Roberto Amato

Genetic architecture of artemisinin-resistant Plasmodium falciparum

We report a large multicenter genome-wide association study of Plasmodium falciparum resistance to artemisinin, the frontline antimalarial drug. Across 15 locations in Southeast Asia, we identified at least 20 mutations in kelch13 (PF3D7_1343700) affecting the encoded propeller and BTB/POZ domains, which were associated with a slow parasite clearance rate after treatment with artemisinin derivatives. Nonsynonymous polymorphisms in fd (ferredoxin), arps10 (apicoplast ribosomal protein S10), mdr2 (multidrug resistance protein 2) and crt (chloroquine resistance transporter) also showed strong associations with artemisinin resistance. Analysis of the fine structure of the parasite population showed that the fd, arps10, mdr2 and crt polymorphisms are markers of a genetic background on which kelch13 mutations are particularly likely to arise and that they correlate with the contemporary geographical boundaries and population frequencies of artemisinin resistance. These findings indicate that the risk of new resistance-causing mutations emerging is determined by specific predisposing genetic factors in the underlying parasite population.

Dihydroartemisinin–piperaquine resistance in Plasmodium falciparum malaria in Cambodia: a multisite prospective cohort study

BACKGROUND Artemisinin resistance in Plasmodium falciparum threatens to reduce the efficacy of artemisinin combination therapies (ACTs), thus compromising global efforts to eliminate malaria. Recent treatment failures with dihydroartemisinin-piperaquine, the current first-line ACT in Cambodia, suggest that piperaquine resistance may be emerging in this country. We explored the relation between artemisinin resistance and dihydroartemisinin-piperaquine failures, and sought to confirm the presence of piperaquine-resistant P falciparum infections in Cambodia. METHODS In this prospective cohort study, we enrolled patients aged 2-65 years with uncomplicated P falciparum malaria in three Cambodian provinces: Pursat, Preah Vihear, and Ratanakiri. Participants were given standard 3-day courses of dihydroartemisinin-piperaquine. Peripheral blood parasite densities were measured until parasites cleared and then weekly to 63 days. The primary outcome was recrudescent P falciparum parasitaemia within 63 days. We measured piperaquine plasma concentrations at baseline, 7 days, and day of recrudescence. We assessed phenotypic and genotypic markers of drug resistance in parasite isolates. The study is registered with ClinicalTrials.gov, number NCT01736319. FINDINGS Between Sept 4, 2012, and Dec 31, 2013, we enrolled 241 participants. In Pursat, where artemisinin resistance is entrenched, 37 (46%) of 81 patients had parasite recrudescence. In Preah Vihear, where artemisinin resistance is emerging, ten (16%) of 63 patients had recrudescence and in Ratanakiri, where artemisinin resistance is rare, one (2%) of 60 patients did. Patients with recrudescent P falciparum infections were more likely to have detectable piperaquine plasma concentrations at baseline compared with non-recrudescent patients, but did not differ significantly in age, initial parasite density, or piperaquine plasma concentrations at 7 days. Recrudescent parasites had a higher prevalence of kelch13 mutations, higher piperaquine 50% inhibitory concentration (IC50) values, and lower mefloquine IC50 values; none had multiple pfmdr1 copies, a genetic marker of mefloquine resistance. INTERPRETATION Dihydroartemisinin-piperaquine failures are caused by both artemisinin and piperaquine resistance, and commonly occur in places where dihydroartemisinin-piperaquine has been used in the private sector. In Cambodia, artesunate plus mefloquine may be a viable option to treat dihydroartemisinin-piperaquine failures, and a more effective first-line ACT in areas where dihydroartemisinin-piperaquine failures are common. The use of single low-dose primaquine to eliminate circulating gametocytes is needed in areas where artemisinin and ACT resistance is prevalent. FUNDING National Institute of Allergy and Infectious Diseases.

