Malaria shaped human spatial organisation for the last 74 thousand years

– Background

Many abiotic factors limit species’ distributions or create isolating barriers between populations. Biotic factors, like pathogens that cause disease as well as other interspecies interactions, can also shape the distribution and determine the presence of a species. Although new methods allow for the collection of direct evidence from the past in the form of “ancient genomes”, this evidence is severely limited and rarely available, especially the further in the past we go. Indirect evidence is more readily available, such as archeological remains and present-day genetic variation, which reflects the effects of past demographic events. In this article, the authors used an interdisciplinary approach, using multiple sources of indirect evidence, to tackle the question: Could diseases have impacted the locations of early human settlements? The authors use malaria as proof of principle, trying to go back through time (74 kya to 5 kya, thousand years ago, kya) to assess the impact of malaria on early human settlements across the Sub-Saharan Africa.
Before agriculture, early humans lived in sparse populations as hunter-gatherers, moving frequently across regions. Historical evidence suggests that the presence of multiple human subpopulations locally adapted to the conditions of their sub-habitats, which is supported by archeological and genetic evidence. Elucidating past climatic conditions has been the primary focus in understanding what factors drove our species’ distribution; however, these environments were also shared by other organisms, including those that might cause human disease. Another way to approximate this using indirect evidence is through correlations of the potential presence of the parasite with that of its host, which was the authors’ main idea in this preprint.

-Preprint key findings

The authors used species distribution models (SDM) of several mosquito vectors of Plasmodium through time. SDMs find ecological (e.g., climatic) variables that are correlated with species (2) presence. After using these correlations to reconstruct these predicted distribution through time based on the suitability of the environment as climate changed, the authors added vector characteristics to infer the potential for Plasmodium falciparum transmission using a modified vector competence formula. This was called the malaria stability index, interpreted as the potential risk of malaria transmission. Then, something similar was done on the host side, using the human niche estimates based on archeological presence with climatic variables. The method’s workflow is summarized in Fig S2 from the supplementary material (see figure above taken from the preprint) (3).
The models combine vector data to predict suitable places of malaria (estimating the malaria stability index, MSI), using Plasmodium falciparum. The MSI first increases just before the out of Africa migration ~60 Kya. A second peak in the MSI occurred around 10 Kya, preceding agricultural development (Fig 1 & 2, preprint). The main finding of this preprint comes from correlating the constructed malaria stability index with their predicted human core niche and non-core distribution through time up until 74 Kya. The result suggests that the core human distribution had minimal overlap with suitable areas that have a higher malaria stability index until ~15kya. Thus, the human modeled core niche (Fig 3, preprint) shows a lower malaria stability index, proposing a negative relationship between the malaria stability index and the suitability for human settlements. This relationship started to break down 15kya ago in West Africa, the time and place where sickle cell anaemia is thought to have arisen, likely as an adaptation that allowed humans to colonise areas that were previously too dangerous because of malaria.

– What I like about this preprint & why I think work is important

This preprint used a unique method to explore co-occurrence patterns through time and offers indirect evidence to a long-standing query. Furthermore, it showcases interdisciplinary research, combining archaeology, epidemiology, and anthropology, and the use of publicly available databases, such as the presence of mosquitoes and paleoclimate data. This article sets a precedent for using indirect evidence to predict how diseases impact a species’ distribution through time.
This preprint also made me think about potential limitations of their study, including the method, their scope, and the reconciliation with current knowledge in the field. In brief, this preprint focuses on P. falciparum, one of several parasite species that cause malaria. The divergence between P. falciparum and P. praefalciparum is estimated ~40,000 years (4), yet it remains unknown when the current P. falciparum form could become present, up-to-date evidence suggests host specificity, vector presence, and human demographic factors would all be required for the sustenance of P. falciparum, especially since P. praefalciparum has not been found in humans despite sharing the same space (6). Also, the hunter-gatherer lifestyle seems unlikely to have been able to sustain transmission of this parasite, and due to specialist behavior, unlike other species, would be unlikely to survive without humans (5). Other species that cause malaria, however, were more likely to have been present such as P. vivax which, unlike P. falciparum, have a dormant stage and could thrive under discontinuous transmission (5). This seems to match their timeframe better and is the most parsimonious explanation for malaria throughout history. Human genetic evidence supports that malaria disease played a role during this time frame in human evolution, particularly the Duffy null allele that confers resistance to P. vivax, and is nearly fixed across sub-Saharan Africa. Thus, what can be gained from their correlation is helpful, in my opinion, in shorter timeframes for P. falciparum. Furthermore, other diseases might act in addition to explain the human spatial distribution through time, as it has been proposed to be required to explain the genetic composition of human populations, which cannot be solely explained by malaria resistance (6).

 

doi: https://doi.org/10.1242/prelights.41130

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