Plasmodium falciparum causes placental malaria, which results in adverse outcomes for mother and child. P. falciparum-infected erythrocytes that express the parasite protein VAR2CSA on their surface can bind to placental chondroitin sulfate A. It has been hypothesized that naturally acquired antibodies towards VAR2CSA protect against placental infection, but it has proven difficult to identify robust antibody correlates of protection from disease. The objective of this study was to develop a prediction model using antibody features that could identify women protected from placental malaria.We used a systems serology approach with elastic net-regularized logistic regression, partial least squares discriminant analysis, and a case-control study design to identify naturally acquired antibody features mid-pregnancy that were associated with protection from placental malaria at delivery in a cohort of 77 pregnant women from Madang, Papua New Guinea.The machine learning techniques selected 6 out of 169 measured antibody features towards VAR2CSA that could predict (with 86% accuracy) whether a woman would subsequently have active placental malaria infection at delivery. Selected features included previously described associations with inhibition of placental binding and/or opsonic phagocytosis of infected erythrocytes, and network analysis indicated that there are not one but multiple pathways to protection from placental malaria.We have identified candidate antibody features that could accurately identify malaria-infected women as protected from placental infection. It is likely that there are multiple pathways to protection against placental malaria.This study was supported by the National Health and Medical Research Council . Plasmodium falciparum malaria is greatest in young children and pregnant women  to sequester in the maternal blood spaces of the placenta  family of variant surface antigens (VSA). PfEMP1s are encoded by var genes and are composed of multiple Duffy binding-like (DBL) domains and cysteine-rich interdomain regions (CIDR). VAR2CSA has six DBL domains, with CSA adhesion being strongly associated with the DBL2 domain, which is present in the N-terminal region of the protein , in which pregnant women received either three courses of sulfadoxine pyrimethamine (SP) and azithromycin or one course of SP and chloroquine. Women were recruited at 14–26 gestation weeks and followed up until delivery. All women presenting for their first antenatal visit at one of the nine participating health centers in Madang Papua New Guinea were invited to participate in the original cohort study. Exclusion criteria included a gestation of >26 weeks, hemoglobin <6 g/dl with symptomatic anemia, previous serious adverse reactions to the IPTp study medications, permanent disability or chronic medical conditions, known multiple pregnancy, age <16 years, or known unavailability to follow-up P. falciparum IEs in peripheral blood and/or placenta at delivery. Groups included women with no evidence of infection in peripheral blood by PCR or light microscopy nor on examination of placental histology at delivery (n = 50); women with active placental malaria characterized by detection of P. falciparum IEs by placental histology (n = 50); and women with P. falciparum infection by light microscopy and/or PCR in the peripheral blood but with no IEs detected by placental histology examination (n = 27). Sample size was based on published work that used a similar approach to investigate antibody responses to infectious diseases    in 20% dimethyl sulfoxide (DMSO) in liquid nitrogen for later use or used immediately after isolation. Natural killer (NK) cells were isolated from fresh venous blood collected in sodium heparin vacutainers (BD). NK cells were isolated by negative selection using the RosetteSep Human NK Enrichment Cocktail (STEMCELL Technologies) as per manufacturer’s instructions.Neutrophils were isolated from fresh venous blood collected in lithium heparin vacutainers  using the EasySep Direct Human Neutrophil Isolation Kit  as per manufacturer’s instructions. Neutrophil purity was assessed by cell morphology using light microscopy of Giemsa stained smears of the isolated cells, and viability was assessed using trypan blue exclusion. Monocytes were isolated from both fresh venous blood, collected in lithium heparin vacutainers (BD), as well as from buffy coats supplied from the Australian Red Cross Blood Service. Monocytes were isolated by negative selection using the RosetteSep Human Monocyte Enrichment Cocktail (STEMCELL Technologies) as per manufacturer’s instructions. Monocyte purity was assessed by staining  and measuring CD14P. falciparum line CS2  and CSA  as previously described . 3D7 wasMultiplex assays were used to detect plasma levels of antigen-specific antibodies (Abs) towards VAR2CSA DBL domains. Features assessed included total IgG, IgG1, IgG2, IgG3, IgG4, IgA1, IgA2, IgM as well as antibody engagement with complement (C1q) and FcγRs . To conduct the multiplex assays, DBL domains  of the V4 beads/mL in 1:100 dilution of plasma in PBS-1% BSA and 50 µL were aliquoted into each well of a 96-well round bottom plate . Plates were incubated on a shaker overnight at 4°C, then centrifuged and washed with PBS-0.1% Tween20 using a magnetic plate-washer (Bio-Plex Pro wash station). The anti-human Ab detectors for IgG, IgG1, IgG2, IgG3, IgG4, IgA1, IgA2, or IgM conjugated with phycoerythrin (PE)  were added, and the mixture was incubated for 2 hr on a plate shaker. C1q , FcγRI (R&D Systems), and FcγRIIIb (R&D Systems) were biotinylated using EZ-Link Sulfo-NHS-LC-Biotin (Thermo Fisher Scientific) as per manufacturer’s instructions and then labeled streptavidin-PE (SouthernBiotech), before being added to samples. For FcγRIIa and FcγRIIIa, the beads/plasma samples mixture was incubated with biotinylated recombinant dimeric FcγRIIa and FcγRIIIa ectodomains . Phagocytosis was measured by gating on THP-1 using forward scatter (FSC) and side scatter (SSC) parameters. Phagocytic score was calculated as (% of THP-1 cells positive for beads × geometric MFI of the bead-positive THP-1 cells). All samples were run in duplicate.Antibody-dependent cellular phagocytosis (ADCP) of beads coated with VAR2CSA DBL domains and opsonized with plasma or purified IgG was assessed using THP-1 cells. Individual DBL domains  were bioADCP of IE opsonized with plasma by THP-1 cells was assessed as previously described . Phagocy4 monocytes in leukocyte medium were plated out per well and rested at 37°C for 1 hr prior to phagocytosis. 30 μL of the opsonized beads were then added to each well with monocytes. The monocytes and beads were co-incubated for 50 min at 37°C with 5% CO2. After incubation, the cells were washed and resuspended in cold PBS-2% PFA. Phagocytosis was measured by gating monocytes on the FSC and SSC. All samples were run in duplicate, and assays were repeated with three different primary cell donors. For each donor, a phagocytic score was calculated (% of monocytes cells positive for beads × geometric MFI of the bead-positive monocytes) and then the average of the phagocytic scores for the three donors was taken.Monocyte phagocytosis of beads coated with VAR2CSA DBL domains and opsonized with plasma was assessed. Beads were coated with DBL domains as described above, except that neutravidin 1 μm beads were incubated with 6 μL of 1 mg/mL of each DBL domain. To measure ADCP, a sterile 96-well U bottom plate (Corning) was blocked with salt PBS buffer (PBS plus 0.25 M NaCl and 1% BSA) for 30 min at room temperature. 40 μL of plasma  was added to each well along with 20 μL of beads (0.01% v/v) and incubated for 1 hr at room temperature. The beads were then washed and resuspended in 60 µL of leukocyte media. In a separate 96-well U bottom plate, 5 × 107 IE/mL) was mixed and left for 1 hr at room temperature, before being washed and resuspended in 50 μL RPMI-1640 with 25 mM HEPES, 0.5% Albumax (w/v), 5% heat-inactivated human serum (HIHS). In a separate 96-well U bottom plate, 5 × 104 monocytes in leukocyte medium were plated out per well and rested at 37°C for 2 hr prior to phagocytosis. Then 25 μL of the opsonized IE were added to each well with monocytes. The monocytes and IE were co-incubated for 40 min at 37°C with 5% CO2. After incubation, the cells were washed and resuspended in cold PBS-2% PFA. Phagocytosis was measured by gating on monocytes using the FSC and SSC parameters. All samples were run in duplicate, and assays were repeated with three different primary cell donors. For each donor, a phagocytic score was calculated (% of monocytes cells positive for DHE × MFI of the DHE-positive monocytes) and then the average of the phagocytic scores for the three donors was used.ADCP of opsonized IE by primary monocytes was assessed. A sterile 96-well U bottom plate (Corning) was blocked with PBS-1% BSA. In each well, 30 μL of diluted plasma (1:10) along with 3.3 μL of DHE-stained IE in leukocyte media  and then the average of the phagocytic scores for the three donors was used.Antibody-dependent neutrophil phagocytosis (ADNP) of beads coated with VAR2CSA DBL domains and opsonized with plasma was assessed. Beads were coated with DBL as described for primary monocytes. Neutravidin 1 μm beads were incubated with 6 μL of 1 mg/mL of the respective DBL domain. To quantitate ADNP, 12 μL of plasma  was added to each well of a sterile 96-well U bottom plate (Corning) along with 6 μL of beads (0.01% v/v) and incubated for 1 hr at room temperature. The beads were then washed and resuspended in 30 μL of leukocyte medium. In a separate 96-well U bottom plate, 3 × 107 IE/mL) were mixed in a sterile 96-well U bottom plate (Corning), incubated for 1 hr at room temperature, before being washed and resuspended in 50 μL of leukocyte medium. In a separate 96-well U bottom plate, 2.5 × 104 neutrophils in 50 μL of leukocyte medium were plated out per well, 25 μL of the opsonized IE were then added to each well, and the plate was incubated for 1 hr at 37°C with 5% CO2. After incubation, the cells were washed and resuspended in cold PBS-2% PFA. Phagocytosis was measured by gating neutrophils on the FSC and SSC. All samples were run in duplicate, and assays were repeated with three different primary cell donors. For each donor, a phagocytic score was calculated (% of neutrophil cells positive for beads × geometric MFI of the bead-positive neutrophils) and then the average of the phagocytic scores for the three donors was used.ADNP of IE opsonized with plasma was assessed. 