Author
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FRETTS, AMANDA - University Of Washington |
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FOLLIS, JACK - University Of St Thomas |
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NETTLETON, JENNIFER - University Of Texas Health Science Center |
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LEMAITRE, ROZENN - University Of Washington |
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NGWA, JULIUS - Boston University |
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WOJCZYNSKI, MARK - Washington University |
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KALAFATI, IOANNA - Harokopio University Of Athens |
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VARGA, TIBOR - Lund University |
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FRAZIER-WOOD, ALEXIS - Baylor College Of Medicine |
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HOUSTON, DENISE - Wake Forest School Of Medicine |
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LAHTI, JARI - University Of Helsinki |
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ERICSON, ULRIKA - Lund University |
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VAN DEN HOOVEN, EDITH - Erasmus University |
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MIKKILA, VERA - University Of Turku |
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KIEFTE-DE JONG, JESSICA - Erasmus University |
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MOZAFFARIAN, DARIUSH - Jean Mayer Human Nutrition Research Center On Aging At Tufts University |
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RICE, KENNETH - University Of Washington |
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RENSTROM, FRIDA - Lund University |
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NORTH, KARI - University Of North Carolina |
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MCKEOWN, NICOLA - Jean Mayer Human Nutrition Research Center On Aging At Tufts University |
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FEITOSA, MARY - Washington University |
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KANONI, STAVROULA - Queen Mary University Of London |
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SMITH, CAREN - Jean Mayer Human Nutrition Research Center On Aging At Tufts University |
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GARCIA, MELISSA - National Institute For Health And Welfare (HELSINKI) |
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TIAINEN, ANNA-MAIJA - National Institute For Health And Welfare (HELSINKI) |
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SONESTEDT, EMILY - Lund University |
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MANICHAIKUL, ANI - University Of Virginia |
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VAN ROOIJ, FRANK J - Erasmus University |
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DIMITRIOUS, MARIA - Harokopio University Of Athens |
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RAITAKARA, OLLI - University Of Turku |
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PANKOW, JAMES - University Of Minnesota |
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DJOUSSE, LUC - Brigham & Women'S Hospital |
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PROVINCE, MICHAEL - Washington University |
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HU, FRANK - Harvard Medical School |
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Lai, Chao Qiang |
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KELLER, MARGAUX - National Institute On Aging (NIA, NIH) |
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PERALA, MIA-MARIA - National Institute For Health And Welfare (HELSINKI) |
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ROTTER, JEROME - Harbor-Ucla Medical Center |
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HOFMAN, ALBERT - Erasmus University |
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GRAFF, MISA - University Of North Carolina |
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KAHONEN, MIKA - Tampere University Hospital |
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MUKAMAL, KENNETH - Beth Israel Deaconess Medical Center |
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JOHANSSON, INGEGERD - University Of Umea |
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ORDOVAS, JOSE - Jean Mayer Human Nutrition Research Center On Aging At Tufts University |
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LIU, YONGMEI - Wake Forest School Of Medicine |
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MANNISTO, SATU - National Institute For Health And Welfare (HELSINKI) |
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UTTERLINDEN, ANDRE - Erasmus University |
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DELOUKAS, PANOS - Queen Mary University Of London |
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SEPPALA, ILKKA - Tampere University Hospital |
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PSATY, BRUCE - University Of Washington |
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CUPPLES, L - Boston University |
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BORECKI, INGRID - Washington University |
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FRANKS, PAUL - University Of Umea |
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ARNETT, DONNA - University Of Alabama |
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NALLS, MIKE - National Institute On Aging (NIA, NIH) |
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ERIKSSON, JOHAN - University Of Helsinki |
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ORHO-MELANDER, MARJU - Lund University |
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FRANCO, OSCAR - University Of Turku |
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LEHTIMAKI, TERHO - University Of Tampere Medical School |
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DEDOUSSIS, GEORGE - Harokopio University Of Athens |
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MEIGS, JAMES - Massachusetts General Hospital |
