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PubMed2026

Polygenic Risk Scores for Incident Dementia in the Multi-Ethnic Study of Atherosclerosis.

Over 75 Alzheimer's disease (AD) and dementia-associated variants have been identified through genome-wide association studies, but the utility of polygenic risk scores (PRS) for predicting AD and dementia in diverse and admixed populations remains unclear. We compared how PRS approaches differing in p-value thresholds, variant weights, and source ancestry perform in predicting dementia in 6338 African American, Chinese, Hispanic, and White individuals from the Multi-Ethnic Study of Atherosclerosis. We tested clumping and thresholding (C+T) methods with varying parameters against Bayesian approaches (PRS-CS, PRS-CSx). We compared the ability of each method to predict incident dementia in all participants and in groups stratified by self-reported race/ethnicity. We additionally analyzed performance across groups stratified by estimated proportion of non-Finnish European (NFE)-like ancestry. Including more variants does not improve performance. We found comparable associations between dementia and PRS when comparing a C+T method with only 15 SNPs and PRS derived from Bayesian models that include > 800,000 SNPs (HR5e-08 = 1.18, 95% CI: 1.08-1.28; HRCSx = 1.17, 95% CI: 1.07-1.27). The p < 5e-08 C+T method was more strongly associated with incident dementia in populations genetically dissimilar from the source data (HRlowNFE_5e-08 = 1.27, 95% CI: 1.08-1.50; HRlowNFE_CSx = 1.12, 95% CI: 0.94-1.33). More selective PRS models using genome-wide significant SNPs may be preferable for dementia prediction in diverse populations.

Aged↗

PubMed2003

The analysis of profile data--revisited.

We revisit a former problem that led to much commentary regarding a proposed use of testing whether profiles for several groups in a repeated measurement scenario were parallel. Here we review previous approaches and propose Bayesian model selection to indicate whether the profiles can be considered parallel and if so support an estimation procedure for the profile differences.

Analysis of Variance↗

PubMedDate not supplied

Assessing tumour markers.

This paper explores the factors involved in assessing the value of a medical test in a given clinical situation. It examines the problems involved in designing studies to investigate the role for a tumour marker in differential diagnosis and patient monitoring. An overview is given, including a critical evaluation of the preliminary research, the laboratory assay technique and potential clinical problems. Some examples are given. Specific approaches to the analysis of monitoring data are outlined, including the application of a sequential Bayesian model. This is illustrated using data from patients in the Medical Research Council's series of studies on the tumour marker Carcinoembryonic antigen.

Carcinoembryonic Antigen↗

PubMedDate not supplied

Bayesian analysis of space-time variation in disease risk.

The analysis of variation of risk for a given disease in space and time is a key issue in descriptive epidemiology. When the data are scarce, maximum likelihood estimates of the area-specific risk and of its linear time-trend can be seriously affected by random variation. In this paper, we propose a Bayesian model in which both area-specific intercept and trend are modelled as random effects and correlation between them is allowed for. This model is an extension of that originally proposed for disease mapping. It is illustrated by the analysis of the cumulative prevalence of insulin dependent diabetes mellitus as observed at the military examination of 18-year-old conscripts born in Sardinia during the period 1936-1971. Data concerning the genetic differentiation of the Sardinian population are used to interpret the results.

Adolescent↗

PubMedDate not supplied

Spatial variation of natural radiation and childhood leukaemia incidence in Great Britain.

