Biomedical subjects

P Uimari

Publications and source records attributed to P Uimari.

12 recordsLinked to original sources

PubMed2002

Chromosome 19q13 and multiple sclerosis susceptibility in Finland: a linkage and two-stage association study.

Several studies have previously provided some albeit weak evidence for linkage or association between chromosome 19q13 and multiple sclerosis (MS) susceptibility. We performed a two-stage association analysis with 19 markers spanning 7 Mb/5.5 cM of 19q13. In stage 1 analysis (135 MS families) allelic and haplotypic associations were found with markers within or close to the ApoE-ApoC subregion. These observations were taken as a hypothesis, which was tested in stage 2 in 125 families. However, none of the initial associations were replicated suggesting that they were most likely due to chance. Linkage analysis was performed in 27 Finnish multiplex families using 10 microsatellites spanning 23 Mb/24 cM of 19q13. DNA was available from 72 MS patients and 150 unaffected relatives. Parametric and non-parametric linkage analyses did not provide evidence for linkage when all families were tested. After stratifying the families according to HLA-DR15 there was weak evidence for linkage to the 19q13.1 subregion in DR15 negative families (LOD(max)=1.8). Taken together these results do not support a major role of chromosome 19q13.2-q13.3 in MS susceptibility among Finnish MS patients, whereas conclusions on the 19q13.1 subregion are less clear and this region requires further study.

Adolescent↗

PubMed2001

Bayesian oligogenic analysis of quantitative and qualitative traits in general pedigrees.

A Bayesian method for multipoint oligogenic analysis of quantitative and qualitative traits is presented. This method can be applied to general pedigrees, which do not necessarily have to be "peelable" and can have large numbers of markers. The number of quantitative/qualitative trait loci (QTL), their map positions in the genome, and phenotypic effects (mode of inheritances) are all estimated simultaneously within the same framework. The summaries of the estimated parameters are based on the marginal posterior distributions that are obtained through Markov chain Monte Carlo (MCMC) methods. The method uses founder alleles together with segregation indicators in order to determine the genotypes of the trait loci of all individuals in the pedigree. To improve mixing properties of the sampler, we propose (1) joint sampling of map position and segregation indicators, (2) omitting data augmentation for untyped or uninformative markers (homozygous parent), and (3) updating several markers jointly within a single block. The performance of the method was tested with two replicate GAW10 data sets (considering two levels of available marker information). The results were concordant and similar to those presented earlier with other methods. These analyses clearly illustrate the utility and wide applicability of the method.

Algorithms↗

PubMed2001

Bayesian association mapping for quantitative traits in a mixture of two populations.

We introduce a novel Bayesian approach to estimate and account for population structure simultaneously with association mapping of multiple quantitative trait loci. The method is designed for an analysis of unrelated individuals from a mixture of two populations (no admixture), where the individual population memberships are unknown. In our approach, the population structure is estimated and accounted for by using data on additional "grouping" markers which are assumed to be in Hardy-Weinberg equilibrium within the populations but have different allele frequencies between the populations. We use Bayesian hierarchical modeling and Markov chain Monte Carlo estimation, where we allow both population stratification and genetic heterogeneity. In our model the number of quantitative trait loci and their positions are treated as random variables, and we obtain their posterior distributions. Here we select the candidate and the grouping markers based on results from a preliminary SOLAR analysis.

Bayes Theorem↗

PubMed2001

Respiratory distress syndrome: evaluation of genetic susceptibility and protection by transmission disequilibrium test.

Based on epidemiological data and genetic association studies, neonatal respiratory distress syndrome (RDS) is a complex disease with a multigenic background. The genes coding for surfactant proteins (SP) A and B have been assigned as the most likely genes in the etiology of RDS. The major factor predisposing to RDS is prematurity, and thus the phenotype of a very premature newborn infant that does not develop the disease can be regarded as hypernormal. Altogether 107 father-mother-offspring trios were divided into two sets according to the proband's phenotype, to evaluate familial segregation of candidate gene polymorphisms by the transmission disequilibrium test. A set of 76 trios were analyzed for transmission disequilibrium from parents to affected offspring. Another set of 31 trios were studied for allele transmission from parents to hypernormal offspring born very prematurely before the gestational age of 32 weeks. SP-A1-A2 haplotype 6A(2)-1A(0) showed significant excess transmission to affected infants and SP-A1 allele 6A(2) decreased transmission to the hypernormals. The present family study provides strong support for a direct or indirect role of the SP-A alleles as genetic predisposers to RDS in premature infants. The inclusion of parent-hypernormal offspring trios in transmission disequilibrium test is a useful approach to test for genetic protection against a disease.

