Association between variations in the TLR4 gene and incident type 2 diabetes is modified by the ratio of total cholesterol to HDL-cholesterol

<p>Abstract</p> <p>Background</p> <p>Toll-like receptor 4 (TLR4), the signaling receptor for lipopolysaccharides, is an important member of the innate immunity system. Since several studies have suggested that type 2 diabetes might be associated with changes in the innate immune response, we sought to investigate the association between genetic variants in the <it>TLR4 </it>gene and incident type 2 diabetes.</p> <p>Methods</p> <p>A case-cohort study was conducted in initially healthy, middle-aged subjects from the MONICA/KORA Augsburg studies including 498 individuals with incident type 2 diabetes and 1,569 non-cases. Seven SNPs were systematically selected in the <it>TLR4 </it>gene and haplotypes were reconstructed.</p> <p>Results</p> <p>The effect of <it>TLR4 </it>SNPs on incident type 2 diabetes was modified by the ratio of total cholesterol to high-density lipoprotein cholesterol (TC/HDL-C). In men, four out of seven <it>TLR4 </it>variants showed significant interaction with TC/HDL-C after correction for multiple testing (p < 0.01). The influence of the minor alleles of those variants on the incidence of type 2 diabetes was observed particularly for male patients with high values of TC/HDL-C. Consistent with these findings, haplotype-based analyses also revealed that the effect of two haplotypes on incident type 2 diabetes was modified by TC/HDL-C in men (p < 10^-3). However, none of the investigated variants or haplotypes was associated with type 2 diabetes in main effect models without assessment of effect modifications.</p> <p>Conclusion</p> <p>We conclude that minor alleles of several <it>TLR4 </it>variants, although not directly associated with type 2 diabetes might increase the risk for type 2 diabetes in subjects with high TC/HDL-C. Additionally, our results confirm previous studies reporting sex-related dissimilarities in the development of type 2 diabetes.</p

Metabolite profiling reveals new insights into the regulation of serum urate in humans

Albrecht E, Waldenberger M, Krumsiek J, et al. Metabolite profiling reveals new insights into the regulation of serum urate in humans. Metabolomics. 2013;10(1):141-151.Serum urate, the final breakdown product of purine metabolism, is causally involved in the pathogenesis of gout, and implicated in cardiovascular disease and type 2 diabetes. Serum urate levels highly differ between men and women; however the underlying biological processes in its regulation are still not completely understood and are assumed to result from a complex interplay between genetic, environmental and lifestyle factors. In order to describe the metabolic vicinity of serum urate, we analyzed 355 metabolites in 1,764 individuals of the population-based KORA F4 study and constructed a metabolite network around serum urate using Gaussian Graphical Modeling in a hypothesis-free approach. We subsequently investigated the effect of sex and urate lowering medication on all 38 metabolites assigned to the network. Within the resulting network three main clusters could be detected around urate, including the well-known pathway of purine metabolism, as well as several dipeptides, a group of essential amino acids, and a group of steroids. Of the 38 assigned metabolites, 25 showed strong differences between sexes. Association with uricostatic medication intake was not only confined to purine metabolism but seen for seven metabolites within the network. Our findings highlight pathways that are important in the regulation of serum urate and suggest that dipeptides, amino acids, and steroid hormones are playing a role in its regulation. The findings might have an impact on the development of specific targets in the treatment and prevention of hyperuricemia

Meta-Analysis of 28,141 Individuals Identifies Common Variants within Five New Loci That Influence Uric Acid Concentrations

Elevated serum uric acid levels cause gout and are a risk factor for cardiovascular disease and diabetes. To investigate the polygenetic basis of serum uric acid levels, we conducted a meta-analysis of genome-wide association scans from 14 studies totalling 28,141 participants of European descent, resulting in identification of 954 SNPs distributed across nine loci that exceeded the threshold of genome-wide significance, five of which are novel. Overall, the common variants associated with serum uric acid levels fall in the following nine regions: SLC2A9 (p = 5.2×10−201), ABCG2 (p = 3.1×10−26), SLC17A1 (p = 3.0×10−14), SLC22A11 (p = 6.7×10−14), SLC22A12 (p = 2.0×10−9), SLC16A9 (p = 1.1×10−8), GCKR (p = 1.4×10−9), LRRC16A (p = 8.5×10−9), and near PDZK1 (p = 2.7×10−9). Identified variants were analyzed for gender differences. We found that the minor allele for rs734553 in SLC2A9 has greater influence in lowering uric acid levels in women and the minor allele of rs2231142 in ABCG2 elevates uric acid levels more strongly in men compared to women. To further characterize the identified variants, we analyzed their association with a panel of metabolites. rs12356193 within SLC16A9 was associated with DL-carnitine (p = 4.0×10−26) and propionyl-L-carnitine (p = 5.0×10−8) concentrations, which in turn were associated with serum UA levels (p = 1.4×10−57 and p = 8.1×10−54, respectively), forming a triangle between SNP, metabolites, and UA levels. Taken together, these associations highlight additional pathways that are important in the regulation of serum uric acid levels and point toward novel potential targets for pharmacological intervention to prevent or treat hyperuricemia. In addition, these findings strongly support the hypothesis that transport proteins are key in regulating serum uric acid levels

