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PubMedDate not supplied

Development of a multivariate statistical model to predict peroxisome proliferation in the rat, based on urinary 1H-NMR spectral patterns.

A previous report of this work (Ringeissen et al. 2003) described the use of nuclear magnetic resonance (NMR) spectroscopy coupled with multivariate statistical data analysis (MVDA) to identify novel biomarkers of peroxisome proliferation (PP) in Wistar Han rats. Two potential biomarkers of peroxisome proliferation in the rat were described, N-methylnicotinamide (NMN) and N-methyl-4-pyridone-3-carboxamide (4PY). The inference from these results was that the tryptophan-nicotinamide adenine dinucleotide (NAD(+)) pathway was altered in correlation with peroxisome proliferation, a hypothesis subsequently confirmed by TaqMan analysis of the relevant genes encoding two key enzymes in the pathway, aminocarboxymuconate-semialdehyde decarboxylase (EC 4.1.1.45) and quinolinate phosphoribosyltransferase (EC 2.4.2.19). The objective of the present study was to investigate these data further and identify other metabolites in the NMR spectrum correlating equally with PP. MVDA Partial Least Squares (PLS) models were constructed that provided a better prediction of PP in Wistar Han rats than levels of 4PY and NMN alone. The resulting Wistar Han rat predictive models were then used to predict PP in a test group of Sprague Dawley rats following administration of fenofibrate. The models predicted the presence or absence of PP (above on arbitrary threshold of >2-fold mean control) in all Sprague Dawley rats in the test group.

Animals↗

PubMed2006

A statistical model for dissecting genomic imprinting through genetic mapping.

As a result of nonequivalent genetic contribution of maternal and paternal genomes to offsprings, genomic imprinting or called parent-of-origin effect, has been broadly identified in plants, animals and humans. Its role in shaping organism's development has been unanimously recognized. However, statistical methods for identifying imprinted quantitative trait loci (iQTL) and estimating the imprinted effect have not been well developed. In this article, we propose an efficient statistical procedure for genomewide estimating and testing the effects of significant iQTL underlying the quantitative variation of interested traits. The developed model can be applied to two different genetic cross designs, backcross and F(2) families derived from inbred lines. The proposed procedure is built within the maximum likelihood framework and implemented with the EM algorithm. Extensive simulation studies show that the proposed model is well performed in a variety of situations. To demonstrate the usefulness of the proposed approach, we apply the model to a published data in an F(2) family derived from LG/S and SM/S mouse stains. Two partially maternal imprinting iQTL are identified which regulate the growth of body weight. Our approach provides a testable framework for identifying and estimating iQTL involved in the genetic control of complex traits.

Algorithms↗

PubMed2004

The extreme aged: sampling, measurement, and statistical models in cross-sectional estimation and forecasting.

Little effort has been directed toward studying the relationship between morbidity and mortality at exceptional ages, perhaps for no better reason than it has been difficult to do given available data resources. Two study innovations/adjustments are required to adequately represent count data with reports of health from aged sample persons. These design features are oversampling of the exceptional group and linkage to detailed administrative reports. The National Long-Term Care Survey (NLTCS) has made it possible to study health and functioning in the context of exceptional longevity.

Aged↗

PubMed2003

Choice of data-collection parameters based on statistic modelling.

A new method and the software program BEST for optimal planning of X-ray data collection from protein crystals using the rotation method are presented. From one or a few initial diffraction images, BEST estimates the statistical characteristics of the data set for different combinations of data-collection parameters and suggests the most optimal ones. The anisotropy in diffraction and the permitted width of oscillation without spatially overlapping reflections are taken into account. According to the option chosen, the optimal set of parameters provides a given average signal-to-noise ratio at a given resolution either in the shortest time or with the minimum total radiation dose. BEST has been successfully used at the protein crystallography beamlines at DORIS (DESY). The software proved to be extremely useful in using the available data-collection time in the most efficient way.

Animals↗

PubMedDate not supplied

3D/2D registration and segmentation of scoliotic vertebrae using statistical models.

