Association of β1 and β3 adrenergic receptors gene polymorphisms with insulin resistance and high lipid profiles related to type 2 diabetes and metabolic syndrome.

Association of β1 and β3 adrenergic receptors gene polymorphisms with insulin resistance and high lipid profiles related to type 2 diabetes and metabolic syndrome.

Nutrición Hospitalaria, June 2014

24972470

Ana I Burguete-Garcia, Gabriela A Martinez-Nava, Adan Valladares-Salgado, V H Bermudez Morales, Barbara Estrada-Velasco, Niels Wacher, Jesus Peralta-Romero, Jaime Garcia-Mena, Esteban Parra, Miguel Cruz

Background: Among the diverse genes associated to type 2 diabetes (T2D), the -adrenergic receptors are an excellent candidate to study in Mexican population. The objective of this work was to analyze the association of polymorphisms in ADRB1 (rs1801253) (Arg389Gly) and ADRB3 (Trp64Arg) genes with T2D and metabolic syndrome (MS). Methods: We studied 445 MS patients, 502 with T2D and 552 healthy controls. Anthropometric features and complete biochemical profile were evaluated, and Arg389Gly and Trp64Arg SNPs were determined by TaqMan assays. Data analysis was adjusted by African, Caucasian and Amerindian ancestral percentage. Results: The variant Arg389Gly of ADRB1 was statistically associated with an increase of LDL levels (P < 0.008), and the variant ADRB3 Trp64Arg was associated to larger HOMA-IR (P < 0.018) and with an increase of insulin levels (P < 0.001). A multiple logistic regression analysis was made in three grouping models: For ADRB3 in the codominant model Trp/Arg genotype, there was an OR of 1.53 (1.09-2.13, P < 0.003) which was increased up to OR 2.99 (1.44-6.22, P < 0.003) for the Arg/Arg genotype. Similar risk association was found under the dominant model Trp/Arg-Arg/Arg genotype with OR 1.67 (1.21-2.30; P < 0.002). In the recessive model (Arg/Arg genotype), there was also a high association OR 2.56 (1.24-5.26, P < 0.01). Conclusions: The ADRB3 Trp64Arg variant is a susceptibility gene polymorphism for T2D and the ADRB1 Gly389Arg for lipid metabolism disruption. These results show that these variants are potential biomarkers for predicting metabolic alterations and evolution in diabetic and metabolic syndrome patients.