Inference from single occasion capture experiments using genetic markers.

Accurate estimation of the size of animal populations is an important task in ecological science. Recent advances in the field of molecular genetics researches allow the use of genetic data to estimate the size of a population from a single capture occasion rather than repeated occasions as in the usual capture-recapture experiments. Estimating the population size using genetic data also has sometimes led to estimates that differ markedly from each other and also from classical capture-recapture estimates. Here, we develop a closed form estimator that uses genetic information to estimate the size of a population consisting of mothers and daughters, focusing on estimating the number of mothers, using data from a single sample. We demonstrate the estimator is consistent and propose a parametric bootstrap to estimate the standard errors. The estimator is evaluated in a simulation study and applied to real data. We also consider maximum likelihood in this setting and discover problems that preclude its general use.

Validation of a multigenic model to predict seizure control in newly treated epilepsy.

A multigenic classifier based on five single nucleotide polymorphisms (SNPs) was previously reported to predict treatment response in an Australian newly-diagnosed epilepsy cohort using a k-nearest neighbour (kNN) algorithm. We assessed the validity of this classifier in predicting response to initial antiepileptic drug (AED) treatment in two UK cohorts of newly-diagnosed epilepsy and investigated the utility of these five SNPs in predicting seizure control in general. The original Australian cohort constituted the training set for the classifier and was used to predict response to the first well-tolerated AED monotherapy in independently recruited UK cohorts (Glasgow, n=281; SANAD, n=491). A "leave-one-out" cross-validation was also employed, with training sets derived internally from the UK datasets. The multigenic classifier using the Australian cohort as the training set was unable to predict treatment response in either UK cohort. In the "leave-one-out" analysis, the five SNPs collectively predicted treatment response in both Glasgow and SANAD patients prescribed either carbamazepine or valproate (Glasgow OR=3.1, 95% CI=1.4-6.6, p=0.018; SANAD OR=2.8, 95% CI=1.3-6.1, p=0.048), but not those receiving lamotrigine (Glasgow OR=1.3, 95% CI=0.6-2.8, p=1.0; SANAD OR=2.2, 95% CI=0.9-5.4, p=0.36) or other AEDs (Glasgow OR=0.6, 95% CI=0.2-2.0, p=1.0; SANAD OR=1.9, 95% CI=0.9-4.2, p=0.36). The Australian-based multigenic kNN model is not predictive of initial treatment response in UK cohorts of newly-diagnosed epilepsy. However, the five SNPs identified in the original Australian study appear to collectively have a predictive influence in UK patients prescribed either carbamazepine or valproate.

Cormack-Jolly-Seber model with environmental covariates: a P-spline approach.

In capture-recapture models, survival and capture probabilities can be modelled as functions of time-varying covariates, such as temperature or rainfall. The Cormack-Jolly-Seber (CJS) model allows for flexible modelling of these covariates; however, the functional relationship may not be linear. We extend the CJS model by semi-parametrically modelling capture and survival probabilities using a frequentist approach via P-splines techniques. We investigate the performance of the estimators by conducting simulation studies. We also apply and compare these models with known semi-parametric Bayesian approaches on simulated and real data sets.

LOHAS: loss-of-heterozygosity analysis suite.

Detection of loss of heterozygosity (LOH) plays an important role in genetic, genomic and cancer research. We develop computational methods to estimate the proportion of homozygous SNP calls, identify samples with structural alterations and/or unusual genotypic patterns, cluster samples with close LOH structures and map the genomic segments bearing LOH by analyzing data of genome-wide SNP arrays or customized SNP arrays. In addition to cancer genetics/genomics, we also apply the methods to study long contiguous stretches of homozygosity (LCSH) in general populations. The LCSH analysis aids in the identification of samples with complex LCSH patterns indicative of nonrandom mating and/or meiotic recombination cold spots, separation of samples with different genetic backgrounds and sex, and mapping of regions of LCSH. Affymetrix Human Mapping 500K Set SNP data from an acute lymphoblastic leukemia study containing 304 cancer patients and 50 normal controls and from the HapMap Project containing 30 African trios, 30 Caucasian trios and 90 independent Asian samples were analyzed. We identified common gene regions of LOH, e.g., ETV6 and CDKN1B, and identified frequent regions of LCSH, e.g., the region that encompasses the centromeric gene desert region of chromosome 16. Unsupervised analysis separated cancer subtypes and ethnic subpopulations by patterns of LOH/LCSH. Simulation studies considering LOH width, effect size and heterozygous interference fraction were performed, and the results show that the proposed LOH association test has good test power and controls type 1 error well. The developed algorithms are packaged into LOHAS written in R and R GUI.