Genetic markers associated with dihydroartemisinin–piperaquine failure in Plasmodium falciparum malaria in Cambodia: a genotype–phenotype association study

BACKGROUND As the prevalence of artemisinin-resistant Plasmodium falciparum malaria increases in the Greater Mekong subregion, emerging resistance to partner drugs in artemisinin combination therapies seriously threatens global efforts to treat and eliminate this disease. Molecular markers that predict failure of artemisinin combination therapy are urgently needed to monitor the spread of partner drug resistance, and to recommend alternative treatments in southeast Asia and beyond. METHODS We did a genome-wide association study of 297 P falciparum isolates from Cambodia to investigate the relationship of 11 630 exonic single-nucleotide polymorphisms (SNPs) and 43 copy number variations (CNVs) with in-vitro piperaquine 50% inhibitory concentrations (IC50s), and tested whether these genetic variants are markers of treatment failure with dihydroartemisinin-piperaquine. We then did a survival analysis of 133 patients to determine whether candidate molecular markers predicted parasite recrudescence following dihydroartemisinin-piperaquine treatment. FINDINGS Piperaquine IC50s increased significantly from 2011 to 2013 in three Cambodian provinces (2011 vs 2013 median IC50s: 20·0 nmol/L [IQR 13·7-29·0] vs 39·2 nmol/L [32·8-48·1] for Ratanakiri, 19·3 nmol/L [15·1-26·2] vs 66·2 nmol/L [49·9-83·0] for Preah Vihear, and 19·6 nmol/L [11·9-33·9] vs 81·1 nmol/L [61·3-113·1] for Pursat; all p≤10-3; Kruskal-Wallis test). Genome-wide analysis of SNPs identified a chromosome 13 region that associates with raised piperaquine IC50s. A non-synonymous SNP (encoding a Glu415Gly substitution) in this region, within a gene encoding an exonuclease, associates with parasite recrudescence following dihydroartemisinin-piperaquine treatment. Genome-wide analysis of CNVs revealed that a single copy of the mdr1 gene on chromosome 5 and a novel amplification of the plasmepsin 2 and plasmepsin 3 genes on chromosome 14 also associate with raised piperaquine IC50s. After adjusting for covariates, both exo-E415G and plasmepsin 2-3 markers significantly associate (p=3·0 × 10-8 and p=1·7 × 10-7, respectively) with decreased treatment efficacy (survival rates 0·38 [95% CI 0·25-0·51] and 0·41 [0·28-0·53], respectively). INTERPRETATION The exo-E415G SNP and plasmepsin 2-3 amplification are markers of piperaquine resistance and dihydroartemisinin-piperaquine failures in Cambodia, and can help monitor the spread of these phenotypes into other countries of the Greater Mekong subregion, and elucidate the mechanism of piperaquine resistance. Since plasmepsins are involved in the parasites haemoglobin-to-haemozoin conversion pathway, targeted by related antimalarials, plasmepsin 2-3 amplification probably mediates piperaquine resistance. FUNDING Intramural Research Program of the US National Institute of Allergy and Infectious Diseases, National Institutes of Health, Wellcome Trust, Bill & Melinda Gates Foundation, Medical Research Council, and UK Department for International Development.

Genomic analysis of local variation and recent evolution in Plasmodium vivax

The widespread distribution and relapsing nature of Plasmodium vivax infection present major challenges for the elimination of malaria. To characterize the genetic diversity of this parasite in individual infections and across the population, we performed deep genome sequencing of >200 clinical samples collected across the Asia-Pacific region and analyzed data on >300,000 SNPs and nine regions of the genome with large copy number variations. Individual infections showed complex patterns of genetic structure, with variation not only in the number of dominant clones but also in their level of relatedness and inbreeding. At the population level, we observed strong signals of recent evolutionary selection both in known drug resistance genes and at new loci, and these varied markedly between geographical locations. These findings demonstrate a dynamic landscape of local evolutionary adaptation in the parasite population and provide a foundation for genomic surveillance to guide effective strategies for control and elimination of P. vivax.

Genome-wide scan for signatures of human population differentiation and their relationship with natural selection, functional pathways and diseases.

