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PubMed1999

Direct power comparisons between simple LOD scores and NPL scores for linkage analysis in complex diseases.

Several methods have been proposed for linkage analysis of complex traits with unknown mode of inheritance. These methods include the LOD score maximized over disease models (MMLS) and the "nonparametric" linkage (NPL) statistic. In previous work, we evaluated the increase of type I error when maximizing over two or more genetic models, and we compared the power of MMLS to detect linkage, in a number of complex modes of inheritance, with analysis assuming the true model. In the present study, we compare MMLS and NPL directly. We simulated 100 data sets with 20 families each, using 26 generating models: (1) 4 intermediate models (penetrance of heterozygote between that of the two homozygotes); (2) 6 two-locus additive models; and (3) 16 two-locus heterogeneity models (admixture alpha = 1.0,.7,.5, and.3; alpha = 1.0 replicates simple Mendelian models). For LOD scores, we assumed dominant and recessive inheritance with 50% penetrance. We took the higher of the two maximum LOD scores and subtracted 0.3 to correct for multiple tests (MMLS-C). We compared expected maximum LOD scores and power, using MMLS-C and NPL as well as the true model. Since NPL uses only the affected family members, we also performed an affecteds-only analysis using MMLS-C. The MMLS-C was both uniformly more powerful than NPL for most cases we examined, except when linkage information was low, and close to the results for the true model under locus heterogeneity. We still found better power for the MMLS-C compared with NPL in affecteds-only analysis. The results show that use of two simple modes of inheritance at a fixed penetrance can have more power than NPL when the trait mode of inheritance is complex and when there is heterogeneity in the data set.

Gene Frequency↗
PubMed2001

Spectral analysis of visual potentials evoked by pattern-reversal checkerboard in juvenile patients with headache.

Changes in visual evoked potentials, mainly affecting the amplitude of the major positive wave, are referred to by many authors and are related to the pathophysiological basis of primary headache. We performed both transient pattern-reversal visual evoked potentials and spectral analysis by means of fast Fourier transform of 8-Hz steady-state pattern-reversal visual evoked potentials in 34 children affected with migraine (14 with aura, 20 without aura), and compared them with 14 patients with tension-type headache and 10 healthy subjects. The amplitude of the response to the transient stimulation (P100) was higher and the latency shorter in the patients with headache compared with the controls, but the difference was not statistically significant. The absolute power of the first harmonic (1F) obtained by the spectral analysis of the steady-state stimulation was increased in all the patients with headache compared with the controls, and the increase was significant in patients with migraine. These data seem to confirm the hypothesis of abnormal processing of visual input in migraineurs and could be interpreted as neurophysiological support for the theory that different headache types are related conditions. Furthermore, the spectral analysis of steady-state pattern-reversal visual evoked potentials could be proposed as a test to diagnose migraine.

Child↗
PubMed2002

Clinical trials, immunosuppression and renal transplantation: new trends in design and analysis.

Clinical trials provide a framework to search for more effective and less toxic immunosuppressive agents to control renal transplant rejection. Some methodological aspects are presented. Patient selection and the choice of study endpoints are discussed with emphasis on standardized definitions and classification of histopathology, and on qualification and quantification of chronic rejection. Choosing a Bayesian or a frequentist approach and the afferent hypotheses is discussed together with the interpretation of a P-value and a confidence interval. Strategies for limiting the number of patients, increasing power and feasibility are reviewed, including discussion of surrogate endpoints. New approaches to statistical analysis are then presented, including intention-to-treat versus per-protocol analysis, analysis of correlated data, dependent censoring, and meta-analysis applied to renal transplantation. Pharmacoeconomics are finally introduced as necessary for implementation of decision making regarding therapeutic strategies. Reporting research increases its standards, and the CONSORT (Consolidated Standards of Reporting Trials) and QOROM (Quality of Reporting of Meta-analyses) criteria are to be integrated in the process of clinical trial procedures. In conclusion, observational studies are presented as part of an evidence-based approach in the hierarchy of evidence, keeping in mind that high quality, randomized, controlled trials are still necessary to decrease uncertainty in the field of renal transplantation.

Child↗
PubMed2001

VAPSE-based analysis: a two-phased candidate gene approach for elucidating genetic predisposition to complex disorders.

The extraordinary success of linkage analysis in diseases with Mendelian inheritance has not extended readily to the genetics of common complex diseases. VAPSE-based analysis is a type of candidate gene approach that represents an alternative strategy by which genetic mechanisms can be defined despite the presence of substantial genetic heterogeneity. Recent advances in mutation screening and statistical methodology have enhanced substantially the efficiency and power of this approach. The "bread and butter" of VAPSE-based analysis is genotype-to-phenotype searches in large populations with computerized medical records.

