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Interplay of an Obesity-Based Genetic Risk Score with Dietary and Endocrine Factors on Insulin Resistance

This study aimed to nutrigenetically screen gene-diet and gene-metabolic interactions influencing insulin resistance (IR) phenotypes. A total of 232 obese or overweight adults were categorized by IR status: non-IR (HOMA-IR (homeostatic model assessment - insulin resistance) index ≤ 2.5) and IR (HOMA...

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Detalles Bibliográficos
Autores principales: Ramos-Lopez, Omar, Riezu-Boj, José Ignacio, Milagro, Fermin I., Cuervo, Marta, Goni, Leticia, Martinez, J. Alfredo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7019905/
https://www.ncbi.nlm.nih.gov/pubmed/31877696
http://dx.doi.org/10.3390/nu12010033
Descripción
Sumario:This study aimed to nutrigenetically screen gene-diet and gene-metabolic interactions influencing insulin resistance (IR) phenotypes. A total of 232 obese or overweight adults were categorized by IR status: non-IR (HOMA-IR (homeostatic model assessment - insulin resistance) index ≤ 2.5) and IR (HOMA-IR index > 2.5). A weighted genetic risk score (wGRS) was constructed using 95 single nucleotide polymorphisms related to energy homeostasis, which were genotyped by a next generation sequencing system. Body composition, the metabolic profile and lifestyle variables were evaluated, where individuals with IR showed worse metabolic outcomes. Overall, 16 obesity-predisposing genetic variants were associated with IR (p < 0.10 in the multivariate model). The wGRS strongly associated with the HOMA-IR index (adj. R squared = 0.2705, p < 0.0001). Moreover, the wGRS positively interacted with dietary intake of cholesterol (P int. = 0.002), and with serum concentrations of C-reactive protein (P int. = 0.008) regarding IR status, whereas a negative interaction was found regarding adiponectin blood levels (P int. = 0.006). In conclusion, this study suggests that interactions between an adiposity-based wGRS with nutritional and metabolic/endocrine features influence IR phenotypes, which could facilitate the prescription of personalized nutrition recommendations for precision prevention and management of IR and diabetes.