We propose a new 3D/2D registration method for vertebrae of the scoliotic spine, using two conventional radiographic views (postero-anterior and lateral), and a priori global knowledge of the geometric structure of each vertebra. This geometric knowledge is efficiently captured by a statistical deformable template integrating a set of admissible deformations, expressed by the first modes of variation in Karhunen-Loeve expansion, of the pathological deformations observed on a representative scoliotic vertebra population. The proposed registration method consists of fitting the projections of this deformable template with the preliminary segmented contours of the corresponding vertebra on the two radiographic views. The 3D/2D registration problem is stated as the minimization of a cost function for each vertebra and solved with a gradient descent technique. Registration of the spine is then done vertebra by vertebra. The proposed method efficiently provides accurate 3D reconstruction of each scoliotic vertebra and, consequently, it also provides accurate knowledge of the 3D structure of the whole scoliotic spine. This registration method has been successfully tested on several biplanar radiographic images and validated on 57 scoliotic vertebrae. The validation results reported in this paper demonstrate that the proposed statistical scheme performs better than other conventional 3D reconstruction methods.

Humans↗

PubMed2003

Genomic studies in AIDS: problems and answers. Development of a statistical model integrating both longitudinal cohort studies and transversal observations of extreme cases.

Genomic studies developed to understand HIV-1 infection and pathogenesis have often lead to conflicting results. This is linked to various factors, including differences in cohort design and selection, the numbers of patients involved, the influence of population substructure, the ethnic origins of the participants, and phenotypic definition. These difficulties in the interpretation of results are examined through published studies on the role of polymorphisms in HLA and the chemokine receptors genes in AIDS. Our analysis suggests that the use of haplotypes will strengthen the results obtained in a given cohort, and meta-analysis including multiple cohorts to gather large-enough numbers of patients should also allow clarification of the genetic associations observed. A P-value of 0.001 appears to be a good compromise for significance on candidate genes in a genetic study. Due to the generally limited size of available cohorts, results will have to be validated in other cohorts. We developed a model to fit transversal case studies (extreme case-control studies) with longitudinal cohorts (all-stages patients) for observations on two gene polymorphisms of CCR5 and NQO1. Interestingly, we observe a protective effect for the CCR5-Delta32 mutant allele in 95% of the simulations based on that model when using a population of 600 subjects; however, when using populations of 250 subjects we find a significant protection in only 59% of the simulations. Our model gives thus an explanation for the discrepancies observed in the various genomic studies published in AIDS on CCR5-Delta32 and other gene polymorphisms: they result from statistical fluctuations due to a lack of power. The sizes of most seroconverter cohorts presently available seem thus insufficient since they include less than a few hundred subjects. This result underlines the power and usefulness of the transversal studies involving extreme patients and their complementarity to longitudinal studies involving seroconverter cohorts. The transposition approach of extreme case-control data into longitudinal analysis should prove useful not only in AIDS but also in other diseases induced by chronic exposure to a foreign agent or with chronic clinical manifestations.

Acquired Immunodeficiency Syndrome↗

PubMed1996

A statistical model predicting the seizure threshold for right unilateral ECT in 106 patients.

Titration of the electroconvulsive therapy (ECT) stimulus to the patient's convulsive threshold is the only way to directly assess the patient's seizure threshold. This technique is presently practiced by 39% of ECT providers, according to a recent survey. Because multiple variables influence the seizure threshold in patients, multivariate statistical methods may provide a useful strategy to determine which variables exert the most influence on convulsive threshold. A multivariate ordinal logistic model of seizure threshold was developed on an experimental group of 66 consecutive patients undergoing titrated right unilateral (RUL) ECT for major depression. The accuracy of the model was cross-validated on a second group of 40 patients undergoing similar RUL ECT procedures. The final multivariate ordinal logistic regression model for the seizure threshold level (STL) was significant (Likelihood ratio chi 2 = 54.115; p < 0.0001:R2 = 0.313). Increasing age, African-American race, and longer inion-nasion distances (p < 0.06) predicted higher STL. Female gender was associated with a lower STL. The ability of the final model to accurately predict STL for the validation group was fair (pairwise correlation was 0.576; p < 0.001). The model did well for predicting lower STL, but fared poorly for higher STL. In conclusion, modeling STL may help establish the relative contribution of variables thought to be important to seizure threshold. However, STL models remain impractical for clinical applications in estimating seizure threshold at this time, and empirical stimulus titration should be used.

