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AMD and NJW designed the study. AMD and PNN enrolled the patients. VD, DS, KS, KC, PP, and AMS contributed to the laboratory studies. AMD, WP, and NPJD analyzed the data. All authors contributed to writing the paper.

The authors have declared that no competing interests exist.

In falciparum malaria sequestration of erythrocytes containing mature forms of

We measured plasma concentrations of PfHRP2, using a quantitative antigen-capture enzyme-linked immunosorbent assay, in 337 adult patients with falciparum malaria of varying severity hospitalised on the Thai–Burmese border. Based on in vitro production rates, we constructed a model to link this measure to the total parasite burden in the patient. The estimated geometric mean parasite burden was 7 × 10^{11} (95% confidence interval [CI] 5.8 × 10^{11} to 8.5 × 10^{11}) parasites per body, and was over six times higher in severe malaria (geometric mean 1.7 × 10^{12}, 95% CI 1.3 × 10^{12} to 2.3 × 10^{12}) than in patients hospitalised without signs of severity (geometric mean 2.8 × 10^{11}, 95% CI 2.3 × 10^{11} to 3.5 × 10^{11}; ^{12}, 95% CI 1.9 × 10^{12} to 6.3 × 10^{12};

Plasma PfHRP2 concentrations may be used to estimate the total body parasite biomass in acute falciparum malaria. Severe malaria results from extensive sequestration of parasitised erythrocytes.

Measuring sequestered parasites using plasma PfHRP2 concentrations may provide a more accurate estimate of total parasite mass and hence severity in falciparum malaria.

Malaria is caused by parasites of the genus

It is possible under the microscope to see the number of parasites in the circulating red blood cells but hard to measure how many are inside red blood cells stuck in the small blood vessels at any one time. Knowing the number of parasites blocking up the blood vessels might give a better idea of how severe the disease a patient has. An indirect measure of the number of unseen parasites in the body is a protein, PfHRP2, which the parasites produce and which is released into the blood when the red blood cells split.

They measured the amount of PfHRP2 in the blood of 337 adult patients with

Further work will need to be done to reproduce these findings in other groups of people with malaria. However, estimating the total number of parasites in this way may make it possible to predict more accurately the likely severity of a person's disease.

The World Health Organization has a set of Web pages on malaria:

MedlinePlus has an interactive tutorial on malaria:

Histidine-rich protein 2 (PfHRP2) is a 30-kDa protein produced by

Sequestration of parasitised erythrocytes in the second half of the asexual life cycle (mature trophozoite and schizont stages) in the microvasculature of vital organs compromises the microcirculation, and is a central feature in the pathogenesis of falciparum malaria. Peripheral blood parasitaemia is very widely used to assess disease severity in malaria, but it is only a weak predictor of mortality in falciparum malaria, as the less pathogenic circulating stages can be counted whereas the more pathogenic sequestered mature parasitised erythrocytes are not seen and therefore not counted by the microscopist. These sequestered parasites secrete PfHRP2 into the plasma, and PfHRP2 is liberated at schizont rupture. The plasma concentration of this protein might therefore provide a better estimate for the patient's total parasite biomass, and hence be an accurate prognostic indicator. In a recent study we measured PfHRP2 quantitatively in synchronized

In total 170 patients with uncomplicated malaria and 167 patients with severe malaria who participated in antimalarial treatment studies in Sangklaburi Hospital in western Thailand and in Mae Sot Hospital in northwestern Thailand were included in the study. These are low, seasonal transmission areas. Severe disease is seen in patients of all ages. Disease severity was classified using a modification of definitions employed by Hien et al. [

All samples were tested with the malaria Ag Celisa kits (Cellabs, Sydney, New South Wales, Australia) employing a sandwich ELISA. These kits utilize a monoclonal-antibody-based assay specific for

In our previous study we showed that PfHRP2 is secreted in a stage-dependent manner by parasitised erythrocytes. In in vitro studies of four carefully synchronized cultures, the median (range) amount of PfHRP2 secreted per parasite per erythrocytic cycle was 5.2 × 10^{−15} g (1.1 × 10^{−15} to 13.0 × 10^{−15} g). A median of 89%, or 4.6 × 10^{−15} g, of the total PfHRP2 was liberated at schizont rupture; the remaining 11%, or 0.6 × 10^{−15} g, was secreted almost entirely in the second half of the 48-h erythrocytic cycle [

Since the in vivo plasma elimination kinetics of PfHRP2 affects the relationship between plasma PfHRP2 concentrations and parasite biomass, the kinetics of PfHRP2 was studied in 13 adult patients with falciparum malaria admitted in the Bangkok Hospital for Tropical Diseases, Bangkok, Thailand, ten of whom fulfilled the criteria for severe disease [

This information was used to construct a model to derive parasite numbers from the plasma PfHRP2 concentrations (^{−15}_{d},_{d}_{d}

Total PfHRP2 derives from the amount produced by the generation present in that cycle and the amount produced at schizont rupture of the previous cycle (broken lines). The concentration accumulated from previous production is added to this (black lines). PfHRP2 produced in previous cycles will decline over time (dotted lines). Values chosen for the parameters in this illustration were as follows: Hct, 0.35; body weight, 50 kg; and parasite multiplication factor, eight.