30 µL of diluted plasma (1:10) and 3.3 μL of DHE-stained IE in neutrophil medium (1.65 × 106/mL and 20 μL of neutrophils were added to each well followed by 20 μL luminol horseradish peroxidase (HRP) solution . The plate was spun briefly to settle the contents and read immediately on a FLUOstar plate reader. Luminescence was measured in each well for 1 s every 2 min for 1 hr and was calculated as the average luminescence 5 min either side of the peak of the curve. Luminescence score was standardized to the no serum controls that were run on every plate. All assays were repeated with three different primary cell donors, and the average luminescence score from the three donors was used.Antibody-dependent respiratory burst (ADRB) was measured using an assay of reactive oxygen species (ROS) production. Firstly, 25 μL of 4 μg/mL of individual DBL domains  in PBS w7 cells/mL in PBS-1% FBS were mixed and incubated for 1 hr at room temperature. The IE were then washed and resuspended in 20 μL of PBS. 10 μL of neutrophils in Hanks’ buffered saline solution at 2 × 106/mL, 10 μL of luminol HRP solution, and 5 μL of opsonized IEs were added to each well of a 384-well white, flat bottom plate . The plate was spun briefly to settle the contents and then read immediately on a FLUOstar plate reader . Luminescence was measured as described above. Luminescence score was calculated as the % of the positive plasma control, which was run on every plate. All assays were repeated with three different primary cell donors, and the average luminescence score from the three donors was used.To measure ADRB in response to IEs, 96-well U bottom plates (Corning) were coated with PBS-1% FBS for 1 hr. 1 μL of plasma from each donor was aliquoted into a single well and along with 20 μL of purified IEs at 2 × 106 cells/mL), anti-CD107a-allophycocyanin (APC)-H7 (BD) brefeldin A , and GolgiStop (BD) were added to each well, and the plates were incubated for 5 hr at 37°C. NK cells were then stained for surface markers using anti-CD16-Brilliant violet (BV)-605 (BD), anti-CD56-Brilliant ultraviolet (BD), and anti-CD3-peridinin-chlorophyll-protein , and then stained intracellularly with anti-IFNγ-PE (BD) and anti-TNFα-BV-785 (BD) after fixation (10% PFA) and Perm B solutions (Thermo Fisher Scientific). NK cells were analyzed via flow cytometry and defined as CD3- and CD56highCD16± and CD56lowCD16high. Boolean gates (FlowJo) were used to include all NK cells that expressed degranulation marker CD107a or produced cytokines, IFNγ and TNFα. Levels of CD107a, IFNγ, and TNFα expression or production were calculated as % of NK cells positive for APC-H7, PE, and BV-785, respectively. All assays were repeated with three different primary cell donors, and the average score from the three donors was used.Antibody-dependent cellular cytotoxicity (ADCC) assays using human NK cells were modified for use with DBL antigens . NUNC MaCSA binding inhibition was measured as previously described . The assIgG levels towards schizont extract and MSP-1 were measured by ELISA as previously described  using goPrior to analysis, the data were processed. The right skewness of the distribution of the features was reduced by log-transformation (log(x + 1)). Four antibody features that had negative values were right-shifted to have their minimum at zero prior to log-transformation. Next, the distributions of the features were centered and scaled to have zero mean and unit standard deviation.Demographic and clinical characteristics of the pregnant women were described using the mean (SD) for continuous variables and frequency (%) for categorical variables.t-test. The fold-change in the volcano plot was defined as the exponential of difference between the means of log-transformed and standardized data across the groups. Antibody features were correlated using Pearson pairwise correlation and correlation networks were plotted using the qgraph package   was subsAll of the computations were performed in the R software . The resP. falciparum at enrollment (by PCR and/or light microscopy). Women were selected based on P. falciparum infection status at delivery, using histology to define placental malaria , 50 women who had P. falciparum parasites in the placenta by histology , and 27 women who had no P. falciparum parasites in the placenta by histology but who had peripheral blood parasitemia by PCR and/or light microscopy  at delivery. Of the latter group, 10 were also PCR positive in placental blood, consistent with free circulation of early-stage parasites throughout the body. SP and azithromycin was more efficacious against placental malaria than SP-chloroquine (We measured antibody features in plasma samples collected at enrollment (mean 21 weeks’ gestation) in 127 women and assessed the influence of antibody features on the presence of placental malaria at delivery. All women resided in malaria-exposed areas, and 17 were positive for  malaria . The cohoroquine , but antoroquine .We initially studied antibody to an array of recombinant VAR2CSA DBL proteins see , four ofP. falciparum antigens merozoite surface protein-1 (MSP-1) and schizont extract  and 3D7 that had been selected for high levels of CSA adhesion and studied whether antibody-opsonized IE and beads coated with recombinant DBL domains could activate leukocytes or promote phagocytosis to identify which antibody features associated with innate immune cells play important roles in parasite clearance or killing. We adapted existing cellular assays to measure ADCP of DBL protein-coated fluorescent beads and IE using THP-1 cells .FCR3), ADCP, and ADNP of CSA-binding IE , binding inhibition of IE to CSA (CSA.Binding.Inhibition.FCR3), IgA2 to DBL2 (IgA2.DBL2.1010), and IgG3 to CSA binding IE (IgG3.3D7). For all six features, antibody levels were significantly higher in the non-placental infection group compared to the placental malaria group , but theP. falciparum infection from placental malaria. The combination of a prospective study design and a systems serology approach provided an unbiased way to identify the key features of the antibody response to VAR2CSA that mediates protection. Using this approach, we identified six antibody features of 169 tested, which were able to correctly differentiate, on average, 86% of the pregnant women with placental malaria and non-placental infection. The antibody features identified fell into broad functional groups: antibody that blocks placental binding of IEs and opsonizing antibody that result in phagocytic clearance of IEs  . Interesnfection . IgA2 canfection , and as Our analysis suggests that features determined by measuring antibody to VAR2CSA-expressing IE are important indicators of protection from placental malaria. Four features measured antibody to IE using representatives of the dominant 3D7-like and FCR3-like clades  whose N-Antibody responses to VAR2CSA domains serve as excellent markers of exposure to malaria in pregnant women , but fewThe correlation network showed close correlations between different antibody responses to recombinant DBL domains  but the protective antibody features were dispersed, suggesting that distinct pathways contribute to the development of protection against placental malaria. The analysis of functions identified in the selected features further supports this, with most protected women (and few unprotected women) having significant antibody that promoted both binding inhibition to CSA and phagocytosis; however, no consistent pattern of antibody functions in protected women was seen. Similar associations have been seen in the relationships between antibody features and protection from viral pathogens, and there is a growing awareness that polyfunctional antibody responses, rather than a single functional correlate, contribute to protection from disease . None ofWe used systems serology to identify protective features of the naturally acquired antibody response to VAR2CSA, a PfEMP1 variant that is specifically associated with placental malaria, complementing a recent study that used systems serology to identify functional antibody correlates of vaccine-induced immunity, in subjects vaccinated with RTS,S . A systeWe were interested in measuring antibodies to placental binding parasites and defined placental malaria by the detection of IE in the placenta by histology because previous studies have shown that these are the infections associated with adverse pregnancy outcomes . Ring stP. falciparum infection with, and without, placental malaria; the prospective study design; and the use of native antigens on IEs to complement the data we acquired using recombinant protein. Together, this allowed us to discover the determinants of naturally acquired protective immunity. Weaknesses include the lack of inclusion of full-length VAR2CSA in our Luminex and bead-based assays, and an imbalance in numbers between women with parasitemia but no placental infection relative to the other groups. Samples from all women in the former group were selected for this study , but this group is relatively rare, with placental infection in the absence of peripheral infection being substantially more common . Our results suggest that multiple pathways exist that lead to the development of protective immunity against placental malaria. Next steps will include validating this set of features in other sample sets from different geographical settings and also determining whether these antibody features predict protection from adverse pregnancy outcomes such as low birth weight. The immune responses identified are relevant to further development of pregnancy malaria-specific therapies such as vaccines or monoclonal antibodies and possibly to the identification of protective antibody against malaria in non-pregnant populations. Multiple antibody functions and characteristics may be required to develop robust protective immunity to placental malaria.10.5061/dryad.wpzgmsbkx.Dataset used for  