982 resultados para Allele frequency


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PURPOSE:
To investigate whether variation in the distribution of the risk allele frequency of the Y402H single-nucleotide polymorphism (SNP) across various ethnicities and geographic regions reflects differences in the prevalence of late age-related macular degeneration (AMD) in those ethnicities.

METHODS:
Published data were obtained via a systematic search. Study samples were grouped into clusters by ethnicity and geographic location and the Spearman correlation coefficient of the prevalence of late AMD and risk allele frequencies was calculated across clusters.

RESULTS:
Across all ethnicities, AMD prevalence was seen to increase with age. Populations of European descent had both higher risk allele frequencies and prevalence of late AMD than did Japanese, Chinese, and Hispanic descendants. Results for African descendants were anomalous: although allele frequency was similar to that in European populations, the age-specific prevalence of late AMD was considerably lower. The correlation coefficient for the association between allele frequency and AMD prevalence was 0.40 (95% confidence interval [CI] = -0.36 to 0.84, P = 0.28) in all populations combined and 0.71 (95% CI = 0.02-0.94, P = 0.04) when people of African descent were excluded.

CONCLUSIONS:
Evidence was found at the population level to support a positive association between the Y204H risk allele and the prevalence of AMD after exclusion of studies undertaken on persons of African ancestry. Data in African, Middle Eastern, and South American populations are needed to provide a better understanding of the association of late AMD genetic risk across ethnicities.

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Gremlin, a cell growth and differentiation factor, promotes the development of diabetic nephropathy in animal models, but whether GREM1 gene variants associate with diabetic nephropathy is unknown. We comprehensively screened the 5' upstream region (including the predicted promoter), all exons, intron-exon boundaries, complete untranslated regions, and the 3' region downstream of the GREM1 gene. We identified 31 unique variants, including 24 with a minor allele frequency exceeding 5%, and 9 haplotype-tagging single nucleotide polymorphisms (htSNPs). We selected one additional variant that we predicted to alter transcription factor binding. We genotyped 709 individuals with type 1 diabetes of whom 267 had nephropathy (cases) and 442 had no evidence of kidney disease (controls). Three individual SNPs significantly associated with nephropathy at the 5% level, and two remained significant after adjustment for multiple testing. Subsequently, we genotyped a replicate population comprising 597 cases and 502 controls: this population supported an association with one of the SNPs (rs1129456; P = 0.0003). Combined analysis, adjusted for recruitment center (n = 8), suggested that the T allele conferred greater odds of nephropathy (OR 1.69; 95% CI 1.36 to 2.11). In summary, the GREM1 variant rs1129456 associates with diabetic nephropathy, perhaps explaining some of the genetic susceptibility to this condition.

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We conducted a genome-wide association study testing single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) for association with early-onset myocardial infarction in 2,967 cases and 3,075 controls. We carried out replication in an independent sample with an effective sample size of up to 19,492. SNPs at nine loci reached genome-wide significance: three are newly identified (21q22 near MRPS6-SLC5A3-KCNE2, 6p24 in PHACTR1 and 2q33 in WDR12) and six replicated prior observations1-4 (9p21, 1p13 near CELSR2-PSRC1-SORT1, 10q11 near CXCL12, 1q41 in MIA3, 19p13 near LDLR and 1p32 near PCSK9). We tested 554 common copy number polymorphisms (>1% allele frequency) and none met the pre-specified threshold for replication (P < 10-3). We identified 8,065 rare CNVs but did not detect a greater CNV burden in cases compared to controls, in genes compared to the genome as a whole, or at any individual locus. SNPs at nine loci were reproducibly associated with myocardial infarction, but tests of common and rare CNVs failed to identify additional associations with myocardial infarction risk.

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Aim

To assess the association of POMC haplotype-tagged single nucleotide polymorphisms (htSNPs) with the development of type 1 diabetes (T1D) in a Caucasian population.

Methods

All exons, intron 1, and approximately 6-kb upstream and 3-kb downstream of the POMC gene were bidirectionally resequenced to identify DNA polymorphisms in 30 individuals. Allele frequencies were determined (60 chromosomes) and efficient htSNPs were selected using the htSNP2 programme. Genotyping was performed in 390 cases, 339 controls and 245 T1D parent-offspring trios, using Taqman, Sequenom and direct-sequencing technologies.

