Genome-wide and fine-resolution association analysis of malaria in West Africa

Inferring strain-level mutational drivers of phage-bacteria interaction phenotypes arising during coevolutionary dynamics

The enormous diversity of bacteriophages and their bacterial hosts presents a significant challenge to predict which phages infect a focal set of bacteria. Infection is largely determined by complementary-and largely uncharacterized-genetics of adsorption, injection, cell take-over, and lysis. Here we present a machine learning approach to predict phage-bacteria interactions trained on genome sequences of and phenotypic interactions among 51 Escherichia coli strains and 45 phage λ strains that coevolved in laboratory conditions for 37 days. Leveraging multiple inference strategies and without a priori knowledge of driver mutations, this framework predicts both who infects whom and the quantitative levels of infections across a suite of 2,295 potential interactions. We found that the most effective approach inferred interaction phenotypes from independent contributions from phage and bacteria mutations, accurately predicting 86% of interactions while reducing the relative error in the estimated strength of the infection phenotype by 40%. Feature selection revealed key phage λ and Escherchia coli mutations that have a significant influence on the outcome of phage-bacteria interactions, corroborating sites previously known to affect phage λ infections, as well as identifying mutations in genes of unknown function not previously shown to influence bacterial resistance. The method's success in recapitulating strain-level infection outcomes arising during coevolutionary dynamics may also help inform generalized approaches for imputing genetic drivers of interaction phenotypes in complex communities of phage and bacteria.

Inferring strain-level mutational drivers of phage-bacteria interaction phenotypes arising during coevolutionary dynamics

The enormous diversity of bacteriophages and their bacterial hosts presents a significant challenge to predict which phages infect a focal set of bacteria. Infection is largely determined by complementary - and largely uncharacterized - genetics of adsorption, injection, cell take-over and lysis. Here we present a machine learning approach to predict phage-bacteria interactions trained on genome sequences of and phenotypic interactions amongst 51 Escherichia coli strains and 45 phage λ strains that coevolved in laboratory conditions for 37 days. Leveraging multiple inference strategies and without a priori knowledge of driver mutations, this framework predicts both who infects whom and the quantitative levels of infections across a suite of 2,295 potential interactions. We found that the most effective approach inferred interaction phenotypes from independent contributions from phage and bacteria mutations, accurately predicting 86 % of interactions while reducing the relative error in the estimated strength of the infection phenotype by 40 % . Feature selection revealed key phage λ and E. coli mutations that have a significant influence on the outcome of phage-bacteria interactions, corroborating sites previously known to affect phage λ infections, as well as identifying mutations in genes of unknown function not previously shown to influence bacterial resistance. The method's success in recapitulating strain-level infection outcomes arising during coevolutionary dynamics may also help inform generalized approaches for imputing genetic drivers of interaction phenotypes in complex communities of phage and bacteria.

From Genome-wide Association Studies to Functional Variants: ARL14 Cis-regulatory Variants Are Associated With Severe Malaria

BACKGROUND

Genome-wide association studies have identified several nonfunctional tag single-nucleotide polymorphisms (SNPs) associated with severe malaria. We hypothesized that causal SNPs could play a significant role in severe malaria by altering promoter or enhancer activity. Here, we sought to identify such regulatory SNPs.

METHODS

SNPs in linkage disequilibrium with tagSNPs associated with severe malaria were identified and were further annotated using FUMA. Then, SNPs were prioritized using the integrative weighted scoring method to identify regulatory ones. Gene reporter assays were performed to assess the regulatory effect of a region containing candidates. The association between SNPs and severe malaria was assessed using logistic regression models in a Senegalese cohort.

RESULTS

Among 418 SNPs, the best candidates were rs116525449 and rs79644959, which were in full disequilibrium between them, and located within the ARL14 promoter. Our gene reporter assay results revealed that the region containing the SNPs exhibited cell-specific promoter or enhancer activity, while the SNPs influenced promoter activity. We detected an association between severe malaria and those 2 SNPs using the overdominance model and we replicated the association of severe malaria with the tagSNP rs116423146.

CONCLUSIONS

We suggest that these SNPs regulate ARL14 expression in immune cells and the presentation of antigens to T lymphocytes, thus influencing severe malaria development.

Hunter-gatherer genetics research: Importance and avenues

Major developments in the field of genetics in the past few decades have revolutionised notions of what it means to be human. Although currently only a few populations around the world practise a hunting and gathering lifestyle, this mode of subsistence has characterised members of our species since its very origins and allowed us to migrate across the planet. Therefore, the geographical distribution of hunter-gatherer populations, dependence on local ecosystems and connections to past populations and neighbouring groups have provided unique insights into our evolutionary origins. However, given the vulnerable status of hunter-gatherers worldwide, the development of the field of anthropological genetics requires that we reevaluate how we conduct research with these communities. Here, we review how the inclusion of hunter-gatherer populations in genetics studies has advanced our understanding of human origins, ancient population migrations and interactions as well as phenotypic adaptations and adaptability to different environments, and the important scientific and medical applications of these advancements. At the same time, we highlight the necessity to address yet unresolved questions and identify areas in which the field may benefit from improvements.

Non-O ABO blood group genotypes differ in their associations with Plasmodium falciparum rosetting and severe malaria

Blood group O is associated with protection against severe malaria and reduced size and stability of P. falciparum-host red blood cell (RBC) rosettes compared to non-O blood groups. Whether the non-O blood groups encoded by the specific ABO genotypes AO, BO, AA, BB and AB differ in their associations with severe malaria and rosetting is unknown. The A and B antigens are host RBC receptors for rosetting, hence we hypothesized that the higher levels of A and/or B antigen on RBCs from AA, BB and AB genotypes compared to AO/BO genotypes could lead to larger rosettes, increased microvascular obstruction and higher risk of malaria pathology. We used a case-control study of Kenyan children and in vitro adhesion assays to test the hypothesis that "double dose" non-O genotypes (AA, BB, AB) are associated with increased risk of severe malaria and larger rosettes than "single dose" heterozygotes (AO, BO). In the case-control study, compared to OO, the double dose genotypes consistently had higher odds ratios (OR) for severe malaria than single dose genotypes, with AB (OR 1.93) and AO (OR 1.27) showing most marked difference (p = 0.02, Wald test). In vitro experiments with blood group A-preferring P. falciparum parasites showed that significantly larger rosettes were formed with AA and AB host RBCs compared to OO, whereas AO and BO genotypes rosettes were indistinguishable from OO. Overall, the data show that ABO genotype influences P. falciparum rosetting and support the hypothesis that double dose non-O genotypes confer a greater risk of severe malaria than AO/BO heterozygosity.

Importance of Diversity in Precision Medicine: Generalizability of Genetic Associations Across Ancestry Groups Toward Better Identification of Disease Susceptibility Variants

Genome-wide association studies (GWAS) revolutionized our understanding of common genetic variation and its impact on common human disease and traits. Developed and adopted in the mid-2000s, GWAS led to searchable genotype-phenotype catalogs and genome-wide datasets available for further data mining and analysis for the eventual development of translational applications. The GWAS revolution was swift and specific, including almost exclusively populations of European descent, to the neglect of the majority of the world's genetic diversity. In this narrative review, we recount the GWAS landscape of the early years that established a genotype-phenotype catalog that is now universally understood to be inadequate for a complete understanding of complex human genetics. We then describe approaches taken to augment the genotype-phenotype catalog, including the study populations, collaborative consortia, and study design approaches aimed to generalize and then ultimately discover genome-wide associations in non-European descent populations. The collaborations and data resources established in the efforts to diversify genomic findings undoubtedly provide the foundations of the next chapters of genetic association studies with the advent of budget-friendly whole-genome sequencing.

