Challenges in the clinical assessment of novel tuberculosis drugs

To effectively tackle the global TB epidemic, novel treatment strategies are critically needed to shorten the duration of TB therapy and treat drug-resistant TB. Drug development for TB, stymied for decades, has enjoyed a renaissance over the past several years. However, development of new TB regimens is hindered by the limitations in our understanding and use of preclinical models; the paucity of accurate, early surrogate markers of cure, and challenges in untangling the individual contributions of drugs to multidrug regimens in a complex, multi-compartment disease. Lack of profit motive, advocacy, and imagination has contributed mightily to the dearth of drugs we have on the shelf to treat this ancient disease. Areas that will speed the development of new regimens for TB include novel murine and in vitro pharmacodynamics models, clinical endpoints that are not culture-based, innovative clinical trial designs, and an infusion of much-needed funding

Defining the optimal dose of rifapentine for pulmonary tuberculosis: Exposure-response relations from two phase II clinical trials.

Rifapentine is a highly active antituberculosis antibiotic with treatment-shortening potential; however, exposure-response relations and the dose needed for maximal bactericidal activity have not been established. We used pharmacokinetic/pharmacodynamic data from 657 adults with pulmonary tuberculosis participating in treatment trials to compare rifapentine (n = 405) with rifampin (n = 252) as part of intensive-phase therapy. Population pharmacokinetic/pharmacodynamic analyses were performed with nonlinear mixed-effects modeling. Time to stable culture conversion of sputum to negative was determined in cultures obtained over 4 months of therapy. Rifapentine exposures were lower in participants who were coinfected with human immunodeficiency virus, black, male, or fasting when taking drug. Rifapentine exposure, large lung cavity size, and geographic region were independently associated with time to culture conversion in liquid media. Maximal treatment efficacy is likely achieved with rifapentine at 1,200 mg daily. Patients with large lung cavities appear less responsive to treatment, even at high rifapentine doses

Does effective population size affect rates of molecular evolution : mitochondrial data for host/parasite species pairs in bees suggests not

Adaptive evolutionary theory argues that organisms with larger effective population size (Ne) should have higher rates of adaptive evolution and therefore greater capacity to win evolutionary arm races. However, in some certain cases, species with much smaller Ne may be able to survive besides their opponents for an extensive evolutionary time. Neutral theory predicts that accelerated rates of molecular evolution in organisms with exceedingly small Ne are due to the effects of genetic drift and fixation of slightly deleterious mutations. We test this prediction in two obligate social parasite species and their respective host species from the bee tribe Allodapini. The parasites (genus Inquilina) have been locked into tight coevolutionary arm races with their exclusive hosts (genus Exoneura) for ~15 million years, even though Inquilina exhibit Ne that are an order of magnitude smaller than their host. In this study, we compared rates of molecular evolution between host and parasite using nonsynonymous to synonymous substitution rate ratios (dN/dS) of eleven mitochondrial protein-coding genes sequenced from transcriptomes. Tests of selection on mitochondrial genes indicated no significant differences between host and parasite dN/dS, with evidence for purifying selection acting on all mitochondrial genes of host and parasite species. Several potential factors which could weaken the inverse relationship between Ne and rate of molecular evolution are discussed

A new toolbox to distinguish the sources of spatial memory error

Studying the sources of errors in memory recall has proven invaluable for understanding the mechanisms of working memory (WM). While one-dimensional memory features (e.g. colour, orientation) can be analysed using existing mixture modelling toolboxes to separate the influence of imprecision, guessing, and misbinding (the tendency to confuse features that belong to different memoranda), such toolboxes are not currently available for two-dimensional spatial WM tasks. Here we present a method to isolate sources of spatial error in tasks where participants have to report the spatial location of an item in memory, using two-dimensional mixture models. The method recovers simulated parameters well, and is robust to the influence of response distributions and biases, and number of non-targets and trials. To demonstrate the model, we fit data from a complex spatial WM task, and show the recovered parameters correspond well with previous spatial WM findings, and with recovered parameters on a one-dimensional analogue of this task, suggesting convergent validity for this two-dimensional modelling approach. Because the extra dimension allows greater separation of memoranda and responses, spatial tasks turn out to be much better for separating misbinding from imprecision and guessing than one-dimensional tasks. Code for these models is freely available in the MemToolbox2D package and is integrated to work with the commonly used Matlab package MemToolbox

Application of multiplexed ion mobility spectrometry towards the identification of host protein signatures of treatment effect in pulmonary tuberculosis.

