Biomedical subjects

S J Iturria

Publications and source records attributed to S J Iturria.

6 recordsLinked to original sources

PubMed2001

A pedigree partitioning approach to quantitative trait loci mapping of IgE serum level in the GAW12 Hutterite data.

We present a semi-automatic method that uses principles from factor analysis to subdivide large pedigrees into smaller, non-overlapping sub-pedigrees. Application of our method to the Genetic Analysis Workshop 12 Hutterite pedigree yielded 12 sub-pedigrees that were used to carry out a genome-wide linkage scan for IgE serum level in SOLAR. Two-point analyses resulted in strong evidence for linkage to two marker loci on chromosome 1, D1S3723 (lod = 3.70) and D1S534 (lod = 3.58). Multipoint analysis resulted in a maximum lod of 4.58 on chromosome 1 at 143 cM. After extending the two pedigrees that contributed the most evidence for linkage, the maximum lod score decreased to 4.18, with most of the evidence for linkage due to a single large sub-pedigree.

Adult↗

PubMed2000

An EM algorithm for obtaining maximum likelihood estimates in the multi-phenotype variance components linkage model.

In recent years variance components models have been developed for localising genes that contribute to human quantitative variation. In typical applications one assumes a multivariate normal model for phenotypes and estimates model parameters by maximum likelihood. For the joint analysis of several correlated phenotypes, however, finding the maximum likelihood estimates for an appropriate multivariate normal model can be a difficult computational task due to complex constraints among the model parameters. We propose an algorithm for computing maximum likelihood estimates in a multi-phenotype variance components linkage model that readily accommodates these parameter constraints. Data simulated for Genetic Analysis Workshop 10 are used to demonstrate the potential increase in power to detect linkage that can be obtained if correlated phenotypes are analysed jointly rather than individually.

Algorithms↗

PubMed2000

Genes influencing variation in serum osteocalcin concentrations are linked to markers on chromosomes 16q and 20q.

Osteocalcin (OC) is an important constituent of bone that is synthesized by osteoblasts. Serum levels of OC have been used as a biochemical marker of bone turnover. To identify the genes influencing variation in serum OC levels, we conducted a genome-wide scan in 429 individuals comprising 10 large multigenerational families. OC levels were measured by immunoassay, and genetic markers were typed at approximately 10-cM intervals across the genome. Quantitative trait linkage was tested using a multipoint analysis based on variance component methodology, adjusting for the effects of age, sex, and oral contraceptive use. Significance levels for linkage were obtained empirically, by Monte Carlo simulation. The heritability of OC levels in this population was 62 +/- 8%. We detected significant evidence for linkage between a quantitative trait locus influencing serum OC levels and markers on chromosome 16q, and suggestive evidence for linkage of OC levels with markers on chromosome 20q. The multipoint lod scores peaked at 3.35 on chromosome 16 and 2.78 on chromosome 20, corresponding to P values of 0.00004 and 0.00017, respectively. A potential candidate gene for bone formation in the linked region on chromosome 20 is CDMP1, which encodes cartilage-derived morphogenetic protein 1. Future studies should evaluate whether variation in CDMP1 or in other genes in the linked regions on chromosomes 16 and 20 influence the rate of bone turnover.

Adolescent↗

PubMed1999

Oligogenic model selection using the Bayesian Information Criterion: linkage analysis of the P300 Cz event-related brain potential.

The traditional likelihood-based approach to hypothesis testing may not be an optimal strategy for evaluating oligogenic models of inheritance. Under oligogenic inheritance the number of possible multilocus models can become very large; there may be several competing linkage models having similar likelihoods; and comparisons among non-nested models can be required to determine if a given multilocus model provides a significantly better fit to observed phenotypic variation than an alternative model. We propose an efficient Bayesian approach to oligogenic model selection that makes use of existing model likelihoods, and show how model uncertainty can be incorporated into parameter estimation.

Alcoholism↗

PubMed1999

An empirical test of the significance of an observed quantitative trait locus effect that preserves additive genetic variation.

We propose a constrained permutation test that assesses the significance of an observed quantitative trait locus effect against a background of genetic and environmental variation. Permutations of phenotypes are not selected at random, but rather are chosen in a manner that attempts to maintain the additive genetic variability in phenotypes. Such a constraint maintains the nonindependence among observations under the null hypothesis of no linkage. The empirical distribution of the lod scores calculated using permuted phenotypes is compared to that obtained using phenotypes simulated from the assumed underlying multivariate normal model. We make comparisons of univariate analyses for both a quantitative phenotype that appears consistent with a multivariate normal model and a quantitative phenotype containing pronounced outliers. An example of a bivariate analysis is also presented.

Alcoholism↗

PubMed1999

Comparison of the 60- and 100-item NCI-block questionnaires with validation data.

Large epidemiological studies often require short food frequency questionnaires (FFQ) to minimize the respondent burden or to control for confounding from dietary factors. In this analysis, we compared the extensively used National Cancer Institute-Block 60- and 100-item FFQs with one another and with usual intake as estimated from 12 days of validation data. The analysis focused on nutrients from different aspects of the diet, including energy, fat, saturated fat, beta-carotene, dietary fiber, and vitamin C. By use of an errors-in-variables analysis, the correlations of usual intake with the two types of FFQs for these nutrients were not different. Attenuation coefficients, a measure of misclassification error, for both FFQs were of similar magnitude and indicated that substantial attenuation of logistic regression coefficients would result from either FFQ. Our results confirm previous analyses describing the validity and utility of the 60-item FFQ (Epidemiology 1, 58-64, 1990) and indicate that it is essentially equivalent to the 100-item FFQ for epidemiological analyses of major nutrients.

Adult↗