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True Association (true + association)
Selected AbstractsCentralizing the non-central chi-square: a new method to correct for population stratification in genetic case-control association studiesGENETIC EPIDEMIOLOGY, Issue 4 2006Prakash Gorroochurn Abstract We present a new method, the ,-centralization (DC) method, to correct for population stratification (PS) in case-control association studies. DC works well even when there is a lot of confounding due to PS. The latter causes overdispersion in the usual chi-square statistics which then have non-central chi-square distributions. Other methods approach the non-centrality indirectly, but we deal with it directly, by estimating the non-centrality parameter , itself. Specifically: (1) We define a quantity ,, a function of the relevant subpopulation parameters. We show that, for relatively large samples, , exactly predicts the elevation of the false positive rate due to PS, when there is no true association between marker genotype and disease. (This quantity , is quite different from Wright's FST and can be large even when FST is small.) (2) We show how to estimate ,, using a panel of unlinked "neutral" loci. (3) We then show that ,2 corresponds to , the non-centrality parameter of the chi-square distribution. Thus, we can centralize the chi-square using our estimate of ,; this is the DC method. (4) We demonstrate, via computer simulations, that DC works well with as few as 25,30 unlinked markers, where the markers are chosen to have allele frequencies reasonably close (within ±.1) to those at the test locus. (5) We compare DC with genomic control and show that where as the latter becomes overconservative when there is considerable confounding due to PS (i.e. when , is large), DC performs well for all values of ,. Genet. Epidemiol. 2006. © 2006 Wiley-Liss, Inc. [source] Low specificity of anti-tissue transglutaminase antibodies in patients with primary biliary cirrhosisJOURNAL OF CLINICAL LABORATORY ANALYSIS, Issue 5 2006N. Bizzaro Abstract The association between celiac disease (CD) and primary biliary cirrhosis (PBC) is well documented in medical literature; however, a high frequency of false positive results of the anti-transglutaminase (anti-tTG) test has been reported in patients with PBC. To verify if the positive results for anti-tTG autoantibody are false positives due to cross reactivity with mitochondrial antigens, we studied 105 adult patients affected with PBC, positive for anti-mitochondrial M2 antibodies. Anti-tTG IgA antibodies were studied by using six different immunoenzymatic assays that employ the tTG antigen obtained from different sources (human recombinant, placenta, red blood cells, and guinea pig liver). On the whole, 28 out of 105 PBC subjects tested positive for anti-tTG IgA antibodies, but only two were eventually found to be affected by CD; the other 26 were shown to be false positive. The specificity of the various antigenic substrates ranged from 88.5% of the human erythrocytes tTG to 97.1% of the human recombinant tTG. The results of this study showed that a true association between PBC and CD was present in only 2% of the patients and that, in most cases, the false positive results were attributable to the type of substrate utilized in the assay. J. Clin. Lab. Anal. 20:184,189, 2006. © 2006 Wiley-Liss, Inc. [source] Methylphenidate use in children and risk of cancer at 18 sites: results of surveillance analyses,PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, Issue 12 2007Nina Oestreicher PhD Abstract Purpose A recent report linked methylphenidate (MPH) use in children to cytologic abnormalities in plasma lymphocytes, a possible cancer biomarker. The purpose of this study was to investigate the association of MPH use and childhood cancer risk. Methods Using automated pharmacy databases and the SEER-affiliated cancer registry of the Kaiser Permanente Medical Care Program (KPMCP), we compared cancer rates at 18 sites among 35 400 MPH users who received it before age 20 to rates among KPMCP membership (age, sex, and calendar year standardized). Medical records of MPH exposed cancer cases were reviewed to identify the presence of established risk factors. Results There were 23 cancers among MPH users, versus 20.4 expected (standardized morbidity ratio, SMR,=,1.13, 95% confidence interval (0.72, 1.70)). Given the small number of cancers, site-specific SMR estimates were imprecise. Only one SMR was statistically significant at the p,<,0.05 level, which given the number of comparisons is consistent with the absence of a true association at any site. MPH use was associated