Alzheimer Disease↗
PubMed2005

Statistical analysis of data from studies on experimental autoimmune encephalomyelitis.

Research in multiple sclerosis often employs animal models of the disease, especially experimental autoimmune encephalomyelitis (EAE) in rodents. The statistical analysis procedures chosen for these studies are often suboptimal, either because of violations of the assumptions of the procedure or because the analysis selected is inappropriate for the research question. In this paper, we discuss the types of research questions frequently asked in EAE studies and suggest appropriate and useful research designs and statistical methods that will optimize the information contained within the data. We also discuss other troublesome issues such as missing data, atypical disease profiles, and power analysis.

Animals↗
PubMed2006

Interpreter of maladies: redescription mining applied to biomedical data analysis.

Comprehensive, systematic and integrated data-centric statistical approaches to disease modeling can provide powerful frameworks for understanding disease etiology. Here, one such computational framework based on redescription mining in both its incarnations, static and dynamic, is discussed. The static framework provides bioinformatic tools applicable to multifaceted datasets, containing genetic, transcriptomic, proteomic, and clinical data for diseased patients and normal subjects. The dynamic redescription framework provides systems biology tools to model complex sets of regulatory, metabolic and signaling pathways in the initiation and progression of a disease. As an example, the case of chronic fatigue syndrome (CFS) is considered, which has so far remained intractable and unpredictable in its etiology and nosology. The redescription mining approaches can be applied to the Centers for Disease Control and Prevention's Wichita (KS, USA) dataset, integrating transcriptomic, epidemiological and clinical data, and can also be used to study how pathways in the hypothalamic-pituitary-adrenal axis affect CFS patients.

Algorithms↗
PubMed2006

Ranking analysis of microarray data: a powerful method for identifying differentially expressed genes.

Microarray technology provides a powerful tool for the expression profile of thousands of genes simultaneously, which makes it possible to explore the molecular and metabolic etiology of the development of a complex disease under study. However, classical statistical methods and technologies fail to be applicable to microarray data. Therefore, it is necessary and motivating to develop powerful methods for large-scale statistical analyses. In this paper, we described a novel method, called Ranking Analysis of Microarray Data (RAM). RAM, which is a large-scale two-sample t-test method, is based on comparisons between a set of ranked T statistics and a set of ranked Z values (a set of ranked estimated null scores) yielded by a "randomly splitting" approach instead of a "permutation" approach and a two-simulation strategy for estimating the proportion of genes identified by chance, i.e., the false discovery rate (FDR). The results obtained from the simulated and observed microarray data show that RAM is more efficient in identification of genes differentially expressed and estimation of FDR under undesirable conditions such as a large fudge factor, small sample size, or mixture distribution of noises than Significance Analysis of Microarrays.

Animals↗
PubMed2003

An evaluation of methods for the stratified analysis of clustered binary data in community intervention trials.

A simulation study is conducted in a community intervention setting. Several methods of stratified analysis of clustered binary data are compared in terms of empirical significance and empirical power levels. They are the Mantel-Haenszel test statistic (chi(2) (MH)), the adjusted Mantel-Haenszel test statistic of Donald-Donner (chi(2) (DD)), Rao-Scott (chi(2) (RSN) and chi(2) (RSP)), and Zhang-Boos (chi(2) (ZBN) and chi(2) (ZBP)), Wald (chi(2) (W)), robust Wald (chi(2) (RW)), score (chi(2) (S)), robust score (chi(2) (RS)), and the test statistic based on generalized linear mixed model (GLMM) (chi(2) (GLMM)). When rho not equal 0, chi(2) (MH) has inflated type I error, and it should not be used when observations are correlated. The results also warn of the use of chi(2) (RSN) and chi(2) (RW) due to their poor performance in terms of empirical significance level. chi(2) (ZBP) and chi(2) (GLMM) have better empirical significance levels as compared to other statistics; however, chi(2) (ZBP) tends to have lower empirical powers than other statistics when the number of clusters (N) is less than 24. chi(2) (RSP) provides the highest empirical powers when rho > or = 0.1 and N < or = 12. When rho < or = 0.01, we recommend the use of chi(2) (RS) and chi(2) (GLMM) since they have better overall performance in terms of empirical significance levels and empirical power levels.

Adolescent↗
PubMed2003

The analysis of the influence of birth order and other factors in multiple birth data.

We compare three methods which can be used to analyse the influence of birth order and other factors on health outcomes in multiple birth data. We consider marginal models based on generalized estimating equations (GEE) and two kinds of conditional models; conditional logistic regression (CLR) and mixed effects models (MEM). Although the models may be written similarly, there are differences in both the interpretation and the numerical values assigned to the parameters. Our main conclusion is that GEE and MEM are preferable to CLR since they provide more flexibility in dealing with missing values and covariates. The choice between GEE and MEM is less obvious and depends on the data, the parameter of interest and statistical power.

