Plasmodium infection, altitudinal influence on it, their effect on haematological parameters as well as identify the risk factors of infection.The Mount Cameroon area has experienced a 57.2% decline in confirmed malaria cases between 2006 and 2013 with the implementation of different control measures but, the disease is still of public health concern. The objective of the study was to assess the burden of asymptomatic and sub-microscopic Plasmodium infection by 18S mRNA using nested PCR and full blood count analysis was done using an auto haematology analyser.A cross-sectional community-based survey involving 1319 children of both sexes aged 6 months to 14 years was conducted between July 2017 and May 2018. Malaria parasitaemia was confirmed by Giemsa-stained microscopy, sub-microscopic Plasmodium infection and anaemia were prevalent in 36.4%, 34.0%, 43.8% and 62.3% of the children, respectively. The risk of having sub-microscopic Plasmodium infection was highest in children 5‒9  and 10‒14 years of age , non-insecticide treated net users  and those anaemic . Children with sub-microscopic infection had a significantly lower mean haemoglobin , red blood cell counts , haematocrit , mean corpuscular haemoglobin concentration  and platelet counts  than their negative counterparts. Children < 5 years old (73.8%), having asymptomatic (69.8%) and sub-microscopic Plasmodium infection (78.3%) as well as resident in the middle belt (72.7%) had a higher prevalence of anaemia than their peers.Malaria parasite, asymptomatic malaria parasitaemia and sub-microscopic Plasmodium infection in addition to its corollary on haematological variables among children in the different attitudinal sites of the Mount Cameroon Region accentuate the need for strategic context specific planning of malaria control and preventative measures.The meaningful individual-level heterogeneity in the burden of asymptomatic and sub-microscopic The online version contains supplementary material available at 10.1186/s12936-021-03916-7. Plasmodium falciparum infections manifest through various outcomes ranging from asymptomatic infection to the complicated disease, which may depend on the parasite density [Globally, malaria is still a public health concern, although the death cases have steadily reduced from 736,000 in 2000 to 409,000 deaths in 2019. Cameroon accounts for 3% of this number [ density , 6 as weAsymptomatic malaria is defined by the WHO as the presence of asexual parasites in blood, without symptoms of illness . Other sPlasmodium species by the anopheline vector [Several studies in the central and East part of Africa have reported great numbers of asymptomatic malaria in endemic communities , 10. In e vector . Also, Ge vector  reportedSub-microscopic infections are present across different settings and populations , 14. OkeThe existence of a significant sub-microscopic infection prevalence in an otherwise asymptomatic, microscopically negative population in Ethiopia  highlighPlasmodium infection and their effects on haematological variables among children living in the different altitudinal sites along the Mount Cameroon area. Hence, determining the malaria parasite prevalence, its association with haematological variables in this endemic setting, which may contribute to clinical outcome and death will be fundamental for a strategic planning and control of morbidities associated with the infection.The Mount Cameroon Region represents a meso-hyperendemic setting and malaria epidemiology is highly heterogeneous as seen in many other parts of the country , 20. ThiThe study was carried out in Batoke (Limbe), Dibanda (Buea) and Tole (Buea), which are three semi-rural communities along different altitudinal ranges in the Mount Cameroon area, as shown in Fig. . [The work was conducted among pre- and school aged children of both sexes between 6 months and 14 years old, who granted assent and whose parents/caregivers consented to participate in the study. The inclusion and exclusion criteria of this study were revised according to Teh et al. .This cross-sectional community-based study was conducted in the rainy season between the months of July and October 2017 and between April and May 2018 in Tole, Batoke and Dibanda. Participants were invited for data collection in each community by their local chiefs and coordination was organised by the head/leader of a block within a neighbourhood (“quarter head”) of the various communities. Potential participants were reminded of the collection dates per block by the head/leader of the block. At the start of the study in each site, the parents, guardians and children were educated on the study protocol and the benefits of participation highlighted at their various neighbourhoods using an information sheet. Upon obtaining informed consent/assent from the parents/care givers, the study team proceeded with the collection of samples at specific identified collect sites.2pq/d2 [The sample size for each study altitude was calculated using the 66.2% prevalence of malaria in children in the study area . Sample 2pq/d2  where n A multistage cluster sampling method was used to obtain the required sample. In the first stage, all the communities in the Mount Cameroon area were stratified into 3 zones namely lowland, Middlebelt and highland. One community was randomly selected from each zone namely, Tole (highland), Dibanda (middle belt) and Batoke (lowland). In the second stage, 21 clusters (quarters) were randomly selected from 31 clusters within the three communities. Within the clusters, all the households with children ≤ 14 years of age were selected. In a household where only one child within that age was present, the child was selected automatically. In a case where more than one child was present in a household, only one was randomly selected. A probability proportionate to size sampling method was used to select 400 random malaria negative samples from all the negative samples in the study population for the sub-microscopic studies.Sociodemographic data which included information on gender, age, literacy level of parents/caregivers and malaria preventive methods, as well as fever history of participants were collected using a structured questionnaire. Axillary temperature was measured using an electronic thermometer with a febrile condition considered as temperature ≥ 37.5 °C .Three to four (3–4) millilitres (mL) of venous blood sample was collected from each child using sterile disposable syringes. Part of the blood sample was used to prepare thick and thin films on the same slide for the determination of the presence of malaria parasite by Giemsa-stain microscopy using standard methods . ParasitPlasmodium infection. Genomic deoxyribonucleic acid (DNA) was isolated from the DBS using chelex [Plasmodium genus-specific primers (rPLU5-5ʹCCTGTTGTTGCCTTAAACTTC3ʹ and rPLUS6-5ʹTTAAAATTGTTGCAGTTAAAACG3ʹ) which amplified a 1100-base pair (bp) PCR product from the rRNA small subunit gene (18S rRNA) while the nested primers specific for P. falciparum (rFAL1-5ʹTTAAACTGGTTTGGGAAAACCAAATATATT3ʹ) and rFal2-5ʹACACAATGAACTCAATCATGACTACCCGTC3ʹ) were used, which amplified a 205-bp indicating a P. falciparum infection [Also, 50 μL of the EDTA blood sample was aliquoted onto a Whatman 3 mm filter paper and dried overnight at room temperature. The dried blood spots (DBS) were used to determine sub-microscopic g chelex . Primarynfection .Furthermore, an auto-haematology analyser  was used to assess haematological parameters following the manufacturer’s instructions and the condition of anaemia was defined as haemoglobin level (Hb) < 11 g/dL of whole blood .Sub-microscopic infection was defined as low-density blood-stage malaria parasite infection that was not detected by conventional microscopy but positive using PCR.Plasmodium by microscopy and with an axillary temperature of < 37.5 °C and no record of fever within the past 2 weeks.Asymptomatic malaria parasitaemia was defined as the presence of Parasitaemia was categorized as low , moderate , high , and hyperparasitaemia  .Anaemia was defined as Hb < 11.0 g/dL and further categorized as severe (Hb < 7.0 g/dL), moderate (Hb between 7.0 and 10.0 g/dL), and mild (Hb between 10.1 and < 11 g/dL) .2). Group means were compared using Kruskal Wallis and Mann–Whitney U Test. Parasite densities were log transformed before analysis. Associations between predictor variables and primary outcomes were assessed using both bivariate and multivariate logistic regression analysis. Odd ratios (ORs) and 95% confidence intervals (CIs) were computed. Any covariate with a P value < 0.2 in the bivariate analysis was subsequently included in the final multivariable logistic model. Significant levels were measured at 95%CI with the level of significance set at P < 0.05. Post entry and clean-up of data in Microsoft Excel 2016, analysis was performed using the IBM-Statistical Package for Social Sciences (IBM-SPSS) version 20 and Epi-info version 7.Continuous variables were summarized into means and standard deviations (SD) and categorical variables reported as frequencies and percentages, were used to evaluate the descriptive statistics. The differences in proportions were evaluated using Pearson’s Chi-Square  age of 6.0 (3.5) years, residing at lowland , middle belt  and highland  in the Mount Cameroon area were evaluated. As shown in Table The prevalence of sub microscopic malaria was significantly highest P < 0.001) among the 10–14 years age group (60.5%) when compared with the other age groups   in children aged 5‒9 years  old while, in the middle belt it was significantly highest  in children < 5 years  when compared with their respective counterparts. No