Biomedical subjects

Elizabeth A Thompson

Publications and source records attributed to Elizabeth A Thompson.

18 recordsLinked to original sources

PubMed2007

MCMC-based linkage analysis for complex traits on general pedigrees: multipoint analysis with a two-locus model and a polygenic component.

We describe a new program lm_twoqtl, part of the MORGAN package, for parametric linkage analysis with a quantitative trait locus (QTL) model having one or two QTLs and a polygenic component, which models additional familial correlation from other unlinked QTLs. The program has no restriction on number of markers or complexity of pedigrees, facilitating use of more complex models with general pedigrees. This is the first available program that can handle a model with both two QTLs and a polygenic component. Competing programs use only simpler models: one QTL, one QTL plus a polygenic component, or variance components (VC). Use of simple models when they are incorrect, as for complex traits that are influenced by multiple genes, can bias estimates of QTL location or reduce power to detect linkage. We compute the likelihood with Markov Chain Monte Carlo (MCMC) realization of segregation indicators at the hypothesized QTL locations conditional on marker data, summation over phased multilocus genotypes of founders, and peeling of the polygenic component. Simulated examples, with various sized pedigrees, show that two-QTL analysis correctly identifies the location of both QTLs, even when they are closely linked, whereas other analyses, including the VC approach, fail to identify the location of QTLs with modest contribution. Our examples illustrate the advantage of parametric linkage analysis with two QTLs, which provides higher power for linkage detection and better localization than use of simpler models.

Chromosome Mapping↗

PubMed2006

Multipoint linkage analysis with many multiallelic or dense diallelic markers: Markov chain-Monte Carlo provides practical approaches for genome scans on general pedigrees.

Computations for genome scans need to adapt to the increasing use of dense diallelic markers as well as of full-chromosome multipoint linkage analysis with either diallelic or multiallelic markers. Whereas suitable exact-computation tools are available for use with small pedigrees, equivalent exact computation for larger pedigrees remains infeasible. Markov chain-Monte Carlo (MCMC)-based methods currently provide the only computationally practical option. To date, no systematic comparison of the performance of MCMC-based programs is available, nor have these programs been systematically evaluated for use with dense diallelic markers. Using simulated data, we evaluate the performance of two MCMC-based linkage-analysis programs--lm_markers from the MORGAN package and SimWalk2--under a variety of analysis conditions. Pedigrees consisted of 14, 52, or 98 individuals in 3, 5, or 6 generations, respectively, with increasing amounts of missing data in larger pedigrees. One hundred replicates of markers and trait data were simulated on a 100-cM chromosome, with up to 10 multiallelic and up to 200 diallelic markers used simultaneously for computation of multipoint LOD scores. Exact computation was available for comparison in most situations, and comparison with a perfectly informative marker or interprogram comparison was available in the remaining situations. Our results confirm the accuracy of both programs in multipoint analysis with multiallelic markers on pedigrees of varied sizes and missing-data patterns, but there are some computational differences. In contrast, for large numbers of dense diallelic markers, only the lm_markers program was able to provide accurate results within a computationally practical time. Thus, programs in the MORGAN package are the first available to provide a computationally practical option for accurate linkage analyses in genome scans with both large numbers of diallelic markers and large pedigrees.

Alleles↗

PubMed2006

Complementary therapy use by patients and parents of children with asthma and the implications for NHS care: a qualitative study.

BACKGROUND: Patients are increasingly using complementary therapies, often for chronic conditions. Asthma is the most common chronic condition in the UK. Previous research indicates that some asthma patients experience gaps in their NHS care. However, little attention has been given to how and why patients and parents of children with asthma use complementary therapies and the implications for NHS care. METHODS: Qualitative study, comprising 50 semi-structured interviews with a purposeful sample of 22 adults and 28 children with asthma (plus a parent), recruited from a range of NHS and non-NHS settings in Bristol, England. Data analysis was thematic, drawing on the principles of constant comparison. RESULTS: A range of complementary therapies were being used for asthma, most commonly Buteyko breathing and homeopathy. Most use took place outside of the NHS, comprising either self-treatment or consultation with private complementary therapists. Complementary therapies were usually used alongside not instead of conventional asthma treatment. A spectrum of complementary therapy users emerged, including "committed", "pragmatic" and "last resort" users. Motivating factors for complementary therapy use included concerns about conventional NHS care ("push factors") and attractive aspects of complementary therapies ("pull factors"). While participants were often uncertain whether therapies had directly helped their asthma, breathing techniques such as the Buteyko Method were most notably reported to enhance symptom control and enable reduction in medication. Across the range of therapies, the process of seeking and using complementary therapies seemed to help patients in two broad ways: it empowered them to take greater personal control over their condition rather than feel dependant on medication, and enabled exploration of a broader range of possible causes of their asthma than commonly discussed within NHS settings. CONCLUSION: Complementary therapy use reflects patients' and parents' underlying desire for greater self-care and need of opportunities to address some of their concerns regarding NHS asthma care. Self-management of chronic conditions is increasingly promoted within the NHS but with little attention to complementary therapy use as one strategy being used by patients and parents. With their desire for self-help, complementary therapy users are in many ways adopting the healthcare personas that current policies aim to encourage.

