Sl2 and McCb of the Swain-Langley (Sl) and McCoy (McC) blood group antigens of the complement receptor 1 (CR1) may confer a survival advantage in the setting of Plasmodium falciparum malaria, but this has not been demonstrated.It has been hypothesized that the African alleles To test this hypothesis, children in western Kenya with severe malaria-associated anaemia or cerebral malaria were matched to symptomatic uncomplicated malaria controls by age and gender. Swain-Langley and McCoy blood group alleles were determined by restriction fragment length polymorphism and conditional logistic regression was carried out.Sl2/2 genotype were less likely to have cerebral malaria  than children with Sl1/1. In particular, individuals with Sl2/2 McCa/b genotype were less likely to have cerebral malaria  than individuals with Sl1/1 McCa/a.No significant association was found between the African alleles and severe malaria-associated anaemia. However, children with Sl2 allele and, possibly, the McCb allele evolved in the context of malaria transmission and that in certain combinations probably confer a survival advantage on these populations.These results support the hypothesis that the  Plasmodium falciparum malaria is responsible for most of the more than one million deaths that occur each year from malaria infection in Africa [n Africa . Most ofn Africa . The patn Africa -7 suggesMr from 190 to 280 kDa. It is found on erythrocytes and most leukocytes and it is divided into three to four long homologous repeat regions (LHRs) and 27 to 30 short consensus repeats (SCRs), also known as complement control protein repeats (CCPs) [P. falciparum erythrocyte membrane protein 1 (PfEMP-1) [P. falciparum late stage parasites bind to uninfected erythrocytes in vitro and has been associated with cerebral malaria in several African studies [CR1 is a protein ranging in s (CCPs) . TogethePfEMP-1) . The int studies ,12.The CR1 gene exhibits a number of polymorphisms. There are several size variants which are felt to be the result of unequal gene crossover . The mosSl2 and McCb alleles may confer a survival advantage in the face of diseases such as malaria. In support of this hypothesis Sl -1,2 erythrocytes were found to rosette less in vitro than Sl 1,-2 erythrocytes [Sl2 or McCb and resistance to severe malaria in The Gambia, West Africa [Sl2 does confer an advantage in the setting of malaria infection.The study of the Sl and McC blood group antigens may offer further clues as to the role of CR1 in the pathogenesis of severe malaria. The phenotypic absence of these antigens, designated Sl -1,2  and McC, Kisumu, Kenya. The NPGH catchment area is the malaria holoendemic region of the Lake Victoria basin in western Kenya, where most individuals are of the Luo ethnic group. Because CM is uncommon in the Lake Victoria basin, CM cases were recruited from the pediatric ward of the Kisii District Hospital (KDH), as well as from the NPGH. KDH is located in the highlands of western Kenya where transmission is seasonal and consequently receives many more CM cases than the NPGH [P. falciparum parasitaemia by Giemsa-stained blood smear and a Blantyre coma score of ≤ 2 [P. falciparum and an axillary temperature ≥ 37.5°C or, in the absence of the latter, two of the following signs or symptoms: nausea/vomiting, irritability, poor feeding, myalgias or headache. Children were excluded from participation if there was evidence of other concomitant serious infections  or chronic illness. All children with suspected CM underwent a lumbar puncture to exclude meningitis and were enrolled if the results of Gram stain and culture were negative. In addition, because some of our studies also included the measurement of erythrocyte complement regulatory proteins, children were excluded if they had a history of blood transfusion in the three months preceding enrolment to avoid the influence of donor erythrocytes.Participants were recruited under human use protocols approved by the Human Subjects Research Review Board, Office of the Surgeon General, US Army, and the Ethics Review Committee of the Kenya Medical Research Institute, Nairobi, Kenya. All procedures were in accordance with the Helsinki Declaration. The study had a matched case-control design. The demographics of some of the study participants as well as the inclusion/exclusion criteria have been described before -7. SMA cthe NPGH . The pree of ≤ 2 , lastingSl1/Sl2 and McCa/McCb Knops blood group alleles result from single nucleotide polymorphisms that cause specific amino acid changes[CR1 exon 29 by PCR. The amplification reactions were carried out on ~500 ng of genomic DNA in a 100 μl final volume containing 1× GeneAmp PCR Buffer II , 2.5 mM MgCl2, 200 μM each dNTP, 0.2 μM each primer and 5 U AmpliTaq Gold® DNA Polymerase . After 9 min of initial denaturation at 95°C, the thermocycling program used consisted of 1 min denaturation at 94°C, 1 min annealing at 58°C, and 1 min extension at 72°C for 44 cycles, followed by a final extension of 10 min at 72°C. For RFLP analysis, 28 μL of each PCR product was digested with either MfeI , for the detection of Sl1/Sl2, or BsmI (New England Biolabs), for the detection of McCa/McCb, and the restriction fragments were resolved by agarose gel electrophoresis as previously described [A whole blood sample