In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:This is the very first study to apply systems serology approaches to study antibody responses directed to specific Plasmodium  antigens and the results demonstrate that these responses correlate with protection from placental malaria. The analyses of samples from approximately 200 women revealed that these antibody features do discriminate between women with placental malaria at delivery and women with malaria detectable in the peripheral blood, but not in placenta. These findings support the effort to develop vaccines against the certain protein antigens of placental malaria parasites.Decision letter after peer review:eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Dominique Soldati-Favre as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Sidhartha Chaudhury (Reviewer #3).Thank you for submitting your article "Identifying women protected from placental malaria using systems serology" for consideration by The Editors and reviewers have discussed your revision plan with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.Essential revisions:1) Your responses to the revisions as proposed by the Reviewers have, in general, been considered as sufficient for addressing their concerns.P. falciparum infection by light microscopy and/or PCR in the peripheral blood but with no IEs visible in the placenta by histology". This response ("Line 85") leaves open whether this definition means "no IEs" or "no mature IEs" by histology. Thus, it seems that a full clear definition is missing in the manuscript, and it is not clear from your response what the planned revision includes. In addition, please indicate in Table 1 how many of the 27 women in this group were positive by microscopy versus PCR of their peripheral blood.2) However, apart from the specific critical points as indicated in the initial decision letter and which are included here once again, the revised manuscript should clearly state your definition of the primary group used to analyze correlates of protection – the "non-placental infection at delivery" group. At present, it appears to be defined as "women with Reviewer #1:The authors have conducted a systems serology study of the relationship between antibody responses to VAR2CSA and protection from placental malaria (PM) in pregnant women from Papua New Guinea.Based on initial analysis of 130 variables and samples from 127 women  and subsequent analysis of 169 variables from 77 women , they identified a list of six selected serological features that discriminated with 86% accuracy between women with placental parasitaemia at delivery and women with peripheral but not placental parasitaemia at the same time point. It is an important conclusion from the work performed that it underscores the likelihood that multiple pathways to clinical protection from PM exists – a conclusion that can safely be extended to other clinical categories of malaria – and probably even to infectious diseases in general. While this may seem obvious to some, it is nevertheless largely ignored in almost all existing reports. In particular, current efforts to develop vaccines against PM are completely focussed on inhibition of adhesion of infected erythrocytes (IEs), completely ignoring the antibody effector functions that rely on opsonization of IEs for cell-mediated destruction, and which the current analysis suggest are important.The manuscript is very well written, based on careful and in-depth analysis, and constitutes a valuable addition to the existing literature.While I am not able to ascertain the finer points of the advanced statistical analyses conducted, I have no reason to suspect that anything is amiss.I have only a couple of specific comments:P. 14 ("ADNP of IE… contributed to protection"): I think it would be more correct to write "ADNP of IE… correlated with placental infection status" as no causal relationship was established.P. 15: The authors list weaknesses of their study, which is commendable. However, they fail to mention what I consider a more prominent weakness than those listed, namely the absence of a test of their six-features-list on an independent data/sample set. While such a test would be optimal, at least it should be mentioned as a weakness if it is not done.Reviewer #2:The authors are the first to use systems serology to examine antibody responses associated with protection from placental malaria. They determine that functional antibodies against CSA-binding IE are associated with protection from placental malaria, in general confirming findings from earlier studies. While the consistency with earlier studies engenders confidence in their findings, it does lessen the novelty. Important aspects of the clinical study design and study cohort need better description and justification. The study would be strengthened considerably if the top features identified here were tested for their predictive capacity in a second confirmatory cohort, albeit the fact that these associations have previously been made in other studies give general confidence in the findings. Protective immunity against placental malaria increases with gravidity, and therefore the authors should report how the protective features that they identify are related to gravidity.Abstract concludes "inhibition of placental binding and/or opsonic phagocytosis of infected erythrocytes" identify women who are protected from placental malaria. This is consistent with earlier studies using non-systems approaches that previously identified these associations.Line 85 "some pregnant women with peripheral blood infection remain free of placental malaria" – while such cases have been sporadically described, the "placental malaria-negative infection" phenotype is an uncommon phenomenon in studies that carefully document placental and peripheral Pf infections, and requires better definition here. Who has used such a study design before? "Placental malaria-negative" can mean that mature parasites do not sequester in the placenta, but does not necessarily mean that all parasites are absent from the placenta. Practically speaking, how could peripheral ring stage parasites be excluded from circulating through the intervillous spaces at the same density they are found in the peripheral blood? Related to this, the authors should provide detailed information on the pregnancy outcomes for the women in the different groups: especially Pf quantification in peripheral blood and placental blood by microscopy and by PCR, etc, but also BW, gestational age. It may be that the "PM-negative infection" phenotype is related to highly sensitive detection of sparse Pf in peripheral blood by PCR versus less sensitive detection of sparse Pf in placental blood using Giemsa-stained histology (see similar comment below).Line 108 "Five of the six leading antibody features we found were related to inhibition of placental sequestration and/or opsonisation for phagocytic clearance" Can the authors comment whether the same antibodies might be mediating both effects, or do they surmise they are unlikely to overlap?Line 112 Please state briefly but clearly here how the samples/women were selected for inclusion in the cohort (in addition to the more detailed description in the Methods).Line 115 "All women resided in heavily malaria exposed areas" is not consistent with the evidence provided in Table 1 that only 14/127 women had Pf detected by PCR at their baseline visit. The authors should explain this. Had these women previously received IPTp, or was this their baseline sample collected before first IPTp?P. falciparum parasites in the placenta but who had peripheral blood parasitemia by PCR and/or light microscopy" This wording and the Methods section indicate peripheral blood was tested for Pf by Giemsa and PCR, but placental blood was tested by Giemsa but not PCR. This is not a fair comparison. What is the sensitivity of their PCR versus their Giemsa stained blood or tissue?Line 119 "no Line 142 "using samples from the 127 women and measuring 13 antibody features directed at ten DBL domains, 15,340 out of 16,510 possible data points were acquired". This is an impressive dataset to examine correlates of protection.All pregnant women in this study have received IPTp and this can affect the PM outcome at delivery. Looks like this has not been really considered in the interpretation of the data, particularly in view of the fact that two types of IPTp combinations were used, and readers are not informed of their potentially different efficacies.Among the identified antibody features in this study it appeared that none of the activities targeted more than one variant of protein or parasite. Can the authors discuss this lack of strain-transcending pattern in these activities? A similar pattern of parasite variant dependent activity of PM antibody has previously been described by Doritchamou et al. IAI 2019. The authors should discuss their findings in that context and also comment whether the six antibody features identified in this study might vary in populations from different geographical areas.Lines 214 – 215 "… the six features identified by elastic net were spread throughout the correlation network and were not well correlated with each other ". Based on this statement it is confusing when the authors conclude that the six features fall into two major functional groups. In particular the inverse correlation between IgG3.DBL2(ID1-ID2a).FCR3 with CSA.Binding.Inhibition.FCR3 is inconsistent with Figure 6 suggesting that these represent related responses.The authors indicated that 17 samples were Pf positive at enrolment. What is the impact of early infection on these identified antibody features in relation to protection against PM and to antibody responses?Reviewer #3:The authors hypothesize that protection from placental malaria requires specific humoral immunity to malaria protein VAR2CSA. The authors obtained plasma samples from 127 pregnant women and grouped them into three categories based on malaria diagnosis at delivery: non-infected at delivery, placental malaria at delivery, and non-placental malaria at delivery. They use systems serology to measure 169 variables related to antibody binding, isotype, and functional activity and used machine learning to