985 resultados para genetic epidemiology


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Genetic association analyses of family-based studies with ordered categorical phenotypes are often conducted using methods either for quantitative or for binary traits, which can lead to suboptimal analyses. Here we present an alternative likelihood-based method of analysis for single nucleotide polymorphism (SNP) genotypes and ordered categorical phenotypes in nuclear families of any size. Our approach, which extends our previous work for binary phenotypes, permits straightforward inclusion of covariate, gene-gene and gene-covariate interaction terms in the likelihood, incorporates a simple model for ascertainment and allows for family-specific effects in the hypothesis test. Additionally, our method produces interpretable parameter estimates and valid confidence intervals. We assess the proposed method using simulated data, and apply it to a polymorphism in the c-reactive protein (CRP) gene typed in families collected to investigate human systemic lupus erythematosus. By including sex interactions in the analysis, we show that the polymorphism is associated with anti-nuclear autoantibody (ANA) production in females, while there appears to be no effect in males.

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Analyses of high-density single-nucleotide polymorphism (SNP) data, such as genetic mapping and linkage disequilibrium (LD) studies, require phase-known haplotypes to allow for the correlation between tightly linked loci. However, current SNP genotyping technology cannot determine phase, which must be inferred statistically. In this paper, we present a new Bayesian Markov chain Monte Carlo (MCMC) algorithm for population haplotype frequency estimation, particulary in the context of LD assessment. The novel feature of the method is the incorporation of a log-linear prior model for population haplotype frequencies. We present simulations to suggest that 1) the log-linear prior model is more appropriate than the standard coalescent process in the presence of recombination (>0.02cM between adjacent loci), and 2) there is substantial inflation in measures of LD obtained by a "two-stage" approach to the analysis by treating the "best" haplotype configuration as correct, without regard to uncertainty in the recombination process. Genet Epidemiol 25:106-114, 2003. (C) 2003 Wiley-Liss, Inc.

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Objective: The VNTR polymorphism 5' of the insulin gene has been related to obesity in a previous study on children with early onset of severe obesity. Our purpose was to analyze the association between this polymorphism and adiposity variability in an unselected population of children and adolescents in northern France.

Research Methods and Procedures: In 293 nuclear families from the Fleurbaix Laventie Ville Santé study, we genotyped the INS VNTR polymorphism in 431 children and adolescents (8 to 18 years of age) and their parents. Overweight was defined according to the international definition in both children and adults. A transmission disequilibrium test in families with an overweight offspring was performed. The prevalence of overweight was compared according to genotype. The effect of the genotype on BMI and waist circumference was tested with a linear regression model, adjusting for age, gender, and Tanner stage.

Results: There was an undertransmission of class III alleles from heterozygous parents to their overweight offspring (p < 0.002). Overweight was associated with class I alleles in children and adolescents (12% I/I, I/III vs. 3% III/III; p < 0.08). Those with a class III/III genotype had a 1 kg/m2 lower mean BMI (p = 0.04) and 3 cm lower waist circumference (p = 0.02) than those bearing one or two class I alleles. No association of adiposity or obesity with class I alleles was found in parents.

Discussion: INS VNTR polymorphism seems to contribute to differences in adiposity level in the general population of children and adolescents.

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Background: The evaluation of associations between genotypes and diseases in a case-control framework plays an important role in genetic epidemiology. This paper focuses on the evaluation of the homogeneity of both genotypic and allelic frequencies. The traditional test that is used to check allelic homogeneity is known to be valid only under Hardy-Weinberg equilibrium, a property that may not hold in practice. Results: We first describe the flaws of the traditional (chi-squared) tests for both allelic and genotypic homogeneity. Besides the known problem of the allelic procedure, we show that whenever these tests are used, an incoherence may arise: sometimes the genotypic homogeneity hypothesis is not rejected, but the allelic hypothesis is. As we argue, this is logically impossible. Some methods that were recently proposed implicitly rely on the idea that this does not happen. In an attempt to correct this incoherence, we describe an alternative frequentist approach that is appropriate even when Hardy-Weinberg equilibrium does not hold. It is then shown that the problem remains and is intrinsic of frequentist procedures. Finally, we introduce the Full Bayesian Significance Test to test both hypotheses and prove that the incoherence cannot happen with these new tests. To illustrate this, all five tests are applied to real and simulated datasets. Using the celebrated power analysis, we show that the Bayesian method is comparable to the frequentist one and has the advantage of being coherent. Conclusions: Contrary to more traditional approaches, the Full Bayesian Significance Test for association studies provides a simple, coherent and powerful tool for detecting associations.