Evolutionary Genetics and Admixture in African Populations

As the ancestral homeland of our species, Africa contains elevated levels of genetic diversity and substantial population structure. Importantly, African genomes are heterogeneous: They contain mixtures of multiple ancestries, each of which have experienced different evolutionary histories. In this review, we view population genetics through the lens of admixture, highlighting how multiple demographic events have shaped African genomes. Each of these historical vignettes paints a recurring picture of population divergence followed by secondary contact. First, we give a brief overview of genetic variation in Africa and examine deep population structure within Africa, including the evidence of ancient introgression from archaic "ghost" populations. Second, we describe the genetic legacies of admixture events that have occurred during the past 10,000 years. This includes gene flow between different click-speaking Khoe-San populations, the stepwise spread of pastoralism from eastern to southern Africa, multiple migrations of Bantu speakers across the continent, as well as admixture from the Middle East and Europe into the Sahel region and North Africa. Furthermore, the genomic signatures of more recent admixture can be found in the Cape Peninsula and throughout the African diaspora. Third, we highlight how natural selection has shaped patterns of genetic variation across the continent, noting that gene flow provides a potent source of adaptive variation and that selective pressures vary across Africa. Finally, we explore the biomedical implications of population structure in Africa on health and disease and call for more ethically conducted studies of genetic variation in Africa.

ATP2B4 regulatory genetic variants are associated with mild malaria

BACKGROUND

Genome-wide association studies have identified ATP2B4 as a severe malaria resistance gene. Recently, 8 potential causal regulatory variants have been shown to be associated with severe malaria.

METHODS

Genotyping of rs10900585, rs11240734, rs1541252, rs1541253, rs1541254, rs1541255, rs10751450, rs10751451 and rs10751452 was performed in 154 unrelated individuals (79 controls and 75 mild malaria patients). rs10751450, rs10751451 and rs10751452 were genotyped by Taqman assays, whereas the fragment of the ATP2B4 gene containing the remaining SNPs was sequenced. Logistic regression analysis was used to assess the association between the SNPs and mild malaria.

RESULTS

The results showed that mild malaria was associated with rs10900585, rs11240734, rs1541252, rs1541253, rs1541254, rs1541255, rs10751450, rs10751451 and rs10751452. The homozygous genotypes for the major alleles were associated with an increased risk of mild malaria. Furthermore, the haplotype containing the major alleles and that containing the minor alleles were the most frequent haplotypes. Individuals with the major haplotypes had a significantly higher risk of mild malaria compared to the carriers of the minor allele haplotype.

CONCLUSIONS

ATP2B4 polymorphisms that have been associated with severe malaria are also associated with mild malaria.

Malaria-driven adaptation of MHC class I in wild bonobo populations

The malaria parasite Plasmodium falciparum causes substantial human mortality, primarily in equatorial Africa. Enriched in affected African populations, the B*53 variant of HLA-B, a cell surface protein that presents peptide antigens to cytotoxic lymphocytes, confers protection against severe malaria. Gorilla, chimpanzee, and bonobo are humans' closest living relatives. These African apes have HLA-B orthologs and are infected by parasites in the same subgenus (Laverania) as P. falciparum, but the consequences of these infections are unclear. Laverania parasites infect bonobos (Pan paniscus) at only one (TL2) of many sites sampled across their range. TL2 spans the Lomami River and has genetically divergent subpopulations of bonobos on each side. Papa-B, the bonobo ortholog of HLA-B, includes variants having a B*53-like (B07) peptide-binding supertype profile. Here we show that B07 Papa-B occur at high frequency in TL2 bonobos and that malaria appears to have independently selected for different B07 alleles in the two subpopulations.

Diagnosis of cerebral malaria: Tools to reduce Plasmodium falciparum associated mortality

Cerebral malaria (CM) is a major cause of mortality in Plasmodium falciparum (Pf) infection and is associated with the sequestration of parasitised erythrocytes in the microvasculature of the host's vital organs. Prompt diagnosis and treatment are key to a positive outcome in CM. However, current diagnostic tools remain inadequate to assess the degree of brain dysfunction associated with CM before the window for effective treatment closes. Several host and parasite factor-based biomarkers have been suggested as rapid diagnostic tools with potential for early CM diagnosis, however, no specific biomarker signature has been validated. Here, we provide an updated review on promising CM biomarker candidates and evaluate their applicability as point-of-care tools in malaria-endemic areas.

Genetic mapping of determinants in drug resistance, virulence, disease susceptibility, and interaction of host-rodent malaria parasites

Genetic mapping has been widely employed to search for genes linked to phenotypes/traits of interest. Because of the ease of maintaining rodent malaria parasites in laboratory mice, many genetic crosses of rodent malaria parasites have been performed to map the parasite genes contributing to malaria parasite development, drug resistance, host immune response, and disease pathogenesis. Drs. Richard Carter, David Walliker, and colleagues at the University of Edinburgh, UK, were the pioneers in developing the systems for genetic mapping of malaria parasite traits, including characterization of genetic markers to follow the inheritance and recombination of parasite chromosomes and performing the first genetic cross using rodent malaria parasites. Additionally, many genetic crosses of inbred mice have been performed to link mouse chromosomal loci to the susceptibility to malaria parasite infections. In this chapter, we review and discuss past and recent advances in genetic marker development, performing genetic crosses, and genetic mapping of both parasite and host genes. Genetic mappings using models of rodent malaria parasites and inbred mice have contributed greatly to our understanding of malaria, including parasite development within their hosts, mechanism of drug resistance, and host-parasite interaction.

The Awesome Power of Human Genetics of Infectious Disease

Since the identification of sickle cell trait as a heritable form of resistance to malaria, candidate gene studies, linkage analysis paired with sequencing, and genome-wide association (GWA) studies have revealed many examples of genetic resistance and susceptibility to infectious diseases. GWA studies enabled the identification of many common variants associated with small shifts in susceptibility to infectious diseases. This is exemplified by multiple loci associated with leprosy, malaria, HIV, tuberculosis, and coronavirus disease 2019 (COVID-19), which illuminate genetic architecture and implicate pathways underlying pathophysiology. Despite these successes, most of the heritability of infectious diseases remains to be explained. As the field advances, current limitations may be overcome by applying methodological innovations such as cellular GWA studies and phenome-wide association (PheWA) studies as well as by improving methodological rigor with more precise case definitions, deeper phenotyping, increased cohort diversity, and functional validation of candidate loci in the laboratory or human challenge studies.

Mouse Models for Unravelling Immunology of Blood Stage Malaria

Malaria comprises a spectrum of disease syndromes and the immune system is a major participant in malarial disease. This is particularly true in relation to the immune responses elicited against blood stages of Plasmodium-parasites that are responsible for the pathogenesis of infection. Mouse models of malaria are commonly used to dissect the immune mechanisms underlying disease. While no single mouse model of Plasmodium infection completely recapitulates all the features of malaria in humans, collectively the existing models are invaluable for defining the events that lead to the immunopathogenesis of malaria. Here we review the different mouse models of Plasmodium infection that are available, and highlight some of the main contributions these models have made with regards to identifying immune mechanisms of parasite control and the immunopathogenesis of malaria.

