OBJECTIVE: To investigate the association between genetic variation in the adipocyte protein perilipin (PLIN) and insulin resistance in an Asian population as well as to examine their modulation by macronutrient intake. RESEARCH DESIGN AND METHODS: A nationally representative sample (Chinese, Malays, and Indians) was selected in the Singapore National Health Survey following the World Health Organization-recommended model for field surveys of diabetes. A total of 1,909 men and 2,198 women (aged 18-69 years) were studied. Genetic (PLIN 11482G-->A and 14995A-->T), lifestyle, clinical, and biochemical data were obtained. Homeostasis model assessment of insulin resistance (HOMA-IR) was used to evaluate insulin resistance. Diet was measured by a validated food frequency questionnaire in one of every two subjects. RESULTS: We did not find a significant between-genotype difference in insulin resistance measures. However, in women we found statistically significant gene-diet interactions (recessive model) between PLIN 11482G-->A/14995A-->T polymorphisms (in high linkage disequilibrium) and saturated fatty acids (SFAs; P = 0.003/0.005) and carbohydrate (P = 0.004/0.012) in determining HOMA-IR. These interactions were in opposite directions and were more significant for 11482G-->A, considered the tag polymorphism. Thus, women in the highest SFA tertile (11.8-19%) had higher HOMA-IR (48% increase; P trend = 0.006) than women in the lowest (3.1-9.4%) only if they were homozygotes for the PLIN minor allele. Conversely, HOMA-IR decreased (-24%; P trend = 0.046) as carbohydrate intake increased. These effects were stronger when SFAs and carbohydrate were combined as an SFA-to-carbohydrate ratio. Moreover, this gene-diet interaction was homogeneously found across the three ethnic groups. CONCLUSIONS: PLIN 11482G-->A/14995A-->T polymorphisms modulate the association between SFAs/carbohydrate in diet and insulin resistance in Asian women.
OBJECTIVE: To investigate the association between genetic variation in the adipocyte protein perilipin (PLIN) and insulin resistance in an Asian population as well as to examine their modulation by macronutrient intake. RESEARCH DESIGN AND METHODS: A nationally representative sample (Chinese, Malays, and Indians) was selected in the Singapore National Health Survey following the World Health Organization-recommended model for field surveys of diabetes. A total of 1,909 men and 2,198 women (aged 18-69 years) were studied. Genetic (PLIN 11482G-->A and 14995A-->T), lifestyle, clinical, and biochemical data were obtained. Homeostasis model assessment of insulin resistance (HOMA-IR) was used to evaluate insulin resistance. Diet was measured by a validated food frequency questionnaire in one of every two subjects. RESULTS: We did not find a significant between-genotype difference in insulin resistance measures. However, in women we found statistically significant gene-diet interactions (recessive model) between PLIN 11482G-->A/14995A-->T polymorphisms (in high linkage disequilibrium) and saturated fatty acids (SFAs; P = 0.003/0.005) and carbohydrate (P = 0.004/0.012) in determining HOMA-IR. These interactions were in opposite directions and were more significant for 11482G-->A, considered the tag polymorphism. Thus, women in the highest SFA tertile (11.8-19%) had higher HOMA-IR (48% increase; P trend = 0.006) than women in the lowest (3.1-9.4%) only if they were homozygotes for the PLIN minor allele. Conversely, HOMA-IR decreased (-24%; P trend = 0.046) as carbohydrate intake increased. These effects were stronger when SFAs and carbohydrate were combined as an SFA-to-carbohydrate ratio. Moreover, this gene-diet interaction was homogeneously found across the three ethnic groups. CONCLUSIONS:PLIN 11482G-->A/14995A-->T polymorphisms modulate the association between SFAs/carbohydrate in diet and insulin resistance in Asian women.
Authors: José López-Miranda; Pablo Pérez-Martínez; Carmen Marin; Francisco Fuentes; Javier Delgado; Francisco Pérez-Jiménez Journal: J Mol Med (Berl) Date: 2006-12-15 Impact factor: 4.599
Authors: Michael Fenech; Ahmed El-Sohemy; Leah Cahill; Lynnette R Ferguson; Tapaeru-Ariki C French; E Shyong Tai; John Milner; Woon-Puay Koh; Lin Xie; Michelle Zucker; Michael Buckley; Leah Cosgrove; Trevor Lockett; Kim Y C Fung; Richard Head Journal: J Nutrigenet Nutrigenomics Date: 2011-05-28
Authors: Hassan S Dashti; Caren E Smith; Yu-Chi Lee; Laurence D Parnell; Chao-Qiang Lai; Donna K Arnett; José M Ordovás; Marta Garaulet Journal: Chronobiol Int Date: 2014-02-18 Impact factor: 2.877