with increased risk of lymphocytic leukemia (SMR,=,2.64 (1.14, 5.20)), based on eight observed cases). The medical records of these exposed cases did not reveal any lymphocytic leukemia risk factors (prior cancer, radiotherapy or chemotherapy, or Down syndrome). Conclusions Our results are consistent with no moderate or strong association between MPH use and cancer risk in children, although our ability to examine dose and duration of use or risk at specific sites was limited by small numbers. Further study of MPH use and lymphocytic leukemia risk is needed to determine whether our results are due to chance alone. Copyright © 2007 John Wiley & Sons, Ltd. [source] Evaluating the Ability of Tree-Based Methods and Logistic Regression for the Detection of SNP-SNP InteractionANNALS OF HUMAN GENETICS, Issue 3 2009M. García-Magariños Summary Most common human diseases are likely to have complex etiologies. Methods of analysis that allow for the phenomenon of epistasis are of growing interest in the genetic dissection of complex diseases. By allowing for epistatic interactions between potential disease loci, we may succeed in identifying genetic variants that might otherwise have remained undetected. Here we aimed to analyze the ability of logistic regression (LR) and two tree-based supervised learning methods, classification and regression trees (CART) and random forest (RF), to detect epistasis. Multifactor-dimensionality reduction (MDR) was also used for comparison. Our approach involves first the simulation of datasets of autosomal biallelic unphased and unlinked single nucleotide polymorphisms (SNPs), each containing a two-loci interaction (causal SNPs) and 98 ,noise' SNPs. We modelled interactions under different scenarios of sample size, missing data, minor allele frequencies (MAF) and several penetrance models: three involving both (indistinguishable) marginal effects and interaction, and two simulating pure interaction effects. In total, we have simulated 99 different scenarios. Although CART, RF, and LR yield similar results in terms of detection of true association, CART and RF perform better than LR with respect to classification error. MAF, penetrance model, and sample size are greater determining factors than percentage of missing data in the ability of the different techniques to detect true association. In pure interaction models, only RF detects association. In conclusion, tree-based methods and LR are important statistical tools for the detection of unknown interactions among true risk-associated SNPs with marginal effects and in the presence of a significant number of noise SNPs. In pure interaction models, RF performs reasonably well in the presence of large sample sizes and low percentages of missing data. However, when the study design is suboptimal (unfavourable to detect interaction in terms of e.g. sample size and MAF) there is a high chance of detecting false, spurious associations. [source] Improving Power for Testing Genetic Association in Case,Control Studies by Reducing the Alternative SpaceBIOMETRICS, Issue 1 2010Jungnam Joo Summary To detect association between a genetic marker and a disease in case,control studies, the Cochran,Armitage trend test is typically used. The trend test is locally optimal when the genetic model is correctly specified. However, in practice, the underlying genetic model, and hence the optimal trend test, are usually unknown. In this case, Pearson's chi-squared test, the maximum of three trend test statistics (optimal for the recessive, additive, and dominant models), and the test based on genetic model selection (GMS) are useful. In this article, we first modify the existing GMS method so that it can be used when the risk allele is unknown. Then we propose a new approach by excluding a genetic model that is not supported by the data. Using either the model selection or exclusion, the alternative space is reduced conditional on the observed data, and hence the power to detect a true association can be increased. Simulation results are reported and the proposed methods are applied to the genetic markers identified from the genome-wide association studies conducted by the Wellcome Trust Case,Control Consortium. The results demonstrate that the genetic model exclusion approach usually performs better than existing methods under its worst situation across scientifically plausible genetic models we considered. [source] Dermatomyositis with the features of inclusion body myositis associated with carcinoma of the bladder: a true association?BRITISH JOURNAL OF DERMATOLOGY, Issue 3 2000J.M. Grau No abstract is available for this article. [source] | |||||||||||||