Adult↗

PubMed2006

A parallel approach to STAP implementation for fMRI data.

PURPOSE: To exploit the capabilities of parallel processing in applying the space-time adaptive processing (STAP) algorithm, previously explored on a small scale for functional magnetic resonance imaging (fMRI) applications, to conventional size fMRI data sets. MATERIALS AND METHODS: STAP is a two-dimensional filter that is able to locate fMRI activations in both space and frequency. It is applied here for the construction of brain activation maps in fMRI using Visual Age C, incorporating Engineering and Scientific Subroutine Library (ESSL) functions, compiled in 64-bit, and executed on an IBM SP supercomputer. RESULTS: Computer simulations incorporating actual MRI noise indicate that STAP, incorporated using the method of steepest descent, is feasible on conventional size data sets and exhibits an improvement in detecting activations over the more traditional cross correlation method of fMRI analysis when the response is unknown. CONCLUSION: STAP is feasible on traditional size fMRI data sets and useful in elucidating spatial and temporal connectivity.

Algorithms↗

PubMed2006

Expectations of patients and parents of children with asthma regarding access to complementary therapy information and services via the NHS: a qualitative study.

OBJECTIVE: To explore the expectations of patients and parents of children with asthma regarding access to complementary therapies via the NHS. METHODS: Fifty semi-structured interviews with adults and parents of children with asthma, from a range of health-care settings, including users and non-users of complementary therapies. Interviews were recorded, transcribed verbatim and the data were analysed thematically. RESULTS: Thirty-one patients were using complementary therapies for asthma, six were using complementary therapies for other health problems and 13 were non-users. Various therapies were used for asthma, most commonly homeopathy and breathing techniques, predominantly outside the NHS. Two broad themes emerging from the data were expectations about access to information and knowledge about complementary therapies via NHS health professionals, and expectations regarding access to complementary therapy services via the NHS. As a minimum, the majority of participants wanted NHS health professionals to be more 'open' towards and know more about complementary therapies than their patients - perceived as not currently usual. Most were positive about greater NHS access to complementary therapy services, for enhancing patient choice, improving equality in access for less affluent patients and facilitating patients' self-help. Participants who were highly sceptical about complementary therapies argued that lack of scientific evidence of effectiveness prohibited the need for greater complementary therapy knowledge or service provision within the NHS. Alongside their expectations, patients and parents expressed realistic views about facilitators and barriers to greater access. CONCLUSIONS: While health service planners and providers often express reservations about the value of complementary therapies, it is important to take patients' preferences into account if policy discourses regarding patient-centred care and choice are to be realized in practice.

Adult↗

PubMed2006

Improving estimates of genetic maps: a maximum likelihood approach.

As a result of previous large, multipoint linkage studies there is a substantial amount of existing marker data. Due to the increased sample size, genetic maps estimated from these data could be more accurate than publicly available maps. However, current methods for map estimation are restricted to data sets containing pedigrees with a small number of individuals, or cannot make full use of marker data that are observed at several loci on members of large, extended pedigrees. In this article, a maximum likelihood (ML) method for map estimation that can make full use of the marker data in a large, multipoint linkage study is described. The method is applied to replicate sets of simulated marker data involving seven linked loci, and pedigree structures based on the real multipoint linkage study of Abkevich et al. (2003, American Journal of Human Genetics 73, 1271-1281). The variance of the ML estimate is accurately estimated, and tests of both simple and composite null hypotheses are performed. An efficient procedure for combining map estimates over data sets is also suggested.

Algorithms↗

PubMed2005

Comparison of marker types and map assumptions using Markov chain Monte Carlo-based linkage analysis of COGA data.

