores. The poly-metabolite scores differentiated, within individual, between the diets that were 80% and 0% energy from UPF.
What do these findings mean?
  • The identified poly-metabolite scores could serve as objective measures of UPF intake in large population studies to complement or reduce reliance on self-reported dietary data.
  • Poly-metabolite scores, predictive of UPF intake, could provide novel insight into the role of UPF in human health.
  • Limitations: Study participants were older US adults whose diets may vary from other populations. Poly-metabolite scores should be evaluated and iteratively improved in populations with diverse diets and a wide range of UPF intake.
生物化学工学
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