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Lon R Cardon

Publications and source records attributed to Lon R Cardon.

At least 19 recordsLinked to original sources
PubMed2006

The relationship between CAG repeat length and age of onset differs for Huntington's disease patients with juvenile onset or adult onset.

Age of onset for Huntington's disease (HD) varies inversely with the length of the disease-causing CAG repeat expansion in the HD gene. A simple exponential regression model yielded adjusted R-squared values of 0.728 in a large set of Venezuelan kindreds and 0.642 in a North American, European, and Australian sample (the HD MAPS cohort). We present evidence that a two-segment exponential regression curve provides a significantly better fit than the simple exponential regression. A plot of natural log-transformed age of onset against CAG repeat length reveals this segmental relationship. This two-segment exponential regression on age of onset data increases the adjusted R-squared values by 0.012 in the Venezuelan kindreds and by 0.035 in the HD MAPS cohort. Although the amount of additional variance explained by the segmental regression approach is modest, the two slopes of the two-segment regression are significantly different from each other in both the Venezuelan kindreds [F(2, 439) = 11.13, P= 2 x 10(-5)] and in the HD MAPS cohort [F(2, 688) = 38.27, P= 2 x 10(-16)]. In both populations, the influence of each CAG repeat on age of onset appears to be stronger in the adult-onset range of CAG repeats than in the juvenile-onset range.

Adult↗
PubMed2006

Significant evidence of one or more susceptibility loci for endometriosis with near-Mendelian inheritance on chromosome 7p13-15.

BACKGROUND: Endometriosis is a common disease with a heritable component. The collaborative International Endogene Study consists of two data sets (Oxford and Australia) comprising 1176 families with multiple affected. The aim was to investigate whether the apparent concentration of cases in a proportion of families could be explained by one or more rare variants with (near-)Mendelian autosomal inheritance. METHODS AND RESULTS: Linkage analyses (aimed at finding chromosomal regions harbouring disease-predisposing genes) were conducted in families with three or more affected (Oxford: n = 52; Australia: n = 196). In the Oxford data set, a non-parametric linkage score (Kong & Cox (K&C) Log of ODds (LOD)) of 3.52 was observed on chromosome 7p (genome-wide significance P = 0.011). A parametric MOD score (equal to maximum LOD maximized over 357 possible inheritance models) of 3.89 was found at 65.72 cM (D7S510) for a dominant model with reduced penetrance. After including the Australian data set, the non-parametric K&C LOD of the combined data set was 1.46 at 57.3 cM; the parametric analysis found an MOD score of 3.30 at D7S484 (empirical significance: P = 0.035) for a recessive model with high penetrance. Critical recombinant analysis narrowed the probable region of linkage down to overlapping 6.4 Mb and 11 Mb intervals containing 48 and 96 genes, respectively. CONCLUSIONS: This is the first report to suggest that there may be one or more high-penetrance susceptibility loci for endometriosis with (near-)Mendelian inheritance.

Australia↗
PubMed2006

Functional epistasis on a common MHC haplotype associated with multiple sclerosis.

Genes in the major histocompatibility complex (MHC) encode proteins important in activating antigen-specific immune responses. Alleles at adjacent MHC loci are often in strong linkage disequilibrium; however, little is known about the mechanisms responsible for this linkage disequilibrium. Here we report that the human MHC HLA-DR2 haplotype, which predisposes to multiple sclerosis, shows more extensive linkage disequilibrium than other common caucasian HLA haplotypes in the DR region and thus seems likely to have been maintained through positive selection. Characterization of two multiple-sclerosis-associated HLA-DR alleles at separate loci by a functional assay in humanized mice indicates that the linkage disequilibrium between the two alleles may be due to a functional epistatic interaction, whereby one allele modifies the T-cell response activated by the second allele through activation-induced cell death. This functional epistasis is associated with a milder form of multiple-sclerosis-like disease. Such epistatic interaction might prove to be an important general mechanism for modifying exuberant immune responses that are deleterious to the host and could also help to explain the strong linkage disequilibrium in this and perhaps other HLA haplotypes.

