992 resultados para Montana Bar Association


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Endometriosis is a common gynecological disease associated with pelvic pain and subfertility. We conducted a genome-wide association study (GWAS) in 3,194 individuals with surgically confirmed endometriosis (cases) and 7,060 controls from Australia and the UK. Polygenic predictive modeling showed significantly increased genetic loading among 1,364 cases with moderate to severe endometriosis. The strongest association signal was on 7p15.2 (rs12700667) for 'all' endometriosis (P = 2.6 x 10(-)(7), odds ratio (OR) = 1.22, 95% CI 1.13-1.32) and for moderate to severe disease (P = 1.5 x 10(-)(9), OR = 1.38, 95% CI 1.24-1.53). We replicated rs12700667 in an independent cohort from the United States of 2,392 self-reported, surgically confirmed endometriosis cases and 2,271 controls (P = 1.2 x 10(-)(3), OR = 1.17, 95% CI 1.06-1.28), resulting in a genome-wide significant P value of 1.4 x 10(-)(9) (OR = 1.20, 95% CI 1.13-1.27) for 'all' endometriosis in our combined datasets of 5,586 cases and 9,331 controls. rs12700667 is located in an intergenic region upstream of the plausible candidate genes NFE2L3 and HOXA10.

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The relationship between major depressive disorder (MDD) and bipolar disorder (BD) remains controversial. Previous research has reported differences and similarities in risk factors for MDD and BD, such as predisposing personality traits. For example, high neuroticism is related to both disorders, whereas openness to experience is specific for BD. This study examined the genetic association between personality and MDD and BD by applying polygenic scores for neuroticism, extraversion, openness to experience, agreeableness and conscientiousness to both disorders. Polygenic scores reflect the weighted sum of multiple single-nucleotide polymorphism alleles associated with the trait for an individual and were based on a meta-analysis of genome-wide association studies for personality traits including 13,835 subjects. Polygenic scores were tested for MDD in the combined Genetic Association Information Network (GAIN-MDD) and MDD2000+ samples (N=8921) and for BD in the combined Systematic Treatment Enhancement Program for Bipolar Disorder and Wellcome Trust Case-Control Consortium samples (N=6329) using logistic regression analyses. At the phenotypic level, personality dimensions were associated with MDD and BD. Polygenic neuroticism scores were significantly positively associated with MDD, whereas polygenic extraversion scores were significantly positively associated with BD. The explained variance of MDD and BD, approximately 0.1%, was highly comparable to the variance explained by the polygenic personality scores in the corresponding personality traits themselves (between 0.1 and 0.4%). This indicates that the proportions of variance explained in mood disorders are at the upper limit of what could have been expected. This study suggests shared genetic risk factors for neuroticism and MDD on the one hand and for extraversion and BD on the other.

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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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We performed a genome-wide association study of melanoma in a discovery cohort of 2,168 Australian individuals with melanoma and 4,387 control individuals. In this discovery phase, we confirm several previously characterized melanoma-associated loci at MC1R, ASIP and MTAP-CDKN2A. We selected variants at nine loci for replication in three independent case-control studies (Europe: 2,804 subjects with melanoma, 7,618 control subjects; United States 1: 1,804 subjects with melanoma, 1,026 control subjects; United States 2: 585 subjects with melanoma, 6,500 control subjects). The combined meta-analysis of all case-control studies identified a new susceptibility locus at 1q21.3 (rs7412746, P = 9.0 x 10(-11), OR in combined replication cohorts of 0.89 (95% CI 0.85-0.95)). We also show evidence suggesting that melanoma associates with 1q42.12 (rs3219090, P = 9.3 x 10(-8)). The associated variants at the 1q21.3 locus span a region with ten genes, and plausible candidate genes for melanoma susceptibility include ARNT and SETDB1. Variants at the 1q21.3 locus do not seem to be associated with human pigmentation or measures of nevus density.

