128 resultados para genotypes


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Context: in the ESR1 gene encoding estrogen receptor (ER)-α may be associated with fat mass in adults. Objectives: The objective of the study was to establish whether ESR1 polymorphisms influence fat mass in childhood. Design: This was a cross-sectional analysis after genotyping of rs9340799, rs2234693, and rs7757956 ESR1 polymorphisms. Setting: The Avon Longitudinal Study of Parents and Children (ALSPAC) was a population-based prospective study. Participants: Participants included 3097 11-yr-old children with results for ESR1 genotyping, puberty measures, and dual-energy x-ray absorptiometry results. Outcomes: Relationships between ESR1 polymorphisms and indices of body composition were measured. Results: The rs7757956 polymorphism was associated with fat mass (P = 0.002). Total body fat mass (adjusted for height) was reduced by 6% in children with TA/AA genotypes, and risk of being overweight (≥85th centile of fat mass) was decreased by 20%. This genetic effect appeared to interact with puberty in girls (P = 0.05 for interaction): in those with the TT genotype, total body fat mass (adjusted for height) was 18% higher in Tanner stages 3-5 vs. stages 1-2; the equivalent difference was 7% in those with TA/AA genotypes. Furthermore, the risk of being overweight was 36% lower in girls with TA/AA genotypes in Tanner stages 3-5, but no reduction was seen in those in stages 1-2. Neither rs9340799 nor rs2234693 polymorphisms were associated with body composition measures. Conclusions: Fat mass in 11-yr-old children was related to the rs7757956 ESR1 polymorphism. This association was strongest in girls in more advanced puberty, in whom the risk of being overweight was reduced by 36% in those with the TA/AA genotype.

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The MFG test is a family-based association test that detects genetic effects contributing to disease in offspring, including offspring allelic effects, maternal allelic effects and MFG incompatibility effects. Like many other family-based association tests, it assumes that the offspring survival and the offspring-parent genotypes are conditionally independent provided the offspring is affected. However, when the putative disease-increasing locus can affect another competing phenotype, for example, offspring viability, the conditional independence assumption fails and these tests could lead to incorrect conclusions regarding the role of the gene in disease. We propose the v-MFG test to adjust for the genetic effects on one phenotype, e.g., viability, when testing the effects of that locus on another phenotype, e.g., disease. Using genotype data from nuclear families containing parents and at least one affected offspring, the v-MFG test models the distribution of family genotypes conditional on offspring phenotypes. It simultaneously estimates genetic effects on two phenotypes, viability and disease. Simulations show that the v-MFG test produces accurate genetic effect estimates on disease as well as on viability under several different scenarios. It generates accurate type-I error rates and provides adequate power with moderate sample sizes to detect genetic effects on disease risk when viability is reduced. We demonstrate the v-MFG test with HLA-DRB1 data from study participants with rheumatoid arthritis (RA) and their parents, we show that the v-MFG test successfully detects an MFG incompatibility effect on RA while simultaneously adjusting for a possible viability loss.

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Genetic factors are known to influence both the peak bone mass and probably the rate of change in bone density. A range of regulatory and structural genes has been proposed to be involved including collagen 1α1 (COL1A1), the estrogen receptor (ER), and the vitamin D receptor (VDR), but the actual genes involved are uncertain. We therefore studied the role of the COL1A1 and VDR loci in control of bone density by linkage in 45 dizygotic twin pairs and 29 nuclear families comprising 120 individuals. The influences on bone density of polymorphisms of COL1A1, VDR, and ER were studied by association both cross-sectionally and longitudinally in 193 elderly postmenopausal women (average age, 69 years) over a mean follow-up time of 6.3 years. Weak linkage of the COL1A1 locus with bone density was observed in both twins and families (p = 0.02 in both data sets), confirming previous observations of linkage of this locus with bone density. Association between the MscI polymorphism of COL1A1 and rate of lumbar spine bone loss was observed with significant gene-environment interaction related to dietary calcium intake (p = 0.0006). In the lowest tertile of dietary calcium intake, carriers of "s" alleles lost more bone than "SS" homozygotes (p = 0.01), whereas the opposite was observed in the highest dietary calcium intake (p = 0.003). Association also was observed between rate of bone loss at both the femoral neck and the lumbar spine and the TaqI VDR polymorphism (p = 0.03). This association was strongest in those in the lowest tertile of calcium intake, also suggesting the presence of gene-environment interaction involving dietary calcium and VDR, influencing bone turnover. No significant association was observed between the PvuII ER polymorphism alone or in combination with VDR or COL1A1 genotypes, with either bone density or its rate of change. These data support the involvement of COL1A1 in determination of bone density and the interaction of both COL1A1 and VDR with calcium intake in regulation of change of bone density over time.

