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An interaction between a FNDC5 variant and obesity modulates glucose metabolism in a Chinese Han population.

Tang S, Zhang R, Jiang F, Wang J, Chen M, Peng D, Yan J, Bao Y, Hu C, Jia W - PLoS ONE (2014)

Bottom Line: Three tagging single nucleotide polymorphisms within the region of the FNDC5 gene were selected and genotyped in 6822 participants.Detailed clinical investigations and biochemistry measurements were carried out in all of the participants.Moreover, rs16835198 was significantly associated with high-density lipoprotein cholesterol (HDL-C) levels (p = 0.013), and HOMA-β cell function (p = 0.028) in the overweight/obese subjects.

View Article: PubMed Central - PubMed

Affiliation: Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, PR China.

ABSTRACT

Background: To investigate the impact of common variants of FNDC5 on type 2 diabetes and clinical traits related to glucose metabolism in a large Chinese population sample.

Methods: Three tagging single nucleotide polymorphisms within the region of the FNDC5 gene were selected and genotyped in 6822 participants. Detailed clinical investigations and biochemistry measurements were carried out in all of the participants. Subjects without diabetes were classified into normal weight and overweight/obese subgroups according to body mass index (BMI).

Results: None of the SNPs were associated with either the risk of type 2 diabetes in all of the participants or with any of the clinical quantitative traits in the controls with normal glucose regulation. Subgroup analysis showed that in controls with normal weight (BMI <25 kg/m(2)), the rs16835198 major allele G was significantly associated with fasting insulin levels, and that each additional copy of the allele resulted in a 0.0178 mU/L increment of the values (p = 0.046). Moreover, after adjusting for confounding variables, there were trends towards correlation of rs16835198 with HOMA-insulin resistance (HOMA-IR) (p = 0.057) and low-density lipoprotein cholesterol (LDL-C) levels (p = 0.083). In overweight/obese subjects (BMI ≥ 25 Kg/m(2)), we noted rs16835198 showed trends towards association with fasting insulin (p = 0.057) and HOMA-IR levels (p = 0.091), both of which declined with additional copies of the major allele G. Moreover, rs16835198 was significantly associated with high-density lipoprotein cholesterol (HDL-C) levels (p = 0.013), and HOMA-β cell function (p = 0.028) in the overweight/obese subjects. Finally, we observed a significant interaction between BMI-rs16835198 and fasting insulin levels in the control group (p = 0.003).

Conclusions: Our data indicate that the effect of the common FNDC5 SNP rs16835198 on fasting insulin was significantly modified by BMI in the Chinese Han population.

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Related in: MedlinePlus

Linkage disequilibrium maps for SNPs genotyped in the region of the FNDC5 gene.A. Shades of red demonstrate the strength of the pairwise linkage disequilibrium based on D’ and numbers represent the value of D’ expressed as a percentage. B. Shades of grey show the strength of the pairwise linkage disequilibrium based on r2 and numbers indicate the value of r2 expressed as a percentage.
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pone-0109957-g001: Linkage disequilibrium maps for SNPs genotyped in the region of the FNDC5 gene.A. Shades of red demonstrate the strength of the pairwise linkage disequilibrium based on D’ and numbers represent the value of D’ expressed as a percentage. B. Shades of grey show the strength of the pairwise linkage disequilibrium based on r2 and numbers indicate the value of r2 expressed as a percentage.

Mentions: All the three SNPs were in Hardy-Weinberg equilibrium in the control population (p>0.05). Linkage disequilibrium analysis for these SNPs was shown in Figure 1. One haplotype block was constructed in this region. Single SNP association analysis failed to detect a significant association between any of the three SNP and type 2 diabetes, with a minimum p value of 0.265 for rs3480. Similarly, logistic regression analysis found no association between any SNP and type 2 diabetes (Table 2). To determine the effect of these SNPs on clinical characteristics in the control participants, we next performed genotype-phenotype analyses using an additive genetic model. As shown in the Supporting Information (Table S1 in File S1), none of the SNPs were significantly associated with quantitative traits related to glucose and lipid metabolism in the control population.


An interaction between a FNDC5 variant and obesity modulates glucose metabolism in a Chinese Han population.