Alleles↗

PubMed2001

Candidate gene regions and genetic heterogeneity in gluten sensitivity.

BACKGROUND: Gluten sensitivity is a common multifactorial disorder, manifested in the small intestine or on the skin as typical coeliac disease or dermatitis herpetiformis, respectively. The only established genetic risk factor is HLA DQ2. AIMS: We tested genetic linkage of previously reported chromosomal loci 5q and 11q in Finnish families with gluten sensitivity. We also tested if genetic linkage to candidate loci on 5q, 11q, 2q33, and HLA DQ differed with respect to clinical manifestations or sex. SUBJECTS: We studied 102 Finnish families with affected sibpairs. For heterogeneity analysis, families were divided into subgroups according to sex and the presence of dermatitis herpetiformis, the skin manifestation of gluten sensitivity. METHODS: Non-parametric linkage between microsatellite markers and disease was tested. Linkage heterogeneity between subgroups was tested using the M test. The transmission/disequilibrium test and association analysis were performed. RESULTS: Evidence of linkage to 11q (MLS 1.37), but not to 5q, was found in the entire dataset of 102 families. Heterogeneity between subgroups was suggested: families with only the intestinal disease showed linkage mainly to 2q33 whereas families with dermatitis herpetiformis showed linkage to 11q and 5q, but not to 2q33. Linkage in all three non-HLA loci was strongest in families with predominantly male patients. HLA DQ2 conferred much stronger susceptibility to females than males. CONCLUSIONS: Independent evidence for the suggested genetic linkage between 11q and gluten sensitivity was obtained. The possible linkage heterogeneity suggests genetic differences between intestinal and skin manifestations, and the gender dependent effect of HLA DQ2.

Adult↗

PubMed1999

A Bayesian Markov chain Monte Carlo approach to map disease genes in simulated GAW11 data.

A Bayesian method for multipoint mapping of disease genes based on Markov chain Monte Carlo algorithms was applied to the simulated GAW11 data (Study 2). The method is based on repeated Gibbs and more general Metropolis-Hastings steps. For simplicity we assumed a single disease locus model with two alleles. A normal distribution for the underlying latent variable of the qualitative phenotype was assumed. Based on a single replicate of the data no clear evidence of any of the genes underlying the simulated disease was found. However, when three replicates were combined the method was able to locate the locus C correctly on chromosome 3.

Algorithms↗

PubMed1999

The effect of using different culling regimens on genetic response with two-trait, two-stage selection in a nucleus broiler stock.

Stochastic simulation was used to study the effect on genetic response and inbreeding of various two-stage two-trait culling strategies. Four different parameter sets were considered for the two traits, BW and egg number. Selection of replacement animals was based on animal model best linear unbiased prediction (BLUP) to obtain estimated breeding values (EBV) at the second stage. Culling at Stage 1 was based on either animal model BLUP or phenotypes, and information from culled animals was either available or not available for calculation of second stage EBV. Besides founder individuals, six discrete generations were considered. Culling based on BLUP of two traits at Stage 1 produced higher response than culling on phenotypic evaluations. It was found that culling based on phenotypic evaluation and not carrying information to the second stage reduce rates of response by 9 to 17% and produced inbreeding higher than or close to that of BLUP selection. This study clearly shows that a double penalty of less response and higher inbreeding is generally paid for not using all information. Optimum selection schemes will depend on relative costs and benefits of collecting and processing the extra information required for full BLUP selection schemes.

Animals↗

PubMed1998

Mapping quantitative trait loci for milk production and health of dairy cattle in a large outbred pedigree.

Quantitative trait loci (QTL) affecting milk production and health of dairy cattle were mapped in a very large Holstein granddaughter design. The analysis included 1794 sons of 14 sires and 206 genetic markers distributed across all 29 autosomes and flanking an estimated 2497 autosomal cM using Kosambi's mapping function. All families were analyzed jointly with least-squares (LS) and variance components (VC) methods. A total of 6 QTL exceeding approximate experiment-wise significance thresholds, 24 QTL exceeding suggestive thresholds, and 34 QTL exceeding chromosome-wise thresholds were identified. Significance thresholds were determined via data permutation (for LS analysis) and chi-square distribution (for VC analysis). The average bootstrap confidence interval for the experiment-wise significant QTL was 48 cM. Some chromosomes harbored QTL affecting several traits, and these were always in coupling phase, defined by consistency with genetic correlations among traits. Chromosome 17 likely harbors 2 QTL affecting milk yield, and some other chromosomes showed some evidence for 2 linked QTL affecting the same trait. In each of these cases, the 2 QTL were in repulsion phase in those families appearing to be heterozygous for both QTL, a finding which supports the build-up of linkage disequilibrium due to selection.