Alleles↗
PubMed2006

Two-stage two-locus models in genome-wide association.

Studies in model organisms suggest that epistasis may play an important role in the etiology of complex diseases and traits in humans. With the era of large-scale genome-wide association studies fast approaching, it is important to quantify whether it will be possible to detect interacting loci using realistic sample sizes in humans and to what extent undetected epistasis will adversely affect power to detect association when single-locus approaches are employed. We therefore investigated the power to detect association for an extensive range of two-locus quantitative trait models that incorporated varying degrees of epistasis. We compared the power to detect association using a single-locus model that ignored interaction effects, a full two-locus model that allowed for interactions, and, most important, two two-stage strategies whereby a subset of loci initially identified using single-locus tests were analyzed using the full two-locus model. Despite the penalty introduced by multiple testing, fitting the full two-locus model performed better than single-locus tests for many of the situations considered, particularly when compared with attempts to detect both individual loci. Using a two-stage strategy reduced the computational burden associated with performing an exhaustive two-locus search across the genome but was not as powerful as the exhaustive search when loci interacted. Two-stage approaches also increased the risk of missing interacting loci that contributed little effect at the margins. Based on our extensive simulations, our results suggest that an exhaustive search involving all pairwise combinations of markers across the genome might provide a useful complement to single-locus scans in identifying interacting loci that contribute to moderate proportions of the phenotypic variance.

Alleles↗
PubMed2006

TUCAN (CARD8) genetic variants and inflammatory bowel disease.

BACKGROUND & AIMS: The identification of the association between Crohn's disease (CD) and NOD2 (CARD15) confirmed both the heritability of CD and highlighted the role of the nuclear factor kappaB (NFkappaB) pathway in disease pathogenesis. Other susceptibility loci exist. TUCAN (CARD8) is located beneath a CD peak of linkage on chromosome 19q. TUCAN is expressed in the gut and is a negative regulator of NFkappaB, making it an excellent candidate gene for gastrointestinal inflammation. METHODS: Ten single nucleotide polymorphisms (SNP) across TUCAN were genotyped in 365 controls, 372 patients with CD, and 373 patients with ulcerative colitis. A diagnostic panel for CD was constructed using smoking status and TUCAN, NOD2, IBD5, NOD1, and TNFSF15 data. RESULTS: We demonstrate significant association between a TUCAN SNP and CD (OR 1.35, P = .0083). The association was more pronounced with disease affecting sites other than the colon (odds ratio, 1.52) and NOD2-negative CD (odds ratio, 1.50). Combination of these data with smoking and NOD2, IBD5, NOD1, and TNFSF15 status demonstrated very strong associations with CD and high sensitivities (96.3%), specificities (99.4%), and likelihood ratios (12.8) for CD, although further work will be needed before this model can be translated into direct clinical utility. CONCLUSIONS: We have shown an association between a likely functional polymorphism in TUCAN and CD. The combination of these data in a genetic panel suggests that clinicians may soon be able to translate genetic advances into direct benefits for patients.

CARD Signaling Adaptor Proteins↗
PubMed2006

Evaluating coverage of genome-wide association studies.

Genome-wide association studies involving hundreds of thousands of SNPs in thousands of cases and controls are now underway. The first of many analytical challenges in these studies involves the choice of SNPs to genotype. It is not practical to construct a different panel of tag SNPs for each study, so the first generation of genome-wide scans will use predefined, commercially available marker panels, which will in part dictate their success or failure. We compare different approaches in use today, and show that although many of them provide substantial coverage of common variation in non-African populations, the precise extent is strongly dependent on the frequencies of alleles of interest and on specific considerations of study design. Overall, despite substantial differences in genotyping technologies, marker selection strategies and number of markers assayed, the first-generation high-throughput platforms all offer similar levels of genome coverage.

