Polymorphisms in genes of interleukin 12 and its receptors and their association with protection against severe malarial anaemia in children in western Kenya

Abstract Background: Malarial anaemia is characterized by destruction of malaria infected red blood cells and suppression of erythropoiesis. Interleukin 12 (IL12) significantly boosts erythropoietic responses in murine models of malarial anaemia and decreased IL12 levels are associated with severe malarial anaemia (SMA) in children. Based on the biological relevance of IL12 in malaria anaemia, the relationship between genetic polymorphisms of IL12 and its receptors and SMA was examined. Methods: Fifty-five tagging single nucleotide polymorphisms covering genes encoding two IL12 subunits, IL12A and IL12B, and its receptors, IL12RB1 and IL12RB2, were examined in a cohort of 913 children residing in Asembo Bay region of western Kenya. Results: An increasing copy number of minor variant (C) in IL12A (rs2243140) was significantly associated with a decreased risk of SMA (P = 0.006; risk ratio, 0.52 for carrying one copy of allele C and 0.28 for two copies). Individuals possessing two copies of a rare variant (C) in IL12RB1 (rs429774) also appeared to be strongly protective against SMA (P = 0.00005; risk ratio, 0.18). In addition, children homozygous for another rare allele (T) in IL12A (rs22431348) were associated with reduced risk of severe anaemia (SA) (P = 0.004; risk ratio, 0.69) and of severe anaemia with any parasitaemia (SAP) (P = 0.004; risk ratio, 0.66). In contrast, AG genotype for another variant in IL12RB1 (rs383483) was associated with susceptibility to high-density parasitaemia (HDP) (P = 0.003; risk ratio, 1.21). Conclusions: This study has shown strong associations between polymorphisms in the genes of IL12A and IL12RB1 and protection from SMA in Kenyan children, suggesting that human genetic variants of IL12 related genes may significantly contribute to the development of anaemia in malaria patients

Detecting Foci of Malaria Transmission with School Surveys: A Pilot Study in the Gambia.

BACKGROUND: In areas of declining malaria transmission such as in The Gambia, the identification of malaria infected individuals becomes increasingly harder. School surveys may be used to identify foci of malaria transmission in the community. METHODS: The survey was carried out in May-June 2011, before the beginning of the malaria transmission season. Thirty two schools in the Upper River Region of The Gambia were selected with probability proportional to size; in each school approximately 100 children were randomly chosen for inclusion in the study. Each child had a finger prick blood sample collected for the determination of antimalarial antibodies by ELISA, malaria infection by microscopy and PCR, and for haemoglobin measurement. In addition, a simple questionnaire on socio-demographic variables and the use of insecticide-treated bed nets was completed. The cut-off for positivity for antimalarial antibodies was obtained using finite mixture models. The clustered nature of the data was taken into account in the analyses. RESULTS: A total of 3,277 children were included in the survey. The mean age was 10 years (SD = 2.7) [range 4-21], with males and females evenly distributed. The prevalence of malaria infection as determined by PCR was 13.6% (426/3124) [95% CI = 12.2-16.3] with marked variation between schools (range 3-25%, p<0.001), while the seroprevalence was 7.8% (234/2994) [95%CI = 6.4-9.8] for MSP119, 11.6% (364/2997) [95%CI = 9.4-14.5] for MSP2, and 20.0% (593/2973) [95% CI = 16.5-23.2) for AMA1. The prevalence of all the three antimalarial antibodies positive was 2.7% (79/2920). CONCLUSIONS: This survey shows that malaria prevalence and seroprevalence before the transmission season were highly heterogeneous

Field evaluation of the diagnostic performance of EasyScan GO: a digital malaria microscopy device based on machine-learning

Background Microscopic examination of Giemsa-stained blood films remains the reference standard for malaria parasite detection and quantification, but is undermined by difficulties in ensuring high-quality manual reading and inter-reader reliability. Automated parasite detection and quantification may address this issue. Methods A multi-centre, observational study was conducted during 2018 and 2019 at 11 sites to assess the performance of the EasyScan Go, a microscopy device employing machine-learning-based image analysis. Sensitivity, specificity, accuracy of species detection and parasite density estimation were assessed with expert microscopy as the reference. Intra- and inter-device reliability of the device was also evaluated by comparing results from repeat reads on the same and two different devices. This study has been reported in accordance with the Standards for Reporting Diagnostic accuracy studies (STARD) checklist. Results In total, 2250 Giemsa-stained blood films were prepared and read independently by expert microscopists and the EasyScan Go device. The diagnostic sensitivity of EasyScan Go was 91.1% (95% CI 88.9–92.7), and specificity 75.6% (95% CI 73.1–78.0). With good quality slides sensitivity was similar (89.1%, 95%CI 86.2–91.5), but specificity increased to 85.1% (95%CI 82.6–87.4). Sensitivity increased with parasitaemia rising from 57% at  200–200,000 parasite/µL. Species were identified accurately in 93% of Plasmodium falciparum samples (kappa = 0.76, 95% CI 0.69–0.83), and in 92% of Plasmodium vivax samples (kappa = 0.73, 95% CI 0.66–0.80). Parasite density estimates by the EasyScan Go were within ± 25% of the microscopic reference counts in 23% of slides. Conclusions The performance of the EasyScan Go in parasite detection and species identification accuracy fulfil WHO-TDR Research Malaria Microscopy competence level 2 criteria. In terms of parasite quantification and false positive rate, it meets the level 4 WHO-TDR Research Malaria Microscopy criteria. All performance parameters were significantly affected by slide quality. Further software improvement is required to improve sensitivity at low parasitaemia and parasite density estimations. Trial registration ClinicalTrials.gov number NCT03512678