Birth Order↗
PubMed2003

Vitreous amino acid concentrations in patients with glaucoma undergoing vitrectomy.

OBJECTIVE: To measure vitreous concentrations of glutamate and other amino acids in patients with glaucoma undergoing vitrectomy. METHODS: Undiluted vitreous samples were collected from patients undergoing vitrectomy at the University of Iowa (Iowa City) between 1997 and 1998 (n = 69). Vitreous concentrations of 16 amino acids, including glutamate, were determined using high-pressure liquid chromatography. Patients with a history of diabetes mellitus were excluded from the analysis. The study group consisted of those with a history of glaucoma (n = 8), and the control group included those with an epiretinal membrane and/or macular hole with no history of glaucoma (n = 17). Comparison of amino acid concentrations between the 2 groups was performed using a multifactor main effects model that adjusted for the effect of 10 selected covariates. Power analysis was done to determine the level of significant difference in amino acid concentrations. RESULTS: The glaucoma group comprised vitreal specimens from patients with primary open-angle (n = 3) and angle-closure glaucomas that included aqueous misdirection (n = 2), uveitis with secondary angle-closure (n = 2), and Axenfeld Rieger syndrome (n = 1). Indications for vitrectomy in this group included epiretinal membrane, retinal detachment, aqueous misdirection, and uveitis. The control group included specimens from patients with a macular hole (n = 11) and epiretinal membrane (n = 7), with 1 eye having both. Surgical indications in controls were macular hole, retinal detachment, and epiretinal membrane. The mean +/- SD levels of vitreous glutamate, glycine, gamma-aminobutyric acid, and alanine were 6.1 +/- 2.4, 16.3 +/- 7.5, 0.8 +/- 0.3, and 260.5 +/- 101.9 microM, respectively, in glaucoma and 5.2 +/- 2.3, 8.5 +/- 2.5, 0.6 +/- 0.2, and 159.5 +/- 54.9 microM in controls (P >.05 for all). None of the 16 amino acid concentrations measured showed a statistically significant difference between glaucoma and controls (P values between.06 and >.99). A power analysis indicated that a 1.8-fold elevation in the glutamate level was needed to reach significance. MAIN OUTCOME MEASURES: Vitreous amino acid concentrations. CONCLUSIONS: None of the 16 amino acids measured, including glutamate, were significantly elevated in the vitreous of glaucomatous eyes compared with controls. Our results are not consistent with the simple hypothesis of glutamate excitotoxicity in glaucoma. Instead, our findings indicate the dynamic nature of extracellular glutamate, whose concentration is dependent on complex mechanisms not yet fully understood. Further studies are needed to fully elucidate the role of glutamate in the pathogenesis of glaucoma.

Aged↗
PubMed2005

Improvement of mapping accuracy by unifying linkage and association analysis.

It is well known that pedigree/family data record information on the coexistence in founder haplotypes of alleles at nearby loci and the cotransmission from parent to offspring that reveal different, but complementary, profiles of the genetic architecture. Either conventional linkage analysis that assumes linkage equilibrium or family-based association tests (FBATs) capture only partial information, leading to inefficiency. For example, FBATs will fail to detect even very tight linkage in the case where no allelic association exists, while a violation of the assumption of linkage equilibrium will result in biased estimation and reduced efficiency in linkage mapping. In this article, by using a data augmentation technique and the EM algorithm, we propose a likelihood-based approach that embeds both linkage and association analyses into a unified framework for general pedigree data. Relative to either linkage or association analysis, the proposed approach is expected to have greater estimation accuracy and power. Monte Carlo simulations support our theoretical expectations and demonstrate that our new methodology: (1) is more powerful than either FBATs or classic linkage analysis; (2) can unbiasedly estimate genetic parameters regardless of whether association exists, thus remedying the bias and less precision of traditional linkage analysis in the presence of association; and (3) is capable of identifying tight linkage alone. The new approach also holds the theoretical advantage that it can extract statistical information to the maximum extent and thereby improve mapping accuracy and power because it integrates multilocus population-based association study and pedigree-based linkage analysis into a coherent framework. Furthermore, our method is numerically stable and computationally efficient, as compared to existing parametric methods that use the simplex algorithm or Newton-type methods to maximize high-order multidimensional likelihood functions, and also offers the computation of Fisher's information matrix. Finally, we apply our methodology to a genetic study on bone mineral density (BMD) for the vitamin D receptor (VDR) gene and find that VDR is significantly linked to BMD at the one-third region of the wrist.

Algorithms↗
PubMed2004

Optical assembling dynamics of individual polymer nanospheres investigated by single-particle fluorescence detection.

