991 resultados para Complex Traits
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The prevalence of type 2 diabetes among Australian residents is 7.5%; however, prevalence rates up to six times higher have been reported for indigenous Australian communities. Epidemiological evidence implicates genetic factors in the susceptibility of indigenous Australians to type 2 diabetes and supports the hypothesis of the thrifty genotype, but, to date, the nature of the genetic predisposition is unknown. We have ascertained clinical details from a community of indigenous Australian descent in North Stradbroke Island, Queensland. In this population, the phenotype is characterized by severe insulin resistance. We have conducted a genomewide scan, at an average resolution of 10 cM, for type 2 diabetes-susceptibility genes in a large multigeneration pedigree from this community. Parametric linkage analysis undertaken using FASTLINK version 4.1p yielded a maximum two-point LOD score of +2.97 at marker D2S2345. Multipoint analysis yielded a peak LOD score of +3.9
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The genetic basis of cardiovascular disease (CVD) with its complex etiology is still largely elusive. Plasma levels of lipids and apolipoproteins are among the major quantitative risk factors for CVD and are well-established intermediate traits that may be more accessible to genetic dissection than clinical CVD end points. Chromosome 19 harbors multiple genes that have been suggested to play a role in lipid metabolism and previous studies indicated the presence of a quantitative trait locus (QTL) for cholesterol levels in genetic isolates. To establish the relevance of genetic variation at chromosome 19 for plasma levels of lipids and apolipoproteins in the general, out-bred Caucasian population, we performed a linkage study in four independent samples, including adolescent Dutch twins and adult Dutch, Swedish and Australian twins totaling 493 dizygotic twin pairs. The average spacing of short-tandem-repeat markers was 6 - 8 cM. In the three adult twin samples, we found consistent evidence for linkage of chromosome 19 with LDL cholesterol levels ( maximum LOD scores of 4.5, 1.7 and 2.1 in the Dutch, Swedish and Australian sample, respectively); no indication for linkage was observed in the adolescent Dutch twin sample. The QTL effects in the three adult samples were not significantly different and a simultaneous analysis of the samples increased the maximum LOD score to 5.7 at 60 cM pter. Bivariate analyses indicated that the putative LDL-C QTL also contributed to the variance in ApoB levels, consistent with the high genetic correlation between these phenotypes. Our study provides strong evidence for the presence of a QTL on chromosome 19 with a major effect on LDL-C plasma levels in outbred Caucasian populations.
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Dissertação para obtenção do Grau de Doutor em Estatística e Gestão do Risco, especialidade em Estatística
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Entre los factores que contribuyen a predecir el rendimiento académico se pueden destacar aquellos que reflejan capacidades cognitivas (inteligencia, por ejemplo), y aquellas diferencias individuales consideradas como no-cognitivas (rasgos de personalidad, por ejemplo). En los últimos años, también se considera al Conocimiento General (CG) como un criterio para el éxito académico (ver Ackerman, 1997), ya que se ha evidenciado que el conocimiento previo ayuda en la adquisición de nuevo conocimiento (Hambrick & Engle, 2001). Uno de los objetivos de la psicología educacional consiste en identificar las principales variables que explican el rendimiento académico, como también proponer modelos teóricos que expliquen las relaciones existentes entre estas variables. El modelo teórico PPIK (Inteligencia-como-Proceso, Personalidad, Intereses e Inteligencia-como-Conocimiento) propuesto por Ackerman (1996) propone que el conocimiento y las destrezas adquiridas en un dominio en particular son el resultado de la dedicación de recursos cognitivos que una persona realiza durante un prolongado período de tiempo. Este modelo propone que los rasgos de personalidad, intereses individuales/vocacionales y aspectos motivacionales están integrados como rasgos complejos que determinan la dirección y la intensidad de la dedicación de recursos cognitivos sobre el aprendizaje que realiza una persona (Ackerman, 2003). En nuestro medio (Córdoba, Argentina), un grupo de investigadores ha desarrollado una serie de recursos técnicos necesarios para la evaluación de algunos de los constructos propuesto por este modelo. Sin embargo, por el momento no contamos con una medida de Conocimiento General. Por lo tanto, en el presente proyecto se propone la construcción de un instrumento para medir Conocimiento General (CG), indispensable para poder contar con una herramienta que permita establecer parámetros sobre el nivel de conocimiento de la población universitaria y para en próximos trabajos poner a prueba los postulados de la teoría PPIK (Ackerman, 1996). Between the factors that contribute to predict the academic achievement, may be featured those who reflect cognitive capacities (i.g. intelligence) and those who reflect individual differences that are considered like non-cognitive (i.g. personality traits). In the last years, also the General Knowledge has been considered like a criterion for the academic successfully (see Ackerman, 1997), since it has been shown that the previous knowledge helps in the acquisition of the new knowledge (Hambrick & Engle, 2001). An interesting theoretical model that has proposed an explanation for the academic achievement, is the PPIK (intelligence like a process, interests and inteligence like knowledge) proposed by Ackerman (1996), who argues that knowledge and the acquired skills in a particular domain are the result of the dedication of cognitive resources that a person perform during a long period of time. This model proposes that personality traits, individuals interests and motivational aspects are integrated as complex traits that determine the direction and the intensity of the dedication of cognitive resources on the learning that a person make (Ackerman, 2003). In our context, (Córdoba, Argentina), a group of researcher has developed a series of necessary technical resoures for the assesment of some of the theoretical constructs proposed by this model. However, by the moment, we do not have an instrument for evaluate the General Knowledge. Therefore, this project aims the construction of an instrument to asess General Knowledge, essential to set parameters on the knowledge level of the university population and for in next works test the PPIK theory postulates.
