References of "Lange, C"
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See detailReprint of: Policy decisions on endocrine disruptors should be based on science across disciplines: A response to Dietrich, et al.
Gore, A. C.; Balthazart, Jacques ULg; Bikle, D. et al

in Frontiers in neuroendocrinology (2014), 35(1), 2-5

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See detailGenomic screening in family-based association testing and the multiple testing problem
Van Steen, Kristel ULg; McQueen, M. B.; Herbert, A. et al

in Genetic Epidemiology. Supplement (2005), 28

The Human Genome Project and its spin- offs are making it increasingly feasible to determine the genetic basis of complex traits using genome- wide association studies. The statistical challenge of ... [more ▼]

The Human Genome Project and its spin- offs are making it increasingly feasible to determine the genetic basis of complex traits using genome- wide association studies. The statistical challenge of analyzing such studies stems from the severe multiple-comparison problem resulting from the analysis of thousands of SNPs. Our methodology for genome- wide family- based association studies, using single SNPs or haplotypes, can identify associations that achieve genome- wide significance. In relation to developing guidelines for our screening tools, we determined lower bounds for the estimated power to detect the gene underlying the disease- susceptibility locus, which hold regardless of the linkage disequilibrium structure present in the data. We also assessed the power of our approach in the presence of multiple disease- susceptibility loci. Our screening tools accommodate genomic control and use the concept of haplotype- tagging SNPs. Our methods use the entire sample and do not require separate screening and validation samples to establish genome- wide significance, as population- based designs do. [less ▲]

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See detailPaternal history of asthma and airway responsiveness in children with asthma
Raby, B. A.; Van Steen, Kristel ULg; Celedon, J. C. et al

in American Journal of Respiratory & Critical Care Medicine (2005), 172(5), 552-8

RATIONALE: Little is known regarding the relationship between parental history of asthma and subsequent airway hyperresponsiveness (AHR) in children with asthma. OBJECTIVES: We evaluated this relationship ... [more ▼]

RATIONALE: Little is known regarding the relationship between parental history of asthma and subsequent airway hyperresponsiveness (AHR) in children with asthma. OBJECTIVES: We evaluated this relationship in 1,041 children with asthma participating in a randomized trial of antiinflammatory medications (the Childhood Asthma Management Program [CAMP]). METHODS: Methacholine challenge testing was performed before treatment randomization and once per year over an average of 4.5 years postrandomization. Cross-sectional and longitudinal repeated measures analyses were performed to model the relationship between PC20 (the methacholine concentration causing a 20% fall in FEV1) with maternal, paternal, and joint parental histories of asthma. Models were adjusted for potential confounders. MEASUREMENTS AND MAIN RESULTS: At baseline, AHR was strongly associated with a paternal history of asthma. Children with a paternal history of asthma demonstrated significantly greater AHR than those without such history (median log(e)PC20, 0.84 vs. 1.13; p = 0.006). Although maternal history of asthma was not associated with AHR, children with two parents with asthma had greater AHR than those with no parents with asthma (median log(e)PC20, 0.52 vs. 1.17; p = 0.0008). Longitudinal multivariate analysis of the relation between paternal history of asthma and AHR using repeated PC20 measurements over 44 months postrandomization confirmed a significant association between paternal history of asthma and AHR among children in CAMP. CONCLUSIONS: Our findings suggest that the genetic contribution of the father is associated with AHR, an important determinant of disease severity among children with asthma. [less ▲]

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See detailPBAT: a comprehensive software package for genome-wide association analysis of complex family-based studies
Van Steen, Kristel ULg; Lange, C.

in Human Genomics (2005), 2(1), 67-9

The PBAT software package (v2.5) provides a unique set of tools for complex family-based association analysis at a genome-wide level. PBAT can handle nuclear families with missing parental genotypes ... [more ▼]

The PBAT software package (v2.5) provides a unique set of tools for complex family-based association analysis at a genome-wide level. PBAT can handle nuclear families with missing parental genotypes, extended pedigrees with missing genotypic information, analysis of single nucleotide polymorphisms (SNPs), haplotype analysis, quantitative traits, multivariate/longitudinal data and time to onset phenotypes. The data analysis can be adjusted for covariates and gene/environment interactions. Haplotype-based features include sliding windows and the reconstruction of the haplotypes of the probands. PBAT's screening tools allow the user successfully to handle the multiple comparisons problem at a genome-wide level, even for 100,000 SNPs and more. Moreover, PBAT is computationally fast. A genome scan of 300,000 SNPs in 2,000 trios takes 4 central processing unit (CPU)-days. PBAT is available for Linux, Sun Solaris and Windows XP. [less ▲]

