Management of severe malaria remains a critical global challenge. In this study, using a multiplexed quantitative proteomics pipeline we systematically investigated the plasma proteome alterations in non-severe and severe malaria patients. We identified a few parasite proteins in severe malaria patients, which could be promising from a diagnostic perspective. Further, from host proteome analysis we observed substantial modulations in many crucial physiological pathways, including lipid metabolism, cytokine signaling, complement, and coagulation cascades in severe malaria. We propose that severe manifestations of malaria are possibly underpinned by modulations of the host physiology and defense machinery, which is evidently reflected in the plasma proteome alterations. Importantly, we identified multiple blood markers that can effectively define different complications of severe falciparum malaria, including cerebral syndromes and severe anemia. The ability of our identified blood markers to distinguish different severe complications of malaria may aid in developing new clinical tests for monitoring malaria severity. Kumar et al. use proteomes of patients with falciparum and vivax malaria and dengue fever, and identify differentially abundant proteins and their associated functions in the different severities and diseases. This study offers mechanistic pathways to malaria severity, and adopts a machine learning approach for predictive proteins for the malarial types and severities. Plasmodium genus1, and the vector involved is female Anopheles mosquito. It is the most widespread tropical parasitic disease with a worldwide occurrence of 228 million clinical cases and 0.4 million deaths in 2018 (ref. 2). India majorly contributes to the global malaria burden and has the largest population in the world at risk of malaria, with 85% of the total Indian population living in malarious zones3. Worrisomely, the subsidiary burdens of malaria, such as malnutrition and anemia, increase the risk of complications and severity of the disease5. Among the five parasites causing malaria in humans, Plasmodium falciparum and Plasmodium vivax have the most extensive global distributions and are capable of leading severe fatal clinical manifestations6. Particularly, P. falciparum infections often turn severe and life-threatening, specifically when managed inappropriately8. One of the prime causes behind the progression of this parasitic infection from mild through complicated to severe disease is missed or delayed diagnosis10. Of note, neither parasite density nor parasitemia can consistently define malaria severity11. Hyper-parasitemia does not necessarily provide primary prognostic significance in semi-immune individuals, as they often tolerate high parasitemia burden without any physiological signs of disease or severe effects12.Malaria is a vector-borne infectious disease caused by the protozoan parasites of the 16. Additionally, the RDT-based detection approaches target PfHRPII for P. falciparum only, pLDH for all Plasmodium species, and aldolase for P. falciparum and P. vivax. Importantly, many population-based studies have shown partial or complete deletion of pfhrpII and pfhrpIII genes, which may lead to false-negative results in RDTs19. Overall, these issues amply highlight the need for identification of additional parasite proteins and host factors for better diagnosis of malaria. Moreover, the establishment of predictive blood biomarkers for malaria severity and complications would be highly promising for prognosis, monitoring disease progression and responses to therapy, and predicting outcomes.There are several limitations for the existing diagnostic methods for malaria, which include microscopic examination of thick and thin blood smears, polymerase chain reaction (PCR)-based molecular diagnostics, and rapid diagnostic tests (RDTs)18. Intriguingly, several studies from our and other research groups have defined promising panels of plasma and serum markers in falciparum24 and vivax26 malaria. A considerable amount of further research is required to understand the complex pathophysiology of severe malaria29. In particular, the blood markers that can effectively define different complications of severe malaria are not clearly demarcated hitherto. Indeed, the precise mechanisms that cause a transition from non-severe to severe fatal clinical manifestations in malaria, which often happens very rapidly, remains largely obscure. These are the critical questions that remained to be addressed to understand the molecular basis of severe malaria.In recent years, plasma/serum proteomics studies have contributed substantially to elucidate the complex pathogenesis of malaria and other infectious diseasesIn this study, we performed comprehensive proteomics analysis of plasma samples from falciparum malaria patients with different severity levels and clinical manifestations to understand the mechanisms of malaria severity and its complications. We further carried out a comparative analysis with differentially abundant plasma proteins identified in vivax malaria (VM) and dengue patients to specify the alterations observed in falciparum malaria. Importantly, we identified several blood-based host proteins marker for malaria severity and complexity, which can aid in monitoring disease progression. Further, we have also identified parasite proteins such as Serine Repeat Antigen 4 and Fructose-Bisphosphate Aldolase in severe malaria patients’ plasma samples, which can help in the diagnosis of severe malaria. To the best of our knowledge, this is one of the most comprehensive blood-based proteomic studies on falciparum and VM. Our findings provided insights regarding malaria pathogenesis and molecular cues of severity and complicated disease manifestations associated with this parasitic infection.p < 0.05) (in both NSFM and SFM) as compared to HC. The magnitude of alterations (decrease) in platelet counts and hemoglobin (Hb) levels were found to be more prominent in severe malaria. Liver function parameters including total bilirubin, serum glutamic-oxaloacetic transaminase (SGOT), serum glutamic-pyruvic transaminase (SGPT), and alkaline phosphatase (ALP) were found to be higher in SFM patients as compared to NSFM and HC  in SA as compared to CB and other different types of complications of SFM, while the other parameters were almost comparable. These liver function parameters were slightly higher in non-severe malaria as compared to HC, but the level of alteration was minimal , Non-severe falciparum malaria (NSFM), Severe falciparum malaria (SFM), Cerebral malaria (CB), Severe anemia (SA), Control for severe anemia (CSA), Control for cerebral malaria (CCB), Non-severe dengue fever (NSD), Severe dengue (SD), Non-severe vivax malaria (NSVM), and Severe vivax malaria (SVM). The subjects were recruited from different malaria epidemic regions in India. The number of samples analyzed for each group is provided in Supplementary Data 32. TMT-based multiplexed quantitative proteomics was used to map the plasma proteome (host) alterations, while we used a label-free quantitation (LFQ) approach for detection and quantification of the parasite  proteins in host plasma. Quality control check (QC) of the datasets was performed by plotting the density plots for FM, VM, and DF using raw and normalized abundances at a proteome scale  altered proteins were considered for machine learning, and the elastic net regularized logistic regression method was applied to predict the best panel of proteins. Some selected targets were validated using mass spectrometry (MS)-based multiple reaction monitoring (MRM) assays. Eventually, we investigated the physiological pathways over-expressed in falciparum and VM  altered in SFM as compared to NSFM, and their abundance profiles enabled us to differentiate SFM and NSFM , and it distinguished between the three study populations: HC, NSFM, and SFM  and 11,530 peptides were identified corresponding to 1495 proteins identified combining all the samples, among which 296 proteins were present in more than 60% of the clinical samples used for the label-based FM study Fig. . The proSFM Fig. . SignifiThe platelet degranulation process was found to be highly active in FM. Plasminogen (PLG), Platelet factor 4 (PF4), Profilin-1 (PFN1), Kininogen-1 (KNG1), and Pro-platelet basic protein (PPBP) were found to be down-regulated in NSFM as compared to SFM, while Alpha1-antitrypsin (SERPINA1) and Alpha2-antiplasmin (SERPINF2) were dysregulated in SFM as compared to NSFM Fig. . Proteinn = 6) and cerebral malaria  exhibited 28 and 35 differentially abundant proteins (p < 0.05), respectively, in comparison to HC and 17 proteins in SA as compared to CB  can effectively distinguish CB or SA as compared to HC  as compared to NSFM. Most of these proteins were found to be down-regulated in CB. Out of these 12 altered proteins, 3 candidates—HGFA33, SERPINA3, and ALX1 protein—were found to be up-regulated, while the other 9 proteins were down-regulated as compared to NSFM. Five proteins were significantly altered, specifically in CB as compared to NSFM. Of note, these proteins were unaltered in meningitis patients   in NSVM and SVM as comparison to HC and 45 differentially abundant proteins (p < 0.05) in SVM as compared to NSVM, respectively  in NSVM, SVM, and DF also showed three distinct clusters  using an LFQ approach.  