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Prior genome-wide association studies (GWAS) of major depressive disorder (MDD) have met with limited success. We sought to increase statistical power to detect disease loci by conducting a GWAS mega-analysis for MDD. In the MDD discovery phase, we analyzed more than 1.2 million autosomal and X chromosome single-nucleotide polymorphisms (SNPs) in 18 759 independent and unrelated subjects of recent European ancestry (9240 MDD cases and 9519 controls). In the MDD replication phase, we evaluated 554 SNPs in independent samples (6783 MDD cases and 50 695 controls). We also conducted a cross-disorder meta-analysis using 819 autosomal SNPs with P<0.0001 for either MDD or the Psychiatric GWAS Consortium bipolar disorder (BIP) mega-analysis (9238 MDD cases/8039 controls and 6998 BIP cases/7775 controls). No SNPs achieved genome-wide significance in the MDD discovery phase, the MDD replication phase or in pre-planned secondary analyses (by sex, recurrent MDD, recurrent early-onset MDD, age of onset, pre-pubertal onset MDD or typical-like MDD from a latent class analyses of the MDD criteria). In the MDD-bipolar cross-disorder analysis, 15 SNPs exceeded genome-wide significance (P<5 × 10(-8)), and all were in a 248 kb interval of high LD on 3p21.1 (chr3:52 425 083-53 822 102, minimum P=5.9 × 10(-9) at rs2535629). Although this is the largest genome-wide analysis of MDD yet conducted, its high prevalence means that the sample is still underpowered to detect genetic effects typical for complex traits. Therefore, we were unable to identify robust and replicable findings. We discuss what this means for genetic research for MDD. The 3p21.1 MDD-BIP finding should be interpreted with caution as the most significant SNP did not replicate in MDD samples, and genotyping in independent samples will be needed to resolve its status.
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Etant données la complexité et la redondance des réseaux de gènes influençant de nombreux phénotypes, l'étude des rares cas d'un locus unique ayant des effets importants sur de nombreux phénotypes peut fournir des informations cruciales sur l'évolution des traits complexes. Nous avons séquencé le génome de la fourmi de feu Solenopsis invicta pour étudier comment l'expression des gènes détermine les effets majeurs et étendus de deux loci uniques sur le phénotype. Le premier locus concerne la détermination du sexe par le modèle des allèles complémentaires. Ce locus est connu pour déterminer le sexe chez tous les hyménoptères mais n'a été caractérisé que chez les abeilles. Les hétérozygotes pour ce locus se développent en reines diploïdes (ou ouvrières stériles) alors que les homozygotes se développent en mâles diploïdes incapables de produire du sperme et les hémizygotes en mâles haploïdes fertiles. Nous avons comparé l'expression des gènes entre les reines et les deux types de mâles au stade pupe, ainsi que 1 et 11 jours après l'émergence. Nous avons trouvé un changement prononcé de l'expression des gènes chez les mâles diploïdes, passant de très proche de celle des reines au stade pupe à identique aux mâles haploïdes 11 jours après l'émergence. Cela signifie que les mâles diploïdes sont condamnés à être stériles parce que les effets après émergence du locus de détermination du sexe ne per¬mettent pas d'effacer les effets de la ploïdie sur l'expression des gènes pendant le stade pupe, quand la spermatogénèse prend place. Le second locus aux effets majeurs que nous avons étudié est le supergène dit "green beard", qui consiste en 616 gènes couvrant 55% d'un chromosome (13 Mb) et est caractérisé par une absence de recombinaison entre les deux variants du supergène : "Social B" et "Social b" (SB et Sb). Au travers de l'effet "green beard", par lequel les ouvrières avec le supergène Sb discriminent favorablement les reines qui partagent ce supergène de façon perceptible, le génotype des reines fondatrices au niveau de ce supergène détermine l'organisation de la colonie : soit elle contient une seule reine SB/SB, soit plusieurs reines SB/Sb. Nous avons montré que le chromosome Sb a évolué comme le