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The present study aimed to investigate the association of endothelial nitric oxide synthase (eNOS) gene polymorphisms with primary open angle glaucoma (POAG). We conducted a case-control study that included 90 patients with POAG and 127 healthy controls whose blood samples were genotyped for the functional polymorphisms T-786C and Glu298Asp of the eNOS gene by Taqman fluorescent allelic discrimination assay. The T-786C polymorphism was significantly associated as a risk factor for POAG among women (OR: 228; 95% CI: 1.11 to 4.70, p = 0.024) and marginally associated to the risk of POAG in the patients >= 52 years of age at diagnosis (OR: 2.11; 95% CI: 0.98 to 4.55, p = 0,055). However, these results was not confirmed after adjustments for gender, age, self-declared skin color, tobacco smoking and eNOS genotypes by multivariate logistic regression model (OR: 2.08; 95% CI: 0.87 to 5.01, p = 0.101 and OR: 2.20; 95% CI: 0.95 to 5.12, p = 0.067, respectively). The haplotype CG of T-786C and Glu298Asp showed a borderline association with risk of POAG in the overall analysis (OR: 1.76; 95% CI: 0.98 to 3.14, p = 0.055) and among women (OR: 2.02; 95% CI: 0.98 to 4.16, p = 0.052). Furthermore, the CG haplotype was significantly associated with the development of POAG for the age at diagnosis group >= 52 years (OR: 3.48; 95% CI: 1.54 to 7.84, p = 0.002). We suggested that haplotypes of the polymorphisms T-786C and Glu298Asp of eNOS may interact with gender and age in modulating the risk of POAG. (C) 2012 Elsevier B.V. All rights reserved.

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Background Studies have suggested that asthma in obese individuals differs from the classic asthma phenotype, presenting as a disease that is more difficult to control. Objective The objective of the present study was to determine whether obesity, age or a combination of the two are associated with worse spirometry parameters in patients with asthma. Methods This was an observational cross-sectional study involving patients over 18 years of age who had been diagnosed with asthma (allergic or nonallergic). We evaluated the results of their spirometric tests. The patients were classified in accordance with two criteria: body mass index (BMI) and age. Based on their BMIs, the patients were divided into three groups: normal weight, overweight and obese. Patients were also separated into two categories by age: 18-59 years of age; and >= 60 years of age. Results We evaluated 451 patients with asthma and their spirometry tests. In the present study, the pulmonary function parameters were negatively correlated with BMI and age (P < 0.05). We found that there was a statistically significant correlation between spirometric values and BMI among patients 18-59 years of age (P < 0.001), however, among patients over 60, we did not observe this negative association. Conclusions and Clinical Relevance The spirometric values decreased significantly in proportion to the increase of BMI and age in patients with asthma, especially among young adults. There was no negative correlation between BMI and FEV1 in the group >= 60 years of age, suggesting that perhaps the time of disease is a major factor in the loss of lung function than weight gain in the elderly.