We performed multipoint linkage analysis of the electrophysiological trait ECB21 on chromosome 4 in the full pedigrees provided by the Collaborative Study on the Genetics of Alcoholism (COGA). Three Markov chain Monte Carlo (MCMC)-based approaches were applied to the provided and re-estimated genetic maps and to five different marker panels consisting of microsatellite (STRP) and/or SNP markers at various densities. We found evidence of linkage near the GABRB1 STRP using all methods, maps, and marker panels. Difficulties encountered with SNP panels included convergence problems and demanding computations.

Alcoholism↗

PubMed2005

MCMC multilocus lod scores: application of a new approach.

On extended pedigrees with extensive missing data, the calculation of multilocus likelihoods for linkage analysis is often beyond the computational bounds of exact methods. Growing interest therefore surrounds the implementation of Monte Carlo estimation methods. In this paper, we demonstrate the speed and accuracy of a new Markov chain Monte Carlo method for the estimation of linkage likelihoods through an analysis of real data from a study of early-onset Alzheimer's disease. For those data sets where comparison with exact analysis is possible, we achieved up to a 100-fold increase in speed. Our approach is implemented in the program lm_bayes within the framework of the freely available MORGAN 2.6 package for Monte Carlo genetic analysis (http://www.stat.washington.edu/thompson/Genepi/MORGAN/Morgan.shtml).

Alzheimer Disease↗

PubMed2005

A pilot, randomized, double-blinded, placebo-controlled trial of individualized homeopathy for symptoms of estrogen withdrawal in breast-cancer survivors.

OBJECTIVE: To pilot an investigation of individualized homeopathy for symptoms of estrogen withdrawal in breast cancer survivors. DESIGN: Randomized, double-blinded, placebo-controlled trial. SETTING: Outpatient department of a National Health Service (NHS) homeopathic hospital. PARTICIPANTS: Fifty-seven (57) women met inclusion criteria and 53 were randomized to the study. INTERVENTION: After 2 weeks of baseline assessment, all participants received a consultation plus either oral homeopathic medicine or placebo, assessed every 4 weeks for 16 weeks. OUTCOME MEASURES: The primary outcome measures were the activity score and profile score of the Measure Yourself Medical Outcome Profile (MYMOP). RESULTS: Eighty-five percent (85%) (45/53) of women completed the study. There was no evidence of a difference seen between groups for either activity (adjusted difference =-0.4, 95% confidence interval CI -1.0 to 0.2, p = 0.17) or profile scores (adjusted difference = -0.4, 95% CI -0.9 to 0.1, p = 0.13) using this trial design, although post hoc power calculations suggests that 65-175 would be needed per group to detect differences of this magnitude with sufficient precision. Clinically relevant improvements in symptoms and mood disturbance were seen for both groups over the study period. CONCLUSION: Improvements were seen for symptom scores over the study period. However, presuming these improvements were caused by the individualized homeopathic approach, the study failed to show clearly that the specific effect of the remedy added further to the nonspecific effects of the consultation. Future trial design must ensure adequate power to account for the nonspecific impact of such complex individualized interventions while pragmatic designs may more readily answer questions of clinical and cost effectiveness.

Adult↗

PubMed2005

Homeopathic treatment for chronic disease: a 6-year, university-hospital outpatient observational study.

OBJECTIVE: The aim of this study was to assess health changes seen in routine homeopathic care for patients with a wide range of chronic conditions who were referred to a hospital outpatient department. DESIGN: This was an observational study of 6544 consecutive follow-up patients during a 6-year period. SETTING: Hospital outpatient unit within an acute National Health Service (NHS) Teaching Trust in the United Kingdom. PARTICIPANTS: Every patient attending the hospital outpatient unit for a follow-up appointment over the study period was included, commencing with their first follow-up attendance. MAIN OUTCOME MEASURE: Outcomes were based on scores on a 7-point Likert-type scale at the end of the consultation and were assessed as overall outcomes compared to the initial baseline assessments. RESULTS: A total of 6544 consecutive follow-up patients were given outcome scores. Of the patients 70.7% (n = 4627) reported positive health changes, with 50.7% (n = 3318) recording their improvement as better (+2) or much better (+3). CONCLUSIONS: Homeopathic intervention offered positive health changes to a substantial proportion of a large cohort of patients with a wide range of chronic diseases. Additional observational research, including studies using different designs, is necessary for further research development in homeopathy.

Adolescent↗

PubMed2004

A STAP algorithm approach to fMRI: a simulation study.

