Biomedical subjects

Josée Dupuis

Publications and source records attributed to Josée Dupuis.

13 recordsLinked to original sources

PubMed2006

Genetic variation at the low-density lipoprotein receptor-related protein 5 (LRP5) locus modulates Wnt signaling and the relationship of physical activity with bone mineral density in men.

Polymorphisms in the LRP5 gene have been associated with bone mineral density (BMD) in men and/or women. However, the functional basis for this association remains obscure. We hypothesized that LRP5 alleles could modulate Wnt signaling and the relationship between physical activity and BMD. This genetic association study was performed in the population-based Framingham Study Offspring Cohort, and included a subset of 1797 unrelated individuals who provided blood samples for DNA and who had BMD measurements of the hip and spine. Ten single-nucleotide polymorphisms (SNPs) spanning the LRP5 gene were genotyped and used for association and interaction analyses with BMD by regression methods. LRP5 haplotypes were transiently co-expressed with Wnt3a, MesD and Dkk1 in HEK293 cells and their activity evaluated by the TCF-Lef reporter assay. Six out of ten SNPs in LRP5 were associated with one or more of the femur or spine BMDs in men or women after adjustment for covariates, and these associations differed between genders. In men< or =age 60 years, 3 SNPs were significantly associated with BMD: rs2306862 on Exon 10 with femoral neck BMD (p=0.01) and Ward's BMD (p=0.01); rs4988321/p. V667M with Ward's BMD (p=0.02); and intronic rs901825 with trochanter BMD (p=0.03). In women, 3 SNPs in intron 2 were significantly associated with BMD: rs4988330 for trochanter (p=0.01) and spine BMD (p=0.003); rs312778 with femoral neck BMD (p=0.05); and rs4988331 with spine BMD (p=0.04). For each additional rare allele, BMD changed by 3-5% in males and 2-4% in females. Moreover, there was a significant interaction between physical activity and rs2306862 in exon 10 (p for interaction=0.02) and rs3736228/p. A1330V in exon 18 (p for interaction=0.05) on spine BMD in men. In both cases, the TT genotype was associated with lower BMD in men with higher physical activity scores, conversely with higher BMD in men with lower physical activity scores. In vitro, TCF-Lef activity in presence of Wnt3a was significantly reduced in cells expressing LRP5 haplotypes carrying the T allele of exon 10 and 18 compared to the wild-type allele, whereas co-expression of Dkk1 completely inhibited Wnt3a response through all LRP5 haplotypes. In summary, genetic variation in exons 10 and 18 of the LRP5 gene modulates Wnt signaling and the relationship between physical activity and BMD in men. These observations suggest that Wnt-LRP5 may play a role in the adaptation of bone to mechanical load in humans, and may explain some gender-related differences in bone mass.

Aged↗

PubMed2006

Poor performance of bootstrap confidence intervals for the location of a quantitative trait locus.

The aim of many genetic studies is to locate the genomic regions (called quantitative trait loci, QTL) that contribute to variation in a quantitative trait (such as body weight). Confidence intervals for the locations of QTL are particularly important for the design of further experiments to identify the gene or genes responsible for the effect. Likelihood support intervals are the most widely used method to obtain confidence intervals for QTL location, but the nonparametric bootstrap has also been recommended. Through extensive computer simulation, we show that bootstrap confidence intervals behave poorly and so should not be used in this context. The profile likelihood (or LOD curve) for QTL location has a tendency to peak at genetic markers, and so the distribution of the maximum-likelihood estimate (MLE) of QTL location has the unusual feature of point masses at genetic markers; this contributes to the poor behavior of the bootstrap. Likelihood support intervals and approximate Bayes credible intervals, on the other hand, are shown to behave appropriately.

Bayes Theorem↗

PubMed2006

PAI-1 Gene 4G/5G polymorphism and risk of type 2 diabetes in a population-based sample.