A nonparametric estimation of the infection curve.

Predicting the future course of an epidemic depends on being able to estimate the current numbers of infected individuals. However, while back-projection techniques allow reliable estimation of the numbers of infected individuals in the more distant past, they are less reliable in the recent past. We propose two new nonparametric methods to estimate the unobserved numbers of infected individuals in the recent past in an epidemic. The proposed methods are noniterative, easily computed and asymptotically normal with simple variance formulas. Simulations show that the proposed methods are much more robust and accurate than the existing back projection method, especially for the recent past, which is our primary interest. We apply the proposed methods to the 2003 Severe Acute Respiratory Syndorme (SARS) epidemic in Hong Kong.

A varying coefficient model to measure the effectiveness of mass media anti-smoking campaigns in generating calls to a Quitline.

BACKGROUND: Anti-smoking advertisements are an effective population-based smoking reduction strategy. The Quitline telephone service provides a first point of contact for adults considering quitting. Because of data complexity, the relationship between anti-smoking advertising placement, intensity, and time trends in total call volume is poorly understood. In this study we use a recently developed semi-varying coefficient model to elucidate this relationship. METHODS: Semi-varying coefficient models comprise parametric and nonparametric components. The model is fitted to the daily number of calls to Quitline in Victoria, Australia to estimate a nonparametric long-term trend and parametric terms for day-of-the-week effects and to clarify the relationship with target audience rating points (TARPs) for the Quit and nicotine replacement advertising campaigns. RESULTS: The number of calls to Quitline increased with the TARP value of both the Quit and other smoking cessation advertisement; the TARP values associated with the Quit program were almost twice as effective. The varying coefficient term was statistically significant for peak periods with little or no advertising. CONCLUSIONS: Semi-varying coefficient models are useful for modeling public health data when there is little or no information on other factors related to the at-risk population. These models are well suited to modeling call volume to Quitline, because the varying coefficient allowed the underlying time trend to depend on fixed covariates that also vary with time, thereby explaining more of the variation in the call model.

Multi-SNP pharmacogenomic classifier is superior to single-SNP models for predicting drug outcome in complex diseases.

OBJECTIVES: Most pharmacogenomic studies have attempted to identify single nucleotide polymorphism (SNP) markers that are predictive for treatment outcomes. It is, however, unlikely in complex diseases such as epilepsy, affecting heterogeneous populations, that a single SNP will adequately explain treatment outcomes. This study reports an approach to develop a multi-SNP model to classify treatment outcomes for such a disease and compares this with single-SNP models. METHODS: A prospectively collected dataset of outcomes in 115 patients newly treated for epilepsy, with genotyping for 4041 SNPs in 279 candidate genes, was used for the model development. A cross-validation-based methodology identified SNPs most influential in predicting seizure control after 1 year of drug treatment and then incorporated these into a multi-SNP classification model; using the k-Nearest Neighbour (kNN) supervised learning approach. The classifier was cross-validated to determine its effectiveness in predicting treatment outcome in the developmental cohort and then in two independent validation cohorts. In each, the classification by the multi-SNP model was compared with that of models using the individual SNPs alone. RESULTS: Five SNPs were selected for the multi-SNP model. Cross-validation showed that the multi-SNP model had a predictive accuracy of 83.5% in the developmental cohort and sensitivity and positive predictive values above 80% in both the independent validation cohorts. In all cases, the multi-SNP model classified the treatment outcomes better than those using any individual SNPs alone. CONCLUSION: The results show that a classifier using multiple SNPs can predict treatment outcome more reliably than single-SNP models. This multi-SNP classifier should be tested on data from newly diagnosed epilepsy populations to determine its broad clinical validity. Our method to developing a multi-SNP classifier could be applied to pharmacogenomic studies of other complex diseases.

A double-nonparametric procedure for estimating the number of delay-reported cases.

This paper proposes a double-nonparametric procedure to estimate the population size for reporting delay data without the specification of the incidence function and the delay distribution function. Asymptotic results of the proposed estimator are given. Simulation studies show that the proposed procedure works better than the existing estimating procedures. The method has been applied to a suicide reporting system in Hong Kong for improving monitoring and surveillance purposes.

Applications of additive semivarying coefficient models: monthly suicide data from Hong Kong.

A semivarying coefficient model for the monthly numbers of suicides in Hong Kong is developed and a new estimation procedure for estimating the parametric component is proposed. The estimators are examined in a small simulation study and fitted to monthly suicide data to estimate a nonparametric long-term trend and parametric seasonal and socioeconomic effects. Fitting the model detected interpretable structure in the data that is consistent with that driving public health policy. While exploratory, the analysis motivates the collection of more detailed data and the development of more sophisticated models to help determine target groups and strategies to reduce the suicide rate in Hong Kong.

