Abstract
The treatment of Type 2 Diabetes Mellitus (T2DM) consists primarily of oral antidiabetic drugs (OADs) that stimulate insulin secretion, such as sulfonylureas (SUs) and reduce hepatic glucose production (e.g., biguanides), among others. The marked inter-individual differences among T2DM patients’ response to these drugs have become an issue on prescribing and dosing efficiently. In this study, fourteen polymorphisms selected from Genome-wide association studies (GWAS) were screened in 495 T2DM Mexican patients previously treated with OADs to find the relationship between the presence of these polymorphisms and response to the OADs. Then, a novel association screening method, based on global probabilities, was used to globally characterize important relationships between the drug response to OADs and genetic and clinical parameters, including polymorphisms, patient information, and type of treatment. Two polymorphisms, ABCC8-Ala1369Ser and KCNJ11-Glu23Lys, showed a significant impact on response to SUs. Heterozygous ABCC8-Ala1369Ser variant (A/C) carriers exhibited a higher response to SUs compared to homozygous ABCC8-Ala1369Ser variant (A/A) carriers (p-value = 0.029) and to homozygous wild-type genotypes (C/C) (p-value = 0.012). The homozygous KCNJ11-Glu23Lys variant (C/C) and wild-type (T/T) genotypes had a lower response to SUs compared to heterozygous (C/T) carriers (p-value = 0.039). The screening of OADs response related genetic and clinical factors could help improve the prescribing and dosing of OADs for T2DM patients and thus contribute to the design of personalized treatments.
Highlights
Type 2 Diabetes Mellitus (T2DM) is the most common form of diabetes in adults
A cross-sectional and retrospective study with convenience sampling was carried out in T2DM patients treated with oral antidiabetic drugs (OADs), in monotherapy or in combination for at least 6 months, to determine possible association between patient data, gene variants, and drug response assessed by HbA1c values
To study the association between diabetes-related SNPs, patient data and antidiabetic drug response, we have developed a metric called direct information (DI), which is derived from the inference framework direct coupling analysis (DCA) (Morcos et al, 2011)
Summary
Type 2 Diabetes Mellitus (T2DM) is the most common form of diabetes in adults. T2DM is associated with multiple complications, such as blindness, lower limb amputation, and premature death (Marchetti et al, 2009; Barquera et al, 2013). In Mexico, the average age for death by diabetes or its complications was 66.7 in 2010, compared with the lifespan of 76 years of non-diabetic individuals (Agudelo-Botero and Davila-Cervantes, 2015). The average annual economic cost from 2006 to 2010 of T2DM patients in Mexico was $941,345,886 USD of direct cost, $177,220,390 USD of indirect cost, and $27,969,427 USD from its complications. This immense cost, coupled with the issues of inequity and access to healthcare in Mexico, where 51% of the cost comes from household income, represents a huge social burden (Arredondo and De Icaza, 2011; Barquera et al, 2013)
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