As assessed in the pilot study described above, PfHRP2 elimination followed a first-order process, with a half-life (_{R})

In the second half of the subsequent cycle, during the trophozoite and schizont stages, a total amount of 0.6 × 10^{−15} g of PfHRP2 per parasite will be released into the circulation by the newly infected erythrocytes. This production was assumed to be at a constant rate (1.2 × 10^{−15} g per parasite per cycle time) in the second half of the cycle. With time expressed as units of asexual cycle length and the elimination constant _{TS}

where ^{−15}

If _{0} is the concentration of PfHRP2 derived from the current cycle, _{0}_{R}_{0} = _{R}_{TS}_{0}
) will thus be the area under the concentration–time curve divided by the time span of the erythrocytic cycle of the parasite generation present at the moment of blood sampling. For one cycle from

Substituting equations

However, PfHRP2 accumulated from the erythrocytic cycles before the cycle during which the blood sample was taken will also contribute to the observed concentration of PfHRP2, because the elimination half-life exceeds the asexual cycle length. If _{1}
is the concentration of PfHRP2 derived from the cycle previous to the cycle at the moment of blood sampling, the amount of PfHRP2 (_{1}
) produced in the previous cycle will be _{0}/^{−k}(_{0}/

For the ^{th} previous cycle, the formula to calculate the contribution to the observed concentration of PfHRP2 can be generalized by induction to

The total expected PfHRP2 concentration observed in a peripheral blood sample (_{obs}
) can thus be expressed as

which can be solved to

Substituting

Rearrangement of _{tot}

For the calculations of total body parasite biomass, an in vivo multiplication rate of eight was assumed. This is the average derived multiplication rate observed at detectable parasitaemias in patients with acute malaria in experimental infections before treatment [_{tot})_{obs}

_{d}^{−3} × body weight (in kilograms), equalling the estimated plasma volume, so that

The total circulating number of parasites _{cir})

where

The estimated number of sequestered parasites was calculated as the difference between the estimated total parasite biomass and the total circulating parasite biomass.

The model was subjected to uncertainty and sensitivity analysis with the following parameters as variables: (a) multiplication rate ^{−15} g and a standard deviation of 2.0 × 10^{−15} g (from [_{d}^{−6} g/l. Using these parameters 10,000 simulations were performed using the S-PLUS mathematical program (Insightful, Seattle, Washington, United States), with the predicted total parasite biomass as outcome. This showed that the predicted parasite biomass was log-normally distributed with a geometric mean of 2.9 × 10^{12}. The coefficient of variation of the log-transformed outcome was 3%, indicating a high level of consistency.

The partial rank correlation coefficients between each parameter and the outcome of the model were 0.64, −0.10, and −0.48 for multiplication rate, PfHRP2 half-life, and the amount of PfHRP2 secreted per cycle, respectively. This indicates that multiplication rate was the most influential factor affecting the total parasite biomass estimate, followed by the amount of PfHRP2 secreted per cycle. The variation in PfHRP2 half-life had only a small effect on the calculations. To illustrate the impact of the multiplication rate on the model, ^{−3} g/l, Hct of 0.35%, and a body weight of 50 kg at different parasite multiplication rates.

Values chosen for the parameters were as follows: PfHRP2 concentration, 1,000 μg/l; Hct, 0.35; and body weight, 50 kg.

Data were analysed using SPSS for Windows release 10.05 (SPSS, Chicago, Illinois, United States). Continuous variables that were not normally distributed were log-transformed. The laboratory findings in the uncomplicated and severe groups were assessed using Student's

The lowest limit of detection of purified PfHRP2 was 1.5 × 10^{−6} g/l. The titration curves were similar when normal human plasma or PBS-TWEEN was used as the diluent. The mean (95% CI) plasma PfHRP2 concentration in 337 patients with falciparum malaria was 8.4 × 10^{−4} g/l (5.7 × 10^{−4} to 11.1 × 10^{−4} g/l).