identify 6 variables that could accurately distinguish between placental and non-placental malaria cases. They delve into these 6 variables to provide some insight into the mechanisms of protection against placental malaria.Strengths: The cohorts in this study are large and robust, with 50 placental and 27 non-placental cases with similar demographic profiles. They assess a wide range of serology measures for binding, isotype, isotype subclass, and functional responses against both infected erythrocyte and recombinant antigens. They find significant group-level differences in serology measures between placental and non-placental malaria groups suggesting that there is great potential in this data set to identify correlates of immunity and potential mechanisms of protection.Weaknesses: They used a elastic network-regularized linear regression method to identify from 169 variables, the top variables that distinguish placental and non-placental malaria cases, and then use a Partial Least Square Discriminant Analysis method to assess how accurately a subset of these variables could be used to predict placental malaria susceptibility. While this overall approach is reasonable, it contains a substantial risk of overfitting that is not properly assessed in the study. Overfit models produce seemingly highly accurate predictions that result from incidental/random variation in the data rather than biologically significant differences, and jeopardize the scientific conclusions of the study.Furthermore, the authors assume that differences between the placental malaria and non-placental malaria groups reflect correlates of protection, thus justifying an exploration into mechanisms of protection. However, these two groups could reflect differences in malaria exposure, despite demographic similarities in age/residence. If correlates of protection cannot be distinguished from correlates of exposure, this limits what can be inferred about mechanisms of protection.Appraisal: The authors conclusions rest substantially on the six variables identified through machine learning. Ultimately the study conclusions cannot be supported by the data without demonstrating that these six variables reflect biologically significant differences and do not simply arise from analysis choices and model overfitting.1) It is important to demonstrate that malaria exposure is similar in the placental and non-placental malaria groups because a key assumption made here is that a comparison between these groups identifies correlates of protection, and not simply correlates of exposure. Indeed, the authors find that the non-placental malaria group had almost double the PCR positive rate of the placental malaria group at enrolment, suggesting it is possible they had higher exposure, despite similar demographic profiles.One way to address this would be to take serological markers in the data that others in literature have shown to be linked to exposure, and show that there is no significant differences between the three groups with respect to these serological markers of exposure.2) Much of the conclusions of this study rests on the outcome of the machine learning analysis, so it is critical that each step of this analysis is properly justified.In the elastic network-regularized logistic regression (ENLR), more detail is needed to explain how correlated variables are handled. For example, why was α set to 0.50, as opposed to any other value between 0 and 1? To what degree are the findings that a small number of non-correlated variables predictive of placental malaria susceptibility simply a reflection of the analysis approach rather than the underlying biology?3) Only three variables out of the top 20 identified by logistic regression have odds-ratios whose lower bound IQR exceeds 1.0 . Does this suggest the observed effects are not significant? How was it decided that 20 variables would be selected for further study?4) In the Partial Least Squares Discriminant Analysis (PLSDA), was any cross-validation done? Or was the model trained on the entire data set? PLSDA can be highly susceptible to overfitting, and cross-validation should be done to assess prediction accuracy.Also, given the imbalance in the data set , other measures of accuracy should be considered, such as sensitivity, specificity, Cohen's kappa value, and/or ROC AUC.5) An assessment of the this approach (ENLR + PLSDA) in terms of its risk for overfitting must be done. Guided feature reduction (ENLR) combined with PLSDA carries a high risk of overfitting. A comparison with 6 random variables in PLSDA is not sufficient to assess overfitting because it doesn't account for the degree to which guided feature reduction (ENLR) step contributes to overfitting.Authors should consider doing a permutation test, where the data set is randomized with respect to outcome , and then the entire ENLR + PLSDA method is carried out to determine prediction accuracy. This can be carried out for N different permutations (for example N=100 times) to determine the average prediction accuracy for this randomized outcome. Because the outcome is randomized, it is decoupled from the immune data, and thus acts as a 'negative control' for machine learning and it should fail to predict the outcome with any accuracy greater than chance. The degree to which it does 'accurately' predict this randomized outcome is a reflection of the overfitting of the model. Essential revisions:P. falciparum infection by light microscopy and/or PCR in the peripheral blood but with no IEs visible in the placenta by histology". This response ("Line 85") leaves open whether this definition means "no IEs" or "no mature IEs" by histology. Thus, it seems that a full clear definition is missing in the manuscript, and it is not clear from your response what the planned revision includes. In addition, please indicate in Table 1 how many of the 27 women in this group were positive by microscopy versus PCR of their peripheral blood.The revised manuscript should clearly state your definition of the primary group used to analyze correlates of protection – the "non-placental infection at delivery" group. At present, it appears to be defined as "women with We have added further clarification to the text under Methods, lines 148 onwards and Results, Cohort description, starting at line 467, to indicate that placental malaria was defined as no IEs visible by histology . As those authors observed, histology is most sensitive at detecting mature trophozoites and schizonts, in part because they actively accumulate in the intervillous space, and in part because they are both larger and contain visible hemozoin. We did record presence of any IEs on histology examination irrespective of stage as placental malaria.We have expanded Table 1 to add the results of peripheral blood PCR and microscopy. See also response to reviewer 2.Reviewer #1:The authors have conducted a systems serology study of the relationship between antibody responses to VAR2CSA and protection from placental malaria (PM) in pregnant women from Papua New Guinea.Based on initial analysis of 130 variables and samples from 127 women  and subsequent analysis of 169 variables from 77 women , they identified a list of six selected serological features that discriminated with 86% accuracy between women with placental parasitaemia at delivery and women with peripheral but not placental parasitaemia at the same time point. It is an important conclusion from the work performed that it underscores the likelihood that multiple pathways to clinical protection from PM exists – a conclusion that can safely be extended to other clinical categories of malaria – and probably even to infectious diseases in general. While this may seem obvious to some, it is nevertheless largely ignored in almost all existing reports. In particular, current efforts to develop vaccines against PM are completely focussed on inhibition of adhesion of infected erythrocytes (IEs), completely ignoring the antibody effector functions that rely on opsonization of IEs for cell-mediated destruction, and which the current analysis suggest are important.The manuscript is very well written, based on careful and in-depth analysis, and constitutes a valuable addition to the existing literature.While I am not able to ascertain the finer points of the advanced statistical analyses conducted, I have no reason to suspect that anything is amiss.I have only a couple of specific comments:P. 14 ("ADNP of IE… contributed to protection"): I think it would be more correct to write "ADNP of IE… correlated with placental infection status" as no causal relationship was established.We agree and have revised the sentence as suggested.ADNP of IE, which has not previously been systematically studied in malaria immunity also correlated with placental infection status”P. 15: The authors list weaknesses of their study, which is commendable. However, they fail to mention what I consider a more prominent weakness than those listed, namely the absence of a test of their six-features-list on an independent data/sample set. While such a test would be optimal, at least it should be mentioned as a weakness if it is not done.Line 678-680 “We have added the following to the section on study weaknesses:Demonstration that our selected variables correlate with lack of placental malaria in other cohorts would further strengthen the findings.”Line 760-2 “Reviewer #2:The authors are the first to use systems serology to examine antibody responses associated with protection from placental malaria. They determine that functional antibodies against CSA-binding IE are associated with protection from placental malaria, in general confirming findings from earlier studies. While the consistency with earlier studies engenders confidence in their findings, it does lessen the novelty. Important aspects of the clinical study design and study cohort need better description and justification. The study would be strengthened considerably if the top features identified here were tested for their predictive capacity in a second confirmatory cohort, albeit the fact that these associations have previously been made in other studies give general confidence in the findings. Protective immunity against placental malaria increases