Genetic differences both between individuals and populations are studied for their evolutionary relevance and for their potential medical applications. Most of the genetic differentiation among populations are caused by random drift that should affect all loci across the genome in a similar manner. When a locus shows extraordinary high or low levels of population differentiation, this may be interpreted as evidence for natural selection. The most used measure of population differentiation was devised by Wright and is known as fixation index, or FST. We performed a genome-wide estimation of FST on about 4 millions of SNPs from HapMap project data. We demonstrated a heterogeneous distribution of FST values between autosomes and heterochromosomes. When we compared the FST values obtained in this study with another evolutionary measure obtained by comparative interspecific approach, we found that genes under positive selection appeared to show low levels of population differentiation. We applied a gene set approach, widely used for microarray data analysis, to detect functional pathways under selection. We found that one pathway related to antigen processing and presentation showed low levels of FST, while several pathways related to cell signalling, growth and morphogenesis showed high FST values. Finally, we detected a signature of selection within genes associated with human complex diseases. These results can help to identify which process occurred during human evolution and adaptation to different environments. They also support the hypothesis that common diseases could have a genetic background shaped by human evolution.

A novel approach to simulate gene-environment interactions in complex diseases

BackgroundComplex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the major part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.). Despite a large amount of information that has been collected about both genetic and environmental risk factors, there are few examples of studies on their interactions in epidemiological literature. One reason can be the incomplete knowledge of the power of statistical methods designed to search for risk factors and their interactions in these data sets. An improvement in this direction would lead to a better understanding and description of gene-environment interactions. To this aim, a possible strategy is to challenge the different statistical methods against data sets where the underlying phenomenon is completely known and fully controllable, for example simulated ones.ResultsWe present a mathematical approach that models gene-environment interactions. By this method it is possible to generate simulated populations having gene-environment interactions of any form, involving any number of genetic and environmental factors and also allowing non-linear interactions as epistasis. In particular, we implemented a simple version of this model in a Gene-Environment iNteraction Simulator (GENS), a tool designed to simulate case-control data sets where a one gene-one environment interaction influences the disease risk. The main aim has been to allow the input of population characteristics by using standard epidemiological measures and to implement constraints to make the simulator behaviour biologically meaningful.ConclusionsBy the multi-logistic model implemented in GENS it is possible to simulate case-control samples of complex disease where gene-environment interactions influence the disease risk. The user has full control of the main characteristics of the simulated population and a Monte Carlo process allows random variability. A knowledge-based approach reduces the complexity of the mathematical model by using reasonable biological constraints and makes the simulation more understandable in biological terms. Simulated data sets can be used for the assessment of novel statistical methods or for the evaluation of the statistical power when designing a study.

Schizophrenia and vitamin D related genes could have been subject to latitude-driven adaptation

BackgroundMany natural phenomena are directly or indirectly related to latitude. Living at different latitudes, indeed, has its consequences with being exposed to different climates, diets, light/dark cycles, etc. In humans, one of the best known examples of genetic traits following a latitudinal gradient is skin pigmentation. Nevertheless, also several diseases show latitudinal clinals such as hypertension, cancer, dismetabolic conditions, schizophrenia, Parkinsons disease and many more.ResultsWe investigated, for the first time on a wide genomic scale, the latitude-driven adaptation phenomena. In particular, we selected a set of genes showing signs of latitude-dependent population differentiation. The biological characterization of these genes showed enrichment for neural-related processes. In light of this, we investigated whether genes associated to neuropsychiatric diseases were enriched by Latitude-Related Genes (LRGs). We found a strong enrichment of LRGs in the set of genes associated to schizophrenia. In an attempt to try to explain this possible link between latitude and schizophrenia, we investigated their associations with vitamin D. We found in a set of vitamin D related genes a significant enrichment of both LRGs and of genes involved in schizophrenia.ConclusionsOur results suggest a latitude-driven adaptation for both schizophrenia and vitamin D related genes. In addition we confirm, at a molecular level, the link between schizophrenia and vitamin D. Finally, we discuss a model in which schizophrenia is, at least partly, a maladaptive by-product of latitude dependent adaptive changes in vitamin D metabolism.

Estimating Geographical Variation in the Risk of Zoonotic Plasmodium knowlesi Infection in Countries Eliminating Malaria

