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At least 217 records · Page 12Linked to original sources
PubMed2000

Microsatellite size homoplasy, SSCP, and population structure: a case study in the freshwater snail Bulinus truncatus.

The extent of microsatellite size homoplasy, as well as its effect on several population genetics statistics, was investigated in natural populations using the single-strand conformation polymorphism (SSCP) method. The analysis was conducted using 240 individuals from 13 populations of the freshwater snail Bulinus truncatus at a GT(n)CT(m) compound microsatellite locus. We showed that SSCP can be used to uncover, at least partly, size homoplasy in the core sequence of this category of loci. Eight conformers (SSCP variants) were detected among the three size variants (electromorphs). Sequencing revealed that each conformer corresponded to a different combination of repeats in the GT(n) and CT(m) arrays. Part of this additional variability was detected within populations, resulting in a substantial increase in gene diversity in four populations. Additional variability also changed the values of parameters used to analyze population differentiation among populations: pairwise tests of differentiation were significant much more often with conformers than with electromorphs. On the other hand, pairwise estimates of F(st) were either smaller or larger with conformers than with electromorphs, depending on whether or not electromorphs were shared among populations. However, estimates of F(st) (or analogs) over all populations were very similar, ranging between 0.66 and 0.75. Our results were consistent with the theoretical prediction that homoplasy should not always lead to stronger population structure. Finally, conformer sequences and electromorph size distribution suggested that single-point and/or stepwise mutations occurring simultaneously in the different repeated arrays of compound microsatellites produce sequence variation without size variation and hence generate more size homoplasy than expected under a simple stepwise mutation model.

Animals↗
PubMed2000

Impact of genomics on drug discovery and clinical medicine.

Genomics, particularly high-throughput sequencing and characterization of expressed human genes, has created new opportunities for drug discovery. Knowledge of all the human genes and their functions may allow effective preventive measures, and change drug research strategy and drug discovery development processes. Pharmacogenomics is the application of genomic technologies such as gene sequencing, statistical genetics, and gene expression analysis to drugs in clinical development and on the market. It applies the large-scale systematic approaches of genomics to speed the discovery of drug response markers, whether they act at the level of the drug target, drug metabolism, or disease pathways. The potential implication of genomics and pharmacogenomics in clinical research and clinical medicine is that disease could be treated according to genetic and specific individual markers, selecting medications and dosages that are optimized for individual patients. The possibility of defining patient populations genetically may improve outcomes by predicting individual responses to drugs, and could improve safety and efficacy in therapeutic areas such as neuropsychiatry, cardiovascular medicine, endocrinology (diabetes and obesity) and oncology. Ethical questions need to be addressed and guidelines established for the use of genomics in clinical research and clinical medicine. Significant achievements are possible with an interdisciplinary approach that includes genetic, technological and therapeutic measures.

Alzheimer Disease↗
PubMed1994

Swim test immobility co-segregates with serotonergic but not cholinergic sensitivity in cross-breeds of Flinders Line rats.

The Flinders Sensitive Line (FSL) rat, a genetic animal model of depression, was cross-bred with its normal control, the Flinders Resistant Line (FRL) rat, in order to investigate the relationship between cholinergic sensitivity, the selected variable, and two apparent genetically correlated variables, serotonergic sensitivity and swim test immobility. Cross-breeding established F1, F2 and back-cross progeny, with at least 20 rats of each sex for each group. Cholinergic sensitivity was assessed as the hypothermic response to oxotremorine (0.2 mg/kg) in 30 day old rats. Serotonergic sensitivity was assessed as the hypothermic response to 8-OH-DPAT, a serotonin (5-HT)-1A agonist, in 35-40 day old rats. Immobility was assessed as the time spent immobile in a 5 min swim test in 60-70 day old rats. For each variable, there were highly significant group differences, with the parental FSL and FRL groups being at the extremes. The segregating populations tended to be intermediate between the parental lines and were generally significantly different from both FSL and FRL groups. However, the crosses more closely resembled the FRL parent for only the cholinergic responses, the distributions for 8-OH-DPAT and immobility suggesting predominantly additive genetics. Statistical analyses with chi square to compare response distributions and regression to quantify the association between variables in the segregating populations confirmed that cholinergic sensitivity was different from serotonergic sensitivity and immobility, which were significantly correlated with each other.(ABSTRACT TRUNCATED AT 250 WORDS)

8-Hydroxy-2-(di-n-propylamino)tetralin↗
PubMed2006

Systematic position of copepods of the genus Achtheres (Crustacea: Copepoda: Siphonostomatoida) parasitizing perch, Perca fluviatilis L., and zander, Sander lucioperca (L.).

