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PubMed2004

The association among renal insufficiency, pharmacotherapy, and outcomes in 6,427 patients with heart failure and coronary artery disease.

OBJECTIVES: This study was designed to examine the use of cardiovascular medications and outcomes in patients with heart failure (HF) and renal dysfunction. BACKGROUND: Renal insufficiency is associated with poorer outcomes in patients with HF, but the mechanisms are uncertain. In particular, the degree of therapeutic nihilism in these patients, and whether it is appropriate, is unclear. METHODS: This was a prospective cohort study with a one-year follow-up. RESULTS: In 6,427 patients with cardiologist-diagnosed HF and angiographically proven coronary artery disease (mean age 69 years; 65% men; one-year mortality, 10%), 39% had creatinine clearances <60 ml/min. Patients with renal insufficiency were less likely to be prescribed angiotensin-converting enzyme (ACE) inhibitors, beta-blockers, statins, or aspirin (all p < 0.001). However, users of aspirin (odds ratio [OR] 0.69, 95% confidence interval [CI] 0.57 to 0.85), statins (OR 0.79, 95% CI 0.64 to 0.97), and beta-blockers (OR 0.75, 95% CI 0.62 to 0.90) were less likely to die in the subsequent 12 months than nonusers, irrespective of renal function (all OR adjusted for covariates including atherosclerotic burden and ejection fraction). Although ACE inhibitor users with creatinine clearances > or =60 ml/min had lower 12-month mortality (OR 0.72, 95% CI 0.48 to 0.99), ACE inhibitor users with clearances <60 ml/min did not (OR 1.21, 95% CI 0.97 to 1.51). CONCLUSIONS: Renal insufficiency is common in patients with HF and coronary artery disease, and these patients have more advanced coronary atherosclerosis. Patients with renal insufficiency are less likely to be prescribed efficacious therapies, but have better outcomes if they receive these medications.

Adrenergic beta-Antagonists↗

PubMed2004

Adaptive evolution of HoxA-11 and HoxA-13 at the origin of the uterus in mammals.

The evolution of morphological characters is mediated by the evolution of developmental genes. Evolutionary changes can either affect cis-regulatory elements, leading to differences in their temporal and spatial regulation, or affect the coding region. Although there is ample evidence for the importance of cis-regulatory evolution, it has only recently been shown that transcription factors do not remain functionally equivalent during evolution. These results suggest that the evolution of transcription factors may play an active role in the evolution of development. To test this idea we investigated the molecular evolution of two genes essential for the development and function of the mammalian female reproductive organs, HoxA-11 and HoxA-13. We predicted that if coding-region evolution plays an active role in developmental evolution, then these genes should have experienced adaptive evolution at the origin of the mammalian female reproductive system. We report the sequences of HoxA-11 from basal mammalian and amniote taxa and analyse HoxA-11 and HoxA-13 for signatures of adaptive molecular evolution. The data demonstrate that these genes were under strong positive (directional) selection in the stem lineage of therian and eutherian mammals, coincident with the evolution of the uterus and vagina. These results support the idea that adaptive evolution of transcription factors can be an integral part in the evolution of novel structures.

Adaptation, Biological↗

PubMed2000

The contribution of genetic influences to measures of lower-extremity function in older male twins.

Tests of balance, gait, and endurance were administered to 95 monozygotic (MZ) and 92 dizygotic (DZ), white male twins aged 68 to 79 years who had been born in the United States. Within-twin-pair correlations were calculated for each individual task and for an overall summary performance score. These were subjected to structural equation modeling to determine the contributions of genetic and environmental influences to individual differences in performance scores. MZ intraclass correlations were significant and greater than DZ correlations for the 8-foot walk and the repeated chair stands task, but not for the standing balance task. The heritability of the lower-extremity summary score was 57%, of which 39% was due to additive genetic effects and 18% due to nonadditive effects. In addition, we found that genetic influences contributed primarily to twin similarity in the poorest quartile of performance, whereas shared environmental influences contributed to twin similarity in the best quartile.

Aged↗

PubMed2004

Evolutionary genetics of dorsal wing colour in Colias butterflies.

The evolution of butterfly wing colouration is strongly affected by its multiple functions and by the correlated evolution of wing colour elements. Both factors may prevent local adaptation to ecological conditions. We investigated one aspect of wing colouration, the degree of dorsal wing melanization, in the butterfly Colias philodice eriphyle across an elevational gradient and its correlation with another aspect of wing colouration, ventral wing melanization. Dorsal wing melanization increased with elevation and these differences persisted in a common environment. Full-sibling analysis revealed high heritability for males but only intermediate heritability for females. The correlation between ventral and dorsal melanization showed significant elevational and sex-specific differences. In males the two traits were highly correlated, whereas in females the strength of the correlation decreased with increasing elevation. We conclude that uncoupling of ventral and dorsal melanization has evolved in females but not in males and discuss possible mechanisms underlying uncoupling.