Elevated plasma levels of plasminogen activator inhibitor-1 (PAI-1) increase risk for type 2 diabetes. The PAI-1 4G/5G polymorphism is a major genetic determinant of plasma PAI-1 levels, with 4G/4G homozygotes having elevated PAI-1 levels relative to 5G allele carriers. These observations suggest the hypothesis that the PAI-1 4G/5G polymorphism could be a genetic risk factor for diabetes. We tested this hypothesis among 2169 participants of the Framingham Offspring Study followed for seven examinations over 26 years for 216 cases of type 2 diabetes. PAI-1 4G/4G homozygotes (genotype frequency, 27.4%) were not at significantly (p > 0.05) increased risk of incident diabetes compared with 5G allele carriers and did not have elevated levels of diabetes-related quantitative traits including BMI, fasting plasma glucose, or fasting insulin. In proportional hazards regression models accounting for correlation among siblings, with the 5G/5G genotype as the referent, the hazard ratio for incident diabetes for 4G/5G carriers was 0.93 (95% confidence interval, 0.68 to 1.28) and for 4G/4G carriers was 1.20 (95% confidence interval, 0.83 to 1.92). Results were not altered by further adjustment for sex or levels of BMI, triglycerides, or PAI-1. We conclude that the PAI-1 4G/5G polymorphism is not an important genetic risk factor for type 2 diabetes in this community-based sample. Elevated PAI-1 levels may be associated with an increased risk for diabetes as a marker for underlying endothelial dysfunction rather than by a direct effect of genetically mediated elevated levels.

Adult↗

PubMed2005

Comparisons of case-selection approaches based on allele sharing and/or disease severity index: application to the GAW14 simulated data.

For mapping complex disease traits, linkage studies are often followed by a case-control association strategy in order to identify disease-associated genes/single-nucleotide polymorphisms (SNPs). Substantial efforts are required in selecting the most informative cases from a large collection of affected individuals in order to maximize the power of the study, while taking into consideration study cost. In this article, we applied and extended three case-selection strategies that use allele-sharing information method for families with multiple affected offspring to select most informative cases using additional information on disease severity. Our results revealed that most significant associations, as measured by the lowest p-values, were obtained from a strategy that selected a case with the most allele sharing with other affected sibs from linked families ("linked-best"), despite reduction in sample size resulting from discarding unlinked families. Moreover, information on disease severity appears to be useful to improve the ability to detect associations between markers and disease loci.

Alleles↗

PubMed2005

Identification of polymorphisms explaining a linkage signal: application to the GAW14 simulated data.

We applied three approaches for the identification of polymorphisms explaining the linkage evidence to the Genetic Analysis Workshop 14 simulated data: 1) the genotype-IBD sharing test (GIST); 2) an approach suggested by Horikawa and colleagues; and 3) the homozygote sharing test (HST). These tests were compared with a family-based association test. Two linked regions with highest nonparametric linkage scores were selected to apply these methods. In the first region, Horikawa's method identified the most SNPs within the region containing the disease susceptibility locus, while HST performed best in the second region. However, Horikawa's method also had the most type I errors. These methods show potential as additional tools to complement family-based association tests for the identification of disease susceptibility variants.

Chromosomes, Human, Pair 1↗

PubMed2005

Peptidoglycan recognition proteins Pglyrp3 and Pglyrp4 are encoded from the epidermal differentiation complex and are candidate genes for the Psors4 locus on chromosome 1q21.

Psoriasis is a common inflammatory skin disease caused by genetic and environmental factors, including bacterial and viral infections. Since the skin is in constant contact with commensal and pathogenic microorganisms, we examined well-supported psoriasis genetic linkage intervals to identify genes encoding innate immune pattern recognition proteins that may play a role in pathogenesis. Two peptidoglycan recognition proteins, Pglyrp3 and Pglyrp4, are localized to the Psors4 locus on chromosome 1q21 in a gene cluster known as the epidermal differentiation complex (EDC). We show that these genes are expressed in the skin as well as in germinal centers in the tonsil. We tested 13 SNPs in or near these genes for association with psoriasis in two independent patient collections: a family-based patient set comprised of 375 individuals from 101 families, and a case-control patient collection of 282 patients with moderate to severe psoriasis and 192 healthy controls. In the family-based analysis, several SNPs in the Pglyrp3-Pglyrp4 locus show association with psoriasis (0.01 < P < 0.05). Multiple-SNP haplotypes incorporating Pglyrp3 and Pglyrp4 SNPs also show significant association in the transmission disequilibrium test (TDT; P < 0.01). In the case-control test, none of the SNPs that we tested show association with psoriasis when analyzed in single-SNP or haplotype-based tests. The discordance between the TDT and case-control results suggests that the two populations are significantly different in disease etiology, that the polymorphism responsible for the Psors4 linkage is elsewhere in the Pglyrp locus, or that the causative Psors4 polymorphism is in a location near but not in the Pglyrp locus. These data are consistent with previous reports of association of psoriasis with genes on 1q21, and suggest a role for Pglyrps in skin biology.

Carrier Proteins↗

PubMed2005

Expectation maximization algorithm based haplotype relative risk (EM-HRR): test of linkage disequilibrium using incomplete case-parents trios.

