Global risk of selection and spread of Plasmodium falciparum histidine-rich protein 2 and 3 gene deletions

Evolution of pfhrp2 and pfhrp3 deletions in Equatorial Guinea between the pre- and post-RDT introduction

BACKGROUND

Pfhrp2 and pfhrp3 deletions are threatening Plasmodium falciparum malaria diagnosis by rapid diagnostic tests (RDT) due to false negatives. This study assesses the changes in the frequencies of pfhrp2 and pfhrp3 deletions (pfhrp2Del and pfhrp3Del, respectively) and the genes in their flaking regions, before and after RDT introduction in Equatorial Guinea.

METHODS

A total of 566 P. falciparum samples were genotyped to assess the presence of pfhrp2 and pfhrp3 deletions and their flanking genes. The specimens were collected 18 years apart from two provinces of Equatorial Guinea, North Bioko (Insular Region) and Litoral Province (Continental Region). Orthologs of pfhrp2 and pfhrp3 genes from other closely related species were used to compare sequencing data to assess pfhrp2 and pfhrp3 evolution. Additionally, population structure was studied using seven neutral microsatellites.

RESULTS

This study found that pfhrp2Del and pfhrp3Del were present before the introduction of RDT; however, they increased in frequency after their use, reaching more than 15%. Haplotype networks suggested that pfhrp2Del and pfhrp3Del emerged multiple times. Exon 2 of pfhrp2 and pfhrp3 genes had high variability, but there were no significant changes in amino acid sequences.

CONCLUSIONS

Baseline sampling before deploying interventions provides a valuable context to interpret changes in genetic markers linked to their efficacy, such as the dynamic of deletions affecting RDT efficacy.

Screening of malaria infections in human blood samples with varying parasite densities and anaemic conditions using AI-Powered mid-infrared spectroscopy

BACKGROUND

Effective testing for malaria, including the detection of infections at very low densities, is vital for the successful elimination of the disease. Unfortunately, existing methods are either inexpensive but poorly sensitive or sensitive but costly. Recent studies have shown that mid-infrared spectroscopy coupled with machine learning (MIRs-ML) has potential for rapidly detecting malaria infections but requires further evaluation on diverse samples representative of natural infections in endemic areas. The aim of this study was, therefore, to demonstrate a simple AI-powered, reagent-free, and user-friendly approach that uses mid-infrared spectra from dried blood spots to accurately detect malaria infections across varying parasite densities and anaemic conditions.

METHODS

Plasmodium falciparum strains NF54 and FCR3 were cultured and mixed with blood from 70 malaria-free individuals to create various malaria parasitaemia and anaemic conditions. Blood dilutions produced three haematocrit ratios (50%, 25%, 12.5%) and five parasitaemia levels (6%, 0.1%, 0.002%, 0.00003%, 0%). Dried blood spots were prepared on Whatman™ filter papers and scanned using attenuated total reflection-Fourier Transform Infrared (ATR-FTIR) for machine-learning analysis. Three classifiers were trained on an 80%/20% split of 4655 spectra: (I) high contrast (6% parasitaemia vs. negative), (II) low contrast (0.00003% vs. negative) and (III) all concentrations (all positive levels vs. negative). The classifiers were validated with unseen datasets to detect malaria at various parasitaemia levels and anaemic conditions. Additionally, these classifiers were tested on samples from a population survey in malaria-endemic villages of southeastern Tanzania.

RESULTS

The AI classifiers attained over 90% accuracy in detecting malaria infections as low as one parasite per microlitre of blood, a sensitivity unattainable by conventional RDTs and microscopy. These laboratory-developed classifiers seamlessly transitioned to field applicability, achieving over 80% accuracy in predicting natural P. falciparum infections in blood samples collected during the field survey. Crucially, the performance remained unaffected by various levels of anaemia, a common complication in malaria patients.

CONCLUSION

These findings suggest that the AI-driven mid-infrared spectroscopy approach holds promise as a simplified, sensitive and cost-effective method for malaria screening, consistently performing well despite variations in parasite densities and anaemic conditions. The technique simply involves scanning dried blood spots with a desktop mid-infrared scanner and analysing the spectra using pre-trained AI classifiers, making it readily adaptable to field conditions in low-resource settings. In this study, the approach was successfully adapted to field use, effectively predicting natural malaria infections in blood samples from a population-level survey in Tanzania. With additional field trials and validation, this technique could significantly enhance malaria surveillance and contribute to accelerating malaria elimination efforts.