with gravidity, and therefore the authors should report how the protective features that they identify are related to gravidity.We thank the reviewer for their helpful comments. We have added a comment to the discussion under study weaknesses regarding the need to confirm our findings in further cohorts , see also response to Reviewer 1. Our plans to examine responses in a second confirmatory cohort have been severely disrupted by COVID-19, especially in regard to sample shipments which have not been possible for the past 12 months.Regarding associations of protective features and gravidity, we have conducted a univariate analysis using linear regression looking at how the antibody levels vary with gravidity in our cohort and have added this to the paper in the form of Supplementary File 4-table 1.In brief: Antibody feature CSA.Binding.Inhibition.FCR3 was positively associated with gravidity, and there was weak evidence that THP1.Phago.CS2 and Neutrophil.Phago.CS2 were also positively associated with gravidity. There was no evidence that IgG3.DBL2(ID1-ID2a).FCR3, IgA2.DBL2.1010 and IgG3.3D7 were associated with gravidity in this cohort. We now discuss these observations in the manuscript (lines 573-585).Abstract concludes "inhibition of placental binding and/or opsonic phagocytosis of infected erythrocytes" identify women who are protected from placental malaria. This is consistent with earlier studies using non-systems approaches that previously identified these associations.We made small edits to the abstract to reflect that selected protective responses include features previously described:“Selected features included previously described associations with inhibition of placental binding and/or opsonic phagocytosis of infected erythrocytes.”Line 50-51 Line 85 "some pregnant women with peripheral blood infection remain free of placental malaria" – while such cases have been sporadically described, the "placental malaria-negative infection" phenotype is an uncommon phenomenon in studies that carefully document placental and peripheral Pf infections, and requires better definition here. Who has used such a study design before? "Placental malaria-negative" can mean that mature parasites do not sequester in the placenta, but does not necessarily mean that all parasites are absent from the placenta. Practically speaking, how could peripheral ring stage parasites be excluded from circulating through the intervillous spaces at the same density they are found in the peripheral blood? Related to this, the authors should provide detailed information on the pregnancy outcomes for the women in the different groups: especially Pf quantification in peripheral blood and placental blood by microscopy and by PCR, etc, but also BW, gestational age. It may be that the "PM-negative infection" phenotype is related to highly sensitive detection of sparse Pf in peripheral blood by PCR versus less sensitive detection of sparse Pf in placental blood using Giemsa-stained histology (see similar comment below).We agree with the reviewer that women with peripheral blood infection without evidence of placental sequestration form a relatively rare group, and we only identified 27 in our cohort. They are analogous to infections that are found in non-pregnant women in malarious areas. When women conceive, some of these infections progress to higher density, especially in younger, less immune women , likely due to emergence of variants than can sequester in the placenta and avoid existing antibody immunity.Previous studies  highlight the difficulty of distinguishing effects of exposure from those of immunity using the more common comparison of women with and without placental malaria, which was also not informative in our hands , compared to our novel inclusion of this additional group .The reason we (and many other studies) use detection of IEs in the placenta by histology to define placental malaria, is because many studies show that these infections are associated with worse pregnancy outcomes such as prematurity, low birth weight or maternal anemia . Identifying women whose infection has not progressed to placental malaria, and the antibody responses that might limit that progression by inhibiting placental sequestration, is our specific aim.The circulating ring stage parasites will pass through the placenta although they do not sequester there, and placental blood PCR did detect them in some women (added to Table 1). These circulating rings are understood not to have any deleterious effects on the placenta, and submicroscopic infections, including in placental blood, appear to be only weakly associated with adverse birth outcomes, unlike active placental infection on histology.We have included further information as requested on the pregnancy outcomes, including BW, hemoglobin and gestational age at delivery and peripheral and placental PCR in Table 1. Original groupings of the cohorts were not done using placental PCR, however subsequent analysis revealed that one individual classified as non-infected  was actually PCR positive in the placental blood. As our analysis identifying protective features did not include the non-infected cohorts, this individual’s results do not affect the conclusions in this paper.Line 108 "Five of the six leading antibody features we found were related to inhibition of placental sequestration and/or opsonisation for phagocytic clearance" Can the authors comment whether the same antibodies might be mediating both effects, or do they surmise they are unlikely to overlap?The diversity of responses in “protected” women in Figure 5G suggests that these often do not overlap, or the overlap is heterogenous in different women. However, determining whether individual antibodies have overlapping functions would ideally require monoclonals and therefore we cannot confidently comment on whether the same antibody might be able to mediate both functions.Line 112 Please state briefly but clearly here how the samples/women were selected for inclusion in the cohort (in addition to the more detailed description in the Methods).As suggested, in addition to the detailed description in the methods, we have briefly described the selection of the cohort in the Results section , see below:P. falciparum infection status at delivery […] The three groups were frequency matched for primigravidity, IPTp regime receipt, bed net use, rural residency and age”LINE 467 onwards: “Women were selected based on Line 115 "All women resided in heavily malaria exposed areas" is not consistent with the evidence provided in Table 1 that only 14/127 women had Pf detected by PCR at their baseline visit. The authors should explain this. Had these women previously received IPTp, or was this their baseline sample collected before first IPTp?P. falciparum at first antenatal visit by microscopy and PCR respectively , and transmission in the area had only recently declined .Line 466: We have removed the word “heavily”, given the relatively low parasite prevalence. In an earlier study at one of our nine sites we found 64% of women to have current or past placental malaria on histology and 34% and 49% to have All women were recruited at first antenatal visit before receiving any IPTp. We have clarified this under “Human Subjects” in the methods in line 143-4.P. falciparum parasites in the placenta but who had peripheral blood parasitemia by PCR and/or light microscopy" This wording and the Methods section indicate peripheral blood was tested for Pf by Giemsa and PCR, but placental blood was tested by Giemsa but not PCR. This is not a fair comparison. What is the sensitivity of their PCR versus their Giemsa stained blood or tissue?“Peripheral blood collected at 14-26 gestation weeks, before initiation of IPTp, was used in the antibody assays.”Line 119 "no See our earlier response to line 85. We specifically grouped women with malaria infection into those with and without placental malaria on histology, as classically defined . Our question was, are there antibody responses that might explain why some infected women have not progressed to placental malaria, when others have. Antibody responses that prevent infection crossing a threshold  are more relevant to blood stage immunity than antibodies that simply prevent infection, as may be sought for pre-erythrocytic infection.Line 142 "using samples from the 127 women and measuring 13 antibody features directed at ten DBL domains, 15,340 out of 16,510 possible data points were acquired". This is an impressive dataset to examine correlates of protection.All pregnant women in this study have received IPTp and this can affect the PM outcome at delivery. Looks like this has not been really considered in the interpretation of the data, particularly in view of the fact that two types of IPTp combinations were used, and readers are not informed of their potentially different efficacies.We added a statement to the results highlighting the different efficacy of SPAZ and SPCQ against placental malaria (Line 476-7). As shown in Table 1, a slightly higher proportion of women in the non-placental malaria group received the less efficacious SPCQ.