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RAPID COMMUNICATION |
1 GSF National Research Center for Environment and Health, Institute of Epidemiology, Ingolstädter Landstraße 1, D–85764 Neuherberg, Germany, 2 Else Kröner-Fresenius-Center for Nutritional Medicine, Technical University of Munich, Munich, Germany, 3 IBE, Chair of Epidemiology, Ludwig-Maximilians University of Munich, Munich, Germany, 4 Institute of Biometrics and Epidemiology, German Diabetes Center, Leibniz Institute at Heinrich-Heine-University, Düsseldorf, Germany and 5 Institute for Clinical Diabetes Research, German Diabetes Center, Leibniz Institute at Heinrich-Heine-University, Düsseldorf, Germany
(Correspondence should be addressed to T Illig; Email: illig{at}gsf.de)
Abstract
Objective: The aim of our study was to determine the variant pattern of the leukemia-associated Rho guanine nucleotide exchange factor (LARG, or ARHGEF12) gene and investigate whether LARG variants are associated with diabetes mellitus type 2 (T2DM), the metabolic syndrome (MetS), or related parameters such as insulin sensitivity in German Caucasians.
Design: We analyzed single nucleotide polymorphisms (SNPs) in the LARG gene in the 55–74-year-old individuals of the population-based German Caucasian Cooperative Health Research in the region of Augsberg (KORA) survey 4 (S4).
Methods: Sequencing of Tyr1306Cys, which was of functional relevance in Pima Indians, in 48 randomly selected individuals and genotyping of 11 additional LARG SNPs in 1653 subjects were performed. Four linkage disequilibrium (LD) blocks (r2
0.8) were established and each block was statistically analyzed for association with metabolic traits. The association with T2DM and the MetS was analyzed by logistic regression in 1462 subjects, and HOMA-IR (homeostasis model assessment of insulin resistance) as a measure of insulin sensitivity was analyzed by the Kruskal–Wallis test in 1346 fasting subjects.
Results: The polymorphism Tyr1306Cys, which was significantly associated with insulin sensitivity in Pima Indians, was not found in the KORA S4 population. Statistical analysis yielded no significant associations (P>0.05) between the analyzed LARG variants and T2DM, the MetS, or related parameters such as insulin sensitivity.
Conclusions: Caucasian individuals and Pima Indians differ in their genetic variance pattern in the LARG gene region. There is no evidence in the Caucasian KORA study that variants of the LARG gene confer susceptibility for T2DM, insulin sensitivity, or the MetS.
Introduction
Lifestyle factors and genetic background play causal roles for the development of type 2 diabetes mellitus (T2DM) (1). Obesity, hypertension, dyslipidemia, and T2DM as a result of insulin resistance and impaired insulin secretion are characteristic parameters of the metabolic syndrome (MetS) (2). Insulin action is partly regulated by RhoA, a member of the Rho family of GTPases. RhoA activation reduces skeletal muscle glucose transport by the repression of signals of insulin receptor substrate and phosphatidylinositol 3-kinase/ serine–threonine kinase (3). LARG (leukemia-associated Rho guanine nucleotide exchange factor) is a member of the Rho family of guanine nucleotide exchange factors (GEFs) (4), which are involved in the regulation of the GTP-dependent Rho protein cycle. Decreased LARG activity leads to decreased RhoA activity and thus to increased insulin sensitivity (5).
A genome screen in more than 1200 Pima Indians detected a linkage between the microsatellite marker D11S4464 on chromosome 11q23–24 and body mass index (BMI) (logarithm of odds (LOD)=3.6) as well as T2DM (LOD=1.7) (6). The LARG gene, spanning 152 kb and consisting of 40 exons, is located 3.5 mega bases away from this marker. Its synonymous name (HUGO Gene Nomenclature Committee) is ARHGEF12 (Rho guanine nucleotide exchange factor 12). Kovacs et al. identified variants in the LARG gene and detected that an A/G substitution in exon 38 (Tyr1306Cys) coding for an amino acid exchange was significantly associated with insulin-mediated glucose uptake in 322 nondia-betic Pima Indians (7). Moreover, the genetic variant caused altered protein expression in NIH3T3 mouse fibroblasts. The LARG (Cys1306) protein had a significantly reduced (P=0.03) activity when compared with LARG (Tyr1306) protein (7). The aim of our study was to determine the variant pattern of the LARG gene in the population-based KORA (Cooperative Health Research in the Region of Augsburg) survey 4 (S4) and to investigate whether LARG variants are associated with T2DM, the MetS, or related parameters such as insulin sensitivity in German Caucasians.
