Browsing by Subject "TCF7L2"

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  • Kristensen, Peter L.; Pedersen-Bjergaard, Ulrik; Due-Andersen, Rikke; Hoi-Hansen, Thomas; Grimmeshave, Lise; Lyssenko, Valeriya; Groop, Leif; Holst, Jens J.; Vaag, Allan A.; Thorsteinsson, Birger (2016)
    Introduction: In healthy carriers of the T allele of the transcription factor 7-like 2 (TCF7L2), fasting plasma glucagon concentrations are lower compared with those with the C allele. We hypothesised that presence of the T allele is associated with a diminished glucagon response during hypoglycaemia and a higher frequency of severe hypoglycaemia (SH) in type 1 diabetes (T1DM). Material and methods: This is a post hoc study of an earlier prospective observational study of SH and four mechanistic studies of physiological responses to hypoglycaemia. 269 patients with T1DM were followed in a one-year observational study. A log-linear negative binomial model was applied with events of SH as dependent variable and TCF7L2 alleles as explanatory variable. In four experimental studies including 65 people, TCF7L2 genotyping was done and plasma glucagon concentration during experimental hypoglycaemia was determined. Results: Incidences of SH were TT 0.54, TC 0.98 and CC 1.01 episodes per patient-year with no significant difference between groups. During experimental hypoglycaemia, the TCF7L2 polymorphism did not influence glucagon secretion. Discussion: Patients with T1DM carrying the T allele of the TCF7L2 polymorphism do not exhibit diminished glucagon response during hypoglycaemia and are not at increased risk of severe hypoglycaemia compared with carriers of the C allele.
  • Ahlqvist, Emma; Prasad, Rashmi B.; Groop, Leif (2020)
    Type 2 diabetes (T2D) is defined by a single metabolite, glucose, but is increasingly recognized as a highly heterogeneous disease, including individuals with varying clinical characteristics, disease progression, drug response, and risk of complications. Identification of subtypes with differing risk profiles and disease etiologies at diagnosis could open up avenues for personalized medicine and allow clinical resources to be focused to the patients who would be most likely to develop diabetic complications, thereby both improving patient health and reducing costs for the health sector. More homogeneous populations also offer increased power in experimental, genetic, and clinical studies. Clinical parameters are easily available and reflect relevant disease pathways, including the effects of both genetic and environmental exposures. We used six clinical parameters (GAD autoantibodies, age at diabetes onset, HbA(1c), BMI, and measures of insulin resistance and insulin secretion) to cluster adult-onset diabetes patients into five subtypes. These subtypes have been robustly reproduced in several populations and associated with different risks of complications, comorbidities, genetics, and response to treatment. Importantly, the group with severe insulin-deficient diabetes (SIDD) had increased risk of retinopathy and neuropathy, whereas the severe insulin-resistant diabetes (SIRD) group had the highest risk for diabetic kidney disease (DKD) and fatty liver, emphasizing the importance of insulin resistance for DKD and hepatosteatosis in T2D. In conclusion, we believe that subclassification using these highly relevant parameters could provide a framework for personalized medicine in diabetes.