Circulating MicroRNAs predict glycemic improvement and response to a behavioral intervention.

2021 
Author(s): Flowers, Elena; Allen, Isabel Elaine; Kanaya, Alka M; Aouizerat, Bradley E | Abstract: BackgroundMicroRNAs may be important regulators of risk for type 2 diabetes. The purpose of this longitudinal observational study was to assess whether circulating microRNAs predicted improvements in fasting blood glucose, a major risk factor for type 2 diabetes, over 12 months.MethodsThe study included participants (n = 82) from a previously completed trial that tested the effect of restorative yoga on individuals with prediabetes. Circulating microRNAs were measured using a flow cytometry miRNA assay. Linear models were used to determine the optimal sets of microRNA predictors overall and by intervention group.ResultsSubsets of microRNAs were significant predictors of final fasting blood glucose after 12-months (R2 = 0.754, p l 0.001) and changes in fasting blood glucose over 12-months (R2 = 0.731, p l 0.001). Three microRNAs (let-7c, miR-363, miR-374b) were significant for the control group only, however there was no significant interaction by intervention group.ConclusionsCirculating microRNAs are significant predictors of fasting blood glucose in individuals with prediabetes. Among the identified microRNAs, several have previously been associated with risk for type 2 diabetes. This is one of the first studies to use a longitudinal design to assess whether microRNAs predict changes in fasting blood glucose over time. Further exploration of the function of the microRNAs included in these models may provide new insights about the complex etiology of type 2 diabetes and responses to behavioral risk reduction interventions.Trial registrationThis study was a secondary analysis of a previously completed clinical trial that is registered at clinicaltrials.gov (NCT01024816) on December 3, 2009.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    45
    References
    0
    Citations
    NaN
    KQI
    []