TOPLINE:
A phytochemical and a medium-chain fatty acid showed strong potential to enhance the prediction of prediabetes beyond established clinical risk factors in at-risk Hispanic adolescents.
METHODOLOGY:
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Two-hour oral glucose tolerance tests were conducted in two independent, prospective cohorts — one consisting of 143 Hispanic youth (mean age 11 years) without baseline prediabetes and another of 56 predominantly Hispanic young adults (mean age 20 years) without baseline prediabetes.
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Baseline metabolite levels were measured in plasma from a 2-hour postglucose challenge.
TAKEAWAY:
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In the first cohort, 37 participants (26.6%) developed prediabetes at 1.2 years’ follow-up, and one developed type 2 diabetes, while 15 from the second (26.8%) developed prediabetes over 4.1 years’ follow-up.
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Of 595 metabolite features identified via pathway analysis, two were found to independently predict prediabetes: Caprylic acid and allylphenol sulfate.
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In the first cohort, the area under the curve (AUC) for predicting prediabetes with the complete model, including all risk factors and the two metabolites, was 0.80 (95% CI, 0.72 – 0.87), which was higher than with risk factors only (AUC, 0.63; 95% CI, 0.53 – 0.73).
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In the second group, the model with metabolites and risk factors predicted prediabetes more accurately (AUC, 0.70; 95% CI, 40.55 – 0.86]) than the same model without metabolites (AUC, 0.62; 95% CI, 0.46 – 0.79).
IN PRACTICE:
“These findings provide a new avenue for identifying adolescents at high risk of prediabetes that could help guide personalized preventive treatment to prevent prediabetes/type 2 diabetes in this high-risk population.”
SOURCE:
The study, by Jesse A. Goodrich, of the Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, and colleagues, was published online November 16 in Diabetes Care.
LIMITATIONS:
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Small sample size
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Low conversion to type 2 diabetes
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Diet and activity weren’t strictly controlled.
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Metabolite levels from the 2-hour post-oral glucose tolerance test may make implementing this prediction model in routine clinical practice challenging.
DISCLOSURES:
The authors report no relevant financial relationships.
Miriam E. Tucker is a freelance journalist based in the Washington, DC area. She is a regular contributor to Medscape, with other work appearing in the Washington Post, NPR’s Shots blog, and Diabetes Forecast magazine. She is on Twitter @MiriamETucker.
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