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PubMed1995

Risk prediction with linked markers: pedigree analysis.

Rogatko [1995: Am J Med Genet 59:14-23] has proposed a method for risk prediction with linked markers. The actual implementation of this method required that the analytical forms of likelihood and risk functions be specified. It is impractical to obtain the explicit analytical form of these functions in large phase unknown pedigrees. When large phase unknown pedigrees are encountered, the compound risk can be approximated by a transformation of the discrete distribution obtained by computing the likelihood and risk functions over a grid of points. We propose a method to compute genetic risks when the functional form of the pedigree likelihood is unknown. The method was evaluated using a simple pedigree by comparing the results when functional forms were and were not known. This method was also applied to estimate genetic risks for a single pedigree with nonsyndromal X-linked mental retardation using 3 genetic markers linked to the putative disease gene. Linkage data from an extended pedigree were combined with genome mapping data, and recurrence risk distributions were calculated for members of the pedigree. The results suggest that the proposed method provides accurate risk estimate for genetic diseases. Computer programs are available to apply this method whenever genetic markers are suspected of being linked to a disease gene.

Female↗

PubMed2005

Evidence for genetic drift in the diversification of a geographically isolated population of the hyperthermophilic archaeon Pyrococcus.

Genetic drift is a mechanism of population divergence that is important in the evolution of plants and animals but is thought to be rare in free-living microorganisms because of their typically large population sizes and unrestricted means of dispersal. We used both phylogenetic and insertion sequence (IS) element analyses in hyperthermophilic archaea of the genus Pyrococcus to test the hypothesis that genetic drift played an important role in the diversification of these microorganisms. Multilocus sequence typing of a collection of 36 isolates of Pyrococcus, from different hydrothermal systems in the Pacific Ocean and the Mediterranean Sea, revealed that Pyrococcus populations from different geographic locations are genetically differentiated. Analysis of IS elements in these isolates exposed their presence in all individuals of only one geographically isolated lineage, that of Vulcano Island in the Mediterranean Sea. Detailed sequence analysis of six selected IS elements in the Vulcano population showed that these elements cause deleterious genomic alterations, including inactivation of gene function. The high frequency of IS elements in the sampled population together with their observed harmful effects in the genome of Pyrococcus provide molecular evidence that the Vulcano Island population of Pyrococcus is geographically isolated and that those genetic mobile elements have been brought up to high frequency by genetic drift. Thus, genetic drift resulting from physical isolation should be considered as a factor influencing differentiation in prokaryotes.

Base Sequence↗

PubMed2001

Structure-based phylogenetic analysis of short-chain alcohol dehydrogenases and reclassification of the 17beta-hydroxysteroid dehydrogenase family.

Short-chain alcohol dehydrogenases (SCAD) constitute a large and diverse family of ancient origin. Several of its members play an important role in human physiology and disease, especially in the metabolism of steroid substrates (e.g., prostaglandins, estrogens, androgens, and corticosteroids). Their involvement in common human disorders such as endocrine-related cancer, osteoporosis, and Alzheimer disease makes them an important candidate for drug targets. Recent phylogenetic analysis of SCAD is incomplete and does not allow any conclusions on very ancient divergences or on a functional characterization of novel proteins within this complex family. We have developed a 3D structure-based approach to establish the deep-branching pattern within the SCAD family. In this approach, pairwise superpositions of X-ray structures were used to calculate similarity scores as an input for a tree-building algorithm. The resulting phylogeny was validated by comparison with the results of sequence-based algorithms and biochemical data. It was possible to use the 3D data as a template for the reliable determination of the phylogenetic position of novel proteins as a first step toward functional predictions. We were able to discern new patterns in the phylogenetic relationships of the SCAD family, including a basal dichotomy of the 17beta-hydroxysteroid dehydrogenases (17beta-HSDs). These data provide an important contribution toward the development of type-specific inhibitors for 17beta-HSDs for the treatment and prevention of disease. Our structure-based phylogenetic approach can also be applied to increase the reliability of evolutionary reconstructions in other large protein families.

17-Hydroxysteroid Dehydrogenases↗

PubMed2005

Functional constraints on the constitutive androstane receptor inferred from human sequence variation and cross-species comparisons.