The Haplotype Relative Risk (HRR) was first proposed [Falk et al., Ann Hum Genet 1987] to test for Linkage Disequilibrium (LD) between a marker and a putative disease locus using case-parent trios. Spurious association does not appear in such family-based studies under population admixture. In this paper, we extend the HRR to accommodate incomplete trios via the Expectation-Maximization (EM) algorithm [Dempster et al., J R Stat Soc Ser B, 1977]. In addition to triads and dyads (parent-offspring pair), the EM-HRR easily incorporates individuals with no parental genotype information available, which is excluded from the one parent Transmission/Disequilibrium Test (1-TDT) [Sun et al., Am J Epidemiol 1999]. Due to the data structure of EM-HRR, transmitted alleles are always available regardless of the number of missing parental genotypes. As a result of having a larger sample size, computer simulations reveal that the EM-HRR is more powerful in detecting LD than the 1-TDT in a population under Hardy-Weinberg Equilibirum (HWE). If admixture is not extreme, the EM-HRR remains more powerful. When a large degree of admixture exists, the EM-HRR performs better the 1-TDT when the association is strong, though not as well when the association is weak. We illustrate the proposed method with an application to the Framingham Heart Study.

Algorithms↗

PubMed2005

Genome scan of systemic biomarkers of vascular inflammation in the Framingham Heart Study: evidence for susceptibility loci on 1q.

Vascular inflammation plays a central role in atherosclerosis and inflammatory biomarkers predict risk of cardiovascular disease (CVD). Thus, finding genes that influence systemic levels of inflammatory biomarkers may provide insights into genetic determinants of vascular inflammation and CVD. We conducted variance-component linkage analyses of blood levels of four biomarkers of vascular inflammation [C-reactive protein (CRP), interleukin-6 (IL-6), monocyte chemoattractant protein-1 (MCP-1), soluble intercellular adhesion molecule-1 (sICAM-1)] in 304 extended families from the Framingham Heart Study, using data from a 10cM genome scan. We computed p-values by a permutation approach. Heritability estimates ranged from 14% (IL-6) to 44% (MCP-1) after log transforming and adjusting for covariates. Significant linkage to MCP-1 was found on chromosome 1 (LOD=4.27 at 186cM; genome-wide p=0.005), in a region containing inflammatory candidate genes such as SELE, SELP (E- and P-selectin) and CRP. Other linkage peaks with LOD scores >2 were found for MCP-1 on chromosome 1 (LOD=2.04 at 16cM; LOD=2.34 at 70cM) and chromosome 17 (LOD=2.44 at 22cM) and for sICAM-1 on chromosome 1 at 229cM (LOD=2.09) less than 5cM from the interleukin-10 (IL10) gene. Multiple genes on chromosome 1 may influence inflammatory biomarker levels and may have a potential role in development of CVD.

Aged↗

PubMed2005

Identifying SNPs predictive of phenotype using random forests.

There has been a great interest and a few successes in the identification of complex disease susceptibility genes in recent years. Association studies, where a large number of single-nucleotide polymorphisms (SNPs) are typed in a sample of cases and controls to determine which genes are associated with a specific disease, provide a powerful approach for complex disease gene mapping. Genes of interest in those studies may contain large numbers of SNPs that classical statistical methods cannot handle simultaneously without requiring prohibitively large sample sizes. By contrast, high-dimensional nonparametric methods thrive on large numbers of predictors. This work explores the application of one such method, random forests, to the problem of identifying SNPs predictive of the phenotype in the case-control study design. A random forest is a collection of classification trees grown on bootstrap samples of observations, using a random subset of predictors to define the best split at each node. The observations left out of the bootstrap samples are used to estimate prediction error. The importance of a predictor is quantified by the increase in misclassification occurring when the values of the predictor are randomly permuted. We extend the concept of importance to pairs of predictors, to capture joint effects, and we explore the behavior of importance measures over a range of two-locus disease models in the presence of a varying number of SNPs unassociated with the phenotype. We illustrate the application of random forests with a data set of asthma cases and unaffected controls genotyped at 42 SNPs in ADAM33, a previously identified asthma susceptibility gene. SNPs and SNP pairs highly associated with asthma tend to have the highest importance index value, but predictive importance and association do not always coincide.

Case-Control Studies↗

PubMed2004

The insulin gene variable number tandem repeat and risk of type 2 diabetes in a population-based sample of families and unrelated men and women.