significant difference with age was observed in highlands even though the prevalence was highest in children 5–9 years old . On the other hand, while children < 5 years in the low, middle belt and high lands had similar prevalence of asymptomatic malaria parasitaemia, those 5–9 years  and 10–14 years  resident in the lowlands, had the highest prevalence and the difference was significant . As shown in Fig. 2 = 5.157, P = 0.023) where, females had higher prevalence  than males . Conversely, significantly higher  prevalence was observed in males  and females  in the lowland when compared with those in the middle belt and highland, respectively.The overall microscopic prevalence of malaria parasite was 36.4% (CI: 33.8–39.0). The prevalence of asymptomatic falciparum malaria among the 1271 children without fever varied with altitude. The overall prevalence in the low, middle belt and high lands was 44.6% (CI: 39.8–49.6), 25.2% (CI: 39.8–49) and 34.1% (CI: 29.6–38.8), respectively, and the difference was statistically significant (χThe geometric mean parasite density (GMPD) was significantly higher P < 0.001) in children residing in the lowland (449 parasites/ µL of blood) those < 5 years old in the lowland  and middle belt  and males  in the middle belt , 12.4% (59/476) and 3.4% (16/476). As shown in Fig. Overall, the prevalence of sub-microscopic malaria parasitaemia with respect to altitude was highest in children in the highland (66.7%) and lowest in the lowland 29.2%). With respect to age related differences and altitude, among children < 5 years, those resident in middle belt had the highest sub-microscopic malaria parasite prevalence (34.1%). On the other hand, the 5–9 and 10–14 years old, resident in highland had significantly higher (P < 0.001) prevalence  than those in the other altitudinal sites. Moreover, males and female’s resident in the highlands had the highest prevalence of sub-microscopic infection (75.4% and 58.7%), compared to the other altitudinal sites at P < 0.001 and P = 0.002, respectively, as shown in Table 9.2%. WitPlasmodium infection than their respective equal  with an increase in age with youngest age group having a prevalence of 73.8%. The occurrence of anaemia was significantly higher in children from the middle belt (72.7%), those with asymptomatic microscopic (68.1%) and sub-microscopic (78.3%) 12/L) and Plt (280.83 ± 112.62) counts, Hct (31.92%) and MCHC (31.33 ± 4.74 g/L) than their negative counterparts as shown in Table The mean haematological parameters were comparable between children with and without sub microscopic infection except for the mean Hb levels, haematocrit (Hct), RBC (red blood cell) and platelet (Plt) counts, mean corpuscular haemoglobin concentration (MCHC) and red cell distribution–coefficient of variation (RDW-CV). Children with sub microscopic infection had a significantly lower mean Hb concentration (9.86 ± 1.7 g/dL), RBC , those between 5 and 9 years (P =  < 0.001) and 10‒14 years (P =  < 0.001), those who did not use ITN (P = 0.04) and anaemic children (P =  < 0.001) were more likely to have sub-microscopic malaria parasite infection. The odds of carrying sub-microscopic infection is presented in Table P. falciparum infection on anaemia and haematological indices as public health problems in children ≤ 14 years across low, middle belt and highland altitudes in the Mount Cameroon area.Considerable progress has been made in the past years in reducing malaria morbidity and mortality in Africa, with Cameroon inclusive, largely due to interventions such as LLIN and use of artemisinin-based combination therapy , 31. DetFindings from the study suggests that children < 5 years and 5–9 years in the middle belt and lowland respectively, are the most affected by the malaria parasite and, therefore, constitute sensitive groups for monitoring changes in malaria burden using microscopy in the Mount Cameroon area. Case management which is one of the current surveillance methods in the country focus more on the < 5 years age group, although findings from this study indicated that 5–9 years old had more detectable infections. Consequently, health education and treatment should not only target vulnerable groups (< 5 years and pregnant women), but all the age groups.P. falciparum infection has previously been reported in other parts of Africa [The prevalence and density of asymptomatic malaria parasitaemia with respect to age and gender were significantly different across the different altitudinal sites. This result is not surprising because several studies have reported that in Cameroon, malaria burden and transmission intensity are heterogeneous with spatial and temporal variations between altitudes and geographical areas, with prevalence rates varying from one area to another . Althougf Africa , 38. Horf Africa  showed tPlasmodium species between transmission season, since they are a major reservoir.The present study is the first large-scale description of sub-microscopic malaria parasite prevalence among children in three communities in the Mount Cameroon area using the nested PCR method. The overall sub-microscopic malaria parasitaemia of 43.8% was observed in microscopic negative slides by PCR in the study population. In line with other studies, Okell et al.  reportedFindings from the study indicated that the proportion of sub-microscopic infection in the communities were significantly associated with age, as older children had an increased chance of being carriers of sub-microscopic infection compared with those younger. This is consistent with reports from other studies from Uganda , Kenya , India  and EthiPlasmodium infections in older children may be an important source of the local transmission of the parasite. In addition, the unusual significantly higher GMPD observed in children < 10 years living in the highlands than those in the middle belt is also of concern especially as the climatic conditions in the highlands are considered unfavourable for the development of the vector and transmission of the parasite.The importance of the sub-microscopic parasite pool rests on the understanding that sub-microscopic infections can transmit malaria , althougThe higher prevalence of sub-microscopic infection in highland dwellers than lowland support findings of other studies , 46, whiIn addition to altitudinal effect that may affect transmission dynamics, findings from the study revealed non-users of ITN were 2-folds more likely to carry sub-microscopic infection. This observation supports the findings of other studies that proper use of ITN significantly reduces malaria morbidity and mortality .It has been reported that sub-microscopic infections go undetected and untreated with little or no clinical manifestation in many malaria endemic communities . HoweverThe high prevalence of anaemia (62.3%) in children less than or equal to 14 years among the population in this area highlights anaemia as a severe public health problem in malaria endemic communities. The association between malaria parasitaemia and anaemia is well established in previous studies , 52–54. Plasmodium infection in the study was associated with lower Hb, Hct, RBC count as well as MCHC as confirmed by the decrease in their mean values in those positive. It is most likely that sub-microscopic Plasmodium infection would have exacerbated the reduction in the red cell indices as asymptomatic parasitaemia and protracted malaria infections have been associated with a marked reduction in Hb concentration and with a clinically significant RBC destruction [Sub-microscopic truction  indicatitruction .Plasmodium infection. The association of platelet count and malaria has previously been described [Plasmodium infection. Thrombocytopenia seems to occur through peripheral destruction [Findings revealed reduction in platelet count in children with sub-microscopic escribed . Howevertruction , excessitruction  as well truction .While the findings reported have implications for the control and better management of malaria related morbidities in the Mount Cameroon area it could have a wider applicability in other regions with similar altitudinal ranges and environmental conditions. The study is however not without limitation, the study design does not allow the assessment of causality between asymptomatic and sub microscopic parasitaemia and other aetiologies associated with anaemia. However, the findings add invaluable evidence to the clinical relevance of sub-microscopic infection and contributions of asymptomatic malaria to the burden of anaemia, which is often overlooked.Plasmodium infection in addition to its corollary on haematological variables among children in the different attitudinal sites of the Mount Cameroon Region accentuate the need for strategic context specific planning of malaria control and preventative measures. While proper case management continues to be a focus of control efforts, novel strategies are also needed to target the asymptomatic and sub-microscopic parasite reservoirs alongside the consequences on anaemia and haematological indices among children in endemic regions. This information is priceless to use the limited resources in a cost-effective way to appropriately implement management.The significant heterogeneity in the burden of asymptomatic and sub-microscopic Additional file 1. Although not significant GMPD decreased with an increase in age in the high lands as well as the higher values observed in males than females in the low (465) and high lands (385). However, the GMPD/ µL of blood in males (465) and females (434) was significantly higher (P < 0.001) in the lowland when compared with the other altitudinal sites.