obtained at enrolment, and prior to any blood transfusion, was used to extract DNA and/or blotted onto filter papers for later extraction. Personnel who were unaware of the group assignments of the study participants carried out DNA extraction, amplification and interpretation of restriction fragment length polymorphisms (RFLPs) patterns. DNA was extracted from whole blood using the QIAamp DNA blood extraction protocol . DNA extraction from filter papers was performed using saponin and Chelex as previously described . Once exd changes in exon d changes. Brieflyescribed .All analyses were done using SPSS version 11.5 . Chi-square tests were performed to compare the observed and predicted frequencies of genotypes based on allelic frequencies in different ethnic groups. Conditional logistic regression based on matched pairs and adjusted for ethnic groups was carried out for each single locus (Sl and McC) and for the combination of the two loci. Thus, each regression model included terms both for genotype and ethnic group. All tests were two-sided with α = 0.05.Table Sl2 and McCb alleles were more common in The Gambia [e Gambia , Mali [1e Gambia  and westSl2 or McCb alleles confer resistance or susceptibility to severe malaria compared to the Sl1 and McCa alleles, conditional logistic regression of the individual genotypes at each locus was carried out using Sl1/1 or McCa/a as reference . On the other hand, individuals with the Sl2/2 genotype were less likely to have cerebral malaria than individuals with Sl1/1 . This finding was independent of the hospital site since inclusion of this variable in the model did not affect the results. There was no significant effect of the McCa/b or McCb/b genotypes, when averaged over the different Sl alleles, on resistance or susceptibility to CM.In order to explore whether the ce Table . There wSl1/1 McCa/a genotype as reference  decreased from Sl1/2 to Sl2/2, suggesting a gene dose effect. The strongest association was seen with genotype Sl2/2 McCa/b . Interestingly, heterozygosity at both loci or homozygozity for Sl2 and McCb did not show any significant benefit.In order to determine the effect of the different genotype combinations at the Swain-Langley and McCoy loci on the susceptibility to severe malaria conditional logistic regression was carried out using the ce Table . Only siSl2/2 genotype that confers the Sl -1,2 phenotype have decreased susceptibility to CM compared to individuals with the Sl1/1 genotype. This finding was independent of ethnicity, of the genotype at the McC locus and of the hospital site where the cases and controls were recruited. Among the combined genotypes, a trend of increasing benefit was observed in the background of McCa/a from Sl1/2 to Sl2/2, which is consistent with a gene dose effect. Although the level of statistical significance may be influenced by a larger sample size in the Sl2/2 category, the association nevertheless appears strongest with the acquisition of one McCb allele , whereas the McCb allele is the result of the substitution of the acidic amino acid glutamic acid for the basic amino acid lysine at position 1590 (K1590E) [Sl2 and McCb, did not offer any significant advantage.The mechanism by which the (K1590E) . These m(K1590E) . TherefoAlthough the current expectation is that CR1 may influence the development of severe malaria by virtue of its function as a regulator of the complement cascade on RBCs or by its direct interaction with the infected RBCs leading to rosette formation, CR1 may exert its effect on malaria in other ways that are not yet understood. In addition to being present on RBCs, CR1 is also present on follicular dendritic cells, macrophages and T and B lymphocytes and, therefore, may also have immunoregulatory functions that affect the development of immunity against malaria . Mice deFurther evidence that the role of CR1 in the pathogenesis of severe malaria may not be as expected is found in a recent case-control study in Papua New Guinea that aimed to determine whether there was an association between individuals who had the low CR1 expression allele (L) and resistance to severe malaria . ContrarThe results obtained in the study presented here have biological significance and are further supportive evidence of the importance of CR1 in the pathogenesis of severe malaria. Whatever the mechanism is by which CR1 is involved in the pathogenesis of malaria, knowledge of which alleles are associated with resistance or susceptibility to severe malaria will make it possible to observe the relationship between structure and function and susceptibility to severe malaria.Sl2 allele and, possibly, the McCb allele have evolved in the context of malaria transmission in Africa and that in certain combinations probably confer a survival advantage to malaria endemic populations.The results support the conclusion that the Vandana Thathy, assisted by Bernard Guyah, optimized and carried out the PCR, performed the restriction enzyme digestions and interpreted the RFLP results. JoAnn M. Moulds developed the PCR-RFLP assay. Walter Otieno supervised the clinical evaluations of the study participants. José A. Stoute was the principal investigator who designed the study, wrote the protocol and drafted the original manuscript that was reviewed and edited by all authors.