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Migraine is a common neurological disorder with a genetically complex background. This paper describes a meta-analysis of genome-wide association (GWA) studies on migraine, performed by the Dutch-Icelandic migraine genetics (DICE) consortium, which brings together six population-based European migraine cohorts with a total sample size of 10,980 individuals (2446 cases and 8534 controls). A total of 32 SNPs showed marginal evidence for association at a P-value<10(-5). The best result was obtained for SNP rs9908234, which had a P-value of 8.00 x 10(-8). This top SNP is located in the nerve growth factor receptor (NGFR) gene. However, this SNP did not replicate in three cohorts from the Netherlands and Australia. Of the other 31 SNPs, 18 SNPs were tested in two replication cohorts, but none replicated. In addition, we explored previously identified candidate genes in the meta-analysis data set. This revealed a modest gene-based significant association between migraine and the metadherin (MTDH) gene, previously identified in the first clinic-based GWA study (GWAS) for migraine (Bonferroni-corrected gene-based P-value=0.026). This finding is consistent with the involvement of the glutamate pathway in migraine. Additional research is necessary to further confirm the involvement of glutamate.

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BACKGROUND Given moderately strong genetic contributions to variation in alcoholism and heaviness of drinking (50% to 60% heritability) with high correlation of genetic influences, we have conducted a quantitative trait genome-wide association study (GWAS) for phenotypes related to alcohol use and dependence. METHODS Diagnostic interview and blood/buccal samples were obtained from sibships ascertained through the Australian Twin Registry. Genome-wide single nucleotide polymorphism (SNP) genotyping was performed with 8754 individuals (2062 alcohol-dependent cases) selected for informativeness for alcohol use disorder and associated quantitative traits. Family-based association tests were performed for alcohol dependence, dependence factor score, and heaviness of drinking factor score, with confirmatory case-population control comparisons using an unassessed population control series of 3393 Australians with genome-wide SNP data. RESULTS No findings reached genome-wide significance (p = 8.4 x 10(-8) for this study), with lowest p value for primary phenotypes of 1.2 x 10(-7). Convergent findings for quantitative consumption and diagnostic and quantitative dependence measures suggest possible roles for a transmembrane protein gene (TMEM108) and for ANKS1A. The major finding, however, was small effect sizes estimated for individual SNPs, suggesting that hundreds of genetic variants make modest contributions (1/4% of variance or less) to alcohol dependence risk. CONCLUSIONS We conclude that: - 1) meta-analyses of consumption data may contribute usefully to gene discovery; - 2) translation of human alcoholism GWAS results to drug discovery or clinically useful prediction of risk will be challenging, and; - 3) through accumulation across studies, GWAS data may become valuable for improved genetic risk differentiation in research in biological psychiatry (e.g., prospective high-risk or resilience studies).

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Type 1 diabetes is a disease where the insulin-producing beta cells of the pancreas are destroyed by an autoimmune mechanism. The incidence of type 1 diabetes, as well as the incidence of the diabetic kidney complication, diabetic nephropathy, are increasing worldwide. Nephrin is a crucial molecule for the filtration function of the kidney. It localises in the podocyte foot processes partially forming the interpodocyte final sieve of the filtration barrier, the slit diaphragm. The expression of nephrin is altered in diabetic nephropathy. Recently, nephrin was found from the beta cells of the pancreas as well, which makes this molecule interesting in the context of type 1 diabetes and especially in diabetic nephropathy. In this thesis work, the expression of other podocyte molecules in the beta cells of the pancreas, in addition to nephrin, were deciphered. It was also hypothesised that patients with type 1 diabetes may develop autoantibodies against novel beta cell molecules comparably to the formation of autoantibodies to GAD, IA-2 and insulin. The possible association of such novel autoantibodies with the pathogenesis of diabetic nephropathy was also assessed. Furthermore, expression of nephrin in lymphoid tissues has been suggested, and this issue was more thoroughly deciphered here. The expression of nephrin in the human lymphoid tissues, and a set of podocyte molecules in the human, mouse and rat pancreas at the gene and protein level were studied by polymerase chain reaction (PCR) -based methods and immunochemical methods. To detect autoantibodies to novel beta cell molecules, specific radioimmunoprecipitation assays were developed. These assays were used to screen a follow-up material of 66 patients with type 1 diabetes and a patient material of 150 diabetic patients with signs of diabetic nephropathy. Nephrin expression was detected in the lymphoid follicle germinal centres, specifically in the follicular dendritic cells. In addition to the previously reported expression of nephrin in the pancreas, expression of the podocyte molecules, densin, filtrin, FAT and alpha-actinin-4 were detected in the beta cells. Circulating antibodies to nephrin, densin and filtrin were discovered in a subset of patients with type 1 diabetes. However, no association of these autoantibodies with the pathogenesis of diabetic nephropathy was detected. In conclusion, the expression of five podocyte molecules in the beta cells of the pancreas suggests some molecular similarities between the two cell types. The novel autoantibodies against shared molecules of the kidney podocytes and the pancreatic beta cells appear to be part of the common autoimmune mechanism in patients with type 1 diabetes. No data suggested that the autoantibodies would be active participants of the kidney injury detected in diabetic nephropathy.