Plasmodium falciparum infection, individuals can remain asymptomatic, present with mild fever in uncomplicated malaria cases, or show one or more severe malaria symptoms. Several studies have investigated associations between parasite transcription and clinical severity, but no broad conclusions have yet been drawn. Here, we apply a series of bioinformatic approaches based on P. falciparum’s tightly regulated transcriptional pattern during its ~48-hour intraerythrocytic developmental cycle (IDC) to publicly available transcriptomes of parasites obtained from malaria cases of differing clinical severity across multiple studies. Our analysis shows that within each IDC, the circulation time of infected erythrocytes without sequestering to endothelial cells decreases with increasing parasitaemia or disease severity. Accordingly, we find that the size of circulating infected erythrocytes is inversely related to parasite density and disease severity. We propose that enhanced adhesiveness of infected erythrocytes leads to a rapid increase in parasite burden, promoting higher parasitaemia and increased disease severity.Following  P. falciparum and find that longer circulation of infected erythrocytes without sequestering to endothelial cells associates with decreasing parasitaemia and less severe disease.To understand malaria symptoms, several studies investigate association between parasite’s transcriptome and disease severity. Here, Thomson-Luque et al. reanalyze available transcriptomic data of  The major causative agent of malaria, Plasmodium falciparum, causes disease through continuous asexual intraerythrocytic developmental cycles (IDCs), each lasting ~48 h and producing 8–30 new parasites2. Circulation of young parasite forms within each IDC, called ring stages, is a hallmark of P. falciparum malaria3, while more developed stages express parasite antigens at the host cell surface to promote their adhesion to the vascular endothelium and avoid splenic clearance5. P. falciparum infection can produce a range of clinical outcomes: remaining asymptomatic despite infection, presenting with fever and other non-specific symptoms in uncomplicated malaria, or exhibiting one or several signs of severe disease leading to cerebral malaria, severe anaemia, coma, pulmonary oedema, or metabolic acidosis6. This array of malaria presentations associates with parasite burden, and with different stages of a progressively developing protective immunity which increases with parasite exposure and host age8. Protection from severe malaria is rapidly acquired after a few clinical episodes in areas of high transmission9, and years of exposure result in mostly asymptomatic infections in adolescence and adulthood11. Accordingly, in malaria-endemic areas, parasitaemia with high parasite burden is often seen in young children with severe malaria12. In contrast, lower parasitaemia typifies uncomplicated malaria or asymptomatic infections in older individuals14, reflecting cumulative exposure and gradual naturally acquired immunity to malaria. Nevertheless, in age-matched individuals with apparently similar parasite exposures, different clinical outcomes have been linked to parasites causing severe malaria with higher or lower parasitaemias15, or parasites promoting non-severe vs severe malaria17, without allowing for major conclusions regarding the contribution of parasite transcription to disease outcome. Recently, in a cohort study in the seasonal transmission setting of Mali, we compared parasites persisting at low parasitaemias in asymptomatic children at the end of the 6-month dry season with parasites causing uncomplicated malaria in age-matched individuals during the ensuing wet season, and found highly different transcriptional signatures. We determined that gene expression differences were strongly associated with the developmental stage of circulating P. falciparum within the ~48 h IDC18. Indeed, during each IDC, P. falciparum follows a tightly regulated, developmental stage-dependent19 transcriptional pattern from merozoite invasion of erythrocytes, through the ring- and trophozoite-stages, until the multinucleated schizont releases new merozoites at the end of the IDC22, and parasite transcription from patients’ blood can reveal the stage composition of circulating parasites24. Our recent data showed that during the dry season, P. falciparum-infected erythrocytes circulate longer within the ~48 h IDC and low parasitaemia is maintained for several months through increased splenic clearance18, hinting that previously reported transcriptomes from P. falciparum field isolates causing distinct clinical outcomes may also have been influenced by differences in adhesion efficiency and circulation times of parasitized erythrocytes.Worldwide over 200 million malaria cases occur yearly, out of which ~2 million progress to severe disease, leading in 2019 to more than 400,000 deaths, mostly of African children under the age of five20; and based on the simple idea that genes that are differentially upregulated in more vs less-developed parasite stages comprise transcripts peaking at later stages of the IDC, whereas genes that are differentially upregulated in less-developed stages represent transcripts peaking earlier in the IDC. Accordingly, an approach using in vitro grown parasite lines previously assigned ~4400 P. falciparum transcripts to a particular IDC stage, allowing predictions of the stage composition of mixed parasite samples24, which we also applied here. Furthermore, we use previously described algorithms integrating the parasites’ full transcriptome to determine expected stage-compositions17, and the maximum likelihood estimate of average parasite age in hours post erythrocyte invasion (hpi)16 of a given sample. Applying these bioinformatic methods to previously published studies we determine the expression profile of differentially expressed genes (DEGs)20, and predict the developmental stages present in each sample24. Our re-interpretation of the transcriptional analyses and the calculations of parasites’ age in the various studies reveals new transcriptional signatures supporting the hypothesis that shorter circulation time of infected erythrocytes within the ~48 h IDC associates with increased parasite growth rates, virulence, and disease severity.In this work, we revisit ten studies published between 2007 and 2020 that report parasite transcriptional differences between distinct disease severities, parasite burdens, non-negative matrix factorization (NMF) clustering of expression profiles, or transmission intensities to bioinformatically interrogate transcriptional differences dependent on developmental stage. Our approach centered on the tight transcriptional pattern governing the ~48 h IDCP. falciparum transcription associating with parasite burden and/or disease severity, we identified ten published studies between 2007 and 2020 that reported transcriptional differences between malaria parasites isolated from individuals presenting with a spectrum of malaria symptoms and parasitaemias and residing in areas of different transmission intensities , and in malaria cases (high parasitaemias), we observed later peaks  in upregulated genes in the dry season, and earlier peaks  for the upregulated genes in malaria cases   or wet seasons (high parasitaemias) again revealed more developed parasites alongside fewer ring stages from transcripts upregulated in the dry season, while transcripts upregulated in malaria cases associated with higher proportions of early ring stages    method defined by Lemieux et al.16 applied to the transcriptomes of parasites collected in the dry season and malaria cases determined that the expected age in hpi was higher in parasites circulating in the dry vs the wet season  , Yamagishi et al. , and Lee et al.  (p < 0.001 Mann–Whitney)   and for others we calculated from their accessible gene count matrices . Strikingly, we observed that the four studies comparing freshly obtained parasites from low vs high parasitaemias  and mild vs severe disease  showed similar patterns as the observed comparison between dry and wet season parasites. Curves of expression and heatmaps along the ~48 h IDC in the reference HB3 ey) Fig. , likely st) Fig. ; and agast) Fig. .Fig. 3DEP. falciparum reference in vitro   Fig. . Accordi24 revealed that upregulated DEGs in clusters 1 or 3 peaked later than DEGs upregulated in cluster 2  and  and also upregulated DEGs in cluster 1 peaked later than upregulated DEGs in cluster 3    and mild malaria cases . Conversely, more young stages were predicted in the samples originating from high parasitaemias or severe malaria cases in the same studies (p < 0.05 one-way ANOVA)  determined significantly more mature parasites in the low parasitaemias in Milner et al. and in the less severe malaria samples from Tonkin-Hill et al.  Fig. . The MLEal. Fig. , while tP. coatneyi in four rhesus macaques is the only study involving longitudinal parasite sampling, including acute malaria with high parasitaemias and chronic low-level infection following sub-curative treatment25. Applying the MLE method to the whole transcriptome of the different groups of samples, we observed that a higher proportion of younger parasites were present in acute infection/higher parasitaemias than in low parasitaemias immediately or long after the sub-curative treatment . We were also able to measure the size of infected erythrocytes on thick smears collected at the time of blood draw in two of these studies , and we confirmed that the average parasite size was significantly larger in low than in high parasitaemias , and we observed that while the area size of circulating parasites correlated positively with estimated age in hpi and peak expression times of DEGs ; it correlated negatively with the proportion of ring stages predicted by Painter categorizations of DEGs or by the full transcriptome mixture model method, and it also correlated negatively with parasite density , and particularly evident at low parasitaemias where circulating parasites are larger , which allowed us to seek associations between parasitaemia and the predicted proportions of non-ring stages according to the mixture model by Tonkin-Hill et al.ngs Fig.  or the pngs Fig.  and paraity Fig. , and we P. falciparum infections are not fully understood, higher parasitaemia is frequently associated with poorer prognoses31. In this study, we accessed publicly available transcriptional profiles of parasites from reports across the malaria clinical spectrum and parasitaemia range. We showed a clear relation between circulation of older parasites within each ~48 h asexual replication cycle and lower parasitaemia. Our data support a model in which higher parasite burdens result from parasites sequestering from peripheral circulation by competently binding to endothelial cells and thus evading splenic clearance, contributing to more rapid parasitaemia growth and worse clinical presentations. Asymptomatically infected children typically present with low-level parasitaemias, which are often sub-microscopic33, mild, or uncomplicated malaria cases typically associated with higher parasite burdens than the ones observed in asymptomatic infected children30, but lower than what is frequently seen in severe or complicated malaria cases31. This gradient led to the hypothesis that intrinsic replication rates of P. falciparum may contribute to the level of parasitaemia. However, in vitro culture of parasites collected from uncomplicated and severe malaria cases fails to consistently explain parasitaemia differences found in clinical settings35, and our recently published data show similar in vitro replication ability between parasites causing mild malaria and asymptomatic infection18. Furthermore, we recently reported transcriptional differences between parasites causing mild and subclinical malaria associated with increased circulation time of parasites causing subclinical malaria18, which we confirmed here  than the period needed to have parasites reach the same stage from severe malaria cases  (p = 0.05 t test)16. These are two clues in two different publications, of what we now put in evidence across multiple studies, and is possibly a major driver of P. falciparum ability to grow within a host. Early stage adhesion of infected erythrocytes