Adult↗

PubMed2004

A transversely isotropic, transversely homogeneous microstructural-statistical model of articular cartilage.

Articular cartilage is a multi-phasic, composite, fibre-reinforced material. Therefore, its mechanical properties are determined by the tissue microstructure. The presence of cells (chondrocytes) and collagen fibres within the proteoglycan matrix influences, at a local and a global level, the material symmetries. The volumetric concentration and shape of chondrocytes, and the volumetric concentration and spatial arrangement of collagen fibres have been observed to change as a function of depth in articular cartilage. In particular, collagen fibres are perpendicular to the bone-cartilage interface in the deep zone, their orientation is almost random in the middle zone, and they are parallel to the surface in the superficial zone. The aim of this work is to develop a model of elastic properties of articular cartilage based on its microstructure. In previous work, we addressed this problem based on Piola's notation for fourth-order tensors. Here, mathematical tools initially developed for transversely isotropic composite materials comprised of a statistical orientation of spheroidal inclusions are extended to articular cartilage, while taking into account the dependence of the elastic properties on cartilage depth. The resulting model is transversely isotropic and transversely homogeneous (TITH), the transverse plane being parallel to the bone-cartilage interface and the articular surface. Our results demonstrate that the axial elastic modulus decreases from the deep zone to the articular surface, a result that is in good agreement with experimental findings. Finite element simulations were carried out, in order to explore the TITH model's behaviour in articular cartilage compression tests. The force response, fluid flow and displacement fields obtained with the TITH model were compared with the classical linear elastic, isotropic, homogeneous (IH) model, showing that the IH model is unable to predict the non-uniform behaviour of the tissue. Based on considerations that the mechanical stability of the tissue depends on its topological and microstructural properties, our long-term goal is to clearly understand the stability conditions in topological terms, and the relationship with the growth and remodelling mechanisms in the healthy and diseased tissue.

Cartilage, Articular↗

PubMed2002

A statistical model for the genetic origin of allometric scaling laws in biology.

Many biological processes, from cellular metabolism to population dynamics, are characterized by particular allometric scaling (power-law) relationships between size and rate. Although such allometric relationships may be under genetic determination, their precise genetic mechanisms have not been clearly understood due to a lack of a statistical analytical method. In this paper, we present a basic statistical framework for mapping quantitative genes (or quantitative trait loci, QTL) responsible for universal quarter-power scaling laws of organic structure and function with the entire body size. Our model framework allows the testing of whether a single QTL affects the allometric relationship of two traits or whether more than one linked QTL is segregating. Like traditional multi-trait mapping, this new model can increase the power to detect the underlying QTL and the precision of its localization on the genome. Beyond the traditional method, this model is integrated with pervasive scaling laws to take advantage of the mechanistic relationships of biological structures and processes. Simulation studies indicate that the estimation precision of the QTL position and effect can be improved when the scaling relationship of the two traits is considered. The application of our model in a real example from forest trees leads to successful detection of a QTL governing the allometric relationship of third-year stem height with third-year stem biomass. The model proposed here has implications for genetic, evolutionary, biomedicinal and breeding research.

Animals↗

PubMed1989

Mild versus definite osteoporosis: comparison of bone densitometry techniques using different statistical models.