Plasmodium parasitaemia, but may result from long-term exposure to the parasite. Studies of hepatosplenomegaly associated with Schistosoma mansoni infection and exposure to Plasmodium infection indicate that differences that occur over 1–2 km in levels of Plasmodium transmission are related to the degree of exacerbation of hepatosplenomegaly and that Plasmodium falciparum schizont antigen (Pfs)-IgG3 levels may be a marker for the differing levels of exposure.Amongst school-aged children living in malaria endemic areas, chronic morbidity and exacerbation of morbidity associated with other infections are often not coincident with the presence or levels of To investigate the validity of Pfs-IgG3 measurements as a tool to assess these comparative exposure levels on a microgeographical scale, cross-sectional community surveys were conducted over a 10 × 6 km study site in Makueni District, Kenya, during low and high malaria transmission seasons. During both high and low malaria transmission seasons, thick blood smears were examined microscopically and circulating Pfs-IgG3 levels measured from dried blood spot elute. GIS techniques were used to map prevalence of parasitaemia and Pfs-IgG3 levels.Microgeographical variations in prevalence of parasitaemia were observed during the high but not the low transmission season. Pfs-IgG3 levels were stable between high and low transmission seasons, but increased with age throughout childhood before reaching a plateau in adults. Adjusting Pfs-IgG3 levels of school-aged children for age prior to mapping resulted in spatial patterns that reflected the microgeographical variations observed for high season prevalence of parasitaemia, however, Pfs-IgG3 levels of adults did not. The distances over which age-adjusted Pfs-IgG3 of school-aged children fluctuated were comparable with those distances over which chronic morbidity has previous been shown to vary.Age-adjusted Pfs-IgG3 levels of school-aged children are stable and when mapped can provide a tool sensitive enough to detect microgeographical variations in malaria exposure, that would be useful for studying the aetiology of morbidities associated with long-term exposure and co-infections. Plasmodium infection can be responsible for, or along with co-infections, can contribute to, the development of more subtle morbidities such as chronic hepatosplenomegaly and mild/moderate anaemia. These more subtle morbidities are often not directly correlated with the presence or levels of parasitaemia [School-aged children in areas of stable malaria transmission are often immune to the severe complications attributable to the infection such as cerebral malaria and severe anaemia, as immunity to severe malaria develops after as few as one or two previous attacks . School-sitaemia -5.Plasmodium falciparum endemic areas [Schistosomiasis mansoni is also associated with childhood hepatosplenomegaly, in an intensity dependent manner. However, it has a higher prevalence in malaria endemic areas [P. falciparum schizont antigen (Pfs)-IgG3 [S. mansoni adult worm antigen (SWA), its production is driven by P. falciparum infection rather than S. mansoni infection [P. falciparum is known to vary on a microgeographical scale in relation to mosquito breeding sites, due to mosquito host-seeking behaviour [P. falciparum infection. However, the decline of Pfs-IgG3 levels with distance of residence from the river described by Booth and colleagues, could not be confirmed as exposure-related, as neither parasitological nor entomological data were available.Chronic hepatosplenomegaly, with the enlarged organs having a firm consistency, has been widely reported amongst school-aged children in ic areas ,6. Schisic areas , and hasfs)-IgG3 . Althougnfection ,10. In, nfection . As tranehaviour -14, thisPlasmodium infection on a microgeographical scale. Such characteristics would allow circulating Pfs-IgG3 to be used as a marker for assessing the contribution of chronic exposure to malaria towards chronic, subtle morbidities that do not necessarily coincide with current parasitaemia. To achieve this, community wide surveys were conducted in an area with a complex network of water bodies and Pfs-IgG3 levels were measured during both the low and high transmission seasons. Microgeographical fluctuations in Pfs-IgG3 were compared with spatial patterns of peripheral blood smear detectable parasitaemia at the same time points. Age-adjusted Pfs-IgG3 levels in children, but not adults, were found to be a more stable microgeographical marker of relative exposure than parasitaemia, pointing to the potential usefulness of the Pfs-IgG3 marker in studies of chronic, subtle morbidities that may be caused or exacerbated by P. falciparum