results in effective evasion of splenic clearance and a subsequent rapid increase in parasitaemia and severity of disease. With two studies18 we could relate the parasite transcriptional signatures with size measurements of circulating parasites within the lower and higher parasitaemia groups, which confirmed the presence of more mature parasites in individuals with lower parasitaemias  and high (34) parasitaemia in Malawi. DEGs were reported.Milner et al. 2012: 58 P. falciparum parasitaemias (defined by % of Pf RNAseq tags within a sample ranging from 0.001 to 72.95%) and clinical presentations in Indonesia. DEGs were not originally reported. We determined DEGs between 16 samples with Pf tags >20% (high parasitaemia) and 20 samples with Pf tags between 2 and 5% (low parasitaemia).Yamagishi et al. 2014: 116 samples from varying P. falciparum malaria cases and 25 severe P. falciparum malaria samples, including cerebral malaria (5), hyperlactatemia (8), and both (12) from The Gambia. DEGs were reported.Lee et al. 2018: 21 samples from uncomplicated P. falciparum malaria cases, and 23 samples from severe malaria patients in Papuan adults. DEGs were reported.Tonkin-Hill et al. 2018: 21 samples from non-severe P. falciparum uncomplicated malaria cases from areas of different transmission intensities in Kenya and Sudan. DEGs were reported.Rono et al. 2017: 96 samples of P. falciparum positive individuals across diverse clinical presentations and age clustered in three groups. DEGs were not originally reported. We determined DEGs including all samples and using the same clustering.Daily et al. 2007: 43 samples from P. falciparum mild malaria cases and 9 samples from severe P. falciparum malaria in The Gambia cultured until the schizont stage. DEGs between each group and reference 3D7 were reported.Lemieux et al. 2009: 8 samples from P. falciparum field isolates effectively cultured in vitro until trophozoite stage from asymptomatic children, children with uncomplicated malaria, or children with cerebral malaria in Cameron. DEGs were reported.Almelli et al. 2014: 3 pooled samples of six P. coatneyi samples collected during acute infection, following sub-curative treatment and at chronic stage of four laboratory-reared Rhesus macaques. DEGs were not reported.Cordy et al. 2019: An 11th study was included to investigate the relation of parasite sizes on thick blood smear and parasite density, which was not included in any gene expression analyses.Coulibaly et al. in preparation: a case–control study of severe malaria in Bandiagara, Bamako, Sikasso, and satellites villages with 6-month to 10-year-old participants enrolled and followed from October 2014 to December 2018 in Mali. Cases were recruited among children hospitalized or seeking care with cerebral malaria (Blantyre score ≤2) or severe anaemia (hemoglobin level ≤5 g/dl) at the dedicated health facilities. Controls were children suffering from uncomplicated malaria seeking care at the same health facilities and matched by age class, residence, sex and ethnicity to the index case. The study protocol obtained ethical clearance from the Ethics Committee of Faculty of Pharmacy and Faculty of Medicine and Odonto-stomatology, University of Sciences, Techniques and Technologies of Bamako, Mali; letter of approval #2014//97/CE/FMPOS. Individual informed consent was obtained from parents or guardians. Data were anonymized to guarantee confidentiality of volunteers’ identities.P. falciparum 3D7 (PlasmoDB release 47)46 by Hisat247. Reads of Lee et al. were additionally mapped to human (UCSC hg38)48 to only use reads that uniquely mapped to P. falciparum. FeatureCount (-g ID --primary -C -Q 30 -p -t gene)49 were used to create the final gene expression table. Gene annotations were obtained from GENCODE (release 34)50 and PlasmoDB (release 47). Conversion between new and old gene names was done by gene aliases from PlasmoDB (release 47), and genes of Cordy et al. were converted into the annotated P. falciparum orthologs.Most studies provided gene expression data; however, Lee et al. did not. Raw sequencing reads from Lee et al. and Andrade et al. were processed through Cutadapt (-q 30 --pair-filter=any -m 25) and mapped to 51 with TMM normalization52, p < 0.05 and fold change >1.5. The EDAseq package53 was used for principal component analysis, relative log expression (RLE), and mean variance trend. Samples in each study with mean RLE exceeding ±0.1 after limma/voom normalization55 were excluded from analysis. Genes of all studies were filtered by more than 2 counts per million in ten or more samples.DEGs of studies not providing a DEG list  were determined by the quasi-likelihood F-test in the EdgeR packagehttp://mkweb.bcgsc.ca/tableviewer/visualize/)56, and the Venn diagrams obtained through the platform from Bioinformatics and Evolutionary Genomics at Ghent University (http://bioinformatics.psb.ugent.be/webtools/Venn/) available online.Shared reported DEGs between different studies were assessed and highlighted through the online platform “circos table viewer”  for the different studies. The number of DEGs associated with the functional group in each study was calculated together with the fold enrichment. The statistical threshold was set as (–log10 (0.05) = 1.3).Over-represented functional annotations, keywords, and pathways were defined using DAVIDP. falciparum housekeeping gene glycine-tRNA ligase (PF3D7_1420400) . Within each GO group genes were ordered by their peak time of transcription in vitro according to Painter et al.24.Normalized reads of DEGs involved in GO terms (rows) for each subject (columns) were included in heatmaps, where samples from each study subject were ordered by increasing parasite density (parasite/μL) ; by %Pf tags ; or by the expression of the P. falciparum HB3 parasite line in vitro along the 48 h IDC defined by Bozdech et al.20, which reported microarray gene expression for 3719 P. falciparum genes over the 48 timepoints of the IDC. Heatmaps were generated with online application Morpheus (https://software.broadinstitute.org/morpheus/). Expression curves show the median ± IQR of the log2 expression values along the 48 h IDC.For transcripts found up- or downregulated in each study comparison, we plotted the relative expression in P. falciparum 3D7 parasite line in vitro along the IDC defined by Painter et al.24 with a Lomb–Scargle periodogram approach as previously described58, to define the peak time of total abundance for 5428 genes over the 48 timepoints throughout the 48 h IDC.For transcripts found up- or downregulated in each study comparison, we plotted the hours post invasion at which transcription peaked in 24 further used the expression data of P. falciparum 3D7 parasite line in vitro along the IDC to bin transcripts based on their peak times of transcription, stabilization, and decay into groups representing six developmental stage: early ring (0–10 hpi), mid-ring (11–15 hpi), late ring/early trophozoite (16–21 hpi), mid-trophozoite (22–26 hpi), late trophozoite (27–32 hpi), and schizont (33–48 hpi). We used this categorization to show the proportion of DEGs found up- and downregulated in each study comparison.Painter et al.17, which used RNAseq reference data of López-Barragán et al.23, was applied to the different studies. In brief, proportions of parasite life cycle stages were estimated in a constrained linear model by fitting to transcriptomic profiles of known stages. Data with old gene names were converted and any duplicated genes were collapsed by average expression value. Genes with less than 2 counts per million in ten or more samples were excluded.The mixture model described by Tonkin-Hill et al.16 with microarray reference data of Bozdech et al.20, the maximum likelihood method was applied as to the different studies transcriptome. In brief, hpi was estimated by the peak in probability of parasite age given by hourly gene expression data of the HB3 strain. Data with new gene names were converted according to the reference set and any duplicated genes were collapsed by average expression value.Described by Lemieux et al.P. falciparum parasites were measured on Giemsa- or Field-stained thick blood films made at the time of the blood draw for RNA extraction and/or parasite density quantification of samples from Andrade et al., Milner et al., and Coulibaly et al. in preparation. Slides were imaged to obtain 3–20 photomicrographs blindly acquired from each case with a 63× or 100× objective. Fiji software Image J was used to independently quantify the parasite areas by three to four researchers. The average measure of the interclass correlation for Malian and Malawian samples was 0.963 and 0.889, respectively. Conversion from 63× sizes to 100× was obtained using the πr2 formula. Parasite densities were personally communicated.P. falciparum parasites synchronized to schizont stage were added E64 compound (Sigma-Aldrich) to prevent egress of merozoites for 6–8 h, and later merozoites were purified through filtration and cultured with non-infected RBCs and RPMI medium supplemented with Albumax-II for up to 16 h.3D7 p value of ≤0.05. All analyses were performed with GraphPad Prism software version 8.0 or 9.0,or R (http://www.R-project.org).For continuous variables two-tailed Mann–Whitney or Kruskal–Wallis was used to test for differences between two or more groups respectively. Fisher’s exact test was used on absolute DEG counts assigned to different developmental stages according to Painter et al. One-way ANOVA with Sidak multiple comparisons test was used to compare proportion of similar stages between groups of each study according to Tonkin-Hill et al.’s mixture model. Pearson correlation or Spearman’s rank correlations were obtained accordingly. Statistical significance was defined as a two-tailed Further information on research design is available in the Supplementary Information FilePeer Review FileReporting summary


Background: Studies of long-term malaria cohorts have provided essential insights into howPlasmodium falciparum interacts with humans, and influences the development of antimalarial immunity. Immunity to malaria is acquired gradually after multiple infections, some of which present with clinical symptoms. However, there is considerable variation in the number of clinical episodes experienced by children of the same age within the same cohort. Understanding this variation in clinical symptoms and how it relates to the development of naturally acquired immunity is crucial in identifying how and when some children stop experiencing further malaria episodes. Where variability in clinical episodes may result from different rates of acquisition of immunity, or from variable exposure to the parasite.Methods: Using data from a longitudinal cohort of children residing in an area of moderateP. falciparum transmission in Kilifi district, Kenya, we fitted cumulative episode curves as monotonic-increasing splines, to 56 children under surveillance for malaria from the age of 5 to 15.Results: There was large variability in the accumulation of numbers of clinical malaria episodes experienced by the children, despite being of similar age and living in the same general location. One group of children from a particular sub-region of the cohort stopped accumulating clinical malaria episodes earlier than other children in the study. Despite lack of further clinical episodes of malaria, these children had higher asymptomatic parasite densities and higher antibody titres to a panel ofP. falciparum blood-stage antigens.Conclusions: This suggests development of clinical immunity rather than lack of exposure to the parasite, and supports the view that this immunity to malaria disease is maintained by a greater exposure toP. falciparum, and thus higher parasite burdens. Our study illustrates the complexity of anti-malaria immunity and underscores the need for analyses which can sufficiently reflect the heterogeneity within endemic populations. A malaria infection is caused by the protozoan parasitePlasmodium, with the most virulent human parasite,Plasmodium falciparum (Pf), responsible for over 90% of malaria-related morbidity and mortality, mostly in sub-Saharan Africa. Subsequent repeated exposure toPf infections eventually leads to the development of partial immunity. Evidence for such immunity includes the