Unexpected study results could aid in the development of antidiabetic drugs: An NIDDK study recently found that activating Gi-type proteins in mouse liver cells led to increased glucose production and impaired glucose tolerance. This was a surprise, as this class of G proteins is known to inhibit physiological functions. Increased Gi signaling also stimulated glucose release from human liver cells. The findings, which were published in The Journal of Clinical Investigation, suggest a potential strategy for developing novel antidiabetic drugs that can lower blood glucose levels by suppressing the liver's production of glucose.
Infant formula and type 1 diabetes: Researchers funded by the NIDDK and NIH's Eunice Kennedy Shriver National Institute of Child Health and Development conducted a study to test whether infants who are at risk for type 1 diabetes may have reduced risk for developing the disease if they consume formula with broken down proteins instead of complex proteins, such as those in cow's milk formula. The TRIGR study spanned 15 years and found that the formula with broken down proteins did not significantly decrease the incidence of type 1 diabetes compared to conventional formula, disproving the hypothesis from some prior studies. The study appeared January 2 in JAMA, the Journal of the American Medical Association.
Precision approaches to prevent and treat obesity: Dr. Susan Z. Yanovski, co-director of the NIDDK Office of Obesity Research, and Dr. Jack Yanovski, chief of the Section on Growth and Obesity in NIH's Eunice Kennedy Shriver National Institute of Child Health and Human Development, recently co-authored a paper discussing precision medicine approaches to prevent and treat obesity. The article, published January 16, 2018, in JAMA, the Journal of the American Medical Association, highlighted the interactions between genes and environment that may affect individual susceptibility to obesity or response to treatment. Early identification of those who are susceptible to obesity may improve the likelihood of prevention. Also, predictors of therapeutic response may lead to recommendations not only for medical or surgical treatments, but also for nutritional or physical activity interventions that would be most likely to be successful for an individual patient.