Parasitic copepods of the genus Achtheres commonly infect perch, Perca fluviatilis, and zander, Sander lucioperca, in Europe. The aim of this study was to verify the specific identity of these copepods. The parasites were examined morphologically, biometrically and genetically. Statistical processing of the biometrical data was based on both empirical measurements and transformed data related to total length and genital trunk width. Principal component analysis was applied to both sets of data. DNA of both parasite 'forms' was amplified using two sets of primers (EU5.8S+EU18S and 18SF1+28SR) and the products were subjected to restriction fragment length polymorphism (RFLP). Morphological differences were found in the overall shape of the copepod bodies as well as in the details of the armament of some appendages. The morphometric study emphasized the importance of second maxillae and genital process as the variables most distinctly distinguishing the two 'forms'. The two 'forms' of Achtheres differed in the DNA sequence amplified by one set of primers. RFLP revealed even more extensive differences between these two copepods. We concluded that the copepods parasitizing perch should be referred to as Achtheres percarum von Nordmann, 1832, whereas a long-forgotten name, A. sandrae Gadd, 1901, should be applied to the copepods from zander.

Animal Structures↗
PubMed1995

A major locus influencing plasma high-density lipoprotein cholesterol levels in the San Antonio Family Heart Study. Segregation and linkage analyses.

To detect and measure the effects of a single locus on quantitative variation in plasma concentrations of HDL cholesterol (HDL-C), we conducted statistical genetic analyses on data from 526 Mexican American individuals in 25 randomly ascertained pedigrees. By using maximum-likelihood complex segregation analysis, we found evidence for a major locus with a codominant mixture model that included the phenotypic means, standard deviations, relative frequency of a low HDL-C allele, and heritability for plasma HDL-C levels, plus the effects of sex (genotype specific), age-by-sex, age2-by-sex, plasma concentrations of apolipoprotein (apo)AI and triglycerides (genotype specific), exogenous sex hormone use, and menopausal status under an unrestricted general model. Inclusion of the four covariates (in addition to the sex and age-by-sex effects) accounted for nearly 79% of the variance in total plasma HDL-C levels. Of the remaining 21% of the variance, the detected major locus accounted for approximately 55% in men and 21% in women; the total genetic contributions to the variance by genes were approximately 82% in men and 69% in women. Linkage analyses with penetrance parameter estimates from the segregation analysis excluded tight linkage between the detected major locus and markers for the following candidate loci: the apoAI/apoCIII genomic region (P < .05), apoB (P < .01), hepatic lipase (P < .001), lipoprotein lipase (P < .001), and the LDL receptor (P < .001). While not excluding the apoE locus (LOD = -0.348, P < .21), the analysis provided no support for tight linkage between it and the detected major locus.

Adolescent↗
PubMed2002

Two loci affect angiotensin I-converting enzyme activity in baboons.

Serum LDL cholesterol (LDLC) concentrations and ACE activities are risk factors for the development of cardiovascular disease (CVD). However, the relationship between ACE and CVD susceptibility, and possible mechanisms of action, is controversial. With data on 622 pedigreed baboons, we used statistical genetic methods to determine the mode of inheritance of ACE activities and its relationship to LDLC on different diets. ACE activity was moderately heritable, and quantitative trait linkage analyses detected a quantitative trait locus (QTL) for ACE activity on the baboon homolog of human chromosome 17 (near the ACE structural locus, maximum multipoint lod=7.5, genomic P=0.000003). Bivariate analyses revealed that ACE activity was genetically correlated (rhoG) with LDLC response (LDLCRC) to a high-cholesterol diet (rhoG=0.30+/-0.13, P=0.01) but not to LDLC on a basal diet (rhoG=0.08+/-0.13). Bivariate genetic analyses indicated that a previously detected QTL for LDLCRC had significant (P=0.025) pleiotropic effects on ACE activity levels and accounted for the genetic correlation. Therefore, we have detected 2 putative loci that affect ACE activity in baboons, one of which also affects LDLC dietary response. The existence of at least 2 genes that affect ACE activity, one of which is diet-responsive, may help explain the lack of consistency among studies of the relationship between ACE and CVD.