Case-Control Studies↗
PubMed2006

Genome-wide association: a promising start to a long race.

A recent study by Cheung et al. demonstrates how to identify expression quantitative trait loci (eQTLs) underlying gene expression phenotypes through a combination of genome-wide linkage analysis and subsequent fine mapping or by genome-wide association (GWA) analysis. This study emphasizes the complexity of human traits, highlighting the challenges faced by investigators--in particular, insufficient linkage disequilibrium between the trait and marker variant, genetic heterogeneity and correcting for multiple testing will all adversely impact the power to detect loci by association. These issues must be considered carefully if the GWA approach is to succeed in mapping complex phenotypes.

Chromosome Mapping↗
PubMed2006

Fine-scale map of encyclopedia of DNA elements regions in the Korean population.

The International HapMap Project aims to generate detailed human genome variation maps by densely genotyping single-nucleotide polymorphisms (SNPs) in CEPH, Chinese, Japanese, and Yoruba samples. This will undoubtedly become an important facility for genetic studies of diseases and complex traits in the four populations. To address how the genetic information contained in such variation maps is transferable to other populations, the Korean government, industries, and academics have launched the Korean HapMap project to genotype high-density Encyclopedia of DNA Elements (ENCODE) regions in 90 Korean individuals. Here we show that the LD pattern, block structure, haplotype diversity, and recombination rate are highly concordant between Korean and the two HapMap Asian samples, particularly Japanese. The availability of information from both Chinese and Japanese samples helps to predict more accurately the possible performance of HapMap markers in Korean disease-gene studies. Tagging SNPs selected from the two HapMap Asian maps, especially the Japanese map, were shown to be very effective for Korean samples. These results demonstrate that the HapMap variation maps are robust in related populations and will serve as an important resource for the studies of the Korean population in particular.

Asian People↗
PubMed2006

The portability of tagSNPs across populations: a worldwide survey.

In the search for common genetic variants that contribute to prevalent human diseases, patterns of linkage disequilibrium (LD) among linked markers should be considered when selecting SNPs. Genotyping efficiency can be increased by choosing tagging SNPs (tagSNPs) in LD with other SNPs. However, it remains to be seen whether tagSNPs defined in one population efficiently capture LD in other populations; that is, how portable tagSNPs are. Indeed, tagSNP portability is a challenge for the applicability of HapMap results. We analyzed 144 SNPs in a 1-Mb region of chromosome 22 in 1055 individuals from 38 worldwide populations, classified into seven continental groups. We measured tagSNP portability by choosing three reference populations (to approximate the three HapMap populations), defining tagSNPs, and applying them to other populations independently on the availability of information on the tagSNPs in the compared population. We found that tagSNPs are highly informative in other populations within each continental group. Moreover, tagSNPs defined in Europeans are often efficient for Middle Eastern and Central/South Asian populations. TagSNPs defined in the three reference populations are also efficient for more distant and differentiated populations (Oceania, Americas), in which the impact of their special demographic history on the genetic structure does not interfere with successfully detecting the most common haplotype variation. This high degree of portability lends promise to the search for disease association in different populations, once tagSNPs are defined in a few reference populations like those analyzed in the HapMap initiative.

Chromosomes, Human, Pair 22↗
PubMed2005

An evaluation of HapMap sample size and tagging SNP performance in large-scale empirical and simulated data sets.

A substantial investment has been made in the generation of large public resources designed to enable the identification of tag SNP sets, but data establishing the adequacy of the sample sizes used are limited. Using large-scale empirical and simulated data sets, we found that the sample sizes used in the HapMap project are sufficient to capture common variation, but that performance declines substantially for variants with minor allele frequencies of <5%.

Chromosome Mapping↗
PubMed2005

Shaking the tree: mapping complex disease genes with linkage disequilibrium.