and/or interactions with co-infecting pathogens.Here we examine if finger-prick serum Pfs-IgG3 levels are (a) more temporally stable than blood smear detectable parasitaemia and (b) can be used, in areas with complex patterns of surface water distribution, to estimate relative exposure to P. falciparum is the most prevalent species, but P. malariae is also present. The transmitting mosquito vectors are A. funestus and A. gambiae, both are found to the east of the study area, while A. gambiae is the predominant vector in the west. Entomological inoculation rates (EIR) are not available for this area but it is considered to be meso-endemic. The study site was 10 km by 6 km, with the volcanic Chuylu Hills to the Northwest. Yumbuni, the community nearest to the Chuylu Hills is situated on lava flows that divert streams underground, so that the only surface water is a short stretch of a permanent stream, a seasonal stream and seasonal ponds, which dry up during the long dry season  occupants per household). Family groups often live within the same compound, and children attend one of 5 primary schools. The area is 800 m above sea level, with seasonal rains typically falling in November/December and April/May, though annual variations can occur, providing conditions suitable for stable but seasonal malaria transmission. All households in Yumbuni and Lower Mangelete were mapped using a Magellan 315 GPS. Signals from at least 5 satellites ensured a positional accuracy of within 5 metres. The stream courses and irrigational canals were mapped by taking co-ordinates at regular intervals (approx. every 100 m). Ponds and points of interest  were recorded. Co-ordinates were downloaded using GPS Utility 4.04  and imported into ArcView  for visualisation and distance calculations. Distances were assigned to individuals using household demography data. Maps were generated using either the prevalence of parasitaemia or the mean antibody OD on a household basis. Households are mapped with a 0.5 km radius and when circles are overlapping, the average prevalence or mean antibody OD is shown.Plasmodium infections was taken at each of two time points: November 2003, a low transmission time point and February 2004, a high transmission time point. The low transmission time point was at the end of a long dry period, which started in May 2003. The high transmission time point was after substantial rains in January 2004. A smear was considered negative if no Plasmodium parasite had been identified within 15 fields of view. Dried blood spots (DBS) were collected on filter papers  at both time points. 1044 individuals  from 344 of the 493 households participated during the low transmission season survey, representing 34.0% of the total population. 973 individuals (age-range 3 to 95-yrs), from 369 of 493 households participated during the high transmission survey, representing 31.7% of the total population. 684 individuals, from 293 households, participated in both surveys. At both time points the sample population differed significantly from the total population in terms of age and sex, as adult males were under represented. There was good compliance amongst school-aged children (5 to 17-yrs), with over 60% of school-aged children participating at one or other time point, and 47.1% participating at both time points. S. mansoni infection intensities had previously been surveyed; participants provided two stool samples and 2 Kato Katz slides [S. mansoni infections and minor ailments. The study received approval from the Kenya Medical Research Institute National Ethical Review Committee.All adults who gave informed consent and all children, for whom their parents or guardians gave consent, were included in cross-sectional surveys. A thick blood smear for identification of Plasmodium falciparum cultures, by centrifugation at 2000 rpm through 60% Percoll . The schizont layer was resuspended at a concentration of 1 × 108 schizonts/ml, aliquoted into cryotubes, freeze-thawed twice and stored at -80°C until use. S. mansoni worm Ag (SWA) was prepared as previously described [The Pfs Ag was prepared as previously described . Brieflyescribed .A pre-study trial comparing Ab levels measured from plasma samples and whole blood spots dried onto filter papers showed that although there was a need for a reduced sample dilution factor with DBS elute, correlations between the two methods of collection were high (r = 0.899). Samples were allocated randomly for individual and survey into 96-well formats. Replicate European plasma samples were added to each plate to ensure standardisation of readings between plates, but were not sufficient in number to define a positive cut-off. One 6 mm diameter disc was punched out from a DBS for each individual study participant and eluted in 100 μl PBS/0.3% TNBP/1% Tween 80/0.02% sodium azide . Samples were shaken at room temperature for 5 min and incubated overnight at 4°C. Supernatants were stored at -80°C until use.o-phenylenediamine (Sigma) and read at a dual wavelength of 360 nm and 490 nm. Specific antibody levels were expressed as the mean OD of duplicate assays.ELISA were carried out in duplicate. 