Impact of APOE Alleles-by-Diet Interactions on Glycemic and Lipid Features- A Cross-Sectional Study of a Cohort of Type 2 Diabetes Patients from Western Mexico: Implications for Personalized Medicine

• Published in: Pharmacogenomics and personalized medicine 2020-01, Vol.13, p.655-663
• Main Authors: Torres-Valadez, Rafael, Ramos-Lopez, Omar, Frías Delgadillo, Kevin J, Flores-García, Aurelio, Rojas Carrillo, Esaú, Aguiar-García, Pedro, Bernal Pérez, J Antonio, Martinez-Lopez, Erika, Martínez, J Alfredo, Zepeda-Carrillo, Eloy A
• Format: Article
• Language: English
• Subjects: Alleles; apoe alleles; Apolipoprotein E; Automation; Blood levels; Cholesterol; Cross-sectional studies; Diabetes; Diabetes mellitus (non-insulin dependent); Diet; Dietary intake; Disease; Energy intake; Food; Food consumption; gene-nutrient interactions; Genotyping; Glibenclamide; Glucose; glycemic control; High density lipoprotein; Insulin; Lipids; Lipoproteins; Low density lipoprotein; Medical records; Metabolism; Metformin; Mortality; Nutrition research; Original Research; Patients; personalized medicine; Phenotypes; Plasma; Precision medicine; Software; Statistical analysis; Triglycerides; type 2 diabetes; ω-6:ω-3 pufa ratio
• ISSN: 1178-7066; 1178-7066
• DOI: 10.2147/PGPM.S277952

To analyze clinically relevant interactions between the apolipoprotein E ( ) ε2, ε3 and ε4 alleles and nutritional factors on glycemic control and lipid levels in a cohort of type 2 diabetes (T2D) patients from western Mexico. In this cross-sectional study of the cohort of T2D patients, a total of 224 individuals were selected for interaction studies. Clinical and anthropometric data were obtained from pre-designed medical records. Dietary intake was assessed by validated three-day food consumption records. Biochemical measurements were determined by automated methods. genotyping was performed by a real-time allelic discrimination assay. Gene-diet interactions were tested by corrected multiple linear regression analyses, which were adjusted by potential confounding factors such as age, sex, energy intake, BMI and anti-hyperglycemic therapy (Metformin, Glibenclamide or Insulin), and years with T2D. Seventy-six percent of patients with T2D were on Metformin therapy. The frequencies of the alleles were ε2 (5.8%), ε3 (74.1%) and ε4 (20.1%). After statistical settings, significant alleles-by-diet interactions in relation to the metabolic profile were found. Interestingly, higher blood levels of total cholesterol (p int. = 0.016), non-HDL-c (p int. = 0.024), and LDL-c (p int. = 0.030) were found only in carriers of the ε2 allele with a low consumption of MUFA. In contrast, carriers of the ε4 allele with a high ω-6:ω-3 PUFA ratio in the diet had higher %HbA1c blood concentrations (p int. = 0.035). This study suggests a differential metabolic impact of alleles on lipid/glycemic phenotypes depending on the dietary intake, with important potential implications in the personalized medicine and nutritional management of patients with type 2 diabetes mellitus.