Results

Thirteen polymorphisms (two novel) with a minor allele frequency greater than 1% were identified. Six POMC htSNPs (rs3754863 G>A, ss161151662 A>G, rs3754860 C>T, rs1009388 G>C, rs3769671 A>C, rs1042571 G>A) were identified. Allele and haplotype frequencies were similar between case and control groups (P>0.60 by permutation test), and assessment of allele transmission distortion from informative parents to affected offspring also failed to find any association. Stratification of these analyses for age-at-onset and HLA-DR risk group (DR3/DR4) revealed no significant associations. A haplotype block of 9.86-kb from rs3754863 to rs1042571 was identified, encompassing the POMC gene. Comparison of haplotype frequencies identified the GGCGAG haplotype as protective against T1D in 12.9% of cases vs. 18.3% of controls: ?2=8.18, Pc=0.03 by permutation test.

Conclusion

The POMC SNP haplotype GGCGAG may have a protective effect against T1D in the UK population. However, this finding needs to be replicated, and the cellular and molecular processes influenced by this POMC haplotype determined to fully appreciate its impact.

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We read with interest the comments offered by Drs. Hughes and Bradley (1) on our systematic review (2). Four single nucleotide polymorphisms (SNPs), rs9332739 and rs547154 in the complement component 2 gene (C2) and rs4151667 and rs641153 in the complement factor B gene (CFB), were pooled. Hughes and Bradley point out that we omitted the most common variant, rs12614. In fact, rs12614 is in high linkage disequilibrium (LD) with rs641153, which was included, and the major allele of both of these SNPs is in the range of 90% (population code, CEU, in the International HapMap Project (http://hapmap.ncbi.nlm.nih.gov/)). Moreover, our review was initiated in September 2010, at which point only 4 studies had published associations with rs12614, whereas 14 studies (n = 11,378) were available for rs641153. While it is true that both SNPs are better analyzed as a haplotype, these data were simply not available for pooling.
Hughes and Bradley also point out that we obtained and pooled new data that were not previously published. While it is recommended that contact with authors be completed as part of a comprehensive meta-analysis, we acknowledge that these additional data were not previously published and peer reviewed and, hence, do not have the same level of transparency. However, given that sample collections often increase over time and that the instrumentation for genotyping is continually improving, we thought that it would be advantageous to use the most recent information; this is a subjective decision.
We also agree that the allele frequencies given by Kaur et al. (3) were exactly opposite to those expected and were suggestive of strand flipping. However, we specifically queried this with the lead author on 2 separate occasions and were assured it was not.
Hughes and Bradley do make an interesting suggestion that SNPs in high LD should be used as a gauge of genotyping quality in HuGE reviews. This is an interesting idea but difficult to put into practice as the r2 parameter they propose as a measure of LD has some unusual properties. Although r2 is a measure of LD, it is also linked to the allele frequency; even small differences in allele frequencies between 2 linked SNPs can reduce the r2 dramatically. Wray (4) explored these effects and found that, at a baseline allele frequency of 10%, even a difference in allele frequency between 2 SNPs as small as 2% can drop the r2 value below 0.8. This degree of allele frequency difference is consistent with what could be expected for sampling error. Furthermore, when we look at 2 linked dialleleic SNPs, giving 4 possible haplotypes, the absence of 1 haplotype dramatically reduces r2, despite the 2 loci being in high LD as measured by D'. In fact, this is the situation for rs12614 and rs641153, where the low frequency of 1 haplotype means that the r2 is 0.01 but the D' is 1.
Hughes and Bradley also suggest consideration of genotype call rate restrictions as an inclusion criterion for metaanalysis. This would be more appropriate when focusing on genetic variants per se, as considered within the context of a genome-wide association study or other specific genetic analysis where large numbers of SNPs are evaluated (5).
The concerns raised by Hughes and Bradley reflect the limited ability of a meta-analysis based on summary data to tease out inconsistencies best identified at the individual level. We agree that SNPs in LD should be evaluated, but this will not necessarily be straightforward. A move to make genetic data sets publicly available, as in the Database of Genotypes and Phenotypes (http://www.ncbi.nlm.nih.gov/ gap), is a step in the right direction for greater transparency.

