Metabolomic Profiling of an Ultraprocessed Dietary Pattern in a Domiciled Randomized Controlled Crossover Feeding Trial
O'Connor LE, Hall KD, Herrick KA, Reedy J, Chung ST, Stagliano M, Courville AB, Sinha R, Freedman ND, Hong HG, Albert PS, Loftfield E
The Journal of nutrition · 38 citas
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Cómo se estudió
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- Ensayo controlado aleatorizado (indexado por PubMed)
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Quién lo pagó
- Financiación
- Financiación independiente
- Gobierno
- National Institutes of Health
- Gobierno
- National Cancer Institute
- Gobierno
- National Institute of Diabetes and Digestive and Kidney Diseases
Según 3 financiadores declarados.
Publicación
- Publicado
- 2023-06-03 · J Nutr · vol. 153 · número 8 · págs. 2181–2192
- Editorial
- Elsevier BV
- Citado
- 39 citas · más que el 99% de estudios similares · 9.0× el promedio de su campo
- Impacto
- Entre el 10 % más citado de su campo
- Referencias
- 66 trabajos
- Acceso
- Lectura gratuita
- Áreas de investigación
- Consumer Attitudes and Food Labeling · Metabolomics and Mass Spectrometry Studies · Nutritional Studies and Diet
- Palabras clave
- ultra-processed foods, dietary habits, NOVA classification, metabolomics, dietary biomarkers, plasma metabolites, urinary metabolites, short-term dietary intervention, pimelic acid, acesulfame, food processing
- MeSH
- humans, body mass index, diet, energy intake, food handling, food, adult, metabolomics, young adult, fast foods
12 autores
- Lauren E O’Connor🇺🇸National Institutes of Health; Agricultural Research Service; United States Department of Agriculture; Beltsville Human Nutrition Research Center; Beltsville Agricultural Research Center; National Cancer Institute
- Kevin D. Hall🇺🇸National Institute of Diabetes and Digestive and Kidney Diseases
- Kirsten Herrick🇺🇸National Institutes of Health; National Cancer Institute
- Jill Reedy🇺🇸National Institutes of Health; National Cancer Institute
- Stephanie Therese Chung🇺🇸National Institute of Diabetes and Digestive and Kidney Diseases
- Michael S. Stagliano🇺🇸National Institute of Diabetes and Digestive and Kidney Diseases
- Amber B. Courville🇺🇸National Institute of Diabetes and Digestive and Kidney Diseases
- Rashmi R. Sinha🇺🇸National Cancer Institute; Division of Cancer Epidemiology and Genetics
- Neal D. Freedman🇺🇸National Cancer Institute; Division of Cancer Epidemiology and Genetics
- Hyokyoung Grace Hong🇺🇸National Cancer Institute; Division of Cancer Epidemiology and Genetics
- Paul S. Albert🇺🇸National Cancer Institute; Division of Cancer Epidemiology and Genetics
- Erikka Loftfield🇺🇸 · autor de correspondenciaNational Cancer Institute; Division of Cancer Epidemiology and Genetics
Resumen
El texto original del estudio, en el idioma en que se publicó.
Background
Objective markers of ultraprocessed foods (UPF) may improve the assessment of UPF intake and provide insight into how UPF influences health.
Objectives
To identify metabolites that differed between dietary patterns (DPs) high in or void of UPF according to Nova classification.
Methods
In a randomized, crossover, controlled-feeding trial (clinicaltrials.govNCT03407053), 20 domiciled healthy participants (mean ± standard deviation: age 31 ± 7 y, body mass index [kg/m2] 22 ± 11.6) consumed ad libitum a UPF-DP (80% UPF) and an unprocessed DP (UN-DP; 0% UPF) for 2 wk each. Metabolites were measured using liquid chromatography with tandem mass spectrometry in ethylenediaminetetraacetic acid plasma, collected at week 2 and 24-h, and spot urine, collected at weeks 1 and 2, of each DP. Linear mixed models, adjusted for energy intake, were used to identify metabolites that differed between DPs.
Results
After multiple comparisons correction, 257 out of 993 plasma and 606 out of 1279 24-h urine metabolites differed between UPF-DP and UN-DP. Overall, 21 known and 9 unknown metabolites differed between DPs across all time points and biospecimen types. Six metabolites were higher (4-hydroxy-L-glutamic acid, N-acetylaminooctanoic acid, 2-methoxyhydroquinone sulfate, 4-ethylphenylsulfate, 4-vinylphenol sulfate, and acesulfame) and 14 were lower following the UPF-DP; pimelic acid, was lower in plasma but higher in urine following the UPF-DP.
Conclusions
Consuming a DP high in, compared with 1 void of, UPF has a measurable impact on the short-term human metabolome. Observed differential metabolites could serve as candidate biomarkers of UPF intake or metabolic response in larger samples with varying UPF-DPs. This trial was registered at clinicaltrials.gov as NCT03407053 and NCT03878108.
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