for sporozoites gliding and invasion36. SERA4, along with the other SERA member proteins, helps in maintaining the blood stage of the pathogen’s life cycle. However, their clear physiological functions still remain unknown37, and need to be investigated further.HSP 70 and HSP 90 were reported as up-regulated at temperature 38 °C and above, which helps the survival of the parasite in the erythrocytic stage of its life cycle in the hyperthermic condition of the hostp < 0.05) plasma proteins identified in malaria and dengue. Of note, we are able to separate VM, FM, dengue, and HC samples based on the abundance profiles of the altered plasma proteins  for the three models were as follows: (i) dengue vs. malaria: 0.1, 0.26, 0.975, 0.967, and 0.96; (ii) FM vs. VM: 0, 80.2, 1, 1, and 1; and (iii) CB vs. SA: 0.04, 41.73, 1, 1, and 1, respectively. It is evident from the model performance metrics that the resulting elastic net regularized logistic regression model can predict and classify dengue vs. malaria, FM vs. VM, and cerebral vs. severe malaria anemia cases almost perfectly. These results are quite fairly stable across all (outer) k-fold iterations  and performance metrics  across malaria and Dengue effectively differentiated between these two infections  from dengue patients. The three-dimensional PLS-DA plot for all altered proteins and heat map profiles of the top 20 significantly altered proteins , FM (n = 30 × 3), VM (n = 30 × 3), and DF (n = 27 × 3) along with 15 synthetic heavy peptides. The measurements obtained in MRM correlated well with the TMT-based discovery-phase proteomics  proteins and parasite proteins in plasma samples using MRM-based mass spectrometric assays. We have considered 7048 transitions corresponding to 86 human plasma proteins (403 unique peptides), which were identified as the best classifier in our machine learning analysis for the optimization of MRM assays. Initially, we started with 40 different method files having a maximum of ~200 transitions, then we refined our methods and finalized 847 transition corresponding to 128 peptides and 46 proteins Fig. . MRM assSimilarly, we validated the detection and quantification of the parasite proteins in human plasma samples. Ninety-five transitions corresponding to eight parasite proteins were optimized, and we were able to quantify those in the plasma samples using MRM assays . The variants of PfEMP1 are involved in cytoadherence and mediate binding of the infected erythrocytes to endothelial vasculature6. Some of the parasite proteins that were identified in the plasma samples of SFM patients, such as FBA, HSP 70, HSP 90, enolase, and SRA4 can generate antibody responses, as we have shown previously in VM38. Similarly, Moussa et al.24 reported the presence of FBA, SRA protein, and histone H3 in plasma samples of children with CB. Most of these proteins play a very important role in catalytic activity and protein binding  possibly due to alterations in the levels of proteins such as PF4, PPBP, PFN1, KNG1, CLU, and PLG in NSFM , a platelet-secreted chemokine, and platelet activation marker that takes part in the process of clearing the parasites by inducing macrophage chemotaxis and mediating neutrophil accumulation44 . This leads to the activation of endothelium, disruption of blood flow, and ultimately causes tissue hypoxia. These events lead to an increase of endothelial receptors, and therefore shedding of soluble endothelial receptors, eventually leading to endothelial damage57. We anticipate that this could be one of the possible mechanisms associated with the progression of NSFM to CB .We observed up-regulation of the proteins related to intrinsic pathways such as vWF, F10, and F2 in SFM. Infected RBCs induce the expression of tissue factors on endothelial cells and monocytes, which results in the expression of cytokines via signaling pathways, ultimately leading to endothelial cell activation. vWF is a secondary marker for endothelial cell activationity Fig. 47. Impor CB Fig. . Some of60. We observed increased levels of C3 which is an active component of the complement system. Complement C5, C6, and C7 form a complex c5c6c7 (ref. 61), and bind to the cell membrane and membrane attack complex with the help of C8 and C9 (refs. 63). In our study, we observed all of these three proteins forming the complex  were down-regulated while the free monomers (C8 and C9) were up-regulated in NSFM  in circulation65. We observed a significant elevation in blood levels of Hb subunit alpha and beta in FM patients, as also described previously by Kassa et al.23. The free Hb is oxidized by free radicals, thereby releasing free heme. Of note, free heme is very toxic to the cells and induces inflammation, macrophage activation, and oxidative stress. However, the down-regulation of these proteins  indicate their involvement in scavenging of free heme and ROS in FM. RBC lysis and highly activated complement system may have direct effects on the destruction of erythrocytes and cytokines indirectly affect the inhibition of erythropoiesis. This clearly indicates an increased removal of the infected and uninfected erythrocytes that plays an essential role in severe anemia during malaria  and reduce the process of erythropoiesisParasite proteins that were consistently detected in almost all the severe malaria patients could be promising for developing different diagnostic approaches. Of note, those could be an indicator of severe infection as they are specifically detected in severe malaria patients. However, it remains to be seen whether these blood-based protein markers for malaria severity and complexity identified in our study are validated in bigger heterogeneous clinical cohorts. One potential caveat to this study is the possibility for asymptomatic infection in the control cohorts, although these were entirely devoid of any clinical symptoms of malaria. Moreover, genetic analysis of human plasma samples for glucose 6 phosphate dehydrogenase (G6PD) deficiency and hemoglobinopathies was outside the scope of this study. This leaves a lack of information on certain key host responses during the regulation of host proteins in the response of malaria. These could be an effective future continuation of the present investigation, especially as the findings continue to move towards translational research. Collectively, our findings provided some novel mechanistic insights into malaria severity, and we anticipate that this will accelerate the opportunities for developing clinical tests integrating these host and parasite proteins for monitoring malaria severity and complexity.This study was conducted involving malaria and DF patients, and control subjects from two different malaria-endemic regions of India. Subjects were enrolled in Calcutta medical college (CMC), Kolkata, India, and Sardar Patel medical college (SPMC), Bikaner, India. More precisely, this comprehensive proteomics study was accomplished involving HC subjects, and patients suffering from NSFM, SFM, and different complications  and CB and their corresponding control subjects, anemic [CSA], and meningitis patients [CCB], NSD; SD, NSVM, and SVM. This study was approved by the institutional review boards and ethics committee of the Indian Institute of Technology Bombay (IITB-IEC/2016/026). Prior to the sample collection process, written informed consent was received from each participant after giving detailed explanations about the experimental procedure in the language best understood by the potential participants.66. The brief workflow is depicted in Supplementary Materials and Methods, and schematic representation is provided in Supplementary Fig. P. falciparum and P. vivax) were excluded from this study. The case definitions of severe malaria67 were adopted from standard WHO guidelines  NSD and (2) SD based on clinical features  and hematological parameters . In our study, IgM was used as the confirmatory marker for dengue infection. If NS1 was found to be positive, we retested for IgM during the 5–7 days of fever to confirm the diagnosis.According to the recent WHO guidelineg for 10 min, and plasma samples were stored at −80 °C until further processing69.Blood samples were collected into ethylenediaminetetraacetic acid (EDTA), BD vacutainer, tube, and gently mixed by inverting 8–10 times. EDTA-anticoagulated blood (3 ml) was centrifuged at 1000Blood samples of malaria-infected patients were collected from the different endemic regions of India. The collected samples were microscopy and RDT-positive samples. Further confirmation of the malaria parasite, nested PCR was performed using dried blood spots of the obtained samples. Only PCR-positive singly infected patient samples were taken forward for multi-omic study. For nested PCR from dried blood spots, Whatman filter paper 1 was taken, and 20 µl of RBC pellet was spotted on the Whatman paper. For each sample, 3–5 spots were made as per the availability of the RBC pellet. Two dried spots were punched in a 1.5 ml eppendorf tube. Added 200 µl of 0.5% freshly prepared saponin in PBS (or up to the volume required to submerge the punched spots). A short spin was given to settle down the droplets on the brim. Samples were incubated