Literature DB >> 35314857

Establishing 24-Hour Urinary Sucrose Plus Fructose as a Predictive Biomarker for Total Sugars Intake.

Laurence S Freedman1, Victor Kipnis2, Douglas Midthune2, John Commins3, Brian Barrett3, Virag Sagi-Kiss4, Susana A Palma-Duran4, Carol S Johnston4, Diane M O'Brien5, Natasha Tasevska4.   

Abstract

BACKGROUND: Twenty-four-hour urinary sucrose and fructose (24uSF) has been studied as a biomarker of total sugars intake in two feeding studies conducted in the United Kingdom (UK) and Arizona (AZ). We compare the biomarker performance in these populations, testing whether it meets the criteria for a predictive biomarker.
METHODS: The UK and AZ feeding studies included 13 and 98 participants, respectively, aged 18 to 70 years, consuming their usual diet under controlled conditions. Linear mixed models relating 24uSF to total sugars and personal characteristics were developed in each study and compared. The AZ calibrated biomarker equation was applied to generate biomarker-estimated total sugars intake in UK participants. Stability of the model across AZ study subpopulations was also examined.
RESULTS: Model coefficients were similar between the two studies [e.g., log(total sugars): UK 0.99, AZ 1.03, P = 0.67], as was the ratio of calibrated biomarker person-specific bias to between-person variance (UK 0.32, AZ 0.25, P = 0.68). The AZ equation estimated UK log(total sugar intakes) with mean squared prediction error of 0.27, similar to the AZ study estimate (0.28). Within the AZ study, the regression coefficients of log(total sugars) were similar across age, gender, and body mass index subpopulations.
CONCLUSIONS: Similar model coefficients in the two studies and good prediction of UK sugar intakes by the AZ equation suggest that 24uSF meets the criteria for a predictive biomarker. Testing the biomarker performance in other populations is advisable. IMPACT: Applications of the 24uSF biomarker will enable improved assessment of the role of sugars intake in risk of chronic disease, including cancer. See related commentary by Prentice, p. 1151. ©2022 American Association for Cancer Research.

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Year:  2022        PMID: 35314857      PMCID: PMC9167729          DOI: 10.1158/1055-9965.EPI-21-1293

Source DB:  PubMed          Journal:  Cancer Epidemiol Biomarkers Prev        ISSN: 1055-9965            Impact factor:   4.090


  24 in total

1.  Urinary fructose: a potential biomarker for dietary fructose intake in children.

Authors:  S A Johner; L Libuda; L Shi; A Retzlaff; G Joslowski; T Remer
Journal:  Eur J Clin Nutr       Date:  2010-08-18       Impact factor: 4.016

2.  Use of a urinary sugars biomarker to assess measurement error in self-reported sugars intake in the nutrition and physical activity assessment study (NPAAS).

Authors:  Natasha Tasevska; Douglas Midthune; Lesley F Tinker; Nancy Potischman; Johanna W Lampe; Marian L Neuhouser; Jeannette M Beasley; Linda Van Horn; Ross L Prentice; Victor Kipnis
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2014-09-18       Impact factor: 4.254

3.  Urinary sucrose and fructose as biomarkers for sugar consumption.

Authors:  Natasa Tasevska; Shirley A Runswick; Alison McTaggart; Sheila A Bingham
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2005-05       Impact factor: 4.254

4.  Association between added sugar intake and micronutrient dilution: a cross-sectional study in two adult Swedish populations.

Authors:  Esther González-Padilla; Joana A Dias; Stina Ramne; Kjell Olsson; Cecilia Nälsén; Emily Sonestedt
Journal:  Nutr Metab (Lond)       Date:  2020-02-11       Impact factor: 4.169

5.  Biomarker-calibrated protein intake and bone health in the Women's Health Initiative clinical trials and observational study.

Authors:  Jeannette M Beasley; Andrea Z LaCroix; Joseph C Larson; Ying Huang; Marian L Neuhouser; Lesley F Tinker; Rebecca Jackson; Linda Snetselaar; Karen C Johnson; Charles B Eaton; Ross L Prentice
Journal:  Am J Clin Nutr       Date:  2014-02-19       Impact factor: 7.045

6.  Biomarker-predicted sugars intake compared with self-reported measures in US Hispanics/Latinos: results from the HCHS/SOL SOLNAS study.

Authors:  J M Beasley; M Jung; N Tasevska; W W Wong; A M Siega-Riz; D Sotres-Alvarez; M D Gellman; J R Kizer; P A Shaw; J Stamler; M Stoutenberg; L Van Horn; A A Franke; J Wylie-Rosett; Y Mossavar-Rahmani
Journal:  Public Health Nutr       Date:  2016-06-24       Impact factor: 4.022

7.  Validity Coefficient of Repeated Measurements of Urinary Marker of Sugar Intake Is Comparable to Urinary Nitrogen as Marker of Protein Intake in Free-living Subjects.

Authors:  Taymara C Abreu; Paul J M Hulshof; Hendriek C Boshuizen; Laura Trijsburg; Nicola Gray; Jeanne H M de Vries
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2020-09-30       Impact factor: 4.254

8.  Use of the predictive sugars biomarker to evaluate self-reported total sugars intake in the Observing Protein and Energy Nutrition (OPEN) study.

Authors:  Natasa Tasevska; Douglas Midthune; Nancy Potischman; Amy F Subar; Amanda J Cross; Sheila A Bingham; Arthur Schatzkin; Victor Kipnis
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2011-01-28       Impact factor: 4.254

9.  Associations of Biomarker-Calibrated Intake of Total Sugars With the Risk of Type 2 Diabetes and Cardiovascular Disease in the Women's Health Initiative Observational Study.

Authors:  Natasha Tasevska; Mary Pettinger; Victor Kipnis; Douglas Midthune; Lesley F Tinker; Nancy Potischman; Marian L Neuhouser; Jeannette M Beasley; Linda Van Horn; Barbara V Howard; Simin Liu; JoAnn E Manson; James M Shikany; Cynthia A Thomson; Ross L Prentice
Journal:  Am J Epidemiol       Date:  2018-10-01       Impact factor: 4.897

10.  Epidemiologic assessment of sugars consumption using biomarkers: comparisons of obese and nonobese individuals in the European prospective investigation of cancer Norfolk.

Authors:  Sheila Bingham; Robert Luben; Ailsa Welch; Natasa Tasevska; Nick Wareham; Kay Tee Khaw
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2007-08       Impact factor: 4.254

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