This paper describes an analysis of the geographical variation of childhood leukaemia incidence in Great Britain over a 15 year period in relation to natural radiation (gamma and radon). Data at the level of the 459 district level local authorities in England, Wales and regional districts in Scotland are analysed in two complementary ways: first, by Poisson regressions with the inclusion of environmental covariates and a smooth spatial structure; secondly, by a hierarchical Bayesian model in which extra-Poisson variability is modelled explicitly in terms of spatial and non-spatial components. From this analysis, we deduce a strong indication that a main part of the variability is accounted for by a local neighbourhood 'clustering' structure. This structure is furthermore relatively stable over the 15 year period for the lymphocytic leukaemias which make up the majority of observed cases. We found no evidence of a positive association of childhood leukaemia incidence with outdoor or indoor gamma radiation levels. There is no consistent evidence of any association with radon levels. Indeed, in the Poisson regressions, a significant positive association was only observed for one 5-year period, a result which is not compatible with a stable environmental effect. Moreover, this positive association became clearly non-significant when over-dispersion relative to the Poisson distribution was taken into account.

Air Pollution, Indoor↗

PubMed1993

A graphical user interface to facilitate patient-specific drug dosing.

This paper describes the development of a graphical user-interface (GUI) designed to facilitate the process of generating patient-specific drug doses using bayesian modelling software. The graphical user interface was developed in Visual Basic (Microsoft, Inc.) and runs under the Windows 3.1 (Microsoft, Inc.) operating system. Patient demographic data are stored in a relational database (Access, Microsoft, Inc.). The GUI and the database communicate via dynamic data exchange links. The largely object-oriented nature of the language allowed us to change the entire look and feel of the system with a few simple changes to the underlying code. Use of the relational database to store patient demographic information allows greater flexibility in searching for and displaying patient specific information. The GUI reduces the time required to enter data. The prototype has allowed us to experiment with different presentation methods, greatly improving the clinical acceptance of the dosing programs.

Computer Simulation↗

PubMed2003

Relation of risk of systemic lupus erythematosus to west African admixture in a Caribbean population.

Risk of systemic lupus erythematosus (SLE) is higher in people of west African descent than in Europeans. The objective of this study was to distinguish between genetic and environmental explanations for this ethnic difference by examining the relationship of disease risk to individual admixture (defined as the proportion of the genome that is of west African ancestry); 124 cases of SLE and 219 matched controls resident in Trinidad were studied. Analysis of admixture was restricted to 52 cases and 107 controls who reported no Indian or Chinese ancestry. These individuals were typed with a panel of 26 single-nucleotide polymorphisms and five insertion/deletion polymorphisms chosen to have large allele frequency differentials between west African, European and Native American populations. A Bayesian model for population admixture, individual admixture and locus ancestry was fitted by Markov chain simulation. Mean west African admixture (M) was 0.81 in cases and 0.74 in controls (P=0.01). The risk ratio for SLE associated with unit change in M was estimated as 32.5 with a 95% confidence interval (CI) of 2.0-518. Adjustment for measures of socioeconomic status (household amenities in childhood and years of education) altered this risk ratio only slightly (adjusted risk ratio: 28.4, 95% CI 1.7-485). These results support an additive genetic model for the ethnic difference in risk of SLE between west Africans and Europeans, rather than an environmental explanation or an "overdominant" model in which risk is higher in heterozygous than in homozygous individuals. This conclusion lays a basis for localizing the genes underlying this ethnic difference in risk of SLE by admixture mapping.

Adult↗

PubMed2004

Computerized coding of injury narrative data from the National Health Interview Survey.

OBJECTIVE: To investigate the accuracy of a computerized method for classifying injury narratives into external-cause-of-injury and poisoning (E-code) categories. METHODS: This study used injury narratives and corresponding E-codes assigned by experts from the 1997 and 1998 US National Health Interview Survey (NHIS). A Fuzzy Bayesian model was used to assign injury descriptions to 13 E-code categories. Sensitivity, specificity and positive predictive value were measured by comparing the computer generated codes with E-code categories assigned by experts. RESULTS: The computer program correctly classified 4695 (82.7%) of the 5677 injury narratives when multiple words were included as keywords in the model. The use of multiple-word predictors compared with using single words alone improved both the sensitivity and specificity of the computer generated codes. The program is capable of identifying and filtering out cases that would benefit most from manual coding. For example, the program could be used to code the narrative if the maximum probability of a category given the keywords in the narrative was at least 0.9. If the maximum probability was lower than 0.9 (which will be the case for approximately 33% of the narratives) the case would be filtered out for manual review. CONCLUSIONS: A computer program based on Fuzzy Bayes logic is capable of accurately categorizing cause-of-injury codes from injury narratives. The capacity to filter out certain cases for manual coding improves the utility of this process.

