Dissecting the genetic bases of severe malaria resistance using genome-wide and post genomewide study approaches

P. falciparum malaria remains one of the leading public health problems worldwide. The global tally of malaria in 2018 was estimated at 228 million cases and 405, 000 deaths worldwide. African countries disproportionately carry the global burden of malaria accounting for 93% and 94% of cases and deaths, respectively. Even though most infected children recover from P. falciparum malaria, a small subset (~1%) of cases progresses to severe disease and death. Over the last decade, several genome-wide association studies (GWASs) have been conducted in diverse malaria endemic populations to understand the natural host protective immunity against severe malaria that can provide clues for the development of new vaccines and therapeutics. However, beyond identifying association variants, conventional GWAS approaches can't inform the underpinning biological functions. To bridge this gap, we applied various contemporary statistical genetic analytic approaches to malaria GWAS datasets of diverse malaria endemic populations. First, we accessed malaria resistance GWAS datasets of three African populations (N=~11,000) including Kenya, Gambia and Malawi from European Genome Phenome Archive (EGA) through MalariaGEN consortium standard data accession procedures. We explored the challenges of GWAS approaches in the genetically diverse Africa populations and figured out how various advanced statistical genetic methods can be implemented to address these challenges. We investigated single nucleotide polymorphism (SNP) heritability (h2 g) of malaria resistance in the Gambian populations and determined appropriate quality (QC) thresholds to accurately estimate the h2 g in our dataset. Second, we estimated h2 g in the three populations and partitioned the h2 g into chromosomes, allele frequencies and annotations using the genetic relationship-matrix restricted maximum likelihood approaches. We further created African specific reference panel from African population datasets obtained from 1000 Genomes Project and African Genome Variation Project dataset and computed linkage disequilibrium (LD). We used LD information obtained from these reference panels to compute cell-type specific and none cell-type specific enrichments for GWAS-summary statistics meta-analyzed across the three populations. Our results showed for the first time that malaria resistance is polygenic trait with h2 g of ~20% and that the causal variants are overrepresented around protein coding regions of the genome. We further showed that the h2 g is disproportionately concentrated on three chromosomes (chr 5, 11 and 20), suggesting cost-effectiveness of targeting these chromosomes in future malaria genomic sequencing studies. Third, we systematically predicted plausible candidate genes and pathways from functional analysis of severe malaria resistance GWAS summary statistics (N = 17,000) meta-analyzed across eleven populations in malaria endemic regions in Africa, Asia and Oceania. We applied positional mapping, expression quantitative trait locus (eQTL), chromatin interaction mapping and gene-based association analyses to identify candidate severe malaria resistance genes. We performed network and pathway analyses to investigate their shared biological functions. We further applied rare variant analysis to raw GWAS datasets of three malaria endemic populations including Kenya, Malawi and Gambia and performed various population genetic structures of the identified genes in the three endemic populations and 20 world-wide ethnics. Our functional mapping analysis identified 57 genes located in the known malaria genomic loci while our gene-based GWAS analysis identified additional 125 genes across the genome. The identified genes were significantly enriched in malaria pathogenic pathways including multiple overlapping pathways in erythrocyte-related functions, blood coagulations, ion channels, adhesion molecules, membrane signaling elements and neuronal systems. Furthermore, our population genetic analysis revealed that the minor allele frequencies (MAF) of the SNPs residing in the identified genes are generally higher in the three malaria endemic populations compared to global populations. Overall, our results suggest that severe malaria resistance trait is attributed to multiple genes that are enriched in pathways linked to severe malaria pathogenesis. This highlights the possibility of harnessing new malaria therapeutics that can simultaneously target multiple malaria protective host molecular pathways. In conclusions, this project showed that malaria resistance trait is mainly a polygenic trait which is influenced by genes and pathways linked to blood stage lifecycle of P. falciparum. These findings constitute the foundations for future experimental studies that can potentially lead to translational medicine including development of new vaccines and therapeutics. However, ‘-omics' studies including those implemented in this study, are limited to single datatype analysis and lack adequate power to explain the complexity of molecular processes and usually lead to identification of correlations than causations. Thus, beyond singe locus analysis, the future direction of malaria resistance requires a paradigm shift from single-omics to multi-stage and multi-dimensional integrative multi-omics studies that combines multiple data types from the human host, the parasite, and the environment. The current biotechnological and statistical advances may eventually lead to the feasibility of systems biology studies and revolutionize malaria research

Genome-wide association studies of severe P. falciparum malaria susceptibility: progress, pitfalls and prospects