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STUDY QUESTION: Do DNA variants in the growth regulation by estrogen in breast cancer 1 (GREB1) region regulate endometrial GREB1 expression and increase the risk of developing endometriosis in women? SUMMARY ANSWER: We identified new single nucleotide polymorphisms (SNPs) with strong association with endometriosis at the GREB1 locus although we did not detect altered GREB1 expression in endometriosis patients with defined genotypes. WHAT IS ALREADY KNOWN: Genome-wide association studies have identified the GREB1 region on chromosome 2p25.1 for increasing endometriosis risk. The differential expression of GREB1 has also been reported by others in association with endometriosis disease phenotype. STUDY DESIGN, SIZE, DURATION: Fine mapping studies comprehensively evaluated SNPs within the GREB1 region in a large-scale data set (>2500 cases and >4000 controls). Publicly available bioinformatics tools were employed to functionally annotate SNPs showing the strongest association signal with endometriosis risk. Endometrial GREB1 mRNA and protein expression was studied with respect to phases of the menstrual cycle (n = 2-45 per cycle stage) and expression quantitative trait loci (eQTL) analysis for significant SNPs were undertaken for GREB1 [mRNA (n = 94) and protein (n = 44) in endometrium]. PARTICIPANTS/MATERIALS, SETTING, METHODS: Participants in this study are females who provided blood and/or endometrial tissue samples in a hospital setting. The key SNPs were genotyped using Sequenom MassARRAY. The functional roles and regulatory annotations for identified SNPs are predicted by various publicly available bioinformatics tools. Endometrial GREB1 expression work employed qRT-PCR, western blotting and immunohistochemistry studies. MAIN RESULTS AND THE ROLE OF CHANCE: Fine mapping results identified a number of SNPs showing stronger association (0.004 < P < 0.032) with endometriosis risk than the original GWAS SNP (rs13394619) (P = 0.034). Some of these SNPs were predicted to have functional roles, for example, interaction with transcription factor motifs. The haplotype (a combination of alleles) formed by the risk alleles from two common SNPs showed significant association (P = 0.026) with endometriosis and epistasis analysis showed no evidence for interaction between the two SNPs, suggesting an additive effect of SNPs on endometriosis risk. In normal human endometrium, GREB1 protein expression was altered depending on the cycle stage (significantly different in late proliferative versus late secretory, P < 0.05) and cell type (glandular epithelium, not stromal cells). However, GREB1 expression in endometriosis cases versus controls and eQTL analyses did not reveal any significant changes. LIMITATIONS, REASONS FOR CAUTION: In silico prediction tools are generally based on cell lines different to our tissue and disease of interest. Functional annotations drawn from these analyses should be considered with this limitation in mind. We identified cell-specific and hormone-specific changes in GREB1 protein expression. The lack of a significant difference observed following our GREB1 expression studies may be the result of moderate power on mixed cell populations in the endometrial tissue samples. WIDER IMPLICATIONS OF THE FINDINGS: This study further implicates the GREB1 region on chromosome 2p25.1 and the GREB1 gene with involvement in endometriosis risk. More detailed functional studies are required to determine the role of the novel GREB1 transcripts in endometriosis pathophysiology. STUDY FUNDING/COMPETING INTERESTS: Funding for this work was provided by NHMRC Project Grants APP1012245, APP1026033, APP1049472 and APP1046880. There are no competing interests.