Risk score prediction model based on single nucleotide polymorphism for predicting malaria: a machine learning approach

BACKGROUND

The malaria risk prediction is currently limited to using advanced statistical methods, such as time series and cluster analysis on epidemiological data. Nevertheless, machine learning models have been explored to study the complexity of malaria through blood smear images and environmental data. However, to the best of our knowledge, no study analyses the contribution of Single Nucleotide Polymorphisms (SNPs) to malaria using a machine learning model. More specifically, this study aims to quantify an individual's susceptibility to the development of malaria by using risk scores obtained from the cumulative effects of SNPs, known as weighted genetic risk scores (wGRS).

RESULTS

We proposed an SNP-based feature extraction algorithm that incorporates the susceptibility information of an individual to malaria to generate the feature set. However, it can become computationally expensive for a machine learning model to learn from many SNPs. Therefore, we reduced the feature set by employing the Logistic Regression and Recursive Feature Elimination (LR-RFE) method to select SNPs that improve the efficacy of our model. Next, we calculated the wGRS of the selected feature set, which is used as the model's target variables. Moreover, to compare the performance of the wGRS-only model, we calculated and evaluated the combination of wGRS with genotype frequency (wGRS + GF). Finally, Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting (XGBoost), and Ridge regression algorithms are utilized to establish the machine learning models for malaria risk prediction.

CONCLUSIONS

Our proposed approach identified SNP rs334 as the most contributing feature with an importance score of 6.224 compared to the baseline, with an importance score of 1.1314. This is an important result as prior studies have proven that rs334 is a major genetic risk factor for malaria. The analysis and comparison of the three machine learning models demonstrated that LightGBM achieves the highest model performance with a Mean Absolute Error (MAE) score of 0.0373. Furthermore, based on wGRS + GF, all models performed significantly better than wGRS alone, in which LightGBM obtained the best performance (0.0033 MAE score).

Risk Association, Linkage Disequilibrium, and Haplotype Analyses of β-Like Globin Gene Polymorphisms with Malaria Risk in the Sabah Population of Malaysian Borneo

Single nucleotide polymorphisms (SNPs) in the β-like globin gene of the human hosts to the risk of malaria are unclear. Therefore, this study investigates these associations in the Sabah population, with a high incidence of malaria cases. In brief, DNA was extracted from 188 post-diagnostic blood samples infected with Plasmodium parasites and 170 healthy controls without a history of malaria. Genotyping of the β-like globin C-158T, G79A, C16G, and C-551T SNPs was performed using a polymerase chain reaction-restriction fragment length polymorphism approach. Risk association, linkage disequilibrium (LD), and haplotype analyses of these SNPs were assessed. This study found that the variant allele in the C-158T and C16G SNPs were protective against malaria infections by 0.5-fold, while the variant allele in the G79A SNP had a 6-fold increased risk of malaria infection. No SNP combination was in perfect LD, but several haplotypes (CGCC, CGCT, and CGGC) were identified to link with different correlation levels of malaria risk in the population. In conclusion, the C-158T, G79A, and C16G SNPs in the β-like globin gene are associated with the risk of malaria. The haplotypes (CGCC, CGCT, and CGGC) identified in this study could serve as biomarkers to estimate malaria risk in the population. This study provides essential data for the design of malaria control and management strategies.

Forward Genetics in Apicomplexa Biology: The Host Side of the Story

Forward genetic approaches have been widely used in parasitology and have proven their power to reveal the complexities of host-parasite interactions in an unbiased fashion. Many aspects of the parasite's biology, including the identification of virulence factors, replication determinants, antibiotic resistance genes, and other factors required for parasitic life, have been discovered using such strategies. Forward genetic approaches have also been employed to understand host resistance mechanisms to parasitic infection. Here, we will introduce and review all forward genetic approaches that have been used to identify host factors involved with Apicomplexa infections, which include classical genetic screens and QTL mapping, GWAS, ENU mutagenesis, overexpression, RNAi and CRISPR-Cas9 library screens. Collectively, these screens have improved our understanding of host resistance mechanisms, immune regulation, vaccine and drug designs for Apicomplexa parasites. We will also discuss how recent advances in molecular genetics give present opportunities to further explore host-parasite relationships.

Identification of ATP2B4 Regulatory Element Containing Functional Genetic Variants Associated with Severe Malaria

Genome-wide association studies for severe malaria (SM) have identified 30 genetic variants mostly located in non-coding regions. Here, we aimed to identify potential causal genetic variants located in these loci and demonstrate their functional activity. We systematically investigated the regulatory effect of the SNPs in linkage disequilibrium (LD) with the malaria-associated genetic variants. Annotating and prioritizing genetic variants led to the identification of a regulatory region containing five ATP2B4 SNPs in LD with rs10900585. We found significant associations between SM and rs10900585 and our candidate SNPs (rs11240734, rs1541252, rs1541253, rs1541254, and rs1541255) in a Senegalese population. Then, we demonstrated that both individual SNPs and the combination of SNPs had regulatory effects. Moreover, CRISPR/Cas9-mediated deletion of this region decreased ATP2B4 transcript and protein levels and increased Ca²⁺ intracellular concentration in the K562 cell line. Our data demonstrate that severe malaria-associated genetic variants alter the expression of ATP2B4 encoding a plasma membrane calcium-transporting ATPase 4 (PMCA4) expressed on red blood cells. Altering the activity of this regulatory element affects the risk of SM, likely through calcium concentration effect on parasitaemia.

Cerebral Malaria: Current Clinical and Immunological Aspects

This review focuses on current clinical and immunological aspects of cerebral malaria induced by Plasmodium falciparum infection. Albeit many issues concerning the inflammatory responses remain unresolved and need further investigations, current knowledge of the underlying molecular mechanisms is highlighted. Furthermore, and in the light of significant limitations in preventative diagnosis and treatment of cerebral malaria, this review mainly discusses our understanding of immune mechanisms in the light of the most recent research findings. Remarkably, the newly proposed CD8+ T cell-driven pathophysiological aspects within the central nervous system are summarized, giving first rational insights into encouraging studies with immune-modulating adjunctive therapies that protect from symptomatic cerebral participation of Plasmodium falciparum infection.

Individualized Medicine in Africa: Bringing the Practice Into the Realms of Population Heterogeneity

The declared aim of "personalized", "stratified" or "precision" approaches is to place individual variation, as ascertained through genomic and various other biomarkers, at the heart of Scientific Medicine using it to predict risk of disease or response to therapy and to tailor interventions and target therapies so as to maximize benefit and minimize risk for individual patients and efficiency for the health care system overall. It is often contrasted to current practices for which the scientific base is rooted in concepts of a "universal biology" and a "typical" or "average patient" and in which variation is ignored. Yet both approaches equally overlook the hierarchical nature of human variation and the critical importance of differences between populations. Impact of genetic heterogeneity has to be seen within that context to be meaningful and subsequently useful. In Africa such complexity is compounded by the high effective size of its populations, their diverse histories and the diversity of the environmental terrains they occupy, rendering analysis of gene environment interactions including the establishment of phenotype genotype correlations even more cumbersome. Henceforth "Individualized" methods and approaches can only magnify the shortcomings of universal approaches if adopted without due regard to these complexities. In the current perspective we review examples of potential hurdles that may confront biomedical scientists and analysts in genomic medicine in clinical and public health genomics in Africa citing specific examples from the current SARS-COV2 pandemic and the challenges of establishing reference biobanks and pharmacogenomics reference values.