chromosome Y, accumulant probablement des allèles favorables dans des colonies avec plusieurs reines mais défavorables dans des colonies avec une seule reine (cf. gènes sexuellement antagonistes), ainsi que des transposons et des séquences répéti¬tives. Nous avons également montré que le polymorphisme du supergène cause de grandes différences d'expression chez les ouvrières et particulièrement les reines mais pas chez les mâles. Pour comprendre comment le polymorphisme du supergène chez les reines peut affecter l'organisation de la colonie, nous avons comparé l'expression entre les génotypes SB/SB et SB/Sb chez des reines vierges (1 et 11 jours) et des reines matures. Nous avons montré que les reines SB/SB sur-régulent des gènes impliqués dans la reproduction, expli-quant pourquoi elle grandissent plus rapidement et peuvent fonder des colonies de façon indépendante, tandis que les reines SB/Sb (qui ne peuvent fonder une nouvelle colonie) sur-régulent des gènes de signalement chimique qui affectent l'organisation des colonies par l'effet "green beard". - Given the complexity and redundancy of the gene networks that underlie many pheno- types, the study of rare cases of a single locus having major effects on many phenotypes can give powerful insights into the evolution of complex traits. We sequenced the genome of Solenopsis invicta fire ants to study how gene expression mediates the widespread major effects of two single loci on phenotype. The first is the complementary sex-determining locus, which is known to exist in most Hymenoptera despite being characterized only for honeybees. Heterozygotes at this locus become diploid queens (or sterile workers), homozy¬gotes become aspermic diploid males, and hemizygotes become fertile haploid males. We compared gene expression between queens and both types of males in pupae and 1 and 11 days after eclosion. We found a pronounced shift in gene expression in diploid males, from being nearly identical to queens as pupae to identical to haploid males 11 days after eclosion. This means that diploid males are condemned to sterility because the overriding effects of the sex locus after eclosion cannot undo the ploidy effects on expression during the pupal stage, when spermatogenesis must be completed. The second locus with major ef¬fects that we studied was the so-called "green beard" supergene, which consists of 616 genes encompassing 55% of one chromosome (13 Mb), without recombination between the two variants "Social B" and "Social b" (SB and Sb) supergene. Through the green beard effect, i.e. workers with the Sb supergene discriminating in favor of queens who perceptibly share this supergene, the founding queen's genotype at the supergene determines colony organi¬zation: either headed by a single SB/SB queen or many SB/Sb queens. We show that the Sb chromosome evolved like a Y-chromosome, probably accumulating alleles beneficial in multi-queen colonies but disadvantageous in single-queen colonies (cf. sexually antagonistic genes), as well as transposons and repetitive sequences. We also show that the polymor¬phism of the supergene causes widespread expression differences in workers and especially queens but not in males. To understand how the polymorphism at the supergene in queen can transform colony organization, we compared the expression between SB/SB and SB/Sb virgin queens (1 and 11 days) and mother queens. We show that SB/SB queens up-regulate genes involved in reproduction, explaining why they mature faster and can found colonies independently, while SB/Sb queens (which cannot found colonies) up-regulate chemical signaling genes that can transform colonies through the green beard effect.
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The extensive variability of individual human genomes contributes to phenotypic variability. Structural genomic variants, and copy number variants (CNVs) in particular, have recently been rediscovered as contributors to the genomic plasticity and evolution and as pathoetiologic elements for both monogenic and complex traits. Herein we review some of the consequences of CNVs in the context of human inherited diseases.