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See detailGenomic screening in family-based association testing
Murphy, A.; McGueen, M. B.; Su, J. et al

in Genetic Epidemiology. Supplement (2005), 29

Due to the recent gains in the availability of single-nucleotide polymorphism data, genome-wide association testing has become feasible. It is hoped that this additional data may confirm the presence of ... [more ▼]

Due to the recent gains in the availability of single-nucleotide polymorphism data, genome-wide association testing has become feasible. It is hoped that this additional data may confirm the presence of disease susceptibility loci, and identify new genetic determinants of disease. However, the problem of multiple comparisons threatens to diminish any potential gains from this newly available data. To circumvent the multiple comparisons issue, we utilize a recently developed screening technique using family-based association testing. This screening methodology allows for the identification of the most promising single-nucleotide polymorphisms for testing without biasing the nominal significance level of our test statistic. We compare the results of our screening technique across univariate and multivariate family-based association tests. From our analyses, we observe that the screening technique, applied to different settings, is fairly consistent in identifying optimal markers for testing. One of the identified markers, TSC0047225, was significantly associated with both the ttth1 (p=0.004) and ttth1-ttth4 (p=0.004) phenotype(s). We find that both univariate- and multivariate-based screening techniques are powerful tools for detecting an association. [less ▲]

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See detailGenomic screening and replication using the same data set in family-based association testing
Van Steen, Kristel ULg; McQueen, M. B.; Herbert, A. et al

in Nature Genetics (2005), 37(7), 683-691

The Human Genome Project and its spin- offs are making it increasingly feasible to determine the genetic basis of complex traits using genome- wide association studies. The statistical challenge of ... [more ▼]

The Human Genome Project and its spin- offs are making it increasingly feasible to determine the genetic basis of complex traits using genome- wide association studies. The statistical challenge of analyzing such studies stems from the severe multiple-comparison problem resulting from the analysis of thousands of SNPs. Our methodology for genome- wide family- based association studies, using single SNPs or haplotypes, can identify associations that achieve genome- wide significance. In relation to developing guidelines for our screening tools, we determined lower bounds for the estimated power to detect the gene underlying the disease- susceptibility locus, which hold regardless of the linkage disequilibrium structure present in the data. We also assessed the power of our approach in the presence of multiple disease- susceptibility loci. Our screening tools accommodate genomic control and use the concept of haplotype- tagging SNPs. Our methods use the entire sample and do not require separate screening and validation samples to establish genome- wide significance, as population- based designs do. [less ▲]

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See detailComparison of linkage and association strategies for quantitative traits using the COGA dataset.
McQueen, M. B.; Murphy, A.; Kraft, P. et al

in BMC Genetics (2005), 6 Suppl 1

ABSTRACT : Genome scans using dense single-nucleotide polymorphism (SNP) data have recently become a reality. It is thought that the increase in information content for linkage analysis as a result of the ... [more ▼]

ABSTRACT : Genome scans using dense single-nucleotide polymorphism (SNP) data have recently become a reality. It is thought that the increase in information content for linkage analysis as a result of the denser scans will help refine previously identified linkage regions and possibly identify new regions not identifiable using the sparser, microsatellite scans. In the context of the dense SNP scans, it is also possible to consider association strategies to provide even more information about potential regions of interest. To circumvent the multiple-testing issues inherent in association analysis, we use a recently developed strategy, implemented in PBAT, which screens the data to identify the optimal SNPs for testing, without biasing the nominal significance level. We compare the results from the PBAT analysis to that of quantitative linkage analysis on chromosome 4 using the Collaborative Study on the Genetics of Alcoholism data, as released through Genetic Analysis Workshop 14. [less ▲]

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See detailCombined analysis from eleven linkage studies of bipolar disorder provides strong evidence of susceptibility loci on chromosomes 6q and 8q
McQueen, M. B.; Devlin, B.; Faraone, S. V. et al

in American Journal of Human Genetics (2005), 77(4), 582-95

Several independent studies and meta-analyses aimed at identifying genomic regions linked to bipolar disorder (BP) have failed to find clear and consistent evidence of linkage regions. Our hypothesis is ... [more ▼]