50 μl of 8 μg/ml Pfs Ag, or 50 μl of 10 μg/ml SWA, in bicarbonate coating buffer were coated onto Immulon 2 plates  and incubated overnight at 4°C. Plates were blocked with 1% milk powder . 50 μl of DBS elute diluted 1:10 for IgG3 assays and 1:25 for IgG4 assays was incubated overnight at 4°C. Antigen specific antibodies were detected using biotinylated anti-human IgG3  at a 1:500 dilution, or biotinylated anti-human IgG4  at a 1:2000 dilution, followed by 1:3000 poly-HRP . Assays were developed with 2× 10 transformed and adjusted for age using split linear regression prior to mapping. Loess lines were fitted to scatter plots of age against transformed Pfs-IgG3 to determine at which age to split the linear regression (<= 17-yrs and >17-yrs). Analysis of spatial clustering used SaTScan™ software [Statistical analysis was carried out using SPSS 12 for Windows . Participants were divided into three-age groups . Chi-squared analysis was used to determine differences in malaria prevalence by age and by distance of residence from water bodies. Paired students t-tests were used to analyse longitudinal differences in Pfs-IgG3 levels. Differences in Pfs-IgG3 of individuals by age and by distance of residence from water bodies were analysed by ANOVA with Hochberg GT2 post-hoc analysis, as suitable for groups containing different sample numbers. Pfs-IgG3 levels of individuals with and without detectable parasitaemia were compared by Students t-test. Correlations between Pfs and SWA antibody levels were calculated using Spearman's Rank correlations. Pfs-IgG3 was logP. falciparum infections than adults . The prevalence of parasitaemia was 26.5% in the <5-yr olds, 15.3% in school-aged children (5- to 17-yrs), and 11.3% in adults. During the high transmission season the prevalence of parasitaemia was 42.5% in the <5-year olds, 51.8% in school-aged children, and 42.1% in adults. The prevalence of parasitaemia was not significantly different between <5-yr olds and adults  during the high transmission season, but remained significant between school-aged children and adults .The overall prevalence of peripheral blood smear detectable parasitaemia was 14.0% at the low transmission season time-point and 47.7% at the high transmission time-point. During the low transmission season a significantly greater proportion of <5-yr olds and 5- to 17-yr olds had detectable P. falciparum prevalence were drawn using the prevalence per household . However, spatial trends in transmission were present in the high transmission season . However, prevalence during the high transmission season was significantly greater for individuals living within 1 km of the nearest pond . Although there was a significant difference in prevalence of parasitaemia, with distance from the nearest permanent stream, during the high transmission season , post-hoc analysis indicated that this was due to the higher prevalence amongst individuals who resided 3.5–4 km from the streams. Those who resided 3.5–4.5 km from a permanent stream were the same individuals who lived within a kilometre of a pond. As prevalence of parasitaemia was age-related during the high transmission season, individuals were grouped according to whether they were school-aged (5- to 17-yrs) or adults (>17-yrs). There were insufficient <5-years olds to include them in this further analysis (n = 33 for the high transmission season). The relationship between distance of residence from nearest pond and prevalence of parasitaemia during the high transmission season , but not for adults . When analysis was repeated solely on individuals who participated in both surveys, results were similar (data not shown).In concurrence with the cluster analysis, there was no significant relationship between the distance of an individuals' residence from the nearest pond and prevalence of parasitaemia, during the low transmission season , age-adjusted Pfs-IgG3 levels decreased significantly as distance to nearest water body increased , the only part of the study area where Biophalaria intermediate hosts of S. mansoni were found (authors' unpublished results). This area did not correspond with areas of higher levels of age-adjusted Pfs-IgG3, indicating that the presence of S. mansoni did not influence Pfs-IgG3 levels.SWA-IgG3 and SWA-IgG4 