Animals↗
PubMed2006

Dissecting trait heterogeneity: a comparison of three clustering methods applied to genotypic data.

BACKGROUND: Trait heterogeneity, which exists when a trait has been defined with insufficient specificity such that it is actually two or more distinct traits, has been implicated as a confounding factor in traditional statistical genetics of complex human disease. In the absence of detailed phenotypic data collected consistently in combination with genetic data, unsupervised computational methodologies offer the potential for discovering underlying trait heterogeneity. The performance of three such methods--Bayesian Classification, Hypergraph-Based Clustering, and Fuzzy k-Modes Clustering--appropriate for categorical data were compared. Also tested was the ability of these methods to detect trait heterogeneity in the presence of locus heterogeneity and/or gene-gene interaction, which are two other complicating factors in discovering genetic models of complex human disease. To determine the efficacy of applying the Bayesian Classification method to real data, the reliability of its internal clustering metrics at finding good clusterings was evaluated using permutation testing. RESULTS: Bayesian Classification outperformed the other two methods, with the exception that the Fuzzy k-Modes Clustering performed best on the most complex genetic model. Bayesian Classification achieved excellent recovery for 75% of the datasets simulated under the simplest genetic model, while it achieved moderate recovery for 56% of datasets with a sample size of 500 or more (across all simulated models) and for 86% of datasets with 10 or fewer nonfunctional loci (across all simulated models). Neither Hypergraph Clustering nor Fuzzy k-Modes Clustering achieved good or excellent cluster recovery for a majority of datasets even under a restricted set of conditions. When using the average log of class strength as the internal clustering metric, the false positive rate was controlled very well, at three percent or less for all three significance levels (0.01, 0.05, 0.10), and the false negative rate was acceptably low (18 percent) for the least stringent significance level of 0.10. CONCLUSION: Bayesian Classification shows promise as an unsupervised computational method for dissecting trait heterogeneity in genotypic data. Its control of false positive and false negative rates lends confidence to the validity of its results. Further investigation of how different parameter settings may improve the performance of Bayesian Classification, especially under more complex genetic models, is ongoing.

Algorithms↗
PubMed2005

The quantitative trait linkage disequilibrium test: a more powerful alternative to the quantitative transmission disequilibrium test for use in the absence of population stratification.

Linkage analysis based on identity-by-descent allele-sharing can be used to identify a chromosomal region harboring a quantitative trait locus (QTL), but lacks the resolution required for gene identification. Consequently, linkage disequilibrium (association) analysis is often employed for fine-mapping. Variance-components based combined linkage and association analysis for quantitative traits in sib pairs, in which association is modeled as a mean effect and linkage is modeled in the covariance structure has been extended to general pedigrees (quantitative transmission disequilibrium test, QTDT). The QTDT approach accommodates data not only from parents and siblings, but also from all available relatives. QTDT is also robust to population stratification. However, when population stratification is absent, it is possible to utilize even more information, namely the additional information contained in the founder genotypes. In this paper, we introduce a simple modification of the allelic transmission scoring method used in the QTDT that results in a more powerful test of linkage disequilibrium, but is only applicable in the absence of population stratification. This test, the quantitative trait linkage disequilibrium (QTLD) test, has been incorporated into a new procedure in the statistical genetics computer package SOLAR. We apply this procedure in a linkage/association analysis of an electrophysiological measurement previously shown to be related to alcoholism. We also demonstrate by simulation the increase in power obtained with the QTLD test, relative to the QTDT, when a true association exists between a marker and a QTL.

Genetic Predisposition to Disease↗
PubMed2005

A quantitative trait locus for normal variation in forearm bone mineral density in pedigreed baboons maps to the ortholog of human chromosome 11q.

Baboons share many anatomical, physiological, and developmental characteristics with humans that make them excellent models for human bone maintenance and turnover. We conducted statistical genetic analyses, including a whole-genome linkage screen, of dual-energy x-ray absorptiometry-acquired measures of areal bone mineral density (aBMD), currently the most reliable single predictor of susceptibility to osteoporotic fracture in humans, from three forearm sites on the radius and ulna of 667 pedigreed baboons. We used a maximum likelihood-based variance decomposition approach to detect and quantify the effects of genes on normal variation in aBMD in the forearm of these baboons and to localize these effects to chromosomal regions. We estimated significant heritability for aBMD at all three sites and found evidence for a quantitative trait locus (QTL) contributing significantly to the genetic effects on this trait in a region of the baboon genome homologous to human chromosome 11q12-13. This first reported genome-wide linkage screen in a nonhuman primate for QTLs affecting forearm aBMD provides important cross-species replication of a QTL found in humans. The concordance of our results in a nonhuman primate with those reported for humans provides strong evidence that a gene (or genes) in this region affects normal variation in BMD.