age-associated decrease in frequency and severity of clinical malaria episodes among children living in endemic areas wherePf infections in older children present with lower parasite densities, infrequent malaria symptoms and may produce morePf-specific antibodies.Malaria is a major global health problem responsible for millions of clinical cases each year with the highest burden of mortality in children under 5 years of age the precise mechanism(s) by which partial immunity to malaria develops and is maintained, remains unclear. Development of partial immunity to malaria likely involves a complex interplay between an antigenically diverse parasite and a dynamic host immune response. Investigating this process within human populations is challenging given the many factors that influence the development and maintenance of immunity toPf including age, genetics, the number of previous clinical episodes as well as past and current exposure to the parasite. While some of these factors are relatively easily quantified, accurately estimating total exposure is extremely difficult as not all exposure results in clinical manifestations. Exposure toPf has been demonstrated to be extremely heterogeneous, exhibiting both temporal  and micro-geographic variation.Although repeated clinical episodes of malaria have been shown to lead to substantial and diverse host immune responses. Individuals typically under active surveillance are followed for several years, during which time all clinical cases of malaria are recorded. Given the impracticality of large, continuous entomological surveys, such studies typically estimate parasite exposure based on the incidence of clinical malaria within a specified geographic area. The aggregate number of episodes an individual experiences is dependent on both the extent of their exposure to thePf parasites and their level of immunity. As such, in areas with reasonably high transmission intensity, the number of episodes an individual experiences would be expected to decline over time, not necessarily because transmission intensity in that geographic area is reducing, but rather because of the development of partial immunity.Longitudinal study cohorts, often considered the “goldstandard’ in observational studies of natural infection, can provide very useful insights into the development of antimalarial immunity), where a plateau in accumulated episodes from children in an endemic region may be considered as evidence of the development of immunity. By visualizing the rate of accumulation of clinical episodes for each child individually, we are better able to capture the heterogeneity of clinical episodes within the population. For a subset of individuals who stop accumulating more episodes within this age-span, we compared the levels of antibodies to selectedPf-antigens to help determine if the decline in the rate of accumulating episodes is related to acquisition of immunity or rather reduced exposure to the parasite.After following 56 individuals over ten-years from a longitudinal study cohort, we are able to compare the rate at which each individual acquires episodes over time, an approach only possible with long-term surveillance datasets. In such an approach, the development of immunity against malaria may be illustrated as a cumulative malaria episode curve . Written informed consent in the local languages (Swahili or Giriama) was required from parents/guardians for participation. whereby transmission in Junju village has remained stable with a parasite prevalence of 30% during the dry season. However, there are two high malaria transmissions seasons, May to August and October to December, during which parasite prevalence rises beyond 70%. Children are recruited into the cohort at or shortly after birth and actively monitored on a weekly basis for detection of malaria episodes until 15 years of age. Extensive and detailed records of the number and dates of malaria episodes for each child over the period they are enrolled in the cohort are maintained.The study took place at the KEMRI-Wellcome Trust Research Programme (KWTRP) situated next to the Kilifi County Hospital, Kilifi, Kenya. The hospital serves approximately 500,000 people living in Kilifi County. The children investigated were residents of Junju a community on the southern side of an Indian Ocean creek and inhabited by predominantly Mijikenda people. Over the last 15 years, there has been a gradual, heterogeneous decline in malaria transmission in Kilifi CountyThe Junju cohort was started in 2005 with children of various ages but has since continuously recruited newly born children, who subsequently drop out of the surveillance at the age of 15 years. The size of the cohort at any one point is 300–400 children. For these analyses, 56 children who were born between 2001 and 2003 and had completed 10 years of malaria surveillance within the cohort were selected to determine whether there is heterogeneity in the rate of accumulation of clinical episodes with age.. A year was defined from 1st of April to the 31st of March, capturing the total number of episodes before the wet season, which normally starts in April after a relative dry period of at least four months with minimalPf transmission. For example, 2015 corresponds to the 1st of April 2014 to the 31st of March 2015. Parasite load (determined by microscopy and PCR) and serum antibody levels were measured from blood samples collected at the end of the dry season each year.A clinical malaria episode was defined as a body temperature greater than 37.5°C and 2500 parasites per microlitre of bloodPf episodes are normally diagnosed during weekly active surveillance carried out by a field worker based in the same village as the child. During these visits auxiliary body temperature, and or recent history of fever is taken, and if a child is febrile a blood sample is taken for aPf specific rapid diagnostic test (RDT) and for blood smears. The blood smears are read later to determine thePf parasite densities used in this paper, whilst immediate antimalarial treatments are administered based on the RDT testing.Pf densities and prevalence. Furthermore, q-rtPCR has been applied to all the samples collected since 2007 to complement the microscopy data.Additionally, an annual cross-sectional survey is conducted in March, just before the beginning of the rains that marks the beginning of the main malaria transmission season in Kilifi. During these surveys, 5ml of venous blood  and blood smears for detection and subsequent calculation of the associated cross-sectionalPf-infected red cells counted against 500 leukocytes and 1,000 red blood cells, respectively. To detect lower parasite densities, a highly sensitivePf -specific PCR assay based onThick and thin blood films were stained with Giemsa andA sensitive high qPCR assay was used for detection where 500 µl of whole venous blood was used to extract DNA using an automated DNA extraction and purification method  according to the manufacturer’s instructions. DNA was eluted in 100 µl of DNAse free water/elution buffer from which 13.5 µl was used to amplify the 18S ribosomal RNA gene by qPCR  which already contains the DNA polymerase (AmpliTaq Gold™DNA Polymerase)) in triplicates in a hydrolysis probe assay using primers and probes previously described. The PCR cycling conditions were carried as described using Applied Biosystems 7500 real-time PCR system. Non-template control was used as a negative control (in triplicate wells) with parasite quantification against known cultured parasite standards comprising of six serial dilutions of extracted DNA also run-in triplicate.Pf -specific plasma IgG plasma antibody responses were quantified against recombinantPf AMA1 , MSP1-42 kDa  and MSP3, to which circulating IgG antibodies were associated with clinical protection in previous studies. RecombinantPf antigens were kindly provided by L.H. Miller and colleagues from the Laboratory of Malaria and Vector Research . were included in every ELISA plate to provide a standard dilution curve that allowed conversion of optical density (OD) readings to antibody concentrations relative to levels present in MIG.Eleven serial dilutions of a purified immunoglobulin reagent  prepared from a pool of immune Malawian adultsµg/mL in bicarbonate buffer (100µL/well). One-hundred microliters per well of 1 in 1,000 dilution of test plasma in 0.3% (vol/vol) PBST + EDTA was added after plates had been washed three times with 0.05% (vol/vol) Tween in phosphate buffered saline (PBST), and thereafter blocked with 10% (vol/vol) foetal calf serum (FCS)/PBS (200µL/well). Plates with test plasma were then incubated for 1.5 h at room temperature in a humidified chamber. Plates were then washed five times before the addition of alkaline phosphatase (AP)-labelled goat anti-human IgG Abs (Sigma) conjugate at 1:2,000 dilution 0.05% PBST at 100µL/well. After 1h incubation with the conjugate, the plates were washed five times and the human IgG complexed with the AP-labelled conjugate revealed with and P-nitrophenyl phosphate (Sigma). The substrate reaction was stopped with 50µL/well of 3 M NaOH, after which the plates were left for 5 min in the dark before being read at 405/570 nm. Antibody levels were quantified against respective standard curves on each plate of a purified hyperimmune IgG from immune adults and expressed in arbitrary units”.Plasma samples from the cross-sectional surveys of 2015, 2016 and 2017 were tested for human IgG antibodies specific for AMA1, MSP1-42 and MSP3 antigens using a standard ELISA protocol. Recombinant Pf antigens were provided by L. H. Miller . Plates were coated overnight at 4 °C, with recombinant proteins at 1 were fitted to the 56 children who completed the cohort study from Junju, from the age of 5 to 15. The functional relationship of accumulated malaria episodes over timet,g(t), may be represented as a smoothed function through linear combinations of model coefficientskc and basis functionskϕ(t), whereSpline functions. These functions were fitted inR using theSCAM package. A log-link function was used to model the malaria count data. The smoothing parameter of each SCAM was fixed at 0.01 at 7 basis functions to make lines across all children comparable. The first derivative of the fitted accumulation of malaria episodes (g′(t)) represents the estimated number of episodes for that time point,t. Children who stop experiencing episodes in their last three years in the study were considered plateauers and their parasite density and antibody levels were investigated to see if this was due to a drop in exposure.Shape constrained additive models were used to ensure the accumulated malaria episode function never decreased and followed a monotonic functional relationship with timelme4.To understand why those children experiencing no more clinical malaria episodes, measurements of the levels of AMA1, MSP1 and MSP3-specific antibodies were compared between plateauers and children who experienced episodes up to the last three years of the cohort study. Antibody measurements were measured from samples taken in 2015, 2016 and 2017 and followed a crossed design structure fitted through a mixed model framework in the R packageXβ are the models fixed effects of Group  and Year  andZυ is the random effect of Participant. An F-test was used to determine the significant differences of the fixed effects based on the Kenward-Roger method from the lmerTest R package. Standard error of the difference was derived from the predictmeans package in R for each linear mixed effect model. For comparisons between antibodies AMA1  and MSP1 (FVO) the sample sizes for each group and year were: Continuous 11, Plateau 6 (2015); Continuous 10, Plateau 8 (2016) and; Continuous 10, Plateau 8 (2017). The comparison group sizes for antibodies AMA1 (FVO), MSP1  and MSP3 (FVO) were: Continuous 10, Plateau 8 (2015); Continuous 10, Plateau 8 (2016) and Continuous 10. Plateau 8 (2017). Please note that these sample sizes do not add to 56. The samples for antibody comparison comprise children from the 56 who had antibody measurements from 2015 to 2017. Where,By the age of 8, 2 out of 56 children do not go on to experience any further clinical malaria episode over the entire study period. This value increases to 22 out of 56 by age 12. Generally, there does not seem to be any