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Obesity has become a major worldwide challenge to public health, owing to an interaction between the Western 'obesogenic' environment and a strong genetic contribution. Recent extensive genome-wide association studies (GWASs) have identified numerous single nucleotide polymorphisms associated with obesity, but these loci together account for only a small fraction of the known heritable component. Thus, the 'common disease, common variant' hypothesis is increasingly coming under challenge. Here we report a highly penetrant form of obesity, initially observed in 31 subjects who were heterozygous for deletions of at least 593 kilobases at 16p11.2 and whose ascertainment included cognitive deficits. Nineteen similar deletions were identified from GWAS data in 16,053 individuals from eight European cohorts. These deletions were absent from healthy non-obese controls and accounted for 0.7% of our morbid obesity cases (body mass index (BMI) >or= 40 kg m(-2) or BMI standard deviation score >or= 4; P = 6.4 x 10(-8), odds ratio 43.0), demonstrating the potential importance in common disease of rare variants with strong effects. This highlights a promising strategy for identifying missing heritability in obesity and other complex traits: cohorts with extreme phenotypes are likely to be enriched for rare variants, thereby improving power for their discovery. Subsequent analysis of the loci so identified may well reveal additional rare variants that further contribute to the missing heritability, as recently reported for SIM1 (ref. 3). The most productive approach may therefore be to combine the 'power of the extreme' in small, well-phenotyped cohorts, with targeted follow-up in case-control and population cohorts.
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Nowadays, genome-wide association studies (GWAS) and genomic selection (GS) methods which use genome-wide marker data for phenotype prediction are of much potential interest in plant breeding. However, to our knowledge, no studies have been performed yet on the predictive ability of these methods for structured traits when using training populations with high levels of genetic diversity. Such an example of a highly heterozygous, perennial species is grapevine. The present study compares the accuracy of models based on GWAS or GS alone, or in combination, for predicting simple or complex traits, linked or not with population structure. In order to explore the relevance of these methods in this context, we performed simulations using approx 90,000 SNPs on a population of 3,000 individuals structured into three groups and corresponding to published diversity grapevine data. To estimate the parameters of the prediction models, we defined four training populations of 1,000 individuals, corresponding to these three groups and a core collection. Finally, to estimate the accuracy of the models, we also simulated four breeding populations of 200 individuals. Although prediction accuracy was low when breeding populations were too distant from the training populations, high accuracy levels were obtained using the sole core-collection as training population. The highest prediction accuracy was obtained (up to 0.9) using the combined GWAS-GS model. We thus recommend using the combined prediction model and a core-collection as training population for grapevine breeding or for other important economic crops with the same characteristics.
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Sphingomonas wittichii RW1 is a dibenzofuran and dibenzodioxin-degrading bacterium with potentially interesting properties for bioaugmentation of contaminated sites. In order to understand the capacity of the microorganism to survive in the environment we used a genome-wide transposon scanning approach. RW1 transposon libraries were generated with around 22 000 independent insertions. Libraries were grown for an average of 50 generations (five successive passages in batch liquid medium) with salicylate as sole carbon and energy source in presence or absence of salt stress at -1.5 MPa. Alternatively, libraries were grown in sand with salicylate, at 50% water holding capacity, for 4 and 10 days (equivalent to 7 generations). Library DNA was recovered from the different growth conditions and scanned by ultrahigh throughput sequencing for the positions and numbers of inserted transposed kanamycin resistance gene. No transposon reads were recovered in 579 genes (10% of all annotated genes in the RW1 genome) in any of the libraries, suggesting those to be essential for survival under the used conditions. Libraries recovered from sand differed strongly from those incubated in liquid batch medium. In particular, important functions for survival of cells in sand at the short term concerned nutrient scavenging, energy metabolism and motility. In contrast to this, fatty acid metabolism and oxidative stress response were essential for longer term survival of cells in sand. Comparison to transcriptome data suggested important functions in sand for flagellar movement, pili synthesis, trehalose and polysaccharide synthesis and putative cell surface antigen proteins. Interestingly, a variety of genes were also identified, interruption of which cause significant increase in fitness during growth on salicylate. One of these was an Lrp family transcription regulator and mutants in this gene covered more than 90% of the total library after 50 generations of growth on salicylate. Our results demonstrate the power of genome-wide transposon scanning approaches for analysis of complex traits.
