Claudio J. Struchiner

Genome sequences of the human body louse and its primary endosymbiont provide insights into the permanent parasitic lifestyle

As an obligatory parasite of humans, the body louse (Pediculus humanus humanus) is an important vector for human diseases, including epidemic typhus, relapsing fever, and trench fever. Here, we present genome sequences of the body louse and its primary bacterial endosymbiont Candidatus Riesia pediculicola. The body louse has the smallest known insect genome, spanning 108 Mb. Despite its status as an obligate parasite, it retains a remarkably complete basal insect repertoire of 10,773 protein-coding genes and 57 microRNAs. Representing hemimetabolous insects, the genome of the body louse thus provides a reference for studies of holometabolous insects. Compared with other insect genomes, the body louse genome contains significantly fewer genes associated with environmental sensing and response, including odorant and gustatory receptors and detoxifying enzymes. The unique architecture of the 18 minicircular mitochondrial chromosomes of the body louse may be linked to the loss of the gene encoding the mitochondrial single-stranded DNA binding protein. The genome of the obligatory louse endosymbiont Candidatus Riesia pediculicola encodes less than 600 genes on a short, linear chromosome and a circular plasmid. The plasmid harbors a unique arrangement of genes required for the synthesis of pantothenate, an essential vitamin deficient in the louse diet. The human body louse, its primary endosymbiont, and the bacterial pathogens that it vectors all possess genomes reduced in size compared with their free-living close relatives. Thus, the body louse genome project offers unique information and tools to use in advancing understanding of coevolution among vectors, symbionts, and pathogens.

Causal inference in infectious diseases.

Since the 1970s, Rubin has promoted a model for causal inference based on the potential outcomes if individuals received each of the treatments under study. Commonly, the assumption is made that the outcome in one individual is independent of the treatment assignment and outcome in other individuals. In infectious diseases, however, whether one person becomes infected is quite often dependent on the infection outcome in other individuals, a situation known as dependent happenings. Here, we review the model proposed by Rubin for the example of infectious disease. Consequences of the violation of the stability assumption include the need for an expanded representation of outcomes, and the existence of different kinds of effects, such as direct and indirect effects. Effects of interest include changes in susceptibility as well as changes in infectiousness. We define the transmission probability formally as an average causal parameter of effect in a population by conditioning on exposure to infection. Unconditional indirect and total effects are difficult to define formally using this model for causal inference. The assignment mechanism can influence the sampling mechanism when it determines who is exposed to infection, raising problems that require further inquiry. We conclude by contrasting the role of differential exposure to infection in direct and indirect effects.

Design and analysis of vaccine studies

and Examples.- Overview of Vaccine Effects and Study Designs.- Immunology and Early Phase Trials.- Binomial and Stochastic Transmission Models.- and Deterministic Models.- Evaluating Protective Effects of Vaccination.- Modes of Action and Time-Varying VE.- Further Evaluation of Protective Effects.- Vaccine Effects on Post-Infection Outcomes.- Household-Based Studies.- Analysis of Households in Communities.- Analysis of Independent Households.- Assessing Indirect, Total, and Overall Effects.- Randomization and Baseline Transmission.- Surrogates of Protection.

Pharmacogenetics of warfarin: development of a dosing algorithm for brazilian patients.

A dosing algorithm including genetic (VKORC1 and CYP2C9 genotypes) and nongenetic factors (age, weight, therapeutic indication, and cotreatment with amiodarone or simvastatin) explained 51% of the variance in stable weekly warfarin doses in 390 patients attending an anticoagulant clinic in a Brazilian public hospital. The VKORC1 3673G>A genotype was the most important predictor of warfarin dose, with a partial R2 value of 23.9%. Replacing the VKORC1 3673G>A genotype with VKORC1 diplotype did not increase the algorithms predictive power. We suggest that three other single‐nucleotide polymorphisms (SNPs) (5808T>G, 6853G>C, and 9041G>A) that are in strong linkage disequilibrium (LD) with 3673G>A would be equally good predictors of the warfarin dose requirement. The algorithms predictive power was similar across the self‐identified “race/color” subsets. “Race/color” was not associated with stable warfarin dose in the multiple regression model, although the required warfarin dose was significantly lower (P = 0.006) in white (29 ± 13 mg/week, n = 196) than in black patients (35 ± 15 mg/week, n = 76).

Uncertainties regarding dengue modeling in Rio de Janeiro, Brazil

Dengue fever is currently the most important arthropod-borne viral disease in Brazil. Mathematical modeling of disease dynamics is a very useful tool for the evaluation of control measures. To be used in decision-making, however, a mathematical model must be carefully parameterized and validated with epidemiological and entomological data. In this work, we developed a simple dengue model to answer three questions: (i) which parameters are worth pursuing in the field in order to develop a dengue transmission model for Brazilian cities; (ii) how vector density spatial heterogeneity influences control efforts; (iii) with a degree of uncertainty, what is the invasion potential of dengue virus type 4 (DEN-4) in Rio de Janeiro city. Our model consists of an expression for the basic reproductive number (R0) that incorporates vector density spatial heterogeneity. To deal with the uncertainty regarding parameter values, we parameterized the model using a priori probability density functions covering a range of plausible values for each parameter. Using the Latin Hypercube Sampling procedure, values for the parameters were generated. We conclude that, even in the presence of vector spatial heterogeneity, the two most important entomological parameters to be estimated in the field are the mortality rate and the extrinsic incubation period. The spatial heterogeneity of the vector population increases the risk of epidemics and makes the control strategies more complex. At last, we conclude that Rio de Janeiro is at risk of a DEN-4 invasion. Finally, we stress the point that epidemiologists, mathematicians, and entomologists need to interact more to find better approaches to the measuring and interpretation of the transmission dynamics of arthropod-borne diseases.