Members of the NR1I subfamily of nuclear receptors play a role in the transcriptional activation of genes involved in drug metabolism and transport. NR1I3, the constitutive androstane receptor (CAR), mediates the induction of several genes involved in drug response, including members of the CYP3A, CYP2B and UGT1A subfamilies. Large inter-individual variation in drug clearance has been reported for many drug metabolising enzyme genes. Sequence variation at the CAR locus could potentially contribute to variation in downstream targets, as well as to the substantial variation in expression level reported. We used a comparative genomics-based approach to select resequencing segments in 70 subjects from three populations. We identified 21 polymorphic sites, one of which results in an amino acid substitution. Our study reveals a common haplotype shared by all three populations which is remarkably similar to the ancestral sequence, confirming that CAR is under strong functional constraints. The level and pattern of sequence variation is approximately similar across populations, suggesting that interethnic differences in drug metabolism are not likely to be due to genetic variation at the CAR locus. We also identify several common non-coding variants that occur at highly conserved sites across four major branches of the mammalian phylogeny, suggesting that they may affect CAR expression and, ultimately, the activity of its downstream targets.

Animals↗

PubMed2005

Independent origin of the growth hormone gene family in New World monkeys and Old World monkeys/hominoids.

The growth hormone (GH) gene family represents an erratic and complex evolutionary pattern, involving many evolutionary events, such as multiple gene duplications, positive selection, the birth-and-death process and gene conversions. In the present study, we cloned and sequenced GH-like genes from three species of New World monkeys (NWM). Phylogenetic analysis strongly suggest monophyly for NWM GH-like genes with respect to those of Old World monkeys (OWM) and hominoids, indicating that independent gene duplications have occurred in NWM GH-like genes. There are three main clusters of genes in putatively functional NWM GH-like genes, according to our gene tree. Comparison of the ratios of nonsynonymous and synonymous substitutions revealed that these three clusters of genes evolved under different kinds of selective pressures. Detailed analysis of the evolution of pseudogenes showed that the evolutionary pattern of this gene family in platyrrhines is in agreement with the so-called birth-and-death process.

Animals↗

PubMed2005

Adjusted Kaplan-Meier estimator and log-rank test with inverse probability of treatment weighting for survival data.

Estimation and group comparison of survival curves are two very common issues in survival analysis. In practice, the Kaplan-Meier estimates of survival functions may be biased due to unbalanced distribution of confounders. Here we develop an adjusted Kaplan-Meier estimator (AKME) to reduce confounding effects using inverse probability of treatment weighting (IPTW). Each observation is weighted by its inverse probability of being in a certain group. The AKME is shown to be a consistent estimate of the survival function, and the variance of the AKME is derived. A weighted log-rank test is proposed for comparing group differences of survival functions. Simulation studies are used to illustrate the performance of AKME and the weighted log-rank test. The method proposed here outperforms the Kaplan-Meier estimate, and it does better than or as well as other estimators based on stratification. The AKME and the weighted log-rank test are applied to two real examples: one is the study of times to reinfection of sexually transmitted diseases, and the other is the primary biliary cirrhosis (PBC) study.

Adult↗

PubMed1999

High-dimensional image registration using symmetric priors.

This paper is about warping a brain image from one subject (the object image) so that it matches another (the template image). A high-dimensional model is used, whereby a finite element approach is employed to estimate translations at the location of each voxel in the template image. Bayesian statistics are used to obtain a maximum a posteriori (MAP) estimate of the deformation field. The validity of any registration method is largely based upon the constraints or, in this instance, priors incorporated into the model describing the transformations. In this approach we assume that the priors should have some form of symmetry, in that priors describing the probability distribution of the deformations should be identical to those for the inverses (i.e., warping brain A to brain B should not be different probabilistically from warping B to A). The fundamental assumption is that the probability of stretching a voxel by a factor of n is considered to be the same as the probability of shrinking n voxels by a factor of n(-1). In the Bayesian framework adopted here, the priors are assumed to have a Gibbs form, where the Gibbs potential is a penalty function that embodies this symmetry. The penalty function of choice is based upon the singular values of the Jacobian having a lognormal distribution. This enforces a continuous one-to-one mapping. A gradient descent algorithm is presented that incorporates the above priors in order to obtain a MAP estimate of the deformations. We demonstrate this approach for the two-dimensional case, but the principles can be extended to three dimensions. A number of examples are given to demonstrate how the method works.

Bayes Theorem↗

PubMed2004

Neural mechanisms for prediction: do insects have forward models?

