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PubMed2005

Dual multiple change-point model leads to more accurate recombination detection.

MOTIVATION: We introduce a dual multiple change-point (MCP) model for recombination detection among aligned nucleotide sequences. The dual MCP model is an extension of the model introduced previously by Suchard and co-workers. In the original single MCP model, one change-point process is used to model spatial phylogenetic variation. Here, we show that using two change-point processes, one for spatial variation of tree topologies and the other for spatial variation of substitution process parameters, increases recombination detection accuracy. Statistical analysis is done in a Bayesian framework using reversible jump Markov chain Monte Carlo sampling to approximate the joint posterior distribution of all model parameters. RESULTS: We use primate mitochondrial DNA data with simulated recombination break-points at specific locations to compare the two models. We also analyze two real HIV sequences to identify recombination break-points using the dual MCP model.

Algorithms↗
PubMedDate not supplied

Probabilistic sensitivity analysis for decision trees with multiple branches: use of the Dirichlet distribution in a Bayesian framework.

In structuring decision models of medical interventions, it is commonly recommended that only 2 branches be used for each chance node to avoid logical inconsistencies that can arise during sensitivity analyses if the branching probabilities do not sum to 1. However, information may be naturally available in an unconditional form, and structuring a tree in conditional form may complicate rather than simplify the sensitivity analysis of the unconditional probabilities. Current guidance emphasizes using probabilistic sensitivity analysis, and a method is required to provide probabilistic probabilities over multiple branches that appropriately represents uncertainty while satisfying the requirement that mutually exclusive event probabilities should sum to 1. The authors argue that the Dirichlet distribution, the multivariate equivalent of the beta distribution, is appropriate for this purpose and illustrate its use for generating a fully probabilistic transition matrix for a Markov model. Furthermore, they demonstrate that by adopting a Bayesian approach, the problem of observing zero counts for transitions of interest can be overcome.

Asthma↗
PubMed2005

Bayesian normalization and identification for differential gene expression data.

Commonly accepted intensity-dependent normalization in spotted microarray studies takes account of measurement errors in the differential expression ratio but ignores measurement errors in the total intensity, although the definitions imply the same measurement error components are involved in both statistics. Furthermore, identification of differentially expressed genes is usually considered separately following normalization, which is statistically problematic. By incorporating the measurement errors in both total intensities and differential expression ratios, we propose a measurement-error model for intensity-dependent normalization and identification of differentially expressed genes. This model is also flexible enough to incorporate intra-array and inter-array effects. A Bayesian framework is proposed for the analysis of the proposed measurement-error model to avoid the potential risk of using the common two-step procedure. We also propose a Bayesian identification of differentially expressed genes to control the false discovery rate instead of the ad hoc thresholding of the posterior odds ratio. The simulation study and an application to real microarray data demonstrate promising results.

Bayes Theorem↗
PubMed2005

Bayesian implementation of a genetic model-free approach to the meta-analysis of genetic association studies.

A genetic model-free method for the meta-analysis of genetic association studies is described that estimates the mode of inheritance from the data rather than assuming that it is known. For a bi-allelic polymorphism, with G as risk allele and g as wild-type, the genetic model depends on the ratio of the two log odds ratios, lambda = log OR(Gg)/log OR(GG), where OR(GG) compares GG with gg and OR(Gg) compares Gg with gg. Modelling log OR(GG) as a random effect creates a hierarchical model that can be implemented within a Bayesian framework. In Bayesian modelling, vague prior distributions have to be specified for all unknown parameters when no external information is available. When the data are sparse even supposedly vague prior distributions may have an influence on the posterior estimates. We investigate the impact of different vague prior distributions for the between-study standard deviation of log OR(GG) and for lambda, by considering three published meta-analyses and associated simulations. Our results show that depending on the characteristics of the meta-analysis the results may indeed be sensitive to the choice of vague prior distribution for either parameter. Genetic association studies usually use a case-control design that should be analysed by the corresponding retrospective likelihood. However, under some circumstances the prospective likelihood has been shown to produce identical results and it is usually preferred for its simplicity. In our meta-analyses the two likelihoods give very similar results.

