The geography of malaria genetics in the Democratic Republic of Congo: A complex and fragmented landscape

Malaria vaccine-related adverse events among children under 5 in sub-Saharan Africa: systematic review and meta-analysis protocol

INTRODUCTION

The RTS,S vaccine has been approved for use in children under 5 living in moderate to high malaria transmission areas. However, clinically important adverse events have been reported in countries in sub-Saharan Africa. This systematic review aims to assess the frequency, severity and clinical importance of vaccine-related adverse events.

METHODS AND ANALYSIS

This systematic review protocol has been prepared following robust methods and reported in line with the Preferred Reporting Items for Systematic reviews and Meta-Analyses for protocols guidelines. We will search PubMed, CINAHL, LILACS, Google Scholar, SCOPUS, WEB OF SCIENCE, Cochrane library, HINARI, African Journals Online, Trip Pro and TOXNET from 2000 to 30 September 2023, without language restrictions. We will also search conference proceedings, dissertations, World Bank Open Knowledge Repository, and WHO, PATH, UNICEF, Food and Drugs Authorities and European Medicines Agency databases, preprint repositories and reference lists of relevant studies for additional studies. Experts in the field will be contacted for unpublished or published studies missed by our searches. At least two reviewers will independently select studies and extract data using pretested tools and assess risk of bias in the included studies using the Cochrane risk of bias tool. Any disagreements will be resolved through discussion between the reviewers. Heterogeneity will be explored graphically, and statistically using the I2 statistic. We will conduct random-effects meta-analysis when heterogeneity is appreciable, and express dichotomous outcomes (serious adverse events, cerebral malaria and febrile convulsion) as risk ratio (RR) with their 95% CI. We will perform subgroup analysis to assess the impact of heterogeneity and sensitivity analyses to test the robustness of the effect estimates. The overall level of evidence will be assessed using Grading of Recommendations Assessment, Development and Evaluation.

ETHICS AND DISSEMINATION

Ethical approval is not required for a systematic review. The findings of this study will be disseminated through stakeholder forums, conferences and peer-review publications.

PROSPERO REGISTRATION NUMBER

CRD42021275155.

Genetic structure of Spirometra mansoni (Cestoda: Diphyllobothriidae) populations in China revealed by a Target SSR-seq method

BACKGROUND

In China, the plerocercoid of the cestode Spirometra mansoni is the main causative agent of human and animal sparganosis. However, the population genetic structure of this parasite remains unclear. In this study, we genotyped S. mansoni isolates with the aim to improve current knowledge on the evolution and population diversity of this cestode.

METHODS

We first screened 34 perfect simple sequence repeats (SSRs) using all available omic data and then constructed target sequencing technology (Target SSR-seq) based on the Illumina NovaSeq platform. Next, a series of STRUCTURE. clustering, principal component, analysis of molecular variance and TreeMix analyses were performed on 362 worm samples isolated from 12 different hosts in 16 geographical populations of China to identify the genetic structure.

RESULTS

A total of 170 alleles were detected. The whole population could be organized and was found to be derived from the admixture of two ancestral clusters. TreeMix analysis hinted that possible gene flow occurred from Guizhou (GZ) to Sichuan (SC), SC to Jaingxi (JX), SC to Hubei (HB), GZ to Yunnan (YN) and GZ to Jiangsu (JS). Both neighbor-joining clustering and principal coordinate analysis showed that isolates from intermediate hosts tend to cluster together, while parasites from definitive hosts revealed greater genetic differences. Generally, a S. mansoni population was observed to harbor high genetic diversity, moderate genetic differentiation and a little genetic exchange among geographical populations.

CONCLUSIONS

A Target SSR-seq genotyping method was successfully developed, and an in-depth view of genetic diversity and genetic relationship will have important implications for the prevention and control of sparganosis.

Modeling impact and cost-effectiveness of driving-Y gene drives for malaria elimination in the Democratic Republic of the Congo

Malaria elimination will be challenging in countries that currently continue to bear high malaria burden. Sex-ratio-distorting gene drives, such as driving-Y, could play a role in an integrated elimination strategy if they can effectively suppress vector populations. Using a spatially explicit, agent-based model of malaria transmission in eight provinces spanning the range of transmission intensities across the Democratic Republic of the Congo, we predict the impact and cost-effectiveness of integrating driving-Y gene drive mosquitoes in malaria elimination strategies that include existing interventions such as insecticide-treated nets and case management of symptomatic malaria. Gene drive mosquitoes could eliminate malaria and were the most cost-effective intervention overall if the drive component was highly effective with at least 95% X-shredder efficiency at relatively low fertility cost, and associated cost of deployment below 7.17 $int per person per year. Suppression gene drive could be a cost-effective supplemental intervention for malaria elimination, but tight constraints on drive effectiveness and cost ceilings may limit its feasibility.