'Forward models' are increasingly recognized as a crucial explanatory concept in vertebrate motor control. The essential idea is that an important function implemented by nervous systems is prediction of the sensory consequences of action. This is often associated with higher cognitive capabilities; however, many of the purposes forward models are thought to have analogues in insect behaviour, and the concept is closely connected to those of 'efference copy' and 'corollary discharge'. This article considers recent evidence from invertebrates that demonstrates the predictive modulation of sensory processes by motor output, and discusses to what extent this supports the conclusion that insect nervous systems also implement forward models. Several promising directions for further research are outlined.

Animals↗

PubMedDate not supplied

Improved methods of estimating survival probabilities applied to renal transplant data.

In the evaluation of clinical studies of different kinds with survival time as the response variable to be analysed the estimation of survival probabilities plays an important role. The ordinary procedure in survival data analysis for estimating survival probabilities is the Kaplan-Meier product-limit estimator. However, in the case of heavy censoring or if the largest observed failure times are censored the product-limit method is known to be a biased estimator of the survival function. Recently, two improved methods of estimating survival functions, a semiparametric procedure and an approach using splines, were proposed (Klein JP, Lee SC and Moeschberger ML, Biometrics, 46 (1990) 795-811; Whittemore AS and Keller JB, Biometrics, 42 (1986) 495-506). These new methods are less biased than the product-limit estimator, especially for heavily censored data. A computer program based on the integrated statistical and graphical software package RS/1 was developed for the calculation and graphical representation of the new estimators. Their improved properties are illustrated by the application to renal transplant data.

Computer Graphics↗

PubMed2000

Using conditional logistic regression to fit proportional odds models to interval censored data.

An easily implemented approach to fitting the proportional odds regression model to interval-censored data is presented. The approach is based on using conditional logistic regression routines in standard statistical packages. Using conditional logistic regression allows the practitioner to sidestep complications that attend estimation of the baseline odds ratio function. The approach is applicable both for interval-censored data in settings in which examinations continue regardless of whether the event of interest has occurred and for current status data. The methodology is illustrated through an application to data from an AIDS study of the effect of treatment with ZDV+ddC versus ZDV alone on 50% drop in CD4 cell count from baseline level. Simulations are presented to assess the accuracy of the procedure.

Acquired Immunodeficiency Syndrome↗

PubMed2006

Causal inference of regulator-target pairs by gene mapping of expression phenotypes.

BACKGROUND: Correlations between polymorphic markers and observed phenotypes provide the basis for mapping traits in quantitative genetics. When the phenotype is gene expression, then loci involved in regulatory control can theoretically be implicated. Recent efforts to construct gene regulatory networks from genotype and gene expression data have shown that biologically relevant networks can be achieved from an integrative approach. In this paper, we consider the problem of identifying individual pairs of genes in a direct or indirect, causal, trans-acting relationship. RESULTS: Inspired by epistatic models of multi-locus quantitative trait (QTL) mapping, we propose a unified model of expression and genotype to identify quantitative trait genes (QTG) by extending the conventional linear model to include both genotype and expression of regulator genes and their interactions. The model provides mapping of specific genes in contrast to standard linkage approaches that implicate large QTL intervals typically containing tens of genes. In simulations, we found that the method can often detect weak trans-acting regulators amid the background noise of thousands of traits and is robust to transcription models containing multiple regulator genes. We reanalyze several pleiotropic loci derived from a large set of yeast matings and identify a likely alternative regulator not previously published. However, we also found that many regulators can not be so easily mapped due to the presence of cis-acting QTLs on the regulators, which induce close linkage among small neighborhoods of genes. QTG mapped regulator-target pairs linked to ARN1 were combined to form a regulatory module, which we observed to be highly enriched in iron homeostasis related genes and contained several causally directed links that had not been identified in other automatic reconstructions of that regulatory module. Finally, we also confirm the surprising, previously published results that regulators controlling gene expression are not enriched for transcription factors, but we do show that our more precise mapping model reveals functional enrichment for several other biological processes related to the regulation of the cell. CONCLUSION: By incorporating interacting expression and genotype, our QTG mapping method can identify specific regulator genes in contrast to standard QTL interval mapping. We have shown that the method can recover biologically significant regulator-target pairs and the approach leads to a general framework for inducing a regulatory module network topology of directed and undirected edges that can be used to identify leads in pathway analysis.