Bayes Theorem↗
PubMed2006

Age-period-cohort analysis of cervical cancer incidence in Hong Kong from 1972 to 2001 using maximum likelihood and Bayesian methods.

OBJECTIVE: To examine the secular effects of opportunistic screening for cervical cancer in a rich, developed community where most other such populations have long adopted organised screening. DESIGN, SETTING, AND PARTICIPANTS: The analysis was based on 15 140 cases of invasive cervical cancer from 1972 to 2001. The effects of chronological age, time period, and birth cohort were decomposed using both maximum likelihood and Bayesian methods. RESULTS: The overall age adjusted incidence decreased from 24.9 in 1972-74 to 9.5 per 100,000 in 1999-2001, in a log-linear fashion, yielding an average annual reduction of 4.0% (p<0.001) during the 30 year period. There were two second order and thus identifiable changes: (1) around the mid-1920s cohort curve representing an age-period interaction masquerading as a cohort change that denotes the first availability of Pap testing during the 1960s concentrated among women in their 40s; (2) a hook around the calendar years 1982-83 when cervical cytology became a standard screening test for pregnant women. CONCLUSIONS: Hong Kong's cervical cancer rates have declined since Pap tests first became available in the 1960s, most probably because of increasing population coverage over time and in successive generations in a haphazard fashion and punctuated by the systematic introduction of routine cytology as part of antenatal care in the 1980s.

Adult↗
PubMed2026

Multi-omics integration and colocalization analyses prioritize candidate molecular loci associated with hypothermia.

BACKGROUND: Hypothermia is a life-threatening condition lacking specific pharmacological treatments. This study aimed to prioritize genetically supported molecular loci associated with hypothermia and to explore their pharmacological tractability using multi-omics data. METHODS: Initially, 2532 druggable genes were curated from the Drug-Gene Interaction Database and established literature. These were cross-referenced with cis-eQTL and cis-pQTL datasets, encompassing 870,655 and 114,281 SNPs for blood, respectively, alongside 2379 shared SNPs across adipose, skeletal muscle, and heart tissues. Matched instrumental variables were integrated with hypothermia GWAS summary statistics for two-sample Mendelian randomization (MR) and Bayesian colocalization. Transcriptomic differential expression analysis (DEA) was subsequently conducted as an exploratory analysis of cold-exposure-associated expression changes. Database-derived compound annotations were systematically re-evaluated according to target specificity, established pharmacological mechanism, and concordance with the direction of the MR estimates. RESULTS: Among 671 gene-level MR tests, 36 genes reached nominal significance, whereas only ABCC8 remained significant after FDR correction. Colocalization was evaluable for 8 of these 36 genes, and 4 loci (COL18A1, SLC1A7, ADIPOQ, and MERTK) met the prespecified PP.H4>0.90 threshold. The remaining 28 loci were not evaluable because sufficient overlapping regional variants were unavailable after harmonization. Transcriptomic analysis identified altered expression of SLC1A3 and SLCO4A1 under cold exposure, although these findings did not directly validate the colocalization-supported loci. Re-evaluation of database-derived compound annotations did not identify any direct, selective, and directionally concordant drug-repurposing candidate for hypothermia. CONCLUSIONS: COL18A1, SLC1A7, ADIPOQ, and MERTK showed colocalization support among the 8 evaluable nominal MR-associated loci. Because colocalization coverage was limited, these genes should be regarded as preliminary candidate loci rather than established therapeutic targets. The pharmacological annotations were indirect, non-selective, unsupported, or directionally inconsistent and should be interpreted solely as hypothesis-generating information.

Bayesian colocalization↗
PubMed2004

Ecdysozoan phylogeny and Bayesian inference: first use of nearly complete 28S and 18S rRNA gene sequences to classify the arthropods and their kin.