RationaleThe monitoring of TB treatments in clinical practice and clinical trials relies on traditional sputum-based culture status indicators at specific time points. Accurate, predictive, blood-based protein markers would provide a simpler and more informative view of patient health and response to treatment.ObjectiveWe utilized sensitive, high throughput multiplexed ion mobility-mass spectrometry (IM-MS) to characterize the serum proteome of TB patients at the start of and at 8 weeks of rifamycin-based treatment. We sought to identify treatment specific signatures within patients as well as correlate the proteome signatures to various clinical markers of treatment efficacy.MethodsSerum samples were collected from 289 subjects enrolled in CDC TB Trials Consortium Study 29 at time of enrollment and at the end of the intensive phase (after 40 doses of TB treatment). Serum proteins were immunoaffinity-depleted of high abundant components, digested to peptides and analyzed for data acquisition utilizing a unique liquid chromatography IM-MS platform (LC-IM-MS). Linear mixed models were utilized to identify serum protein changes in the host response to antibiotic treatment as well as correlations with culture status end points.ResultsA total of 10,137 peptides corresponding to 872 proteins were identified, quantified, and used for statistical analysis across the longitudinal patient cohort. In response to TB treatment, 244 proteins were significantly altered. Pathway/network comparisons helped visualize the interconnected proteins, identifying up regulated (lipid transport, coagulation cascade, endopeptidase activity) and down regulated (acute phase) processes and pathways in addition to other cross regulated networks (inflammation, cell adhesion, extracellular matrix). Detection of possible lung injury serum proteins such as HPSE, significantly downregulated upon treatment. Analyses of microbiologic data over time identified a core set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2) which change in response to treatment and also strongly correlate with culture status. A similar set of proteins at baseline were found to be predictive of week 6 and 8 culture status.ConclusionA comprehensive host serum protein dataset reflective of TB treatment effect is defined. A repeating set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2, among others) were found to change significantly in response to treatment, to strongly correlate with culture status, and at baseline to be predictive of future culture conversion. If validated in cohorts with long term follow-up to capture failure and relapse of TB, these protein markers could be developed for monitoring of treatment in clinical trials and in patient care

Candidate malaria susceptibility/protective SNPs in hospital and population-based studies: the effect of sub-structuring

Background: Populations of East Africa including Sudan, exhibit some of the highest indices of genetic diversity in the continent and worldwide. The current study aims to address the possible impact of population structure and population stratification on the outcome of case-control association-analysis of malaria candidate-genes in different Sudanese populations, where the pronounced genetic heterogeneity becomes a source of concern for the potential effect on the studies outcome. Methods: A total of 72 SNPs were genotyped using the Sequenom iPLEX Gold assay in 449 DNA samples that included; cases and controls from two village populations, malaria patients and out-patients from the area of Sinnar and additional controls consisting of healthy Nilo-Saharan speaking individuals. The population substructure was estimated using the Structure 2.2 programme. Results & Discussion: The Hardy-Weinberg Equilibrium values were generally within expectation in Hausa and Massalit. However, in the Sinnar area there was a notable excess of homozygosity, which was attributed to the Whalund effect arising from population amalgamation within the sample. The programme STRUCTURE revealed a division of both Hausa and Massalit into two substructures with the partition in Hausa more pronounced than in Massalit; in Sinnar there was no defined substructure. More than 25 of the 72 SNPs assayed were informative in all areas. Some important SNPs were not differentially distributed between malaria cases and controls, including SNPs in CD36 and NOS2. A number of SNPs showed significant p-values for differences in distribution of genotypes between cases and controls including: rs1805015 (in IL4R1) (P=0001), rs17047661 (in CR1) (P=0.02) and rs1800750 (TNF-376) (P=0.01) in the hospital samples; rs1050828 (G6PD+202) (P=0.02) and rs1800896 (IL10-1082) (P=0.04) in Massalit and rs2243250 (IL4-589) (P=0.04) in Hausa. Conclusions: The difference in population structure partly accounts for some of these significant associations, and the strength of association proved to be sensitive to all levels of sub-structuring whether in the hospital or population-based study

Racial Differences in Tuberculosis Infection in United States Communities: The Coronary Artery Risk Development in Young Adults Study

Previously reported associations between race/ethnicity and tuberculosis infection have lacked sufficient adjustment for socioeconomic factors. We analyzed race/ethnicity and self-reported tuberculosis infection data from the Coronary Artery Risk Development in Young Adults (CARDIA) study, a well-characterized cohort of 5115 black and white participants, and found that after adjusting for sociodemographic and clinical factors, black participants were more likely to report tuberculosis infection and/or disease (odds ratio, 2.0; 95% confidence interval, 1.5–2.9)