Bayesian screening for feature selection.

Biomedical applications such as genome-wide association studies screen large databases with high-dimensional features to identify rare, weakly expressed, and important continuous-valued features for subsequent detailed analysis. We describe an exact, rapid Bayesian screening approach with attractive diagnostic properties using a Gaussian random mixture model focusing on the missed discovery rate (the probability of failing to identify potentially informative features) rather than the false discovery rate ordinarily used with multiple hypothesis testing. The method provides the likelihood that a feature merits further investigation, as well as distributions of the effect magnitudes and the proportion of features with the same expected responses under alternative conditions. Important features include the dependence of the critical values on clinical and regulatory priorities and direct assessment of the diagnostic properties.

BMA-Mod: A Bayesian model averaging strategy for determining dose-response relationships in the presence of model uncertainty.

Successful pharmaceutical drug development requires finding correct doses. The issues that conventional dose-response analyses consider, namely whether responses are related to doses, which doses have responses differing from a control dose response, the functional form of a dose-response relationship, and the dose(s) to carry forward, do not need to be addressed simultaneously. Determining if a dose-response relationship exists, regardless of its functional form, and then identifying a range of doses to study further may be a more efficient strategy. This article describes a novel estimation-focused Bayesian approach (BMA-Mod) for carrying out the analyses when the actual dose-response function is unknown. Realizations from Bayesian analyses of linear, generalized linear, and nonlinear regression models that may include random effects and covariates other than dose are optimally combined to produce distributions of important secondary quantities, including test-control differences, predictive distributions of possible outcomes from future trials, and ranges of doses corresponding to target outcomes. The objective is similar to the objective of the hypothesis-testing based MCP-Mod approach, but provides more model and distributional flexibility and does not require testing hypotheses or adjusting for multiple comparisons. A number of examples illustrate the application of the method.

Unified screening for potential elevated adverse event risk and other associations.

Patients in large clinical trials and in studies employing large observational databases report many different adverse events, most of which will not have been anticipated at the outset. Conventional hypothesis testing of between group differences for each adverse event can be problematic: Lack of significance does not mean lack of risk, the tests usually are not adjusted for multiplicity, and the data determine which hypotheses are tested. This article describes a Bayesian screening approach suitable for clinical trials and large observational databases that do not test hypotheses, are self-adjusting for multiplicity, provide a direct assessment of the likelihood of no material drug-event association, and quantify the strength of the observed association. Clinical and/or regulatory considerations define the criteria for assessing drug-event associations. The diagnostic properties of this new approach can be evaluated analytically. The result of comparison of the results from the method relative to current methods when applied to a commonly used data set indicates that the findings are largely similar, but with some interesting differences that may be relevant in application. Applying the method to a large vaccine trial reduces the number of adverse events that might require further investigation substantially.

Genomic analysis of a cardinalfish with larval homing potential reveals genetic admixture in the Okinawa Islands.

Discrepancies between potential and observed dispersal distances of reef fish indicate the need for a better understanding of the influence of larval behaviour on recruitment and dispersal. Population genetic studies can provide insight on the degree to which populations are connected, and the development of restriction site-associated sequencing (RAD-Seq) methods has made such studies of nonmodel organisms more accessible. We applied double-digest RAD-Seq methods to test for population differentiation in the coral reef-dwelling cardinalfish, Siphamia tubifer, which based on behavioural studies, have the potential to use navigational cues to return to natal reefs. Analysis of 11,836 SNPs from fish collected at coral reefs in Okinawa, Japan, from eleven locations over 3 years reveals little genetic differentiation between groups of S. tubifer at spatial scales from 2 to 140 km and between years at one location: pairwise FST values were between 0.0116 and 0.0214. These results suggest that the Kuroshio Current largely influences larval dispersal in the region, and in contrast to expectations based on studies of other cardinalfishes, there is no evidence of population structure for S. tubifer at the spatial scales examined. However, analyses of outlier loci putatively under selection reveal patterns of temporal differentiation that indicate high population turnover and variable larval supply from divergent source populations between years. These findings highlight the need for more studies of fishes across various geographic regions that also examine temporal patterns of genetic differentiation to better understand the potential connections between early life-history traits and connectivity of reef fish populations.