Expansion of artemisinin partial resistance mutations and lack of histidine rich protein-2 and -3 deletions in Plasmodium falciparum infections from Rukara, Rwanda

BACKGROUND

Emerging artemisinin partial resistance and diagnostic resistance are a threat to malaria control in Africa. Plasmodium falciparum kelch13 (k13) propeller-domain mutations that confer artemisinin partial resistance have emerged in Africa. k13-561H was initially described at a frequency of 7.4% from Masaka in 2014-2015, but not present in nearby Rukara. By 2018, 19.6% of isolates in Masaka and 22% of isolates in Rukara contained the mutation. Longitudinal monitoring is essential to inform control efforts. In Rukara, an assessment was conducted to evaluate recent k13-561H prevalence changes, as well as other key mutations. Prevalence of hrp2/3 deletions was also assessed.

METHODS

Samples collected in Rukara in 2021 were genotyped for key artemisinin and partner drug resistance mutations using molecular inversion probe assays and for hrp2/3 deletions using qPCR.

RESULTS

Clinically validated k13 artemisinin partial resistance mutations continue to increase in prevalence with the overall level of mutant infections reaching 32% in Rwanda. The increase appears to be due to the rapid emergence of k13-675V (6.4%, 6/94 infections), previously not observed, rather than continued expansion of 561H (23.5% 20/85). Mutations to partner drugs and other anti-malarials were variable, with high levels of multidrug resistance 1 (mdr1) N86 (95.5%) associated with lumefantrine decreased susceptibility and dihydrofolate reductase (dhfr) 164L (24.7%) associated with a high level of antifolate resistance, but low levels of amodiaquine resistance polymorphisms with chloroquine resistance transporter (crt) 76T: at 6.1% prevalence. No hrp2 or hrp3 gene deletions associated with diagnostic resistance were found.

CONCLUSIONS

Increasing prevalence of artemisinin partial resistance due to k13-561H and the rapid expansion of k13-675V is concerning for the longevity of artemisinin effectiveness in the region. False negative RDT results do not appear to be an issue with no hrp2 or hpr3 deletions detected. Continued molecular surveillance in this region and surrounding areas is needed to follow artemisinin partial resistance and provide early detection of partner drug resistance, which would likely compromise control and increase malaria morbidity and mortality in East Africa.

Expansion of Artemisinin Partial Resistance Mutations and Lack of Histidine Rich Protein-2 and -3 Deletions in Plasmodium falciparum infections from Rukara, Rwanda

Background

Emerging artemisinin resistance and diagnostic resistance are a threat to malaria control in Africa. Plasmodium falciparum kelch13 (K13) propeller-domain mutations that confer artemisinin partial resistance have emerged in Africa. K13-561H was initially described at a frequency of 7.4% from Masaka in 2014-2015 but not present in nearby Rukara. By 2018, 19.6% of isolates in Masaka and 22% of isolates in Rukara contained the mutation. Longitudinal monitoring is essential to inform control efforts. In Rukara, we sought to assess recent K13-561H prevalence changes, as well as for other key mutations. Prevalence of hrp2/3 deletions was also assessed.

Methods

We genotyped samples collected in Rukara in 2021 for key artemisinin and partner drug resistance mutations using molecular inversion probe assays and for hrp2/3 deletions using qPCR.

Results

Clinically validated K13 artemisinin partial resistance mutations continue to increase in prevalence with the overall level of artemisinin resistance mutant infections reaching 32% in Rwanda. The increase appears to be due to the rapid emergence of K13-675V (6.4%, 6/94 infections), previously not observed, rather than continued expansion of 561H (23.5% 20/85). Mutations to partner drugs and other antimalarials were variable, with high levels of multidrug resistance 1 (MDR1) N86 (95.5%) associated with lumefantrine resistance and dihydrofolate reductase (DHFR) 164L (24.7%) associated with antifolate resistance, but low levels of amodiaquine resistance polymorphisms with chloroquine resistance transporter (CRT ) 76T: at 6.1% prevalence. No hrp2 or hrp3 gene deletions associated with diagnostic resistance were found.

Conclusions

Increasing prevalence of artemisinin partial resistance due to K13-561H and the rapid expansion of K13-675V is concerning for the longevity of artemisinin effectiveness in the region. False negative mRDT results do not appear to be an issue with no hrp2 or hpr3 deletions detected. Continued molecular surveillance in this region and surrounding areas is needed to follow artemisinin resistance and provide early detection of partner drug resistance, which would likely compromise control and increase malaria morbidity and mortality in East Africa.