Animals↗
PubMed1988

Measuring managed care: does it really save money?

As managed care contracts become a way of doing business, healthcare providers and insurers must learn to evaluate whether these programs save money and how much. Cost savings can be estimated using genetic statistical methods. However, each analysis must address such issues as the measurement method, claims submission lags, study period, length, method of utilization measurement, cost variability, replicability, and the effect on quality of care.

Cost-Benefit Analysis↗
PubMed2003

Probabilistic graphical models for computational biomedicine.

BACKGROUND: As genomics becomes increasingly relevant to medicine, medical informatics and bioinformatics are gradually converging into a larger field that we call computational biomedicine. OBJECTIVES: Developing a computational framework that is common to the different disciplines that compose computational biomedicine will be a major enabler of the further development and integration of this research domain. METHODS: Probabilistic graphical models such as Hidden Markov Models, belief networks, and missing-data models together with computational methods such as dynamic programming, Expectation-Maximization, data-augmentation Gibbs sampling, and the Metropolis-Hastings algorithm provide the tools for an integrated probabilistic approach to computational biomedicine. RESULTS AND CONCLUSIONS: We show how graphical models have already found a broad application in different fields composing computational biomedicine. We also indicate several challenges that lie at the interface between medical informatics, statistical genomics, and bioinformatics. We also argue that graphical models offer a unified framework making it possible to integrate in a statistically meaningful way multiple models ranging from the molecular level to cellular and to clinical levels. Because of their versatility and firm statistical underpinning, we assert that probabilistic graphical models can serve as the lingua franca for many computationally intensive approaches to biology and medicine. As such, graphical models should be a foundation of the curriculum of students in these fields. From such a foundation, students could then build towards specific computational methods in medical informatics, medical image analysis, statistical genetics, or bioinformatics while keeping the communication open between these areas.

Computational Biology↗
PubMed2004

Establishing mathematical laws of genomic variation.

As the biological arm of the Rasch community, genomic measurement is concerned with asserting and testing hypotheses regarding the quantitative status of genomic variables, including alleles, genotypes, gene expression levels, and phenotypes, as well as DNA, RNA, and protein sequence information. The defining goal of this scientific paradigm, in contrast to the sample-dependent model-fitting and deterministic hypothesis testing of classical statistical genetics, is the identification, validation, and maintenance of a common unit of genomic measurement that maintains its magnitude and meaning, within an allowable range of error, regardless of the laboratory technology used to generate outcomes or the particular group of individuals or organisms under investigation. Such an invariant metric, the basis of a standard genometric scale and associated system of genomic metrology, can be identified, validated, and maintained through 1) routine implementation of the Rasch family of measurement models to construct sample- and scale-free measures from different types of genomic data and 2) cross-calibration of genomic measurement instruments between and among researchers, laboratories, universities, corporations, and databases. This manuscript provides an introductory overview of the guiding principles of fundamental measurement theory and the work of Rasch, connects these concepts to well-known tenets of population genetics, and highlights the potential benefits, both theoretical and applied, associated with achieving objectivity in genomic measurement.

Animals↗
PubMed2004

Ideal discrimination of discrete clinical endpoints using multilocus genotypes.

Multifactor Dimensionality Reduction (MDR) is a method for the classification and prediction of discrete clinical endpoints using attributes constructed from multilocus genotype data. Empirical studies with both real and simulated data suggest that MDR has good power for detecting gene-gene interactions in the absence of independent main effects. The purpose of this study is to develop an objective, theory-driven approach to evaluate the strengths and limitations of MDR. To accomplish this goal, we borrow concepts from ideal observer analysis used in visual perception to evaluate the theoretical limits of classifying and predicting discrete clinical endpoints using multilocus genotype data. We conclude that MDR ideally discriminates between low risk and high risk subjects using attributes constructed from multilocus genotype data. We also how that the classification approach used once a multilocus attribute is constructed is similar to that of a naive Bayes classifier. This study provides a theoretical foundation for the continued development, evaluation, and application of the MDR as a data mining tool in the domain of statistical genetics and genetic epidemiology.