Racial and ethnic disparities in genetic testing for hearing loss: a systematic review and synthesis

Racial/ethnic disparities in the diagnostic efficacy of genetic testing for hearing loss have been described. These disparities may relate to differences in variant classification between different racial/ethnic groups, which may, in turn, derive from disparate representation of these groups in the published literature. We sought to quantify racial/ethnic disparities in the published literature on the human genetics of hearing loss. We conducted a search of PubMed for articles describing single-gene, multiple-gene, or whole-exome sequencing for individuals with sensorineural hearing loss. Data on the included subjects, including race/ethnicity and/or region of origin, a number of subjects tested, and method of testing, were extracted. 1355 populations representing 311,092 subjects from 1165 studies were included. Overall, subjects of European and Asian ancestry were equivalently represented, but those of Latino American, African, and indigenous North American ancestry were significantly underrepresented; over 96% of all subjects in the published literature were European or Asian. Within populations, the majority of subjects derived from a small subset of countries. The observed disparity was greater for multiple-gene and whole-exome sequencing than for single-gene sequencing. These findings illustrate the large disparity in the published literature on the genetics of hearing loss, and demonstrate the need for increased representation of Latino American, African, and indigenous North American populations.

Leveraging Mann-Whitney U test on large-scale genetic variation data for analysing malaria genetic markers

Background

The malaria risk analysis of multiple populations is crucial and of great importance whilst compressing limitations. However, the exponential growth in diversity and accumulation of genetic variation data obtained from malaria-infected patients through Genome-Wide Association Studies opens up unprecedented opportunities to explore the significant differences between genetic markers (risk factors), particularly in the resistance or susceptibility of populations to malaria risk. Thus, this study proposes using statistical tests to analyse large-scale genetic variation data, comprising 20,854 samples from 11 populations within three continents: Africa, Oceania, and Asia.

Methods

Even though statistical tests have been utilized to conduct case–control studies since the 1950s to link risk factors to a particular disease, several challenges faced, including the choice of data (ordinal vs. non-ordinal) and test (parametric vs. non-parametric). This study overcomes these challenges by adopting the Mann–Whitney U test to analyse large-scale genetic variation data; to explore the statistical significance of markers between populations; and to further identify the highly differentiated markers.

Results

The findings of this study revealed a significant difference in the genetic markers between populations (p < 0.01) in all the case groups and most control groups. However, for the highly differentiated genetic markers, a significant difference (p < 0.01) was present for most genetic markers with varying p-values between the populations in the case and control groups. Moreover, several genetic markers were observed to have very significant differences (p < 0.001) across all populations, while others exist between certain specific populations. Also, several genetic markers have no significant differences between populations.

Conclusions

These findings further support that the genetic markers contribute differently between populations towards malaria resistance or susceptibility, thus showing differences in the likelihood of malaria infection. In addition, this study demonstrated the robustness of the Mann–Whitney U test in analysing genetic markers in large-scale genetic variation data, thereby indicating an alternative method to explore genetic markers in other complex diseases. The findings hold great promise for genetic markers analysis, and the pipeline emphasized in this study can fully be reproduced to analyse new data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-022-04104-x.

Advances in integrative African genomics

There has been a rapid increase in human genome sequencing in the past two decades, resulting in the identification of millions of previously unknown genetic variants. However, African populations are under-represented in sequencing efforts. Additional sequencing from diverse African populations and the construction of African-specific reference genomes is needed to better characterize the full spectrum of variation in humans. However, sequencing alone is insufficient to address the molecular and cellular mechanisms underlying variable phenotypes and disease risks. Determining functional consequences of genetic variation using multi-omics approaches is a fundamental post-genomic challenge. We discuss approaches to close the knowledge gaps about African genomic diversity and review advances in African integrative genomic studies and their implications for precision medicine.

Decreased parasite burden and altered host response in children with sickle cell anemia and severe anemia with malaria

Plasmodium falciparum malaria causes morbidity and mortality in African children with sickle cell anemia (SCA), but comparisons of host responses to P falciparum between children with SCA (homozygous sickle cell disease/hemoglobin SS [HbSS]) and normal hemoglobin genotype/hemoglobin AA (HbAA) are limited. We assessed parasite biomass and plasma markers of inflammation and endothelial activation in children with HbAA (n = 208) or HbSS (n = 22) who presented with severe anemia and P falciparum parasitemia to Mulago Hospital in Kampala, Uganda. Genotyping was performed at study completion. No child had known SCA at enrollment. Children with HbSS did not differ from children with HbAA in peripheral parasite density, but had significantly lower sequestered parasite biomass. Children with HbSS had greater leukocytosis but significantly lower concentrations of several plasma inflammatory cytokines, including tumor necrosis factor α (TNF-α). In contrast, children with HbSS had threefold greater concentrations of angiopoietin-2 (Angpt-2), a marker of endothelial dysregulation associated with mortality in severe malaria. Lower TNF-α concentrations were associated with increased risk of postdischarge mortality or readmission, whereas higher Angpt-2 concentrations were associated with increased risk of recurrent clinical malaria. Children with SCA have decreased parasite sequestration and inflammation but increased endothelial dysregulation during severe anemia with P falciparum parasitemia, which may ameliorate acute infectious complications but predispose to harmful long-term sequelae.

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.

Causes of Phenotypic Variability and Disabilities after Prenatal Viral Infections

Prenatal viral infection can lead to a spectrum of neurodevelopmental disabilities or fetal demise. These can include microencephaly, global developmental delay, intellectual disability, refractory epilepsy, deafness, retinal defects, and cortical-visual impairment. Each of these clinical conditions can occur on a semi-quantitative to continuous spectrum, from mild to severe disease, and often as a collective of phenotypes. Such serious outcomes result from viruses’ overlapping neuropathology and hosts’ common neuronal and gene regulatory response to infections. The etiology of variability in clinical outcomes is not yet clear, but it may be related to viral, host, vector, and/or environmental risk and protective factors that likely interact in multiple ways. In this perspective of the literature, we work toward understanding the causes of phenotypic variability after prenatal viral infections by highlighting key aspects of the viral lifecycle that can affect human disease, with special attention to the 2015 Zika pandemic. Therefore, this work offers important insights into how viral infections and environmental teratogens affect the prenatal brain, toward our ultimate goal of preventing neurodevelopmental disabilities.

An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility

BACKGROUND

While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility.

RESULTS

Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb)) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs associated with both severe COVID-19 and other human traits demonstrated colocalization of the GWAS signal at the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN). This finding points to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity.

CONCLUSIONS

Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches. The iCPAGdb web portal is accessible at http://cpag.oit.duke.edu and the software code at https://github.com/tbalmat/iCPAGdb .