Abstract Background P. falciparum malaria has been recognized as one of the prominent evolutionary selective forces of human genome that led to the emergence of multiple host protective alleles. A comprehensive understanding of the genetic bases of severe malaria susceptibility and resistance can potentially pave ways to the development of new therapeutics and vaccines. Genome-wide association studies (GWASs) have recently been implemented in malaria endemic areas and identified a number of novel association genetic variants. However, there are several open questions around heritability, epistatic interactions, genetic correlations and associated molecular pathways among others. Here, we assess the progress and pitfalls of severe malaria susceptibility GWASs and discuss the biology of the novel variants. Results We obtained all severe malaria susceptibility GWASs published thus far and accessed GWAS dataset of Gambian populations from European Phenome Genome Archive (EGA) through the MalariaGen consortium standard data access protocols. We noticed that, while some of the well-known variants including HbS and ABO blood group were replicated across endemic populations, only few novel variants were convincingly identified and their biological functions remain to be understood. We estimated SNP-heritability of severe malaria at 20.1% in Gambian populations and showed how advanced statistical genetic analytic methods can potentially be implemented in malaria susceptibility studies to provide useful functional insights. Conclusions The ultimate goal of malaria susceptibility study is to discover a novel causal biological pathway that provide protections against severe malaria; a fundamental step towards translational medicine such as development of vaccine and new therapeutics. Beyond singe locus analysis, the future direction of malaria susceptibility requires a paradigm shift from single -omics to multi-stage and multi-dimensional integrative functional studies that combines multiple data types from the human host, the parasite, the mosquitoes and the environment. The current biotechnological and statistical advances may eventually lead to the feasibility of systems biology studies and revolutionize malaria research

Spatial distribution of Glossina sp. and Trypanosoma sp. in south-western Ethiopia

Background Accurate information on the distribution of the tsetse fly is of paramount importance to better control animal trypanosomosis. Entomological and parasitological surveys were conducted in the tsetse belt of south-western Ethiopia to describe the prevalence of trypanosomosis (PoT), the abundance of tsetse flies (AT) and to evaluate the association with potential risk factors. Methods The study was conducted between 2009 and 2012. The parasitological survey data were analysed by a random effects logistic regression model, whereas the entomological survey data were analysed by a Poisson regression model. The percentage of animals with trypanosomosis was regressed on the tsetse fly count using a random effects logistic regression model. Results The following six risk factors were evaluated for PoT (i) altitude: significant and inverse correlation with trypanosomosis, (ii) annual variation of PoT: no significant difference between years, (iii) regional state: compared to Benishangul-Gumuz (18.0 %), the three remaining regional states showed significantly lower PoT, (iv) river system: the PoT differed significantly between the river systems, (iv) sex: male animals (11.0 %) were more affected than females (9.0 %), and finally (vi) age at sampling: no difference between the considered classes. Observed trypanosome species were T. congolense (76.0 %), T. vivax (18.1 %), T. b. brucei (3.6 %), and mixed T. congolense/vivax (2.4 %). The first four risk factors listed above were also evaluated for AT, and all have a significant effect on AT. In the multivariable model only altitude was retained with AT decreasing with increasing altitude. Four different Glossina species were identified i.e. G. tachinoides (52.0 %), G. pallidipes (26.0 %), G.morsitans submorsitans (15.0 %) and G. fuscipes fuscipes (7.0 %). Significant differences in catches/trap/day between districts were observed for each species. No association could be found between the tsetse fly counts and trypanosomosis prevalence. Conclusions Trypanosomosis remains a constraint to livestock production in south-western Ethiopia. Four Glossina and three Trypanosoma species were observed. Altitude had a significant impact on AT and PoT. PoT is not associated with AT, which could be explained by the importance of mechanical transmission. This needs to be investigated further as it might jeopardize control strategies that target the tsetse fly population

Insilico Functional Analysis of Genome-Wide Dataset From 17,000 Individuals Identifies Candidate Malaria Resistance Genes Enriched in Malaria Pathogenic Pathways

Recent genome-wide association studies (GWASs) of severe malaria have identified several association variants. However, much about the underlying biological functions are yet to be discovered. Here, we systematically predicted plausible candidate genes and pathways from functional analysis of severe malaria resistance GWAS summary statistics (N = 17,000) meta-analysed across 11 populations in malaria endemic regions. We applied positional mapping, expression quantitative trait locus (eQTL), chromatin interaction mapping, and gene-based association analyses to identify candidate severe malaria resistance genes. We further applied rare variant analysis to raw GWAS datasets (N = 11,000) of three malaria endemic populations including Kenya, Malawi, and Gambia and performed various population genetic structures of the identified genes in the three populations and global populations. We performed network and pathway analyses to investigate their shared biological functions. Our functional mapping analysis identified 57 genes located in the known malaria genomic loci, while our gene-based GWAS analysis identified additional 125 genes across the genome. The identified genes were significantly enriched in malaria pathogenic pathways including multiple overlapping pathways in erythrocyte-related functions, blood coagulations, ion channels, adhesion molecules, membrane signalling elements, and neuronal systems. Our population genetic analysis revealed that the minor allele frequencies (MAF) of the single nucleotide polymorphisms (SNPs) residing in the identified genes are generally higher in the three malaria endemic populations compared to global populations. Overall, our results suggest that severe malaria resistance trait is attributed to multiple genes, highlighting the possibility of harnessing new malaria therapeutics that can simultaneously target multiple malaria protective host molecular pathways