Monitoring potential adverse event rate differences using data from blinded trials: the canary in the coal mine.

The development of drugs and biologicals whose mechanisms of action may extend beyond their target indications has led to a need to identify unexpected potential toxicities promptly even while blinded clinical trials are under way. One component of recently issued FDA rules regarding safety reporting requirements raises the possibility of breaking the blind for pre-identified serious adverse events that are not the clinical endpoints of a blinded study. Concern has been expressed that unblinding individual cases of frequently occurring adverse events could compromise the overall validity of the study. However, if external information is available about adverse event rates among patients not receiving the test product in populations similar to the study population, then it may be possible to address the potential for elevated risk without unblinding the trial. This article describes a Bayesian approach for determining the likelihood of elevated risk suitable binomial or Poisson likelihoods that applies regardless of the metric used to express the difference. The method appears to be particularly appropriate for routine monitoring of safety information for project development programs that include large blinded trials. Copyright © 2016 John Wiley & Sons, Ltd.

Control charts for monitoring accumulating adverse event count frequencies from single and multiple blinded trials.

Conventional practice monitors accumulating information about drug safety in terms of the numbers of adverse events reported from trials in a drug development program. Estimates of between-treatment adverse event risk differences can be obtained readily from unblinded trials with adjustment for differences among trials using conventional statistical methods. Recent regulatory guidelines require monitoring the cumulative frequency of adverse event reports to identify possible between-treatment adverse event risk differences without unblinding ongoing trials. Conventional statistical methods for assessing between-treatment adverse event risks cannot be applied when the trials are blinded. However, CUSUM charts can be used to monitor the accumulation of adverse event occurrences. CUSUM charts for monitoring adverse event occurrence in a Bayesian paradigm are based on assumptions about the process generating the adverse event counts in a trial as expressed by informative prior distributions. This article describes the construction of control charts for monitoring adverse event occurrence based on statistical models for the processes, characterizes their statistical properties, and describes how to construct useful prior distributions. Application of the approach to two adverse events of interest in a real trial gave nearly identical results for binomial and Poisson observed event count likelihoods. Copyright © 2016 John Wiley & Sons, Ltd.

Life history of the symbiotically luminous cardinalfish Siphamia tubifer (Perciformes: Apogonidae).

Characteristics of the life history of the coral reef-dwelling cardinalfish Siphamia tubifer, from Okinawa, Japan, were defined. A paternal mouthbrooder, S. tubifer, is unusual in forming a bioluminescent symbiosis with Photobacterium mandapamensis. The examined S. tubifer (n = 1273) ranged in size from 9·5 to 43·5 mm standard length (LS ), and the minimum size at sexual maturity was 22 mm LS . The number of S. tubifer associated during the day among the spines of host urchins was 22·9 ± 16·1 (mean ± s.d.; Diadema setosum) and 3·6 ± 3·2 (Echinothrix calamaris). Diet consisted primarily of crustacean zooplankton. Batch fecundity (number of eggs; FB ) was related to LS by the equations: males (fertilized eggs) FB = 27·5LS - 189·46; females (eggs) FB = 31·3LS - 392·63. Individual mass (M; g) as a function of LS was described by the equation: M=9·74×10-5LS2·68. Growth, determined from otolith microstructure analysis, was described with the von Bertalanffy growth function with the following coefficients: L∞ = 40·8 mm LS , K = 0·026 day(-1) and t0 = 23·25 days. Planktonic larval duration was estimated to be 30 days. The age of the oldest examined individual was 240 days. The light organ of S. tubifer, which harbours the symbiotic population of P. mandapamensis, increased linearly in diameter as S. tubifer LS increased, and the bacterial population increased logarithmically with S. tubifer LS . These characteristics indicate that once settled, S. tubifer grows quickly, reproduces early and typically survives much less than 1 year in Okinawa. These characteristics are generally similar to other small reef fishes but they indicate that S. tubifer experiences higher mortality.

Joint modeling of survival and longitudinal non-survival data: current methods and issues. Report of the DIA Bayesian joint modeling working group.

