Rule-based modeling of chronic disease epidemiology: elderly depression as an illustration

Background

Rule-based Modeling (RBM) is a computer simulation modeling methodology already used to model infectious diseases. Extending this technique to the assessment of chronic diseases, mixing quantitative and qualitative data appear to be a promising alternative to classical methods. Elderly depression reveals an important source of comorbidities. Yet, the intertwined relationship between late-life events and the social support of the elderly person remains difficult to capture. We illustrate the usefulness of RBM in modeling chronic diseases using the example of elderly depression in Belgium.

Methods

We defined a conceptual framework of interactions between late-life events and social support impacting elderly depression. This conceptual framework was underpinned by experts'' opinions elicited through a questionnaire. Several scenarios were implemented successively to better mimic the real population, and to explore a treatment effect and a socio-economic distinction. The simulated patterns of depression by age were compared with empirical patterns retrieved from the Belgian Health Interview Survey.

Results

Simulations were run using different groupings of experts'' opinions on the parameters. The results indicate that the conceptual framework can reflect a realistic evolution of the prevalence of depression. Indeed, simulations combining the opinions of well-selected experts and a treatment effect showed no significant difference with the empirical pattern.

Conclusions

Our conceptual framework together with a quantification of parameters through elicited expert opinions improves the insights into possible dynamics driving elderly depression. While RBM does not require high-level skill in mathematics or computer programming, the whole implementation process provides a powerful tool to learn about complex chronic diseases, combining advantages of both quantitative and qualitative approaches.     

Anxiolytic‐Like Action of Selected 4‐(Alkylamino)‐3‐nitrocoumarin Derivatives in BALB/c Mice

In this work, we explored the possible polypharmacological potential of the already established antimicrobials against gastrointestinal pathogens, 4‐(alkylamino)‐3‐nitrocoumarins, as antianxiety agents, using a battery of in vivo experiments. Three chosen coumarin derivatives, differing in the substituent (sec‐butylamino, hexadecylamino, or benzylamino) at position 4, at the doses of 25, 50 and 100 mg kg^–1, were evaluated in light/dark, open‐field, horizontal wire and diazepam‐induced sleep models using male BALB/c mice. Depending on the applied dose, all three tested coumarins displayed a noteworthy anxiolytic‐like effect. 4‐(sec‐Butylamino)‐3‐nitro‐2H‐chromen‐2‐one and 4‐(hexadecylamino)‐3‐nitro‐2H‐chromen‐2‐one could be recognized as true anxiolytics in the lowest applied dose, based on three tests, without exerting any sedative effects. Thus, the 3‐nitrocoumarin core deserves further chemical diversity exploration in the ‘antianxiety’ direction.     

The Evolution of Virulence in RNA Viruses under a Competition–Colonization Trade-Off

RNA viruses exist in large intra-host populations which display great genotypic and phenotypic diversity. We analyze a model of viral competition between two viruses infecting a constantly replenished cell pool. We assume a trade-off between the ability of the virus to colonize new cells (cell killing rate or virulence) and its local competitiveness (replicative success within coinfected cells). We characterize the conditions that allow for viral spread by means of the basic reproductive number and show that a local coexistence equilibrium exists, which is asymptotically stable. At this equilibrium, the less virulent competitor has a reproductive advantage over the more virulent colonizer reflected by a larger equilibrium population size of the competitor. The equilibria at which one virus outcompetes the other one are unstable, i.e., a second virus is always able to permanently invade. We generalize the two-virus model to multiple viral strains, each displaying a different virulence. To account for the large phenotypic diversity in viral populations, we consider a continuous spectrum of virulences and present a continuum limit of this multiple viral strains model that describes the time evolution of an initial continuous distribution of virulence without mutations. We provide a proof of the existence of solutions of the model equations, analytically assess the properties of stationary solutions, and present numerical approximations of solutions for different initial distributions. Our simulations suggest that initial continuous distributions of virulence evolve toward a distribution that is extremely skewed in favor of competitors. At equilibrium, only the least virulent part of the population survives. The discrepancy of this finding in the continuum limit with the two-virus model is attributed to the skewed equilibrium subpopulation sizes and to the transition to a continuum. Consequently, in viral quasispecies with high virulence diversity, the model predicts collective virulence attenuation. This result may contribute to understanding virulence attenuation, which has been reported in several experimental studies.     

Coordination of apical and basal embryo development revealed by tissue-specific GNOM functions

Flowering-plant embryogenesis generates the basic body organization, including the apical and basal stem cell niches, i.e. shoot and root meristems, the major tissue layers and the cotyledon(s). gnom mutant embryos fail to initiate the root meristem at the early-globular stage and the cotyledon primordia at the late globular/transition stage. Tissue-specific GNOM expression in the gnom mutant embryo revealed that both apical and basal embryo organization depend on GNOM provascular expression and a functioning apical-basal auxin flux: GNOM provascular expression in gnom mutant background resulted in non-cell-autonomous reconstitution of apical and basal tissues which could be linked to changes in auxin responses in those tissues, stressing the importance of apical-basal auxin flow for overall embryo organization. Although reconstitution of apical-basal auxin flux in gnom results in the formation of single cotyledons (monocots), only additional GNOM epidermal expression is able to induce wild-type apical patterning. We conclude that provascular expression of GNOM is vital for both apical and basal tissue organization, and that epidermal GNOM expression is required for radial-to-bilateral symmetry transition of the embryo. We propose GNOM-dependent auxin sinks as a means to generate auxin gradients across tissues.     