Subjects and methods
Subjects
KORA S4 is a population-based study of adults with German nationality and main address in the study region of Augsburg (8). This survey included a standardized interview and clinical investigation and was conducted under the same conditions as the previous three surveys within the World Health Organization (WHO) MONICA Augsburg project (9). An oral glucose tolerance test (OGTT) was performed in 1354 participants aged 55–74 years (10). Measurement of quantitative parameters important for T2DM and the MetS was performed according to standardized protocols (10). The WHO criteria (11) were used for the definition of diabetes, and the MetS was defined according to the International Diabetes Federation definition for Europid persons (12). Finally, 1462 subjects, consisting of 1226 nondiabetic individuals who had undergone an OGTT, and 236 subjects with T2DM, were included in statistical analysis for T2DM and the MetS. For the quantitative parameters, 1346 fasting subjects were analyzed. Subjects with diabetes mellitus type 1 (n=18 for the analysis of T2DM and the MetS or n=8 for the analysis of quantitative parameters respectively) were excluded. Of the individuals in the analyzed sample 51.5% were men, the average age was 64 years and the mean BMI was 28 kg/ m2. Men (n=137) and women (n=99) with T2DM had a higher mean age (65.07/65.09 years) and a higher mean BMI (29.88/32.27 kg/m2) compared with participants without T2DM (mean age, 63.98/63.81 years; mean BMI, 27.99/28.43 kg/m2). All participants gave written informed consent for genetic studies.
Sequencing
For sequencing, 10–50 ng genomic DNA sample of 48 randomly selected subjects from KORA S4 were amplified by PCR using HotStarTaq DNA polymerase (Qiagen) and a DNA Engine Tetrad thermal cycler (BioRad). Sequencing was done with the Big Dye Terminators version 3.7 (Applied Biosystems, Foster City, CA, USA) on an ABI 3730 sequencer (ABI) according to manufacturer’s protocol. Sequence analysis was performed using Informax Vector NTI Suite 9.0.0 (Invitrogen).
Genotyping
Eleven polymorphisms were selected by literature and according to linkage disequilibrium (LD) blocks (r20.8) by the HapMap project (www.hapmap.org) (public release no. 21a). Polymorphisms with a minor allele frequency below 10% were not included in the genotyping process due to the low power to detect an association. The selected single nucleotide polymorphisms (SNPs) completely cover the common genetic variation in the LARG gene and flanking regions.
DNA samples were genotyped with the MassARRAY system using the iPLEX chemistry (Sequenom, San Diego, CA, USA). Primer extension products were loaded onto a 384 element chip using a nanoliter pipetting system (SpectroCHIP, SpectroPOINT Spotter, Sequenom). The samples were analyzed in a MALDI TOF MS (matrix-assisted laser desorption ionization time of flight mass spectrometer: Bruker Daltonik, Leipzig, Germany). The resulting mass spectra were analyzed automatically for peak identification via the SpectroTYPER RT 3.4 software (Sequenom). For quality reasons, 10% of the spectra were checked independently by two investigators.
Statistical analysis
The Hardy–Weinberg equilibrium (HWE) was checked by Fisher’s exact test, and the LD structure was calculated with the java linkage disequilibrium plotter (JLIN) program (http://www.genepi.com.au/projects/jlin). All further analyses were performed with SAS (Statistical Analysis System version 9.1, Cary, NC, USA) and parametric analyses were adjusted for age and sex and additional for BMI when quantitative parameters were analyzed. T2DM and the MetS were analyzed by logistic regression. Quantitative parameters with approximate normal distribution were analyzed by linear regression, and homeostasis model assessment of insulin resistance (HOMA-IR) as a measure of insulin sensitivity was calculated by the product of fasting glucose (mU/l) and fasting insulin (mmol/l) divided by 22.5 (13) and analyzed by nonparametric Kruskal–Wallis test. All regression analyses were performed comparing the homozygous or heterozygous minor allele carriers separately, with the homozygous major allele carriers as reference group. P<0.05 was regarded as statistically significant. The power calculation was done with genetic power calculator software (14).