APOA5 variants and metabolic syndrome in caucasians

Apolipoprotein A5 (APOA5) gene variants were reported to be associated with two components of metabolic syndrome (MetS): higher TG levels and lower HDL levels. Moreover, a recent Japanese case-control study found variant -1131T&gt;C associated with MetS itself. Thus, our study systematically analyzed the APOA5 gene for association with lipid parameters, any other features of MetS, including waist circumference, glucose-related parameters, blood pressure, uric acid, and MetS itself in Caucasians. Ten polymorphisms were analyzed in a large fasting sample of the population-based Cooperative Health Research in the Region of Augsburg (KORA) survey S4 (n = 1,354; southern Germany) and in a second fasting sample, the Salzburg Atherosclerosis Prevention Program in Subjects at High Individual Risk (SAPHIR) study (n = 1,770; Austria). Minor alleles of variants -1131T&gt;C, -3A&gt;G, c.56C&gt;G, 476G&gt;A, and 1259T&gt;C were significantly associated with higher TG levels in single polymorphism (P &lt; 0.001) and haplotype (P G was associated with higher risk for MetS [odds ratio (95% confidence interval) = 1.43 (1.04, 1.99), P = 0.03 for KORA and 1.48 (1.10, 1.99), P = 0.009 for SAPHIR). Our study confirms the association of the APOA5 locus with TG and HDL levels in humans. Furthermore, the data suggest a different mechanism of APOA5 impact on MetS in Caucasians, as variant c.56C&gt;G (not analyzed in the Japanese study) and not -1131T&gt;C, as in the Japanese subjects, was associated with MetS

Meta-analysis of 28,141 individuals identifies common variants within five new loci that influence uric acid concentrations

Elevated serum uric acid levels cause gout and are a risk factor for cardiovascular disease and diabetes. To investigate the polygenetic basis of serum uric acid levels, we conducted a meta-analysis of genome-wide association scans from 14 studies totalling 28,141 participants of European descent, resulting in identification of 954 SNPs distributed across nine loci that exceeded the threshold of genome-wide significance, five of which are novel. Overall, the common variants associated with serum uric acid levels fall in the following nine regions: SLC2A9 (p = 5.2x10(-201)), ABCG2 (p = 3.1x10(-26)), SLC17A1 (p = 3.0x10(-14)), SLC22A11 (p = 6.7x10(-14)), SLC22A12 (p = 2.0x10(-9)), SLC16A9 (p = 1.1x10(-8)), GCKR (p = 1.4x10(-9)), LRRC16A (p = 8.5x10(-9)), and near PDZK1 (p = 2.7x10(-9)). Identified variants were analyzed for gender differences. We found that the minor allele for rs734553 in SLC2A9 has greater influence in lowering uric acid levels in women and the minor allele of rs2231142 in ABCG2 elevates uric acid levels more strongly in men compared to women. To further characterize the identified variants, we analyzed their association with a panel of metabolites. rs12356193 within SLC16A9 was associated with DL-carnitine (p = 4.0x10(-26)) and propionyl-L-carnitine (p = 5.0x10(-8)) concentrations, which in turn were associated with serum UA levels (p = 1.4x10(-57) and p = 8.1x10(-54), respectively), forming a triangle between SNP, metabolites, and UA levels. Taken together, these associations highlight additional pathways that are important in the regulation of serum uric acid levels and point toward novel potential targets for pharmacological intervention to prevent or treat hyperuricemia. In addition, these findings strongly support the hypothesis that transport proteins are key in regulating serum uric acid levels