Relationships among the ecdysozoans, or molting animals, have been difficult to resolve. Here, we use nearly complete 28S+18S ribosomal RNA gene sequences to estimate the relations of 35 ecdysozoan taxa, including newly obtained 28S sequences from 25 of these. The tree-building algorithms were likelihood-based Bayesian inference and minimum-evolution analysis of LogDet-transformed distances, and hypotheses were tested wth parametric bootstrapping. Better taxonomic resolution and recovery of established taxa were obtained here, especially with Bayesian inference, than in previous parsimony-based studies that used 18S rRNA sequences (or 18S plus small parts of 28S). In our gene trees, priapulan worms represent the basal ecdysozoans, followed by nematomorphs, or nematomorphs plus nematodes, followed by Panarthropoda. Panarthropoda was monophyletic with high support, although the relationships among its three phyla (arthropods, onychophorans, tardigrades) remain uncertain. The four groups of arthropods-hexapods (insects and related forms), crustaceans, chelicerates (spiders, scorpions, horseshoe crabs), and myriapods (centipedes, millipedes, and relatives)-formed two well-supported clades: Hexapoda in a paraphyletic crustacea (Pancrustacea), and 'Chelicerata+Myriapoda' (a clade that we name 'Paradoxopoda'). Pycnogonids (sea spiders) were either chelicerates or part of the 'chelicerate+myriapod' clade, but not basal arthropods. Certain clades derived from morphological taxonomy, such as Mandibulata, Atelocerata, Schizoramia, Maxillopoda and Cycloneuralia, are inconsistent with these rRNA data. The 28S gene contained more signal than the 18S gene, and contributed to the improved phylogenetic resolution. Our findings are similar to those obtained from mitochondrial and nuclear (e.g., elongation factor, RNA polymerase, Hox) protein-encoding genes, and should revive interest in using rRNA genes to study arthropod and ecdysozoan relationships.

Animals↗
PubMed2004

Phylogeny and evolution of medical species of Candida and related taxa: a multigenic analysis.

Hemiascomycetes are species of yeasts within the order Saccharomycetales. The order encompasses disparate genera with a variety of life styles, including opportunistic human pathogens (e.g., Candida albicans), plant pathogens (e.g., Eremothecium gossypii), and cosmopolitan yeasts associated with water and decaying vegetation. To analyze the phylogeny of medically important species of yeasts, we selected 38 human pathogenic and related strains in the order Saccharomycetales. The DNA sequences of six nuclear genes were analyzed by maximum likelihood and Bayesian phylogenetic methods. The maximum likelihood analysis of the combined data for all six genes resolved three major lineages with significant support according to Bayesian posterior probability. One clade was mostly comprised of pathogenic species of Candida. Another major group contained members of the family Metschnikowiaceae as a monophyletic group, three species of Debaryomyces, and strains of Candida guilliermondii. The third clade consisted exclusively of species of the family Saccharomycetaceae. Analysis of the evolution of key characters indicated that both codon reassignment and coenzyme Q(9) likely had single origins with multiple losses. Tests of correlated character evolution revealed that these two traits evolved independently.

Bayes Theorem↗
PubMed1998

Approaches for optimal sequential decision analysis in clinical trials.

Unlike traditional approaches, Bayesian methods enable formal combination of expert opinion and objective information into interim and final analyses of clinical trial data. However, most previous Bayesian approaches have based the stopping decision on the posterior probability content of one or more regions of the parameter space, thus implicitly determining a loss and decision structure. In this paper, we offer a fully Bayesian approach to this problem, specifying not only the likelihood and prior distributions but appropriate loss functions as well. At each data monitoring point, we enumerate the available decisions and investigate the use of backward induction, implemented via Monte Carlo methods, to choose the optimal course of action. We then present a forward sampling algorithm that substantially eases the analytic and computational burdens associated with backward induction, offering the possibility of fully Bayesian optimal sequential monitoring for previously untenable numbers of interim looks. We show that forward sampling can always identify the optimal sequential strategy in the case of a one-parameter exponential family with a conjugate prior and monotone loss functions as well as the best member of a certain class of strategies when backward induction is infeasible. Finally, we illustrate and compare the forward and backward approaches using data from a recent AIDS clinical trial.

