Prostaglandin E synthase 2 (<i>PTGES2</i>) <i>Arg298His</i> polymorphism and parameters of the metabolic syndrome

Lindner, Inka; Helwig, Ulf; Rubin, Diana; Fischer, Alexandra; Marten, Berit; Schreiber, Stefan; Döring, Frank; Schrezenmeir, Jürgen

doi:10.1002/mnfr.200700144

Cited by 12 publications

(6 citation statements)

References 21 publications

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“…SNPs identified in genome wide association studies of body mass index or obesity (INSIG2 rs7566605 [15], FTO rs9939609 [16], MC4R rs17700144 [17], TMEM18 rs11127485 [17], NPC1 rs1805081 [18]), reported to be associated with body weight, body mass index, body composition indices (fat mass, fat-free mass, percentage body fat or sum of skinfolds), body fat distribution indices (waist circumference, waist-to-hip ratio, abdominal visceral and subcutaneous fat), leanness or obesity in human populations (MTTP rs3816873 [3], SREBF1 rs2297508 [19], LEPR (rs1137100 [3], rs1137101 [3], rs8179183 [3]), PPARG rs1801282 [3], FABP2 (rs6857641 [3], rs1799883 [3]), FABP1 rs2241883 [20], TCF7L2 rs7903146 [3], PTGES2 rs132823456 [21]) or located within quantitative trait loci (QTL) which constitute potential candidates influencing obesity-related phenotypes (ABCC8 [22], HSD11B1 [23], ALPI [24], IGF1 [25], TBC1D1 [26], M4CR [27], [28]) were included in the statistical modeling.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of 41 Candidate Gene Variants for Obesity in the EPIC-Potsdam Cohort by Multi-Locus Stepwise Regression

et al. 2013

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ObjectiveObesity has become a leading preventable cause of morbidity and mortality in many parts of the world. It is thought to originate from multiple genetic and environmental determinants. The aim of the current study was to introduce haplotype-based multi-locus stepwise regression (MSR) as a method to investigate combinations of unlinked single nucleotide polymorphisms (SNPs) for obesity phenotypes.MethodsIn 2,122 healthy randomly selected men and women of the EPIC-Potsdam cohort, the association between 41 SNPs from 18 obesity-candidate genes and either body mass index (BMI, mean = 25.9 kg/m2, SD = 4.1) or waist circumference (WC, mean = 85.2 cm, SD = 12.6) was assessed. Single SNP analyses were done by using linear regression adjusted for age, sex, and other covariates. Subsequently, MSR was applied to search for the ‘best’ SNP combinations. Combinations were selected according to specific AICc and p-value criteria. Model uncertainty was accounted for by a permutation test.ResultsThe strongest single SNP effects on BMI were found for TBC1D1 rs637797 (β = −0.33, SE = 0.13), FTO rs9939609 (β = 0.28, SE = 0.13), MC4R rs17700144 (β = 0.41, SE = 0.15), and MC4R rs10871777 (β = 0.34, SE = 0.14). All these SNPs showed similar effects on waist circumference. The two ‘best’ six-SNP combinations for BMI (global p-value = 3.45⋅10–6 and 6.82⋅10–6) showed effects ranging from −1.70 (SE = 0.34) to 0.74 kg/m2 (SE = 0.21) per allele combination. We selected two six-SNP combinations on waist circumference (global p-value = 7.80⋅10–6 and 9.76⋅10–6) with an allele combination effect of −2.96 cm (SE = 0.76) at maximum. Additional adjustment for BMI revealed 15 three-SNP combinations (global p-values ranged from 3.09⋅10–4 to 1.02⋅10–2). However, after carrying out the permutation test all SNP combinations lost significance indicating that the statistical associations might have occurred by chance.ConclusionMSR provides a tool to search for risk-related SNP combinations of common traits or diseases. However, the search process does not always find meaningful SNP combinations in a dataset.

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Section: Methodsmentioning

confidence: 99%

Evaluation of 41 Candidate Gene Variants for Obesity in the EPIC-Potsdam Cohort by Multi-Locus Stepwise Regression

et al. 2013

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“…Insulin resistance was associated with elevated plasma prostanoid levels,9 and patients with an early development of type 2 diabetes showed signs of increased cyclooxygenase‐mediated inflammation in a cohort of elderly men 10. Furthermore, polymorphisms in the gene of the cyclooxygenase11 and the PGE 2 synthase12, 13 were correlated with the development of type 2 diabetes. Thus, although no direct evidence has been provided so far, prostaglandins in addition to cytokines might contribute to the development of insulin resistance.…”

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confidence: 99%

Aggravation by prostaglandin E2 of interleukin-6-dependent insulin resistance in hepatocytes