The impact of antimalarial resistance on the genetic structure of Plasmodium falciparum in the DRC

The Democratic Republic of the Congo (DRC) harbors 11% of global malaria cases, yet little is known about the spatial and genetic structure of the parasite population in that country. We sequence 2537 Plasmodium falciparum infections, including a nationally representative population sample from DRC and samples from surrounding countries, using molecular inversion probes - a high-throughput genotyping tool. We identify an east-west divide in haplotypes known to confer resistance to chloroquine and sulfadoxine-pyrimethamine. Furthermore, we identify highly related parasites over large geographic distances, indicative of gene flow and migration. Our results are consistent with a background of isolation by distance combined with the effects of selection for antimalarial drug resistance. This study provides a high-resolution view of parasite genetic structure across a large country in Africa and provides a baseline to study how implementation programs may impact parasite populations.

The genome of the malaria parasite Plasmodium falciparum contains a record of past evolutionary forces. Here, using 2537 parasite sequences from the Democratic Republic of the Congo, the authors demonstrate how drug pressure and human movement have shaped the present-day parasite population.

A Scoping Review of Spatial Analysis Approaches Using Health Survey Data in Sub-Saharan Africa

Spatial analysis has become an increasingly used analytic approach to describe and analyze spatial characteristics of disease burden, but the depth and coverage of its usage for health surveys data in Sub-Saharan Africa are not well known. The objective of this scoping review was to conduct an evaluation of studies using spatial statistics approaches for national health survey data in the SSA region. An organized literature search for studies related to spatial statistics and national health surveys was conducted through PMC, PubMed/Medline, Scopus, NLM Catalog, and Science Direct electronic databases. Of the 4,193 unique articles identified, 153 were included in the final review. Spatial smoothing and prediction methods were predominant (n = 108), followed by spatial description aggregation (n = 25), and spatial autocorrelation and clustering (n = 19). Bayesian statistics methods and lattice data modelling were predominant (n = 108). Most studies focused on malaria and fever (n = 47) followed by health services coverage (n = 38). Only fifteen studies employed nonstandard spatial analyses (e.g., spatial model assessment, joint spatial modelling, accounting for survey design). We recommend that for future spatial analysis using health survey data in the SSA region, there must be an improve recognition and awareness of the potential dangers of a naïve application of spatial statistical methods. We also recommend a wide range of applications using big health data and the future of data science for health systems to monitor and evaluate impacts that are not well understood at local levels.

Detecting geospatial patterns of Plasmodium falciparum parasite migration in Cambodia using optimized estimated effective migration surfaces

BACKGROUND

Understanding the genetic structure of natural populations provides insight into the demographic and adaptive processes that have affected those populations. Such information, particularly when integrated with geospatial data, can have translational applications for a variety of fields, including public health. Estimated effective migration surfaces (EEMS) is an approach that allows visualization of the spatial patterns in genomic data to understand population structure and migration. In this study, we developed a workflow to optimize the resolution of spatial grids used to generate EEMS migration maps and applied this optimized workflow to estimate migration of Plasmodium falciparum in Cambodia and bordering regions of Thailand and Vietnam.

METHODS

The optimal density of EEMS grids was determined based on a new workflow created using density clustering to define genomic clusters and the spatial distance between genomic clusters. Topological skeletons were used to capture the spatial distribution for each genomic cluster and to determine the EEMS grid density; i.e., both genomic and spatial clustering were used to guide the optimization of EEMS grids. Model accuracy for migration estimates using the optimized workflow was tested and compared to grid resolutions selected without the optimized workflow. As a test case, the optimized workflow was applied to genomic data generated from P. falciparum sampled in Cambodia and bordering regions, and migration maps were compared to estimates of malaria endemicity, as well as geographic properties of the study area, as a means of validating observed migration patterns.