Several independent studies and meta-analyses aimed at identifying genomic regions linked to bipolar disorder (BP) have failed to find clear and consistent evidence of linkage regions. Our hypothesis is that combining the original genotype data provides benefits of increased power and control over sources of heterogeneity that outweigh the difficulty and potential pitfalls of the implementation. We conducted a combined analysis using the original genotype data from 11 BP genomewide linkage scans comprising 5,179 individuals from 1,067 families. Heterogeneity among studies was minimized in our analyses by using uniform methods of analysis and a common, standardized marker map and was assessed using novel methods developed for meta-analysis of genome scans. To date, this collaboration is the largest and most comprehensive analysis of linkage samples involving a psychiatric disorder. We demonstrate that combining original genome-scan data is a powerful approach for the elucidation of linkage regions underlying complex disease. Our results establish genomewide significant linkage to BP on chromosomes 6q and 8q, which provides solid information to guide future gene-finding efforts that rely on fine-mapping and association approaches. [less ▲]

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See detailTesting for association in genetic studies
Laird, N. M.; Kraft, P.; Lange, C. et al

in Silverman, E.; Shapiro, S. D.; Lomas, D. A. (Eds.) et al Respiratory Genetics (2005)

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See detailGenomic screening in family-based association testing
Murphy, A.; McGueen, M. B.; Su, J. et al

in BMC Genetics (2005), 6

Due to the recent gains in the availability of single-nucleotide polymorphism data, genome-wide association testing has become feasible. It is hoped that this additional data may confirm the presence of ... [more ▼]

Due to the recent gains in the availability of single-nucleotide polymorphism data, genome-wide association testing has become feasible. It is hoped that this additional data may confirm the presence of disease susceptibility loci, and identify new genetic determinants of disease. However, the problem of multiple comparisons threatens to diminish any potential gains from this newly available data. To circumvent the multiple comparisons issue, we utilize a recently developed screening technique using family-based association testing. This screening methodology allows for the identification of the most promising single-nucleotide polymorphisms for testing without biasing the nominal significance level of our test statistic. We compare the results of our screening technique across univariate and multivariate family-based association tests. From our analyses, we observe that the screening technique, applied to different settings, is fairly consistent in identifying optimal markers for testing. One of the identified markers, TSC0047225, was significantly associated with both the ttth1 (p=0.004) and ttth1-ttth4 (p=0.004) phenotype(s). We find that both univariate- and multivariate-based screening techniques are powerful tools for detecting an association. [less ▲]

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See detailComparison of linkage and association strategies for quantitative traits using the COGA dataset
McQueen, M. B.; Murphy, A.; Kraft, P. et al

in Genetic Epidemiology. Supplement (2005), 29(Suppl I), 1-9

Genome scans using dense single-nucleotide polymorphism ( SNP) data have recently become a reality. It is thought that the increase in information content for linkage analysis as a result of the denser ... [more ▼]

Genome scans using dense single-nucleotide polymorphism ( SNP) data have recently become a reality. It is thought that the increase in information content for linkage analysis as a result of the denser scans will help refine previously identified linkage regions and possibly identify new regions not identifiable using the sparser, microsatellite scans. In the context of the dense SNP scans, it is also possible to consider association strategies to provide even more information about potential regions of interest. To circumvent the multiple-testing issues inherent in association analysis, we use a recently developed strategy, implemented in PBAT, which screens the data to identify the optimal SNPs for testing, without biasing the nominal significance level. We compare the results from the PBAT analysis to that of quantitative linkage analysis on chromosome 4 using the Collaborative Study on the Genetics of Alcoholism data, as released through Genetic Analysis Workshop 14. [less ▲]

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See detailGenomic screening and replication in one data set in family-based association testing
Lange, C.; Van Steen, Kristel ULg; McQueen, M. et al

in Conference Abstract Book (2005)

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See detailGenetic predictors of asthma exacerbations among children in the childhood asthma management program
Celedon, J. C.; Van Steen, Kristel ULg; Lange, C. et al

in Conference Abstract Book (2005)

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See detailA family-based association test for repeatedly measured quantitative traits adjusting for unknown environmental and/or polygenic effects
Lange, C.; Van Steen, Kristel ULg; Andrew, T. et al

in Statistical Applications in Genetics and Molecular Biology (2004), 3(1), 17

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See detailGenomic screening in family-based association testing
Van Steen, Kristel ULg; McQueen, M.; Herbert, A. et al

in Genetic Epidemiology (2004), 27

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