PURPOSE: To adapt the space-time adaptive processing (STAP) algorithm, previously developed in the field of sensor array processing and applied to radar signal processing, for use in construction of brain activation maps in functional magnetic resonance imaging (fMRI). MATERIALS AND METHODS: STAP is a two-dimensional filter in which both the spatial and temporal responses are controlled adaptively. It processes space-time data as a complete spatiotemporal set. Unlike presently used fMRI techniques, STAP locates activated regions both spatially and in frequency. RESULTS: Computer simulations incorporating actual MRI noise indicate that STAP exhibits a high degree of accuracy in detecting the small signal intensity changes inherent in fMRI. CONCLUSION: Because STAP processes space-time data as a single data matrix, it exhibits potential over currently available fMRI methods in providing a measure of the full spatiotemporal extent of a task-related activity.

Algorithms↗

PubMed2003

Approaches to mapping genetically correlated complex traits.

Our Markov chain Monte Carlo (MCMC) methods were used in linkage analyses of the Framingham Heart Study data using all available pedigrees. Our goal was to detect and map loci associated with covariate-adjusted traits log triglyceride (lnTG) and high-density lipoprotein cholesterol (HDL) using multipoint LOD score analysis, Bayesian oligogenic linkage analysis and identity-by-descent (IBD) scoring methods. Each method used all marker data for all markers on a chromosome. Bayesian linkage analysis detected a linkage signal on chromosome 7 for lnTG and HDL, corroborating previously published results. However, these results were not replicated in a classical linkage analysis of the data or by using IBD scoring methods.We conclude that Bayesian linkage analysis provides a powerful paradigm for mapping trait loci but interpretation of the Bayesian linkage signals is subjective. In the absence of a LOD score method accommodating genetically complex traits and linkage heterogeneity, validation of these signals remains elusive.

Cholesterol, HDL↗

PubMed2003

Estimation of the inbreeding coefficient through use of genomic data.

Many linkage studies are performed in inbred populations, either small isolated populations or large populations with a long tradition of marriages between relatives. In such populations, there exist very complex genealogies with unknown loops. Therefore, the true inbreeding coefficient of an individual is often unknown. Good estimators of the inbreeding coefficient (f) are important, since it has been shown that underestimation of f may lead to false linkage conclusions. When an individual is genotyped for markers spanning the whole genome, it should be possible to use this genomic information to estimate that individual's f. To do so, we propose a maximum-likelihood method that takes marker dependencies into account through a hidden Markov model. This methodology also allows us to infer the full probability distribution of the identity-by-descent (IBD) status of the two alleles of an individual at each marker along the genome (posterior IBD probabilities) and provides a variance for the estimates. We simulate a full genome scan mimicking the true autosomal genome for (1) a first-cousin pedigree and (2) a quadruple-second-cousin pedigree. In both cases, we find that our method accurately estimates f for different marker maps. We also find that the proportion of genome IBD in an individual with a given genealogy is very variable. The approach is illustrated with data from a study of demyelinating autosomal recessive Charcot-Marie-Tooth disease.

Charcot-Marie-Tooth Disease↗

PubMed2003

A score for Bayesian genome screening.

Bayesian Monte Carlo Markov chain (MCMC) techniques have shown promise in dissecting complex genetic traits. The methods introduced by Heath ([1997], Am. J. Hum. Genet. 61:748-760), and implemented in the program Loki, have been able to localize genes for complex traits in both real and simulated data sets. Loki estimates the posterior probability of quantitative trait loci (QTL) at locations on a chromosome in an iterative MCMC process. Unfortunately, interpretation of the results and assessment of their significance have been difficult. Here, we introduce a score, the log of the posterior placement probability ratio (LOP), for assessing oligogenic QTL detection and localization. The LOP is the log of the posterior probability of linkage to the real chromosome divided by the posterior probability of linkage to an unlinked pseudochromosome, with marker informativeness similar to the marker data on the real chromosome. Since the LOP cannot be calculated exactly, we estimate it in simultaneous MCMC on both real and pseudochromosomes. We investigate empirically the distributional properties of the LOP in the presence and absence of trait genes. The LOP is not subject to trait model misspecification in the way a lod score may be, and we show that the LOP can detect linkage for loci of small effect when the lod score cannot. We show how, in the absence of linkage, an empirical distribution of the LOP may be estimated by simulation and used to provide an assessment of linkage detection significance.