Algorithms↗

PubMed2003

Short-term projections for variant Creutzfeldt-Jakob disease onsets.

Projections of both the short- and long-term course of the variant Creutzfeldt-Jakob disease (vCJD) epidemic in Great Britain have demonstrated great uncertainty due to the lack of knowledge of key aspects of the biology and epidemiology of this new disease. Such projections are sensitive to assumptions made regarding the pattern of exposure to BSE-infected animals, the effectiveness of control measures introduced in 1989 and 1996 in reducing this exposure, the functional form of the incubation period distribution and patterns of age-dependent susceptibility/exposure. This paper provides short-term projections for vCJD onsets using the time- and age-distributed onset data to the end of 2000, with results that are directly comparable to the other papers in this issue. These results demonstrate the continued uncertainty in the future scale of this disease.

Age Distribution↗

PubMed2005

Genetic and environmental factors influencing mortality up to weaning of Bruna dels Pirineus beef calves in mountain areas. A survival analysis.

Survival analysis techniques were used to analyze survival up to weaning of beef calves in the Pyrenean mountains areas of Catalonia, Spain. The Kaplan-Meier curve showed that the survival experience was not constant throughout the lactation period, as the mortality rate was more pronounced during the first month of life. The proportional hazards model analysis showed that several factors influenced the instantaneous mortality rate, with the herd-year effect having the strongest influence. Calves born in the first part of the breeding season, from September to February, had the lowest mortality risk (P < 0.001), showing that mortality risk increases as births accumulate. Calves from cows younger than 1,300 d of productive life had a higher risk of mortality (P < 0.05). Unassisted calvings presented the smallest risk of mortality, and mortality risk increased up to five times as birth became more difficult (P < 0.001). This risk also tended to increase slightly when calf birth weight was small (P < 0.10); for bigger calves, no increase of risk was detected, probably because calving difficulty was included in the model. These results suggest the need for improving the environment in the second part of the breeding period and paying more attention to births from younger cows. The survival curve fitted a parametric piecewise exponential function very well, with cut points at 16 and 32 d. The lower risk corresponded to the period of 33 to 180 d, the risk for the periods 17 to 32 d and 1 to 16 d being multiplied by 7 and 26, respectively. Confirming the robustness of the Cox model, the relative risks estimated for the different factors under this piecewise exponential model or a Weibull time-dependent model were similar to those reported above, as well as to those estimated under a frailty model, including the sire as a random effect. The modal estimates of sire variance under different baseline functions were close to 0.3, although the standard errors were very large. At weaning, the heritability estimate in the binary scale reached a value of only 0.037 because the survival at weaning was very high (96.9%) in this population. Nevertheless, in populations with a higher mortality, the inclusion of survival to weaning in the breeding objective might be justified. Overall, these results show that survival analysis is a powerful tool to analyze the mortality curve until weaning of beef calves.

Age Factors↗

PubMed2005

An EM algorithm for shape classification based on level sets.

In this paper, we propose an expectation-maximization (EM) approach to separate a shape database into different shape classes, while simultaneously estimating the shape contours that best exemplify each of the different shape classes. We begin our formulation by employing the level set function as the shape descriptor. Next, for each shape class we assume that there exists an unknown underlying level set function whose zero level set describes the contour that best represents the shapes within that shape class. The level set function for each example shape in the database is modeled as a noisy measurement of the appropriate shape class's unknown underlying level set function. Based on this measurement model and the judicious introduction of the class labels as the hidden data, our EM formulation calculates the labels for shape classification and estimates the shape contours that best typify the different shape classes. This resulting iterative algorithm is computationally efficient, simple, and accurate. We demonstrate the utility and performance of this algorithm by applying it to two medical applications.

Algorithms↗

PubMed2002

Estimation of health effects of prenatal methylmercury exposure using structural equation models.