Altitude↗

PubMed2005

Modeling both the magnitude and phase of complex-valued fMRI data.

In MRI and fMRI, images or voxel measurement are complex valued or bivariate at each time point. Recently, (Rowe, D.B., Logan, B.R., 2004. A complex way to compute fMRI activation. NeuroImage 23 (3), 1078-1092) introduced an fMRI magnitude activation model that utilized both the real and imaginary data in each voxel. This model, following traditional beliefs, specified that the phase time course were fixed unknown quantities which may be estimated voxel-by-voxel. Subsequently, (Rowe, D.B., Logan, B.R., 2005. Complex fMRI analysis with unrestricted phase is equivalent to a magnitude-only model. NeuroImage 24 (2), 603-606) generalized the model to have no restrictions on the phase time course. They showed that this unrestricted phase model was mathematically equivalent to the usual magnitude-only data model including regression coefficients and voxel activation statistic but philosophically different due to it derivation from complex data. Recent findings by (Hoogenrad, F.G., Reichenbach, J.R., Haacke, E.M., Lai, S., Kuppusamy, K., Sprenger, M., 1998. In vivo measurement of changes in venous blood-oxygenation with high resolution functional MRI at .95 Tesla by measuring changes in susceptibility and velocity. Magn. Reson. Med. 39 (1), 97-107) and (Menon, R.S., 2002. Postacquisition suppression of large-vessel BOLD signals in high-resolution fMRI. Magn. Reson. Med. 47 (1), 1-9) indicate that the voxel phase time course may exhibit task related changes. In this paper, a general complex fMRI activation model is introduced that describes both the magnitude and phase in complex data which can be used to specifically characterize task related change in both. Hypotheses regarding task related magnitude and/or phase changes are evaluated using derived activation statistics. It was found that the Rowe-Logan complex constant phase model strongly biases against voxels with task related phase changes and that the current very general complex linear phase model can be cast to address several different hypotheses sensitive to different magnitude/phase changes.

Algorithms↗

PubMed2006

Polymorphisms of the AURKA (STK15/Aurora Kinase) Gene and Breast Cancer Risk (United States).

AURKA is an important protein in the regulation of G2 to M transition during mitosis. Due to this regulatory function, it has been hypothesized to be a potential cancer susceptibility gene. Two non-synonymous polymorphisms (F31I and V57I) have been associated with breast cancer risk in prior studies. We sought to confirm these findings in a large case control study nested within a prospective cohort, the Nurses' Health Study. Post-menopausal women who were homozygous for the 31I and 57V alleles had an increased risk of invasive breast cancer (OR 1.63, 95% CI 1.08-2.45). We also performed a meta-analysis to summarize the findings of this and prior studies of association between the F31I polymorphism and breast cancer risk (Summary OR 1.29, 95% CI 1.08-1.53, p-heterogeneity = 0.29). These results confirm prior findings that AURKA represents a low penetrance breast cancer susceptibility gene.

Adult↗

PubMed2001

[Strength of inspiratory muscles in chronic heart failure and chronic pulmonary obstructive disease].

BACKGROUND: The maximal pressure generated by inspiratory muscles (PIMax) is an index of their strength which is diminished in both chronic obstructive pulmonary disease (COPD) and chronic heart failure (CHF). Although inspiratory muscle power output (IMPO), which includes both strength and velocity of shortening, has been shown to be reduced in COPD, there is no information regarding IMPO in CHF. AIM: To measure IMPO in patients with CHF and COPD. PATIENTS AND METHODS: We studied 9 CHF patients with functional capacity II and III and 9 patients with severe COPD. Eight normal subjects of similar ages were included as controls. Power output was measured using the incremental threshold loading test. RESULTS: Maximal IMPO was significantly reduced in both groups of patients. Power output developed with each increasing load was also diminished, basically as a consequence of a reduction in Vinsp. The degree of dyspnea at the end of the test was greater in COPD than in CHF patients and normal subjects. For a given level of power, dyspnea was also greater in patients than in normals subjects. There was no decrease in SpO2 during the test. CONCLUSIONS: IMPO is equally reduced in COPD and CHF patients. Power output is better related to dyspnea than PIMax, probably because of the inclusion of shortening velocity.

Analysis of Variance↗

PubMed1996

Linkage of rheumatoid arthritis to the candidate gene NRAMP1 on 2q35.

