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ARS Home » Northeast Area » Boston, Massachusetts » Research » Publications at this Location » Publication #284737
Title: Perilipin polymorphism interacts with saturated fat and carbohydrates to modulate insulin resistance

Author
item SMITH, CAREN - Jean Mayer Human Nutrition Research Center On Aging At Tufts University
item ARNETT, DONNA - University Of Alabama
item CORELLA, DOLORES - University Of Valencia
item TSAI, MICHAEL - University Of Minnesota
item Lai, Chao Qiang
item Parnell, Laurence
item LEE, YU-CHI - Jean Mayer Human Nutrition Research Center On Aging At Tufts University
item ORDOVAS, JOSE - Jean Mayer Human Nutrition Research Center On Aging At Tufts University

Submitted to: Nutrition, Metabolism and Cardiovascular Diseases
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/1/2010
Publication Date: 5/1/2012
Citation: Smith, C.E., Arnett, D.K., Corella, D., Tsai, M.Y., Lai, C., Parnell, L.D., Lee, Y., Ordovas, J.M. 2012. Perilipin polymorphism interacts with saturated fat and carbohydrates to modulate insulin resistance. Nutrition, Metabolism and Cardiovascular Diseases. 22(5):449-455.

Interpretive Summary: Insulin resistance refers to the body’s inability to respond to the hormone insulin, which is needed in order for the cells to use glucose as fuel. Individuals who develop insulin resistance are at risk of progressing to type 2 diabetes. Although obesity is a major risk factor for insulin resistance, genetic and dietary factors have also been shown to play a role in its development. Variations in the perilipin 1 gene, which regulates the metabolism of the cells that store fat (adipocytes), have been reported to be associated with risk of both obesity and insulin resistance. Dietary factors have been shown to modify this association. In a group of Singaporean Asian women, those who carried a particular perilipin 1 variant and who also consumed a large amount of saturated fat, relative to the amount of carbohydrate, were more likely to have insulin resistance. In the current study, we sought to replicate that finding in an independent population living in the US. We observed similar relationships between the same perilipin 1 variant and the same nutrients in women in this second population, which increases our confidence that the original results are reliable. Replication studies of this type are necessary before gene-diet interactions can be applied in the design of tailored dietary recommendations.

Technical Abstract: Macronutrient intakes and genetic variants have been shown to interact to alter insulin resistance, but replications of gene-nutrient interactions across independent populations are rare, despite their critical importance in establishing credibility. We aimed to investigate a previously demonstrated saturated fat and carbohydrate interaction for insulin resistance for perilipin (PLIN1), a regulator of adipocyte metabolism. We investigated the previously shown interaction for PLIN1 11482G>A (rs894160) on insulin resistance in US men (n = 462) and women (n =508) (mean SD, 49+/-16 years). In multivariable linear regression models, we found an interaction (P less than 0.05) between the ratio of saturated fat to carbohydrate intake as a continuous variable and PLIN1 11482G>A for HOMA-IR (homeostasis model assessment of insulin resistance) in women. For carriers of the minor allele but not for non-carriers, as the ratio of saturated fat to carbohydrate intake increased, predicted HOMA-IR increased (P=0.002). By dichotomizing the ratio of saturated fat to carbohydrate intake into high and low, we found significant interaction terms for insulin and HOMA-IR (P less than 0.05). When the ratio of saturated fat to carbohydrate was high, insulin and HOMA-IR were higher in minor allele carriers (P=0.004 and P=0.003, respectively), but did not differ when the ratio was low. Similar patterns or trends were observed when saturated fat and carbohydrate were dichotomized into high and low as individual macronutrients. Replication of the previously reported interaction between macronutrient intakes and PLIN1 genotype for insulin resistance reinforces the potential usefulness of applying genotype information in the dietary management of insulin resistance.