discernible trend in terms of cumulative number of episodes for the 38 children who experienced an episode within the last three years of the study . Of the The 22 children who stopped experiencing episodes in the last few years of the study tended to be in the South-West region of the region, whereas the rest of the children were mostly located in the North-East region . When coPf antigens compared to children who continuously experienced clinical malaria episodes , FVO , L32  and MSP3 ;Children who plateaued in their accumulation of clinical episodes had higher levels of antibodies, specific for a number of keyF2,31.11 = 15.26,p < 0.001), FVO , L32 , MSP1 , FUP , FVO  and MSP3 FVO ,Further, there were large yearly differences across all groups in the levels of circulating antibodies JAddy_Epi_Data_Codebook.pdf (data code book)SummaryofAnalysis.html Creative Commons Attribution 4.0 International license (CC-BY 4.0).Data are available under the terms of the My concern has been addressed.Is the work clearly and accurately presented and does it cite the current literature?PartlyIf applicable, is the statistical analysis and its interpretation appropriate?YesAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?YesAre sufficient details of methods and analysis provided to allow replication by others?PartlyReviewer Expertise:Immunology of infectious diseasesI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Thank you to the authors for addressing my comments. The updated manuscript communicates the research very nicely. I particularly appreciate the updated description of the study design and inclusion of Table 1. I am still somewhat confused by the response to my question on the ELISA and use of mixed alleles. I understand the concept behind wanting to mix alleles, but the results  are presented per allele i.e. 3D7 and FVO separately. So were the antigen alleles mixed 1:1 and also assessed individually in the ELISA? Thank you for the clarification.Is the work clearly and accurately presented and does it cite the current literature?PartlyIf applicable, is the statistical analysis and its interpretation appropriate?YesAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?YesAre sufficient details of methods and analysis provided to allow replication by others?PartlyReviewer Expertise:Immunology of infectious diseasesI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. We thank the reviewer for their response.For AMA1, ELISA plates were coated with a 1:1 mixture of FVO and 3D7 alleles" was included in error. This part of the methods has been corrected. The sentence " I thank the authors for their consideration of my comments. The additional information they provide in the publication satisfies my earlier concerns.Is the work clearly and accurately presented and does it cite the current literature?PartlyIf applicable, is the statistical analysis and its interpretation appropriate?YesAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?YesAre sufficient details of methods and analysis provided to allow replication by others?YesReviewer Expertise:Mathematical modelling of infectious diseasesI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. This manuscript studies the acquisition of clinical episodes of malaria over 10 years and identifies two patterns; one where children stop acquiring further clinical episodes after age 12 and one where they continue to acquire them. They relate this to both asymptomatic parasite densities and anti-malarial antibody responses. The data availability is fantastic and very clear with the additional files outlining the variable information and the script used for analyses. The manuscript is generally well-written but could use further clarification on the points below (in addition to points made by the first reviewer).Data from the yearly cross-sectional surveys: the authors present asymptomatic parasite densities in Fig3c but as far as I can tell, they have not presented a summary of this data i.e. # of children with asymptomatic infections at each yearly survey and thus # of children that make up the data presented in Fig3c. I think this is important for their conclusion “children from the same sub-region develop immunity at different rates based on their exposure to the parasite”. Are the authors relating exposure to the parasite density or the total # infections (inc asymptomatic) experienced? Are all 56 children infected at each survey (I think no from the dataset)? Are the data in Fig3c from the blood-smears or qPCR ?ELISA results: in the methods it said the two alleles for AMA1 were mixed, so I am unclear how there are different results presented for both alleles? As the authors state in the introduction, current infections can have a big impact on antibody levels – can they comment on whether individuals from either group had current infections at the time the sampling was made for antibody measurements? In those that have current infections have the authors directly correlated/associated the parasite density with antibody level i.e. to give strength to their statement that antibodies are “a reflection of the level of Pf infection”? Minor points:nd paragraph in particular could be revised so it covers the whole cohort first then describes the 56 kids in this study. Would a schematic help? This might also help clarify the sampling for the yearly surveys, clinical episodes, antibodies etc.Study population: This section in the methods is a little difficult to follow given it’s a rolling enrolment and then a sub-group has been used. The 2Antigen/ELISA technical details: antigens need more info i.e. the expression system and construct – this could be referenced to a prior publication . What hyperimmune sample/s were used for the standard curve? Are they available for others to use i.e. is this a reference pool? How was the standard curve conversion performed? If this has all been done before a reference can be cited.Fig3C: the parasite densities between the two groups are still fairly similar and do vary year on year - can the authors comment on whether that difference in parasite density is meaningful/statistically significant?)/molecular force of blood-stage infection (PMID: 24040428)? Or antibodies against mosquito salivary gland antigens ?Discussion on characterising exposure in longitudinal cohorts: how about work that uses genotyping to understand the force of infection , as it could be argued the current manuscript does not identify the targets or mechanisms of the acquired immunity in these children – scope for future work.Final sentence in discussion on mechanisms responsible for partial immunity “ I cannot comment on technical details of the mathematical models. Major points:Is the work clearly and accurately presented and does it cite the current literature?PartlyIf applicable, is the statistical analysis and its interpretation appropriate?YesAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?YesAre sufficient details of methods and analysis provided to allow replication by others?PartlyReviewer Expertise:Immunology of infectious diseasesI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. We thank both reviewers for the positive review of our work. Their comments have added to the manuscript and have improved the quality and readability of the manuscript. We have addressed each point with and answer. In some cases, we have provided more information and clarity, in other cases we have accepted the issue and added to our manuscript accordingly. Responses from all reviewers have been included here.This manuscript studies the acquisition of clinical episodes of malaria over 10 years and identifies two patterns; one where children stop acquiring further clinical episodes after age 12 and one where they continue to acquire them. They relate this to both asymptomatic parasite densities and anti-malarial antibody responses. The data availability is fantastic and very clear with the additional files outlining the variable information and the script used for analyses. The manuscript is generally well-written but could use further clarification on the points below (in addition to points made by the first reviewer). Major points:Data from the yearly cross-sectional surveys: the authors present asymptomatic parasite densities in Fig3c but as far as I can tell, they have not presented a summary of this data i.e. # of children with asymptomatic infections at each yearly survey and thus # of children that make up the data presented in Fig3c. I think this is important for their conclusion “children from the same sub-region develop immunity at different rates based on their exposure to the parasite”. Are the authors relating exposure to the parasite density or the total # infections (inc asymptomatic) experienced? Are all 56 children infected at each survey (I think no from the dataset)? Are the data in Fig3c from the blood-smears or qPCR ? Added new Table 1 about yearly summaries cross-sectional surveys which answers this point and addressed in text . Exposure to the parasite is assessed using both asymptomatic measurements and clinical episodes. All 56 children live in a malaria region. qPCR data were used for Figure 3c.ELISA results: in the methods it said the two alleles for AMA1 were mixed, so I am unclear how there are different results presented for both alleles? As the authors state in the introduction, current infections can have a big impact on antibody levels – can they comment on whether individuals from either group had current infections at the time the sampling was made for antibody measurements? In those that have current infections have the authors directly correlated/associated the parasite density with antibody level i.e. to give strength to their statement that antibodies are “a reflection of the level of Pf infection”? The mixing of the two alleles means that we are only interested in the antibody response to AMA1 – irrespective to whatever alleles. Mixing ensures we minimise missing the response owing to the polymorphism. There are too few samples to do an adequate correlation between parasite density for a few of the antibodies. Added reference of evidence of relationship between parasite and antibodies in text (See the Discussion).Minor points:Study population: This section in the methods is a little difficult to follow given it’s a rolling enrolment and then a sub-group has been used. The 2nd paragraph in particular could be revised so it covers the whole cohort first then describes the 56 kids in this study. Would a schematic help? This might also help clarify the sampling for the yearly surveys, clinical episodes, antibodies etc. This question is similar to the other reviewers question, see the response to the other reviewer.Antigen/ELISA technical details: antigens need more info i.e. the expression system and construct – this could be referenced to a prior publication . What hyperimmune sample/s were used for the standard curve? Are they available for others to use i.e. is this a reference pool? How was the standard curve conversion performed? If this has all been done before a reference can be cited. This has been addressed in text (see Methods section “Antigens for ELISA”). Fig3C: the parasite densities between the two groups are still fairly similar and do vary year on year - can the authors comment on whether that difference in parasite density is meaningful/statistically significant? This difference is on the log-scale and shows that the parasite density is similar in both groups until 2010. This difference illustrates that although the temporal trends look similar, there is obvious spatial effects, plateauers seem to have higher parasite densities since 2010, but tend to live in the South-West. We cannot say which parasite density cut-off is responsible for the development of immunity here. A formal statistical comparison here is would not provide additional information as 95% confidence intervals have been produced.Discussion on characterising exposure in longitudinal cohorts: how about work that uses genotyping to understand the force of infection (PMID: 226658091)/molecular force of blood-stage infection (PMID: 240404282)? Or antibodies against mosquito salivary gland antigens ? Changed in text (see Discussion). Final sentence in discussion on mechanisms responsible for partial immunity “By assessing each study