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BACKGROUND Blood pressure (BP) is known to aggregate in families. Yet, heritability estimates are population-specific and no Swiss data have been published so far. We estimated the heritability of ambulatory and office BP in a Swiss population-based sample. METHODS The Swiss Kidney Project on Genes in Hypertension is a population-based family study focusing on BP genetics. Office and ambulatory BP were measured in 1009 individuals from 271 nuclear families. Heritability was estimated for SBP, DBP, and pulse pressure using a maximum likelihood method implanted in the Statistical Analysis in Genetic Epidemiology software. RESULTS The 518 women and 491 men included in this analysis had a mean (±SD) age of 48.3 (±17.4) and 47.3 (±17.7) years, and a mean BMI of 23.8 (±4.2) and 25.9 (±4.1) kg/m, respectively. Narrow-sense heritability estimates (±standard error) for ambulatory SBP, DBP, and pulse pressure were 0.37 ± 0.07, 0.26 ± 0.07, and 0.29 ± 0.07 for 24-h BP; 0.39 ± 0.07, 0.28 ± 0.07, and 0.27 ± 0.07 for day BP; and 0.25 ± 0.07, 0.20 ± 0.07, and 0.30 ± 0.07 for night BP, respectively (all P < 0.001). Heritability estimates for office SBP, DBP, and pulse pressure were 0.21 ± 0.08, 0.25 ± 0.08, and 0.18 ± 0.07 (all P < 0.01). CONCLUSIONS We found significant heritability estimates for both ambulatory and office BP in this Swiss population-based study. Our findings justify the ongoing search for the genetic determinants of BP.

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Hypertension is usually defined as having values of systolic blood pressure ≥140 mmHg, diastolic blood pressure ≥90 mmHg. Hypertension is one of the main adverse effects of glucocorticoid on the cardiovascular system. Glucocorticoids are essential hormones, secreted from adrenal glands in circadian fashion. Glucocorticoid's effect on blood pressure is conveyed by the glucocorticoid receptor (NR3C1), an omnipresent nuclear transcription factor. Although polymorphisms in this gene have long been implicated to be a causal factor for cardiovascular diseases such as hypertension, no study has yet thoroughly interrogated the gene's polymorphisms for their effect on blood pressure levels. Therefore, I have first resequenced ∼30 kb of the gene, encompassing all exons, promoter regions, 5'/3' UTRs as well as at least 1.5 kb of the gene's flanking regions from 114 chromosome 5 monosomic cell lines, comprised of three major American ethnic groups—European American, African American and Mexican American. I observed 115 polymorphisms and 14 common molecularly phased haplotypes. A subset of markers was chosen for genotyping study populations of GENOA (Genetic Epidemiology Network of Atherosclerosis; 1022 non-Hispanic whites, 1228 African Americans and 954 Mexican Americans). Since these study populations include sibships, the family-based association test was performed on 4 blood pressure-related quantitative variables—pulse, systolic blood pressure, diastolic blood pressure and mean arterial pressure. Using these analyses, multiple correlated SNPs are significantly protective against high systolic blood pressure in non-Hispanic whites, which includes rsb198, a SNP formerly associated with beneficial body compositions. Haplotype association analysis also supports this finding and all p-values remained significant after permutation tests. I therefore conclude that multiple correlated SNPs on the gene may confer protection against high blood pressure in non-Hispanic whites. ^

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The central problem of complex inheritance is to map oligogenes for disease susceptibility, integrating linkage and association over samples that differ in several ways. Combination of evidence over multiple samples with 1,037 families supports loci contributing to asthma susceptibility in the cytokine region on 5q [maximum logarithm of odds (lod) = 2.61 near IL-4], but no evidence for atopy. The principal problems with retrospective collaboration on linkage appear to have been solved, providing far more information than a single study. A multipoint lod table evaluated at commonly agreed reference loci is required for both collaboration and metaanalysis, but variations in ascertainment, pedigree structure, phenotype definition, and marker selection are tolerated. These methods are invariant with statistical methods that increase the power of lods and are applicable to all diseases, motivating collaboration rather than competition. In contrast to linkage, positional cloning by allelic association has yet to be extended to multiple samples, a prerequisite for efficient combination with linkage and the greatest current challenge to genetic epidemiology.