Genetic factors affect the susceptibility to bacterial infections in diabetes

Diabetes increases the risk of bacterial infections. We investigated whether common genetic variants associate with infection susceptibility in Finnish diabetic individuals. We performed genome-wide association studies and pathway analysis for bacterial infection frequency in Finnish adult diabetic individuals (FinnDiane Study; N = 5092, Diabetes Registry Vaasa; N = 4247) using national register data on antibiotic prescription purchases. Replication analyses were performed in a Swedish diabetic population (ANDIS; N = 9602) and in a Finnish non-diabetic population (FinnGen; N = 159,166). Genome-wide data indicated moderate but significant narrow-sense heritability for infection susceptibility (h² = 16%, P = 0.02). Variants on chromosome 2 were associated with reduced infection susceptibility (rs62192851, P = 2.23 × 10^–7). Homozygotic carriers of the rs62192851 effect allele (N = 44) had a 37% lower median annual antibiotic purchase rate, compared to homozygotic carriers of the reference allele (N = 4231): 0.38 [IQR 0.22–0.90] and 0.60 [0.30–1.20] respectively, P = 0.01). Variants rs6727834 and rs10188087, in linkage disequilibrium with rs62192851, replicated in the FinnGen-cohort (P < 0.05), but no variants replicated in the ANDIS-cohort. Pathway analysis suggested the IRAK1 mediated NF-κB activation through IKK complex recruitment-pathway to be a mediator of the phenotype. Common genetic variants on chromosome 2 may associate with reduced risk of bacterial infections in Finnish individuals with diabetes.

Immunological lessons from genome-wide association studies of infections

Over the past few years, genome-wide association studies (GWAS) have been increasingly applied to identify host genetic factors influencing clinical and laboratory traits related to immunity and infection, and to understand the interplay between the host and the microbial genomes. By screening large cohorts of individuals suffering from various infectious diseases, GWAS explored resistance against infection, natural history of the disease, development of life-threatening clinical signs, and innate and adaptive immune responses. These efforts provided fundamental insight on the role of major genes in the interindividual variability in the response to infection and on the mechanisms of the immune response against human pathogens both at the individual and population levels.

An atlas connecting shared genetic architecture of human diseases and molecular phenotypes provides insight into COVID-19 susceptibility

While genome-wide associations studies (GWAS) have successfully elucidated the genetic architecture of complex human traits and diseases, understanding mechanisms that lead from genetic variation to pathophysiology remains an important challenge. Methods are needed to systematically bridge this crucial gap to facilitate experimental testing of hypotheses and translation to clinical utility. Here, we leveraged cross-phenotype associations to identify traits with shared genetic architecture, using linkage disequilibrium (LD) information to accurately capture shared SNPs by proxy, and calculate significance of enrichment. This shared genetic architecture was examined across differing biological scales through incorporating data from catalogs of clinical, cellular, and molecular GWAS. We have created an interactive web database (interactive Cross-Phenotype Analysis of GWAS database (iCPAGdb); http://cpag.oit.duke.edu) to facilitate exploration and allow rapid analysis of user-uploaded GWAS summary statistics. This database revealed well-known relationships among phenotypes, as well as the generation of novel hypotheses to explain the pathophysiology of common diseases. Application of iCPAGdb to a recent GWAS of severe COVID-19 demonstrated unexpected overlap of GWAS signals between COVID-19 and human diseases, including with idiopathic pulmonary fibrosis driven by the DPP9 locus. Transcriptomics from peripheral blood of COVID-19 patients demonstrated that DPP9 was induced in SARS-CoV-2 compared to healthy controls or those with bacterial infection. Further investigation of cross-phenotype SNPs with severe COVID-19 demonstrated colocalization of the GWAS signal of the ABO locus with plasma protein levels of a reported receptor of SARS-CoV-2, CD209 (DC-SIGN), pointing to a possible mechanism whereby glycosylation of CD209 by ABO may regulate COVID-19 disease severity. Thus, connecting genetically related traits across phenotypic scales links human diseases to molecular and cellular measurements that can reveal mechanisms and lead to novel biomarkers and therapeutic approaches.

Genome-Wide Association Study Identifies Novel Colony Stimulating Factor 1 Locus Conferring Susceptibility to Cryptococcosis in Human Immunodeficiency Virus-Infected South Africans

BACKGROUND

Cryptococcus is the most common cause of meningitis in human immunodeficiency virus (HIV)-infected Africans. Despite universal exposure, only 5%-10% of patients with HIV/acquired immune deficiency syndrome and profound CD4+ T-cell depletion develop disseminated cryptococcosis: host genetic factors may play a role. Prior targeted immunogenetic studies in cryptococcosis have comprised few Africans.

METHODS

We analyzed genome-wide single-nucleotide polymorphism (SNP) genotype data from 524 patients of African descent: 243 cases (advanced HIV with cryptococcal antigenemia and/or cryptococcal meningitis) and 281 controls (advanced HIV, no history of cryptococcosis, negative serum cryptococcal antigen).

RESULTS

Six loci upstream of the colony-stimulating factor 1 (CSF1) gene, encoding macrophage colony-stimulating factor (M-CSF) were associated with susceptibility to cryptococcosis at P < 10-6 and remained significantly associated in a second South African cohort (83 cases; 128 controls). Meta-analysis of the genotyped CSF1 SNP rs1999713 showed an odds ratio for cryptococcosis susceptibility of 0.53 (95% confidence interval, 0.42-0.66; P = 5.96 × 10-8). Ex vivo functional validation and transcriptomic studies confirmed the importance of macrophage activation by M-CSF in host defence against Cryptococcus in HIV-infected patients and healthy, ethnically matched controls.

CONCLUSIONS

This first genome-wide association study of susceptibility to cryptococcosis has identified novel and immunologically relevant susceptibility loci, which may help define novel strategies for prevention or immunotherapy of HIV-associated cryptococcal meningitis.

Integrative genomic analysis reveals mechanisms of immune evasion in P. falciparum malaria

The mechanisms behind the ability of Plasmodium falciparum to evade host immune system are poorly understood and are a major roadblock in achieving malaria elimination. Here, we use integrative genomic profiling and a longitudinal pediatric cohort in Burkina Faso to demonstrate the role of post-transcriptional regulation in host immune response in malaria. We report a strong signature of miRNA expression differentiation associated with P. falciparum infection (127 out of 320 miRNAs, B-H FDR 5%) and parasitemia (72 miRNAs, B-H FDR 5%). Integrative miRNA-mRNA analysis implicates several infection-responsive miRNAs (e.g., miR-16-5p, miR-15a-5p and miR-181c-5p) promoting lymphocyte cell death. miRNA cis-eQTL analysis using whole-genome sequencing data identified 1,376 genetic variants associated with the expression of 34 miRNAs (B-H FDR 5%). We report a protective effect of rs114136945 minor allele on parasitemia mediated through miR-598-3p expression. These results highlight the impact of post-transcriptional regulation, immune cell death processes and host genetic regulatory control in malaria.