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The Wellcome Trust Case Control Consortium 3 anorexia nervosa genome-wide association scan includes 2907 cases from 15 different populations of European origin genotyped on the Illumina 670K chip. We compared methods for identifying population stratification, and suggest list of markers that may help to counter this problem. It is usual to identify population structure in such studies using only common variants with minor allele frequency (MAF) >5%; we find that this may result in highly informative SNPs being discarded, and suggest that instead all SNPs with MAF >1% may be used. We established informative axes of variation identified via principal component analysis and highlight important features of the genetic structure of diverse European-descent populations, some studied for the first time at this scale. Finally, we investigated the substructure within each of these 15 populations and identified SNPs that help capture hidden stratification. This work can provide information regarding the designing and interpretation of association results in the International Consortia. 

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BACKGROUND: Susceptibility to aggressive periodontitis (AgP) is influenced by genetic as well as environmental factors. Studies linking gene variants to AgP have been mainly centred in developed countries with limited data from Africa.
AIM: To investigate whether previously reported candidate gene associations with AgP could be replicated in a population from Sudan.


METHODS: The investigation was a case-control design. Cases with AgP (n = 132) and controls (n = 136) were identified from patients attending the Periodontal Department in Khartoum Dental Hospital. Genotyping was performed using the Sequenom MassARRAY iPLEX platform. Analysis focused on gene variants with a minor allele frequency (MAF) > 25% in the Sudanese subjects that had previously been reported to be associated with AgP.


RESULTS: One candidate gene rs1537415 (GLT6D1) was significantly associated with AgP, OR = 1.50 (95% CI 1.04-2.17), p = 0.0295 (increasing to p = 0.09 after correction for multiple testing). The association strengthened to OR = 1.56 (95% CI 1.15-2.16), p = 0.0042 when the controls were supplemented with data from the Hap map for the Yoruba in Ibadan (n = 147) and remained significant (p = 0.013) after correction for multiple testing.


CONCLUSION: The study independently replicated the finding that rs1537415, a variant in glycosyl transferase gene GLT6D1, is associated with AgP and provided the first report of genetic associations with AgP in a Sudanese population.

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The prevalence of factor V (FV) Leiden among normal populations has primarily been determined using blood donors. This control group is carefully selected and therefore may not accurately reflect the true prevalence within the population. We assessed the prevalence of FV Leiden within the Irish population using Guthrie card samples randomly selected from all newborns. We compared this result with the prevalence of FV Leiden within blood donors. A novel nested polymerase chain reaction (PCR) method for FV Leiden was developed for analysis of the Guthrie card samples. There was no significant difference between the allele frequency within the Guthrie card samples and blood donors (2.07% vs. 2.35%, P = 0.66)

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The prothrombin G20210A polymorphism is associated with a threefold-increased risk of venous thrombosis. There is considerable variation in the reported prevalence of this polymorphism within normal populations, ranging from 0 to 6.5%. The prevalence within the Irish population has not been determined. A restriction fragment length polymorphism (RFLP)-based assay is commonly used for the detection of the prothrombin 20210A allele. This assay does not include a control restriction digest fragment and, consequently, failure of the enzyme activity or lack of addition of enzyme to the sample cannot be distinguished from wild-type prothrombin. We developed a RFLP-based assay, which incorporates an invariant digest site, resulting in the generation of a control digest fragment. Furthermore, we developed a nested polymerase chain reaction (PCR) method for the amplification and digestion of poor-quality or low-concentration DNA. In the Irish population studied, five of 385 (1.29%) were heterozygous and one patient was homozygous for the prothrombin 20210A polymorphism. This is the first reported data on an Irish or Celtic population and suggests that the allele frequency is similar to Anglo-Saxon populations. The nested PCR method successfully amplified and digested 100/100 (100%) of the archived samples; none of these samples could be analyzed by the standard single-round PCR method. In conclusion, nested PCR should be considered in the analysis of archived samples. Single-round PCR is appropriate for recently collected samples; however, an invariant control digest site should be incorporated in RFLP-based assays to validate the integrity of the digestion enzyme and limit the risk of false-negative results.

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To identify previously unknown genetic loci associated with fasting glucose concentrations, we examined the leading association signals in ten genome-wide association scans involving a total of 36,610 individuals of European descent. Variants in the gene encoding melatonin receptor 1B (MTNR1B) were consistently associated with fasting glucose across all ten studies. The strongest signal was observed at rs10830963, where each G allele (frequency 0.30 in HapMap CEU) was associated with an increase of 0.07 (95% CI = 0.06-0.08) mmol/l in fasting glucose levels (P = 3.2 x 10(-50)) and reduced beta-cell function as measured by homeostasis model assessment (HOMA-B, P = 1.1 x 10(-15)). The same allele was associated with an increased risk of type 2 diabetes (odds ratio = 1.09 (1.05-1.12), per G allele P = 3.3 x 10(-7)) in a meta-analysis of 13 case-control studies totaling 18,236 cases and 64,453 controls. Our analyses also confirm previous associations of fasting glucose with variants at the G6PC2 (rs560887, P = 1.1 x 10(-57)) and GCK (rs4607517, P = 1.0 x 10(-25)) loci.