AIDS-Related Opportunistic Infections↗
PubMed1995

Cumulative meta-analysis of clinical trials builds evidence for exemplary medical care.

Cumulative meta-analysis of clinical trials (a Bayesian interpretation for accumulating evidence) will profoundly affect medical care by summarizing evidence in the assessment of technology innovations. Application of the technique to the randomized control trials (RCTs) of streptokinase treatment of acute myocardial infarction, reduction of peri-operative mortality by antibiotic prophylaxis, and prevention of death from bleeding peptic ulcers has revealed efficacy years before it was suspected by any other means. Arrangement of the trials according to event rate in the controls, effect sizes, quality of the trials or according to covariables of interest has supplied unique information. If carried out prospectively the technique supplies invaluable information regarding indications for another trial, the number of patients necessary to determine the validity of past trends, and the type of patients who might be benefitted. Careful examination in a cumulative manner of the prior trials can reduce the need for future large trials.

Bayes Theorem↗
PubMed2005

The surface free energy of dental gold-based materials.

OBJECTIVE: A gold composite material (Captek) has been developed which is claimed to resist plaque deposition. This study's aim was to compare the surface free energy (SFE) of this composite material with that of a type III casting gold. METHODS: Contact angle measurements, using the Wilhelmy technique, were made on four bar-shaped samples of each material, using five test liquids (diiodomethane, ethylene glycol, formamide, glycerol and water) and four measurements per sample per liquid. For each material, the dispersive, Lewis acid and Lewis base components of SFE (gamma(S)D, gamma(S)+, gamma(S)-, respectively) were estimated by least squares analysis and also by a Bayesian method. RESULTS: The gold composite material and the type III casting gold did not differ significantly in their gamma(S)D values (95% confidence interval for gold composite minus type III gold, -5.0 to +2.7). Both materials had low gamma(S)+ values in common with most solids. The gold composite had a significantly lower Lewis base component of SFE than the type III gold-8.4 mN/m for the former material compared to 19.1 mN/m for the latter (95% confidence interval for gold composite minus type III gold, -16.4 to -4.9). The difference between materials could be related to the lack of non-precious metals and the structure of the gold composite material. CONCLUSIONS: It is hypothesized that difference in gamma(S)- components of SFE may be an important parameter in predicting bacterial adhesion and plaque resistance. Methods that only determine SFE as a single parameter may be unable to differentiate adequately between dental restorative materials.

Bayes Theorem↗
PubMedDate not supplied

[Bayesian prediction of chloramphenicol blood levels in children with sepsis and malnutrition].

OBJECTIVE: To validate the population pharmacokinetic parameters of chloramphenicol in pediatric patients with sepsis and malnutrition (PPSM) using a bayesian forecasting program. DESIGN: Retrospective evaluation of predictive performance of a bayesian program in PPSM. SETTING: Tertiary care center. PATIENTS: Fifteen MPSP and ten NMPSP that receiving treatment with chloramphenicol. METHODS AND MAIN RESULTS: In the first part of the study, the medical records of 10 MPSP and 10 NMPSP who had received treatment with chloramphenicol were reviewed. The population pharmacokinetic parameter values for each group were estimated using a nonparametric expectation maximization algorithm (NPEM). In the second part, data gathered from five other MPSP receiving chloramphenicol were entered into a bayesian program. Chloramphenicol pharmacokinetic values for each of these five patients were estimated, first using the values of NMPSP as a priori distribution and then repeating the analysis using the MPSP values. The bayesian serum chloramphenicol concentrations predicted for each population model were compared with the actual peaks and troughs. The specific model for MPSP permitted forecasting the peak and trough serum chloramphenicol concentrations with less bias and a better precision compared with the NMPSP population model. CONCLUSIONS: These data indicate that chloramphenicol pharmacokinetics in PPSM can be predicted with minimal bias and good precision using a bayesian forecasting program, allowing a better control of the chloramphenicol serum concentrations. In addition, the limited number of samples required by the bayesian method may represent an important economical benefit for the patient.