High Levels of Genetic Diversity within Nilo-Saharan Populations: Implications for Human Adaptation

Africa contains more human genetic variation than any other continent, but the majority of the population-scale analyses of the African peoples have focused on just two of the four major linguistic groups, the Niger-Congo and Afro-Asiatic, leaving the Nilo-Saharan and Khoisan populations under-represented. In order to assess genetic variation and signatures of selection within a Nilo-Saharan population and between the Nilo-Saharan and Niger-Congo and Afro-Asiatic, we sequenced 50 genomes from the Nilo-Saharan Lugbara population of North-West Uganda and 250 genomes from 6 previously unsequenced Niger-Congo populations. We compared these data to data from a further 16 Eurasian and African populations including the Gumuz, another putative Nilo-Saharan population from Ethiopia. Of the 21 million variants identified in the Nilo-Saharan population, 3.57 million (17%) were not represented in dbSNP and included predicted non-synonymous mutations with possible phenotypic effects. We found greater genetic differentiation between the Nilo-Saharan Lugbara and Gumuz populations than between any two Afro-Asiatic or Niger-Congo populations. F3 tests showed that Gumuz contributed a genetic component to most Niger-Congo B populations whereas Lugabara did not. We scanned the genomes of the Lugbara for evidence of selective sweeps. We found selective sweeps at four loci (SLC24A5, SNX13, TYRP1, and UVRAG) associated with skin pigmentation, three of which already have been reported to be under selection. These selective sweeps point toward adaptations to the intense UV radiation of the Sahel.

Endemic Burkitt lymphoma: a complication of asymptomatic malaria in sub-Saharan Africa based on published literature and primary data from Uganda, Tanzania, and Kenya

BACKGROUND

Endemic Burkitt lymphoma (eBL) is an aggressive B cell non-Hodgkin lymphoma associated with antigenic stimulation from Plasmodium falciparum malaria. Whether eBL risk is related to malaria parasite density is unknown. To address this issue, children with eBL, asymptomatic and clinical malaria, as a surrogate of malaria parasite density, were assessed.

METHODS

Malaria-related laboratory results (parasite density, haemoglobin, platelet count, and white cell count [WBC]) count) were compiled for 4019 eBL cases and 80,532 subjects evaluated for asymptomatic malaria or clinical malaria (severe malaria anaemia, hyperparasitaemia, cerebral malaria, malaria prostration, moderate malaria, and mild malaria) in 21 representative studies published in Africa (mostly East Africa) and 850 eBL cases and 2878 controls with primary data from the Epidemiology of Burkitt Lymphoma in East African Children and Minors (EMBLEM) case-control study in Uganda, Tanzania, and Kenya. The average values of malaria-related laboratory results were computed by condition and trends across single-year age groups were assessed using regression and spline models.

RESULTS

Overall, malaria infection or malaria was diagnosed in 37,089 of children compiled from the literature. Children with eBL and asymptomatic parasitaemia/antigenaemia, but not those with clinical malaria, were closest in their mean age (age 7.1-7.2 vs. 7.4-9.8 years), haemoglobin level (10.0-10.4 vs. 11.7-12.3 g/dL), malaria parasite density (2800 vs. 1827-7780 parasites/µL), platelet count (347,000-353,000 vs. 244,000-306,000 platelets/µL), and WBC count (8180-8890 vs. 7100-7410 cells/µL). Parasite density in these two groups peaked between four to five years, then decreased steadily thereafter; conversely, haemoglobin showed a corresponding increase with age. Children with clinical malaria were markedly different: all had an average age below 5 years, had dramatically elevated parasite density (13,905-869,000 parasites/µL) and dramatically decreased platelet count (< 159,000 platelets/µL) and haemoglobin (< 7 g/dL).

CONCLUSIONS

eBL and asymptomatic parasitaemia/antigenaemia, but not clinical malaria, were the most similar conditions with respect to mean age and malaria-related laboratory results. These results suggest that children with asymptomatic parasitaemia/antigenaemia may be the population at risk of eBL.

Human genetics and malaria resistance

Malaria has been the pre-eminent cause of early mortality in many parts of the world throughout much of the last five thousand years and, as a result, it is the strongest force for selective pressure on the human genome yet described. Around one third of the variability in the risk of severe and complicated malaria is now explained by additive host genetic effects. Many individual variants have been identified that are associated with malaria protection, but the most important all relate to the structure or function of red blood cells. They include the classical polymorphisms that cause sickle cell trait, α-thalassaemia, G6PD deficiency, and the major red cell blood group variants. More recently however, with improving technology and experimental design, others have been identified that include the Dantu blood group variant, polymorphisms in the red cell membrane protein ATP2B4, and several variants related to the immune response. Characterising how these genes confer their effects could eventually inform novel therapeutic approaches to combat malaria. Nevertheless, all together, only a small proportion of the heritable component of malaria resistance can be explained by the variants described so far, underscoring its complex genetic architecture and the need for continued research.

A common polymorphism in the mechanosensitive ion channel PIEZO1 is associated with protection from severe malaria in humans

Malaria caused by the apicomplexan parasite Plasmodium falciparum has served as a strong evolutionary force throughout human history, selecting for red blood cell polymorphisms that confer innate protection against severe disease. Recently, gain-of-function mutations in the mechanosensitive ion channel PIEZO1 were shown to ameliorate Plasmodium parasite growth, blood-brain barrier dysfunction, and mortality in a mouse model of malaria. In humans, the gain-of-function allele PIEZO1 E756del is highly prevalent and enriched in Africans, raising the possibility that it is under positive selection due to malaria. Here we used a case-control study design to test for an association between PIEZO1 E756del and malaria severity among children in Gabon. We found that the E756del variant is strongly associated with protection against severe malaria in heterozygotes. In subjects with sickle cell trait, heterozygosity for PIEZO1 E756del did not confer additive protection and homozygosity was associated with an elevated risk of severe disease, suggesting an epistatic relationship between hemoglobin S and PIEZO1 E756del. Using donor blood samples, we show that red cells heterozygous for PIEZO1 E756del are not dehydrated and can support the intracellular growth of P. falciparum similar to wild-type cells. However, surface expression of the P. falciparum virulence protein PfEMP-1 was significantly reduced in infected cells heterozygous for PIEZO1 756del, a phenomenon that has been observed with other protective polymorphisms, such as hemoglobin C. Our findings demonstrate that PIEZO1 is an important innate determinant of malaria susceptibility in humans and suggest that the mechanism of protection may be related to impaired export of P. falciparum virulence proteins.

Genome-wide heritability analysis of severe malaria resistance reveals evidence of polygenic inheritance

BACKGROUND

Estimating single nucleotide polymorphism (SNP)-heritability (h2g) of severe malaria resistance and its distribution across the genome might shed new light in to the underlying biology.

METHOD

We investigated h2g of severe malaria resistance from a genome-wide association study (GWAS) dataset (sample size = 11 657). We estimated the h2g and partitioned in to chromosomes, allele frequencies and annotations using the genetic relationship-matrix restricted maximum likelihood approach. We further examined non-cell type-specific and cell type-specific enrichments from GWAS-summary statistics.

RESULTS

The h2g of severe malaria resistance was estimated at 0.21 (se = 0.05, P = 2.7 × 10-5), 0.20 (se = 0.05, P = 7.5 × 10-5) and 0.17 (se = 0.05, P = 7.2 × 10-4) in Gambian, Kenyan and Malawi populations, respectively. A comparable range of h2g [0.21 (se = 0.02, P < 1 × 10-5)] was estimated from GWAS-summary statistics meta-analysed across the three populations. Partitioning analysis from raw genotype data showed significant enrichment of h2g in genic SNPs while summary statistics analysis suggests evidences of enrichment in multiple categories. Supporting the polygenic inheritance, the h2g of severe malaria resistance is distributed across the chromosomes and allelic frequency spectrum. However, the h2g is disproportionately concentrated on three chromosomes (chr 5, 11 and 20), suggesting cost-effectiveness of targeting these chromosomes in future malaria genomic sequencing studies.