Analysis of Variance↗

PubMed1997

Sensitivity of segregation analysis to data structure and transformation: a case study of trypanotolerance in mice.

Sensitivity of segregation analysis for data structure and data transformation was studied using data from two trials in which mice were challenged at three months of age with a cloned isolate of Trypanosoma congolense and survival time was recorded. Data included records from three inbred strains (C57BL/6 (tolerant), A/J, and BALB/c (both susceptible)) and their crosses. Data were standardized and normalized using a modified power transformation. Segregation analysis was applied to both untransformed and transformed data to determine the genetic inheritance of trypanotolerance in these mice. Data from the two trials were analysed separately and combined. Four genetic models were compared; a one locus model, a polygenic model, a mixed model with common variance, and a mixed model with different variances for each major genotype. Even though the separate data sets and the combined data set all supported the hypothesis of a major gene (or a tightly linked cluster of genes) with different variances within each genotype, parameter estimates were highly sensitive to data transformation and several sets of parameter estimates gave similar likelihood values because of high dependency between parameters. Based on the results segregation analysis can be very sensitive to data structure in a crossbreeding design and to data transformation. Interpretation of the results can be misleading if the entire parameter space is not studied carefully.

Animals↗

PubMed1997

Mapping-linked quantitative trait loci using Bayesian analysis and Markov chain Monte Carlo algorithms.

A Bayesian method for mapping linked quantitative trait loci (QTL) using multiple linked genetic markers is presented. Parameter estimation and hypothesis testing was implemented via Markov chain Monte Carlo (MCMC) algorithms. Parameters included were allele frequencies and substitution effects for two biallelic QTL, map positions of the QTL, and markers, allele frequencies of the markers, and polygenic and residual variances. Missing data were polygenic effects and multi-locus marker-QTL genotypes. Three different MCMC schemes for testing the presence of a single or two linked QTL on the chromosome were compared. The first approach includes a model indicator variable representing two unlinked QTL, affecting the trait, one linked and one unlinked QTL, or both QTL linked with the markers. The second approach incorporates an indicator variable for each QTL into the model for phenotype, allowing or not allowing for a substitution effect of a QTL, on phenotype, and the third approach is based on model determination by reversible jump MCMC. Methods were evaluated empirically by analyzing simulated granddaughter designs. All methods identified correctly a second, linked QTL and did not reject the one-QTL model when there was only a single QTL, and no additional or an unlinked QTL.

Algorithms↗

PubMed1997

Advances in statistical methods to map quantitative trait loci in outbred populations.

Statistical methods to map quantitative trait loci (QTL) in outbred populations are reviewed, extensions and applications to human and plant genetic data are indicated, and areas for further research are identified. Simple and computationally inexpensive methods include (multiple) linear regression of phenotype on marker genotypes and regression of squared phenotypic differences among relative pairs on estimated proportions of identity-by-descent at a locus. These methods are less suited for genetic parameter estimation in outbred populations but allow the determination of test statistic distributions via simulation or data permutation; however, further inferences including confidence intervals of QTL location require the use of Monte Carlo or bootstrap sampling techniques. A method which is intermediate in computational requirements is residual maximum likelihood (REML) with a covariance matrix of random QTL effects conditional on information from multiple linked markers. Testing for the number of QTLs on a chromosome is difficult in a classical framework. The computationally most demanding methods are maximum likelihood and Bayesian analysis, which take account of the distribution of multilocus marker-QTL genotypes on a pedigree and permit investigators to fit different models of variation at the QTL. The Bayesian analysis includes the number of QTLs on a chromosome as an unknown.

Bayes Theorem↗

PubMed1996

The use of multiple markers in a Bayesian method for mapping quantitative trait loci.

Information on multiple linked genetic markers was used in a Bayesian method for the statistical mapping of quantitative trait loci (QTL). Bayesian parameter estimation and hypothesis testing were implemented via Markov chain Monte Carlo algorithms. Variables sampled were the augmented data (marker-QTL genotypes, polygenic effects), an indicator variable for linkage or nonlinkage, and the parameters. The parameter vector included allele frequencies at the markers and the QTL, map distances of the markers and the QTL, QTL substitution effect, and polygenic and residual variances. The criterion for QTL detection was the marginal posterior probability of a QTL being located on the chromosome carrying the markers. The method was evaluated empirically by analyzing simulated granddaughter designs consisting of 2000 sons, 20 related sires, and their ancestors.

Algorithms↗