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  • DKFZ Publication Database  (3)
  • GENE  (3)
  • single nucleotide polymorphism  (2)
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  • DKFZ Publication Database  (3)
Keywords
  • 1
    Keywords: CELLS ; EXPRESSION ; CELL ; COMBINATION ; Germany ; human ; COHORT ; POPULATION ; RISK ; GENE ; PROTEIN ; SAMPLE ; SAMPLES ; DNA ; BINDING ; ASSOCIATION ; polymorphism ; POLYMORPHISMS ; single nucleotide polymorphism ; VARIANTS ; HUMANS ; ASSAY ; PROMOTER ; SNP ; OBESITY ; SINGLE ; VARIANT ; SINGLE NUCLEOTIDE POLYMORPHISMS ; FUNCTIONAL-CHARACTERIZATION ; HAPLOTYPES ; INSULIN-RESISTANCE ; metabolic syndrome ; USA ; REPLACEMENT ; Adiponectin ; STATE ; Luciferase reporter ; PLASMA ADIPONECTIN ; TYPE-2 DIABETIC-PATIENTS ; APM1 GENE ; HYPOADIPONECTINEMIA
    Abstract: OBJECTIVE-Adiponectin (APM1, ACDC) is an adipocyte-derived protein with downregulated expression in obesity and insulin-resistant states. Several potentially regulatory single nucleotide polymorphisms (SNPs) within the APM1 gene promoter region have been associated with circulating adiponectin levels. None of them have been functionally characterized in adiponectin-expressing cells. Hence, we investigated three SNPs (rs16861194, rs17300539, and rs266729) for their influence on adiponectin promoter activity and their association with circulating adiponectin levels. RESEARCH DESIGN AND METHODS-Basal and rosiglitazone-induced promoter activity of different SNP combinations (haplotypes) was analyzed in 3T3-L1 adipocytes using luciferase reporter gene assays and DNA binding studies comparing all possible APM1 haplotypes. This functional approach was complemented with analysis of epidemiological population-based data of 1,692 participants of the MONICA/KORA S123 cohort and 696 participants from the KORA S4 cohort for SNP and haplotype association with circulating adiponectin levels. RESULTS-Major to minor allele replacements of the three SNPs revealed significant effects on promoter activity in luciferase assays. Particularly, a minor variant in rs16861194 resulted in reduced basal and rosiglitazone-induced promoter activity and hypoadiponectinemia in the epidemiological datasets. The haplotype with the minor allele in all three SNPs showed a complete loss of promoter activity, and no subject carried this haplotype in either of the epidemiological samples (combined P value for statistically significant difference from a random sample was 0.006). CONCLUSIONS-Our results clearly demonstrate that promoter variants associated with hypoadiponectinemia in humans substantially affect adiponectin promoter activity in adipocytes. Our combination of functional experiments with epidemiological data overcomes the drawback of each approach alone. Diabetes 58-984-991, 2009
    Type of Publication: Journal article published
    PubMed ID: 19074982
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  • 2
    Keywords: SIMULATIONS ; Germany ; POPULATION ; GENE ; SAMPLE ; IMPACT ; SIMULATION ; ASSOCIATION ; polymorphism ; single nucleotide polymorphism ; SUSCEPTIBILITY ; FREQUENCIES ; PERFORMANCE ; NUMBER ; genetics ; SNP ; GENOTYPES ; MEASUREMENT ERROR ; genotyping ; UNCERTAINTY ; sensitivity ; SNPs ; methods ; GENOTYPE ; HAPLOTYPE ; HAPLOTYPES ; TESTS ; TRAITS ; LINKAGE PHASE ; genetic association ; Genetic ; MISCLASSIFICATION ; PROBABILITIES ; single nucleotide ; association studies ; genotyping error
    Abstract: P〉Haplotypes are an important concept for genetic association studies, but involve uncertainty due to statistical reconstruction from single nucleotide polymorphism (SNP) genotypes and genotype error. We developed a re-sampling approach to quantify haplotype misclassification probabilities and implemented the MC-SIMEX approach to tackle this as a 3 x 3 misclassification problem. Using a previously published approach as a benchmark for comparison, we evaluated the performance of our approach by simulations and exemplified it on real data from 15 SNPs of the APM1 gene. Misclassification due to reconstruction error was small for most, but notable for some, especially rarer haplotypes. Genotype error added misclassification to all haplotypes resulting in a non-negligible drop in sensitivity. In our real data example, the bias of association estimates due to reconstruction error alone reached -48.2% for a 1% genotype error, indicating that haplotype misclassification should not be ignored if high genotype error can be expected. Our 3 x 3 misclassification view of haplotype error adds a novel perspective to currently used methods based on genotype intensities and expected number of haplotype copies. Our findings give a sense of the impact of haplotype error under realistic scenarios and underscore the importance of high-quality genotyping, in which case the bias in haplotype association estimates is negligible
    Type of Publication: Journal article published
    PubMed ID: 20649529
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  • 3
    Keywords: Germany ; MODEL ; DISEASE ; GENE ; SAMPLE ; IMPACT ; ASSOCIATION ; FREQUENCIES ; PERFORMANCE ; genetics ; RATES ; REPLICATION ; UNCERTAINTY ; transmission/disequilibrium test ; TESTS ; ERROR ; HARDY-WEINBERG EQUILIBRIUM ; ROBUST ; CONTROL GENETIC ASSOCIATION ; MISCLASSIFICATION ; TAGGING SNP SELECTION
    Abstract: Background: We investigated the influence of genotyping errors on the type I error rate and empirical power of two haplotype based association methods applied to candidate regions. We compared the performance of the Mantel Statistic Using Haplotype Sharing and the haplotype frequency based score test with that of the Armitage trend test. Our study is based on 1000 replication of simulated case-control data settings with 500 cases and 500 controls, respectively. One of the examined markers was set to be the disease locus with a simulated odds ratio of 3. Differential and non-differential genotyping errors were introduced following a misclassification model with varying mean error rates per locus in the range of 0.2% to 15.6%. Results: We found that the type I error rate of all three test statistics hold the nominal significance level in the presence of nondifferential genotyping errors and low error rates. For high and differential error rates, the type I error rate of all three test statistics was inflated, even when genetic markers not in Hardy-Weinberg Equilibrium were removed. The empirical power of all three association test statistics remained high at around 89% to 94% when genotyping error rates were low, but decreased to 48% to 80% for high and nondifferential genotyping error rates. Conclusion: Currently realistic genotyping error rates for candidate gene analysis (mean error rate per locus of 0.2%) pose no significant problem for the type I error rate as well as the power of all three investigated test statistics
    Type of Publication: Journal article published
    PubMed ID: 19178712
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