CONCLUSION

We report for the first time that the heritability of malaria resistance is largely ascribed by common SNPs and the causal variants are overrepresented in protein coding regions of the genome. Further studies with larger sample sizes are needed to better understand the underpinning genetics of severe malaria resistance.

Insights into malaria susceptibility using genome-wide data on 17,000 individuals from Africa, Asia and Oceania

The human genetic factors that affect resistance to infectious disease are poorly understood. Here we report a genome-wide association study in 17,000 severe malaria cases and population controls from 11 countries, informed by sequencing of family trios and by direct typing of candidate loci in an additional 15,000 samples. We identify five replicable associations with genome-wide levels of evidence including a newly implicated variant on chromosome 6. Jointly, these variants account for around one-tenth of the heritability of severe malaria, which we estimate as ~23% using genome-wide genotypes. We interrogate available functional data and discover an erythroid-specific transcription start site underlying the known association in ATP2B4, but are unable to identify a likely causal mechanism at the chromosome 6 locus.  Previously reported HLA associations do not replicate in these samples. This large dataset will provide a foundation for further research on thegenetic determinants of malaria resistance in diverse populations.

Hemoglobin E, malaria and natural selection

It is known that there has been positive natural selection for hemoglobin S and C in humans despite negative health effects, due to its role in malaria resistance. However, it is not well understood, if there has been natural selection for hemoglobin E (HbE), which is a common variant in Southeast Asia. Therefore, we reviewed previous studies and discussed the potential role of natural selection in the prevalence of HbE. Our review shows that in vitro studies, evolutionary genetics studies and epidemiologic studies largely support an involvement of natural selection in the evolution of HbE and a protective role of HbE against malaria infection. However, the evidence is inconsistent, provided from different regions, and insufficient to perform an aggregated analysis such as a meta-analysis. In addition, few candidate gene, genome-wide association or epistasis studies, which have been made possible with the use of big data in the post-genomic era, have investigated HbE. The biological pathways linking HbE and malaria infection have not yet been fully elucidated. Therefore, further research is necessary before it can be concluded that there was positive natural selection for HbE due to protection against malaria.

Lay summary: Our review shows that evidence largely supports an involvement of natural selection in the evolution of HbE and a protective role of HbE against malaria. However, the evidence is not consistent. Further research is necessary before it is concluded.

Gene expression profiling in blood from cerebral malaria patients and mild malaria patients living in Senegal

Background

Plasmodium falciparum malaria remains a major health problem in Africa. The mechanisms of pathogenesis are not fully understood. Transcriptomic studies may provide new insights into molecular pathways involved in the severe form of the disease.

Methods

Blood transcriptional levels were assessed in patients with cerebral malaria, non-cerebral malaria, or mild malaria by using microarray technology to look for gene expression profiles associated with clinical status. Multi-way ANOVA was used to extract differentially expressed genes. Network and pathways analyses were used to detect enrichment for biological pathways.

Results

We identified a set of 443 genes that were differentially expressed in the three patient groups after applying a false discovery rate of 10%. Since the cerebral patients displayed a particular transcriptional pattern, we focused our analysis on the differences between cerebral malaria patients and mild malaria patients. We further found 842 differentially expressed genes after applying a false discovery rate of 10%. Unsupervised hierarchical clustering of cerebral malaria-informative genes led to clustering of the cerebral malaria patients. The support vector machine method allowed us to correctly classify five out of six cerebral malaria patients and six of six mild malaria patients. Furthermore, the products of the differentially expressed genes were mapped onto a human protein-protein network. This led to the identification of the proteins with the highest number of interactions, including GSK3B, RELA, and APP. The enrichment analysis of the gene functional annotation indicates that genes involved in immune signalling pathways play a role in the occurrence of cerebral malaria. These include BCR-, TCR-, TLR-, cytokine-, FcεRI-, and FCGR- signalling pathways and natural killer cell cytotoxicity pathways, which are involved in the activation of immune cells. In addition, our results revealed an enrichment of genes involved in Alzheimer’s disease.

Conclusions

In the present study, we examine a set of genes whose expression differed in cerebral malaria patients and mild malaria patients. Moreover, our results provide new insights into the potential effect of the dysregulation of gene expression in immune pathways. Host genetic variation may partly explain such alteration of gene expression. Further studies are required to investigate this in African populations.

Targeted ultra-deep sequencing of a South African Bantu-speaking cohort to comprehensively map and characterize common and novel variants in 65 pharmacologically-related genes

BACKGROUND

African populations are characterised by high genetic diversity, which provides opportunities for discovering and elucidating novel variants of clinical importance, especially those affecting therapeutic outcome. Significantly more knowledge is however needed before such populations can take full advantage of the advances in precision medicine. Coupled with the need to concisely map and better understand the pharmacological implications of genetic diversity in populations of sub-Sharan African ancestry, the aim of this study was to identify and characterize known and novel variants present within 65 important absorption, distribution, metabolism and excretion genes.

PATIENTS AND METHODS

Targeted ultra-deep next-generation sequencing was used to screen a cohort of 40 South African individuals of Bantu ancestry.

RESULTS

We identified a total of 1662 variants of which 129 are novel. Moreover, out of the 1662 variants 22 represent potential loss-of-function variants. A high level of allele frequency differentiation was observed for variants identified in this study when compared with other populations. Notably, on the basis of prior studies, many appear to be pharmacologically important in the pharmacokinetics of a broad range of drugs, including antiretrovirals, chemotherapeutic drugs, antiepileptics, antidepressants, and anticoagulants. An in-depth analysis was undertaken to interrogate the pharmacogenetic implications of this genetic diversity.

CONCLUSION

Despite the new insights gained from this study, the work illustrates that a more comprehensive understanding of population-specific differences is needed to facilitate the development of pharmacogenetic-based interventions for optimal drug therapy in patients of African ancestry.

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

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.

Genetics of Malaria Inflammatory Responses: A Pathogenesis Perspective

Despite significant progress in combating malaria in recent years the burden of severe disease and death due to Plasmodium infections remains a global public health concern. Only a fraction of infected people develops severe clinical syndromes motivating a longstanding search for genetic determinants of malaria severity. Strong genetic effects have been repeatedly ascribed to mutations and allelic variants of proteins expressed in red blood cells but the role of inflammatory response genes in disease pathogenesis has been difficult to discern. We revisited genetic evidence provided by inflammatory response genes that have been repeatedly associated to malaria, namely TNF, NOS2, IFNAR1, HMOX1, TLRs, CD36, and CD40LG. This highlighted specific genetic variants having opposing roles in the development of distinct malaria clinical outcomes and unveiled diverse levels of genetic heterogeneity that shaped the complex association landscape of inflammatory response genes with malaria. However, scrutinizing genetic effects of individual variants corroborates a pathogenesis model where pro-inflammatory genetic variants acting in early infection stages contribute to resolve infection but at later stages confer increased vulnerability to severe organ dysfunction driven by tissue inflammation. Human genetics studies are an invaluable tool to find genes and molecular pathways involved in the inflammatory response to malaria but their precise roles in disease pathogenesis are still unexploited. Genome editing in malaria experimental models and novel genotyping-by-sequencing techniques are promising approaches to delineate the relevance of inflammatory response gene variants in the natural history of infection thereby will offer new rational angles on adjuvant therapeutics for prevention and clinical management of severe malaria.