The macrophage resistance gene NRAMP1 regulates priming/activation of macrophages for enhanced TNF alpha, IL 1 beta, and MHC class II expression. Since all of these functions are of potential importance in the induction or maintenance or both of autoimmune disease, samples from the Arthritis and Rheumatism Council's repository of multicase rheumatoid arthritis families were typed for a dinucleotide repeat in the NRAMP1 promoter region and four other 2q34 (TNP1) or 2q35 (IL8R, VIL1, DES) marker genes. Identity by descent (IBD) sib pair analysis using a three locus haplotype NRAMP1-IL8RB-VIL1, or NRAMP1 alone, provided preliminary evidence (maximum lod score = 1.01, p = 0.024) for a gene in this region contributing to suceptibility to rheumatoid arthritis. Candidacy for NRAMP1 as the disease susceptibility gene was supported by a significant bias (p = 0.048) towards transmission of the NRAMP1 promoter region allele 3 in affected offspring.

Arthritis, Rheumatoid↗

PubMedDate not supplied

Comparison of three multitrait methods for QTL detection.

A comparison of power and accuracy of estimation of position and QTL effects of three multitrait methods and one single trait method for QTL detection was carried out on simulated data, taking into account the mixture of full and half-sib families. One multitrait method was based on a multivariate function as the penetrance function (MV). The two other multitrait methods were based on univariate analysis of linear combination(s) (LC) of the traits. One was obtained by a principal component analysis (PCA) performed on the phenotypic data. The second was based on a discriminate analysis (DA). It calculates a LC of the traits at each position, maximising the ratio between the genetic and the residual variabilities due to the putative QTL. Due to its number of parameters, MV was less powerful and accurate than the other methods. In general, DA better detected QTL, but it had lower accuracy for the QTL effect estimation when the detection power was low, due to higher bias than the other methods. In this case, PCA was better. Otherwise, PCA was slightly less powerful and accurate than DA. Compared to the single trait method, power can be improved by 30% to 100% with multitrait methods.

Computer Simulation↗

PubMed1997

Accurate confidence limits for quantiles under random censoring.

In survival analysis, estimates of median survival times in homogeneous samples are often based on the Kaplan-Meier estimator of the survivor function. Confidence intervals for quantiles, such as median survival, are typically constructed via large sample theory or the bootstrap. The former has suspect accuracy for small sample sizes under moderate censoring and the latter is computationally intensive. In this paper, improvements on so-called test-based intervals and reflected intervals (cf., Slud, Byar, and Green, 1984, Biometrics 40, 587-600) are sought. Using the Edgeworth expansion for the distribution of the studentized Nelson-Aalen estimator derived in Strawderman and Wells (1997, Journal of the American Statistical Association 92), we propose a method for producing more accurate confidence intervals for quantiles with randomly censored data. The intervals are very simple to compute, and numerical results using simulated data show that our new test-based interval outperforms commonly used methods for computing confidence intervals for small sample sizes and/or heavy censoring, especially with regard to maintaining specified coverage.

Biometry↗

PubMed1996

Prognosis versus actual outcome. II. The effectiveness of clinical parameters in developing an accurate prognosis.

The assignment of prognosis is one of the most important functions undertaken in clinical practice, yet there is little evidence to support the current decision-making process which is based on an outdated model of disease etiology and progression. This study evaluated 100 treated periodontal patients (2,484 teeth) under maintenance care for 5 years, with 38 of these patients followed for 8 years, to determine the relationship of assigned prognoses to the clinical criteria commonly used in the development of prognosis. The method of generalized estimating equations (GEE) for correlated data was utilized to determine the relationship of each clinical factor to the assignment of initial prognosis, improvement in prognosis at 5 years, and worsening in prognosis at 5 years. A multiple linear regression model was constructed for predicting initial prognosis based on initial clinical data. Increased probing depth, more severe furcation involvement, greater mobility, unsatisfactory crown-to-root ratio, malpositioned teeth, and teeth used as fixed abutments resulted in worse initial prognoses. The coefficients from this model were able to predict accurately the 5-year and 8-year prognoses 81% of the time. When teeth with "good" prognoses were excluded, the predictive accuracy dropped approximately 50%. Multiple logistic regression models indicated that improvement in prognoses and worsening in prognoses were both strongly associated with initial probing depth, initial furcation involvement, initial tooth malposition, and smoking when adjusted for initial prognosis. In addition, good hygiene was found to increase the probability of improvement in prognosis while initial mobility was found to decrease the likelihood of improvement in prognosis. Neither of these factors was found to be significant in worsening of prognosis. Smoking decreased the likelihood of improvement by 60% and doubled the likelihood of worsening in prognosis at 5 years. The results of this study indicate that some clinical factors used in the assignment of prognoses are clearly associated with changes in clinical condition over time. The data also demonstrated that the traditional approach for assigning prognoses is ineffective for teeth with an initial prognosis of less than good. Since most periodontally involved teeth are compromised, further work should include the development of a more effective method for assigning prognoses that is based on clear, objective clinical criteria.

