High number of previous Plasmodium falciparum clinical episodes increases risk of future episodes in a sub-group of individuals

One hundred malaria attacks since birth. A longitudinal study of African children and young adults exposed to high malaria transmission

Background

Despite significant progress in malaria control over the past twenty years, malaria remains a leading cause of child morbidity and mortality in Tropical Africa. As most patients do not consult any health facility much uncertainty persists about the true burden of the disease and the range of individual differences in susceptibility to malaria.

Methods

Over a 25-years period, from 1990 to 2015, the inhabitants of Dielmo village, Senegal, an area of intense malaria transmission, have been monitored daily for their presence in the village and the occurrence of diseases. In case of fever thick blood films were systematically examined through microscopy for malaria parasites and patients received prompt diagnosis and treatment.

Findings

We analysed data collected in 111 children and young adults monitored for at least 10 years (mean 17.3 years, maximum 25 years) enrolled either at birth (95 persons) or during the two first years of life. A total of 11,599 episodes of fever were documented, including 5268 malaria attacks. The maximum number of malaria attacks in a single person was 112. Three other persons suffered one hundred or more malaria attacks during follow-up. The minimum number of malaria attacks in a single person was 11. The mean numbers of malaria attacks in children reaching their 4th, 7th, and 10th birthdays were 23.0, 37.7, and 43.6 attacks since birth, respectively. Sixteen children (14.4%) suffered ten or more malaria attacks each year at ages 1-3 years, and six children (5.4%) each year at age 4-6 years.

Interpretation

Long-term close monitoring shows that in highly endemic areas the malaria burden is higher than expected. Susceptibility to the disease may vary up to 10-fold, and for most children childhood is an endless history of malaria fever episodes. No other parasitic, bacterial or viral infection in human populations has such an impact on health.

Funding

The Pasteur Institutes of Dakar and Paris, the Institut de Recherche pour le Développement, and the French Ministry of Cooperation provided funding.

Joint modelling of time-to-clinical malaria and parasite count in a cohort in an endemic area

Background

In malaria endemic areas such as sub-Saharan Africa, repeated exposure to malaria results in acquired immunity to clinical disease but not infection. In prospective studies, time-to-clinical malaria and longitudinal parasite count trajectory are often analysed separately which may result in inefficient estimates since these two processes can be associated. Including parasite count as a time-dependent covariate in a model of time-to-clinical malaria episode may also be inaccurate because while clinical malaria disease frequently leads to treatment which may instantly affect the level of parasite count, standard time-to-event models require that time-dependent covariates be external to the event process. We investigated whether jointly modelling time-to-clinical malaria disease and longitudinal parasite count improves precision in risk factor estimates and assessed the strength of association between the hazard of clinical malaria and parasite count.

Methods

Using a cohort data of participants enrolled with uncomplicated malaria in Malawi, a conventional Cox Proportional Hazards (PH) model of time-to-first clinical malaria episode with time-dependent parasite count was compared with three competing joint models. The joint models had different association structures linking a quasi-Poisson mixed-effects of parasite count and event-time Cox PH sub-models.

Results

There were 120 participants of whom 115 (95.8%) had >1 follow-up visit and 100 (87.5%) experienced the episode. Adults >15 years being reference, log hazard ratio for children <5 years was 0.74 (95% CI: 0.17, 1.26) in the joint model with best fit vs. 0.62 (95% CI: 0.04, 1.18) from the conventional Cox PH model. The log hazard ratio for the 5-15 years was 0.72 (95% CI: 0.22, 1.22) in the joint model vs.0.63 (95% CI: 0.11, 1.17) in the Cox PH model. The area under parasite count trajectory was strongly associated with the risk of clinical malaria, with a unit increase corresponding to-0.0012 (95% CI: -0.0021, -0.0004) decrease in log hazard ratio.

Conclusion

Jointly modelling longitudinal parasite count and time-to-clinical malaria disease improves precision in log hazard ratio estimates compared to conventional time-dependent Cox PH model. The improved precision of joint modelling may improve study efficiency and allow for design of clinical trials with relatively lower sample sizes with increased power.

