Nutrients (May 2021)

An Artificial-Intelligence-Discovered Functional Ingredient, NRT_N0G5IJ, Derived from <i>Pisum sativum</i>, Decreases HbA1c in a Prediabetic Population

  • Sweeny Chauhan,
  • Alish Kerr,
  • Brian Keogh,
  • Stephanie Nolan,
  • Rory Casey,
  • Alessandro Adelfio,
  • Niall Murphy,
  • Aoife Doherty,
  • Heidi Davis,
  • Audrey M. Wall,
  • Nora Khaldi

DOI
https://doi.org/10.3390/nu13051635
Journal volume & issue
Vol. 13, no. 5
p. 1635

Abstract

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The prevalence of prediabetes is rapidly increasing, and this can lead to an increased risk for individuals to develop type 2 diabetes and associated diseases. Therefore, it is necessary to develop nutritional strategies to maintain healthy glucose levels and prevent glucose metabolism dysregulation in the general population. Functional ingredients offer great potential for the prevention of various health conditions, including blood glucose regulation, in a cost-effective manner. Using an artificial intelligence (AI) approach, a functional ingredient, NRT_N0G5IJ, was predicted and produced from Pisum sativum (pea) protein by hydrolysis and then validated. Treatment of human skeletal muscle cells with NRT_N0G5IJ significantly increased glucose uptake, indicating efficacy of this ingredient in vitro. When db/db diabetic mice were treated with NRT_N0G5IJ, we observed a significant reduction in glycated haemoglobin (HbA1c) levels and a concomitant benefit on fasting glucose. A pilot double-blinded, placebo controlled human trial in a population of healthy individuals with elevated HbA1c (5.6% to 6.4%) showed that HbA1c percentage was significantly reduced when NRT_N0G5IJ was supplemented in the diet over a 12-week period. Here, we provide evidence of an AI approach to discovery and demonstrate that a functional ingredient identified using this technology could be used as a supplement to maintain healthy glucose regulation.

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