Much effort and expense are being spent internationally to detect genetic polymorphisms contributing to susceptibility to complex human disease. Concomitantly, the technology for detecting and genotyping single nucleotide polymorphisms (SNPs) has undergone rapid development, yielding extensive catalogues of these polymorphisms across the genome. Population-based maps of the correlations amongst SNPs (linkage disequilibrium) are now being developed to accelerate the discovery of genes for complex human diseases. These genomic advances coincide with an increasing recognition of the importance of very large sample sizes for studying genetic effects. Together, these new genetic and epidemiological data hold renewed promise for the identification of susceptibility genes for complex traits. We review the state of knowledge about the structure of the human genome as related to SNPs and linkage disequilibrium, discuss the potential applications of this knowledge to mapping complex disease genes, and consider the issues facing whole genome association scanning using SNPs.

Chromosome Mapping↗
PubMed2005

Prospects and pitfalls in whole genome association studies.

Recent large-scale studies of common genetic variation throughout the human genome are making it feasible to conduct whole genome studies of genotype-phenotype associations. Such studies have the potential to uncover novel contributors to common complex traits and thus lead to insights into the aetiology of multifactorial phenotypes. Despite this promise, it is important to recognize that the availability of genetic markers and the ability to assay them at realistic cost does not guarantee success of this approach. There are a number of practical issues that require close attention, some forms of allelic architecture are not readily amenable to the association approach with even the most rigorous design, and doubtless new hurdles will emerge as the studies begin. Here we discuss the promise and current challenges of the whole genome approach, and raise some issues to consider in interpreting the results of the first whole genome studies.

Genetic Markers↗
PubMed2005

Disentangling linkage disequilibrium and linkage from dense single-nucleotide polymorphism trio data.

Parent-offspring trios are widely collected for disease gene-mapping studies and are being extensively genotyped as part of the International HapMap Project. With dense maps of markers on trios, the effects of LD and linkage can be separated, allowing estimation of recombination rates in a model-free setting. Here we define a model-free multipoint method on the basis of dense sequence polymorphism data from parent-offspring trios to estimate intermarker recombination rates. We use simulations to show that this method has up to 92% power to detect recombination hotspots of intensity 25 times background over a region of size 10 kb typed at density 1 marker per 2.5 kb and almost 100% power to detect large hotspots of intensity >125 times background over regions of size 10 kb typed with just 1 marker per 5 kb (alpha = 0.05). We found strong agreement at megabase scales between estimates from our method applied to HapMap trio data and estimates from the genetic map. At finer scales, using Centre d'Etude du Polymorphisme Humain (CEPH) pedigree data across a 10-Mb region of chromosome 20, a comparison of population recombination rate estimates obtained from our method with estimates obtained using a coalescent-based approximate-likelihood method implemented in PHASE 2.0 shows detection of the same coldspots and most hotspots: The Spearman rank correlation between the estimates from our method and those from PHASE is 0.58 (p < 2.2(-16)).

Computer Simulation↗
PubMed2005

A comparison of tagging methods and their tagging space.

Single-nucleotide polymorphism (SNP) tagging is widely used as a way of saving genotyping costs in association studies. A number of different tagging methods have been developed to reduce the number of markers to be genotyped while maintaining power for detecting effects on non-assayed SNPs. How the different methods perform in different settings, the degree to which they overlap and share common tags and how they differ are important questions. We investigated these questions by comparing three widely used tagging methods/algorithms--one haplotype r2-based method, one pair-wise r2-based method and one method which was based on haplotype diversity but focused on major haplotypes. Tagging efficiency was defined as the number of genotyped markers divided by the number of tagging SNPs. Tagging effectiveness was defined as the proportion of un-genotyped or 'hidden' SNPs being detected (having a pair-wise or haplotype r2 with a set of tagging SNPs over a threshold, e.g. haplotype r2> or =0.80). The ENCODE regions genotyped on the HapMap CEPH individuals were examined in this study. Tagging effectiveness was generally poor for rare SNPs than for common SNPs, for all three tagging methods. Inclusion of rare SNPs into initial HapMap scheme could enhance the performance of tags on rare hidden SNPs at the expense of increased genotyping cost. At a moderate tagging efficiency, more than 90% of hidden SNPs detected by tagging SNPs selected by one method were also detected by tagging SNPs selected by another method, and this figure could be increased to 100% if tagging efficiency was allowed to drop. These results indicate that the tagging space is highly concordant between different tagging methods, despite the fact that they often involve different sets of tagging SNPs.