Variation in natural exposure to anopheles mosquitoes and its effects on malaria transmission

Variation in biting frequency by Anopheles mosquitoes can explain some of the heterogeneity in malaria transmission in endemic areas. In this study in Burkina Faso, we assessed natural exposure to mosquitoes by matching the genotype of blood meals from 1066 mosquitoes with blood from residents of local households. We observed that the distribution of mosquito bites exceeded the Pareto rule (20/80) in two of the three surveys performed (20/85, 76, and 96) and, at its most pronounced, is estimated to have profound epidemiological consequences, inflating the basic reproduction number of malaria by 8-fold. The distribution of bites from sporozoite-positive mosquitoes followed a similar pattern, with a small number of individuals within households receiving multiple potentially infectious bites over the period of a few days. Together, our findings indicate that heterogeneity in mosquito exposure contributes considerably to heterogeneity in infection risk and suggest significant variation in malaria transmission potential.

A Malaria-Resistant Phenotype with Immunological Correlates in a Tanzanian Birth Cohort Exposed to Intense Malaria Transmission

AbstractMalaria incidence is highly heterogeneous even in areas of high transmission, although no conclusive evidence exists that innate or naturally acquired resistance can prevent infection over an extended period of time. This longitudinal study examined immunoparasitological evidence for a malaria-resistant phenotype in which children do not develop malaria despite an extended period of exposure to parasites. Within a birth cohort followed from 2002 to 2006 in Muheza, Tanzania, an area of intense transmission, children (N = 687) provided blood smears biweekly during infancy and monthly thereafter. Maternal and childhood characteristics were obtained, cord-blood cytokines were measured, and antibody responses were assayed as measures of stage-specific exposure. Sixty-three (9.2%) children had no blood smear-positive slides over 2 years of follow-up (range: 1-3.5 years) and were identified as malaria resistant. Malaria-resistant children were similar to other children with respect to completeness of follow-up and all maternal and childhood characteristics except residence area. Antibody seroprevalence was similar for two sporozoite antigens, but malaria-resistant children had a lower antibody seroprevalence to merozoite antigens merozoite surface protein 1 (5.4% versus 30.2%; P < 0.0001) and apical membrane antigen 1 (7.2% versus 33.3%; P < 0.0001). Malaria-resistant children had higher cytokine levels in cord blood, particularly interleukin-1β. In summary, a subset of children living in an area of intense transmission was exposed to malaria parasites, but never developed patent parasitemia; this phenotype was associated with a distinct cytokine profile at birth and antibody profile during infancy. Further research with malaria-resistant children may identify mechanisms for naturally acquired immunity.

Immunity to malaria in an era of declining malaria transmission

With increasing malaria control and goals of malaria elimination, many endemic areas are transitioning from high-to-low-to-no malaria transmission. Reductions in transmission will impact on the development of naturally acquired immunity to malaria, which develops after repeated exposure to Plasmodium spp. However, it is currently unclear how declining transmission and malaria exposure will affect the development and maintenance of naturally acquired immunity. Here we review the key processes which underpin this knowledge; the amount of Plasmodium spp. exposure required to generate effective immune responses, the longevity of antibody responses and the ability to mount an effective response upon re-exposure through memory responses. Lastly we identify research priorities which will increase our understanding of how changing transmission will impact on malarial immunity.

Identifying children with excess malaria episodes after adjusting for variation in exposure: identification from a longitudinal study using statistical count models

BACKGROUND

The distribution of Plasmodium falciparum clinical malaria episodes is over-dispersed among children in endemic areas, with more children experiencing multiple clinical episodes than would be expected based on a Poisson distribution. There is consistent evidence for micro-epidemiological variation in exposure to P. falciparum. The aim of the current study was to identify children with excess malaria episodes after controlling for malaria exposure.

METHODS

We selected the model that best fit the data out of the models examined and included the following covariates: age, a weighted local prevalence of infection as an index of exposure, and calendar time to predict episodes of malaria on active surveillance malaria data from 2,463 children of under 15 years of age followed for between 5 and 15 years each. Using parameters from the zero-inflated negative binomial model which best fitted our data, we ran 100 simulations of the model based on our population to determine the variation that might be seen due to chance.

