The Carbon Isotope Ratio of Alanine in Red Blood Cells is a New Candidate Biomarker of Sugar-sweetened Beverage Intake

Overview

Journal J Nutr

Publisher Elsevier

Specialty Nutritional Sciences

Date 2013 Apr 26

PMID 23616504

Citations 32

Authors

Kyungcheol Choy

Sarah H Nash

Alan R Kristal

Scarlett Hopkins

Bert B Boyer

Diane M OBrien

Affiliations

Soon will be listed here.

Abstract

An objective dietary biomarker would help clarify the contribution of sugar-sweetened beverage (SSB) intake to obesity and chronic disease risk. Previous studies have proposed the carbon isotope ratio (δ(13)C) as a biomarker of SSB intake but found associations that were of modest size and confounded by other components of the diet. We investigated whether the δ(13)C values of nonessential amino acids (δ(13)CNEAA) in RBCs could provide valid biomarkers that are more specific to SSBs. We assessed the associations of RBC δ(13)CNEAA with SSB intake in a study population of 68 Yup'ik people, using gas chromatography/combustion/isotope ratio mass spectrometry to measure δ(13)CNEAA and four 24-h dietary recalls to assess intake. Among RBC nonessential amino acids, alanine δ(13)C (δ(13)Calanine) was strongly correlated with intake of SSBs, added sugar, and total sugar (r = 0.70, 0.59, and 0.57, respectively; P < 0.0001) but uncorrelated with other dietary sources of elevated δ(13)C. We also evaluated whether sweetener intake could be noninvasively assessed using hair δ(13)Calanine in a subset of the study population (n = 30). Hair δ(13)Calanine was correlated with RBC δ(13)Calanine (r = 0.65; P < 0.0001) and showed similar associations with SSB intake. These results show that δ(13)Calanine in RBCs provides a valid and specific biomarker of SSB intake for the Yup'ik population and suggest RBCs and hair δ(13)Calanine as candidate biomarkers of SSB intake for validation in the general U.S. population. Ultimately, these biomarkers could clarify our understanding of whether and how SSB intake contributes to chronic disease.

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References

Bland J, Altman D . Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986; 1(8476):307-10. View

Dodd K, Guenther P, Freedman L, Subar A, Kipnis V, Midthune D . Statistical methods for estimating usual intake of nutrients and foods: a review of the theory. J Am Diet Assoc. 2006; 106(10):1640-50. DOI: 10.1016/j.jada.2006.07.011. View

Davy B, Jahren A, Hedrick V, Comber D . Association of δ¹³C in fingerstick blood with added-sugar and sugar-sweetened beverage intake. J Am Diet Assoc. 2011; 111(6):874-8. PMC: 3115617. DOI: 10.1016/j.jada.2011.03.019. View

Poppitt S, Swann D, Black A, Prentice A . Assessment of selective under-reporting of food intake by both obese and non-obese women in a metabolic facility. Int J Obes Relat Metab Disord. 1998; 22(4):303-11. DOI: 10.1038/sj.ijo.0800584. View

Bersamin A, Luick B, Ruppert E, Stern J, Zidenberg-Cherr S . Diet quality among Yup'ik Eskimos living in rural communities is low: the Center for Alaska Native Health Research Pilot Study. J Am Diet Assoc. 2006; 106(7):1055-63. DOI: 10.1016/j.jada.2006.04.026. View

van Baak M, Astrup A . Consumption of sugars and body weight. Obes Rev. 2009; 10 Suppl 1:9-23. DOI: 10.1111/j.1467-789X.2008.00561.x. View

Nielsen S, Siega-Riz A, Popkin B . Trends in energy intake in U.S. between 1977 and 1996: similar shifts seen across age groups. Obes Res. 2002; 10(5):370-8. DOI: 10.1038/oby.2002.51. View

Jackson A . Aminoacids: essential and non-essential?. Lancet. 1983; 1(8332):1034-7. DOI: 10.1016/s0140-6736(83)92656-9. View

Allison D, Mattes R . Nutritively sweetened beverage consumption and obesity: the need for solid evidence on a fluid issue. JAMA. 2009; 301(3):318-20. PMC: 2864605. DOI: 10.1001/jama.2008.974. View

10.

Cook C, Alvig A, Liu Y, Schoeller D . The natural 13C abundance of plasma glucose is a useful biomarker of recent dietary caloric sweetener intake. J Nutr. 2009; 140(2):333-7. DOI: 10.3945/jn.109.114777. View

11.

Nash S, Kristal A, Bersamin A, Hopkins S, Boyer B, OBrien D . Carbon and nitrogen stable isotope ratios predict intake of sweeteners in a Yup'ik study population. J Nutr. 2012; 143(2):161-5. PMC: 3542907. DOI: 10.3945/jn.112.169425. View

12.

Pascual M, Jahoor F, Reeds P . Dietary glucose is extensively recycled in the splanchnic bed of fed adult mice. J Nutr. 1997; 127(8):1480-8. DOI: 10.1093/jn/127.8.1480. View

13.

FELIG P . The glucose-alanine cycle. Metabolism. 1973; 22(2):179-207. DOI: 10.1016/0026-0495(73)90269-2. View

14.

Waterhouse C, Keilson J . The contribution of glucose to alanine metabolism in man. J Lab Clin Med. 1978; 92(5):803-12. View

15.

Tasevska N, Runswick S, McTaggart A, Bingham S . Urinary sucrose and fructose as biomarkers for sugar consumption. Cancer Epidemiol Biomarkers Prev. 2005; 14(5):1287-94. DOI: 10.1158/1055-9965.EPI-04-0827. View

16.

Bingham S . Biomarkers in nutritional epidemiology. Public Health Nutr. 2003; 5(6A):821-7. DOI: 10.1079/phn2002368. View

17.

Ma Y, Olendzki B, Pagoto S, Hurley T, Magner R, Ockene I . Number of 24-hour diet recalls needed to estimate energy intake. Ann Epidemiol. 2009; 19(8):553-9. PMC: 2803049. DOI: 10.1016/j.annepidem.2009.04.010. View

18.

OBrien D, Fogel M, Boggs C . Renewable and nonrenewable resources: amino acid turnover and allocation to reproduction in Lepidoptera. Proc Natl Acad Sci U S A. 2002; 99(7):4413-8. PMC: 123662. DOI: 10.1073/pnas.072346699. View

19.

Luceri C, Caderni G, Lodovici M, Spagnesi M, Monserrat C, Lancioni L . Urinary excretion of sucrose and fructose as a predictor of sucrose intake in dietary intervention studies. Cancer Epidemiol Biomarkers Prev. 1996; 5(3):167-71. View

20.

Tasevska N, Midthune D, Potischman N, Subar A, Cross A, Bingham S . Use of the predictive sugars biomarker to evaluate self-reported total sugars intake in the Observing Protein and Energy Nutrition (OPEN) study. Cancer Epidemiol Biomarkers Prev. 2011; 20(3):490-500. PMC: 6276797. DOI: 10.1158/1055-9965.EPI-10-0820. View