participant’s malaria history over ten years, we were able to provide a more comprehensive analysis of the diversity of malaria history within a cohort, facilitating more accurate identification of individual immune status and ultimately a less confounded investigation of the mechanisms responsible for development of partial immunity to malaria”. It might be worth also reflecting on work by others suggesting functional antibody assays are needed to identify targets of immunity rather than magnitude alone (PMID: 307232255), as it could be argued the current manuscript does not identify the targets or mechanisms of the acquired immunity in these children – scope for future work.I cannot comment on technical details of the mathematical models. Changed in text (see Discussion). This manuscript studies the variation in the number of clinical episodes experienced by children of the same age within the same cohort and relates it to the development of naturally acquired immunity. The analysis presented is particularly important as it highlights the need to account for heterogeneity within endemic populations in order to better define control and elimination measures. This is a well written manuscript and I have a few comments:If antibody levels were compared between plateauers and children who experienced episodes up to the last three years of the cohort study, it is not clear to me why the sample sizes are different between comparisons AMA1/MSP1(FVO) and AMA1(FVO)/MSP1/MSP3(FVO) over the years. For example, considering 2015, “continuous” are 11 when the comparison is between antibodies AMA1  and MSP1 (FVO), and 10 when comparison is between antibodies AMA1 (FVO), MSP1  and MSP3 (FVO). Also, individuals do not add up to 56 (sample size). Please, clarify it.Sentences like “cumulative episodes by the age of 15”, “with one child accumulating 32 episodes by the age of 15”, “another child, who experienced only 1 clinical episode before the age of 15” and “children who plateaued in their accumulation of clinical malaria episodes did not experience more than 9 episodes” are technically inconsistent if the analysis comprised children aged from 5 to 15. Please, rephrase them. The authors should also consider starting Figure x-tick labels (Age) with 5 and ending it with 15.If my understanding is correct, by selecting 56 children who were born between 2001 and 2003, the age of them should not be equal at a given time. Therefore, why do the authors choose to do antibody analysis over “Year”  and not over “Age” ? It seems to me that the analysis over “Age” is one that best assesses each study participant's history of malaria. Please, clarify it.The sentence “MSP1 was the only antigen for which there were no distinct differences between the two groups of children” may lead to wrong inferences. The authors should consider mentioning the sample size of the analysis as one of its limitations and improve the discussion about MSP1 antigen results.   I cannot comment on technical details of antibody methods and techniques.Is the work clearly and accurately presented and does it cite the current literature?PartlyIf applicable, is the statistical analysis and its interpretation appropriate?YesAre all the source data underlying the results available to ensure full reproducibility?YesIs the study design appropriate and is the work technically sound?YesAre the conclusions drawn adequately supported by the results?YesAre sufficient details of methods and analysis provided to allow replication by others?YesReviewer Expertise:Mathematical modelling of infectious diseasesI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. This manuscript studies the variation in the number of clinical episodes experienced by children of the same age within the same cohort and relates it to the development of naturally acquired immunity. The analysis presented is particularly important as it highlights the need to account for heterogeneity within endemic populations in order to better define control and elimination measures. This is a well written manuscript and I have a few comments: If antibody levels were compared between plateauers and children who experienced episodes up to the last three years of the cohort study, it is not clear to me why the sample sizes are different between comparisons AMA1/MSP1(FVO) and AMA1(FVO)/MSP1/MSP3(FVO) over the years. For example, considering 2015, “continuous” are 11 when the comparison is between antibodies AMA1  and MSP1 (FVO), and 10 when comparison is between antibodies AMA1 (FVO), MSP1  and MSP3 (FVO). Also, individuals do not add up to 56 (sample size). Please, clarify it. The initial part of this study focuses on children who have completed the cohort study and left when they were 15 by 2018 . When comparing antibody data we want to remove all possible confounders, such as age. Also, the antibody data follow a repeated measures design, the same children sampled each year. Further, there is strong year-to-year variation in clinical malaria episodes and parasite densities across the study. So, in order to obtain an unbiased antibody comparison between plateauers and non-plateauers children who have antibody measurements across all three years were considered, and these were all children of the same age. A linear-mixed-model (LMM) was used, to identify the individual effect of each child and this was modelled as a random effect. The reason why 11 children were included for some antibodies and 10 for other, is because these are the same individuals, but there was a missing value for AMA1 (FVO), MSP1  and MSP3 (FVO) antibodies. We reduced the influence this missing value has on our result by using a linear-mixed-model (LMM) and having child as a random effect. This has been clarified in the text .Sentences like “cumulative episodes by the age of 15”, “with one child accumulating 32 episodes by the age of 15”, “another child, who experienced only 1 clinical episode before the age of 15” and “children who plateaued in their accumulation of clinical malaria episodes did not experience more than 9 episodes” are technically inconsistent if the analysis comprised children aged from 5 to 15. Please, rephrase them. The authors should also consider starting Figure x-tick labels (Age) with 5 and ending it with 15. Changed in text .If my understanding is correct, by selecting 56 children who were born between 2001 and 2003, the age of them should not be equal at a given time. Therefore, why do the authors choose to do antibody analysis over “Year”  and not over “Age” ? It seems to me that the analysis over “Age” is one that best assesses each study participant's history of malaria. Please, clarify it. Following from above, to ensure Age was not confounding our plateauers vs non-plateauers comparison, only children of the same age and over three years were considered. We could not adequately do an Age comparison due to the oldest children leaving the study after one antibody sample. Therefore, any Age comparison (only data from 2015) would be confounded by 2015 being a high transmission year. Age is not a variable of interest in the manuscript but rather whether children plateau or not in their clinical symptoms. As this illustrates the complexity of longitudinal malaria cohort studies.The sentence “MSP1 was the only antigen for which there were no distinct differences between the two groups of children” may lead to wrong inferences. The authors should consider mentioning the sample size of the analysis as one of its limitations and improve the discussion about MSP1 antigen results. Changed in text .


One of the main markers of arterial stiffness is pulse wave velocity (PWV). This parameter is well studied as a marker for end-organ damage in the adult population, being considered a strong predictor of major cardiovascular events. This study assessed PWV in children with chronic kidney disease (CKD) as a marker of cardiovascular risk. We conducted a prospective observational single-center cohort study of 42 consecutively pediatric patients (9–18 years old) with terminal CKD and dialysis, at the Hemodialysis Department of the “M. S. Curie” Hospital, Bucharest. We measured PWV by echocardiography in the ascending aorta (AscAo) and the descending aorta (DescAo), and we correlated them with left ventricular hypertrophy (LVH). Fifteen patients (35.7%) presented vascular dysfunction defined as PWV above the 95th percentile of normal values in the AscAo and/or DescAo. Cardiac disease (LVH/LV remodeling) was discovered in 32 patients (76.2%). All patients with vascular damage also had cardiac disease. Cardiac damage was already present in all patients with vascular disease, and the DescAo is more frequently affected than the AscAo (86.6% vs. 46.9%). Elevated PWV could represent an important parameter for identifying children with CKD and high cardiovascular risk. The main leading cause of death in end-stage renal disease (ESRD) is cardiovascular disease (CVD) ,2. The pThere is emerging literature describing arterial stiffness in pediatric populations and the relation of arterial stiffness to pediatric CKD, but this study has primarily focused on pediatric patients with terminal CKD and dialysis. Measuring the vascular rigidity/elasticity parameters and correlating them with cardiac disease markers  in CKD may offer an additional predictive value for major cardiovascular events and mortality ,13,14,15According to the recommendations of the American Heart Association from 2015 , there aRegarding the measurement of PWV in children, a method has not been validated yet, given the fact that this parameter is closely dependent on body dimensions and height. More recently, some research studies have evaluated the results of various calculation methods for PWV and tried to determine which one is less prone to errors and easier to reproduce ,22. ThesConsidering that both methods are predisposed to errors, especially in the pediatric population, some researchers have attempted to develop a more precise modality to determine the distance covered by the pulse wave. In 2010, Jo et. al. .The aim of this study is to assess if PWV could be an adequate marker of vascular remodeling in a pediatric population with CKD, along with technical aspects of PWV measurements in children.This single-center prospective observational cohort study enrolled 42 consecutively pediatric patients referred to the Nephrology and Hemodialysis Department of “M. S. Curie” Clinical Emergency Hospital. Twenty-five patients were females (59.5%), and 17 males, between 9 and 18 years old, with end-stage CKD, all undergoing dialysis; the patients were evaluated between September 2014 and September 2020. The exclusion criteria were as follows: other secondary forms of hypertension, congenital cardiovascular diseases, history of aortic surgery, aortic valve pathology, and inflammatory large-vessel vasculitis. One patient was excluded, who had Takayasu arteritis.The patients were evaluated using Philips ultrasound machine Philips CX50, Philips Affiniti, and Philips iE33 with S5-1, S8-3, and 17-5 transducers and having continuous ECG monitoring during the whole examination. During the examination, we measured both systolic and diastolic blood pressure, weight, and height for all the patients. Blood pressure measurements were performed on the right arm at the examination time by an automatic oscillometric method after 5 min of rest in a supine position.BTL Cardio Point-ABPM; 30 min intervals for daytime and 60 min intervals overnight were used for BP measurement.The patients were diagnosed with arterial hypertension (stage 1 or 2), controlled or uncontrolled by treatment, based on the Clinical Guideline of American Academy of Pediatrics, considering age, sex, and height percentiles, using median blood pressure values during 24-h ambulatory monitoring . Blood pPWV was measured non-invasively in the ascending aorta according to the formula L1/ΔT1, where L1 = 2 cm and ΔT1 represents the transit time of the pulse wave from the aortic valve (X point) to the established reference in the ascending aorta . Transit time was calculated as being the difference between the time from the start of the QRS complex to the beginning of the systolic wave at the Y point and the time from the start of the QRS complex to the beginning of the systolic flow at the X point .To minimize the