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Many common genetic variants identified by genome-wide association studies for complex traits map to genes previously linked to rare inherited Mendelian disorders. A systematic analysis of common single-nucleotide polymorphisms (SNPs) in genes responsible for Mendelian diseases with kidney phenotypes has not been performed. We thus developed a comprehensive database of genes for Mendelian kidney conditions and evaluated the association between common genetic variants within these genes and kidney function in the general population. Using the Online Mendelian Inheritance in Man database, we identified 731 unique disease entries related to specific renal search terms and confirmed a kidney phenotype in 218 of these entries, corresponding to mutations in 258 genes. We interrogated common SNPs (minor allele frequency >5%) within these genes for association with the estimated GFR in 74,354 European-ancestry participants from the CKDGen Consortium. However, the top four candidate SNPs (rs6433115 at LRP2, rs1050700 at TSC1, rs249942 at PALB2, and rs9827843 at ROBO2) did not achieve significance in a stage 2 meta-analysis performed in 56,246 additional independent individuals, indicating that these common SNPs are not associated with estimated GFR. The effect of less common or rare variants in these genes on kidney function in the general population and disease-specific cohorts requires further research.
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Genome-wide association studies have been instrumental in identifying genetic variants associated with complex traits such as human disease or gene expression phenotypes. It has been proposed that extending existing analysis methods by considering interactions between pairs of loci may uncover additional genetic effects. However, the large number of possible two-marker tests presents significant computational and statistical challenges. Although several strategies to detect epistasis effects have been proposed and tested for specific phenotypes, so far there has been no systematic attempt to compare their performance using real data. We made use of thousands of gene expression traits from linkage and eQTL studies, to compare the performance of different strategies. We found that using information from marginal associations between markers and phenotypes to detect epistatic effects yielded a lower false discovery rate (FDR) than a strategy solely using biological annotation in yeast, whereas results from human data were inconclusive. For future studies whose aim is to discover epistatic effects, we recommend incorporating information about marginal associations between SNPs and phenotypes instead of relying solely on biological annotation. Improved methods to discover epistatic effects will result in a more complete understanding of complex genetic effects.
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BACKGROUND: Genotypes obtained with commercial SNP arrays have been extensively used in many large case-control or population-based cohorts for SNP-based genome-wide association studies for a multitude of traits. Yet, these genotypes capture only a small fraction of the variance of the studied traits. Genomic structural variants (GSV) such as Copy Number Variation (CNV) may account for part of the missing heritability, but their comprehensive detection requires either next-generation arrays or sequencing. Sophisticated algorithms that infer CNVs by combining the intensities from SNP-probes for the two alleles can already be used to extract a partial view of such GSV from existing data sets. RESULTS: Here we present several advances to facilitate the latter approach. First, we introduce a novel CNV detection method based on a Gaussian Mixture Model. Second, we propose a new algorithm, PCA merge, for combining copy-number profiles from many individuals into consensus regions. We applied both our new methods as well as existing ones to data from 5612 individuals from the CoLaus study who were genotyped on Affymetrix 500K arrays. We developed a number of procedures in order to evaluate the performance of the different methods. This includes comparison with previously published CNVs as well as using a replication sample of 239 individuals, genotyped with Illumina 550K arrays. We also established a new evaluation procedure that employs the fact that related individuals are expected to share their CNVs more frequently than randomly selected individuals. The ability to detect both rare and common CNVs provides a valuable resource that will facilitate association studies exploring potential phenotypic associations with CNVs. CONCLUSION: Our new methodologies for CNV detection and their evaluation will help in extracting additional information from the large amount of SNP-genotyping data on various cohorts and use this to explore structural variants and their impact on complex traits.
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There is evidence across several species for genetic control of phenotypic variation of complex traits, 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), 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 BMI, possibly mediated by DNA methylation. 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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Hypertension and chronic kidney disease (CKD) are complex traits representing major global health problems. Multiple genome-wide association studies have identified common variants in the promoter of the UMOD gene, which encodes uromodulin, the major protein secreted in normal urine, that cause independent susceptibility to CKD and hypertension. Despite compelling genetic evidence for the association between UMOD risk variants and disease susceptibility in the general population, the underlying biological mechanism is not understood. Here, we demonstrate that UMOD risk variants increased UMOD expression in vitro and in vivo. Uromodulin overexpression in transgenic mice led to salt-sensitive hypertension and to the presence of age-dependent renal lesions similar to those observed in elderly individuals homozygous for UMOD promoter risk variants. The link between uromodulin and hypertension is due to activation of the renal sodium cotransporter NKCC2. We demonstrated the relevance of this mechanism in humans by showing that pharmacological inhibition of NKCC2 was more effective in lowering blood pressure in hypertensive patients who are homozygous for UMOD promoter risk variants than in other hypertensive patients. Our findings link genetic susceptibility to hypertension and CKD to the level of uromodulin expression and uromodulin's effect on salt reabsorption in the kidney. These findings point to uromodulin as a therapeutic target for lowering blood pressure and preserving renal function.