Age Factors↗

PubMed2003

Bayesian gene/species tree reconciliation and orthology analysis using MCMC.

MOTIVATION: Comparative genomics in general and orthology analysis in particular are becoming increasingly important parts of gene function prediction. Previously, orthology analysis and reconciliation has been performed only with respect to the parsimony model. This discards many plausible solutions and sometimes precludes finding the correct one. In many other areas in bioinformatics probabilistic models have proven to be both more realistic and powerful than parsimony models. For instance, they allow for assessing solution reliability and consideration of alternative solutions in a uniform way. There is also an added benefit in making model assumptions explicit and therefore making model comparisons possible. For orthology analysis, uncertainty has recently been addressed using parsimonious reconciliation combined with bootstrap techniques. However, until now no probabilistic methods have been available. RESULTS: We introduce a probabilistic gene evolution model based on a birth-death process in which a gene tree evolves 'inside' a species tree. Based on this model, we develop a tool with the capacity to perform practical orthology analysis, based on Fitch's original definition, and more generally for reconciling pairs of gene and species trees. Our gene evolution model is biologically sound (Nei et al., 1997) and intuitively attractive. We develop a Bayesian analysis based on MCMC which facilitates approximation of an a posteriori distribution for reconciliations. That is, we can find the most probable reconciliations and estimate the probability of any reconciliation, given the observed gene tree. This also gives a way to estimate the probability that a pair of genes are orthologs. The main algorithmic contribution presented here consists of an algorithm for computing the likelihood of a given reconciliation. To the best of our knowledge, this is the first successful introduction of this type of probabilistic methods, which flourish in phylogeny analysis, into reconciliation and orthology analysis. The MCMC algorithm has been implemented and, although not yet being in its final form, tests show that it performs very well on synthetic as well as biological data. Using standard correspondences, our results carry over to allele trees as well as biogeography.

Algorithms↗

PubMed1998

Epifil: a dynamic model of infection and disease in lymphatic filariasis.

The lack of a quantitative framework that describes the dynamic relationships between infection and morbidity has constrained efforts aimed at the community-level control of lymphatic filariasis. In this paper, we describe the development and validation of EPIFIL, a dynamic model of filariasis infection intensity and chronic disease. Infection dynamics are modeled using the well established immigration-death formulation, incorporating the acquisition of immunity to infective larvae over time. The dynamics of disease (lymphodema and hydrocele) are modeled as a catalytic function of a variety of factors, including worm load and the impact of immunopathological responses. The model was parameterized using age-stratified data collected from a Bancroftian filariasis endemic area in Pondicherry in southern India. The fitted parameters suggest that a relatively simple model including only acquired immunity to infection and irreversible progression to disease can satisfactorily explain the observed infection and disease patterns. Disease progression is assumed to be a consequence of worm induced damage and to occur at a high rate for hydrocele and a low rate for lymphodema. This suggests that immunopathology involvement may not be a necessary component of observed age-disease profiles. These findings support a central role for worm burden in the initiation and progression of chronic filarial disease.

Adolescent↗

PubMed2002

Combining several screening tests: optimality of the risk score.

The development of biomarkers for cancer screening is an active area of research. While several biomarkers exist, none is sufficiently sensitive and specific on its own for population screening. It is likely that successful screening programs will require combinations of multiple markers. We consider how to combine multiple disease markers for optimal performance of a screening program. We show that the risk score, defined as the probability of disease given data on multiple markers, is the optimal function in the sense that the receiver operating characteristic (ROC) curve is maximized at every point. Arguments draw on the Neyman-Pearson lemma. This contrasts with the corresponding optimality result of classic decision theory, which is set in a Bayesian framework and is based on minimizing an expected loss function associated with decision errors. Ours is an optimality result defined from a strictly frequentist point of view and does not rely on the notion of associating costs with misclassifications. The implication for data analysis is that binary regression methods can be used to yield appropriate relative weightings of different biomarkers, at least in large samples. We propose some modifications to standard binary regression methods for application to the disease screening problem. A flexible biologically motivated simulation model for cancer biomarkers is presented and we evaluate our methods by application to it. An application to real data concerning two ovarian cancer biomarkers is also presented. Our results are equally relevant to the more general medical diagnostic testing problem, where results of multiple tests or predictors are combined to yield a composite diagnostic test. Moreover, our methods justify the development of clinical prediction scores based on binary regression.