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Identifying adaptive genetic variation is a challenging task, in particular in non-model species for which genomic information is still limited or absent. Here, we studied distribution patterns of amplified fragment length polymorphisms (AFLPs) in response to environmental variation, in 13 alpine plant species consistently sampled across the entire European Alps. Multiple linear regressions were performed between AFLP allele frequencies per site as dependent variables and two categories of independent variables, namely Moran's eigenvector map MEM variables (to account for spatial and unaccounted environmental variation, and historical demographic processes) and environmental variables. These associations allowed the identification of 153 loci of ecological relevance. Univariate regressions between allele frequency and each environmental factor further showed that loci of ecological relevance were mainly correlated with MEM variables. We found that precipitation and temperature were the best environmental predictors, whereas topographic factors were rarely involved in environmental associations. Climatic factors, subject to rapid variation as a result of the current global warming, are known to strongly influence the fate of alpine plants. Our study shows, for the first time for a large number of species, that the same environmental variables are drivers of plant adaptation at the scale of a whole biome, here the European Alps.

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BACKGROUND: LDL cholesterol has a causal role in the development of cardiovascular disease. Improved understanding of the biological mechanisms that underlie the metabolism and regulation of LDL cholesterol might help to identify novel therapeutic targets. We therefore did a genome-wide association study of LDL-cholesterol concentrations. METHODS: We used genome-wide association data from up to 11,685 participants with measures of circulating LDL-cholesterol concentrations across five studies, including data for 293 461 autosomal single nucleotide polymorphisms (SNPs) with a minor allele frequency of 5% or more that passed our quality control criteria. We also used data from a second genome-wide array in up to 4337 participants from three of these five studies, with data for 290,140 SNPs. We did replication studies in two independent populations consisting of up to 4979 participants. Statistical approaches, including meta-analysis and linkage disequilibrium plots, were used to refine association signals; we analysed pooled data from all seven populations to determine the effect of each SNP on variations in circulating LDL-cholesterol concentrations. FINDINGS: In our initial scan, we found two SNPs (rs599839 [p=1.7x10(-15)] and rs4970834 [p=3.0x10(-11)]) that showed genome-wide statistical association with LDL cholesterol at chromosomal locus 1p13.3. The second genome screen found a third statistically associated SNP at the same locus (rs646776 [p=4.3x10(-9)]). Meta-analysis of data from all studies showed an association of SNPs rs599839 (combined p=1.2x10(-33)) and rs646776 (p=4.8x10(-20)) with LDL-cholesterol concentrations. SNPs rs599839 and rs646776 both explained around 1% of the variation in circulating LDL-cholesterol concentrations and were associated with about 15% of an SD change in LDL cholesterol per allele, assuming an SD of 1 mmol/L. INTERPRETATION: We found evidence for a novel locus for LDL cholesterol on chromosome 1p13.3. These results potentially provide insight into the biological mechanisms that underlie the regulation of LDL cholesterol and might help in the discovery of novel therapeutic targets for cardiovascular disease.

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Seizures associated with fever are a common pediatric problem, affecting about 2-7 % of children between 3 months and 5 years of age. Differentiation of febrile seizures from acute symptomatic seizures secondary to central nervous system infections or seizures associated with fever in children with epilepsy is essential to provide appropriate treatment and follow-up care. Here, we tested the hypothesis that children who exhibit simple febrile seizures during early childhood, but do not develop epileptic seizures later in life, might preferentially carry the ApoE2 allele of the gene coding for the apolipoprotein E. We did not find any differences in the distribution of ApoE alleles or genotypes between individuals who exhibited simple febrile seizures (n = 93) and age-matched, typically developing subjects (n = 80). We found that the observed allele and genotype frequencies did not deviate from Hardy-Weinberg equilibrium, which suggests that the frequencies of ApoE alleles and genotypes are stable in the Swiss population from which our samples were derived. Across both groups of subjects (n = 173), we found an ApoE2 allele frequency of 0.064, an ApoE3 frequency of 0.829 and an ApoE4 frequency of 0.107. Our findings are consistent with previous reports of the distribution of ApoE polymorphism for European subjects free of any neurological disorders, and show that the different alleles of the gene coding for the apolipoprotein E are not associated with the occurrence of simple febrile seizures.