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Genome-wide association studies show strong evidence of association with endometriosis for markers on chromosome 1p36 spanning the potential candidate genes WNT4, CDC42 and LINC00339. WNT4 is involved in development of the uterus, and the expression of CDC42 and LINC00339 are altered in women with endometriosis. We conducted fine mapping to examine the role of coding variants in WNT4 and CDC42 and determine the key SNPs with strongest evidence of association in this region. We identified rare coding variants in WNT4 and CDC42 present only in endometriosis cases. The frequencies were low and cannot account for the common signal associated with increased risk of endometriosis. Genotypes for five common SNPs in the region of chromosome 1p36 show stronger association signals when compared with rs7521902 reported in published genome scans. Of these, three SNPs rs12404660, rs3820282, and rs55938609 were located in DNA sequences with potential functional roles including overlap with transcription factor binding sites for FOXA1, FOXA2, ESR1, and ESR2. Functional studies will be required to identify the gene or genes implicated in endometriosis risk.

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There is evidence across several species for genetic control of phenotypic variation of complex traits1, 2, 3, 4, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using ~170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype)5, 6, 7, is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of ~0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI8, possibly mediated by DNA methylation9, 10. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.

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BACKGROUND Correlations between Educational Attainment (EA) and measures of cognitive performance are as high as 0.8. This makes EA an attractive alternative phenotype for studies wishing to map genes affecting cognition due to the ease of collecting EA data compared to other cognitive phenotypes such as IQ. METHODOLOGY In an Australian family sample of 9538 individuals we performed a genome-wide association scan (GWAS) using the imputed genotypes of approximately 2.4 million single nucleotide polymorphisms (SNP) for a 6-point scale measure of EA. Top hits were checked for replication in an independent sample of 968 individuals. A gene-based test of association was then applied to the GWAS results. Additionally we performed prediction analyses using the GWAS results from our discovery sample to assess the percentage of EA and full scale IQ variance explained by the predicted scores. RESULTS The best SNP fell short of having a genome-wide significant p-value (p = 9.77x10(-7)). In our independent replication sample six SNPs among the top 50 hits pruned for linkage disequilibrium (r(2)<0.8) had a p-value<0.05 but only one of these SNPs survived correction for multiple testing--rs7106258 (p = 9.7*10(-4)) located in an intergenic region of chromosome 11q14.1. The gene based test results were non-significant and our prediction analyses show that the predicted scores explained little variance in EA in our replication sample. CONCLUSION While we have identified a polymorphism chromosome 11q14.1 associated with EA, further replication is warranted. Overall, the absence of genome-wide significant p-values in our large discovery sample confirmed the high polygenic architecture of EA. Only the assembly of large samples or meta-analytic efforts will be able to assess the implication of common DNA polymorphisms in the etiology of EA.

