Transcriptome profiles of Trypanosoma brucei rhodesiense in Malawi reveal focus specific gene expression profiles associated with pathology.

BACKGROUND: Sleeping sickness caused by Trypanosoma brucei rhodesiense is a fatal disease and endemic in Southern and Eastern Africa. There is an urgent need to develop novel diagnostic and control tools to achieve elimination of rhodesiense sleeping sickness which might be achieved through a better understanding of trypanosome gene expression and genetics using endemic isolates. Here, we describe transcriptome profiles and population structure of endemic T. b. rhodesiense isolates in human blood in Malawi. METHODOLOGY: Blood samples of r-HAT cases from Nkhotakota and Rumphi foci were collected in PaxGene tubes for RNA extraction before initiation of r-HAT treatment. 100 million reads were obtained per sample, reads were initially mapped to the human genome reference GRCh38 using HiSat2 and then the unmapped reads were mapped against Trypanosoma brucei reference transcriptome (TriTrypDB54_TbruceiTREU927) using HiSat2. Differential gene expression analysis was done using the DeSeq2 package in R. SNP calling from reads that were mapped to the T. brucei genome was done using GATK in order to identify T.b. rhodesiense population structure. RESULTS: 24 samples were collected from r-HAT cases of which 8 were from Rumphi and 16 from Nkhotakota foci. The isolates from Nkhotakota were enriched with transcripts for cell cycle arrest and stumpy form markers, whereas isolates in Rumphi focus were enriched with transcripts for folate biosynthesis and antigenic variation pathways. These parasite focus-specific transcriptome profiles are consistent with the more virulent disease observed in Rumphi and a less symptomatic disease in Nkhotakota associated with the non-dividing stumpy form. Interestingly, the Malawi T.b. rhodesiense isolates expressed genes enriched for reduced cell proliferation compared to the Uganda T.b. rhodesiense isolates. PCA analysis using SNPs called from the RNAseq data showed that T. b. rhodesiense parasites from Nkhotakota are genetically distinct from those collected in Rumphi. CONCLUSION: Our results suggest that the differences in disease presentation in the two foci is mainly driven by genetic differences in the parasites in the two major endemic foci of Rumphi and Nkhotakota rather than differences in the environment or host response.

Phenome-wide analysis reveals epistatic associations between APOL1 variants and chronic kidney disease and multiple other disorders.

BACKGROUND: APOL1 variants G1 and G2 are common in populations with recent African ancestry. They are associated with protection from African sleeping sickness, however homozygosity or compound heterozygosity for these variants is associated with chronic kidney disease (CKD) and related conditions. What is not clear is the extent of associations with non-kidney-related disorders, and whether there are clusters of diseases associated with individual APOL1 genotypes. METHODS: Using a cohort of 7462 UK Biobank participants with recent African ancestry, we conducted a phenome-wide association study investigating associations between individual APOL1 genotypes and conditions identified by the International Classification of Disease phenotypes. FINDINGS: We identified 27 potential associations between individual APOL1 genotypes and a diverse range of conditions. G1/G2 compound heterozygotes were specifically associated with 26 of these conditions (all deleteriously), with an over-representation of infectious diseases (including hospitalisation and death resulting from COVID-19). The analysis also exposed complexities in the relationship between APOL1 and CKD that are not evident when risk variants are grouped together: G1 homozygosity, G2 homozygosity, and G1/G2 compound heterozygosity were each shown to be associated with distinct CKD phenotypes. The multi-locus nature of the G1/G2 genotype means that its associations would go undetected in a standard genome-wide association study. INTERPRETATION: Our findings have implications for understanding health risks and better-targeted detection, intervention, and therapeutic strategies, particularly in populations where APOL1 G1 and G2 are common such as in sub-Saharan Africa and its diaspora. FUNDING: This study was funded by the Wellcome Trust (209511/Z/17/Z) and H3Africa (H3A/18/004).

Impact of environmental factors on Biomphalaria pfeifferi vector capacity leading to human infection by Schistosoma mansoni in two regions of western Côte d'Ivoire.

ABSTRACT: BACKGROUND: Intestinal schistosomiasis remains a worrying health problem, particularly in western Côte d'Ivoire, despite control efforts. It is therefore necessary to understand all the factors involved in the development of the disease, including biotic and abiotic factors. The aim of this study was to examine the factors that could support the maintenance of the intermediate host and its vectorial capacity in western Côte d'Ivoire. METHODS: Data on river physicochemical, microbiological, and climatic parameters, the presence or absence of snails with Schistosoma mansoni, and human infections were collected between January 2020 and February 2021. Spearman rank correlation tests, Mann-Whitney, analysis of variance (ANOVA), and an appropriate model selection procedure were used to analyze the data. RESULTS: The overall prevalence of infected snails was 56.05%, with infection reaching 100% in some collection sites and localities. Of 26 sites examined, 25 contained thermophilic coliforms and 22 contained Escherichia coli. Biomphalaria pfeifferi was observed in environments with lower land surface temperature (LST) and higher relative air humidity (RAH), and B. pfeifferi infection predominated in more acidic environments. Thermal coliforms and E. coli preferred higher pH levels. Lower maximum LST (LST_Max) and higher RAH and minimum LST (LST_Min) were favorable to E. coli, and lower LST_Max favored coliforms. The presence of B. pfeifferi was positively influenced by water temperature (T °C), LST_Min, RAH, and precipitation (Pp) (P < 0.05) and negatively influenced by pH, total dissolved solids (TDS), electrical conductivity (EC), LST_Max, and mean land surface temperature (LST). The parameters pH, TDS, EC, LST_Min, LST, and Pp had a positive impact on snail infection, while LST_Max had a negative impact on infection. Only pH had a positive effect on coliform and E. coli abundance. Of the 701 people examined for human schistosomiasis, 73.13% were positive for the point-of-care circulating cathodic antigen (POC-CCA) test and 12.01% for the Kato-Katz (KK) test. A positive correlation was established between human infections and the abundance of Biomphalaria (r2 = 0.879, P = 0.04959). CONCLUSIONS: The results obtained reflect the environmental conditions that are conducive to the maintenance of S. mansoni infection in this part of the country. To combat this infection as effectively as possible, it will be necessary not only to redouble efforts but also to prioritize control according to the level of endemicity at the village level.

An assessment of the genomic structural variation landscape in Sub-Saharan African populations.

Structural variants are responsible for a large part of genomic variation between individuals and play a role in both common and rare diseases. Databases cataloguing structural variants notably do not represent the full spectrum of global diversity, particularly missing information from most African populations. To address this representation gap, we analysed 1,091 high-coverage African genomes, 545 of which are public data sets, and 546 which have been analysed for structural variants for the first time. Variants were called using five different tools and datasets merged and jointly called using SURVIVOR. We identified 67,795 structural variants throughout the genome, with 10,421 genes having at least one variant. Using a conservative overlap in merged data, 6,414 of the structural variants (9.5%) are novel compared to the Database of Genomic Variants. This study contributes to knowledge of the landscape of structural variant diversity in Africa and presents a reliable dataset for potential applications in population genetics and health-related research.