Tang S, Zhang R, Jiang F, Wang J, Chen M, Peng D, Yan J, Bao Y, Hu C, Jia W - PLoS ONE (2014)

Linkage disequilibrium maps for SNPs genotyped in the region of the FNDC5 gene.A. Shades of red demonstrate the strength of the pairwise linkage disequilibrium based on D’ and numbers represent the value of D’ expressed as a percentage. B. Shades of grey show the strength of the pairwise linkage disequilibrium based on r2 and numbers indicate the value of r2 expressed as a percentage.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4219676&req=5

pone-0109957-g001: Linkage disequilibrium maps for SNPs genotyped in the region of the FNDC5 gene.A. Shades of red demonstrate the strength of the pairwise linkage disequilibrium based on D’ and numbers represent the value of D’ expressed as a percentage. B. Shades of grey show the strength of the pairwise linkage disequilibrium based on r2 and numbers indicate the value of r2 expressed as a percentage.
Mentions: All the three SNPs were in Hardy-Weinberg equilibrium in the control population (p>0.05). Linkage disequilibrium analysis for these SNPs was shown in Figure 1. One haplotype block was constructed in this region. Single SNP association analysis failed to detect a significant association between any of the three SNP and type 2 diabetes, with a minimum p value of 0.265 for rs3480. Similarly, logistic regression analysis found no association between any SNP and type 2 diabetes (Table 2). To determine the effect of these SNPs on clinical characteristics in the control participants, we next performed genotype-phenotype analyses using an additive genetic model. As shown in the Supporting Information (Table S1 in File S1), none of the SNPs were significantly associated with quantitative traits related to glucose and lipid metabolism in the control population.

Bottom Line: Three tagging single nucleotide polymorphisms within the region of the FNDC5 gene were selected and genotyped in 6822 participants.Detailed clinical investigations and biochemistry measurements were carried out in all of the participants.Moreover, rs16835198 was significantly associated with high-density lipoprotein cholesterol (HDL-C) levels (p = 0.013), and HOMA-β cell function (p = 0.028) in the overweight/obese subjects.

View Article: PubMed Central - PubMed

Affiliation: Shanghai Diabetes Institute, Department of Endocrinology and Metabolism, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, PR China.

ABSTRACT

Background: To investigate the impact of common variants of FNDC5 on type 2 diabetes and clinical traits related to glucose metabolism in a large Chinese population sample.

Methods: Three tagging single nucleotide polymorphisms within the region of the FNDC5 gene were selected and genotyped in 6822 participants. Detailed clinical investigations and biochemistry measurements were carried out in all of the participants. Subjects without diabetes were classified into normal weight and overweight/obese subgroups according to body mass index (BMI).

Results: None of the SNPs were associated with either the risk of type 2 diabetes in all of the participants or with any of the clinical quantitative traits in the controls with normal glucose regulation. Subgroup analysis showed that in controls with normal weight (BMI <25 kg/m(2)), the rs16835198 major allele G was significantly associated with fasting insulin levels, and that each additional copy of the allele resulted in a 0.0178 mU/L increment of the values (p = 0.046). Moreover, after adjusting for confounding variables, there were trends towards correlation of rs16835198 with HOMA-insulin resistance (HOMA-IR) (p = 0.057) and low-density lipoprotein cholesterol (LDL-C) levels (p = 0.083). In overweight/obese subjects (BMI ≥ 25 Kg/m(2)), we noted rs16835198 showed trends towards association with fasting insulin (p = 0.057) and HOMA-IR levels (p = 0.091), both of which declined with additional copies of the major allele G. Moreover, rs16835198 was significantly associated with high-density lipoprotein cholesterol (HDL-C) levels (p = 0.013), and HOMA-β cell function (p = 0.028) in the overweight/obese subjects. Finally, we observed a significant interaction between BMI-rs16835198 and fasting insulin levels in the control group (p = 0.003).

Conclusions: Our data indicate that the effect of the common FNDC5 SNP rs16835198 on fasting insulin was significantly modified by BMI in the Chinese Han population.

Show MeSH
Related in: MedlinePlus