The temporal order of genetic and pathway alterations in tumorigenesis

Cancer evolves through the accumulation of mutations, but the order in which mutations occur is poorly understood. Inference of a temporal ordering on the level of genes is challenging because clinically and histologically identical tumors often have few mutated genes in common. This heterogeneity may at least in part be due to mutations in different genes having similar phenotypic effects by acting in the same functional pathway. We estimate the constraints on the order in which alterations accumulate during cancer progression from cross-sectional mutation data using a probabilistic graphical model termed Hidden Conjunctive Bayesian Network (H-CBN). The possible orders are analyzed on the level of genes and, after mapping genes to functional pathways, also on the pathway level. We find stronger evidence for pathway order constraints than for gene order constraints, indicating that temporal ordering results from selective pressure acting at the pathway level. The accumulation of changes in core pathways differs among cancer types, yet a common feature is that progression appears to begin with mutations in genes that regulate apoptosis pathways and to conclude with mutations in genes involved in invasion pathways. H-CBN models provide a quantitative and intuitive model of tumorigenesis showing that the genetic events can be linked to the phenotypic progression on the level of pathways.     

Multiple insecticide resistance: an impediment to insecticide-based malaria vector control program

Background

Indoor Residual Spraying (IRS), insecticide-treated nets (ITNs) and long-lasting insecticidal nets (LLINs) are key components in malaria prevention and control strategy. However, the development of resistance by mosquitoes to insecticides recommended for IRS and/or ITNs/LLINs would affect insecticide-based malaria vector control. We assessed the susceptibility levels of Anopheles arabiensis to insecticides used in malaria control, characterized basic mechanisms underlying resistance, and evaluated the role of public health use of insecticides in resistance selection.

Methodology/Principal findings

Susceptibility status of An. arabiensis was assessed using WHO bioassay tests to DDT, permethrin, deltamethrin, malathion and propoxur in Ethiopia from August to September 2009. Mosquito specimens were screened for knockdown resistance (kdr) and insensitive acetylcholinesterase (ace-1^R) mutations using AS-PCR and PCR-RFLP, respectively. DDT residues level in soil from human dwellings and the surrounding environment were determined by Gas Chromatography with Electron Capture Detector. An. arabiensis was resistant to DDT, permethrin, deltamethrin and malathion, but susceptible to propoxur. The West African kdr allele was found in 280 specimens out of 284 with a frequency ranged from 95% to 100%. Ace-1^R mutation was not detected in all specimens scored for the allele. Moreover, DDT residues were found in soil samples from human dwellings but not in the surrounding environment.

Conclusion

The observed multiple-resistance coupled with the occurrence of high kdr frequency in populations of An. arabiensis could profoundly affect the malaria vector control programme in Ethiopia. This needs an urgent call for implementing rational resistance management strategies and integrated vector control intervention.     

The Individualized Genetic Barrier Predicts Treatment Response in a Large Cohort of HIV-1 Infected Patients

The success of combination antiretroviral therapy is limited by the evolutionary escape dynamics of HIV-1. We used Isotonic Conjunctive Bayesian Networks (I-CBNs), a class of probabilistic graphical models, to describe this process. We employed partial order constraints among viral resistance mutations, which give rise to a limited set of mutational pathways, and we modeled phenotypic drug resistance as monotonically increasing along any escape pathway. Using this model, the individualized genetic barrier (IGB) to each drug is derived as the probability of the virus not acquiring additional mutations that confer resistance. Drug-specific IGBs were combined to obtain the IGB to an entire regimen, which quantifies the virus'' genetic potential for developing drug resistance under combination therapy. The IGB was tested as a predictor of therapeutic outcome using between 2,185 and 2,631 treatment change episodes of subtype B infected patients from the Swiss HIV Cohort Study Database, a large observational cohort. Using logistic regression, significant univariate predictors included most of the 18 drugs and single-drug IGBs, the IGB to the entire regimen, the expert rules-based genotypic susceptibility score (GSS), several individual mutations, and the peak viral load before treatment change. In the multivariate analysis, the only genotype-derived variables that remained significantly associated with virological success were GSS and, with 10-fold stronger association, IGB to regimen. When predicting suppression of viral load below 400 cps/ml, IGB outperformed GSS and also improved GSS-containing predictors significantly, but the difference was not significant for suppression below 50 cps/ml. Thus, the IGB to regimen is a novel data-derived predictor of treatment outcome that has potential to improve the interpretation of genotypic drug resistance tests.