Bayes Theorem↗

PubMed2002

Impact of parental relationships in maximum lod score affected sib-pair method.

Many studies are done in small isolated populations and populations where marriages between relatives are encouraged. In this paper, we point out some problems with applying the maximum lod score (MLS) method (Risch, [1990] Am. J. Hum. Genet. 46:242-253) in these populations where relationships exist between the two parents of the affected sib-pairs. Characterizing the parental relationships by the kinship coefficient between the parents (f), the maternal inbreeding coefficient (alpha(m), and the paternal inbreeding coefficient (alpha(p)), we explored the relationship between the identity by descent (IBD) vector expected under the null hypothesis of no linkage and these quantities. We find that the expected IBD vector is no longer (0.25, 0.5, 0.25) when f, alpha(m), and alpha(p) differ from zero. In addition, the expected IBD vector does not always follow the triangle constraints recommended by Holmans ([1993] Am. J. Hum. Genet. 52:362-374). So the classically used MLS statistic needs to be adapted to the presence of parental relationships. We modified the software GENEHUNTER (Kruglyak et al. [1996] Am. J. Hum. Genet. 58: 1347-1363) to do so. Indeed, the current version of the software does not compute the likelihood properly under the null hypothesis. We studied the adapted statistic by simulating data on three different family structures: (1) parents are double first cousins (f=0.125, alpha(m)=alpha(p)=0), (2) each parent is the offspring of first cousins (f=0, alpha(m)=alpha(p)=0.0625), and (3) parents are related as in the pedigree from Goddard et al. ([1996] Am. J. Hum. Genet. 58:1286-1302) (f=0.109, alpha(m)=alpha(p)=0.0625). The appropriate threshold needs to be derived for each case in order to get the correct type I error. And using the classical statistic in the presence of both parental kinship and parental inbreeding almost always leads to false conclusions.

Computer Simulation↗

PubMed2002

The effect of population history on the lengths of ancestral chromosome segments.

An isolated population is a group of individuals who are descended from a founding population who lived some time ago. If the founding individuals are assumed to be noninbred and unrelated, a chromosome sampled from the population can be represented as a mosaic of segments of the original ancestral types. A population in which chromosomes are made up of a few long segments will exhibit linkage disequilibrium due to founder effect over longer distances than a population in which the chromosomes are made up of many short segments. We study the length of intact ancestral segments by obtaining the expected number of junctions (points where DNA of two distinct ancestral types meet) in a chromosome. Assuming random mating, we study analytically the effects of population age, growth patterns, and internal structure on the expected number of junctions in a chromosome. We demonstrate that the type of growth a population has experienced can influence the expected number of junctions, as can population subdivision. These effects are substantial only when population sizes are very small. We also develop an approximation to the variance of the number of junctions and show that the variance is large.

Chromosomes↗

PubMed2002

Homeopathy and the menopause.

Significant numbers of patients in developed countries use complementary, alternative, or unconventional medicine. Homeopathy is one of the most widespread and controversial of these therapies and has been used for over 150 years. There are two main theoretical tenets: the principle of "similars" and the use of dilutions called "potencies". The principle of "similars" states that patients with particular signs and symptoms can be cured if given a drug that produces the same signs and symptoms in a healthy individual. The second principle is that remedies retain biological activity if they are repeatedly diluted and agitated or shaken between each dilution. Data from case histories, observational studies and uncontrolled trials suggest that the homeopathic approach can offer a clinically relevant choice for women with menopausal symptoms and those with breast cancer whether they are taking tamoxifen or not. Randomised controlled trials are being conducted to investigate this potential benefit.

Journal Article↗

PubMed2001

Relationship inference from trios of individuals, in the presence of typing error.

Misspecification of relationships and of genotype data can cause problems in linkage analyses based on genome-scan data. Previous reports have focused on pairwise relationships and a simple error model. This article considers the increased information available from the joint analysis of trios of individuals, integrating this analysis with an error model that allows for the most common genotyping errors. Given observed marker phenotypes in a genome scan, computational methods are outlined both for likelihoods of relationships and for the posterior probabilities of underlying genotypes. The methods are applied to examples from two real data sets: one has been previously well analyzed, and, hence, Mendelian inconsistencies have been removed; the other typifies the pedigree and genotype errors encountered in the initial analyses of a study. It is demonstrated that the coupling of relationship inference and error detection is quite effective, that the error model is computationally practical, and that data on a third relative can often clarify relationships.

Alcoholism↗