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L’hypertriglycéridémie (hyperTG) est une dyslipidémie fréquente, caractérisée par une augmentation de la concentration plasmatique en triglycérides (TG). L’hyperTG est considérée comme un facteur de risque indépendant de la maladie cardiovasculaire, particulièrement de la maladie coronarienne athérosclérotique. Plusieurs facteurs environnementaux et génétiques ont été associés avec l’hyperTG. Cependant, près de 90% des cas d’hyperTG primaire sont encore incomplètement caractérisés au niveau moléculaire. Dernièrement, la protéine GPIHBP1 (glycosylphosphatidylinositol-anchored high-density lipoprotein-binding protein 1), qui a un rôle clef dans le métabolisme des TG, a été associée à l’expression d’hyperTG sévère et rare chez l’humain. Ce mémoire présente les résultats de nos travaux qui ont été effectués afin d’identifier de nouvelles bases moléculaires associées à l’expression de l’hyperTG dans le locus du gène GPIHBP1. Nous avons observé que le polymorphisme GPIHBP1 g.-469G>A (rs72691625), dont la fréquence de l’allèle mineure a été évaluée à 19,6% dans notre échantillon, serait associé à l’expression d’hyperTG (TG ≥ 2mmol/L) dans une population canadienne-française. Ce polymorphisme est associé à un risque 1,67 fois plus grand d’exprimer une triglycéridémie ≥ 2mmol/L chez les porteurs hétérozygotes et 5,7 fois plus grand chez les porteurs homozygotes, comparativement aux non-porteurs. Ce risque d’hyperTG serait exacerbé par la présence concomitante d’une mutation hypertriglycéridémiante dans le gène codant pour la lipoprotéine lipase. La présence de ce polymorphisme serait particulièrement associée à l’expression de la dysbêtalipoprotéinémie familiale et de l’hypertriglycéridémie familiale endogène. GPIHBP1 g.-469G>A est le premier polymorphisme fréquent identifié dans le promoteur du gène à être associé avec l’expression d’hyperTG. GPIHBP1 émerge de plus en plus comme un gène candidat intéressant pour la recherche de nouvelles bases moléculaires pouvant expliquer certaines formes d’hyperTG primaire fréquente.

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The Hardy-Weinberg law, formulated about 100 years ago, states that under certain assumptions, the three genotypes AA, AB and BB at a bi-allelic locus are expected to occur in the proportions p2, 2pq, and q2 respectively, where p is the allele frequency of A, and q = 1-p. There are many statistical tests being used to check whether empirical marker data obeys the Hardy-Weinberg principle. Among these are the classical xi-square test (with or without continuity correction), the likelihood ratio test, Fisher's Exact test, and exact tests in combination with Monte Carlo and Markov Chain algorithms. Tests for Hardy-Weinberg equilibrium (HWE) are numerical in nature, requiring the computation of a test statistic and a p-value. There is however, ample space for the use of graphics in HWE tests, in particular for the ternary plot. Nowadays, many genetical studies are using genetical markers known as Single Nucleotide Polymorphisms (SNPs). SNP data comes in the form of counts, but from the counts one typically computes genotype frequencies and allele frequencies. These frequencies satisfy the unit-sum constraint, and their analysis therefore falls within the realm of compositional data analysis (Aitchison, 1986). SNPs are usually bi-allelic, which implies that the genotype frequencies can be adequately represented in a ternary plot. Compositions that are in exact HWE describe a parabola in the ternary plot. Compositions for which HWE cannot be rejected in a statistical test are typically “close" to the parabola, whereas compositions that differ significantly from HWE are “far". By rewriting the statistics used to test for HWE in terms of heterozygote frequencies, acceptance regions for HWE can be obtained that can be depicted in the ternary plot. This way, compositions can be tested for HWE purely on the basis of their position in the ternary plot (Graffelman & Morales, 2008). This leads to nice graphical representations where large numbers of SNPs can be tested for HWE in a single graph. Several examples of graphical tests for HWE (implemented in R software), will be shown, using SNP data from different human populations