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Genome-wide association studies followed by replication provide a powerful approach to map genetic risk factors for asthma. We sought to search for new variants associated with asthma and attempt to replicate the association with four loci reported previously (ORMDL3, PDE4D, DENND1B and IL1RL1). Genome-wide association analyses of individual single nucleotide polymorphisms (SNPs), rare copy number variants (CNVs) and overall CNV burden were carried out in 986 asthma cases and 1846 asthma-free controls from Australia. The most-associated locus in the SNP analysis was ORMDL3 (rs6503525, P = 4.8 x 10(-)(7)). Five other loci were associated with P < 10(-)(5), most notably the chemokine CXC motif ligand 14 (CXCL14) gene (rs31263, P = 7.8 x 10(-)(6)). We found no evidence for association with the specific risk variants reported recently for PDE4D, DENND1B and ILR1L1. However, a variant in IL1RL1 that is in low linkage disequilibrium with that reported previously was associated with asthma risk after accounting for all variants tested (rs10197862, gene wide P = 0.01). This association replicated convincingly in an independent cohort (P = 2.4 x 10(-)(4)). A 300-kb deletion on chromosome 17q21 was associated with asthma risk, but this did not reach experiment-wide significance. Asthma cases and controls had comparable CNV rates, length and number of genes affected by deletions or duplications. In conclusion, we confirm the association between asthma risk and variants in ORMDL3 and identify a novel risk variant in IL1RL1. Follow-up of the 17q21 deletion in larger cohorts is warranted.

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In this thesis, two separate single nucleotide polymorphism (SNP) genotyping techniques were set up at the Finnish Genome Center, pooled genotyping was evaluated as a screening method for large-scale association studies, and finally, the former approaches were used to identify genetic factors predisposing to two distinct complex diseases by utilizing large epidemiological cohorts and also taking environmental factors into account. The first genotyping platform was based on traditional but improved restriction-fragment-length-polymorphism (RFLP) utilizing 384-microtiter well plates, multiplexing, small reaction volumes (5 µl), and automated genotype calling. We participated in the development of the second genotyping method, based on single nucleotide primer extension (SNuPeTM by Amersham Biosciences), by carrying out the alpha- and beta tests for the chemistry and the allele-calling software. Both techniques proved to be accurate, reliable, and suitable for projects with thousands of samples and tens of markers. Pooled genotyping (genotyping of pooled instead of individual DNA samples) was evaluated with Sequenom s MassArray MALDI-TOF, in addition to SNuPeTM and PCR-RFLP techniques. We used MassArray mainly as a point of comparison, because it is known to be well suited for pooled genotyping. All three methods were shown to be accurate, the standard deviations between measurements being 0.017 for the MassArray, 0.022 for the PCR-RFLP, and 0.026 for the SNuPeTM. The largest source of error in the process of pooled genotyping was shown to be the volumetric error, i.e., the preparation of pools. We also demonstrated that it would have been possible to narrow down the genetic locus underlying congenital chloride diarrhea (CLD), an autosomal recessive disorder, by using the pooling technique instead of genotyping individual samples. Although the approach seems to be well suited for traditional case-control studies, it is difficult to apply if any kind of stratification based on environmental factors is needed. Therefore we chose to continue with individual genotyping in the following association studies. Samples in the two separate large epidemiological cohorts were genotyped with the PCR-RFLP and SNuPeTM techniques. The first of these association studies concerned various pregnancy complications among 100,000 consecutive pregnancies in Finland, of which we genotyped 2292 patients and controls, in addition to a population sample of 644 blood donors, with 7 polymorphisms in the potentially thrombotic genes. In this thesis, the analysis of a sub-study of pregnancy-related venous thromboses was included. We showed that the impact of factor V Leiden polymorphism on pregnancy-related venous thrombosis, but not the other tested polymorphisms, was fairly large (odds ratio 11.6; 95% CI 3.6-33.6), and increased multiplicatively when combined with other risk factors such as obesity or advanced age. Owing to our study design, we were also able to estimate the risks at the population level. The second epidemiological cohort was the Helsinki Birth Cohort of men and women who were born during 1924-1933 in Helsinki. The aim was to identify genetic factors that might modify the well known link between small birth size and adult metabolic diseases, such as type 2 diabetes and impaired glucose tolerance. Among ~500 individuals with detailed birth measurements and current metabolic profile, we found that an insertion/deletion polymorphism of the angiotensin converting enzyme (ACE) gene was associated with the duration of gestation, and weight and length at birth. Interestingly, the ACE insertion allele was also associated with higher indices of insulin secretion (p=0.0004) in adult life, but only among individuals who were born small (those among the lowest third of birth weight). Likewise, low birth weight was associated with higher indices of insulin secretion (p=0.003), but only among carriers of the ACE insertion allele. The association with birth measurements was also found with a common haplotype of the glucocorticoid receptor (GR) gene. Furthermore, the association between short length at birth and adult impaired glucose tolerance was confined to carriers of this haplotype (p=0.007). These associations exemplify the interaction between environmental factors and genotype, which, possibly due to altered gene expression, predisposes to complex metabolic diseases. Indeed, we showed that the common GR gene haplotype associated with reduced mRNA expression in thymus of three individuals (p=0.0002).