RESULTS

We identified 212 out of 2,463 children who had a number of clinical episodes above the 95(th) percentile of the simulations run from the model, hereafter referred to as "excess malaria (EM)". We then identified exposure-matched controls with "average numbers of malaria" episodes, and found that the EM group had higher parasite densities when asymptomatically infected or during clinical malaria, and were less likely to be of haemoglobin AS genotype.

CONCLUSIONS

Of the models tested, the negative zero-inflated negative binomial distribution with exposure, calendar year, and age acting as independent predictors, fitted the distribution of clinical malaria the best. Despite accounting for these factors, a group of children suffer excess malaria episodes beyond those predicted by the model. An epidemiological framework for identifying these children will allow us to study factors that may explain excess malaria episodes.

Dynamical malaria models reveal how immunity buffers effect of climate variability

Assessing the influence of climate on the incidence of Plasmodium falciparum malaria worldwide and how it might impact local malaria dynamics is complex and extrapolation to other settings or future times is controversial. This is especially true in the light of the particularities of the short- and long-term immune responses to infection. In sites of epidemic malaria transmission, it is widely accepted that climate plays an important role in driving malaria outbreaks. However, little is known about the role of climate in endemic settings where clinical immunity develops early in life. To disentangle these differences among high- and low-transmission settings we applied a dynamical model to two unique adjacent cohorts of mesoendemic seasonal and holoendemic perennial malaria transmission in Senegal followed for two decades, recording daily P. falciparum cases. As both cohorts are subject to similar meteorological conditions, we were able to analyze the relevance of different immunological mechanisms compared with climatic forcing in malaria transmission. Transmission was first modeled by using similarly unique datasets of entomological inoculation rate. A stochastic nonlinear human-mosquito model that includes rainfall and temperature covariates, drug treatment periods, and population variability is capable of simulating the complete dynamics of reported malaria cases for both villages. We found that under moderate transmission intensity climate is crucial; however, under high endemicity the development of clinical immunity buffers any effect of climate. Our models open the possibility of forecasting malaria from climate in endemic regions but only after accounting for the interaction between climate and immunity.

Integration of tumour and viral genomic characterizations in HBV-related hepatocellular carcinomas

BACKGROUND AND AIM

Hepatocellular carcinoma (HCC) is the most common liver cancer. We characterised HCC associated with infection compared with non-HBV-related HCC to understand interactions between viral and hepatocyte genomic alterations and their relationships with clinical features.

METHODS

Frozen HBV (n=86) or non-HBV-related (n=90) HCC were collected in two French surgical departments. Viral characterisation was performed by sequencing HBS and HBX genes and quantifying HBV DNA and cccDNA. Nine genes were screened for somatic mutations and expression profiling of 37 genes involved in hepatocarcinogenesis was studied.

RESULTS

HBX revealed frequent non-sense, frameshift and deletions in tumours, suggesting an HBX inactivation selected in HCC. The number of viral copies was frequently lower in tumour than in non-tumour tissues (p=0.0005) and patients with low HBV copies in the non-tumour liver tissues presented additional risk factor (HCV, alcohol or non-alcoholic steato-hepatitis, p=0.006). P53 was the most frequently altered pathway in HBV-related HCC (47%, p=0.001). Furthermore, TP53 mutations were associated with shorter survival only in HBV-related HCC (p=0.02) whereas R249S mutations were identified exclusively in migrants. Compared with other aetiologies, HBV-HCC were more frequently classified in tumours subgroups with upregulation of genes involved in cell-cycle regulation and a progenitor phenotype. Finally, in HBV-related HCC, transcriptomic profiles were associated with specific gene mutations (HBX, TP53, IRF2, AXIN1 and CTNNB1).

CONCLUSIONS

Integrated genomic characterisation of HBV and non-HBV-related HCC emphasised the immense molecular diversity of HCC closely related to aetiologies that could impact clinical care of HCC patients.