“Sulfadoxine pyrimethamine (SP) and azithromycin was more efficacious against placental malaria than SP-chloroquine.”Among the identified antibody features in this study it appeared that none of the activities targeted more than one variant of protein or parasite. Can the authors discuss this lack of strain-transcending pattern in these activities? A similar pattern of parasite variant dependent activity of PM antibody has previously been described by Doritchamou et al. IAI 2019. The authors should discuss their findings in that context and also comment whether the six antibody features identified in this study might vary in populations from different geographical areas.As suggested we have discussed our findings in relation to those described by Doritchamou et al. IAI 2019None of the antibody features targeted more than one variant of the protein or parasite strain. One possible explanation is that epitopes recognised by antibodies mediating each function may vary between strains . This could in turn mean that protective functional features could vary with different populations ). Future studies should ideally include multiple VAR2CSA clades, and study diverse populations.Line 726 onwards: Lines 214 – 215 "… the six features identified by elastic net were spread throughout the correlation network and were not well correlated with each other ". Based on this statement it is confusing when the authors conclude that the six features fall into two major functional groups. In particular the inverse correlation between IgG3.DBL2(ID1-ID2a).FCR3 with CSA.Binding.Inhibition.FCR3 is inconsistent with Figure 6 suggesting that these represent related responses.The broad functional mechanisms of antibody can fall into similar groups, even when the development of responses to different members of each group is only weakly correlated. As the reviewer notes, there was no correlation between IgG3.DBL2(ID1-ID2a).FCR3 with CSA.Binding.Inhibition in Figure 4 and a weak, non-significant negative correlation between them . Although binding inhibition is likely to be primarily mediated by the more-abundant IgG1, we included IgG3 to DBL2 in both Figure 6A and Figure 6B because its principal functional role could fall in either group, as total IgG antibody to this domain is known to block adhesion.The authors indicated that 17 samples were Pf positive at enrolment. What is the impact of early infection on these identified antibody features in relation to protection against PM and to antibody responses?We thank the reviewer for asking this important question, as it has improved the quality of the manuscript. We have now conducted a sub-analysis comparing the identified antibody features at enrolment in the non-placental infection cohort with those in the placental malaria cohort, excluding women who were infected (by light microscopy and/or PCR) at enrolment. In this sub-analysis we saw strong evidence that 4 of the 6 features were higher in the non-placental infection cohort (P≤0.013) and weak evidence that the other two features were higher in the non-placental infection cohort (≤0.064). The maintenance of the protective associations in the smaller, non-infected cohort suggests to us that the protective association seen in these variables was not greatly affected by the presence of the positive samples.These data are included in the manuscript in Supplementary File 4 – table 2. These results are discussed in lines 577 onwards.Reviewer #3:1) It is important to demonstrate that malaria exposure is similar in the placental and non-placental malaria groups because a key assumption made here is that a comparison between these groups identifies correlates of protection, and not simply correlates of exposure. Indeed, the authors find that the non-placental malaria group had almost double the PCR positive rate of the placental malaria group at enrolment, suggesting it is possible they had higher exposure, despite similar demographic profiles.One way to address this would be to take serological markers in the data that others in literature have shown to be linked to exposure, and show that there is no significant differences between the three groups with respect to these serological markers of exposure.Thank you for this suggestion. We measured IgG levels by ELISA to non-pregnancy specific malaria antigens merozoite surface protein-1 and schizont extract which we have previously shown to be strongly associated with exposure  and have done univariate analyses comparing non-infected v placental malaria and non-placental infection v placental malaria. There was no association with absence of placental infection for IgG towards either antigen, suggesting that the features we have identified are not simply correlates of exposure.We have included this in the Results section (line 510 onwards) and in Supplementary File 2.2) Much of the conclusions of this study rests on the outcome of the machine learning analysis, so it is critical that each step of this analysis is properly justified.In the elastic network-regularized logistic regression (ENLR), more detail is needed to explain how correlated variables are handled. For example, why was α set to 0.50, as opposed to any other value between 0 and 1? To what degree are the findings that a small number of non-correlated variables predictive of placental malaria susceptibility simply a reflection of the analysis approach rather than the underlying biology?To address the dependence of the results on Line 411 onwards now states:Identification of Key Antibody Features“The parameter α, which alters the nature of penalization between ridge regression and LASSO, was set to 0.5 to achieve a balance between sparsity and group selection; the final selected antibody features did not alter when 3) Only three variables out of the top 20 identified by logistic regression have odds-ratios whose lower bound IQR exceeds 1.0 . Does this suggest the observed effects are not significant? How was it decided that 20 variables would be selected for further study?Due to the penalisation in the elastic net, the unselected variables are assigned a coefficient of zero (i.e. odds ratio = 1). Here we are repeating ENLR, resampling from the dataset 50,000 times, and therefore, the estimated coefficient for every variable is zero in a certain proportion of resampled datasets (even though a variable may frequently be selected in a high proportion of the resampled datasets). This pushes the lower bounds of the IQRs towards zero, hence lower bound of odds ratio will be very close to 1 for many of the variables. Therefore, taking the penalisation into consideration, this does not necessarily suggest that the effects are insignificant for those variables. Figure 2 presented the top 20 variables for ease of illustration.4) In the Partial Least Squares Discriminant Analysis (PLSDA), was any cross-validation done? Or was the model trained on the entire data set? PLSDA can be highly susceptible to overfitting, and cross-validation should be done to assess prediction accuracy.Yes, 500 repeats of 10-fold cross-validation was performed and the reported performance measures were computed from the cross-validation. This is now added to the “Identification of Key Antibody Features” section and the caption of Figure 3 is edited for clarity.Identification of Key Antibody Features (line 440)“…; 500 repeats of 10-fold cross validation were performed to compute the accuracies.”Figure Legend 3“… ”Also, given the imbalance in the data set , other measures of accuracy should be considered, such as sensitivity, specificity, Cohen's kappa value, and/or ROC AUC.We have now changed figures 3A and 3B and the text (line 555 onwards) by presenting AUROC as the performance measure, as the reviewer suggests.5) An assessment of the this approach (ENLR + PLSDA) in terms of its risk for overfitting must be done. Guided feature reduction (ENLR) combined with PLSDA carries a high risk of overfitting. A comparison with 6 random variables in PLSDA is not sufficient to assess overfitting because it doesn't account for the degree to which guided feature reduction (ENLR) step contributes to overfitting.Authors should consider doing a permutation test, where the data set is randomized with respect to outcome , and then the entire ENLR + PLSDA method is carried out to determine prediction accuracy. This can be carried out for N different permutations (for example N=100 times) to determine the average prediction accuracy for this randomized outcome. Because the outcome is randomized, it is decoupled from the immune data, and thus acts as a 'negative control' for machine learning and it should fail to predict the outcome with any accuracy greater than chance. The degree to which it does 'accurately' predict this randomized outcome is a reflection of the overfitting of the model.We thank the reviewer for raising this important point and agree that the estimated performances are probably slightly optimistic and the accuracy may slightly decrease if this method is applied on external validation data. We performed the analysis suggested by the reviewer, i.e. repeating the whole ENLR + PLSDA process for 100 datasets whose group labels (PM and NPM) were randomly permuted. For each of the 100 datasets, 500 repeats of 10-fold cross validation were performed on the EN and the top six frequently selected variables were fed into the PLSDA, on which 5 repeats of 10-fold cross-validation were performed to compute the AUROC. The AUROCs of the 100 datasets were aggregated to produce the boxplot in Figure 3B.The results  show that the AUROC for our six selected variables is still significantly higher than that for the permutation test.Line 441 onwards now state:Identification of Key Antibody Features“The statistical significance of the results was assessed by comparing the performance of the model with that of two random permutation tests (null cases): 1) the PLSDA model was fitted to six randomly selected antibody features and the performance was computed for 500 repeats of 10-fold cross-validation resampling; 2) 100 datasets were generated by randomly permuting the group labels (PM and NPM) and the same analysis performed for the original data set (i.e. building PLSDA models using the top six frequently selected antibody features found by resampling of elastic net) was repeated for each dataset.”