The purpose of this investigation was to determine the ability of three bone densitometry techniques to discriminate subjects with mild vertebral deformities from those with definite compression fractures. We determined bone mineral density (BMD) in 68 postmenopausal women by quantitative computed tomography (QCT) and dual-photon absorptiometry (DPA) of the spine, as well as single-photon absorptiometry (SPA) of the radius. Forty four individuals were classified as having mild deformities of the spine and 24 were considered to have definite vertebral compressions. Several statistical approaches were used to compare these subgroups and to estimate the relative risk of vertebral fracture. Included among these were percent decrements and zeta-scores, ROC curves, odds ratio estimations, and logistic regression analysis. Individuals with definite vertebral fractures had lower bone mineral density at all sites, but measurement of radial compact bone by SPA failed to reach significance. Using ROC analysis to distinguish mild deformities from true compressions, we found that measurement of spinal trabecular bone by QCT to be the most sensitive discriminator; although measurement of spinal integral bone by DPA also gave satisfactory discrimination, whereas assessment of radial compact bone did not adequately differentiate patients with mild deformities from those with definite compressions. Likewise, we found determination of spinal trabecular bone to be the most robust predictor of relative risk of definite fracture using either odds ratios or logistic regression analysis. Measurement of BMD in the peripheral cortical skeleton offered no predictive power for true vertebral fracture. We concluded that direct assessment of the spine, particularly of the trabecular portion, offered the strongest discrimination and relative risk prediction for definite osteoporotic fractures compared with milder forms of this condition.

Aged↗

PubMed1976

Some theory of reference values. II. Comparison of some statistical models of intraindividual variation in blood constituents.

Three models of intraindividual variation are reviewed, and statistical methods for distinguishing among them are discussed. Application of these methods to short series of observations from healthy individuals indicates that, in the large majority of cases, a strictly homeostatic model is appropriate for such constituents as serum calcium and magnesium. In less closely controlled variables, e.g., serum cholesterol and uric acid, a nonstationary, "rndom walk" model appears moresuitable in most cases. A more general autoregressive model, which includes the other models as extreme cases, could be used to describe all degrees of homeostatic control. This model is more complex, however, and requires at least 10 observations to yield estimates of acceptable precision. Moreover, it is sensitive to fluctuations in within-batch analytical variance. When biological variance is small relative to analytical variance, all three models yield essentially the same predicated values. To illustrate their use, these models have been applied to four short individual series of cholesterol observations showing increasing amounts of intrapersonal variation over long periods of time. I suggest that when less than 10 observations over time are available, the strictly homeostatic model and the nonstationary model be used to derive a "critical range" for assessing future changes. When longer series are available, the more general model might replace the other two for this purpose, if analytical variation has remained reasonably stable (within +/- 20% of its average value) during the period of observation. Much more experience with the use of all three models in health monitoring programs would be highly desirable.

Analysis of Variance↗

PubMed2005

Learning statistical models for annotating proteins with function information using biomedical text.

BACKGROUND: The BioCreative text mining evaluation investigated the application of text mining methods to the task of automatically extracting information from text in biomedical research articles. We participated in Task 2 of the evaluation. For this task, we built a system to automatically annotate a given protein with codes from the Gene Ontology (GO) using the text of an article from the biomedical literature as evidence. METHODS: Our system relies on simple statistical analyses of the full text article provided. We learn n-gram models for each GO code using statistical methods and use these models to hypothesize annotations. We also learn a set of Naïve Bayes models that identify textual clues of possible connections between the given protein and a hypothesized annotation. These models are used to filter and rank the predictions of the n-gram models. RESULTS: We report experiments evaluating the utility of various components of our system on a set of data held out during development, and experiments evaluating the utility of external data sources that we used to learn our models. Finally, we report our evaluation results from the BioCreative organizers. CONCLUSION: We observe that, on the test data, our system performs quite well relative to the other systems submitted to the evaluation. From other experiments on the held-out data, we observe that (i) the Naïve Bayes models were effective in filtering and ranking the initially hypothesized annotations, and (ii) our learned models were significantly more accurate when external data sources were used during learning.

Bayes Theorem↗

PubMed2002

Optimizing detection of QTLs retarding aging: choice of statistical model and animal requirements.