Henkel

Neuschäfer-Rube

Pathe-Neuschäfer-Rube

et al. 2009

Hepatology

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Hepatic insulin resistance is a major contributor to fasting hyperglycemia in patients with metabolic syndrome and type 2 diabetes. Circumstantial evidence suggests that cyclooxygenase products in addition to cytokines might contribute to insulin resistance. However, direct evidence for a role of prostaglandins in the development of hepatic insulin resistance is lacking. Therefore, the impact of prostaglandin E 2 (PGE 2 ) alone and in combination with interleukin-6 (IL-6) on insulin signaling was studied in primary hepatocyte cultures. Rat hepatocytes were incubated with IL-6 and/or PGE 2 and subsequently with insulin. Glycogen synthesis was monitored by radiochemical analysis; the activation state of proteins of the insulin receptor signal chain was analyzed by western blot with phosphospecific antibodies. In hepatocytes, insulin-stimulated glycogen synthesis and insulin-dependent phosphorylation of Akt-kinase were attenuated synergistically by prior incubation with IL-6 and/or PGE 2 while insulin receptor autophosphorylation was barely affected. IL-6 but not PGE 2 induced suppressors of cytokine signaling (SOCS3). PGE 2 but not IL-6 activated extracellular signal-regulated kinase 1/2 (ERK1/2) persistently. Inhibition of ERK1/2 activation by PD98059 abolished the PGE 2 -dependent but not the IL-6-dependent attenuation of insulin signaling. In HepG2 cells expressing a recombinant EP3-receptor, PGE 2 pre-incubation activated ERK1/2, caused a serine phosphorylation of insulin receptor substrate 1 (IRS1), and reduced the insulin-dependent Akt-phosphorylation. Conclusion: PGE 2 might contribute to hepatic insulin resistance via an EP3-receptor-dependent ERK1/2 activation resulting in a serine phosphorylation of insulin receptor substrate, thereby preventing an insulindependent activation of Akt and glycogen synthesis. Since different molecular mechanisms appear to be employed, PGE 2 may synergize with IL-6, which interrupted the insulin receptor signal chain, principally by an induction of SOCS, namely SOCS3. (HEPATOLOGY 2009;50: 781-790.)

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“…Nitz et al reported a protective Arg298His polymorphism (rs13283456) in the PTGES2 gene that was negatively associated with type 2 diabetes in two German populations [26]. The protective allele was also associated with lower insulin resistance in another German population, probably through its effect on body mass index [27]. The Arg298His polymorphism is located close to the chromosome region 9q34.13 which shows significant linkage to body weight.…”

Section: Discussionmentioning

confidence: 99%

Genetic variation in the carbonyl reductase 3 gene confers risk of type 2 diabetes and insulin resistance: a potential regulator of adipogenesis

et al. 2012

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Prostaglandins are potent modulators of insulin sensitivity. We systemically evaluated the association of 61 tag single-nucleotide polymorphisms (SNP) in 14 genes involved in prostaglandin metabolism with type 2 diabetes. Among all genotyped SNPs, rs10483032 in the CBR3 (carbonyl reductase 3) gene, which encodes for an enzyme converting prostaglandin E(2) to prostaglandin F2(α), was associated with type 2 diabetes in 760 type 2 diabetic cases and 760 controls (stage-1 study) (P = 2.0 × 10(-4)). The association was validated in 1,615 cases and 1,162 controls (stage-2 study) (P = 0.009). The A allele at rs10483032 was associated with increased risk of type 2 diabetes (odds ratio = 1.29; 95% confidence interval = 1.14-1.47; combined P < 0.0001). The association was externally validated in the Finland-United States Investigation of NIDDM Genetics (FUSION) study (P = 3.7 × 10(-4)). The risk A allele was associated with higher homeostasis model assessment of insulin resistance (HOMA-IR) in 1,012 non-diabetic controls and 1,138 non-diabetic subjects from the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance (SAPPHIRe) family study. CBR3 gene expression in human abdominal adipose tissue was negatively associated with fasting insulin and HOMA-IR. CBR3 gene expression increased during differentiation of 3T3-L1 preadipocytes into adipocytes. Knockdown of CBR3 in 3T3-L1 preadipocytes enhanced adipogenesis and peroxisome proliferator-activator receptor-γ response element reporter activity. Our results indicated that genetic polymorphism in the CBR3 gene conferred risk of type 2 diabetes and insulin resistance in Chinese. The association was probably mediated through modulation of adipogenesis.

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Prostaglandin E synthase 2 (PTGES2) Arg298His polymorphism and parameters of the metabolic syndrome

Cited by 12 publications

References 21 publications

Evaluation of 41 Candidate Gene Variants for Obesity in the EPIC-Potsdam Cohort by Multi-Locus Stepwise Regression

Evaluation of 41 Candidate Gene Variants for Obesity in the EPIC-Potsdam Cohort by Multi-Locus Stepwise Regression

Aggravation by prostaglandin E2 of interleukin-6-dependent insulin resistance in hepatocytes

Genetic variation in the carbonyl reductase 3 gene confers risk of type 2 diabetes and insulin resistance: a potential regulator of adipogenesis

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