for 10 min at RT. Six hundred microliters of PBS was added to the blood spots for wash and supernatant was discarded. Washing was done for 2–3 times, and then the PCR reaction was set.TM Top 12 abundant depletion column following the manufacturer’s instructions . Briefly, 15 µl of crude plasma was directly added to the resin slurry in the columns, and the mixture was incubated for 60 min at room temperature with gentle vortexing in between. The filtrate was collected in 2 ml Eppendorf tubes by centrifuging at 1000g for 2 min. The depleted plasma samples were concentrated using a vacuum centrifuge.Removal of high abundant proteins is crucial for the detection of the low-abundant proteins, many of which frequently act as potential biomarkers. Therefore, before processing the plasma samples for proteomic analyses, the top 12 highly abundant proteins  were removed by using PierceProtein extracted from the plasma samples of HCs and infected patients were quantified using Bradford Assay kit (Bio-Rad) following the manufacturer’s instructions. The depleted plasma samples were loaded onto one-dimensional sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) gels (12.5% acrylamide-bisacrylamide) for the quality check control  following the manufacturer’s instructions. One hundred micrograms of depleted protein sample from each group  were denatured using 15 µl of 6 M urea. The denatured proteins were reduced by adding tris (2-carboxyethyl) phosphine (TCEP) (Sigma Aldrich) to a final concentration of 20 mM and were incubated at 37 °C for 60 min. The reduced samples were alkylated by adding iodoacetamide  to a final concentration of 40 mM and were incubated at room temperature in dark for 30 min. The samples were then diluted eight times with 50 mM ammonium bicarbonate buffer, and trypsin (Pierce Trypsin) was added to a 1:30 ratio (trypsin: protein) for performing in-solution digestion. Samples were incubated at 37 °C for 18 h for efficient digestion. The digestion was quenched by adding formic acid to a final concentration of 1%TMT six-plex isobaric tags  were used for FM and Dengue (FC) samples and TMT 10-plex isobaric tags  were used for VM samples for labeling of the digested peptides as per the manufacturer’s instructions. In brief, digested peptides were reconstituted in dissolution buffer and were vortexed to mix well. A pooled sample was prepared from each individual patient sample and was considered as a reference for performing normalization of the different mass spectrometric datasets. TMT reagents were reconstituted in 40 µl of anhydrous acetonitrile (ACN) and the reagents were added to the corresponding aliquot of digested plasma protein sample following the labeling strategy  set at 5e (ref. 4) was followed by up to 20 ms/ms scans at a resolution of 30,000 with AGC set at 4e (ref. 5). MS/MS spectra were collected with a normalized collision energy of 35% and an isolation width of 1.2m/z. Dynamic exclusion was set to 40 s, and the peptide match was set to on. Surveys scans were performed in the Orbitrap mass analyzer and data-dependent MS2 scans were performed in Orbitrap mass analyzer trap using higher-energy collisional dissociation (HCD) following isolation with the instrument’s quadrupole. The intensity threshold of the peptide was set 5e (ref. 3). Internal calibration was carried out using a lock mass option (m/z 445.1200025) from ambient air. The same parameters were used for LFQ (n = 21), except collision energy, which was set 30%.Multiplexed TMT-labeled samples (6/10-plex) were analyzed as biological replicates using an Orbitrap Fusion Tribrid mass spectrometer interfaced with an Easy-nLC 1200 system (Thermo Fisher Scientific). The mobile phase consisted of milli-Q water with 0.1% formic acid as solvent A and 0.1% formic acid/80% acetonitrile as solvent B. Each fraction was reconstituted in 15 µl of solvent A and 1 µg of digested peptides were loaded on to a pre-analytical column . Isocratic gradient of 10–35% B in 103 min, 35–95% B in 2 min and holds at 95% B for 15 min at 300 nl/min flow rate were used on an analytical column . A single Orbitrap MS scan from 375 to 1700Homo sapiens fasta  from Uniprot database . All searches were configured with dynamic modifications for the TMT reagents (+229.163 Da) on lysine and N-termini, oxidation of methionine residues (+15.9949 Da) and static modification as carbamidomethyl (+57.021 Da) on cysteines, monoisotopic masses, and trypsin cleavage (max 2 missed cleavages). The peptide precursor mass tolerance was 10 ppm, and MS/MS tolerance was 0.05 Da. The false discovery rate (FDR) for proteins and peptides was kept 1%71. TMT signals were corrected for isotope impurities based on the manufacturer’s instructions.TMT 6-plex- and TMT 10-plex-based quantitative proteomic analysis were carried out using individual samples of malaria and dengue patients. Raw instrument files were processed using Proteome Discoverer (PD) version 2.2 (Thermo Fisher Scientific). In each TMT experiment, .raw files for all fractions were merged and MS2 spectra were searched using the Sequest HT and Mascot (v2.6.0) search engine against Plasmodium falciparum 3D7 (Plasmo TaxID=36329_and_subtaxonomies) (v2017-08-25). The parasite data were downloaded from PlasmoDB (https://plasmodb.org/plasmo/) on 28/06/2018. The search parameters were kept the same as above mentioned for the TMT 6-plex method except for dynamic modifications for the TMT reagents (+229.163 Da) on lysine and N-termini of the peptide.In LFQ, the .raw files from the label-free method were searched against the database of 73, where run-to-run normalization using a reference pool and quantile normalization were performed. Sixty-six proteins were selected based on adjusted p value (p < 0.05) in malaria and p value (p < 0.05) in DF  by driving coefficients of unimportant covariates to zero and (ii) l2 norm helps address the issue of multicollinearity82. k-fold nested cross-validation  was used as it provides robust and almost unbiased parameter estimates and model performance evaluation even for small sample sizes84.The elastic net regularized logistic regression method was used to classify: (1) dengue vs. malaria: HC vs. Dengue, HC vs. malaria, dengue vs. malaria; (2) type of malaria: HC vs. FM, HC vs. VM, FM vs. VM; (3) severity of FM: HC vs. NSFM, HC vs. SFM, NSFM vs. SFM; (4) severity of VM: HC vs. NSVM, HC vs. SVM, NSVM vs. SVM; (5) severity of dengue: HC vs. NSD, HC vs. SD, NSD vs. SD. Of note, the elastic net regularized logistic regression model offers more flexibility in two ways—(i) the lk-fold inner cross-validation loop for hyperparameter tuning and model selection and (ii) k-fold outer cross-validation loop for evaluating the model selected by the inner cross-validation. The entire dataset was randomly split into k-folds, out of which the kth fold was used as a test set and the remaining k−1 folds were used for training purpose. For each split, a model was trained and validated on the training set using (inner) k-fold cross-validation and tested on the held-out test set. The hyperparameters alpha and lambda were tuned by inner k-fold cross-validation over a grid of values ranging from 0 to 1 with a step-size of 0.1 for alpha and another grid of 100 values ranging from 10−2 to 102 for lambda, respectively. To evaluate model performance, ROC–AUC, balanced accuracy, F1-score, and Kappa metrics were computed. These metrics were chosen because we had imbalanced classes. The average variable importance of a protein was measured as the weighted average of variable importance of that protein in all k predictive models in the outer k-fold cross-validation with weights being the balanced accuracy of each model. This implicates that the importance of a protein in the classification of samples is directly proportional to its occurrence in the predictive models, which can classify the samples better. A schematic diagram of the method used here is shown in Figs. The nested cross-validation approach involves using—(i) For validation of the selected proteins as good classifiers for dengue vs. malaria, FM vs. VM, and CB vs. SA models, we created (i) heat map and (ii) three-dimensional PLS-DA plot Fig. . To arriThe elastic net regularized logistic regression model equations for the final biomarker models identified from MRM were as follows:dengue vs. malaria:Falciparum vs. vivax malaria:pPositive Class is the probablility of event that Y=Postitive Class. For these three models, the hyperparameters  and model performance evaluation metrics  were as follows: (i) dengue vs. malaria: 0.22, 0.02, 0.72, 0.89, 0.46, 0.807 (0.666–0.947); (ii) FM vs. VM: 0.25, 4.47, 0.8, 0.77, 0.6, 0.865 (0.772–0.958); and (iii) CB vs. SA: 0.02, 41.10, 0.8, 0.83, 0.56, 0.944 (0.816–1), respectively. These models serve two purposes, and they are as follows:Cerebral vs. severe malaria anemia:They help assess the impact of a particular protein on the estimated log odds or the estimated odds of an individual, for example, being a dengue patient as opposed to being a malaria patient.For illustration sake, let us consider the model Eq. . Note thThis can be interpreted by observing that the estimated odds of an individual being a dengue patient as opposed to s(he) being a malaria patient increase multiplicatively (decrease multiplicatively) by 9.2999 (0.176) for every unit increase in the value of the protein LRG1 (CP).Note that the equation involving the estimated odds The other two logistic regression models corresponding to falciparum vs. vivax malaria or cerebral vs. severe malaria anemia could be interpreted analogously.85, and Reactome pathway Knowledgebase, version 62 (www.reactome.org)86. A multi-functional online software NetworkAnalyst  was applied for constructing and visualizing the PPI networks. The batch selection option of NetworkAnalyst was used to narrow down the network nodes, and the clusters were specified by highlighting with different colors.In order to investigate the complex interactions among the candidate marker proteins and for prediction of the pathways associated with the differentially altered proteins identified in FM, VM, and DF patients, diverse bioinformatic analyses were carried out. The pathway enrichment was performed using Protein Analysis THrough Evolutionary Relationships (PANTHER) classification system, version 12.0 (www. pantherdb.org)n = 17) of each heavy synthetic peptide was spiked into 10 µg of the digested samples, with 142 peptides having 901 transitions over a 20-min chromatographic gradient with a scheduling method. The total 40 methods were used to accommodate all the transitions (approx. 