Precision identification of high-risk phenotypes and progression pathways in severe malaria without requiring longitudinal data

More than 400,000 deaths from severe malaria (SM) are reported every year, mainly in African children. The diversity of clinical presentations associated with SM indicates important differences in disease pathogenesis that require specific treatment, and this clinical heterogeneity of SM remains poorly understood. Here, we apply tools from machine learning and model-based inference to harness large-scale data and dissect the heterogeneity in patterns of clinical features associated with SM in 2904 Gambian children admitted to hospital with malaria. This quantitative analysis reveals features predicting the severity of individual patient outcomes, and the dynamic pathways of SM progression, notably inferred without requiring longitudinal observations. Bayesian inference of these pathways allows us assign quantitative mortality risks to individual patients. 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.

Dissecting in silico Mutation Prediction of Variants in African Genomes: Challenges and Perspectives

Genomic medicine is set to drastically improve clinical care globally due to high throughput technologies which enable speedy in silico detection and analysis of clinically relevant mutations. However, the variability in the in silico prediction methods and categorization of functionally relevant genetic variants can pose specific challenges in some populations. In silico mutation prediction tools could lead to high rates of false positive/negative results, particularly in African genomes that harbor the highest genetic diversity and that are disproportionately underrepresented in public databases and reference panels. These issues are particularly relevant with the recent increase in initiatives, such as the Human Heredity and Health (H3Africa), that are generating huge amounts of genomic sequence data in the absence of policies to guide genomic researchers to return results of variants in so-called actionable genes to research participants. This report (i) provides an inventory of publicly available Whole Exome/Genome data from Africa which could help improve reference panels and explore the frequency of pathogenic variants in actionable genes and related challenges, (ii) reviews available in silico prediction mutation tools and the criteria for categorization of pathogenicity of novel variants, and (iii) proposes recommendations for analyzing pathogenic variants in African genomes for their use in research and clinical practice. In conclusion, this work proposes criteria to define mutation pathogenicity and actionability in human genetic research and clinical practice in Africa and recommends setting up an African expert panel to oversee the proposed criteria.

Mouse NC/Jic strain provides novel insights into host genetic factors for malaria research

Malaria is caused by Plasmodium parasites and is one of the most life-threatening infectious diseases in humans. Infection can result in severe complications such as cerebral malaria, acute lung injury/acute respiratory distress syndrome, and acute renal injury. These complications are mainly caused by P. falciparum infection and are major causes of death associated with malaria. There are a few species of rodent-infective malaria parasites, and mice infected with such parasites are now widely used for screening candidate drugs and vaccines and for studying host immune responses and pathogenesis associated with disease-related complications. We found that mice of the NC/Jic strain infected with rodent malarial parasites exhibit distinctive disease-related complications such as cerebral malaria and nephrotic syndrome, in addition to a rapid increase in parasitemia. Here, we focus on the analysis of host genetic factors that affect malarial pathogenesis and describe the characteristic features, utility, and future prospects for exploitation of the NC/Jic strain as a novel mouse model for malaria research.

Genetic signatures of gene flow and malaria-driven natural selection in sub-Saharan populations of the "endemic Burkitt Lymphoma belt"

Populations in sub-Saharan Africa have historically been exposed to intense selection from chronic infection with falciparum malaria. Interestingly, populations with the highest malaria intensity can be identified by the increased occurrence of endemic Burkitt Lymphoma (eBL), a pediatric cancer that affects populations with intense malaria exposure, in the so called "eBL belt" in sub-Saharan Africa. However, the effects of intense malaria exposure and sub-Saharan populations' genetic histories remain poorly explored. To determine if historical migrations and intense malaria exposure have shaped the genetic composition of the eBL belt populations, we genotyped ~4.3 million SNPs in 1,708 individuals from Ghana and Northern Uganda, located on opposite sides of eBL belt and with ≥ 7 months/year of intense malaria exposure and published evidence of high incidence of BL. Among 35 Ghanaian tribes, we showed a predominantly West-Central African ancestry and genomic footprints of gene flow from Gambian and East African populations. In Uganda, the North West population showed a predominantly Nilotic ancestry, and the North Central population was a mixture of Nilotic and Southern Bantu ancestry, while the Southwest Ugandan population showed a predominant Southern Bantu ancestry. Our results support the hypothesis of diverse ancestral origins of the Ugandan, Kenyan and Tanzanian Great Lakes African populations, reflecting a confluence of Nilotic, Cushitic and Bantu migrations in the last 3000 years. Natural selection analyses suggest, for the first time, a strong positive selection signal in the ATP2B4 gene (rs10900588) in Northern Ugandan populations. These findings provide important baseline genomic data to facilitate disease association studies, including of eBL, in eBL belt populations.

NCR3 polymorphism, haematological parameters, and severe malaria in Senegalese patients

Background

Host factors, including host genetic variation, have been shown to influence the outcome of Plasmodium falciparum infection. Genome-wide linkage studies have mapped mild malaria resistance genes on chromosome 6p21, whereas NCR3-412 polymorphism (rs2736191) lying within this region was found to be associated with mild malaria.

Methods

Blood samples were taken from 188 Plasmodium falciparum malaria patients (76 mild malaria patients, 85 cerebral malaria patients, and 27 severe non-cerebral malaria patients). NCR3-412 (rs2736191) was analysed by sequencing, and haematological parameters were measured. Finally, their association with clinical phenotypes was assessed.

Results

We evidenced an association of thrombocytopenia with both cerebral malaria and severe non-cerebral malaria, and of an association of high leukocyte count with cerebral malaria. Additionally, we found no association of NCR3-412 with either cerebral malaria, severe non-cerebral malaria, or severe malaria after grouping cerebral malaria and severe non-cerebral malaria patients.

Conclusions

Our results suggest that NCR3 genetic variation has no effect, or only a small effect on the occurrence of severe malaria, although it has been strongly associated with mild malaria. We discuss the biological meaning of these results. Besides, we confirmed the association of thrombocytopenia and high leukocyte count with severe malaria phenotypes.

Tipping the Scale Toward Gastric Disease: A Host-Pathogen Genomic Mismatch?

PURPOSE OF REVIEW

Chronic infection with Helicobacter pylori infection is necessary but not sufficient to initiate development of intestinal-type gastric adenocarcinoma. It is not clear what additional factors tip the scale from commensal bacteria towards a pathogen that facilitates development of gastric cancer. Genetic variants in both the pathogen and host have been implicated, but neither alone explains a substantial portion of disease risk.

RECENT FINDINGS

In this review, we consider studies that address the important role of human and bacterial genetics, ancestry and their interactions in determining gastric disease risk. We observe gaps in the current literature that should guide future work to confirm the hypothesis of the interacting roles of host and bacterial genetics that will be necessary to translate these findings into clinically relevant information.

SUMMARY

We summarize genetic risk factors for gastric disease in both H. pylori and human hosts. However, genetic variation of one or the other organism in isolation insufficiently explains gastric disease risk. The most promising models of gastric disease risk simultaneously consider the genetic variation of both the H. pylori and human host, under a co-evolution model.