BACKGROUND: Observational studies in epidemiology always involve concerns regarding validity, especially measurement error, confounding, missing data, and other problems that may affect the study outcomes. Widely used standard statistical techniques, such as multiple regression analysis, may to some extent adjust for these shortcomings. However, structural equations may incorporate most of these considerations, thereby providing overall adjusted estimations of associations. This approach was used in a large epidemiological data set from a prospective study of developmental methyl-mercury toxicity. RESULTS: Structural equation models were developed for assessment of the association between biomarkers of prenatal mercury exposure and neuropsychological test scores in 7 year old children. Eleven neurobehavioral outcomes were grouped into motor function and verbally mediated function. Adjustment for local dependence and item bias was necessary for a satisfactory fit of the model, but had little impact on the estimated mercury effects. The mercury effect on the two latent neurobehavioral functions was similar to the strongest effects seen for individual test scores of motor function and verbal skills. Adjustment for contaminant exposure to poly chlorinated biphenyls (PCBs) changed the estimates only marginally, but the mercury effect could be reduced to non-significance by assuming a large measurement error for the PCB biomarker. CONCLUSIONS: The structural equation analysis allows correction for measurement error in exposure variables, incorporation of multiple outcomes and incomplete cases. This approach therefore deserves to be applied more frequently in the analysis of complex epidemiological data sets.

Biomarkers↗

PubMedDate not supplied

Cloning and characterization of human CAGLP gene encoding a novel EF-hand protein.

The EF-hand proteins, containing conserved Ca2+ binding motifs, play important roles in many biological processes. Through data mining, a novel human gene, CAGLP (calglandulin-like protein) was predicted and subsequently isolated from human skeleton muscle. The open reading frame of CAGLP is 543 bp in length, coding a putative Ca2+ binding protein with four EF-hand motifs. The deduced amino acid sequence of CAGLP displays high similarity with Bothrops insularis snake protein calglandulin (80%). The results of PCR amplification using cDNA from 17 human tissues indicated that human CAGLP is expressed in prostate, thymus, heart, skeleton muscle, bone marrow and ovary. Functional CAGLP::EGFP (enhanced green fluorescent protein) fusion protein revealed that CAGLP accumulated through-out Hela cells. Western blot using anti-EGFP antibodies indicated that the CAGLP protein has a molecular weight of about 19 kD. A phylogenetic tree showed that CAGLP and calglandulin may be orthologous proteins representing a distinct group in the EF-hand proteins.

Base Sequence↗

PubMed2002

A statistical model for interpreting computerized dynamic posturography data.

Computerized dynamic posturography (CDP) is widely used for assessment of altered balance control. CDP trials are quantified using the equilibrium score (ES), which ranges from zero to 100, as a decreasing function of peak sway angle. The problem of how best to model and analyze ESs from a controlled study is considered. The ES often exhibits a skewed distribution in repeated trials, which can lead to incorrect inference when applying standard regression or analysis of variance models. Furthermore, CDP trials are terminated when a patient loses balance. In these situations, the ES is not observable, but is assigned the lowest possible score--zero. As a result, the response variable has a mixed discrete-continuous distribution, further compromising inference obtained by standard statistical methods. Here, we develop alternative methodology for analyzing ESs under a stochastic model extending the ES to a continuous latent random variable that always exists, but is unobserved in the event of a fall. Loss of balance occurs conditionally, with probability depending on the realized latent ES. After fitting the model by a form of quasi-maximum-likelihood, one may perform statistical inference to assess the effects of explanatory variables. An example is provided, using data from the NIH/NIA Baltimore Longitudinal Study on Aging.

Adult↗

PubMed2006

Improving the power of association tests for quantitative traits in family studies.

Association mapping based on family studies can identify genes that influence complex human traits while providing protection against population stratification. Because no gene is likely to have a very large effect on a complex trait, most family studies have limited power. Among the commonly used family-based tests of association for quantitative traits, the quantitative transmission-disequilibrium tests (QTDT) based on the variance-components model is the most flexible and most powerful. This method assumes that the trait values are normally distributed. Departures from normality can inflate the type I error and reduce the power. Although the family-based association tests (FBAT) and pedigree disequilibrium tests (PDT) do not require normal traits, nonnormality can also result in loss of power. In many cases, approximate normality can be achieved by transforming the trait values. However, the true transformation is unknown, and incorrect transformations may compromise the type I error and power. We propose a novel class of association tests for arbitrarily distributed quantitative traits by allowing the true transformation function to be completely unspecified and empirically estimated from the data. Extensive simulation studies showed that the new methods provide accurate control of the type I error and can be substantially more powerful than the existing methods. We applied the new methods to the Collaborative Study on the Genetics of Alcoholism and discovered significant association of single nucleotide polymorphisms (SNP) tsc0022400 on chromosome 7 with the quantitative electrophysiological phenotype TTTH1, which was not detected by any existing methods. We have implemented the new methods in a freely available computer program.

Alcoholism↗