Bayes Theorem↗

PubMed2005

Risk/benefit assessments of human diseases: optimum dose for intervention.

A simple procedure is proposed in order to quantify the tradeoff between a loss suffered from an illness due to exposure to a microbial pathogen and a loss due to a toxic effect, perhaps a different illness, induced by a disinfectant employed to reduce the microbial exposure. Estimates of these two types of risk as a function of disinfectant dose and their associated relative losses provide information for the estimation of the optimum dose of disinfectant that minimizes the total expected loss. The estimates of the optimum dose and expected relative total loss were similar regardless of whether the beta-Poisson, log-logistic, or extreme value function was used to model the risk of illness due to exposure to a microbial pathogen. This is because the optimum dose of the disinfectant and resultant expected minimum loss depend upon the estimated slope (first derivative) of the models at low levels of risk, which appear to be similar for these three models at low levels of risk. Similarly, the choice among these three models does not appear critical for estimating the slope at low levels of risk for the toxic effect induced by the use of a disinfectant. For the proposed procedure to estimate the optimum disinfectant dose, it is not necessary to have absolute values for the losses due to microbial-induced or disinfectant-induced illness, but only relative losses are required. All aspects of the problem are amenable to sensitivity analyses. The issue of risk/benefit tradeoffs, more appropriately called risk/risk tradeoffs, does not appear to be an insurmountable problem.

Disease↗

PubMed2004

Evolutionary expressed sequence tag analysis of Drosophila female reproductive tracts identifies genes subjected to positive selection.

Genes whose products are involved in reproduction include some of the fastest-evolving genes found within the genomes of several organisms. Drosophila has long been used to study the function and evolutionary dynamics of genes thought to be involved in sperm competition and sexual conflict, two processes that have been hypothesized to drive the adaptive evolution of reproductive molecules. Several seminal fluid proteins (Acps) made in the Drosophila male reproductive tract show evidence of rapid adaptive evolution. To identify candidate genes in the female reproductive tract that may be involved in female-male interactions and that may thus have been subjected to adaptive evolution, we used an evolutionary bioinformatics approach to analyze sequences from a cDNA library that we have generated from Drosophila female reproductive tracts. We further demonstrate that several of these genes have been subjected to positive selection. Their expression in female reproductive tracts, presence of signal sequences/transmembrane domains, and rapid adaptive evolution indicate that they are prime candidates to encode female reproductive molecules that interact with rapidly evolving male Acps.

Animals↗

PubMed2000

Solvent accessibility and purifying selection within proteins of Escherichia coli and Salmonella enterica.

The neutral theory of molecular evolution predicts that variation within species is inversely related to the strength of purifying selection, but the strength of purifying selection itself must be related to physical constraints imposed by protein folding and function. In this paper, we analyzed five enzymes for which polymorphic sequence variation within Escherichia coli and/or Salmonella enterica was available, along with a protein structure. Single and multivariate logistic regression models are presented that evaluate amino acid size, physicochemical properties, solvent accessibility, and secondary structure as predictors of polymorphism. A model that contains a positive coefficient of association between polymorphism and solvent accessibility and separate intercepts for each secondary-structure element is sufficient to explain the observed variation in polymorphism between sites. The model predicts an increase in the probability of amino acid polymorphism with increasing solvent accessibility for each protein regardless of physicochemical properties, secondary-structure element, or size of the amino acid. This result, when compared with the distribution of synonymous polymorphism, which shows no association with solvent accessibility, suggests a strong decrease in purifying selection with increasing solvent accessibility.

Aldose-Ketose Isomerases↗

PubMed2005

A quantization method based on threshold optimization for microarray short time series.

BACKGROUND: Reconstructing regulatory networks from gene expression profiles is a challenging problem of functional genomics. In microarray studies the number of samples is often very limited compared to the number of genes, thus the use of discrete data may help reducing the probability of finding random associations between genes. RESULTS: A quantization method, based on a model of the experimental error and on a significance level able to compromise between false positive and false negative classifications, is presented, which can be used as a preliminary step in discrete reverse engineering methods. The method is tested on continuous synthetic data with two discrete reverse engineering methods: Reveal and Dynamic Bayesian Networks. CONCLUSION: The quantization method, evaluated in comparison with two standard methods, 5% threshold based on experimental error and rank sorting, improves the ability of Reveal and Dynamic Bayesian Networks to identify relations among genes.

Algorithms↗