Quantitative trait locus (QTL) analysis makes no assumptions about the identity of genes involved in regulating aging. Moreover, it may be used as the first step in identifying such genes and, thus QTL analysis may be instrumental in formulating new hypotheses about aging. Genetic experiments, however, require hundreds to thousands of animals and are very expensive in mammals. Statistical power to detect longevity genes could be improved by excluding accidental, unrelated to aging mortality. While many early deaths are probably accidental, excluding early mortality altogether eliminates the age-related component, too. We used computer simulations to assess the effect of excluding early age-related, mortality on the statistical power of several common tests, such as t-test, Mann-Whitney and chi(2). Surprisingly, even the age-related, Gompertz component of early mortality reduces the statistical power of the t- and Mann-Whitney tests. For example, in a backcross design, to detect a gene slowing down the rate of aging and increasing mouse life span by 10% (P=0.0001; power=0.8), a regular t-test will require 640 mice, all kept for the entire life span and genotyped. If life spans of only 25% of the longest-lived animals from each of the two groups, carrying a putative longevity allele and not carrying it, are compared, population size can be reduced by two-fold, to about 300, and genotyping by seven-fold, to 90. Confirming simulation results, the significance of the effect of caloric restriction on life span increased from P=3.4x10(-5) to 1.1x10(-7), when life spans of only 40% of the longest-lived mice from each of the two groups, ad libitum fed and calorie restricted, were compared. Finally, finding the optimal combination of statistical test, the number of phenotyped and the number of genotyped animals, which would minimize experimental costs was addressed.

Aging↗

PubMed2000

Statistical models for analysis of cytogenetic biomarkers.

BACKGROUND: Bleomycin-induced chromosomal breaks (CB) and sister chromatid exchange (SCE) in peripheral blood lymphocytes have been shown to be sensitive cytological markers for susceptibility to DNA damage in patients with various types of cancer and in healthy controls. Factors such as age, sex, smoking, and alcohol consumption could affect the values of some of these biomarkers and should be considered as covariates when analyzing cytogenetic biomarkers because these factors can affect the frequency of CB and SCE. METHODS: We propose a statistical method using negative binomial (NB) distribution to evaluate the numbers of CB and SCE. In order to determine the best model to represent the frequency of CB and SCE, we compared the NB model with the widely used Poisson model and log-transformed normal model by using generalized linear models. To demonstrate the better fit of the NB model, we analyzed three different data sets from studies conducted at The University of Texas M.D. Anderson Cancer Center. The first set was a case-control study of lung cancer in a population of African Americans and Mexican Americans (286 cases and 156 controls), the second set consisted of 311 head and neck cancer patients, and the third set consisted of 105 Hodgkin's disease patients. RESULTS: For CB; the estimates of the variability for Hodgkin's disease, head and neck, and lung cancers were 487.24, 502.82, and 520.15, respectively. For SCE, the estimates of the variability for Hodgkin's disease was 9777.01. For CB, the dispersion estimates under the three models (Poisson, NB, and Normal) for Hodgkin's disease, head and neck, and lung cancers were: 12.30, 1.20, 0.85; 8.94, 1.05, 0.22; and 10.10, 1.05, 0.25, respectively. For SCE (Hodgkin's disease only), the dispersion estimates under the three models (Poisson, NB, and Normal) were 30.91, 1.11, 0.10, respectively. CONCLUSIONS: Our results demonstrate that the NB model provides a better interpretation and fit for the frequency of CB and SCE in different cancer types. Therefore, we recommend it as a model for the analysis of cytogenetic biomarkers.

Biomarkers↗

PubMed2004

Protein family comparison using statistical models and predicted structural information.

BACKGROUND: This paper presents a simple method to increase the sensitivity of protein family comparisons by incorporating secondary structure (SS) information. We build upon the effective information theory approach towards profile-profile comparison described in [Yona & Levitt 2002]. Our method augments profile columns using PSIPRED secondary structure predictions and assesses statistical similarity using information theoretical principles. RESULTS: Our tests show that this tool detects more similarities between protein families of distant homology than the previous primary sequence-based method. A very significant improvement in performance is observed when the real secondary structure is used. CONCLUSIONS: Integration of primary and secondary structure information can substantially improve detection of relationships between remotely related protein families.