A total of 337 adult patients with falciparum malaria were enrolled over a period of 10 y. Patient characteristics are summarised in

Applying the model described above, the peripheral blood plasma concentration of PfHRP2 was used to estimate the total body parasite burden in 337 adult patients with falciparum malaria, assuming a uniform in vivo multiplication rate of eight (^{11} (95% CI 5.8 × 10^{11} to 8.5 × 10^{11}) parasites/body (

When the numbers of sequestered parasites were calculated (by subtraction) a negative value was obtained in 22% of the patients; in these cases patients were assumed to have very few or no sequestered parasites. The median number of sequestered parasites obtained in this way for all malaria cases was 2.5 × 10^{11} (interquartile range 4.7 × 10^{9} to 1.5 × 10^{12}) parasites/body.

The number of sequestered parasites was also assessed in relation to the parasite stage in the peripheral blood smear. We have reported previously that in patients with severe malaria a predominance of mature stages (trophozoites and schizonts) in the peripheral blood (>10^{4}/μl) is associated with a fatal outcome, presumably because this reflects a stage distribution of more mature parasites composing the total parasite burden and thus a greater sequestered parasite biomass [^{4}/μl mature-stage parasites in the peripheral blood, the number of sequestered parasites in patients with severe malaria (median [interquartile range]) was four times higher if mature-stage parastites predominated (^{12} (2.5 × 10^{11} to 5.4 × 10^{12}) parasites compared with 4.0 × 10^{11} (6.7 × 10^{9} to 2.1 × 10^{12}) parasites if mature-stage parasites did not predominate (_{s}

The estimated total parasite biomass increased in proportion to severity of the disease.The geometric mean (95% CI) parasite load was six times lower in patients hospitalised without evidence of severe malaria than in patients with severe malaria: 2.8 × 10^{11} (2.3 × 10^{11} to 3.5 × 10^{11}) versus 1.7 × 10^{12} (1.3 × 10^{12} to 2.3 × 10^{12}) parasites/body (^{12} (95% CI 1.9 × 10^{12} to 6.3 × 10^{12}) versus 1.5 × 10^{12} (95% CI 1.2 × 10^{12} to 2.0 × 10^{12}) parasites/body (^{10} (6.7 × 10^{9} to 4.1 × 10^{11}) compared to 9.1 × 10^{11} (6.1 × 10^{10} to 3.2 × 10^{12}) parasites/body (Mann-Whitney ^{12} (4.3 × 10^{11} to 1.4 × 10^{13}) versus 7.6 × 10^{11} (1.2 × 10^{10} to 2.7 × 10^{12}), but this difference was of borderline statistical significance (Mann-Whitney

Plasma PfHRP2 concentrations (squares) in peripheral blood samples from 170 patients with uncomplicated malaria, 139 patients with severe malaria who survived, and 28 patients who died. For comparison the calculated circulating parasite biomass is also displayed (circles); this was calculated from the parasitaemia (per 1,000 red blood cells) in a peripheral blood sample and the estimated total red blood cell mass (see text for formulas).

^{12} (2.0 × 10^{12} to 4.1 × 10^{12}) versus 1.3 × 10^{12} (0.9 × 10^{12} to 1.8 × 10^{12}) parasites/body (Student's ^{12} parasites/body, interquartile range 9.4 × 10^{10} to 5.6 × 10^{12}) than in those with an admission lactate concentration below 5 mmol/l (median 5.1 × 10^{11} parasites/body, interquartile range 9.1 × 10^{9} to 2.0 × 10^{12}, Mann-Whitney _{s}

Of the severe malaria patients, 22 had renal failure, defined as a plasma creatinine above 265 μmol/l and a diuresis of less than 400 ml/24 h [_{10} total parasite biomass (Pearson's method, _{10} total circulating number of parasites (

A logistic regression model was constructed with survival as the dependent variable and with the estimated total parasite biomass and previously described prognostic criteria in severe disease as independent variables [

It is known from laboratory studies that cytoadherence via the main adhesion molecule PfEMP1 begins at approximately 12 h of parasite development under febrile conditions, and 50% of the maximum effect is obtained at approximately 14–16 h of development [

If the time of admission to hospital and stage of parasite development (in hours) are unrelated, then the overall ratio of circulating parasites _{cir})_{tot})_{cir},

But the parasite numbers are usually expanding, particularly in uncomplicated malaria before treatment. In the present model we have assumed a multiplication rate of eight per cycle for preceding cycles. If the parasite age distribution is normally distributed with a standard deviation of 4 h, as estimated previously [

If applied to the data from the patients in this series and this model, then with the assumptions above, the population mean parasite age at sequestration _{cir})

and for severe malaria is

The estimate in severe malaria is very close to the value observed in the laboratory. But in severe malaria the next parasite cycle may not sustain a multiplication rate of eight. For a multiplication rate of one this value becomes 17 h. Values between 14 and 17 h are compatible with laboratory observations, but the estimate of 23 h for patients hospitalised with uncomplicated malaria is significantly different from the value observed in ex vivo studies. As it is very unlikely that the age of parasites when they sequester is truly different between the two groups, this apparent excess of circulating parasites in uncomplicated malaria suggests that the assumption of an admission to hospital unrelated to stage of parasite development is incorrect in this group. This suggests that schizogony and the consequent pathological reaction to it are important in stimulating patients with uncomplicated malaria to come to hospital, whereas referral of patients with severe malaria is unrelated to the stage of development of their infecting parasite population.

