Biology subjects

Kwiatkowski, D.

Publications and source records attributed to Kwiatkowski, D..

5 recordsLinked to original sources

bioRxiv2018

Precision identification and prediction of high mortality phenotypes and disease progression pathways in severe malaria without requiring longitudinal data

The parasite Plasmodium falciparum is the main cause of severe malaria (SM). Despite treatment with antimalarial drugs, more than 450,000 SM deaths are reported every year, mainly in African children. The diversity of clinical presentations associated with SM indicate important differences in disease pathogenesis that often require specific treatment, and this clinical heterogeneity of SM is largely unresolved. In this study, we apply new machine learning and inference tools for large-scale data analysis to dissect the heterogeneity in patterns of clinical features associated with SM in 2,695 Gambian children admitted to hospital with Plasmodium falciparum malaria. This quantitative analysis, including the powerful HyperTraPS algorithm for inference of progressive processes, reveals pathways of SM symptom progression and features predicting the severity of individual patient outcomes. Notably, our approach allows the identification and dissection of disease progression pathways without the need for longitudinal observations. Learning these pathways and features from this rich dataset allows us to construct several quantitative measures of the mortality risk associated with a patient presenting with a given set of symptoms. By independently surveying expert practitioners, we show that this data-driven approach agrees with and expands the current state of knowledge on malaria progression, while simultaneously providing a data-supported framework for predicting clinical risk.

pathology↗

bioRxiv2018

The geography of malaria elimination in Bangladesh: combining data layers to estimate the spatial spread of parasites

Malaria control programs face difficult resource allocation decisions. Of particular concern for countries aiming for malaria elimination, the regular movement of individuals to and from endemic areas undermines local interventions by reintroducing infections and sustaining local transmission. Quantifying this movement of malaria parasites around a country has become a priority for national control programs, but remains methodologically challenging, particularly in areas with highly mobile populations. Here, we combined multiple data sources to measure the geographical spread of malaria parasites, including epidemiological surveillance data, travel surveys, parasite genetic data, and anonymized mobile phone data. We collected parasite genetic barcodes and travel surveys from 2,090 patients residing in 176 unions in southeast Bangladesh. We developed a genetic mixing index to quantify the likelihood of samples being local or imported. We then inferred the direction and intensity of parasite flow between locations using an epidemiological model, and estimated the proportion of imported cases assuming mobility patterns parameterized using the travel survey and mobile phone calling data. Our results show that each data source provided related but different information about the patterns of geographic spread of parasites. We identify a consistent north/south separation of the Chittagong Hill Tracts region in Bangladesh, and found that in addition to imported infections from forested regions, frequent mixing also occurs in low transmission but highly populated areas in the southwest. Thus, unlike risk maps generated from incidence alone, our maps provide evidence that elimination programs must address ongoing movement of parasites around the lower transmission areas in the southwest.

epidemiology↗

bioRxiv2018

The origins and relatedness structure of mixed infections vary with local prevalence of P. falciparum malaria

Individual malaria infections can carry multiple strains of Plasmodium falciparum with varying levels of relatedness. Yet, how local epidemiology affects the properties of such mixed infections remains unclear. Here, we develop an enhanced method for strain deconvolution from genome sequencing data, which estimates the number of strains, their proportions, identity-by-descent (IBD) profiles and individual haplotypes. Applying it to the Pf3k data set, we find that the rate of mixed infection varies from 29% to 63% across countries and that 51% of mixed infections involve more than two strains. Further-more, we estimate that 47% of symptomatic dual infections contain sibling strains likely to have been co-transmitted from a single mosquito, and find evidence of mixed infections propagated over successive infection cycles. Finally, leveraging data from the Malaria Atlas Project, we find that prevalence correlates within Africa, but not Asia, with both the rate of mixed infection and the level of IBD.

epidemiology↗

bioRxiv2018

The genetic architecture of target-site resistance to pyrethroid insecticides in the African malaria vectors Anopheles gambiae and Anopheles coluzzii

Resistance to pyrethroid insecticides is a major concern for malaria vector control, because these are the compounds used in almost all insecticide-treated bed-nets (ITNs), and are also widely used for indoor residual spraying (IRS). Pyrethroids target the voltage-gated sodium channel (VGSC), an essential component of the mosquito nervous system, but substitutions in the amino acid sequence can disrupt the activity of these insecticides, inducing a resistance phenotype. Here we use Illumina whole-genome sequence data from phase 1 of the Anopheles gambiae 1000 Genomes Project (Ag1000G) to provide a comprehensive account of genetic variation in the Vgsc gene in mosquito populations from eight African countries. In addition to the three known resistance alleles, we describe 20 non-synonymous nucleotide substitutions at appreciable frequency in one or more populations that are previously unknown in Anopheles mosquitoes. Thirteen of these novel alleles were found to occur almost exclusively on haplotypes carrying the known L995F resistance allele (L1014F in Musca domesticus codon numbering), and may enhance or compensate for the L995F resistance pheno-type. A novel mutation I1527T, which is adjacent to a predicted pyrethroid binding site, was found in tight linkage with either of two alleles causing a V402L substitution, similar to a combination of substitutions found to cause pyrethroid resistance in several other insect species. We analyse the genetic backgrounds on which non-synonymous alleles are found, to determine which alleles have experienced recent positive selection, and to refine our understanding of the spread of resistance between species and geographical locations. We describe twelve distinct haplotype groups with evidence of recent positive selection, five of which carry the known L995F resistance allele, five of which carry the known L995S resistance allele, one of which carries the novel I1527T allele, and one of which carries a novel M490I allele. Seven of these groups are localised to a single geographical location, and five comprise haplotypes from different countries, in one case separated by over 3000 km, providing new information about the geographical distribution and spread of resistance. We also find evidence for multiple introgression events transmitting resistance alleles between An. gambiae and An. coluzzii. We identify markers that could be used to design high-throughput, low-cost genetic assays for improved surveillance of pyrethroid resistance in the field. Our results demonstrate that the molecular basis of target-site pyrethroid resistance in malaria vectors is more complex than previously appreciated, and provide a foundation for the development of new genetic tools to track the spread insecticide resistance and improve the design of strategies for insecticide resistance management.

genomics↗

bioRxiv2017

Inferring adaptive gene-flow in recent African history

Gene-flow from an ancestrally differentiated group has been shown to be a powerful source of selectively advantageous variants. To understand whether recent gene-flow may have contributed to adaptation among humans in sub-Saharan Africa, we applied a novel method to identify deviations in ancestry inferred from genome-wide data in 48 populations. Among the signals of ancestry deviation that we find in the Fula, an historically pastoralist ethnic group from the Gambia, are the region that encodes the lactose persistence phenotype, LCT/MCM6, which has the highest proportion of Eurasian ancestry in the genome. The region with the lowest proportion of non-African ancestry is across DARC, which encodes the Duffy null phenotype and is protective for Plasmodium vivax malaria. In the Jola from the Gambia and a Khoesan speaking group from Namibia we find multiple regions with inferred ancestry deviation including the Major Histocompatibility Complex. Our analysis shows the potential for adaptive gene-flow in recent human history.

evolutionary biology↗