Explicitly modeling underlying relationships between a survival endpoint and processes that generate longitudinal measured or reported outcomes potentially could improve the efficiency of clinical trials and provide greater insight into the various dimensions of the clinical effect of interventions included in the trials. Various strategies have been proposed for using longitudinal findings to elucidate intervention effects on clinical outcomes such as survival. The application of specifically Bayesian approaches for constructing models that address longitudinal and survival outcomes explicitly has been recently addressed in the literature. We review currently available methods for carrying out joint analyses, including issues of implementation and interpretation, identify software tools that can be used to carry out the necessary calculations, and review applications of the methodology.

Bayesian adaptive determination of the sample size required to assure acceptably low adverse event risk.

An emerging concern with new therapeutic agents, especially treatments for type 2 diabetes, a prevalent condition that increases an individual's risk of heart attack or stroke, is the likelihood of adverse events, especially cardiovascular events, that the new agents may cause. These concerns have led to regulatory requirements for demonstrating that a new agent increases the risk of an adverse event relative to a control by no more than, say, 30% or 80% with high (e.g., 97.5%) confidence. We describe a Bayesian adaptive procedure for determining if the sample size for a development program needs to be increased and, if necessary, by how much, to provide the required assurance of limited risk. The decision is based on the predictive likelihood of a sufficiently high posterior probability that the relative risk is no more than a specified bound. Allowance can be made for between-center as well as within-center variability to accommodate large-scale developmental programs, and design alternatives (e.g., many small centers, few large centers) for obtaining additional data if needed can be explored. Binomial or Poisson likelihoods can be used, and center-level covariates can be accommodated. The predictive likelihoods are explored under various conditions to assess the statistical properties of the method.

Segregation effects on the properties of (AuAg)147.

AuAg nanoclusters are promising supported co-catalysts for photocatalytic hydrogen reduction. However, beyond the quantum regime (N > 100) little is known about how the electronic properties of these nanoparticles are affected by chemical ordering. We investigate the effects of chemical ordering on the properties of 147-atom cuboctahedral AuAg nanoclusters, using empirical potentials coupled with an atomic-swap basin-hopping search to optimise the elemental distribution, with the lowest energy arrangements then reminimised using Density Functional Theory (DFT). Force-field calculations show Au atoms preferentially occupy sub-surface positions in the bimetallic structures, which results in the formation of a pseudo-onion structure for Ag-rich compositions. At the DFT-level, however, an Ag core surrounded by an Au shell (Ag@Au) is energetically favoured, as electron density can be drawn more readily when Au atoms are positioned on the nanocluster surface, thus resulting in a partial negative charge. Core@shell configurations are analogous to structures that can be chemically synthesised, and further detailed electronic analysis is discussed in the context of nanocluster applications to co-catalysed photocatalysis.

Indirect treatment comparison between fixed-dose-combinations of amlodipine/losartan and amlodipine/valsartan in blood pressure control.

AIMS: This study compared blood pressure (BP) changes after 8 weeks of therapy between a fixed-dose combination (FDC) of amlodipine/losartan and amlodipine/valsartan using a network meta-analysis because no trials directly compared amlodipine/losartan with other FDCs. METHODS: A systematic search identified six randomised controlled trials (amlodipine/losartan-3, amlodipine/valsartan-3) of FDCs and their component monotherapies. Conventional fixed-effects methods were used to conduct the comparisons. The primary and secondary effect measures were the changes in sitting diastolic and systolic blood pressure (sitDBP, sitSBP) at 8 weeks post-randomisation. RESULTS: The estimated amlodipine/valsartan - amlodipine/losartan difference (95% confidence interval) in sitDBP reduction was -1.27 mmHg, (-5.7, 2.2) for lower dosages and -0.45 mmHg, (-3.7, 2.7) for higher dosages; for sitSBP, the values were -3.74 mmHg, (-9.0, 2.9) for lower dosages and 0.2 mmHg, (-6.2, 6.0) for higher dosages. The confidence of a greater reduction in BP (fixed difference = 0) on amlodipine/losartan 5/50 than on amlodipine/valsartan 5/80 was 77% for sitDBP and 89% for sitSBP. The corresponding confidence for the higher doses was 61% for sitDBP and 48% for sitSBP. The findings support asserting with (fixed) 95% confidence that the BP reduction on amlodipine/valsartan 5/80 exceeds the amlodipine/losartan 5/50 reduction by at most 1.6 mmHg for sitDBP, and at most 1.26 mmHg for sitSBP. The corresponding upper bounds for the higher dosages were 2.31 mmHg (sitDBP) and 5.38 mmHg (sitSBP). CONCLUSIONS: The BP lowering effect with amlodipine/losartan and amlodipine/valsartan was comparable. Potential superiority of the reductions realised with amlodipine/valsartan relative to amlodipine/losartan, are unlikely to be clinically material.