Forms and Records Control↗

PubMed2001

Electron-beam computed tomography: a Bayesian approach to risk assessment.

The epidemic of coronary artery disease continues to affect a large number of individuals who often experience sudden and unexpected events. This underscores the need to develop more effective programs to detect silent atherosclerosis, with the ultimate goal of preventing coronary events. The use of conventional risk factors is helpful in assessing the median risk of a population, but it is often unsatisfactory in estimating the actual risk of an individual patient. As a consequence, newer imaging modalities are being developed to detect atherosclerosis in its early developmental phases. Technologies such as electron-beam computed tomography (EBCT) may render risk stratification more accurate if used in the appropriate patient populations and with the right diagnostic approach. Several studies have already demonstrated the power of coronary calcification as a strong predictor of future cardiovascular events. Nonetheless, the medical literature is currently pervaded by an animated debate, as some investigators still have concerns about the effectiveness of a preventive approach driven by technology. The use of Bayesian models to interpret data acquired with EBCT screening may provide practitioners with valuable evidence to aid in their decision making.

Bayes Theorem↗

PubMed2001

Perception of 3D surface orientation from skew symmetry.

In this paper, we investigate how symmetry can be used to perceive 3D surface orientation. When a symmetric planar object is viewed from an angle, the projected contour has skew symmetry, which provides partial information about the 3D orientation of the object. For a given skew symmetry, this information can be characterized by a constraint curve of possible slant/tilt combinations that are consistent with a mirror-symmetric interpretation. These constraint curves move around when an object is rotated within a plane, and depend on what we will term the spin of the object: the angle between its axis of symmetry and the direction of tilt. To test the influence of symmetry constraint curves, we presented subjects with stereo images of symmetric objects that varied in spin, and had them perform an orientation-matching task. We found that the judgments showed biases that depended on the spin of the objects. Since other sources of information depend only on slant and tilt, not on spin, the biases imply that skew symmetry contributed to subjects' judgments. In a second experiment, we introduced conflicts between stereo and symmetry cues, and found that the spin-dependent biases can be modulated by selectively changing stereo slant. We propose an explanation of these results involving the optimal integration of stereo and skew symmetry, and present a Bayesian model that can account for the pattern of biases.

Analysis of Variance↗

PubMed2001

Risk assessment for Cryptosporidium: a hierarchical Bayesian analysis of human dose response data.

Three dose-response studies were conducted with healthy volunteers using different Cryptosporidium parvum isolates (IOWA, TAMU, and UCP). The study data were previously analyzed for median infectious dose (ID50) using a simple cumulative percent endpoint method (Reed and Muench, 1938). ID50s were derived using two definitions of infection: one as subjects having oocysts detected in stool by direct fluorescence assay, and the other by a clinical finding of diarrhea with or without detected oocysts (Chappell et al., 1998; Okhuysen et al., 1999). In the present study, the data were analyzed using the broader definition of infection (i.e., presence of oocysts in stool and/or diarrheal illness characteristic of cryptosporidiosis). Maximum likelihood dose-response parameter estimates for UCP, IOWA, and TAMU were 2980, 190, and 17.5, respectively. Based on these estimates, the ID50s of the three respective isolates were 2066, 132, and 12.1. The three oocyst isolates were considered representative of a larger population of human-infecting strains and analyzed as combined data using a hierarchical Bayesian model. Hyperparameters defined the distribution of dose-response parameters for the population of strains. Output from Markov Chain Monte Carlo analysis described posterior distributions for the hyperparameters and for the parameters of the IOWA, TAMU, and UCP strains. Point estimates of dose-response parameters produced by this analysis were similar to the maximum likelihood estimates. Finally, the utility of these results for probabilistic risk assessment was evaluated. The risk of infection from single oocyst doses was derived for a mixture of the three isolates (where IOWA, TAMU, or UCP are equally likely), and for an oocyst selected at random from the larger population of strains. These estimated risks of infection were 0.018 and 0.028, respectively.