Network-driven analysis of human–Plasmodium falciparum interactome: processes for malaria drug discovery and extracting in silico targets

Background The emergence and spread of malaria drug resistance have resulted in the need to understand disease mechanisms and importantly identify essential targets and potential drug candidates. Malaria infection involves the complex interaction between the host and pathogen, thus, functional interactions between human and Plasmodium falciparum is essential to obtain a holistic view of the genetic architecture of malaria. Several functional interaction studies have extended the understanding of malaria disease and integrating such datasets would provide further insights towards understanding drug resistance and/or genetic resistance/susceptibility, disease pathogenesis, and drug discovery. Methods This study curated and analysed data including pathogen and host selective genes, host and pathogen protein sequence data, protein–protein interaction datasets, and drug data from literature and databases to perform human-host and P. falciparum network-based analysis. An integrative computational framework is presented that was developed and found to be reasonably accurate based on various evaluations, applications, and experimental evidence of outputs produced, from data-driven analysis. Results This approach revealed 8 hub protein targets essential for parasite and human host-directed malaria drug therapy. In a semantic similarity approach, 26 potential repurposable drugs involved in regulating host immune response to inflammatory-driven disorders and/or inhibiting residual malaria infection that can be appropriated for malaria treatment. Further analysis of host–pathogen network shortest paths enabled the prediction of immune-related biological processes and pathways subverted by P. falciparum to increase its within-host survival. Conclusions Host–pathogen network analysis reveals potential drug targets and biological processes and pathways subverted by P. falciparum to enhance its within malaria host survival. The results presented have implications for drug discovery and will inform experimental studies

Genetic diversity and drug susceptibility profiles of Mycobacterium tuberculosis obtained from Saint Peter's TB specialized Hospital, Ethiopia.

BackgroundTuberculosis (TB) is one of the major public health problems in Ethiopia. Data on genetic diversity and resistance profile of circulating TB strains is critical for informing the national TB control program.MethodsA cross-sectional study was conducted on 213 smear positive pulmonary TB patients between 2015 and 2016. Sputum samples were cultured on LJ media following the Petroff's method. Region of difference-9 (RD9)-deletion typing and spoligo-typing were performed for molecular analysis of M. tuberculosis at species and strain levels, respectively. Drug sensitivity and mutation patterns of the isolates were assessed by the conventional indirect proportion method and molecular line probe assays (LPAs), respectively. Data were analyzed using statistical package for social sciences (SPSS) software version 20.ResultsSpoligo-typing of 150 M. tuberculosis isolates led to 57 different patterns of which 25 were new strains. The majority (71.6%) of the isolates were grouped in to 17 clusters consisting 2 to 24 isolates. The majority of the strains belonged to Euro-American lineage and the predominant spoligotypes were SIT 37 and SIT 149. MDR-TB was detected in 5.2% and 20.3% of new and retreatment cases, respectively. Two MDR-TB isolates exhibited additional resistance to one of the second line anti-TB drugs. Common gene mutations including S531L, S315T1 and M306V were detected in RIF, INH and EMB resistant strains, respectively.ConclusionsThe identification of several new strains, higher proportion of MDR-TB and higher clustering rate in this study, warrants the need for re-enforcement of the national TB control program. The detection of common gene mutations in the majority drug resistant strains might suggest the feasibility of LPAs for rapid screening of drug resistant M. tuberculosis strains in Ethiopia

Use of an Alignment-Free Method for the Geographical Discrimination of GTPVs Based on the GPCR Sequences

International audienceThis article is an oGoatpox virus (GTPV) belongs to the genus Capripoxvirus, together with sheeppox virus (SPPV) and lumpy skin disease virus (LSDV). GTPV primarily affects sheep, goats and some wild ruminants. Although GTPV is only present in Africa and Asia, the recent spread of LSDV in Europe and Asia shows capripoxviruses could escape their traditional geographical regions to cause severe outbreaks in new areas. Therefore, it is crucial to develop effective source tracing of capripoxvirus infections. Earlier, conventional phylogenetic methods, based on limited samples, identified three different nucleotide sequence profiles in the G-protein-coupled chemokine receptor (GPCR) gene of GTPVs. However, this method did not differentiate GTPV strains by their geographical origins. We have sequenced the GPCR gene of additional GTPVs and analyzed them with publicly available sequences, using conventional alignment-based methods and an alignment-free approach exploiting k-mer frequencies. Using the alignment-free method, we can now classify GTPVs based on their geographical origin: African GTPVs and Asian GTPVs, which further split into Western and Central Asian (WCA) GTPVs and Eastern and Southern Asian (ESA) GTPVs. This approach will help determine the source of introduction in GTPV emergence in disease-free regions and detect the importation of additional strains in disease-endemic area