176 transition/method) for host and parasite proteins. During the first phase of optimization, six proteins were not detected and hence removed those from the list. The refinement of the transitions performed by running different plasma pool samples and some individual samples on different days to check the inter-day variation and stability of the peptides  equipped with an Easy-Spray electrospray ionization ion source (Thermo Fisher Scientific). Peptides separations were performed using a C18 column . The mobile phase consists of Milli-Q water with 0.1% formic acid as solvent A and 0.1% formic acid/80% acetonitrile as solvent B. Following chromatographic conditions were used: 20-min gradient at a flow rate of 300 nl/min starting with 100% A (water), stepping up to 2% B (ACN) in 0 min, followed by 45% B at 16 min, followed by a steep increase to 95% B at 17 min and static for 1 min at 95%. The steep decrease to equilibrate the column 5% of B at 19 and then static for another 1 min at 5% of B. The suitability of the system was evaluated using iRT peptide and digested BSA , 90 fractions; VM: n = 4 experimental sets (TMT 10-plex), 25 fractions, and DF: n = 4 experimental sets (TMT 6-plex), 24 fractions). The protein-level summarization and significance analysis of the proteins was performed in R using the MSstatsTMT package73. In brief, The PSMs were preprocessed in PD and were converted into the required input format for MSstatsTMT using an in-house R-code. The protein abundance was calculated based on the peptide quantification using the “protein summarization” script (MSstatsTMT). It includes normalization between the MS runs using reference pool channels and the imputation of missing values before summarizing peptide level data into protein-level data. In the protein summarization method, MSstats assumes missing values are censored and then imputes the missing values using the accelerated failure model. Missing value imputation was performed for only of those proteins, which were quantified in ≥60% of the samples. Then, a moderated t-test was performed on quantile normalized values using “Group-Comparison-TMT” script in R and p value <0.05 were considered as statistically significant73. Proteins passing p value <0.05 threshold of moderated t-test was used for data visualization and pathway analysis. However, adjusted p value Benjamini–Hochberg (BH) was also calculated for multiple comparisons using the MSstatsTMT package in R. BH-corrected p value [p value (adjusted) <0.05] was considered in the selection of proteins for machine learning analysis (except for dengue).The proteins that were quantified with ≥1 unique peptide and detected in at least 60% of the samples were selected for the subsequent differential analysis. The PSMs values were exported from Proteome Discoverer 2.2 (PD) for combined analysis for FM, VM, and DF (FM: Further information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4Supplementary Data 5Supplementary Data 6Supplementary Data 7Reporting Summary


ATP2B4, and several variants related to the immune response. Characterising how these genes confer their effects could eventually inform novel therapeutic approaches to combat malaria. Nevertheless, all together, only a small proportion of the heritable component of malaria resistance can be explained by the variants described so far, underscoring its complex genetic architecture and the need for continued research.Malaria has been the pre-eminent cause of early mortality in many parts of the world throughout much of the last five thousand years and, as a result, it is the strongest force for selective pressure on the human genome yet described. Around one third of the variability in the risk of severe and complicated malaria is now explained by additive host genetic effects. Many individual variants have been identified that are associated with malaria protection, but the most important all relate to the structure or function of red blood cells. They include the classical polymorphisms that cause sickle cell trait, α-thalassaemia, G6PD deficiency, and the major red cell blood group variants. More recently however, with improving technology and experimental design, others have been identified that include the Dantu blood group variant, polymorphisms in the red cell membrane protein  Malaria has been the biggest cause of childhood mortality globally for much of the last 5000 years. Although now coming under some degree of control, mortality remains high in many countries and worldwide there were an estimated 405,000 deaths from malaria in 2018 alone, with more than 90% of these deaths occurring in sub-Saharan Africa WHO . HistoriPlasmodium parasites: P. falciparum, P. vivax, P. malariae, P. ovale and P. knowlesi. P. falciparum and P. vivax are the most prevalent and result in the majority of deaths . It took many years for the veracity of these hypotheses to be established beyond reasonable doubt, but it is now clear that the HbS variant confers the strongest protective effect against severe malaria that has yet been described, with an effect size of  > 80% in heterozygous carriers , while α-thalassaemia confers a protective effect of approximately 40% in homozygotes  , which is expressed on red blood cell membranes and has roles as both a chemokine receptor  in malaria endemic populations have confirmed many of the classical malaria associated genes  domains of a range of P. falciparum merozoite proteins . This discovery led to further functional studies that identified the P. vivax Duffy-binding protein (PvDBP) that is crucial for RBC invasion  and as such it offers a potential alternative vaccine target.Beyond identifying malaria-protective gene variants, investigations into the mechanisms through which these variants confer their protective effects are critical to informing novel approaches to intervention. Functional studies have led to the elucidation of key steps in the molecular processes involved in parasite invasion of host RBCs, with the seminal example of the P. falciparum, HbAS, several mechanisms of protection have been proposed, including sickling of the infected RBCs , was impaired in HbAS RBCs (Cyrklaff et al. P. falciparum growth inhibition (Archer et al. In the case of the most strongly protective variant against ATP2B4 locus in detail using transcriptomics, epigenomics, and gene-editing, and found that the ATP2B4 GWAS SNPs mapped to enhancer elements that regulated ATP2B4 gene expression and subsequent intracellular calcium homeostasis (Lessard et al. ATP2B4 SNPs in the recent GWAS carried out by the Malaria Genomic Epidemiology Network also found that these SNPs regulate ATP2B4 gene expression by disrupting the promoter upstream of the gene’s transcription start site (MalariaGEN GYPB-A hybrid genes whose encoded protein contains the extracellular domain of glycophorin B and the transmembrane and intracellular domains of glycophorin A (Leffler et al. Technological advances have further aided the functional validation efforts for newly identified malaria-protective variants. Lessard et al. investigated the Malaria is the first, and arguably still remains the best, example of the impact that infectious diseases can have on the human genome. While numerous genes have now been identified that are strongly associated with the risk of different forms of malaria, it is those relating to the structure or function of RBCs for which the data are most compelling. This is entirely consistent with the fact that for all but a brief period during the incubation phase, the biological success of malaria parasites in humans is entirely dependent on their ability to invade, grow, and survive within RBCs. While some, including HbAS, the thalassaemias and G6PD deficiency, have been selected to extreme frequencies because of their malaria-protective effects, in many cases the mechanisms are either too poorly understood or too complex to suggest plausible approaches to the development of new treatments (Lelliott et al.