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SISCOVICK, DAVID - University Of Washington |
Submitted to: The American Journal of Clinical Nutrition
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 8/5/2015 Publication Date: 9/9/2015 Citation: Fretts, A.M., Follis, J.L., Nettleton, J.A., Lemaitre, R.N., Ngwa, J.S., Wojczynski, M.K., Kalafati, I.P., Varga, T.V., Frazier-Wood, A.C., Houston, D.K., Lahti, J., Ericson, U., Van Den Hooven, E.H., Mikkila, V., Kiefte-De Jong, J.C., Mozaffarian, D., Rice, K., Renstrom, F., North, K.E., Mckeown, N.M., Feitosa, M.F., Kanoni, S., Smith, C.E., Garcia, M.E., Tiainen, A., Sonestedt, E., Manichaikul, A., Van Rooij, F.A., Dimitrious, M., Raitakara, O., Pankow, J.S., Djousse, L., Province, M.A., Hu, F.B., Lai, C., Keller, M.F., Perala, M., Rotter, J.I., Hofman, A., Graff, M., Kahonen, M., Mukamal, K., Johansson, I., Ordovas, J.M., Liu, Y., Mannisto, S., Utterlinden, A.G., Deloukas, P., Seppala, I., Psaty, B.M., Cupples, L.A., Borecki, I.B., Franks, P.W., Arnett, D.K., Nalls, M.A., Eriksson, J.G., Orho-Melander, M., Franco, O.H., Lehtimaki, T., Dedoussis, G.V., Meigs, J.B., Siscovick, D.S. 2015. Consumption of meat is associated with higher fasting glucose and insulin concentrations regardless of glucose and insulin genetic risk scores: a meta-analysis of 50,345 Caucasians. American Journal of Clinical Nutrition. 102:1266-1278. doi:10.3975/ajcn.114.101238. Interpretive Summary: Diabetes is a growing global problem that affects an individual’s ability to metabolize glucose, resulting in elevated insulin and glucose in the blood. The causes of increased insulin and glucose concentrations are not completely understood, but are related to genetic and dietary factors that have been investigated in many previous studies. Meat consumption and processed meat consumption have been associated with an increased risk of diabetes in some. In addition, a set of genetic variants has also been associated with diabetes-related traits. In the current study, the authors hypothesized that individuals’ responses to meat will vary according to their genetic background. The investigators first evaluated relationships between red meat and processed meat (e.g., hotdogs, bologna, sausage, bacon) and glucose and insulin, without considering genetics. Next, they evaluated whether a previously reported set of genetic variants influenced the glucose and insulin response to meat and processed meat. This type of study is called a gene-diet interaction study, since it examines the role of diet and the role of genes at the same time. Like many interaction studies, the current study was conducted in a large number of individuals (50,345) from the US and Europe. The investigators observed that the consumption of processed meat was associated with higher glucose, and the consumption of unprocessed red meat was associated with higher glucose and insulin. These observations were not affected by the set of genetic variants; that is: they did not find a gene-diet interaction. Although this study did not detect an interaction between meat intake and the particular set of genetic variants that they examined, the authors cannot rule out the possibility that other, unknown genetic factors might affect peoples’ glucose and insulin responses to eating meat. The investigators also note that their study was limited to individuals of European ancestry (whites), so that these results might not apply to people of other ancestries (e.g., Asian, African, Native Americans. Additional research including more genetic variants and/or people of different racial and ethnic backgrounds is needed. Technical Abstract: BACKGROUND: Recent studies suggest that meat intake is associated with diabetes-related phenotypes. However, whether the associations of meat intake and glucose and insulin homeostasis are modified by genes related to glucose and insulin is unknown. OBJECTIVE: We investigated the associations of meat intake and the interaction of meat with genotype on fasting glucose and insulin concentrations in Caucasians free of diabetes mellitus. DESIGN: Fourteen studies that are part of the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium participated in the analysis. Data were provided for up to 50,345 participants. Using linear regression within studies and a fixed-effects meta-analysis across studies, we examined 1) the associations of processed meat and unprocessed red meat intake with fasting glucose and insulin concentrations; and 2) the interactions of processed meat and unprocessed red meat with genetic risk score related to fasting glucose or insulin resistance on fasting glucose and insulin concentrations. RESULTS: Processed meat was associated with higher fasting glucose, and unprocessed red meat was associated with both higher fasting glucose and fasting insulin concentrations after adjustment for potential confounders [not including body mass index (BMI)]. For every additional 50-g serving of processed meat per day, fasting glucose was 0.021 mmol/L (95% CI: 0.011, 0.030 mmol/L) higher. Every additional 100-g serving of unprocessed red meat per day was associated with a 0.037-mmol/L (95% CI: 0.023, 0.051-mmol/L) higher fasting glucose concentration and a 0.049-ln-pmol/L (95% CI: 0.035, 0.063-ln-pmol/L) higher fasting insulin concentration. After additional adjustment for BMI, observed associations were attenuated and no longer statistically significant. The association of processed meat and fasting insulin did not reach statistical significance after correction for multiple comparisons. Observed associations were not modified by genetic loci known to influence fasting glucose or insulin resistance. CONCLUSION: The association of higher fasting glucose and insulin concentrations with meat consumption was not modified by an index of glucose- and insulin-related single-nucleotide polymorphisms. Six of the participating studies are registered at clinicaltrials.gov as NCT0000513 (Atherosclerosis Risk in Communities), NCT00149435 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetics of Lipid Lowering Drugs and Diet Network), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis). |