Animals↗

PubMed2003

Prevalence estimates for paratuberculosis adjusted for test variability using Bayesian analysis.

The ELISA tests that are available to detect an infection with Mycobacterium avium subsp. paratuberculosis (MAP) have a limited validity expressed as the sensitivity (Se) and specificity (Sp). In many studies, the Se and Sp of the tests are treated as constants and this will result in an underestimation of the variability of the true prevalence (TP). Bayesian inference provided a natural framework for using information on the test variability (i.e., the uncertainty) in the estimates of test Se and Sp when estimating the TP. Data from two prevalence studies for MAP using an ELISA in several regions in two locations were available for the analyses. In location 1, all cattle of at least 3 years of age were sampled in approximately 90 randomly sampled herds in each of the four regions of the country. In location 2, in 30 randomly sampled herds in each of three regions, approximately 30 randomly selected cows were sampled. Information about the unknown test Se and Sp and MAP prevalence was incorporated into a Bayesian model by joint prior probability distributions. Posterior estimates were obtained by combining the actual likelihood with the prior distributions using Bayes' formula. The corrected cow-level TP (proportion of infected cows in a herd) was low, 5.8 and 3.6% in locations 1 and 2, respectively. Certain regions within a location differed significantly in herd-level TP (proportion of infected herds). The herd-level TP was 54.3% in location 1 (95% credible interval (CI) 46.1, 63.3%) and 32.9% in location 2 (95% CI: 14.4, 73.3%). The variation in the herd-level TP estimate for location 2 was more than three times as large as the variation in location 1 mainly because of the relatively small number of investigated herds in location 2. In future prevalence studies for MAP, sample size calculations should be based on a very low cow-level prevalence. Approximately 50 and 90% of the herds in the current study had an estimated cow-level TP below 4 and 10%, respectively.

Animals↗

PubMed2002

Multimodality in the superior colliculus: an information theoretic analysis.

The deep superior colliculus (DSC) integrates multisensory input and triggers an orienting movement toward the source of stimulation (target). It would seem reasonable to suppose that input of an additional modality should always increase the amount of information received by a DSC neuron concerning a target. However, of all DSC neurons studied, only about one half in the cat and one-quarter in the monkey were multimodal. The rest received only unimodal input. Multimodal DSC neurons show the properties of multisensory enhancement, in which the neural response to an input of one modality is augmented by input of another modality, and of inverse effectiveness, in which weaker unimodal responses produce a higher percentage enhancement. Previously, we demonstrated that these properties are consistent with the hypothesis that DSC neurons use Bayes' rule to compute the posterior probability that a target is present given their stochastic sensory inputs. Here we use an information theoretic analysis of our Bayesian model to show that input of an additional modality may indeed increase target information, but only if input received from the initial modality does not completely reduce uncertainty concerning the presence of a target. Unimodal DSC neurons may be those whose unimodal input fully reduces target uncertainty and therefore have no need for input of another modality.

Bayes Theorem↗

PubMed2003

Bayesian second-level analysis of functional magnetic resonance images.

We propose a new method for the second-level analysis of functional MRI data based on Bayesian statistics. Our method does not require a computationally costly Bayesian model on the first level of analysis. Rather, modeling for single subjects is realized by means of the commonly applied General Linear Model. On the basis of the resulting parameter estimates for single subjects we calculate posterior probability maps and maps of the effect size for effects of interest in groups of subjects. A comparison of this method with the conventional analysis based on t statistics shows that the new approach is more robust against outliers. Moreover, our method overcomes some of the severe problems of null hypothesis significance tests such as the need to correct for multiple comparisons and facilitates inferences which are hard to formulate in terms of classical inferences.

