Introduction
In an era characterized by rapid environmental changes, urbanization,
and increasing human-animal interactions, the dynamics of infectious
diseases are evolving at an unprecedented pace. Large-scale programs are
dedicated to controlling or eliminating infectious diseases with the
greatest global health impact, with many of these efforts focused on
neglected tropical diseases (NTDs). While NTDs encompass fungal, viral,
and bacterial infections, the majority are caused by parasites,
particularly protozoa and helminths. Vector-borne parasitic diseases
such as malaria, trypanosomiasis, leishmaniasis and filariasis cause
greatest incidence and mortality globally .
Effective control of NTDs relies on the ability to monitor changes in
pathogen populations, ensuring that interventions stay on track toward
elimination goals and enabling targeted resource allocation. However,
conventional monitoring techniques face challenges in many
disease-endemic countries, where diagnostic tools are often limited.
This task becomes increasingly difficult as disease prevalence
decreases. Genomic epidemiology, however, can provide a deep
understanding of parasite population dynamics, enabling strategic
planning of control interventions, monitoring their effects, and raising
alerts if necessary and hence, support disease eradication efforts by
providing actionable knowledge .
While genetic data is most extensively used for diseases caused by
prokaryotes and viruses , phylodynamic tools used in viral and bacterial
genomics capture both epidemiological changes and evolutionary history,
due to the high mutation rates in these pathogens and measurable genetic
changes within the time frame of an outbreak or epidemic . However, in
pathogens with a lower mutation rate and frequent recombination, such as
eukaryotic parasites, inferring transmission events is more challenging
. The application of genomic epidemiology for these parasitic diseases
has lagged behind, hindered by the complexity of the parasite’s life
cycle and the greater size of its genome. Genetic diversity is
influenced by various factors such its life history, population
dynamics, and recent changes in population size. It is crucial to have a
comprehensive understanding of pathogen populations and an accurate
assessment of their population structure over time to accurately
evaluate the effectiveness of control interventions . This information
allows for better understanding of inbreeding patterns and gene flow
that can inform the development of improved strategies for controlling
current populations.
While population genetics of several parasite species has been analysed
using microsatellite regions, the rapid innovation and decreasing cost
of whole-genome sequencing makes it the ideal tool, since genome-wide
data have more resolution and are more comparable between populations
and pathogens, eliminating the need for validated and standardized
marker panels. For many key parasitic diseases, essential genomic
resources like annotated reference genomes are already available.
Genome-wide data can provide insights into sudden emergence and spread
of new pathogen genotypes, reveal recent strong selection on certain
genome regions, and population evolution in response to treatment and
control interventions when signs of a significant bottleneck are
detected. An example is the identification of emerging drug resistance
in the malaria parasite Plasmodium falciparum .
Malaria, caused by Plasmodium parasites, contribute to a very
high disease burden with an estimated 247 million malaria cases in 84
malaria endemic countries . However, in several countries across the
world where control efforts have reduced overall malaria cases, there
has been an increase in the proportion of P. vivax . Moreover,
substantial reductions in P. vivax prevalence over 5-10 years in
several locations have not consistently result in changes in population
structure . P. vivax accounts for 18.0% to 71.5% of malaria
cases outside Africa, with the highest proportion in the Americas . Many
countries in Latin America have made strong progress in malaria control,
reducing the malaria burden from 1.5 to 0.6 million cases between 2000
and 2021 . However, high transmission areas remain predominantly
concentrated in the Amazon rainforest regions, disproportionally
affecting indigenous and remote communities. In 2021, Venezuela,
Colombia, Brazil and Peru were in the top 4 countries contributing mostP. vivax cases (79%) in the region .
Genomic diversity in malaria parasites is generated through a
combination of de novo mutations during asexual replication and
sexual recombination within the mosquito vector. Plasmodiumparasites have a high recombination rate, and frequent infections with
multiple genetically distinct clones, especially in the case of P.
vivax . In addition, parasite genomes are polymorphic, with a diversity
of phenotypic characteristics that impact disease severity . P.
vivax often displays a higher genetic diversity than P.
falciparum , due to key biological factors including frequent subpatent
(i.e. , detectable by molecular methods but not by field
diagnostics) and asymptomatic infections, along with a hidden reservoir
of hypnozoites leading to a larger number of complex infections . The
asymptomatic infections and hypnozoites contribute to this parasite’s
resilience and facilitate its spread and gene flow across large regions,
jeopardizing the effectiveness of local and targeted elimination
strategies . Other factors contributing to the high genetic diversity ofP. vivax are its longer history of association with humans,
larger effective population size and fewer population bottlenecks .
Finally, sexual stages of P. vivax parasites appear early in the
infection, facilitating effective transmission to mosquitoes before
treatment, even at low-level parasitaemia, making the disease more
difficult to eliminate .
In Latin America, the analysis of mitochondrial genomes has previously
shown that the combined effects of geographical population structure and
the relatively low incidence of P. vivax malaria has
resulted in patterns of low local but high regional genetic diversity .
In this study, we take a population genomic approach to investigate the
spatial temporal dynamics of P. vivax in this region, using
genome wide data identified through literature and supplemented with
data from our own studies. Using high-resolution genome wide SNP
variants of these P. vivax isolates, we first compare the Latin
American P. vivax genomes to P. vivax genomes from around
the world. Next, we investigate the population structure, admixture,
relatedness and geneflow, and signatures of positive selection to study
local adaptations of the parasites. With this study we investigate if
and how the declining and more heterogenous transmission is impactingP. vivax population structure in this relatively recently
expanded population and discuss the factors driving diversity and
population structure in this ecologically diverse region. Not only is
this informative for malaria control and elimination strategies, but it
can also identify targets and key pathways important for P. vivaxsurvival.