Abnormalities in insulin regulation are central to the pathogenesis of type 2 diabetes. We assessed variation in the insulin gene variable number tandem repeat (INS VNTR) minisatellite (using the -23Hph1 A/T single nucleotide polymorphism) as a risk factor for 92 cases of incident type 2 diabetes in 883 unrelated Framingham Heart Study (FHS) subjects and in a separate sample of 698 members of 282 FHS nuclear families with 62 diabetes cases. In the unrelated sample, the -23Hph1 TT genotype frequency was 8.0% and was associated with a diabetes hazard ratio of 1.89 [95% confidence interval (CI), 1.01-3.52; P = 0.045] compared with the AA genotype using diabetes age of onset as the time failure variable in a proportional hazards model adjusted for age, offspring sex, body mass index, parental diabetes, and sex by parental diabetes interactions. In sex-stratified analyses, TT increased risk for diabetes in women (hazard ratio, 4.25; 95% CI, 1.76-10.3), but not men (hazard ratio, 1.01; 95% CI, 0.39-2.60). Using a family-based association test to assess transmission disequilibrium in the sample of related subjects, the age- and sex-adjusted z-score for diabetes associated with the T allele was 2.07 (P = 0.04), and a family-based association test using age of onset in a proportional hazards model was also statistically significant (P = 0.03), indicating that increased risk of diabetes was not attributable to population admixture. These data support the hypothesis that the INS VNTR is a genetic risk factor for type 2 diabetes, with the TT genotype accounting for about 6.6% of cases in the FHS population.

Adult↗

PubMed2003

Mapping complex traits using Random Forests.

Random Forest is a prediction technique based on growing trees on bootstrap samples of data, in conjunction with a random selection of explanatory variables to define the best split at each node. In the case of a quantitative outcome, the tree predictor takes on a numerical value. We applied Random Forest to the first replicate of the Genetic Analysis Workshop 13 simulated data set, with the sibling pairs as our units of analysis and identity by descent (IBD) at selected loci as our explanatory variables. With the knowledge of the true model, we performed two sets of analyses on three phenotypes: HDL, triglycerides, and glucose. The goal was to approach the mapping of complex traits from a multivariate perspective. The first set of analyses mimics a candidate gene approach with a high proportion of true genes among the predictors while the second set represents a genome scan analysis using microsatellite markers. Random Forest was able to identify a few of the major genes influencing the phenotypes, such as baseline HDL and triglycerides, but failed to identify the major genes regulating baseline glucose levels.

Chromosome Mapping↗

PubMed2002

Association of the ADAM33 gene with asthma and bronchial hyperresponsiveness.

Asthma is a common respiratory disorder characterized by recurrent episodes of coughing, wheezing and breathlessness. Although environmental factors such as allergen exposure are risk factors in the development of asthma, both twin and family studies point to a strong genetic component. To date, linkage studies have identified more than a dozen genomic regions linked to asthma. In this study, we performed a genome-wide scan on 460 Caucasian families and identified a locus on chromosome 20p13 that was linked to asthma (log(10) of the likelihood ratio (LOD), 2.94) and bronchial hyperresponsiveness (LOD, 3.93). A survey of 135 polymorphisms in 23 genes identified the ADAM33 gene as being significantly associated with asthma using case-control, transmission disequilibrium and haplotype analyses (P = 0.04 0.000003). ADAM proteins are membrane-anchored metalloproteases with diverse functions, which include the shedding of cell-surface proteins such as cytokines and cytokine receptors. The identification and characterization of ADAM33, a putative asthma susceptibility gene identified by positional cloning in an outbred population, should provide insights into the pathogenesis and natural history of this common disease.

ADAM Proteins↗

PubMed2001

A mutation in the LDL receptor-related protein 5 gene results in the autosomal dominant high-bone-mass trait.

Osteoporosis is a complex disease that affects >10 million people in the United States and results in 1.5 million fractures annually. In addition, the high prevalence of osteopenia (low bone mass) in the general population places a large number of people at risk for developing the disease. In an effort to identify genetic factors influencing bone density, we characterized a family that includes individuals who possess exceptionally dense bones but are otherwise phenotypically normal. This high-bone-mass trait (HBM) was originally localized by linkage analysis to chromosome 11q12-13. We refined the interval by extending the pedigree and genotyping additional markers. A systematic search for mutations that segregated with the HBM phenotype uncovered an amino acid change, in a predicted beta-propeller module of the low-density lipoprotein receptor-related protein 5 (LRP5), that results in the HBM phenotype. During analysis of >1,000 individuals, this mutation was observed only in affected individuals from the HBM kindred. By use of in situ hybridization to rat tibia, expression of LRP5 was detected in areas of bone involved in remodeling. Our findings suggest that the HBM mutation confers a unique osteogenic activity in bone remodeling, and this understanding may facilitate the development of novel therapies for the treatment of osteoporosis.

Alleles↗