Anti-Bacterial Agents↗
PubMed1999

Comparison of sotalol versus quinidine for maintenance of normal sinus rhythm in patients with chronic atrial fibrillation.

Many clinicians choose sotalol for the prevention of recurrences of atrial fibrillation (AF) as an alternative to quinidine, which has been associated with an increase in long-term mortality. Using meta-analytic techniques, we compared the effects on maintenance of sinus rhythm and mortality of combined groups of patients with chronic AF treated with sotalol, quinidine, or a control drug. Rates of conversion at 6 months and mortality were combined for each group after performing sensitivity analysis to test for homogeneity. Bayesian estimates and corresponding 95% credibility intervals were constructed to compare the probabilities of achieving sinus rhythm and mortality among groups. A literature search revealed 4 sotalol studies, 6 quinidine studies, and 5 control studies that met inclusion criteria established a priori. The point estimates for maintaining normal sinus rhythm (at 6 months) and corresponding credibility intervals for the 3 groups were sotalol 50% (range 42% to 58%), quinidine 53% (range 48% to 59%), and control 32% (range 26% to 39%). When combining and comparing mortality effects, the following studies met the same inclusion criteria: 4 sotalol studies, 9 quinidine studies, and 7 control studies. The point estimates and corresponding credibility intervals for mortality in the 3 groups were sotalol 2.2% (range 0.6% to 4.8%), quinidine 3.0% (range 1.7% to 4.7%), and control 1.1% (range 0.3% to 2.4%). Sotalol and quinidine are comparable in their ability to maintain sinus rhythm at 6 months (about 50%) and both agents are superior to control. There is a trend for both agents to increase mortality with long-term therapy. These data do not support choosing sotalol over quinidine as a safer alternative for preventing recurrences of chronic AF.

Anti-Arrhythmia Agents↗
PubMed2026

Bayesian Mendelian randomization reveals a protective effect of later age at first sexual intercourse against erectile dysfunction.

Erectile dysfunction (ED) is a prevalent health condition with significant psychosocial impacts, yet the causal role of age at first sexual intercourse (AFS) remains unclear. This study investigated the causal effect of AFS on the risk of ED using Mendelian randomization (MR) and Bayesian methods. Five traditional 2-sample MR analyses and 5 Bayesian MR analyses were performed using genome-wide association studies summary statistics from European populations. Sensitivity analyses included MR Egger regression, MR-pleiotropy residual sum and outlier, and Cochran Q-test. In mixed-sex cohorts (Groups 1 and 2), inverse variance weighted results demonstrated significant protective effects: odds ratio (OR)&#x2005;=&#x2005;0.626, &#x3b8;&#x2005;=&#x2005;-0.469, P&#x2005;=&#x2005;2.73&#x2005;&#xd7;&#x2005;10-6 for Group 1 and OR&#x2005;=&#x2005;0.617, &#x3b8;&#x2005;=&#x2005;-0.483, P&#x2005;=&#x2005;3.56&#x2005;&#xd7;&#x2005;10-5 for Group 2. The analyses for male-specific cohorts (Groups 3-10) showed weaker but consistent effects. For Group 3, OR&#x2005;=&#x2005;0.643, &#x3b8;&#x2005;=&#x2005;-0.442, P&#x2005;=&#x2005;.010. For Group 4, some instrumental variables associated with confounders were removed. The result became statistically insignificant: OR&#x2005;=&#x2005;0.680, &#x3b8;&#x2005;=&#x2005;-0.385, P&#x2005;=&#x2005;.064. For Group 5, the instrument selection criteria were relaxed and significance was retained: OR&#x2005;=&#x2005;0.695, &#x3b8;&#x2005;=&#x2005;-0.364, P&#x2005;=&#x2005;.016. For Groups 6 to 10, Bayesian MR was used to strengthen the inferences. In particular, for Group 8, which has a strongly informed prior, a posterior mean &#x3b8;&#x2005;=&#x2005;-0.358 and a 95% credible interval (-0.575, -0.136) were obtained. This study provides evidence supporting a causal protective effect of later AFS on ED risk. While traditional MR analyses in male-specific cohorts yielded suggestive results, Bayesian MR analyses, which allow for the integration of prior evidence, provided more precise estimates and strengthened the causal inference. These findings may inform future sexual health policies. Strengths include the use of male-specific cohorts and Bayesian enhancement for weak instruments. Limitations include reliance on European-ancestry data and inability to stratify ED subtypes.