Transcript levels of the intermediate size or grey zone fragile X mental retardation 1 alleles are raised, and correlate with the number of CGG repeats.

BACKGROUND: Grey zone or intermediate alleles are one of the three recognised classes of the X-linked fragile X mental retardation 1 (FMR1) gene showing intergenerational instability. These classes are defined according to the number of CGG repeats in the FMR1 5'-untranslated region. Although large CGG expansions (>200 repeats) cause a neurodevelopmental anomaly through silencing of the gene, resulting in a deficit of FMR1 specific protein, smaller expansions (approximately 55-200 repeats) are associated with an increased transcription and late-onset specific phenotypes. Those alleles with a CGG repeat number ranging between approximately 41 and 55 are relatively poorly defined with regard to both transcriptional and translational activity, and also potential phenotypic effects. METHODS AND RESULTS: Based on a sample of 33 males carrying FMR1 alleles within the grey zone range, defined here as 41-60 CGGs, we show an increased transcriptional activity relative to that seen in common alleles (5-40 CGGS). This is the first study to report a significant relationship between FMR1 mRNA levels and CGG repeat number within the grey zone range (p<0.001). From a piecewise linear regression model, the threshold for onset of the increase in mRNA levels as a function of CGG repeat size has been determined at approximately 39 repeats (standard error (SE) 3.24), and that for the reduction in the rate of this increase at approximately 54 repeats (SE 4.27). CONCLUSIONS: The ambiguities associated with the definition and transcription dynamics of the FMR1 gene within the grey zone range are dealt with. There may be specific phenotypes associated with the toxic "gain-of-function" effect of raised mRNA.

Molecular and cognitive predictors of the continuum of autistic behaviours in fragile X.

The distributions of scores for autistic behaviours obtained from the Autism Diagnostic Observation Scale-Generic (ADOS-G) were investigated in 147 males and females affected with the full mutation in the fragile X mental retardation 1 (FMR1) gene, in 59 individuals with the premutation, and in 42 non-fragile X relatives, aged 4-70 years. The scores representing communication and social interaction were continuously distributed across the two fragile X groups, and they were significantly elevated compared with the non-fragile X controls. Strong relationships were found between both these scores and FMRP deficits, but they became insignificant for social interaction, and the sum of social interaction and communication scores, when FSIQ was included as another predictor of autism scores. Other significant predictors of these scores in both sexes were those executive skills which related to verbal fluency, and to the regulation and control of motor behaviour. Overall, our data have shown that cognitive impairment, especially of verbal skills, best explains the comorbidity of autism and fragile X. This implies some more fundamental perturbations of specific neural connections which are essential for both specific behaviours and cognition. We also emphasize that FXS offers a unique molecular model for autism since FMRP regulates the translation of many other genes involved in synaptic formation and plasticity which should be natural targets for further exploration.

Effect of Turner's syndrome and X-linked imprinting on cognitive status: analysis based on pedigree data.

The effects of a monosomy of either the maternally or paternally derived X chromosome in Turner's syndrome (TS) on general neurocognitive status and some executive abilities were assessed using the maximum likelihood estimators for pedigree data. This method increases the power of analysis by accounting for the effect of background heritable variation on a trait. The sample comprised 42 females with regular non-mosaic X monosomy and their non-affected relatives. Wechsler neurocognitive scores and several executive function tests' scores, including the Behaviour Dyscontrol Scale (BDS-2), the Wisconsin Card Sorting Test (WCST), and the Rey Complex Figure Test (RCFT), were considered in the analysis. Results showed a significant effect of TS on all Wechsler index and subtest scores, with greatest deficits observed in Arithmetic, Block Design, Object Assembly and Picture Arrangement, and on the total BDS, RCFT and WCST scores, regardless of parental origin of the single X-chromosome. Our data also showed a significantly higher effect of a paternally derived X chromosome in diminishing the performance on several Wechsler scores relevant to verbal skills, which might suggest X-linked imprinting loci relevant to these skills. Possible reasons for the inconsistency of the results concerning X-linked imprinting of cognitive loci using TS patients are discussed, and the relevance of pedigree analysis to future studies of this problem is emphasized.

Magnetic resonance imaging study in older fragile X premutation male carriers.

Some carriers of a "premutation" allele of the FMR1 gene develop late-onset tremor/ataxia. We conducted a magnetic resonance imaging volumetric study in an unselected sample of eight older male premutation carriers. Volumetric measures, including total brain volume, and the volumes of cerebrum, cerebellum, and cerebral cortex all were significantly reduced in premutation carriers compared with similar data from 21 age-matched normal controls. Total brain and cerebral volumes were significantly related to the number of CGG repeats in the FMR1 gene. Moreover, increased hippocampal volume indicates this premutation may account for both neurodegenerative and neurodevelopmental changes.