Detecting potential safety issues in large clinical or observational trials by Bayesian screening when event counts arise from poisson distributions.

Patients in large clinical trials and in studies employing large observational databases report many different adverse events, most of which will not have been anticipated at the outset. Conventional hypothesis testing of between group differences for each adverse event can be problematic: Lack of significance does not mean lack of risk, the tests usually are not adjusted for multiplicity, and the data determine which hypotheses are tested. This article describes a Bayesian screening approach that does not test hypotheses, is self-adjusting for multiplicity, provides a direct assessment of the likelihood of no material drug-event association, and quantifies the strength of the observed association. The criteria for assessing drug-event associations can be determined by clinical or regulatory considerations. In contrast to conventional approaches, the diagnostic properties of this new approach can be evaluated analytically. Application of the method to findings from a vaccine trial yields results similar to those found by methods using a false discovery rate argument or a hierarchical Bayes approach. [Supplemental materials are available for this article. Go to the publisher's online edition of Journal of Biopharmaceutical Statistics for the following free supplemental resource: Appendix R: Code for calculations.].

Strain-level diversity of symbiont communities between individuals and populations of a bioluminescent fish.

The bioluminescent symbiosis involving the urchin cardinalfish, Siphamia tubifer, and Photobacterium mandapamensis, a luminous member of the Vibrionaceae, is highly specific compared to other bioluminescent fish-bacteria associations. Despite this high degree of specificity, patterns of genetic diversity have been observed for the symbionts from hosts sampled over relatively small spatial scales. We characterized and compared sub-species, strain-level symbiont diversity within and between S. tubifer hosts sampled from the Philippines and Japan using PCR fingerprinting. We then carried out whole genome sequencing of the unique symbiont genotypes identified to characterize the genetic diversity of the symbiont community and the symbiont pangenome. We determined that an individual light organ contains six symbiont genotypes on average, but varied between 1-13. Additionally, we found that there were few genotypes shared between hosts from the same location. A phylogenetic analysis of the unique symbiont strains indicated location-specific clades, suggesting some genetic differentiation in the symbionts between host populations. We also identified symbiont genes that were variable between strains, including luxF, a member of the lux operon, which is responsible for light production. We quantified the light emission and growth rate of two strains missing luxF along with the other strains isolated from the same light organs and determined that strains lacking luxF were dimmer but grew faster than most of the other strains, suggesting a potential metabolic trade-off. This study highlights the importance of strain-level diversity in microbial associations and provides new insight into the underlying genetic architecture of intraspecific symbiont communities within a host.

Enhanced beta cell proliferation in mice overexpressing a constitutively active form of Akt and one allele of p21Cip.

AIMS/HYPOTHESIS: The ability of pancreatic beta cells to proliferate is critical both for normal tissue maintenance and in conditions where there is an increased demand for insulin. Protein kinase B(Akt) plays a major role in promoting proliferation in many cell types, including the insulin-producing beta cells. We have previously reported that mice overexpressing a constitutively active form of Akt(caAkt (Tg)) show enhanced beta cell proliferation that is associated with increased protein levels of cyclin D1, cyclin D2 and cyclin-dependent kinase inhibitor 1A (p21(Cip)). In the present study, we sought to assess the mechanisms responsible for augmented p21(Cip) levels in caAkt(Tg) mice and test the role of p21(Cip) in the proliferative responses induced by activation of Akt signalling. METHODS: To gain a greater understanding of the relationship between Akt and p21(Cip), we evaluated the mechanisms involved in the modulation of p2(Cip) by Akt and the in vivo role of reduced p21(Cip) in proliferative responses induced by Akt. RESULTS: Our experiments showed that Akt signalling regulates p21(Cip) transcription and protein stability. caAkt(Tg) /p21(Cip+/-) mice exhibited fasting and fed hypoglycaemia as well as hyperinsulinaemia when compared with caAkt(Tg) mice. Glucose tolerance tests revealed improved glucose tolerance in caAkt(Tg)/p21(Cip+/-) mice compared with caAkt (Tg). These changes resulted from increased proliferation, survival and beta cell mass in caAkt(Tg)/p21(Cip+/-) compared with caAkt(Tg) mice. CONCLUSIONS/INTERPRETATION: Our data indicate that increased p21(Cip) levels in caAkt(Tg) mice act as a compensatory brake, protecting beta cells from unrestrained proliferation. These studies imply that p21(Cip) could play important roles in the adaptive responses of beta cells to proliferate in conditions such as in insulin resistance.