Amino Acid Sequence↗

PubMed1994

Artificial intelligence versus logistic regression statistical modelling to predict cardiac complications after noncardiac surgery.

The traditional approach to developing models predictive of cardiac events has been to perform logistic regression (LR) analysis on a variety of potential predictors. An alternative to use an artificial intelligence system called a neural network (NN) which simulates biological intelligence. To evaluate the potential applicability of the latter method, we compared the ability of LR and NN techniques to predict cardiac events after noncardiac surgery. A total of 200 patients (training group) underwent cardiac risk assessment before major noncardiac surgery using 17 clinical parameters and 7 quantitative indices based on dipyridamole-thallium imaging. There were 21 post-operative myocardial infarctions and/or cardiac deaths. Data from the training group were used to develop two predictive models: one based on backward stepwise LR multivariate statistical analysis and the other one using a neural network. Both models were then validated on a second group of 160 consecutive patients also referred for preoperative risk stratification (validation group). The NN consisted of 14 input, 29 hidden, and 1 output neurons and used a back-propagation algorithm (learning rate 0.2, training tolerance 0.5, sigmoid transfer function). The sensitivity, specificity, positive and negative predictive accuracies for the prediction of postoperative events in the validation group of 160 patients were, respectively, 67% (6/9), 82% (124/151), 18% (6/33), and 98% (124/127) for LR, and 67% (6/9), 96% (145/151), 50% (6/12), and 98% (145/148) for the NN, with a difference in specificity which attained statistical significance (p < 0.01). Artificial intelligence may provide a useful alternative to conventional LR statistical analysis for the purpose of preoperative cardiac risk assessment.

Artificial Intelligence↗

PubMed2002

Statistical modelling of the central 10-degree visual field in short-wavelength automated perimetry.

BACKGROUND: Reports of short-wavelength pathway dysfunction in retinal eye disease suggest that short-wavelength automated perimetry may be a useful technique for the investigation of central visual function. The aim of this study was to adapt existing statistical procedures used for the investigation of 30-2 short-wavelength automated perimetry to the 10-2 program of the Humphrey Field Analyser. METHODS: A four- or six-point linear interpolation procedure was used to calculate normal visual field sensitivity for each of the 68 stimulus locations of the 10-2 program using empirical normal data from 51 normal subjects examined using the 30-2 program. Prediction limits for normality were derived at each stimulus location, enabling the calculation of age-corrected global perimetric indices and construction of probability maps for diffuse and focal visual field loss. The normal database was validated by empirical data from five normal subjects, stratified for age. RESULTS: The pointwise distribution of normal sensitivity exhibited a Gaussian distribution at the majority of stimulus locations. The pointwise coefficient of variation did not vary significantly across the visual field. Examples of diabetic pseudophakic patients and a patient with age-related macular degeneration are presented to illustrate the effectiveness of SWAP at detecting visual field abnormality in the central visual field. CONCLUSION: Ten-degree SWAP is able to effectively detect focal visual field loss in central retinal eye disease which may precede those found using conventional perimetry. SWAP may prove to be an invaluable technique for the investigation of central retinal eye disease.

Adult↗

PubMed2002

Test of a statistical model for molecular recognition in biological repertoires.

A chance encounter between members of a random repertoire and a molecular target is characteristic of different biological systems, including the immune and olfactory pathways as well as combinatorial libraries. In such systems, the affinity between the target and members of the repertoire is distributed with a probability function describing the propensity of obtaining a particular affinity value. We have previously proposed a phenomenological receptor affinity distribution (RAD) formalism, which describes this probability function based on simple statistical considerations. In the present analysis, we use published data from diverse experimental systems, including phage display libraries, immunoglobulins and enzymes, to test the RAD model and to compare it to other affinity distribution formalisms. The RAD model is found to provide the best description for binding data for over eight orders of magnitude on the affinity scale, and to account for a relationship between repertoire size and the maximal obtainable affinity within different repertoires. This approach points to a potential universality of the rules that govern affinity distributions in biology.

Animals↗