levels were also measured. Pfs-IgG3 levels were highly correlated with SWA-IgG3 levels in this study population during the low and the high transmission seasons, but were weakly correlated with SWA-IgG4 levels Table . SWA-IgGPlasmodium infections, for use in studies of subtle morbidities, such as chronic hepatosplenomegaly, that are often not associated with the presence of peripheral blood detectable parasitaemia, but vary over a microgeographical scale. It was demonstrated that age-group mean Pfs-IgG3 levels were stable between low and high transmission seasons, even though the prevalence of blood smear detectable parasitaemia varied significantly. Low transmission season Pfs-IgG3 was measured in finger-prick samples taken at the end of the dry season, when prevalence of parasitaemia confirmed transmission across the area was low. This indicates that Pfs-IgG3 levels are a more stable marker of exposure than prevalence of parasitaemia. Therefore, even though on a community level, maximum prevalence of detectable malaria parasitaemia is strongly associated with annual EIR [The aim of the present study was to identify a serological marker of accumulative exposure to nual EIR , the sernual EIR  and (c) nual EIR .Pfs-IgG3 levels reached a plateau in >17-yr olds, suggesting that the response reaches saturation in adults. This observed saturation of the IgG3 response in >17-yr olds resulted in a loss of statistical significance, in the relationship between age-adjusted Pfs-IgG3 and distance of residence from nearest water body. A spatial trend of decreasing prevalence of parasitaemia with distance of residence from nearest seasonal pond during the high transmission season was also not significant for adults. This, along with the significantly lower prevalence of parasitaemia in adults, during both low and high transmission seasons, indicates that spatial patterns in exposure cannot be serologically determined, using the present technique, from surveys of immune adults. Response saturation has previously been reported as a caveat to serological markers of exposure to malaria over macrogeographical distances . This isA. gambiae is the predominant vector, with the distances that entomological differences have been observed, as a capture study in Western Kenya showed that 90% of adult A. gambiae mosquitoes are found in households located within 300 m of the nearest larval breeding site [Plasmodium infections would be informative.For school-aged children, in whom antibody levels were still increasing, age-adjusted Pfs-IgG3 levels declined sharply with distance from potential mosquito breeding sites. The distances over which a significant decrease is observed is comparable, particularly in relation to the seasonal streams in the west where ing site , and stuing site ,23. MappPlasmodium infections, could not be determined from the present study, due to small number of children in this age group who participated. However, it is known that IgG3 responses to malaria antigens are the slowest to develop, with predominance of IgG3 over IgG1 to MSP-2, an antigen that preferentially induces IgG3 responses, not being fully established until late adolescence, and IgG1 being the predominant response in very young children (<2 yrs-age) [Assessment of serological markers of exposure in children <5-yrs would also be beneficial, particularly as it is known that within this age group, levels of transmission can have a great impact on the incidence and type of severe complications that occur due to malaria . Whetheryrs-age) ,26. In yPlasmodium and S. mansoni infections is known to occur [Finally, even though cross-reactivity between to occur ,10, SWA-to occur -32, wereSchistosoma species, that have their own complex spatial patterns of transmission.The present study shows that Pfs-IgG3 levels can be used during both the low and high transmission seasons to detect variation in exposure, particularly if population means are used, as levels may remain stable on a population level while fluctuating in individuals; and, important for use in studies of morbidity related to chronic exposure, Pfs-IgG3 levels are more temporally stable than prevalence of parasitaemia. Age-adjusted Pfs-IgG3 levels of school children were however, sensitive to fluctuations in exposure over short distances; distances that were comparable with those over which chronic morbidity varies  and deteThe author(s) declare that they have no competing interests.SW participated in field activities, undertook the serology, analysis and drafted the manuscript. MB participated in the design of the study and participated in fieldwork. FMJ prepared the antigens and participated in the serology. JKM, GK, HCK, JHO and EM participated in the planning and execution of field activities. BJV and DWD participated in the design of the study and critically revised the manuscript. All authors have read and approved the manuscript.The pre-publication history for this paper can be accessed here:


