The Journal of clinical endocrinology and metabolism · 2013
Top single nucleotide polymorphisms affecting carbohydrate metabolism in metabolic syndrome: from the LIPGENE study.
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Delgado-Lista Javier, Perez-Martinez Pablo, Solivera Juan, Garcia-Rios Antonio, Perez-Caballero A I, Lovegrove Julie A, Drevon Christian A, Defoort Catherine, Blaak Ellen E, Dembinska-Kieć Aldona, Risérus Ulf, Herruzo-Gomez Ezequiel, Camargo Antonio, Ordovas Jose M, Roche Helen, Lopez-Miranda José
Аннотация
RATIONALE: Metabolic syndrome (MetS) is a high-prevalence condition characterized by altered energy metabolism, insulin resistance, and elevated cardiovascular risk.
OBJECTIVES: Although many individual single nucleotide polymorphisms (SNPs) have been linked to certain MetS features, there are few studies analyzing the influence of SNPs on carbohydrate metabolism in MetS.
METHODS: A total of 904 SNPs (tag SNPs and functional SNPs) were tested for influence on 8 fasting and dynamic markers of carbohydrate metabolism, by performance of an intravenous glucose tolerance test in 450 participants in the LIPGENE study.
FINDINGS: From 382 initial gene-phenotype associations between SNPs and any phenotypic variables, 61 (16% of the preselected variables) remained significant after bootstrapping. Top SNPs affecting glucose metabolism variables were as follows: fasting glucose, rs26125 (PPARGC1B); fasting insulin, rs4759277 (LRP1); C-peptide, rs4759277 (LRP1); homeostasis assessment of insulin resistance, rs4759277 (LRP1); quantitative insulin sensitivity check index, rs184003 (AGER); sensitivity index, rs7301876 (ABCC9), acute insulin response to glucose, rs290481 (TCF7L2); and disposition index, rs12691 (CEBPA).
CONCLUSIONS: We describe here the top SNPs linked to phenotypic features in carbohydrate metabolism among approximately 1000 candidate gene variations in fasting and postprandial samples of 450 patients with MetS from the LIPGENE study.
OBJECTIVES: Although many individual single nucleotide polymorphisms (SNPs) have been linked to certain MetS features, there are few studies analyzing the influence of SNPs on carbohydrate metabolism in MetS.
METHODS: A total of 904 SNPs (tag SNPs and functional SNPs) were tested for influence on 8 fasting and dynamic markers of carbohydrate metabolism, by performance of an intravenous glucose tolerance test in 450 participants in the LIPGENE study.
FINDINGS: From 382 initial gene-phenotype associations between SNPs and any phenotypic variables, 61 (16% of the preselected variables) remained significant after bootstrapping. Top SNPs affecting glucose metabolism variables were as follows: fasting glucose, rs26125 (PPARGC1B); fasting insulin, rs4759277 (LRP1); C-peptide, rs4759277 (LRP1); homeostasis assessment of insulin resistance, rs4759277 (LRP1); quantitative insulin sensitivity check index, rs184003 (AGER); sensitivity index, rs7301876 (ABCC9), acute insulin response to glucose, rs290481 (TCF7L2); and disposition index, rs12691 (CEBPA).
CONCLUSIONS: We describe here the top SNPs linked to phenotypic features in carbohydrate metabolism among approximately 1000 candidate gene variations in fasting and postprandial samples of 450 patients with MetS from the LIPGENE study.