A predictive Bayesian approach to the design and analysis of bridging studies.

Pharmaceutical product development culminates in confirmatory trials whose evidence for the product's efficacy and safety supports regulatory approval for marketing. Regulatory agencies in countries whose patients were not included in the confirmatory trials often require confirmation of efficacy and safety in their patient populations, which may be accomplished by carrying out bridging studies to establish consistency for local patients of the effects demonstrated by the original trials. This article describes and illustrates an approach for designing and analyzing bridging studies that fully incorporates the information provided by the original trials. The approach determines probability contours or regions of joint predictive intervals for treatment effect and response variability, or endpoints of treatment effect confidence intervals, that are functions of the findings from the original trials, the sample sizes for the bridging studies, and possible deviations from complete consistency with the original trials. The bridging studies are judged consistent with the original trials if their findings fall within the probability contours or regions. Regulatory considerations determine the region definitions and appropriate probability levels. Producer and consumer risks provide a way to assess alternative region and probability choices. [Supplemental materials are available for this article. Go to the Publisher's online edition of the Journal of Biopharmaceutical Statistics for the following free supplemental resource: Appendix 2: R code for Calculations.].

Symbiosis initiation in the bacterially luminous sea urchin cardinalfish Siphamia versicolor.

To determine how each new generation of the sea urchin cardinalfish Siphamia versicolor acquires the symbiotic luminous bacterium Photobacterium mandapamensis, and when in its development the S. versicolor initiates the symbiosis, procedures were established for rearing S. versicolor larvae in an aposymbiotic state. Under the conditions provided, larvae survived and developed for 28 days after their release from the mouths of males. Notochord flexion began at 8 days post release (dpr). By 28 dpr, squamation was evident and the caudal complex was complete. The light organ remained free of bacteria but increased in size and complexity during development of the larvae. Thus, aposymbiotic larvae of the fish can survive and develop for extended periods, major components of the luminescence system develop in the absence of the bacteria and the bacteria are not acquired directly from a parent, via the egg or during mouth brooding. Presentation of the symbiotic bacteria to aposymbiotic larvae at 8-10 dpr, but not earlier, led to initiation of the symbiosis. Upon colonization of the light organ, the bacterial population increased rapidly and cells forming the light-organ chambers exhibited a differentiated appearance. Therefore, the light organ apparently first becomes receptive to colonization after 1 week post-release development, the symbiosis is initiated by bacteria acquired from the environment and bacterial colonization induces morphological changes in the nascent light organ. The abilities to culture larvae of S. versicolor for extended periods and to initiate the symbiosis in aposymbiotic larvae are key steps in establishing the experimental tractability of this highly specific vertebrate and microbe mutualism.

Chromosome-Level Genome Assembly of the Bioluminescent Cardinalfish Siphamia tubifer: An Emerging Model for Symbiosis Research.