Plasmodium falciparum malaria in further detail by investigating the burden and severity of malaria infections among children recruited with severe anaemia to the TRACT trial of blood transfusion in Africa.Sickle cell anaemia (SCA) has historically been associated with high levels of childhood mortality in Africa. Although malaria has a major contribution to this mortality, to date, the clinical pathology of malaria among children with SCA has been poorly described. We aimed to explore the relationship between SCA and HBB following batch-genotyping by PCR at the end of the trial. To avoid confounding from SCA-specific medical interventions, we considered children with an existing diagnosis of SCA (known SCA) separately from those diagnosed at the end of the trial (unknown SCA). The outcomes considered in this secondary analysis were measures of P falciparum parasite burden, features of severe malaria, and mortality at day 28 in malaria-positive children.This study is a post-hoc secondary analysis of the TRACT trial data, conducted after trial completion. TRACT was an open-label, multicentre, factorial, randomised controlled trial enrolling children aged 2 months to 12 years who presented with severe anaemia (haemoglobin <6·0 g/dL) to four hospitals in Africa. This secondary analysis is restricted to Uganda, where the birth prevalence of SCA is approximately 1% and malaria transmission is high. Children were classified as normal (HbAA), heterozygous (HbAS), or homozygous  for the rs334 A→T sickle mutation in P falciparum malaria, whereas the prevalence was significantly lower in children with SCA . Concentrations of plasma P falciparum histidine-rich protein 2 (PfHRP2), a marker of the total burden of malaria parasites within an individual, were significantly lower in children with either known SCA  or unknown SCA  than in HbAA children . In contrast to HbAA children, few HbSS children presented with classic features of severe and complicated malaria, but both the frequency and severity of anaemia were higher in HbSS children. We found no evidence for increased mortality at day 28 in those with SCA compared with those without SCA overall (hazard ratios 1·07 [95% CI 0·31–3·76] for known SCA and 0·67 [0·15–2·90] for unknown SCA).Between Sept 17, 2014, and May 15, 2017, 3944 children with severe anaemia were enrolled into the TRACT trial. 3483 children from Uganda were considered in this secondary analysis. Overall, 1038 (30%) of 3483 Ugandan children had SCA. 1815 (78%) of 2321 children without SCA (HbAA) tested positive for The current study suggests that children with SCA are innately protected against classic severe malaria. However, it also shows that even low-level infections can precipitate severe anaemic crises that would likely prove fatal without rapid access to blood transfusion services.UK Medical Research Council, Wellcome, and UK National Institute for Health and Care Research. HBB, is the classic example of a balanced polymorphism, where current allele frequencies reflect a survival advantage in carriers and increased mortality in homozygotes.Plasmodium falciparum malaria in the positive selection of heterozygotes (HbAS)Sickle cell anaemia (SCA) is the commonest life-threatening genetic disorder worldwide. The causal mutation, the rs334 A→T single-nucleotide polymorphism in P falciparum parasitaemia.P falciparum histidine-rich protein 2 (PfHRP2),17It is often stated that severe malaria is a major reason for the high mortality seen in children with SCA in Africa.Evidence before this studyPlasmodium falciparum malaria has exerted opposite selective forces on children with sickle cell trait (HbAS) and SCA (HbSS). Although the evidence for a malaria-protective effect of HbAS is now overwhelming, recent epidemiological studies have raised questions about the negative effects of malaria on children with SCA.We searched PubMed for articles on the relationship between sickle cell anaemia (SCA) and malaria using the search terms (“sickle cell disease” OR “sickle cell anaemia” OR “sickle cell anemia”) AND “malaria”. The search was done on June 16, 2022, without date or language constraints. Our search revealed 865 articles in total, of which 671 included original research. Most studies included very small numbers of children with both SCA and malaria and less than ten were relevant to the question at hand. It is widely believed that Added value of this studyP falciparum histidine-rich protein 2 (PfHRP2), an assay that captures the total body load of P falciparum parasites in patients with malaria. Recent studies have shown that such measurements can be useful in distinguishing children hospitalised with true severe malaria from children with severe febrile illnesses of alternative cause that are accompanied by incidental parasitaemia.To our knowledge, the current study, which included 347 children presenting with both SCA and malaria to three hospitals in Uganda, is the most comprehensive study yet conducted on this subject. Unlike most previous studies, the current study includes the measurement of plasma concentrations of Implications of all the available evidenceIn conjunction with the findings from previous epidemiological studies, the current study provides strong evidence in support of a malaria-protective effect of SCA at a level similar to that afforded by HbAS. Nevertheless, the study also shows that this protection is incomplete, and that even low-grade malaria infections can precipitate severe anaemic crises in children with SCA that, in the absence of blood transfusion, would almost certainly be rapidly fatal. Overall, the study supports the need for early diagnosis and proactive interventions for preventing malaria in children with SCA.In the current study, we conducted a secondary analysis of data from the Transfusion and Treatment of severe anaemia in African Children Trial  to four hospitals in Africa. Full details of the trial have been published previously.Eligibility for the complicated anaemia stratum required the presence of one or more of the following features of clinical severity: profound anaemia (haemoglobin <4·0 g/dL), impaired consciousness, increased work of breathing, blackwater fever, or known SCA. Children recruited to this stratum were randomly assigned to receive either 20 mL/kg or 30 mL/kg of whole blood, or the equivalent volumes (10 mL/kg or 15 mL/kg) of packed red blood cells. Children were eligible for recruitment to the uncomplicated anaemia stratum if their haemoglobin concentration was between 4·0 g/dL and 6·0 g/dL and they had none of the aforementioned severity features. In this stratum, children were randomly assigned to receive either no immediate transfusion or immediate transfusion of 20 mL/kg or 30 mL/kg of whole blood or the equivalent volumes (10 mL/kg or 15 mL/kg) of packed cells. Children with known SCA were ineligible for recruitment to this stratum because the investigators lacked equipoise regarding the ethics of withholding transfusions from children with known SCA and a haemoglobin concentration of less than 6·0 g/dL. All children were followed up until day 28 for the primary endpoint, mortality, and to day 180 for a range of additional events that included readmission and death.Written informed consent for the trial was sought from all parents or guardians, but where not logistically possible, ethics committees approved verbal assent with delayed consent as soon as practicable.HBB mutation by PCR,0-thalassaemia because neither have been found in previous studies conducted in the same population.28Full details of the management and conduct of the trial have been published previously.P falciparum parasite burden, features of severe malaria, and mortality at day 28 in malaria-positive children. Measures of P falciparum parasite burden were parasite density and plasma PfHRP2 concentration. 11 features of severe malaria were considered, including profound anaemia (haemoglobin <4·0 g/dL), hyperparasitaemia , and plasma PfHRP2 concentration of more than 1000 ng/mL.The outcomes considered in this secondary analysis were measures of We classified children as either: (1) normal (HbAA), (2) heterozygous , or (3) homozygous  for the rs334 A→T mutation. The homozygous group were further classified into those with an existing diagnosis (known SCA) and those whose diagnosis was only revealed by genotyping at the end of the trial (unknown SCA). Because patients with known SCA were excluded from one arm of the trial, and because they are often managed differently in terms of their clinical care , we analysed data on known and unknown SCA groups separately to avoid potential problems with interpretation. We compared baseline characteristics in malaria-positive trial participants by SCA group using Mann-Whitney U tests or Fisher's exact tests for continuous and categorical factors, respectively, and used histograms to examine the distributions. PfHRP2 was also categorised as less than 1000 ng/mL or more than  1000 ng/mL, a value that has been used to distinguish children with true severe malaria from those with severe illnesses in the presence of incidental parasitaemia in other studies.The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report.The recruitment profile for the TRACT trial is summarised in 2 p<0·0001) and lower still in those with either known SCA  or unknown SCA  of the 3483 Ugandan participants tested positive for malaria at recruitment by either RDT or microscopy. Of these children, 1036 (47%) tested positive by both RDT and microscopy, 1136 (52%) were positive by RDT but negative by microscopy, suggestive of recovery from a recent malaria infection, and a small number (26 [1%]) fell into other categories . When stvs 4·5 [3·6–5·4] in HbAA; ranksum p=0·010) or unknown SCA . In keeping with the haematology of SCA,The clinical and laboratory characteristics of malaria-positive trial participants, stratified by SCA group, are summarised in The features of malaria severity, stratified by SCA group, are summarised in By design, most of the children presenting with clinical signs of severe malaria were recruited to the complicated stratum of the trial . Within The mortality to day 28 among the malaria-positive children, stratified by SCA category, is summarised in P falciparum malaria, and both total parasite burden and levels of inflammation, a correlate of clinical severity,5Among 3483 children presenting with all-cause severe anaemia who were enrolled at the point of hospital admission into the TRACT trial in Uganda, 30% had SCA overall. In comparison to HbAA children, a significantly lower proportion of those with SCA tested positive for P falciparum parasites that are sequestered in the cerebral vasculatureP falciparum-infected SCA red blood cells to sequester in the microvasculature. A previous study found that the red cell surface molecule P falciparum erythrocyte membrane protein-1 (PfEMP1) was underexpressed on malaria-infected HbSS red cells and that this led to reduced cytoadherence.Given that steady state haemoglobin concentrations in children with SCA in Africa average only 6·0–8·0 g/dL,P falciparum parasites in children with SCA through the measurement of plasma PfHRP2 concentrations. One previous study involved children hospitalised with severe anaemia and malaria in Kampala, Uganda. The authors found that plasma PfHRP2 concentrations were significantly lower among 22 children who tested positive for SCA  than they were in 205 children with HbAA .pfhrp2 deletionspfhrp2 deletions. Furthermore, such RDTs primarily detect PfHRP2 in malaria-infected red blood cells, in which concentrations are approximately 20 times higher than they are in plasma, where they are mainly determined by the release of PfHRP2 at schizogony during the previous erythrocytic cycle.pfhrp2 deletions is still relatively low in most of sub-Saharan Africa, where they are generally found in children with asymptomatic infections,pfhrp2 or pfhrp2/3 deletions were found in almost 7% of parasites in one recent study, conducted in Uganda during the same era as TRACT.To the best of our knowledge, ours is the second study to have assessed the burden of Although our study is consistent with the conclusion that children with SCA are innately protected from high-density malaria infections, this does not mean that in such children malaria cannot be a significant clinical problem. First, highlighting the major vulnerability of children with SCA to severe anaemia, almost 20% of all the children recruited to TRACT in Uganda who had no previous knowledge of their SCA status were subsequently found to have SCA. This is despite the fact that SCA affects less than 1% of children in the same population overall.Some limitations to our analysis of the association of SCA and 28-day mortality are acknowledged. First, there is always some uncertainty in the causal interpretation of hazards ratios.P falciparum infections can trigger sudden and catastrophic falls in haemoglobin that can rapidly result in death where emergency supplies of blood for transfusion are not available.In conclusion, data from the current and other recent studiesmrcctu.ctuenquiries@ucl.ac.uk.The TRACT trial data are held at the MRC Clinical Trials Unit at University College London , which encourages optimal use of data by employing a controlled access approach to data sharing, incorporating a transparent and robust system to review requests, and providing secure data access consistent with the relevant ethics committee approvals. All requests for data are considered and can be initiated by contacting We declare no competing interests.