RESULTS

Optimized grids displayed both high model accuracy and reduced computing time compared to grid densities selected in an unguided manner. In addition, EEMS migration maps generated for P. falciparum using the optimized grid corresponded to estimates of malaria endemicity and geographic properties of the study region that might be expected to impact malaria parasite migration, supporting the validity of the observed migration patterns.

CONCLUSIONS

Optimized grids reduce spatial uncertainty in the EEMS contours that can result from user-defined parameters, such as the resolution of the spatial grid used in the model. This workflow will be useful to a broad range of EEMS users as it can be applied to analyses involving other organisms of interest and geographic areas.

High-resolution micro-epidemiology of parasite spatial and temporal dynamics in a high malaria transmission setting in Kenya

Novel interventions that leverage the heterogeneity of parasite transmission are needed to achieve malaria elimination. To better understand spatial and temporal dynamics of transmission, we applied amplicon next-generation sequencing of two polymorphic gene regions (csp and ama1) to a cohort identified via reactive case detection in a high-transmission setting in western Kenya. From April 2013 to July 2014, we enrolled 442 symptomatic children with malaria, 442 matched controls, and all household members of both groups. Here, we evaluate genetic similarity between infected individuals using three indices: sharing of parasite haplotypes on binary and proportional scales and the L1 norm. Symptomatic children more commonly share haplotypes with their own household members. Furthermore, we observe robust temporal structuring of parasite genetic similarity and identify the unique molecular signature of an outbreak. These findings of both micro- and macro-scale organization of parasite populations might be harnessed to inform next-generation malaria control measures.

Here, Nelson et al. use amplicon next-generation sequencing of two P. falciparum polymorphic gene regions to investigate the genetic similarity of parasite populations across time and space in a pediatric cohort in Kenya. They identify both micro- and macro-scale structuring of malaria parasites in this high-transmission setting, which could inform future intervention strategies.

The changing landscape of Plasmodium falciparum drug resistance in the Democratic Republic of Congo

BACKGROUND

Drug resistant malaria is a growing concern in the Democratic Republic of the Congo (DRC), where previous studies indicate that parasites resistant to sulfadoxine/pyrimethamine or chloroquine are spatially clustered. This study explores longitudinal changes in spatial patterns to understand how resistant malaria may be spreading within the DRC, using samples from nation-wide population-representative surveys.

METHODS

We selected 552 children with PCR-detectable Plasmodium falciparum infection and identified known variants in the pfdhps and pfcrt genes associated with resistance. We compared the proportion of mutant parasites in 2013 to those previously reported from adults in 2007, and identified risk factors for carrying a resistant allele using multivariate mixed-effects modeling. Finally, we fit a spatial-temporal model to the observed data, providing smooth allele frequency estimates over space and time.

RESULTS

The proportion of co-occurring pfdhps K540E/A581G mutations increased by 16% between 2007 and 2013. The spatial-temporal model suggests that the spatial range of the pfdhps double mutants expanded over time, while the prevalence and range of pfcrt mutations remained steady.

CONCLUSIONS

This study uses population-representative samples to describe the changing landscape of SP resistance within the DRC, and the persistence of chloroquine resistance. Vigilant molecular surveillance is critical for controlling the spread of resistance.

Pathogens in space: Advancing understanding of pathogen dynamics and disease ecology through landscape genetics

Landscape genetics has provided many insights into how heterogeneous landscape features drive processes influencing spatial genetic variation in free-living organisms. This rapidly developing field has focused heavily on vertebrates, and expansion of this scope to the study of infectious diseases holds great potential for landscape geneticists and disease ecologists alike. The potential application of landscape genetics to infectious agents has garnered attention at formative stages in the development of landscape genetics, but systematic examination is lacking. We comprehensively review how landscape genetics is being used to better understand pathogen dynamics. We characterize the field and evaluate the types of questions addressed, approaches used and systems studied. We also review the now established landscape genetic methods and their realized and potential applications to disease ecology. Lastly, we identify emerging frontiers in the landscape genetic study of infectious agents, including recent phylogeographic approaches and frameworks for studying complex multihost and host-vector systems. Our review emphasizes the expanding utility of landscape genetic methods available for elucidating key pathogen dynamics (particularly transmission and spread) and also how landscape genetic studies of pathogens can provide insight into host population dynamics. Through this review, we convey how increasing awareness of the complementarity of landscape genetics and disease ecology among practitioners of each field promises to drive important cross-disciplinary advances.