When a laser beam is focused into colloidal nanoparticle suspensions, a number of nanoparticles can be confined in the focal spot due to an optical gradient force. To reveal the assembling dynamics of polymer nanoparticles, the assembling process was investigated by analyzing the time evolution of the fluorescence intensity of the nanoparticles. In a dilute suspension of 100-nm-sized particles, a stepwise increase of the fluorescence intensity corresponding to a trapped single nanoparticle was observed. Statistical analysis revealed that the initial assembling rate of nanoparticles was proportional to the laser power and concentration of particle suspensions as expected from the diffusion equation. In 40-nm-sized particle suspensions, blinking profiles of fluorescence intensity were obtained, in which 2-3 particles were simultaneously trapped and then escaped from the focal point. It is considered from statistical analyses and two-dimensional Monte Carlo simulations that this assembling phenomenon is attributable to cluster formation assisted by optical trapping.

Journal Article↗
PubMed1997

Spectral electromyographic changes during a muscular strengthening training based on electrical stimulation.

The aim of this study is to describe the effects of neuromuscular electrical stimulation on electromyographic power spectrum evolution through a program of muscle strengthening. Ten healthy subjects received electrical stimulation of the quadriceps femoris muscle. Surface EMG was obtained from rectus femoris during maximum voluntary isometric contractions of quadriceps. Directly from EMG the Zero Crossing Rate and Root Mean Square (RMS) were calculated. Afterwards, the Mean Power Frequency and Median Frequency from EMG power spectrum were obtained using the Maximum Entropy method to estimate the spectrum. An analysis of variance for repeated measures revealed a statistical significance for RMS through the sessions and for spectral shifts towards higher frequencies between, before and after electrical stimulation. The evolution of power spectrum through sessions showed a curvilinear evolution, first decreasing towards lower frequencies and then increasing. These results suggest that electrical stimulation produces immediate changes on the motor unit: increasing the recruitment number and action potential velocity and a selective recruitment of type II fibres. During the strengthening program sessions two main phases were detected: the appearance and recovery from fatigue.

Adolescent↗
PubMed2002

Ciclograma: a tool for detection of rhythmicities in sleep/wake cycles.

The Fourier spectral analysis of binary time series (or rectangular signals) causes methodological problems, due to the fact that it is based on sinusoidal functions. We propose a new tool for the detection of periodicities in binary time series, focusing on sleep/wake cycles. This methodology is based on a weighted histogram of cycle durations. In this paper, we compare our methodology with the Fourier spectral analysis on the basis of simulated and real binary data sets of various lengths. We also provide an approach to statistical validation of the periodicities determined with our methodology. Furthermore, we analyze the discriminating power of both methods in terms of standard deviation. Our results indicate that the Ciclograma is much more powerful than Fourier analysis when applied on this type of time series.

Algorithms↗
PubMed1994

Noninvasive diagnosis of cardiac rejection through echocardiographic tissue characterization.

Ultrasonic tissue characterization is based on the assumption that microscopic tissue structures are identifiable by their acoustic properties. Our study group consisted of 23 cardiac recipients. Two-dimensional images were obtained within 2 hours of endomyocardial biopsy. The end-diastolic echo frames were digitized into the matrix of an image-processing system. A region of interest was placed into the anteroseptal segment of the left ventricle. The texture within the region of interest was analyzed using four major groups of texture analysis (first-order histogram, co-occurrence matrix, run-length statistic, and power spectrum). A total of 408 echocardiographic examinations were compared with histologic findings. The 117 initially calculated texture parameters were reduced incrementally using a series of discriminant analyses. A set of three texture parameters (inverse difference moment undirected, run-length nonuniformity vertical, and sector sum) was able to describe changed echocardiographic texture when rejection occurred. Using these three parameters, echocardiographic sensitivity was 89.0% and specificity was 83.6% for moderate rejection. We conclude that cardiac rejection is associated with echocardiographic texture alterations and that serial echocardiographic texture analysis can reliably identify rejection.

Adult↗
PubMed2000

Social motives and cognitive power-sex associations: predictors of aggressive sexual behavior.

The present study investigated whether implicit social motives and cognitive power-sex associations would predict self-reports of aggressive sexual behavior. Participants wrote stories in response to Thematic Apperception Test pictures, which were scored for power and affiliation-intimacy motives. They also completed a lexical-decision priming task that provided an index of the strength of the cognitive association between the concepts of "power" and "sexuality." For men, high levels of power motivation and strong power-sex associations predicted more frequent aggression. There was also an interaction: Power motivation was unrelated to aggression for men with the weakest power-sex associations. For women, high levels of affiliation-intimacy motivation were associated with more frequent aggression. Strong power-sex associations were also predictive for women but only when affiliation-intimacy motivation was high.

Adult↗