Malaria remains a major public health problem in Indonesian Papua, with children under five years of age being the most affected group. Haematological changes, such as cytopenia that occur during malaria infection have been suggested as potential predictors and can aid in the diagnosis of malaria. This study aimed to assess the haematological alterations associated with malaria infection in children presenting with signs and symptoms of malaria.A retrospective study was performed by collecting data from the medical records of malaria patients at Sorong Regional General Hospital, Sorong, West Papua, Indonesia, both from outpatient and inpatient clinics, from January 2014 until December 2017. The laboratory profile of children suffering from malaria was evaluated.Plasmodium falciparum. Half of the enrolled subjects (50%) had haemoglobin level (Hb) between 5.1 and 10 gr/dL. A total of 41 children (53.2%) less than 5 years old suffered from P. falciparum infection. In the age group of 5–10 years, there were 34 children (57.6%) who suffered from P. falciparum, and in the age group > 10 years, 27 children (58.7%) suffered from P. falciparum infection. Only 4 subjects (5.2%) in the less than 5 years old age group had mixed malaria infection. Among eight predictors of the haematological profile, there were five predictors that were significantly associated with the diagnostic criteria, namely haemoglobin, haematocrit, leukocytes, platelets and monocytes (p < 0.05). Generally, clinical symptoms are not significantly associated with a malaria diagnosis, and only one variable showed a significant relationship, pale, with a P value of 0.001.One hundred and eighty-two children aged 1 month to 18 years old were enrolled. The subjects were mostly male  with a mean age of 6.45 years (SD = 4.3 years). Children below 5 years of age suffered the most from malaria in this study . One hundred two subjects (56%) were infected with Children with malaria had changes in some haematological markers, with anaemia, low platelet count, white blood count, and lymphocyte count being the most important predictors of malaria infection in the study area. These markers could be used to raise suspicion of malaria in children living in high endemic areas, such as West Papua. Anopheles mosquitoes [Plasmodium species infecting humans: Plasmodium falciparum, Plasmodium vivax, Plasmodium malariae Plasmodium ovale curtisi, Plasmodium ovale wallikeri and Plasmodium knowlesi [Plasmodium falciparum and P. vivax are the two main causes of human malaria infections. Falciparum malaria poses a risk of severe complications and contributes to the majority of deaths [Malaria is a life-threatening protozoan disease caused by parasites that are transmitted to humans through the bite of infected female squitoes . The Worsquitoes . There aknowlesi . Plasmodf deaths .In Southeast Asia, Indonesia contributes 9 % of all malaria cases and has the second highest burden of disease after India . The WHO2 covering the bird’s head area of Papua island and the surrounding islands [2 with population density about 365 persons per square kilometre consisting of 30 districts and 26 sub-districts. The population in Sorong city is about 239,815 people in 2017 with the number of villages in about 226 villages and 11 community health centres [West Papua is an Indonesian province located on the western tip of Papua Island, which capital city is Manokwari. The area of the province is about 99671,63 kmBased on the Ministry of Health of the Republic of Indonesia, Annual Parasite Index (API) for West Papua in 2017 was 15‰ and classified by WHO as hyper-endemic area. Specifically API for Sorong city was 1.5‰ and classified by WHO as meso-endemic area. The number of confirmed malaria cases microscopically in 2017 was 13,690 cases and for the city of Sorong was 127 cases .P. falciparum infection, probably as a result of the higher levels of parasitaemia found in these patients [Haematological alterations that are thought to characterize malaria are related to the overt biochemical changes that occur during the asexual stage of the life cycle of the malaria parasite . Patientpatients , 22. Thrpatients , 23, 24.patients . Pancytopatients , 13 thatpatients , 26. It patients , 28. Whepatients , 30.The prediction of haematologic changes in malaria allows clinicians to establish early and effective therapeutic interventions to prevent major complications, especially in nonendemic countries with declining malaria transmission and nonendemic countries . HaematoThe gold standard for malaria examination is microscopic slide examination . KnowledA retrospective study of data from medical records of malaria patients at Sorong Regional General Hospital, Sorong, West Papua, Indonesia Outpatient and Inpatient Clinic from January 2014 until December 2017 was performed. It included 182 children from 1 month to 18 years old with signs and symptoms of malaria at Sorong Regional General Hospital, Sorong, West Papua, Indonesia. Blood samples were collected from children into ethylenediaminetetraacetic acid (EDTA) tubes and used to prepare thin and thick blood films, which were then used for Giemsa microscopy to detect malaria parasites and malaria species. Patients’ haematological predictors were determined using an automated haematology analyzer.The study involved children aged 1 month to 18 years, who were malaria-confirmed by microscopy. Individual data was obtained from medical records. The study included children who were treated as inpatients or outpatients at Sorong Regional General Hospital, Sorong, West Papua, Indonesia from January 2014 until December 2017. The study was approved by the Research Ethics Committee of the Medical School of the Universitas of Sumatera Utara.Children in age group 1 month to 18 years.Any acute febrile illness lasting for 2–7 days.P. vivax and/or P. falciparum malaria.Peripheral blood smear or rapid malaria antigen test positive for Complete medical record data..No malaria found from either rapid diagnostic test (RDT) or microscopic examination..Two to three millilitres of venous blood were collected from each participant using a 5 ml sterile disposable syringe and dispensed into an EDTA anticoagulated test tube, followed by preparation of the thick and thin smears and automated for determination of the complete blood count (CBC). The EDTA test tubes containing the blood samples were gently inverted approximately 8 times to ensure the complete mixture of blood cells. The blood samples were collected by a trained medical laboratory scientist. Blood counts were performed using Sysmex XP 100 Haematology Analyzer.Peripheral blood smears were prepared using venous blood samples. Separate slides were used for thick and thin smears. Examination of thin and thick blood films were based on WHO 2010 guidelines . Thick aDefinition of anaemia was based on WHO guidelines with different cut off for different agegroup and categorized by different severity  .9/L [Lymphocytopenia in chidren is defined as a total lymphocyte count less than 3.0 × 109/L .3/µl [Leukopenia was defined as white blood cells (WBCs) < 4 × 103/µl .3/µl [Monocytosis was defined as an absolute monocyte count > 3 × 103/µl .3/µl [Thrombocytopenia was defined as platelet count < 150 × 103/µl .Categorization of malaria into uncomplicated and severe forms .Severe malaria (SM) was defined by the presence of asexual parasitaemia in addition to at least one or more of the following WHO , 40. TheUncomplicated malaria (UM) was defined as the presence of symptoms and/or signs of malaria and a positive parasitologic test in the absence of evidence of end organ damage .The data are presented as the means, percentages, standard deviations, medians, and ranges. Statistical analysis was performed using ANOVA, the Kruskal-Wallis test, contingency coefficient correlation, the Mann-Whitney U test, and the independent t-test. The data were analysed using SPSS version 21 statistical software with appropriate statistical methods. Differences with P-values of less than 0.05 were considered significant.P. falciparum. Some subjects (50%) had a Hb level between 5.1 and 10 gr/dL. The results of the haematological profile examination of the subjects are presented in Table This study included 182 subjects who met the inclusion and exclusion criteria. The subjects were mostly male  with a mean age of 6.45 years (SD = 4.3 years). Children < 5 years accounted for the majority of the cases, . A total of 102 subjects (56%) were infected with P. falciparum infection (53.2%). Only four subjects (5.2%) less than five years old had mixed infections , the Eastern Mediterranean (69%) and the Western Pacific (71.9%). Plasmodium vivax is the predominant parasite in the WHO region of the Americas (74.1%) [Plasmodium vivax contributed 4% of the total global cases in 2015, but outside Africa the proportion was 41% among all malaria infections. Its high burden of disease is maintained in part due to dormant liver stage parasite forms known as hypnozoites which can induce clinical relapse episodes [ (74.1%) . Plasmodepisodes .P. falciparum. This study also shows that the most common type of Plasmodium infection in Sorong, West Papua, is P. falciparum. This is similar with other provinces in Indonesia and in Manokwari, West Papua, P. falciparum is the predominant malaria species [In the present study, there were more male patients infected with malaria than female patients, which is similar to the results of a study in South Sorong . One hun species , 48.About 42.3% of malaria cases in our study was among children < 5 year old. According to WHO data in 2017, they are the most vulnerable group affected by malaria. They accounted for 61%  of all malaria deaths worldwide [Cytopenia is a disorder in which the production of one or more blood cell types ceases or is greatly reduced. The types of cytopenia are anaemia, which is a reduction in red blood cells (RBCs); leukopenia, which is a reduction in WBCs; neutropenia , which is a deficiency in neutrophils; and thrombocytopenia, which is deficiency in platelets. Bicytopenia is defined as a condition in which two out of three cell lines  are reduced. The simultaneous reduction in all three formed cell lines is termed pancytopenia . These kP. vivax and in children with P. knowlesi infection [Anaemia is also a common manifestation, particularly in infants with nfection –54. Anaenfection , 56.The pathogenesis of anaemia during malaria infection is not clearly understood. However, it is estimated that the main targets of parasites are RBCs, which results in damage to RBCs, acceleration of parasite growth and nonparasitic removal , bone maThis study showed that haematological abnormalities in children with malaria infection are common. Some subjects (50%) had a Hb level between 5.1 and 10 gr/dL. The prevalence of anaemia in This study was 77.4%; 14.8% of subjects had mild anaemia, 35.7% had moderate anaemia, and 26.9% had severe anaemia. The rate of anaemia in children < 5 years old was higher than that in children 5–10 years old and > 10 years old, with a mean Hb of 8.71 gr/dL. Data from household surveys conducted in 25 high-burden African countries between 2015 and 2019 show that, among children < 5 years who tested positive for malaria, the prevalence of moderate to severe anaemia was between 9–76.3% , 64. OurP. falciparum [P. falciparum-infected erythrocytes, leading to pseudothrombocytopenia [There are various hypotheses about thrombocytopenia that occurs in malaria infections. Thrombocytopenia seems to occur through peripheral damage , excessilciparum . This calciparum . Previoulciparum . In addilciparum . Howeverytopenia , 63, 69.3/µL in this study.Thrombocytopenia was seen in 97 children (53.3%) and was highly significant in the age group > 10 years, with a median 105 × 10P. falciparum infection, as many as 65 (35.7%). Thrombocytopenia was observed in malaria-infected children in this study, which is consistent with earlier reports [Plasmodium infection [It is found mostly in  reports , 63. Thenfection , 71–73.P. falciparum infection was lower than P. vivax infection as well as the platelet value  [3/µL vs. 98.1763 ± 0.99502 × 103/µL [In the present study overall, when compared between malaria species in uncomplicated cases, Hb and platelet value in the ue Table  with p vctively) . A study× 103/µL .P. vivax-associated anaemia and thrombocytopenia. Ullah et al. showed something different where P. falciparum-associated anaemia (9.9 ± 4.48 g/dL vs. 10.7 ± 2.36 g/dL) and P. vivax-associated thrombocytopenia (135.8 ± 89.4 × 103/µL vs. 222 ± 118.7 × 103/µL) [On the contrary, studies, such as Goyal et al. , Nadwani 103/µL) .P. falciparum can be severe and life-threatening, whereas P. vivax tends to be mild [P. vivax can cause significant morbidity and even mortality in endemic areas [P. vivax parasite resistant to chloroquine in recent years is one of the main triggers of the new severe vivax malaria [In the recent years, there have been reported many severe vivax malaria cases , 76, 79. be mild . Howeveric areas . Malariaic areas –86. Anot malaria . All the malaria –85.P. vivax infection associated with severe and fatal malaria particularly in young children in Timika, Papua [Price et al. found that a, Papua . OtherwiThis study has shown, however, that there was no significant difference in total white blood cell count in malaria-infected children. Leukopenia was seen in only 17% of children. A study by Maina et al. also showed that there was no significant difference in the total white blood cell count in malaria-infected children compared to control subjects . The difP. falciparum (5.55 × 103/µL) was lower than in P. vivax infection (7.2 × 103/µL). Similar outcome was also reported in a study conducted by Latif et al. showing leukocyte in P. falciparum  compared to P. vivax infection  was lower [P. vivax (8.7 ± 4.5 × 103/µL) was lower than in P. falciparum infection (10.4 ± 11.4 × 103/µL) [Leukocyte value in as lower . This wa 103/µL) .This study showed lymphocytopenia in 97 children (53.3%). The study has further revealed that there were no statistically significant differences in granulocyte and lymphocyte counts between malaria-infected and noninfected children, and these findings are in agreement with many earlier reports , 86–88 bGenerally, clinical symptoms are not significantly associated with a malaria diagnosis, and only one variable shows a significant relationship, pale, with a p value of 0.001 Table . The firConversely, in children, these manifestations of uncomplicated malaria can be misinterpreted and attributed to other prevalent infections, such as pneumonia, gastroenteritis, and sepsis. In highThere are several limitations in this study. First, this was a retrospective study. Some data of the haematological and microscopic results retrieved from medical records were not provided. Second, there was no control group in this study, therefore association between haematological markers in malaria and non-malaria infected groups could not be stated.Children infected with malaria revealed changes in some haematological markers, with anaemia, low platelet counts, white blood counts, and lymphocyte counts being the most important predictors of malaria infection in our study area. Children living in malaria high endemic areas such as West Papua who appear with acute febrile illness and either thrombocytopenia alone or in combination with anaemia should be suspected for malaria, therefore, RDT or microscopic examination must be performed. These haematological markers could raise the suspicion of malaria in this area.


Manual microscopic examination of Leishman/Giemsa stained thin and thick blood smear is still the “gold standard” for malaria diagnosis. One of the drawbacks of this method is that its accuracy, consistency, and diagnosis speed depend on microscopists’ diagnostic and technical skills. It is difficult to get highly skilled microscopists in remote areas of developing countries. To alleviate this problem, in this paper, we propose to investigate state-of-the-art one-stage and two-stage object detection algorithms for automated malaria parasite screening from microscopic image of thick blood slides.YOLOV3 and YOLOV4 models, which are state-of-the-art object detectors in accuracy and speed, are not optimized for detecting small objects such as malaria parasites in microscopic images. We modify these models by increasing feature scale and adding more detection layers to enhance their capability of detecting small objects without notably decreasing detection speed. We propose one modified YOLOV4 model, called YOLOV4-MOD and two modified models of YOLOV3, which are called YOLOV3-MOD1 and YOLOV3-MOD2. Besides, new anchor box sizes are generated using K-means clustering algorithm to exploit the potential of these models in small object detection. The performance of the modified YOLOV3 and YOLOV4 models were evaluated on a publicly available malaria dataset. These models have achieved state-of-the-art accuracy by exceeding performance of their original versions, Faster R-CNN, and SSD in terms of mean average precision (mAP), recall, precision, F1 score, and average IOU. YOLOV4-MOD has achieved the best detection accuracy among all the other models with a mAP of 96.32%. YOLOV3-MOD2 and YOLOV3-MOD1 have achieved mAP of 96.14% and 95.46%, respectively.The experimental results of this study demonstrate that performance of modified YOLOV3 and YOLOV4 models are highly promising for detecting malaria parasites from images captured by a smartphone camera over the microscope eyepiece. The proposed system is suitable for deployment in low-resource setting areas.The online version supplementary material available at 10.1186/s12859-021-04036-4. P. falciparum, P. vivax, P. ovale, P. malariae, and P. knowlesi), of which P. falciparum is the most common, followed by P. vivax. Depending on the severity of infection, all the species pass through four life stages: ring, trophozoite, schizont, and gametocyte  since the default anchor box sizes are much bigger than the size of malaria parasite in microscopic images. We fine-tuned a pre-trained Faster R-CNN model using our malaria dataset with an initial learning rate of 0.001, which is reduced by 0.1 factor at training iterations of 65,000 and 85,000 and optimized using momentum SGD. We trained Faster R-CNN model for a total of 100K iterations. For SSD model, we have used a modified minimum scale of 0.1 and a maximum scale of 0.9 to generate suitable anchor box sizes for our malaria dataset. We trained SSD with Additional file 1. Examples of malaria parasite detection results using different detection models.


