OBJECTIVE: There is considerable interindividual variation in sulfonylurea response in type 2 diabetes. Transcription factor 7-like 2 (TCF7L2) variants have been identified to be strongly associated with type 2 diabetes risk, probably due to decreased beta-cell function. We hypothesized that variation in TCF7L2 would influence response to sulfonylureas but not metformin. We studied the effect of TCF7L2 rs12255372 and rs7903146 genotypes on glycemic response. RESEARCH DESIGN AND METHODS: The DARTS/MEMO (Diabetes Audit and Research Tayside/Medicines Monitoring Unit) collaboration database includes prescribing, biochemistry, and clinical phenotype of all patients with diabetes within Tayside, Scotland, from 1992. Of these, the TCF7L2 genotype was determined in 4,469 patients with type 2 diabetes recruited to GoDARTS (Genetics of Diabetes Audit and Research Tayside) between 1997 and July 2006. A total of 901 incident sulfonylurea users and 945 metformin users were identified. A logistic regression was used with treatment failure defined as an A1C >7% within 3-12 months after treatment initiation. Covariates included the TCF7L2 genotype, BMI, sex, age diagnosed, drug adherence, and drug dose. A1C pretreatment was available in a subset of patients (sulfonylurea n = 579; metformin n = 755). RESULTS: Carriers of the risk allele were less likely to respond to sulfonylureas with an odds ratio (OR) for failure of 1.95 (95% CI 1.23-3.06; P = 0.005), comparing rs12255372 T/T vs. G/G. Including the baseline A1C strengthened this association (OR 2.16 [95% CI 1.21-3.86], P = 0.009). A similar, although slightly weaker, association was seen with rs7903146. No association was seen between metformin response and either single nucleotide polymorphism, after adjustment for baseline A1C. CONCLUSIONS: TCF7L2 variants influence therapeutic response to sulfonylureas but not metformin. This study establishes that genetic variation can alter response to therapy in type 2 diabetes.
OBJECTIVE: There is considerable interindividual variation in sulfonylurea response in type 2 diabetes. Transcription factor 7-like 2 (TCF7L2) variants have been identified to be strongly associated with type 2 diabetes risk, probably due to decreased beta-cell function. We hypothesized that variation in TCF7L2 would influence response to sulfonylureas but not metformin. We studied the effect of TCF7L2rs12255372 and rs7903146 genotypes on glycemic response. RESEARCH DESIGN AND METHODS: The DARTS/MEMO (Diabetes Audit and Research Tayside/Medicines Monitoring Unit) collaboration database includes prescribing, biochemistry, and clinical phenotype of all patients with diabetes within Tayside, Scotland, from 1992. Of these, the TCF7L2 genotype was determined in 4,469 patients with type 2 diabetes recruited to GoDARTS (Genetics of Diabetes Audit and Research Tayside) between 1997 and July 2006. A total of 901 incident sulfonylurea users and 945 metformin users were identified. A logistic regression was used with treatment failure defined as an A1C >7% within 3-12 months after treatment initiation. Covariates included the TCF7L2 genotype, BMI, sex, age diagnosed, drug adherence, and drug dose. A1C pretreatment was available in a subset of patients (sulfonylurea n = 579; metformin n = 755). RESULTS: Carriers of the risk allele were less likely to respond to sulfonylureas with an odds ratio (OR) for failure of 1.95 (95% CI 1.23-3.06; P = 0.005), comparing rs12255372 T/T vs. G/G. Including the baseline A1C strengthened this association (OR 2.16 [95% CI 1.21-3.86], P = 0.009). A similar, although slightly weaker, association was seen with rs7903146. No association was seen between metformin response and either single nucleotide polymorphism, after adjustment for baseline A1C. CONCLUSIONS:TCF7L2 variants influence therapeutic response to sulfonylureas but not metformin. This study establishes that genetic variation can alter response to therapy in type 2 diabetes.
Authors: M A Daniels; C Kan; D M Willmes; K Ismail; F Pistrosch; D Hopkins; G Mingrone; S R Bornstein; A L Birkenfeld Journal: Pharmacogenomics J Date: 2016-07-19 Impact factor: 3.550
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