Background Infection by the simian malaria parasite, Plasmodium knowlesi, can lead to severe and fatal disease in humans, and is the most common cause of malaria in parts of Malaysia. Despite being a serious public health concern, the geographical distribution of P. knowlesi malaria risk is poorly understood because the parasite is often misidentified as one of the human malarias. Human cases have been confirmed in at least nine Southeast Asian countries, many of which are making progress towards eliminating the human malarias. Understanding the geographical distribution of P. knowlesi is important for identifying areas where malaria transmission will continue after the human malarias have been eliminated. Methodology/Principal Findings A total of 439 records of P. knowlesi infections in humans, macaque reservoir and vector species were collated. To predict spatial variation in disease risk, a model was fitted using records from countries where the infection data coverage is high. Predictions were then made throughout Southeast Asia, including regions where infection data are sparse. The resulting map predicts areas of high risk for P. knowlesi infection in a number of countries that are forecast to be malaria-free by 2025 (Malaysia, Cambodia, Thailand and Vietnam) as well as countries projected to be eliminating malaria (Myanmar, Laos, Indonesia and the Philippines). Conclusions/Significance We have produced the first map of P. knowlesi malaria risk, at a fine-scale resolution, to identify priority areas for surveillance based on regions with sparse data and high estimated risk. Our map provides an initial evidence base to better understand the spatial distribution of this disease and its potential wider contribution to malaria incidence. Considering malaria elimination goals, areas for prioritised surveillance are identified.

A Genome Wide Association Study of Plasmodium falciparum Susceptibility to 22 Antimalarial Drugs in Kenya

Background Drug resistance remains a chief concern for malaria control. In order to determine the genetic markers of drug resistant parasites, we tested the genome-wide associations (GWA) of sequence-based genotypes from 35 Kenyan P. falciparum parasites with the activities of 22 antimalarial drugs. Methods and Principal Findings Parasites isolated from children with acute febrile malaria were adapted to culture, and sensitivity was determined by in vitro growth in the presence of anti-malarial drugs. Parasites were genotyped using whole genome sequencing techniques. Associations between 6250 single nucleotide polymorphisms (SNPs) and resistance to individual anti-malarial agents were determined, with false discovery rate adjustment for multiple hypothesis testing. We identified expected associations in the pfcrt region with chloroquine (CQ) activity, and other novel loci associated with amodiaquine, quinazoline, and quinine activities. Signals for CQ and primaquine (PQ) overlap in and around pfcrt, and interestingly the phenotypes are inversely related for these two drugs. We catalog the variation in dhfr, dhps, mdr1, nhe, and crt, including novel SNPs, and confirm the presence of a dhfr-164L quadruple mutant in coastal Kenya. Mutations implicated in sulfadoxine-pyrimethamine resistance are at or near fixation in this sample set. Conclusions/Significance Sequence-based GWA studies are powerful tools for phenotypic association tests. Using this approach on falciparum parasites from coastal Kenya we identified known and previously unreported genes associated with phenotypic resistance to anti-malarial drugs, and observe in high-resolution haplotype visualizations a possible signature of an inverse selective relationship between CQ and PQ.

THE REAL McCOIL: A method for the concurrent estimation of the complexity of infection and SNP allele frequency for malaria parasites.

As many malaria-endemic countries move towards elimination of Plasmodium falciparum, the most virulent human malaria parasite, effective tools for monitoring malaria epidemiology are urgent priorities. P. falciparum population genetic approaches offer promising tools for understanding transmission and spread of the disease, but a high prevalence of multi-clone or polygenomic infections can render estimation of even the most basic parameters, such as allele frequencies, challenging. A previous method, COIL, was developed to estimate complexity of infection (COI) from single nucleotide polymorphism (SNP) data, but relies on monogenomic infections to estimate allele frequencies or requires external allele frequency data which may not available. Estimates limited to monogenomic infections may not be representative, however, and when the average COI is high, they can be difficult or impossible to obtain. Therefore, we developed THE REAL McCOIL, Turning HEterozygous SNP data into Robust Estimates of ALelle frequency, via Markov chain Monte Carlo, and Complexity Of Infection using Likelihood, to incorporate polygenomic samples and simultaneously estimate allele frequency and COI. This approach was tested via simulations then applied to SNP data from cross-sectional surveys performed in three Ugandan sites with varying malaria transmission. We show that THE REAL McCOIL consistently outperforms COIL on simulated data, particularly when most infections are polygenomic. Using field data we show that, unlike with COIL, we can distinguish epidemiologically relevant differences in COI between and within these sites. Surprisingly, for example, we estimated high average COI in a peri-urban subregion with lower transmission intensity, suggesting that many of these cases were imported from surrounding regions with higher transmission intensity. THE REAL McCOIL therefore provides a robust tool for understanding the molecular epidemiology of malaria across transmission settings.