Association of the carriage of <i>BRD2</i> rs206787 and rs516535 and <i>GJD2</i> rs3743123 polymorphisms with juvenile myoclonic epilepsy in Caucasian patients of Siberia
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In recent years, the genetics of juvenile myoclonic epilepsy (JME) has been actively studied; the association of JME with the carriage of polymorphic allelic variants of the BRD2 (EJM3 locus) and GJD2 (EJM2 locus) genes has been established. Objective: to establish risk factors for JME in terms of a genetic predisposition; specifically, polymorphic allelic variants rs206787 and rs516535 in the BRD2 gene and rs3743123 in the GJD2 gene. Patients and methods: Examinations were made in 79 patients with JME and in 150 healthy volunteers, who were Caucasian and resided in the Siberian Federal District (SFD) and underwent determination of the carriage of single nucleotide polymorphisms (SNPs) rs206787 and rs516535 in the BRD2 gene and rs3743123 in the GJD2 gene by real-time polymerase chain reaction. Results and discussion. In 2003, American scientists from New York showed that the alleles associated with the development of JME with an autosomal recessive inheritance pattern might be located in the BRD2 gene. Patients with JME are assumed to have an autosomal dominant inheritance pattern of mutations in the BRD2 gene. British scientists revealed that different populations were found to have an association of SNP rs3918149 and no relationship of BRD2 rs206787 to the development of JME in Caucasians, as well as ascertained local linkage disequilibrium in the BRD2 gene. Our investigation has established complete linkage disequilibrium between the loci in patients with JME and in healthy individuals and no association of the carriage of SNPs rs206787 and rs516535 in the BRD2 gene with the development of JME in the patients residing in the SFD (p >0.05). German scientists studied the impact of SNP in the BRD2 gene on a predisposition to a photoparoxysmal response in patients with JME/genetic generalized epilepsy. Our investigation has indicated the association of the carriage of TT/TT haplotype for SNP rs206787 and rs516535 in the BRD2 gene with a photoparoxysmal response in patients with JME (odds ratio (OR), 3.6; 95% confidence interval (CI), 1.37–9.48; p=0.02). We have confirmed that in the studied sample, the carriage of the T allele in the GJD2 gene (rs3743123) in the homozygous form is associated with the development of JME in Caucasian patients residing in the SFD and is a risk factor for JME (OR, 2.66; 95% CI, 1.24–5.74; p=0.04). The clinically significant association of this SNP in the GJD2 gene with the development of JME had been also previously demonstrated in two independent studies conducted in the European populations in the UK and Germany. There is a rise in the proportion of homozygotes in JME patients versus the control group, suggesting that the 588T allele under consideration increases the risk for JME in the homozygous state in the autosomal recessive inheritance pattern. Conclusion. The findings suggest that it is necessary to genotype Caucasian patients with JME, who reside in Siberia, for determination of the carriage of the TT/TT haplotype in terms of the investigated SNPs in the BRD2 gene (EJM 3 locus) and the carriage the T allele (rs3743123) in the GJD2 gene via a personalized approach to predicting the course of JME, as well as for identification of persons at risk for JME in the families having a history of this disease.Keywords:
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Linkage disequilibrium (LD) is a measure of the degree of association between alleles in a population. The detection of disease-causing variants by association with neighbouring single nucleotide polymorphisms (SNPs) depends on the existence of strong LD between them. Previous studies have indicated that the extent of LD is highly variable in different chromosome regions and different populations, demonstrating the importance of genome-wide accurate measurement of LD at high resolution throughout the human genome. A uniform feature of these studies has been the inability to detect LD in regions of low marker density. To investigate the dependence of LD patterns on marker selection we performed a high-resolution study in African-American, Asian and UK Caucasian populations. We selected over 5000 SNPs with an average spacing of ∼1 SNP per 2 kb after validating ca 12 000 SNPs derived from a dense SNP collection (1 SNP per 0.3 kb on average). Applications of different statistical methods of LD assessment highlight similar areas of high and low LD. However, at high resolution, features such as overall sequence coverage in LD blocks and block boundaries vary substantially with respect to marker density. Model-based linkage disequilibrium unit (LDU) maps appear robust to marker density and consistently influenced by marker allele frequency. The results suggest that very dense marker sets will be required to yield stable views of fine-scale LD in the human genome.
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Summary Genome wide association studies (GWAS) have largely succeeded family-based linkage studies in livestock and human populations as the preferred method to map loci for complex or quantitative traits. However, the type of results produced by the two analyses contrast sharply due to differences in linkage disequilibrium (LD) imposed by the design of studies. In this paper, we demonstrate that association and linkage studies are in agreement provided that (i) the effects from both studies are estimated appropriately as random effects, (ii) all markers are fitted simultaneously and (iii) appropriate adjustments are made for the differences in LD between the study designs. We demonstrate with real data that linkage results can be predicted by the sum of association effects. Our association study captured most of the linkage information because we could predict the linkage results with moderate accuracy. We suggest that the ability of common single nucleotide polymorphism (SNP) to capture the genetic variance in a population will depend on the effective population size of the study organism. The results provide further evidence for many loci of small effect underlying complex traits. The analysis suggests a more informed method for GWAS is to fit statistical models where all SNPs are analysed simultaneously and as random effects.
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Abstract One strategy for detection of disease genes is to exploit linkage disequilibrium in the hope that in candidate regions there will be detectable association between disease and marker alleles. Maps of single nucleotide polymorphisms (SNPs) will be used for this purpose but a recent simulation suggests that a useful level of linkage disequilibrium is unlikely to extend beyond an average distance of 3 Kb in the general population. This implies that very high marker densities will be required to detect disease: SNP associations. The evidence from published data comprising 877 SNP pairs is presented. For comparison, associations between other pairs of markers, principally microsatellites, are examined in a large sample of haplotypes from the fragile X (FRAX) region in Xq27–28. Association ρ is estimated from haplotype frequencies and the decline in linkage disequilibrium with distance is described using the model originally described by Malecot. The evidence from SNP pairs suggest that linkage disequilibrium extends to at least 263 Kb in random haplotypes, but with a considerable amount of variation particularly at small distances. For microsatellites in the FRAX region disequilibrium extends to at least 435 Kb. This suggests that a genome scan with markers spaced every 100 Kb would be powerful (30 000 markers per genome). Higher densities might be required in some genomic regions and presumably will be required to determine causal SNPs.
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This chapter contains sections titled: Introduction Linkage Disequilibrium Mapping Genes Using Linkage Disequilibrium Tests for Association Analysis of Haplotype Data Association Tests for Quantitative Traits Association and Genomic Screening Special Populations Summary References
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Abstract Complex diseases affect a substantial proportion of the human population and are caused by multiple genetic and environmental effects. The association study is a means of identifying genetic variation that may be involved in complex disease etiology. The existence of linkage disequilibrium (nonrandom association of alleles) across the human genome can be used to reduce the number of variants needed to successfully correlate with phenotypic traits. We discuss the current status and problems inherent in performing whole genome association studies to analyze complex diseases.
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Single nucleotide polymorphism (SNP) is the mostly popular polymorphism in human genome and mainly component of genetic difference among individuals. SNP, as perfectly genetic marker, was widely used for population parameters estimation, fine mapping of gene and association analysis. SNP discovery, application and related function research are important topics in genome and genetic research. Linkage disequilibrium(LD) is associated with alleles of closely linked genetic markers. Recently, developments in LD and SNP research will greatly facilitate to genetics research in nearly future.
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