Asymptomatic malaria was detected by malaria rapid-diagnostic tests (mRDT) and real-time PCR. Hemoglobin concentration was determined by HemoCue Hemoglobin 201+. The study outcomes were the prevalence of asymptomatic malaria and anemia (Hemoglobin level <11 g/dL). The overall prevalence of asymptomatic malaria was 36.4% . The monthly prevalence of asymptomatic malaria remained >25% throughout the year, and the highest prevalence (40%) was recorded during the rainy season. Asymptomatic malaria was significantly associated with primigravida, younger maternal age, and anemia. The prevalence of anemia was 68.5% . Asymptomatic malaria, primigravida, younger maternal age and low Body Mass Index were significant predictors of low hemoglobin concentration. We report high prevalence of asymptomatic malaria and anemia among pregnant women on the first ANC visit. Screening of malaria and anemia during the first ANC visit is recommended for targeted interventions.Asymptomatic malaria and anemia during pregnancy increase the risk of negative birth outcomes. This cross-sectional study investigated the prevalence and correlates of asymptomatic malaria and anemia during first antenatal care (ANC) visit among pregnant women in a rural district, Tanzania. HIV-uninfected pregnant women without symptoms of malaria ( Malaria and anaemia in pregnancy are significant maternal health problems causing an increased risk for maternal death, stillbirth, spontaneous abortion, and low birth weight ,2. The WP. falciparum-infected erythrocytes to the placenta is mediated by variant surface antigen 2-CSA (var2CSA), a member of P. falciparum erythrocyte membrane protein 1 (PfEMP1) which binds specifically to chondroitin sulfate A in placental cells  (95% CI: 12.9 to 17.9) A. The seectively B. P. vivThe monthly prevalence of asymptomatic malaria determined by mRDT and real-time PCR at first ANC visit remained above 25% throughout the year  from FebThe association of asymptomatic malaria with various potential correlates was evaluated. Binary logistic regression analysis indicated that asymptomatic malaria was significantly associated with gravidity, maternal age, and anemia. Primigravida was associated with significantly higher odds of asymptomatic malaria compared to multigravida . In addiThe overall prevalence of anemia among pregnant women at first ANC visit was 68.5% [561/819] (95% CI = 65.2 to 71.6). Majority of participants (54.4% [305/561]) had moderate anemia (hemoglobin = 7–9.9 g/dL) followed by mild anemia 43.9% [246/561] (hemoglobin = 10–10.9 g/dL) and only a few pregnant women (1.7% [10/561]) had severe anemia (hemoglobin <7 g/dL) .Potential predictors of anemia at first ANC visit were investigated using binary logistic regression. Maternal age, gravidity, and late initiation of ANC  were significantly associated with anemia at first ANC visit. Adolescence (age <20 years) was significantly associated with higher odds of anemia compared to adults (age ≥20 years) . On the 2) BMI and an increase in maternal age by one year were significantly associated with increased hemoglobin concentrations  g/dL. Various factors associated with hemoglobin concentration were evaluated using linear regression model. Hemoglobin concentration was significantly associated with asymptomatic malaria, gravidity, body mass index (BIM) and maternal age . Asymptotrations . In the trations .This study assessed the prevalence and risk factors of asymptomatic malaria and anemia at first ANC visit among HIV negative pregnant women living in a moderate malaria transmission area of Tanzania. The major findings include: (i) a high prevalence of asymptomatic malaria (36.4%) at the first antenatal care visit, which sustained to be >25% throughout the year during the study period, (ii) an overall high prevalence of anemia (>60%), (iii) delayed presentation for the first antenatal care (5.4 months) and (iv) primigravida and younger maternal age as risk factors for asymptomatic malaria, and anemia at first ANC visit. The prevalence of asymptomatic malaria (36.4%) at first ANC before initiating IPTp-SP found among pregnant women in the study area is higher than the prevalence of asymptomatic malaria at first ANC reported from Kenya (35%) , but lowThe high prevalence of asymptomatic malaria among pregnant women found in this study could indicate the challenge with the current malaria prevention strategies during early pregnancy before initiating the IPTp-SP. In Tanzania, the national malaria control program strives to expand ITNs coverage which is the key strategy to prevent malaria. However, utilization of ITNs among pregnant women in Tanzania has declined from 75% in 2011 to 51% in 2017 ,31. WhilThe prevalence of asymptomatic malaria among pregnant women during their first ANC visit was consistently above 25% throughout the study year. The highest prevalence (40 %) was recorded in February, indicating high transmission during the rainy season. The persistent prevalence of asymptomatic malaria suggests the stable transmission in the study area. The overall prevalence of asymptomatic malaria in pregnant women found in this study is five-fold higher than the current overall prevalence of symptomatic malaria in Tanzania 7.3% . CurrentP. falciparum erythrocyte membrane protein 1 (PfEMP1), which is acquired through consecutive pregnancies [In sub-Saharan Africa, malaria continues to be the main reason for low birth weight which is the risk factor for poor neurodevelopment and infant mortality . For insgnancies . On the High overall prevalence of anemia (68.5%) among pregnant women was found in this study. Majority of participants had moderate to mild anemia. Only few pregnant women were found to have severe anemia at first ANC visit. Pregnant women with asymptomatic malaria had significantly higher odds of moderate to severe anemia compared to those without detected malaria parasites. In addition, asymptomatic malaria was significantly associated with low hemoglobin concentration. A study in Cameroon, reported that both asymptomatic and symptomatic malaria at first ANC visit were associated with low hemoglobin levels and anemia . TherefoFactors such as poor nutrition could be among the reasons for high anemia in the study area. In this study, BMI was associated with significantly low hemoglobin concentration. Although caution is needed when relating BMI with nutritional status especially during pregnancy, this finding may suggest that poor nutrition could be one of the reasons for the high anemia burden in the study area. Additionally, primigravida and adolescent pregnant women were found to have significantly higher odds of anemia compared to multigravida and adult pregnant women, respectively. The high risk of anemia among primigravida and adolescent women may be related to their higher susceptibility to asymptomatic malaria. Anemia prevalence found in this study (68.5 %) is higher than that reported in Nigeria (59.6%), Southeast Ethiopia (27.9%) and in low malaria area of northern Tanzania (23%) ,41,42, iMaternal anemia during pregnancy could lead to adverse birth outcomes such as preterm birth and LBW ,44,45. IThe median gestational age at first ANC visit was 5.4 months. The majority of pregnant women in the study area (85%) appeared to their first ANC visit in the late second and early third trimesters, which is similar to findings from other developing countries ,4. UsualOur findings may also serve as an evaluation for the efficiency of existing interventions for the prevention of malaria and anemia before ANC initiation. The results from this study indicate the need to strengthen and expand the ITNs coverage and usage and screening for malaria and anemia at first ANC visit, particularly for those pregnant women living in a high malaria transmission area.The study had some limitations. As it was conducted in an area of moderate malaria transmission intensity (<50%), the results of this study may not be generalized to areas of lower (<5%) and higher (>50%) malaria transmission intensities. Additionally, the study assessed only asymptomatic malaria in pregnancy. Excluding pregnant women with symptomatic malaria might be underestimating the overall burden of malaria at first ANC visit in the study area. However, the strength of this study is that the data collection spans over one year, covering both high and low malaria seasons. Moreover, the use of sensitive techniques  helped to detect malaria parasitemia missed by mRDT which has limited sensitivity; thus, the findings of this study may reflect the true burden of asymptomatic malaria in the study area.We report delayed presentation in seeking ANC, and a high prevalence of asymptomatic malaria and anemia among pregnant women at first ANC visit. Primigravida and younger maternal age significantly correlate with both asymptomatic malaria and anemia. Asymptomatic malaria and low BMI are significant predictors of low hemoglobin concentration. Screening for malaria and anemia, particularly in primigravida and younger mothers, during the first ANC visit is recommended for targeted interventions. Strengthening ITNs coverage and screening for malaria and anemia during first antenatal care, particularly in areas with high malaria transmission is recommended for targeted intervention and care. Sensitization for earlier ANC initiation and educating women on nutrition and diets during ANC visit is recommended to reduce the burden of anemia. In addition, new strategies to outreach pregnant women who have not yet started ANC are recommended to maximize the benefit from the service and alleviate the burden of malaria and anemia in pregnancy.