Drug-Resistance and Population Structure of Plasmodium falciparum Across the Democratic Republic of Congo Using High-Throughput Molecular Inversion Probes

A better understanding of the drivers of the spread of malaria parasites and drug resistance across space and time is needed. These drivers can be elucidated using genetic tools. Here, a novel molecular inversion probe (MIP) panel targeting all major drug-resistance mutations and a set of microsatellites was used to genotype Plasmodium falciparum infections of 552 children from the 2013-2014 Demographic and Health Survey conducted in the Democratic Republic of the Congo (DRC). Microsatellite-based analysis of population structure suggests that parasites within the DRC form a homogeneous population. In contrast, sulfadoxine-resistance markers in dihydropteroate synthase show marked spatial structure with ongoing spread of double and triple mutants compared with 2007. These findings suggest that parasites in the DRC remain panmictic despite rapidly spreading antimalarial-resistance mutations. Moreover, highly multiplexed targeted sequencing using MIPs emerges as a cost-effective method for elucidating pathogen genetics in complex infections in large cohorts.

Plasmodium falciparum genetic variation of var2csa in the Democratic Republic of the Congo

BACKGROUND

The Democratic Republic of the Congo (DRC) bears a high burden of malaria, which is exacerbated in pregnant women. The VAR2CSA protein plays a crucial role in pregnancy-associated malaria (PAM), and hence quantifying diversity at the var2csa locus in the DRC is important in understanding the basic epidemiology of PAM, and in developing a robust vaccine against PAM.

METHODS

Samples were taken from the 2013-14 Demographic and Health Survey conducted in the DRC, focusing on children under 5 years of age. A short subregion of the var2csa gene was sequenced in 115 spatial clusters, giving country-wide estimates of sequence polymorphism and spatial population structure.

RESULTS

Results indicate that var2csa is highly polymorphic, and that diversity is being maintained through balancing selection, however, there is no clear signal of phylogenetic or geographic structure to this diversity. Linear modelling demonstrates that the number of var2csa variants in a cluster correlates directly with cluster prevalence, but not with other epidemiological factors such as urbanicity.

CONCLUSIONS

Results suggest that the DRC fits within the global pattern of high var2csa diversity and little genetic differentiation between regions. A broad multivalent VAR2CSA vaccine candidate could benefit from targeting stable regions and common variants to address the substantial genetic diversity.

A deep sequencing approach to estimate Plasmodium falciparum complexity of infection (COI) and explore apical membrane antigen 1 diversity

BACKGROUND

Humans living in regions with high falciparum malaria transmission intensity harbour multi-strain infections comprised of several genetically distinct malaria haplotypes. The number of distinct malaria parasite haplotypes identified from an infected human host at a given time is referred to as the complexity of infection (COI). In this study, an amplicon-based deep sequencing method targeting the Plasmodium falciparum apical membrane antigen 1 (pfama1) was utilized to (1) investigate the relationship between P. falciparum prevalence and COI, (2) to explore the population genetic structure of P. falciparum parasites from malaria asymptomatic individuals participating in the 2007 Demographic and Health Survey (DHS) in the Democratic Republic of Congo (DRC), and (3) to explore selection pressures on geospatially divergent parasite populations by comparing AMA1 amino acid frequencies in the DRC and Mali.

RESULTS

A total of 900 P. falciparum infections across 11 DRC provinces were examined. Deep sequencing of both individuals, for COI analysis, and pools of individuals, to examine population structure, identified 77 unique pfama1 haplotypes. The majority of individual infections (64.5%) contained polyclonal (COI > 1) malaria infections based on the presence of genetically distinct pfama1 haplotypes. A minimal correlation between COI and malaria prevalence as determined by sensitive real-time PCR was identified. Population genetic analyses revealed extensive haplotype diversity, the vast majority of which was shared across the sites. AMA1 amino acid frequencies were similar between parasite populations in the DRC and Mali.

CONCLUSIONS

Amplicon-based deep sequencing is a useful tool for the detection of multi-strain infections that can aid in the understanding of antigen heterogeneity of potential malaria vaccine candidates, population genetics of malaria parasites, and factors that influence complex, polyclonal malaria infections. While AMA1 and other diverse markers under balancing selection may perform well for understanding COI, they may offer little geographic or temporal discrimination between parasite populations.