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Categorical models dominate the eating disorder field, but the tandem use of categorical and dimensional models has been proposed. A transdiagnostic dimensional model, number of lifetime eating disorder behaviors (LEDB), was examined with respect to (1) its relationship to a variety of indicators of the individual's functioning, (2) the degree to which it was influenced by genetic and environmental risk factors, and (3) exposure to specific environmental risk factors. Data from self-report and interview from 1002 female twins (mean age = 34.91 years, SD = 2.09) were examined. While 15.4% women met criteria for a lifetime eating disorder, 29% had at least one LEDB. The dimensional measure provided an indicator of associated functioning, and was influenced primarily by the nonshared environment. The number of LEDB was associated with the degree of impaired functioning. This impairment was associated with conflict between parents and criticism from parents when growing up.

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Background The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results We show that GPNN has high power to detect even relatively small genetic effects (2–3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (

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Despite the success of extensive control measures that have been implemented in China for over 50 years, the number of individuals infected with Schistosoma japonicum remains high in the existing endemic areas. A variance components analysis was undertaken to estimate the heritable and environmental components that contribute to S. japonicum infection in the Poyang Lake region of Jiangxi Province, PR China. The total target population was 3148 from four separate administrative villages. Two thousand seven hundred and five of these comprised 400 families ranging in size from 3 to 188. After adjustments were made for gender, water contact and past history of having had schistosomiasis, the heritable component was estimated to account for as much as 58% of the phenotype variation under the polygenic model. Household was not shown to be an important environmental factor. Incorporating village effects indicated that the results were valid for the total population. We conclude that genetic heritability in this region is high and plays an important role in determining risk of infection with S. japonicum. (c) 2005 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

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Background: The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results: We show that GPNN has high power to detect even relatively small genetic effects (2-3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (

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Scavenger receptor BI (SR-BI) is the major receptor for high-density lipoprotein (HDL)
cholesterol (HDL-C). In humans, high amounts of HDL-C in plasma are associated with a
lower risk of coronary heart disease (CHD). Mice that have depleted Scarb1 (SR-BI
knockout mice) have markedly elevated HDL-C levels but, paradoxically, increased
atherosclerosis. The impact of SR-BI on HDL metabolism and CHD risk in humans remains
unclear. Through targeted sequencing of coding regions of lipid-modifying genes in 328
individuals with extremely high plasma HDL-C levels, we identified a homozygote for a lossof-function
variant, in which leucine replaces proline 376 (P376L), in SCARB1, the gene
encoding SR-BI. The P376L variant impairs posttranslational processing of SR-BI and
abrogates selective HDL cholesterol uptake in transfected cells, in hepatocyte-like cells
derived from induced pluripotent stem cells from the homozygous subject, and in mice.
Large population-based studies revealed that subjects who are heterozygous carriers of
the P376L variant have significantly increased levels of plasma HDL-C. P376L carriers have
a profound HDL-related phenotype and an increased risk of CHD (odds ratio = 1.79, which is
statistically significant).

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Background The HCL-32 is a widely-used screening questionnaire for hypomania. We aimed to use a Rasch analysis approach to (i) evaluate the measurement properties, principally unidimensionality, of the HCL-32, and (ii) generate a score table to allow researchers to convert raw HCL-32 scores into an interval-level measurement which will be more appropriate for statistical analyses. Methods Subjects were part of the Bipolar Disorder Research Network (BDRN) study with DSM-IV bipolar disorder (n=389). Multidimensionality was assessed using the Rasch fit statistics and principle components analysis of the residuals (PCA). Item invariance (differential item functioning, DIF) was tested for gender, bipolar diagnosis and current mental state. Item estimates and reliabilities were calculated. Results Three items (29, 30, 32) had unacceptable fit to the Rasch unidimensional model. Item 14 displayed significant DIF for gender and items 8 and 17 for current mental state. Item estimates confirmed that not all items measure hypomania equally. Limitations This sample was recruited as part of a large ongoing genetic epidemiology study of bipolar disorder and may not be fully representative of the broader clinical population of individuals with bipolar disorder. Conclusion The HCL-32 is unidimensional in practice, but measurements may be further strengthened by the removal of four items. Re-scored linear measurements may be more appropriate for clinical research.