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Serum butyrylcholinesterase (BCHE) activity is associated with obesity, blood pressure and biomarkers of cardiovascular and diabetes risk. We have conducted a genome-wide association scan to discover genetic variants affecting BCHE activity, and to clarify whether the associations between BCHE activity and cardiometabolic risk factors are caused by variation in BCHE or whether BCHE variation is secondary to the metabolic abnormalities. We measured serum BCHE in adolescents and adults from three cohorts of Australian twin and family studies. The genotypes from approximately 2.4 million single-nucleotide polymorphisms (SNPs) were available in 8791 participants with BCHE measurements. We detected significant associations with BCHE activity at three independent groups of SNPs at the BCHE locus (P = 5.8 x 10(-262), 7.8 x 10(-47), 2.9 x 10(-12)) and at four other loci: RNPEP (P = 9.4 x 10(-16)), RAPH1-ABI2 (P = 4.1 x 10(-18)), UGT1A1 (P = 4.0 x 10(-8)) and an intergenic region on chromosome 8 (P = 1.4 x 10(-8)). These loci affecting BCHE activity were not associated with metabolic risk factors. On the other hand, SNPs in genes previously associated with metabolic risk had effects on BCHE activity more often than can be explained by chance. In particular, SNPs within FTO and GCKR were associated with BCHE activity, but their effects were partly mediated by body mass index and triglycerides, respectively. We conclude that variation in BCHE activity is due to multiple variants across the spectrum from uncommon/large effect to common/small effect, and partly results from (rather than causes) metabolic abnormalities.

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The impact of erroneous genotypes having passed standard quality control (QC) can be severe in genome-wide association studies, genotype imputation, and estimation of heritability and prediction of genetic risk based on single nucleotide polymorphisms (SNP). To detect such genotyping errors, a simple two-locus QC method, based on the difference in test statistic of association between single SNPs and pairs of SNPs, was developed and applied. The proposed approach could detect many problematic SNPs with statistical significance even when standard single SNP QC analyses fail to detect them in real data. Depending on the data set used, the number of erroneous SNPs that were not filtered out by standard single SNP QC but detected by the proposed approach varied from a few hundred to thousands. Using simulated data, it was shown that the proposed method was powerful and performed better than other tested existing methods. The power of the proposed approach to detect erroneous genotypes was approximately 80% for a 3% error rate per SNP. This novel QC approach is easy to implement and computationally efficient, and can lead to a better quality of genotypes for subsequent genotype-phenotype investigations.

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OBJECTIVE: To further investigate a common variant (rs9939609) in the fat mass- and obesity-associated gene (FTO), which recent genome-wide association studies have shown to be associated with body mass index (BMI) and obesity. DESIGN: We examined the effect of this FTO variant on BMI in 3353 Australian adult male and female twins. RESULTS: The minor A allele of rs9939609 was associated with an increased BMI (P=0.0007). Each additional copy of the A allele was associated with a mean BMI increase of approximately 1.04 kg/m(2) (approximately 3.71 kg). Using variance components decomposition, we estimate that this single-nucleotide polymorphism accounts for approximately 3% of the genetic variance in BMI in our sample (approximately 2% of the total variance). By comparing intrapair variances of monozygotic twins of different genotypes we were able to perform a direct test of gene by environment (G x E) interaction in both sexes and gene by parity (G x P) interaction in women, but no evidence was found for either. CONCLUSIONS: In addition to supporting earlier findings that the rs9939609 variant in the FTO gene is associated with an increased BMI, our results indicate that the associated genetic effect does not interact with environment or parity.

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For complex disease genetics research in human populations, remarkable progress has been made in recent times with the publication of a number of genome-wide association scans (GWAS) and subsequent statistical replications. These studies have identified new genes and pathways implicated in disease, many of which were not known before. Given these early successes, more GWAS are being conducted and planned, both for disease and quantitative phenotypes. Many researchers and clinicians have DNA samples available on collections of families, including both cases and controls. Twin registries around the world have facilitated the collection of large numbers of families, with DNA and multiple quantitative phenotypes collected on twin pairs and their relatives. In the design of a new GWAS with a fixed budget for the number of chips, the question arises whether to include or exclude related individuals. It is commonly believed to be preferable to use unrelated individuals in the first stage of a GWAS because relatives are 'over-matched' for genotypes. In this study, we quantify that for GWAS of a quantitative phenotype, relative to a sample of unrelated individuals surprisingly little power is lost when using relatives. The advantages of using relatives are manifold, including the ability to perform more quality control, the choice to perform within-family tests of association that are robust to population stratification, and the ability to perform joint linkage and association analysis. Therefore, the advantages of using relatives in GWAS for quantitative traits may well outweigh the small disadvantage in terms of statistical power.