Plasmodium falciparum pfk13 and pfmdr1 genes was performed. We analyzed 232 imported malaria cases. The majority (68.53%) of the patients came from Angola and only three patients travelled to a non-African country; one to Brazil and two to Indonesia. P. falciparum was diagnosed in 81.47% of the cases, P. malariae in 7.33%, P. ovale 6.47% and 1.72% carried P. vivax. No mutations were detected in pfk13. Regarding pfmdr1, the wild-type haplotype (N86/Y184/D1246) was also the most prevalent (64.71%) and N86/184F/D1246 was detected in 26.47% of the cases. The typical imported malaria case was middle-aged male, traveling from Angola, infected with P. falciparum carrying wild type pfmdr1 and pfk13. Our study highlights the need for constant surveillance of malaria parasites imported into Portugal as an important pillar of public health.Malaria is one of the ‘big three’ killer infectious diseases, alongside tuberculosis and HIV. In non-endemic areas, malaria may occur in travelers who have recently been to or visited endemic regions. The number of imported malaria cases in Portugal has increased in recent years, mostly due to the close relationship with the community of Portuguese language countries. Samples were collected from malaria-infected patients attending Centro Hospitalar Lisboa Ocidental (CHLO) or the outpatient clinic of Instituto de Higiene e Medicina Tropical (IHMT-NOVA) between March 2014 and May 2021. Molecular characterization of  Anopheles genus. There are 5 species of malaria parasites that cause disease in humans: Plasmodium falciparum, P. ovale, P. vivax, P. malariae [P. knowlesi [P. falciparum [Malaria is transmitted through the bite of an infected female mosquito of the malariae  and P. kknowlesi . In 2020lciparum . Once prlciparum  and limilciparum . Nonethelciparum  due to tlciparum . In 2019Anopheles atroparvus [An. atroparvus, currently circulating in Portugal, retains competence for transmitting imported strains of P. falciparum [Plasmodium infections have been reported by the Portuguese Ministry of Health during the last decade (from 54 cases in 2010 to 116 in 2019) [In Portugal, before the 1950s, there were different levels of endemicity, which were largely associated with the suitability of habitat to the local vector, the mosquito roparvus ,9. By 19lciparum ,11. As tlciparum ,11,12,13lciparum . Travelein 2019) .Before the Portuguese revolution of April 25, 1974, which brought democracy and independence to Angola, Mozambique, Guinea Bissau, São Tomé and Príncipe, Cape Verde (PALOP) and East Timor, many of the activities of research and training on “overseas exotic pathology” were localized at the Instituto de Higiene e Medicina Tropical, closely associated with the Overseas Hospital Egas Moniz . IHMT was integrated into the Nova University of Lisbon (becoming IHMT-NOVA) maintaining a travel clinic, and CHLO maintains ambulatory care at the infectious disease unit beyond emergency and inpatient care. These two units remain a national reference for tropical medicine.P. falciparum genome. Anti-malarial drugs have long been important tools for malaria control [P. falciparum has developed resistance to successively introduced antimalarials, including the currently used first-line treatment, the artemisinin-based combination therapies . There ing ACTs ,20,21,22ing ACTs ,24. Apprulations . MultiplP. falciparum Kelch 13 (pfk13) gene is particularly important because single nucleotide polymorphisms (SNPs) on its propeller domain have been strongly associated with artemisinin resistance in Southeast Asia [P. falciparum multidrug resistance gene 1 . A selection of the pfmdr1 N86/184F/D1246 haplotype has been reported from studies of artemether + lumefantrine (AL) treatment and recrudescence in patients in Asia and Africa [The ast Asia ,27. P. fantrine; ,29) is ad Africa ,31,32,33P. falciparum parasites isolated from imported malaria cases since 2014 at the two above mentioned malaria reference facilities for tropical medicine in Portugal.Global vigilance against artemisinin resistance is vital for sustaining successes toward malaria elimination, particularly in Africa, where malaria is still a major health problem . In thisAnonymized data were collected retrospectively. The collection of patient data and processing and the analysis of parasite genes were performed under the IHMT Ethics Committee Approval 11.18 and 20.18 and CHLO Ethics Committee Approval RNEC:20170700050.P. falciparum histidine-rich protein 2 (PfHRP2) and the enzyme Plasmodium lactate dehydrogenase (pLDH), followed by the gold standard optical microscopic (OM) analysis of thick and thin blood smears (stained with Giemsa). OM enabled detection and identification of Plasmodium species as well as parasite load (parasites/μL of blood). Data referred to in Malaria-infected patients diagnosed at IHMT (outpatient clinic) and at CHLO hospital (out and inpatient cases) in Lisbon, Portugal, between March 2014 and May 2021 were enrolled. The laboratory diagnosis of malaria was performed by rapid diagnostic tests and microscopy and later confirmed by PCR. All patients were first diagnosed by immune-chromatographic tests (rapid diagnostic tests RDTs) based either in malaria antigens P. falciparum confirmed by PCR following the methodology previously published [pfmdr1  and pfk13 . Genes were PCR amplified following the methodology previously published [https://blast.ncbi.nlm.nih.gov/Blast.cgi; accessed on 18 August 2021). The laboratory-adapted 3D7 clone (MRA-102) was used as reference.Parasite samples with ublished  were selOur study analyzed 232 patients who were diagnosed malaria positive at IHMT and CHLO laboratories from March 2014 to May 2021. The study identified 12 patients during 2014, 10 in 2015, 72 in 2016, 26 in 2017, 39 in 2018, 36 in 2019, 29 in 2020 and eight until the end of May 2021. The median age was 43 years (the youngest patient was five and the oldest 77 years) and the majority  were males. Sixteen of the 232 patients (6.90%) reported frequent travel to different African countries, hence were grouped as geographical provenance “Africa” in Plasmodium species confirmation using 18S rRNA gene. No discrepancies were detected between RDTs, OM and PCR diagnostic results. Monoinfection with P. falciparum was detected in the majority of the parasite isolates , 17 (7.73%) were P. malariae, 15 (6.47%) P. ovale and only four patients (1.72%) carried P. vivax. Mixed infections were observed only in seven samples  for  samples . InteresP. falciparum (single infections), we could only obtain a blood sample from 116 patients. Due to the retrospective nature of the study  we could not obtain parasite samples from all of these patients. This limits (somewhat) the estimation of the prevalence of the molecular markers for the correspondent years. Nevertheless, a total of 97 samples were successfully sequenced for pfk13, and all were wild type . None of the pfk13 variants associated with artemisinin resistance in Southeast Asia [pfmdr1 codons 86, 184 and 1246, respectively. Mixed pfmdr1 alleles were not observed  was the most prevalent with a frequency of 64.71%, followed by the haplotype associated with decreased susceptibility to AL (N86/184F/D1246 or NFD) with a frequency of 26.47%  platform. Our study (a retrospective research study) analysed the imported malaria cases diagnosed with malaria at IHMT and CHLO laboratories from March 2014 to May 2021. IHMT and CHLO laboratories cases represent approximately 1/3 of the reported imported malaria cases in Portugal. Hence, our study represents only a fraction of the reported cases during the same period in Portugal nationwide . HoweverP. falciparum in 81.47% of the cases from Africa, including five mixed infections n Africa ; and  within the expected range. It is widely distributed in sub-Saharan Africa with overlapping presence with P. falciparum [P. ovale, also endemic in Africa, where it probably represents the main agent of relapsing malaria, had a prevalence of 6.47% falling within the reported range [P. vivax was identified in mixed infections with P. falciparum (three cases) and as a single infection (one case) in patients arriving from Africa. This was not a surprise since P. vivax has been reported as endemic in Africa [lciparum ,47. P. oed range ,50,51,52n Africa ,54, evenn Africa ,56. Non-n Africa .The information on imported malaria into Portugal is scarce, not systematized and mostly available through individual manuscripts, reflecting (probably) part of the total imported cases into the country, as is the case with the present work. To the best of our knowledge, the present work is the first to present a description of the drug-resistance associated genotypic background of a sizable imported parasite population into Portugal.pfk13 with delayed parasite clearance (decreased parasite susceptibility to ACTs), has generated molecular markers for the surveillance of ACT-resistant parasites [pfk13 gene were not detected among the P. falciparum isolates in our study. The pfk13 SNPs, previously shown to be associated with slow artemisinin clearance (positivity on day 3) of P. falciparum in Southeast Asia, have rarely been reported in Africa [In Southeast Asia, the correlation of specific SNPs in the gene arasites ,36,57. Mn Africa ,59,60. Nn Africa . Other nn Africa . Due to n Africa  or othern Africa ,64,65.pfmdr1 NFD haplotype (26.47%) and a high prevalence of NYD (64.71%), which are associated with parasite reduced susceptibility to AL [Pfmdr1 mutant allele 86Y is associated with a longer time to reinfection after AL treatment [Pfmdr1 86Y has been decreasing in many parts of Africa where AL is used, which is consistent with the expected direction of selection [The presence of SNPs or haplotypes linked to tolerance of artemisinin derivatives can impact parasite survival, potentially resulting in persistence of symptoms and an increased local parasite reservoir. We report a moderate frequency of the ty to AL . Prevalety to AL ,68 (the reatment , reinforelection ,70,71. Felection ,73,74 anelection ,68,75 coAnopheles vector species in Europe and in Portugal is currently An. atroparvus [An. atroparvus was the most efficient vector [In 1975, the WHO announced that malaria had been eradicated in Europe and all recorded cases since were introduced through migration ,76,77. Eroparvus ,90,91. Wt vector . There it vector ,87,89; iAn. atroparvus was probably not susceptible to the African P. falciparum strains [P. vivax strains imported from Africa [Previous studies revealed that  strains ,91,92,93 strains ,93,94, am Africa . Hence, m Africa ,80,81,82In Portugal, there is a clear need for a systematic and more efficient method of early diagnosis, monitoring and referral of malaria cases to an appropriate health facility, not only to reduce probability of reintroduction  but to pP. falciparum carrying wild type pfmdr1 and pfk13. The boost in recent years of people circulation between Portugal and malaria-endemic regions, increases the risk of reintroducing drug-resistant malaria parasites into Portugal. These make the constant monitoring of the imported malaria parasites to Portugal an imperative and important pillar of public health. Furthermore, it is necessary to maintain surveillance of the emergence and spread of mutations in genes associated with response to ACTs, such as pfk13 and pfmdr1, because the geographic dispersion of drug-resistant malaria parasites can cause devastating effects.The typical imported malaria case was middle-aged male, traveling from Angola infected with