Algorithms↗

PubMed2004

Will Lake Michigan lake trout meet the Great Lakes Strategy 2002 PCB reduction goal?

The Great Lakes Strategy 2002 establishes the long-term goal that all Great Lakes fish should be safe to eat without restriction. As an indicator of progress toward that goal, the Strategy specifies that lake trout PCBs will decline 25% from 2000 to 2007. We estimated the plausibility of achieving this near-term goal by examining a time-series of Lake Michigan lake trout PCB concentrations from 1972 to 2000. We used two different Bayesian approaches, Bayesian model averaging (BMA) and dynamic linear models (DLM), to model the trajectory of these historical data and forecast concentrations through 2007. Both approaches indicate that the probability of a 25% reduction from 2000 to 2007 is negligible. The most likely lake trout PCB declines predicted by the BMA and DLM over this time period are 6.8% and 8.9%, respectively. Our results suggest that declines in lake trout PCBs will be in the range of 5-10% assuming conditions similar to recent years. This rate of decline will be difficult to discern without adequate data collection. If sufficient data are not gathered to document further declines, then the relaxation of lake trout consumption advisories is indeed a long-term prospect.

Animals↗

PubMed1997

Mortality risk perceptions: a Bayesian reassessment.

"This study uses data on perceived and actual mortality risks to test several alternative Bayesian models of the factors influencing risk beliefs. The analysis...indicates that while the hazard rate for the individual age group is an influential factor, the overall population death rate and the discounted expected number of life years lost due to the cause of death are also influential in affecting risk perceptions.... The predictive power of a linear perception model increases with the level of the risk and is least accurate for very small risks."

Behavior↗

PubMed2001

The rat approximates an ideal detector of changes in rates of reward: implications for the law of effect.

Rats responded on 2 levers delivering brain stimulation reward on concurrent variable interval schedules. Following many successive sessions with unchanging relative rates of reward, subjects adjusted to an eventual change slowly and showed spontaneous reversions at the beginning of subsequent sessions. When changes in rates of reward occurred between and within every session, subjects adjusted to them about as rapidly as they could in principle do so, as shown by comparison to a Bayesian model of an ideal detector. This and other features of the adjustments to frequent changes imply that the behavioral effect of reinforcement depends on the subject's perception of incomes and changes in incomes rather than on the strengthening and weakening of behaviors in accord with their past effects or expected results. Models for the process by which perceived incomes determine stay durations and for the process that detects changes in rates are developed.

Animals↗

PubMed2001

The subspecific origin of the inland breeding colonies of the cormorant Phalacrocorax carbo in Britain.

The establishment of cormorant breeding colonies inland within south-east Britain since 1981 is a matter of major conservation and pest management concern. This study was initiated to investigate the subspecific origin of two recently established breeding colonies. The analysis examined sequence variation of the control (D-loop) region of the mitochondrial genome. Samples of tissue were obtained from 334 individuals from across the species range in western Europe from both subspecies (Phalacrocorax carbo carbo and P. c. sinensis) and 84 birds from two inland breeding colonies in Britain. Single-strand conformation polymorphism (SSCP) was used to assess mitochondrial variation among samples, revealing four haplotypes. The samples from the traditional breeding colonies clustered into three distinct phylogeographic groupings: Norway-Scotland, Wales-England-Iles des Chausey and the rest of Continental Europe. These results only partly agree with the traditional subspecific taxonomic groupings and are slightly at variance with results using microsatellite DNA frequencies, and a hypothesis using results from both studies is advanced. The subspecific origin of the inland colonies was investigated using maximum likelihood and Bayesian models.

Animals↗