Animals↗
PubMed2005

[Inheritance analysis and molecular marker selection of genes for wheat spindle streak mosaic disease resistance].

Three wheat spindle streak mosaic viruses (WSSMV) resistant cultivars ('Yining Xiaomai', 'Xu87-633', and 'Xifeng') and one susceptible cultivar ('Zhen9523') were used as parents of 3 crosses in this experiment. WSSMV resistance of the parents, F1, and F2 was evaluated under field condition. Based on the segregation ratios of resistant and susceptible plants in F, and F2 populations, it was deduced that the resistance to WSSMV was dominant and the inheritable factors controlling WSSMV resistance were encoded by the nuclear genome. WSSMV resistances in 'Yining Xiaomai' and 'Xifeng' were controlled by two pairs of alleles, which showed complementary effects. However the resistance in 'Xu-87633' was controlled by a single dominant gene. 266 pairs of SSR primers located on 21 wheat chromosomes were used for polymorphic analysis of the two resistant and the susceptible parents 'Yining Xiaomai' and 'Zhen9523', and 108 of them amplified polymorphic DNA products. By Bulk Segregant Analysis of resistant and susceptible pools, one pair of primer located on chromosome arm 2DS, Xgwm261, were found being linked to WSSMV resistance. The 224 F2 individuals were then amplified with marker Xgwm261. The statistic genetic distance between Xgwm261 and the resistance locus was calculated to be 22.9 cM using the software Mapmaker 3.0.

Chromosomes, Plant↗
PubMedDate not supplied

[Correlation of hereditary and environmental effects on external respiratory function and its changes during aging in twins].

The genetic-statistical analysis of 11 variables of the external respiration has been made in 90 twin pairs of the same sex divided into two age groups: 20-44 and 45-80 years. The following classification of indices of the lung ventilation function can be suggested: with high hereditary coefficients that remain unchanged with age, with low coefficients gamma 2 that are the same in both age groups, with increasing hereditary coefficients in aging, and with the high Ignatiev-Jensen criteria in the group of people aged 20-44 and declining ones in the group aged 45-80. The last group of ventilation variables is the largest. In the group aged 20-44 a test with oxygen inhalation increases the effect of environmental factors whereas in the group aged 45-80 it decreases this effect on the indices of the lung ventilation.

Adult↗
PubMedDate not supplied

[Statistical analysis of genetic polymorphisms in epidemiological studies].

Analysis of genetic polymorphisms allows the genes that confer susceptibility to diseases to be analyzed. This paper presents the nomenclature used in genetic epidemiology literature and a basic strategy for statistical analysis of epidemiological studies that use genetic markers. First, a descriptive analysis of a single nucleotide polymorphism is presented, with assessment of Hardy-Weinberg equilibrium. Next, methods to assess the association with disease are presented. To do this, logistic regression models are used and alternative models of inheritance are explored. Finally, methods for the simultaneous analysis of multiple polymorphisms are presented: haplotype frequency estimation and analysis of disease association.

Algorithms↗
PubMed2006

The accuracy of statistical estimates in genetic studies of aging can be significantly improved.

The sample size of the data used in genetic studies is often a factor limiting the accuracy of statistical estimates. In this paper we suggest a new approach to evaluation of genetic influence on risk of development of aging-related health disorders. The approach results in substantial improvement of the accuracy of statistical estimates without an increase in the size of the genetic sample. The approach is based on the joint analysis of data from the genetic samples and easily accessible non-genetic data, such as data collected in epidemiological, demographic, and longitudinal studies of human aging and aging-related pathologies.

Aging↗
PubMed1985

Statistical studies in genetic toxicology: a perspective from the U.S. National Toxicology Program.

This paper surveys recent, as yet unpublished, statistical studies arising from research in genetic toxicology within the U.S. National Toxicology Program (NTP). These studies all involve analyses of data from Ames Salmonella/microsome mutagenicity tests, but the statistical methodologies are broadly applicable. Three issues are addressed: First, what is a tenable sampling model for Ames test data, and how does one best test the adequacy of the Poisson sampling assumption? Second, given that nonmonotone dose-response curves are fairly common in the Salmonella assay, what new statistical techniques or modifications of existing ones seem appropriate to accommodate to this reality? Finally, an intriguing question: How can the extensive NTP Ames test data base be used to assess the characteristics of any mutagen-nonmutagen decision rule? The last issue is illustrated with the commonly used "two-times background" rule.

Animals↗