A chain multinomial model for estimating the real-time fatality rate of a disease, with an application to severe acute respiratory syndrome.

It is well known that statistics using cumulative data are insensitive to changes. World Health Organization (WHO) estimates of fatality rates are of the above type, which may not be able to reflect the latest changes in fatality due to treatment or government policy in a timely fashion. Here, the authors propose an estimate of a real-time fatality rate based on a chain multinomial model with a kernel function. It is more accurate than the WHO estimate in describing fatality, especially earlier in the course of an epidemic. The estimator provides useful information for public health policy makers for understanding the severity of the disease or evaluating the effects of treatments or policies within a shorter time period, which is critical in disease control during an outbreak. Simulation results showed that the performance of the proposed estimator is superior to that of the WHO estimator in terms of its sensitivity to changes and its timeliness in reflecting the severity of the disease.

Phenotypic variation and FMRP levels in fragile X.

Data on the relationships between cognitive and physical phenotypes, and a deficit of fragile X mental retardation 1 (FMR1) gene-specific protein product, FMRP, are presented and discussed in context with earlier findings. The previously unpublished results obtained, using standard procedures of regression and correlations, showed highly significant associations in males between FMRP levels and the Wechsler summary and subtest scores and in females between these levels and the full-scale intelligence quotient (FSIQ), verbal and performance IQ, and some Wechsler subtest scores. The published results based on data from 144 extended families with fragile X, recruited from Australia and the United States within a collaborative NIH-supported project, were obtained using robust modification of maximum likelihood in pedigrees. The results indicated that processing speed, short-term memory, and the ability to control attention, especially in the context of regulating goal-directed behavior, may be primarily affected by the FMRP depletion. The effect of this depletion on physical phenotype was also demonstrated, especially on body and head height and extensibility of finger joints. It is recommended that further studies should rely on more accurate measures of FMRP levels, and use of larger samples, to overcome extensive variability in the data.

Effect of the fragile X status categories and the fragile X mental retardation protein levels on executive functioning in males and females with fragile X.

The effects of a fragile X disorder on executive function impairment were assessed in 144 extended families, which included individuals with fragile X premutation and full mutation and their relatives without fragile X. A modification of the maximum-likelihood estimators for pedigree data, as well as ordinal logistic regression, were used in data analysis. The most outstanding deficit, occurring especially in males, involved impaired capacity to use an intention to regulate purposeful behavior. This deficit occurred independently of general cognitive impairment but was related to depletion of fragile X mental retardation 1 gene protein product. The other executive function deficits were accounted for by the general cognitive impairment. Possible mechanisms of the effect of fragile X premutation on impairments of executive functioning are considered.

Effect of the deficits of fragile X mental retardation protein on cognitive status of fragile x males and females assessed by robust pedigree analysis.

The effect of the fragile X mental retardation 1 (FMR1) gene product (fragile X mental retardation protein [FMRP]) deficits on Full-Scale IQ (FSIQ) and FSIQ-adjusted Wechsler subtests and index scores in fragile X disorder were assessed using a robust modification of the maximum likelihood estimators for pedigree data. The results from 144 extended families have demonstrated a linear effect of progressively reduced levels of FMRP on the FSIQ and all subtest and summary scores in either gender. The effect of FMRP in decreasing FSIQ-adjusted subtest scores was highly significant for Digit Span, Symbol Search, Object Assembly, and Picture Arrangement, with a consistent trend in both genders. Heritability for FSIQ and unadjusted subtest scores estimated from the covariance model did not exceed 50% and varied widely from the highest for Verbal score to the lowest for Picture Completion score. Possible mechanisms by which FMRP deficit impacts on specific weaknesses in fragile X are considered on the basis of present data.

Relationship of birth weight and length with growth in height and body diameters from 5 years of age to maturity.

Birth weight and birth length were compared with several growth measures, including body height and weight, linear measures of limbs, body diameters, and head circumference, in 726 Melbourne schoolchildren of both sexes age 5-18 years. The analysis of relationships between three categories of birth length, weight, and growth measures were based on z-scores and performed by using analysis of variance and partial correlation. The data showed that birth length was correlated with body height and birth weight was correlated with head circumference; the relationships were weak and were less clear around the age corresponding to the peak height velocity in either sex. Further studies are needed to determine the common underlying mechanisms responsible for these associations. Am. J. Hum. Biol. 11:772-778, 1999. Copyright 1999 Wiley-Liss, Inc.