Male↗
PubMed2004

Bayesian statistics for parasitologists.

Bayesian statistical methods are increasingly being used in the analysis of parasitological data. Here, the basis of differences between the Bayesian method and the classical or frequentist approach to statistical inference is explained. This is illustrated with practical implications of Bayesian analyses using prevalence estimation of strongyloidiasis and onchocerciasis as two relevant examples. The strongyloidiasis example addresses the problem of parasitological diagnosis in the absence of a gold standard, whereas the onchocerciasis case focuses on the identification of villages warranting priority mass ivermectin treatment. The advantages and challenges faced by users of the Bayesian approach are also discussed and the readers pointed to further directions for a more in-depth exploration of the issues raised. We advocate collaboration between parasitologists and Bayesian statisticians as a fruitful and rewarding venture for advancing applied research in parasite epidemiology and the control of parasitic infections.

Animals↗
PubMed2006

Extensive multiallelic analysis of the relationship between HLA-DRB1 and rheumatoid arthritis using a Bayesian partition model.

To analyse the association between individual HLA-DRB1 locus genotypes and rheumatoid arthritis (RA) susceptibility, taking in account the multiallelic nature of the shared epitope (SE). In total, 538 patients and 536 controls were genotyped for 12 alleles of the HLA-DRB1 locus. A Bayesian partition model and multivariate logistic models were used to assess the role of the SE and of its individual components. The SE was associated with RA susceptibility (odds ratio (OR) 2 versus 0 SE copy=9.99 (95 CI 4.69-15.30) and OR 1 versus 0 SE copy=3.16 (95% CI 2.42-4.12)). The Bayesian partition model supplied a permutation of the HLA-DRBA locus alleles ordered by increasing disease risk. Alleles associated with highest risks are those that code for the SE. The individual OR estimations for the HLA-DRB1 locus genotypes went from OR=1.00 (95% CI 1.00-1.25) for the less associated genotype to OR=21.40 (95% CI 8.02-65.79) for the most associated one. In conclusion, the allele order risk and the OR estimations for individual genotypes of the HLA-DRB1 locus were consistent with the SE theory. Using an exploratory statistical method without a priori hypothesis, our study allowed a detailed analysis of the multiallelic nature of the SE.

Adult↗
PubMed2006

Disease cluster detection: a critique and a Bayesian proposal.

This paper reviews issues in the analysis of non-focussed clustering, and proposes a novel approach to cluster modelling that can be used in a surveillance context. The novel approach involves the use of local likelihood models for the analysis of clustering in small area health data. Local likelihood is used when interdependence between data events at locations is modelled directly, as opposed to the modelling of a hidden process of cluster centres. This approach allows the use of conventional posterior sampling. It also allows a less parameterized approach to the form of clusters detected. The idea of a spatially dependent lasso which provides the local maxima for the aggregation of locations is considered as an approximation. The methods are applied to a well known data set and compared with Satscan, and a conditional logistic Bayesian model.

Air Pollutants↗