The bioluminescent symbiosis involving the sea urchin cardinalfish Siphamia tubifer and the luminous bacterium Photobacterium mandapamensis is an emerging vertebrate model for the study of microbial symbiosis. However, little genetic data are available for the host, limiting the scope of research that can be implemented with this association. We present a chromosome-level genome assembly for S. tubifer using a combination of PacBio HiFi sequencing and Hi-C technologies. The final assembly was 1.2 Gb distributed on 23 chromosomes and contained 32,365 protein coding genes with a BUSCO score of 99%. A comparison of the S. tubifer genome to that of another nonluminous species of cardinalfish revealed a high degree of synteny, whereas a comparison to a more distant relative in the sister order Gobiiformes revealed the fusion of two chromosomes in the cardinalfish genomes. The complete mitogenome of S. tubifer was also assembled, and an inversion in the vertebrate WANCY tRNA genes as well as heteroplasmy in the length of the control region were discovered. A phylogenetic analysis based on whole the mitochondrial genome indicated that S. tubifer is divergent from the rest of the cardinalfish family, highlighting the potential role of the bioluminescent symbiosis in the initial divergence of Siphamia. This high-quality reference genome will provide novel opportunities for the bioluminescent S. tubifer-P. mandapamensis association to be used as a model for symbiosis research.

A framework for assessing the impact of accelerated approval.

The FDA's Accelerated Approval program (AA) is a regulatory program to expedite availability of products to treat serious or life-threatening illnesses that lack effective treatment alternatives. Ideally, all of the many stakeholders such as patients, physicians, regulators, and health technology assessment [HTA] agencies that are affected by AA should benefit from it. In practice, however, there is intense debate over whether evidence supporting AA is sufficient to meet the needs of the stakeholders who collectively bring an approved product into routine clinical care. As AAs have become more common, it becomes essential to be able to determine their impact objectively and reproducibly in a way that provides for consistent evaluation of therapeutic decision alternatives. We describe the basic features of an approach for evaluating AA impact that accommodates stakeholder-specific views about potential benefits, risks, and costs. The approach is based on a formal decision-analytic framework combining predictive distributions for therapeutic outcomes (efficacy and safety) based on statistical models that incorporate findings from AA trials with stakeholder assessments of various actions that might be taken. The framework described here provides a starting point for communicating the value of a treatment granted AA in the context of what is important to various stakeholders.

Microbial epitopes act as altered peptide ligands to prevent experimental autoimmune encephalomyelitis.

Molecular mimicry refers to structural homologies between a self-protein and a microbial protein. A major epitope of myelin basic protein (MBP), p87-99 (VHFFKNIVTPRTP), induces experimental autoimmune encephalomyelitis (EAE). VHFFK contains the major residues for binding of this self-molecule to T cell receptor (TCR) and to the major histocompatibility complex. Peptides from papilloma virus strains containing the motif VHFFK induce EAE. A peptide from human papilloma virus type 40 (HPV 40) containing VHFFR, and one from HPV 32 containing VHFFH, prevented EAE. A sequence from Bacillus subtilis (RKVVTDFFKNIPQRI) also prevented EAE. T cell lines, producing IL-4 and specific for these microbial peptides, suppressed EAE. Thus, microbial peptides, differing from the core motif of the self-antigen, MBPp87-99, function as altered peptide ligands, and behave as TCR antagonists, in the modulation of autoimmune disease.

Autoimmune diseases prior to the diagnosis of multiple sclerosis: a population-based case-control study.

The objective of this study was to determine whether patients with multiple sclerosis (MS) are more likely to have other autoimmune disorders particularly prior to the diagnosis of MS. We conducted a population-based case-control study of patients enrolled in the Northern California Kaiser Permanente Medical Care Program. Electronic clinical records through 2005 were used to ascertain incident and prevalent MS cases and identify the presence and timing of 44 other diagnoses. Controls were matched 5:1 for gender, age, and Kaiser membership characteristics. We identified 5296 MS cases (including 924 diagnosed between 2001 and 2004) and 26,478 matched controls. Prior to MS diagnosis, cases were more likely than controls to have uveitis (OR = 3.2, 95%; CI 1.7-5.7), inflammatory bowel disease (IBD, OR = 1.7; 95%CI 1.2-2.5), and Bell's palsy (OR = 3.2; 95%CI 1.2-8.3). Cases were also more likely to develop Guillain- Barré syndrome (GBS, OR = 5.0; 95%CI 1.6-15.4) and bullous pemphigoid (OR = 6.7; 95%CI 1.5-29.9). Cases were not more likely than controls to have or to develop rheumatoid arthritis, lupus or thyroiditis. MS may share environmental triggers, genetic susceptibilities and/or alterations in immune homeostasis with IBD and uveitis, but not with other autoimmune disorders.