Results
First, 48 subjects (96 chromosomes) of KORA S4 were sequenced for the polymorphism Tyr1306Cys and only the A allele, which codes for Tyr1306, was detected. For all 11 genetic variants, genotyping was successful with an average success rate of 98.8% and every polymorphism fulfilled the criteria of HWE (P0.05). Four LD blocks (r20.8) were established and for statistical analysis one representative SNP tagging all other polymorphisms of this block was analyzed. Three of these polymorphisms (rs538661, rs476636, and rs2276035) are located in introns, whereas one SNP (rs12806740) is localized in the 5' flanking region (Table 1
).
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). Moreover, in our study, none of the tested quantitative parameters (fasting triglycerides, high- or low-density lipoprotein cholesterol, total cholesterol, percent body fat, waist to hip ratio, uric acid, fasting glucose, 2-h plasma glucose, fasting insulin, blood pressure) were significantly associated with the investigated polymorphisms (data not shown). There was also no significant association between HOMA-IR (lowest P= 0.49) and the analyzed SNPs in 1346 fasting KORA S4 subjects. The median for HOMA-IR was 2.42 (Table 2).
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= 0.05) to detect a minimum OR (odds ratio) for T2DM of 1.3 in a global test was 88% for the polymorphisms rs12806740 or rs538661, and 65% for the polymorphisms rs476636 or rs2276035. The power to detect a minimum OR for the MetS of 1.3 was 100% for all four polymorphisms. Discussion
Sequencing of the polymorphism Tyr1306Cys was performed and four representative polymorphisms in the LARG gene were analyzed for association with T2DM, the MetS, and related parameters. The results of our study give no evidence for any association between polymorphisms in the LARG gene and the analyzed parameters. In contrast to the findings of Kovacs et al., who reported a strong association between the polymorphism Tyr1306Cys and insulin sensitivity during a hyperinsulinemic–euglycemic clamp in Pima Indians (7), this polymorphism is surprisingly monomorph (only the AA genotype was detected) or has at least a very low minor allele frequency in German Caucasians. In the Pima study, the A allele was associated with lower insulin sensitivity (7). Regarding the results for T2DM, the negative association results of Kovacs et al. (7) could be replicated in this study. In both German Caucasians and Pima Indians, none of the genetic variants in the LARG gene were associated with T2DM.
Different from the Pima study (7), the LARG gene is not associated with insulin sensitivity in the German population, but the comparison is not completely adequate, because in the Pima study the gold standard (clamp) for insulin sensitivity was measured whereas in our study HOMA-IR was used.
The strengths of KORA S4 are its large size, intensive phenotyping, and population-based design. In particular, OGTT status is available from almost all subjects. The systematic genetic dissection of the LARG gene and complete coverage of the whole gene locus strengthen our conclusions concerning the association between the gene and the various outcomes. Furthermore, the relative high power of the study fortifies our results for T2DM and the MetS.
Recently, genetic variants of another Rho guanine nucleotide exchange factor gene, ARHGEF11, located on chromosome 1, was found to be associated with insulin resistance or T2DM in Pima Indians or Amish populations respectively (15, 16). It will be interesting in this context to clarify in future studies whether this nucleotide exchange factor plays a role in Caucasian populations.
In conclusion, there is neither evidence that the strongly associated polymorphism Tyr1306Cys in Pima Indians (7) existed in our study population nor was one of the analyzed parameters (T2DM, the MetS, HOMA-IR, and other quantitative traits) significantly associated with genetic variants in the LARG gene. Presumably, polymorphisms in the LARG gene do not play the same role in the different populations mainly because of the missing functional variant Tyr1306Cys in German Caucasians. This study strongly suggests that variants of the LARG gene do not confer susceptibility for T2DM, insulin sensitivity, or the MetS in German Caucasians.
In order to understand the interactions of genes, differences between populations, and the complexity of T2DM, future studies are necessary.
Acknowledgements
The OGTT study was partly funded by the German Federal Ministry of Health, the Ministry of School, Science and Research of the State of North Rhine-Westphalia, and the Anna Wunderlich-Ernst Jühling Foundation (WR, GG). Parts of this work were supported by the German Ministry of Education and Research (BMBF)/National Genome Research Network (NGFN) and the Deutsche Forschungsgemeinschaft (Wi621/12–1). KORA S4 was financed by the GSF, which is funded by the German Federal Ministry of Education, Science, Research and Technology and the State of Bavaria. We are grateful to the KORA study group (Head: Prof. H-E Wichmann) for initiating KORA S4. We also thank all participants of the OGTT study. We further thank Anke Rosin for expert technical help and Guido Fischer for perfect data management.
References
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