Epidemiologia dos acidentes ofídicos nos últimos 100 anos no Brasil: uma revisäo

We review 30 studies on snake bites in Brazil, published from 1901 to 2000, and conclude that epidemiological analyses conducted in the last 100 years are based on the same variables already identified by Vital Brazil in his pioneering report, i.e., characteristics of the individuals prone to snake bites, the bites themselves, and treatment. The original epidemiological profile was also maintained over the years and indicates that such accidents are more frequent among male farm workers in the 15-49-year age bracket, affecting mainly the lower limbs, and caused by snakes from genus Bothrops.

Self-reported skin color, genomic ancestry and the distribution of GST polymorphisms

Background and objective Skin color and self-reported ethnicity have systematically been used in the pharmacogenetic/-genomic literature as phenotypic proxies for geographical ancestry. Population admixture, however, challenges the appropriateness of this approach. We compared the effectiveness of color-based and marker-based biogeographical ancestry classifications in typing polymorphisms in GSTM1, GSTM3 and GSTT1 in the heterogeneous Brazilian population. Methods Individual DNA from 335 healthy Brazilians was typed for a set of insertion/deletion polymorphisms, previously validated as ancestry informative markers. GSTM1-null and GSTT1-null polymorphisms were detected by multiplex PCR and the GSTM3*B polymorphism by restriction-fragment length polymorphism. Nonlinear logistic regression modeling was developed to describe the association between the GST polymorphisms and ancestry estimated by the ancestry informative markers. Results Analysis of the ancestry informative markers data with the Structure software revealed the existence of only two significant clusters, one of which was inferred to be an estimate of the African component of ancestry. Nonlinear logistic regression showed that the odds of having the GSTM1-null genotype decreases (P<0.0004, Wald statistics), whereas the odds of having the GSTM3*B allele increases (P<0.0001) with the increase of the African component of ancestry, throughout the range (0.13–0.95) observed in the population sample. The African component of ancestry proportion was not associated with GSTT1-null frequency. Within the self-reported Black and Intermediate groups, there were significant differences in ancestry informative markers between GSTM1-null and non-null individuals, and between carriers and noncarriers of the GSTM3*B allele. Conclusions Interethnic admixture is a source of cryptic population structure that may lead to spurious genotype–phenotype associations in pharmacogenetic/-genomic studies. Logistic regression modeling of GST polymorphisms shows that admixture must be dealt with as a continuous variable, rather than proportioned in arbitrary subcategories for the convenience of data quantification and analysis.

Acidentes por animais peçonhentos e sistemas nacionais de informação

Neste trabalho foram analisados, sob a otica da vigilância epidemiologica dos acidentes por animais peconhentos, quatro sistemas nacionais de informacao, o SINAN (Sistema de Informacoes de Agravos de Notificacao), o SINITOX (Sistema Nacional de Informacoes Toxico-Farmacologicas), o SIH-SUS (Sistema de Informacoes Hospitalares do Sistema Unico de Saude) e o SIM (Sistema de Informacoes sobre Mortalidade). Concluiu-se que esses sistemas possuem caracteristicas proprias, foram criados para atender demandas diferentes e apesar de produzirem um grande volume de dados, nao conseguem, ainda que analisados em conjunto, dar conta da dimensao real desses acidentes.

Epidemiologia da hanseníase em coorte de contatos intradomiciliares no Rio de Janeiro (1987-1991)

This study aimed to identify factors influencing the development of leprosy (Hansens disease) in household contacts. A dynamic cohort was analyzed from 1987 to 1991 at the Hansens Disease Department of the Oswaldo Cruz Foundation in Rio de Janeiro. The incidence rate was 0.01694 person-years of follow-up. Nevertheless, for subjects at the end of the first year of follow-up the incidence rate was 0.06385 (end of second year, 0.03299; end of third year, 0.02370; end of fourth year, 0.018622; and end of observation period, 0.01694). A stepwise multivariate logistic regression model was proposed to study the risk of developing leprosy, including co-prevalent cases, totaling 758 contacts. In the final model, the risk was associated with a negative Mitsuda skin test (OR = 3.093; CI 95% = 1.735-5.514), prior BCG vaccination (OR = 0.3802; CI 95% = 0.2151-0.66719), and multibacillary primary clinical form (OR = 2.547; CI 95% = 1.249-5.192). The results showed that both multibacillary leprosy and specific immune status are significant indicators for developing the disease in a cohort of household contacts.

Modeling malaria vaccines II: Population effects of stage-specific malaria vaccines dependent on natural boosting

Population effects of malaria vaccination programs will depend on the stage specificity of the vaccine, its duration of effectiveness, whether it is responsive to natural boosting, the proportion vaccinated, and the preexisting endemic conditions. This paper develops models of infection-blocking (sporozoite), disease-modifying (merozoite), and transmission-blocking (gametic) vaccines. It explores numerically their different effects on prevalence of infection and disease when utilized in different types of immunization programs at various levels of coverage. Simulations show that possible qualitative consequences of malaria vaccination programs include decreased prevalence of infection and disease and decreased prevalence of infection without a corresponding decrease in prevalence of disease. Epidemics, either one-time or cyclical, could occur. These effects could be accompanied by changes in the age distribution of disease. Finally, vaccination could contribute to elimination of transmission. The duration of effectiveness of the malaria vaccine relative to the duration of natural immunity could have important consequences for the unvaccinated. The problem of predicting a threshold for elimination of transmission is discussed.