In this study we propose a model to estimate total parasite biomass using quantitation of a parasite-derived product (PfHRP2) that is predictably released into peripheral blood plasma in acute falciparum malaria. The estimated total parasite biomass was clearly associated with disease severity and outcome in univariate analyses. In a logistic regression analysis with outcome as dependent variable, the parasite load estimates did not predict disease severity better than conventional measures:GCS, plasma lactate, and serum creatinine outweighed the contribution of parasite load to the regression model, suggesting a close causal relationship between these variables. The estimated total parasite biomass was also associated with other well-established markers of severity. In contrast with this, peripheral blood parasitaemia and the derived total number of circulating parasites were not associated with disease outcome, nor with other important measures of severity such as admission plasma lactate concentrations. It should be noted that some of the criteria defining severe disease do include the level of the peripheral blood parasitaemia, which is variably related to total biomass, although in the model peripheral parasitaemia was not used in the calculations of parasite biomass. Pre-treatment with antimalarial drugs affecting PfHRP2 production cannot explain the differences in the estimated total parasite biomass between patients with severe versus uncomplicated malaria: documented pre-treatment was relatively rare (only seven out of 337 patients were pre-treated with an effective antimalarial drug), and this did not differ between the groups.

The positive association between sequestered parasite biomass and disease severity fits with the widely accepted view that the sequestration of erythrocytes containing the mature forms of the parasite in the microvasculature of vital organs is the central pathological process in falciparum malaria. The greater the number of sequestered parasites, the more severe is the disease. The cytoadherence of parasitised erythrocytes to the endothelial lining of the microcirculation is very efficient. Mature forms of the parasite are rarely seen in the peripheral blood smear used to assess the patient, whereas they are central to pathology. Overrepresentation of late stages in the peripheral blood smear is a prognostic factor for fatal outcome, because it represents a larger sequestered parasite biomass [

The calculation of the sequestered biomass also revealed some limitations of the model we used, since in 22% of patients a negative value was calculated. This is not unexpected given that estimates for total parasite biomass and circulating parasite biomass derive from completely different parameters, and also that infections can be very synchronous [^{−15} and 11.6 × 10^{−15} g. The antigenicity of PfHRP2 is not constant among parasite isolates because of variation in the expression of antigenic motifs. The calculations also assume a parasite multiplication factor of eight, which was derived from observations in early studies with experimental infection of humans with _{d})_{d},_{d}_{d}

Despite all these potential shortcomings, estimates of the total parasite load derived from the plasma PfHRP2 concentrations were within the range expected and correlated well with disease severity. In clinical studies of severe malaria, measurement of plasma PfHRP2 concentrations may be useful as a research tool to stratify patients by their parasite load.

In summary, this study shows that quantitative measurements of plasma PfHRP2 in patients with falciparum malaria can be used to estimate the total parasite biomass, a parameter pivotal in the pathophysiology of the disease. This calculated total parasite biomass is associated with clinical measures of the severity of the disease.

Scatterplot showing the correlation between the sequestered parasite biomass (as a percentage of the total parasite biomass) and the percentage of late stages (trophozoites and schizonts) in an admission peripheral blood slide in 337 patients with falciparum malaria. The sequestered and total parasite biomass were derived from plasma PfHRP2 concentrations as discussed in the text (Spearman correlation, _{s}

(25 KB DOC).

Scatterplot showing the correlation between the PfHRP2-derived sequestered parasite biomass on admission and admission plasma lactate concentrations in 337 patients with falciparum malaria (Spearman correlation, _{s}

(28 KB DOC).

We thank the directors and staffs of Sangklaburi Hospital and Mae Sot Hospital. We also thank Dr. Wirongrong Chierakul, Dr. Ronatrai Ruangveerayuth, Dr. Brian Angus, Miss Boongong Pimsa-ard, Miss Forradee Nuchsongsin, and Miss Juntima Sritabal for their assistance, and Associate Professor Wichai Supanaranond for support and encouragement. We are grateful to Dr. David Sullivan for provision of PfHRP2 and PfHRP3 standards. This study was part of the Wellcome Trust–Mahidol University Oxford Tropical Medicine Research Programme, funded by the Wellcome Trust of Great Britain. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

confidence interval

Glasgow Coma Score

hematocrit

Histidine-rich protein 2