There is dearth of information on perinatally acquired malaria, as well as its burden in Nigeria. We determined the prevalence of pregnancy-associated malaria and its burden among parturients in Abeokuta, Ogun State.Blood films from 211 parturients were prepared, stained with 10% Giemsa and examined using microscopy. Relevant demographic information was recorded from study participants. Chi-square tests were used to analyse data using SPSS version 20.0.Prevalence of maternal peripheral, placenta and cord blood parasitaemia were 40.8%, 19.0% and 5.7% respectively, and these were significantly correlated with age and gravidity. Prevalence of maternal anaemia was 45.0%, and was significantly associated with malaria infection. The occurrence of Low Birth Weight (LBW) was 10%. Maternal, placental and cord infections with malaria were associated with LBW, with the highest percentage of LBW occurring in babies with high placental malaria parasite density. Preterm delivery and stillbirth were significantly associated with placenta and cord malaria.Impact of malaria on the mother and the newborns, notably anaemia and LBW, solicits the need for promoting use of available malaria prevention during pregnancy. These include LLINs and IPTp. Malaria affects mostly children under the age of five years and pregnant women in sub-Saharan ,2. PregnPlacental malaria has long been recognised as a complication of malaria in pregnancy in areas of stable transmission, and is particularly frequent and more severe in primigravidae . In clinPlasmodium parasites can cross the placenta leading to mother to child transmission of malaria in a condition known as congenital malaria [Studies have shown that  malaria ,13. Duri malaria .Congenital malaria has been documented in malaria-endemic areas for many years. Studies in Africa have shown that 7–10% of new-borns have malaria parasites in their placental blood and a major part of the transmission of parasites from the mother to the child occurs well before the time of delivery ,16. It hConsidering the fact that the consequences of malaria in pregnancy on both the mother and the foetus are enormous and cannot be overemphasised, the prevalence of congenital malaria remains unknown for many parts of tropical Africa , includiThe research was carried out in Abeokuta, which is the capital of Ogun state. It is situated on the east bank of the Ogun River near a group of rocky outcrops in a wooded savannah, 77 km north of Lagos by railway. Two hospitals, Oba-Ademola Maternity Hospital and State hospital Sokeni Ijaiye were involved with this study.Only pregnant women in labour (parturients) were included in the study. A total of 211 parturients were randomly selected within from the two hospitals a timeframe of 3 months, using a formula according to Yamane :Where,n = required sample sizeN = population size e = the error of 5% points = 0.05Applying the above formula, the sample size was determined as follows:Thus, a sample size of 211 parturients was determined.The sample population was selected irrespective of age, educational background, marital status, occupation, cultural or religious affiliation.et al. [et al. [Maternal blood was collected before (for packed cell volume (PCV) determination) and at the onset of labour , into a labelled EDTA bottle, while placental blood was collected using the incision method, after cleaning of the maternal surface with methylated spirit as described by Ezebialu et al. . After d [et al. .Relevant maternal and neonatal demographic and clinical characteristics were recorded in case record forms. Clinical data obtained included details of labour and delivery, anthropometric parameters of the baby and gestational age.Each baby was weighed naked after delivery using the Baby Weigh TM, electronic scale (MedelaR Inc. model 040.7012). Birth weight below 2500 g was considered to be Low Birth Weight (LBW). Stillbirth was regarded as the birth of an infant that died in the womb . Preterm birth in this study related to babies born alive before 37 weeks of pregnancy had been completed.Plasmodium species on the thick blood film while thin smears were used for species identification. Slides were declared negative after observing at least 100 high power fields without detecting any parasites. Parasites were counted by estimating the parasite numbers/μl of blood from the thick film as described Greenwood and Armstrong [Thick and thin smears were prepared and stained with 10% Giemsa as previously described by Cheesbrough . Blood frmstrong .Packed cell volume (PCV) was determined using blood collected into heparinised capillary tubes and spun with a Hawksley micro-haematocrit centrifuge for 5 minutes. Patients were classified as anaemic when the haemoglobin concentration was less than 11g/dl (PCV<33%), while patients with haemoglobin concentration of less than 7g/dl (PCV<21%) were considered to have severe anaemia.Data were entered into Excel and thereafter transferred to SPSS version 20.0 for further analysis. Chi-square and binomial regression were used to analyse data. A probability value of P<0.05 was considered significant.Ethical clearance for the study was obtained from the Research and Ethics Committee of the State Hospital Sokenu Ijaiye. All medical personnel of the selected hospitals and study participants were fully briefed on the objectives of the study. Only parturients who gave their written consent were enrolled in the study. Consent forms were given to willing participants after giving them detailed explanation of the research. Consent was obtained in the early phase of labour when pains were least intense.The majority of the parturients were within the age range 28 -32 yrs (44.5%), followed by the 23-27 yrs cohort (25.1%). The 18-22 yrs group had the lowest frequency (10.4%). Most parturients were multigravidae (41.2%), followed by primigravidae (31.8%) and secundigravidae (27.0%) . All of The prevalence of maternal peripheral blood malaria parasite infection was 86 (40.8%), while that of placenta and cord blood was 40 (19.0%) and 12 (5.7%), respectively. There was no significant relationship between age and maternal peripheral blood infection. The prevalence of placental and cord malaria parasite infections, however, decrease significantly (p<0.05) with age . PrevaleThere was a significant positive correlation between malaria parasite infection of the maternal peripheral blood and occurrence of anemia , 18 (85.7%) and 9 (42.9%) tested positive for maternal, placental and cord malaria infection, respectively . ParturiA high proportion (75.0%) of the preterm babies were born to mothers infected with malaria parasite, although this was not significant . HoweverThe result obtained from the univariate analysis on the usage of preventive measures and malaria history during pregnancy showed that non-usage of Intermittent Preventive Treatment (IPTp) is a significant risk factor for placenta malaria , p=0.018); a higher proportion of the parturients (34.0%) who did not use IPTp tested positive to placental malaria parasite infections . We alsoMalaria parasite infections were observed to be prevalent among the parturients in Abeokuta, Ogun State, and was detected in 40.8% of the mothers, 19.0% of the placentas and 5.7% of the cord blood. This shows that malaria in pregnancy is still a serious problem in Abeokuta despite all efforts in place to control it. Pregnancy was previously identified to increase the vulnerability to malaria infections in Abeokuta .et al. [et al. [et al. [Plasmodium falciparum for placenta sequestration and many hypotheses, based on a systemic or local failure of the immunological response to malaria, have been proposed to explain the preference of the parasites for replication in the placenta [The prevalence of placenta malaria recorded in this study 19.0%) is similar to that reported by Olugbenga et al.  from Nig [et al.  from Bur [et al.  and Bako [et al. . This co.0% is siet al. [The low prevalence of malaria in the umbilical cord (5.1%) recorded in this study is in line with the findings of Falade et al. . Howeveret al. . This iset al. . This waIn this study, anaemia was associated with malaria parasite infection of maternal peripheral blood. A high percentage of women with malaria infections had anaemia compared with the non infected women. Malaria is directly responsible for anaemia through the parasitic destruction of red blood cells (RBCs) as well as auto immune reaction in which non-infected RBCs are also destroyed.The prevalence (45%) of anaemia recorded in this study implies that anaemia in pregnancy is a lingering health issue among pregnant women in Abeokuta, Ogun State; there is need for measures to drastically reduce its occurrence. Women often become anaemic during pregnancy because the demand for iron and vitamins is increased in response to physiological changes during that time.The occurrence of low birth weight (LBW) in the study population was 10%, with the highest prevalence occurring among babies associated with infected placentas (85.7%). Studies have clearly shown that placenta malaria infection is the major cause of malaria related LBW  which arAlthough, the rate of preterm delivery was low (1.9%) it is still important to know that this was significantly associated with placenta and cord malaria. Studies have shown that malaria-infected placentas frequently carry antibodies, cytokines, and macrophages, which are indicative of an active immune response, and this immune response may induce early labour . Women tMalaria at parturition is prevalent in Abeokuta Ogun State and women below the age of 22 yrs and primigravidae are at highest risk. Maternal anaemia and delivery of LBW babies were the major devastating outcomes of malaria in the peripartum period. Other outcome included preterm delivery and stillbirth. The obvious impact of malaria on the mother and the new-born solicits the need for promoting better use of available malaria preventive measure in pregnancy, notably LLINs and IPTp.