errors, the time used for the final calculation represented an average of five consecutive measurements. In the DescAo, we measured PWV according to the formula L2/ΔT2, where L2 represents the length of the aorta from the aortic valve to the diaphragm (X-Z distance—Given the difficulty of measuring the aortic length (L2), we conducted a literature review upon this subject and concluded that the method that would be least prone to errors is according to the following formula : L2 = lePWV values were compared to the normal values allocated to age percentiles by gender of PWV in the pediatric population ,23,24; vhttp://www.csecho.ca/wp-content/themes/twentyeleven-csecho/cardiomath (accessed on 24 December 2021), platform.The calculation of the left ventricle index was done according to the formula approved by the Echocardiography Societies, and we used the software implemented on the The left ventricular mass (LVM) was calculated according to a previously published methodology  on basis3 − LVEDD3)]} + 0.6 [LVM (g) = 0.8{1.04[ allows for further classification of increased LV mass as either concentric hypertrophy (RWT > 0.42) or eccentric hypertrophy (RWT ≤ 0.42).LVMI (g/m2) was calculated as follows: LVMI = left ventricular mass/body surface area (BSA) ,27. SeeA,B.p-value of the predictor candidate in the univariate analysis was below 0.05, this predictor was included in the multivariable regression model.We performed the statistical analysis and created the charts using the software GraphPad Prism 9.2.0, USA; SPSS 27  and Analyse IT 5.5 . The results were analyzed with the software Medcalc . Since most results were not normally distributed, all results are presented with their median and interquartile range (IQR). Differences between groups were assessed by t-test, or chi-squared test when appropriate. We compared the PWV values between the group with and without vascular stiffness, using a t-test. If the Anthropometric, clinical, and echocardiographic data of the patients included in the study group are presented below See .Of the 42 patients from the study group, 32 patients (76.2%) had cardiac disease expressed by concentric remodeling (14.29%), concentric LVH (40.48%), or eccentric LVH (21.43%), and 22 were females. Fifteen (46.9%) patients had increased PWV, LV hypertrophy/remodeling was present in all cases, and 17 patients had LV hypertrophy/remodeling without increased PWV.The characteristics of the patients and the values of the results obtained by echocardiography of the patients from the study group are presented in The mean PWV of the 15 children with LVH and vascular stiffness was 4.53 m/sec in AscAo and 5.279 m/sec in DescAo.p < 0.05) in the group with LVH and vascular stiffness for PWV in DescAo, and age, height, SBP and DBP, and type of RRT. All patients with increased PWV were hypertensive (versus 70.6% hypertensive patients among patients without vascular stiffness)—See p > 0.1). Values of the individual correlations are shown in Linear regression was used to determine the echocardiography parameters among the group without LVH and the groups with LVH +/- vascular stiffness. There is a positive correlation with statistical significance . In the group with cardiac impairment, 21 of 32 patients were females (95% CI = 0.48–0.79), and in the group with vascular impairment associated with cardiac disease, we found 12 females (95% CI = 0.54–0.93) of 15 patients.p value < 0.0001). We observed higher values in group with LVH and arterial stiffness, in PWV AscAo , than in the group without arterial stiffness . Similar findings were observed as we compared the DescAo PWV in the group with vascular stiffness , p < 0.001), and with the non-vascular stiffness group , p < 0.001)  and those with LVH but without vascular stiffness, revealed statistically significant difference in both AscAo and DescAo (< 0.001) .Among the group of 15 participants with vascular stiffness, only seven patients had increased PWV in the AscAo with or without concomitant increased PWV in the DescAo. Higher PWV levels were found in the DescAo in 13/15 patients who had PWV > 95th percentile (including one patient with high PWV in both AscAo and DescAo). Five out of fifteen patients showed an increase in PWV in both the AscAo and the DescAo. Eight out of fifteen had increased PWV in the DescAo, and two out of fifteen had increased PWV in the AscAo .p < 0.01): 60% of those with increased PWV in the aorta present with untreated/insufficiently treated hypertension (versus 17.64% among patients without vascular dysfunction). Additionally, among patients with vascular stiffness, patients with concentric LVH and patients with severe LVH are predominant  were found to have these echocardiographic myocardial findings versus 63% of those without vascular stiffness, the implications of PWV for cardiovascular risk estimation require confirmation. Elevated PWV values indicate increased arterial stiffness and may represent an important parameter for identifying children with CKD and children at high risk for major cardiovascular events .(1)Does impairment of large vessels elasticity occur later in the course of CKD than apparition of abnormal myocardial findings?(2)Is the PWV cut-off value set at the 95th percentile too high and does it require adjustment to a lower threshold to increase the sensitivity of the method for determining vascular stiffness utilizing this noninvasive modality?Our findings raise the following questions:To answer these questions, further research is required to correlate PWV values with other manifestations of abnormal vascular elasticity, such as aortic distensibility or intima-media thickness at the carotid.Another finding we would like to emphasize is the higher incidence of descending aorta stiffness in patients with CKD in comparison to the ascending aorta. We suspect that this finding is related to proximal/distal structural aortic wall differences, which in turn may be related to the distal to the proximal progression of biomechanical changes, similar to the damage described in the aorta with advancing age in the adult population . This paIn the core of our work is the technique we utilized to measure PWV. The most important advantage of the PWV calculation method we utilized is the ability to measure PWV across a short segment of the ascending aorta. This measurement cannot be accomplished using the digital subtraction method, which is much more frequently used, especially in the adult population. This advantage allowed for the demonstration of the different characteristics of the ascending versus descending aorta PWV. Other advantages offered by this technique are the accuracy of measurements of the pulse wave transit times at the level of the descending aorta, as well as low costs, requiring only an ultrasound machine with adequate software and an experienced sonographer.Based on our literature search, comparison of the aortic stiffness at different levels of the aorta in children with CKD has not been the focus of other research studies so far. Studies conducted since 2000 have confirmed, similar to our study, the increase in PWV values in these patients ,12,13,14Although our study provides useful information about the association of PWV as a marker of vascular stiffness and LV hypertrophy or ventricular remodeling in pediatric patients, it is important to consider several limitations. First, our study population included significant gender differences that are hard to interpret and likely related to the overall small number of study patients. Second, our single center study design is prone to bias as well.In 2009, the American Heart Association emphasized the importance of standardizing noninvasive methods for quantifying the cardiovascular risk in the pediatric population, mentioning the usefulness of PWV as a marker of end-organ damage . UnfortuIncreased arterial stiffness was demonstrated to be the vascular hallmark of patients with end-stage renal disease independently of age, blood pressure, and standard risk factors . TherapeThe limitations of this study include the small size of the cohort, single-center study, and significant difference in the gender distribution. Other study limitations include the absence of a normal control group to compare with.Elevated PWV values indicate increased arterial stiffness and may represent an important parameter for identifying children with CKD and children at high risk for major cardiovascular events . The technique used for the assessment of PWV value could be based only on echocardiographic measurements (as we did in our study), but it requires a skilled sonographer to lower possible measurements errors.Further studies, including larger numbers of patients, are necessary to conclude if the cut-off value used in our study for the diagnosis of vascular dysfunction (95th percentile) has the best sensitivity and specificity for detection of this pathology.The non-invasive technique for PWV is an important issue and require further refinement for it to become an important part of the clinical routine. Future studies should provide robust evidence of increased PWV in either the AscAo or the DescAo, in children with HD who had LV structural abnormalities.


Antibodies targeting the protein that causes placental malaria can recognise multiple variants of the protein, which may help guide the development of new vaccines to protect pregnant women from malaria. Related research article Doritchamou JYA, Renn JP, Jenkins B, Mahamar A, Dicko A, Fried M, Duffy PE. 2022. A single full-length VAR2CSA ectodomain variant purifies broadly neutralizing antibodies against placental malaria isolates. eLife11:e76264. doi: 10.7554/eLife.76264.Malaria is a serious, potentially life-threatening disease spread by mosquitoes. Pregnant women are especially at risk, as high densities of the parasite that causes malaria can accumulate in the placenta. This can trigger damaging inflammation in the placenta, which could affect the growth and development of the unborn baby, and even lead to a higher risk of infant death .The malaria parasites that infect pregnant women are unique in displaying a protein called VAR2CSA on their surface. When VAR2CSA binds to CSA, a molecule on the surface of placenta cells, it leads to placental malaria. Over successive pregnancies, the body develops immunity against placental malaria by generating antibodies targeting VAR2CSA, and preventing it from attaching to CSA . This suHowever, the sequences of the gene that codes for VAR2CSA vary between the different parasite strains . Two triDoritchamou et al. first mixed five variants of the VAR2CSA protein (one at a time) with a pooled plasma sample from women who were immune to placental malaria. Each time they mixed a single VAR2CSA variant with the plasma, antibodies that bound to that variant were purified out of the pool and quantified. This revealed that most antibodies had bound to the first two variants, suggesting that antibodies towards the latter variants had already been depleted from the pool because they also recognised the earlier variants.To confirm that antibodies were cross-protective, the researchers then took the antibodies they had purified using one particular VAR2CSA variant and tested their ability to recognise other variants. This revealed that the antibodies that attached to the first VAR2CSA variant were able to recognise all other tested variants. Cross-recognition was seen using purified proteins or using infected red blood cells expressing the variant.The fact that naturally acquired antibodies against one version of full-length VAR2CSA also react with other variants implies that exposure to a small number of VAR2CSA variants might be enough to provide protection . This fiAdditionally, naturally occurring antibodies, which lack an attached sugar called fucose, may be more protective than antibodies induced by a placental malaria vaccine, which have this sugar . The reaThere is also the question of when is the best time to administer a vaccine. Ideally, immunisation would start in young, adolescent girls, a strategy commonly used for HPV vaccines to prevent cervical cancer. Such a vaccine roll-out would require detailed and ongoing consultation in communities where the vaccine might be used, but saving the lives of young mothers and their babies should be worth every effort.