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Endometriosis has a genetic component, and significant linkage has been found to a region on chromosome 10q. Two candidate genes, EMX2 and PTEN, implicated in both endometriosis and endometrial cancer, lie on chromosome 10q. We hypothesized that variation in EMX2 and/or PTEN could contribute to the risk of endometriosis and may account for some of the linkage signal on 10q. We genotyped single nucleotide polymorphisms (SNPs) in a case-control design to evaluate association between endometriosis and common variations in these two genes. The genotyping and statistical analysis were based on samples collected from Australian volunteers. The cases were 768 unrelated women with surgically confirmed endometriosis selected from affected sister pair (ASP) families participating in the Australian Genes behind Endometriosis Study. The controls were 768 female participants in twin studies who, based on screening questions, did not have a diagnosis of endometriosis. Genotypes of 22 SNPs in the EMX2 gene and 15 SNPs in the PTEN gene were the main outcome measures. Statistical analysis provided measures of linkage disequilibrium and association. Permutation testing showed no globally significant association between any SNPs or haplotypes and endometriosis for either gene. It is unlikely that the EMX2 or PTEN gene variants investigated contribute to risk for initiation and/or development of endometriosis.

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Endometriosis is a common gynaecological disease with symptoms of pelvic pain and infertility which affects 7-10% of women in their reproductive years. Activation of an oncogenic allele of Kirsten rat sarcoma viral oncogene homologue (KRAS) in the reproductive tract of mice resulted in the development of endometriosis. We hypothesized that variation in KRAS may influence risk of endometriosis in humans. Thirty tagSNPs spanning a region of 60.7 kb across the KRAS locus were genotyped using iPLEX chemistry on a MALDI-TOF MassARRAY platform in 959 endometriosis cases and 959 unrelated controls, and data were analysed for association with endometriosis. Genotypes were obtained for most individuals with a mean completion rate of 99.1%. We identified six haplotype blocks across the KRAS locus in our sample. There were no significant differences between cases and controls in the frequencies of individual single-nucleotide polymorphisms (SNPs) or haplotypes. We also developed a rapid method to screen for 11 common KRAS and BRAF mutations on the Sequenom MassARRAY system. The assay detected all mutations previously identified by direct sequencing in a panel of positive controls. No germline variants for KRAS or BRAF were detected. Our results demonstrate that any risk of endometriosis in women because of common variation in KRAS must be very small.

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Accurate determination of same-sex twin zygosity is important for medical, scientific and personal reasons. Determination may be based upon questionnaire data, blood group, enzyme isoforms and fetal membrane examination, but assignment of zygosity must ultimately be confirmed by genotypic data. Here methods are reviewed for calculating average probabilities of correctly concluding a twin pair is monozygotic, given they share the same genotypes across all loci for commonly utilized multiplex short tandem repeat (STR) kits.

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Utilizing DNA samples from 91 Afrikaner nuclear families with one or more affected children, five genomic regions on chromosomes 2p, 8q, 11q, 20q, and 21q that gave evidence for association with GTS in previous case-control association studies were investigated for linkage and association with GTS. Highly polymorphic markers with mean heterozygosity of 0.77 were typed and resulting genotypes evaluated using single marker transmission disequilibrium (TDT), single marker haplotype relative risk (HRR), and multi-marker "extended" TDT and HRR methods. Single marker TDT analysis showed evidence for linkage or association, with p-values near 0.05, for markers D2S139, GATA28F12, and D11S1377 on chromosomes 2p11, 8q22 and 11q23-24, respectively. Extended, two-locus TDT and HRR analysis provided further evidence for linkage or association on chromosome 2 with p-values of 0.007 and 0.025, and chromosome 8 with p-values of 0.059 and 0.013, respectively. These results provide important additional evidence for the location of GTS susceptibility loci.