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Broadscale irrigation is a major land use in many of the priority neighbourhood catchments (45,218 hectares in Central Highlands and Dawson) and there is a requirement to provide technical support to sub-regional group field officers and landholders in these priority catchments. This technical support will assist field staff and land managers to identify and implement appropriate, sustainable technologies and management practices.

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Variation in personality traits is 30-60% attributed to genetic influences. Attempts to unravel these genetic influences at the molecular level have, so far, been inconclusive. We performed the first genome-wide association study of Cloninger's temperament scales in a sample of 5117 individuals, in order to identify common genetic variants underlying variation in personality. Participants' scores on Harm Avoidance, Novelty Seeking, Reward Dependence, and Persistence were tested for association with 1,252,387 genetic markers. We also performed gene-based association tests and biological pathway analyses. No genetic variants that significantly contribute to personality variation were identified, while our sample provides over 90% power to detect variants that explain only 1% of the trait variance. This indicates that individual common genetic variants of this size or greater do not contribute to personality trait variation, which has important implications regarding the genetic architecture of personality and the evolutionary mechanisms by which heritable variation is maintained.

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Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and approximately 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 x 10(-)(8)), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.

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We have derived a versatile gene-based test for genome-wide association studies (GWAS). Our approach, called VEGAS (versatile gene-based association study), is applicable to all GWAS designs, including family-based GWAS, meta-analyses of GWAS on the basis of summary data, and DNA-pooling-based GWAS, where existing approaches based on permutation are not possible, as well as singleton data, where they are. The test incorporates information from a full set of markers (or a defined subset) within a gene and accounts for linkage disequilibrium between markers by using simulations from the multivariate normal distribution. We show that for an association study using singletons, our approach produces results equivalent to those obtained via permutation in a fraction of the computation time. We demonstrate proof-of-principle by using the gene-based test to replicate several genes known to be associated on the basis of results from a family-based GWAS for height in 11,536 individuals and a DNA-pooling-based GWAS for melanoma in approximately 1300 cases and controls. Our method has the potential to identify novel associated genes; provide a basis for selecting SNPs for replication; and be directly used in network (pathway) approaches that require per-gene association test statistics. We have implemented the approach in both an easy-to-use web interface, which only requires the uploading of markers with their association p-values, and a separate downloadable application.

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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.