Algorithms↗
PubMed2005

Genome-wide strategies for detecting multiple loci that influence complex diseases.

After nearly 10 years of intense academic and commercial research effort, large genome-wide association studies for common complex diseases are now imminent. Although these conditions involve a complex relationship between genotype and phenotype, including interactions between unlinked loci, the prevailing strategies for analysis of such studies focus on the locus-by-locus paradigm. Here we consider analytical methods that explicitly look for statistical interactions between loci. We show first that they are computationally feasible, even for studies of hundreds of thousands of loci, and second that even with a conservative correction for multiple testing, they can be more powerful than traditional analyses under a range of models for interlocus interactions. We also show that plausible variations across populations in allele frequencies among interacting loci can markedly affect the power to detect their marginal effects, which may account in part for the well-known difficulties in replicating association results. These results suggest that searching for interactions among genetic loci can be fruitfully incorporated into analysis strategies for genome-wide association studies.

Alleles↗
PubMed2005

A high-resolution linkage-disequilibrium map of the human major histocompatibility complex and first generation of tag single-nucleotide polymorphisms.

Autoimmune, inflammatory, and infectious diseases present a major burden to human health and are frequently associated with loci in the human major histocompatibility complex (MHC). Here, we report a high-resolution (1.9 kb) linkage-disequilibrium (LD) map of a 4.46-Mb fragment containing the MHC in U.S. pedigrees with northern and western European ancestry collected by the Centre d'Etude du Polymorphisme Humain (CEPH) and the first generation of haplotype tag single-nucleotide polymorphisms (tagSNPs) that provide up to a fivefold increase in genotyping efficiency for all future MHC-linked disease-association studies. The data confirm previously identified recombination hotspots in the class II region and allow the prediction of numerous novel hotspots in the class I and class III regions. The region of longest LD maps outside the classic MHC to the extended class I region spanning the MHC-linked olfactory-receptor gene cluster. The extended haplotype homozygosity analysis for recent positive selection shows that all 14 outlying haplotype variants map to a single extended haplotype, which most commonly bears HLA-DRB1*1501. The SNP data, haplotype blocks, and tagSNPs analysis reported here have been entered into a multidimensional Web-based database (GLOVAR), where they can be accessed and viewed in the context of relevant genome annotation. This LD map allowed us to give coordinates for the extremely variable LD structure underlying the MHC.

Haplotypes↗
PubMed2005

A comparison of linkage disequilibrium patterns and estimated population recombination rates across multiple populations.

Large-scale studies of linkage disequilibrium (LD) have shown considerable variation in the extent and distribution of pairwise LD within and between populations. Taken at face value, these results suggest that genomewide LD maps for one population may not be generalizable to other populations. However, at least part of this diversity is due to some undesirable features of pairwise LD measures, which are well documented for the D' and r2 measures. In this report, we compare patterns of LD derived from pairwise measures with statistical estimates of population recombination rates ( rho ) along a 10-Mb stretch of chromosome 20 in four population samples, comprising East Asians, African Americans, and U.K. and U.S. individuals of western European descent. The results reveal the expected variability of D' within and between populations but show better concordance in estimates of r2 for the same markers across the population samples. Estimates of rho correlate well across populations, but there is still evidence of population-specific spikes and troughs in rho values. We conclude that it is unlikely that a single haplotype map will provide a definitive guide for association studies of many populations; rather, multiple maps will need to be constructed to provide the best-possible guides for gene mapping.

Black or African American↗