Very high dose cyclophosphamide (Cy) (500-600 mg kg-1) given by single bolus i.p. injection in mice caused acute deaths in all animals within 48 h of treatment (0/10 survivors). These acute deaths were abolished or very significantly reduced if Cy was administered in divided dosage over 8 h (10/10 survivors) or 12 h (14/15 survivors). The effect was maintained at doses of up to 600 mg kg-1 administered in divided dosage over 24 h (15/15 survivors). In 2 human small cell carcinoma xenografts anti-tumour efficacy was not diminished by divided dosage. In both xenografts tumour growth delay was enhanced, although not significantly so, when treated with divided dosage compared with single dose, and in one of the xenografts 3 complete remissions were achieved with divided dosage compared with none after single dosage. It is postulated that the underlying mechanism concerns diminished cardiotoxicity. These results may have significance in clinical studies investigating very high dose Cy.


The World Health Organization estimates that malaria kills an African child every 30 seconds. Many of these children die because they develop severe anemia (a deficiency of red blood cells). As many as 5 million cases of severe malarial anemia occur in African children every year, and 13% of these cases are fatal. Turning the statistics around, more than half of young children in African countries where malaria is endemic (constantly present) are anemic. Nutritional deficiencies and various infections account for some of this disease burden, but malaria is one of the most important factors contributing to anemia.The malaria parasite destroys red blood cells  as part of its life cycle, releasing hemoglobin (Hb)—an iron-containing protein that carries oxygen around the body—into the circulation. Free Hb can cause oxidant stress, which is itself associated with anemia in malaria. An important modulator of such stress is a serum protein called haptoglobin (Hp), which captures Hb during hemolysis.1Hp allele make only Hp1-1, a homodimeric protein. People with two copies of the2Hp allele (the2/2Hp genotype) make Hp2-2, a large circular polymer, and those with one copy of each allele make the linear polymer Hp1-2 in addition to these two forms. The functional properties of the three Hp forms are somewhat different. In particular, Hp2-2 binds Hb much less tightly than the other forms. Sarah Atkinson and her colleagues reasoned, therefore, that the2/2Hp genotype might be a risk factor for anemia in children in malaria-endemic areas. To test their hypothesis, they measured Hb levels in Gambian children at the start and end of the malaria season, and now report in a new study that, as predicted, the2/2Hp genotype is associated with seasonal childhood anemia in this population.Hp exists in three molecular forms that are genetically determined by two variants  of a single gene. People who have two copies of theHp genotypes, assessed their blood Hb and serum Hp concentrations and iron status, and determined whether they were infected with malaria parasites. These variables were re-measured at the end of the malaria season. In addition, the researchers determined two other genetic polymorphisms that might influence Hb levels over the malaria season—anHb variant that causes sickle cell anemia(HbS), andglucose-6 phosphate dehydrogenase (G6PD) gene variants associated with hemolytic anemia.Most cases of malaria in The Gambia occur between September and December, so the researchers recruited 780 children aged two to six years from ten Gambian villages in July 2001, determined theirHp genotype. This univariate (single) analysis included 671 children—a few children were not included because of incomplete data. Baseline hb levels were not affected byHp genotype, but the average drop in hb was 8.9 g/l in the 17% of children with the2/2Hp genotype compared with only 5.1 g/l in children with the other genotypes. By contrast, the magnitude of the drop in Hb levels over the season was not affected byHbS orG6PD genotype—two other genetic traits that affect the red blood cells. Because multiple factors influence Hb concentrations , the researchers also did a multiple regression analysis of their data to test the effect of all such factors on Hb levels at the end of the malaria season. There were 565 children who had data complete enough for this more detailed analysis, and, once again, theHp genotype emerged as a risk factor for anemia, even after adjusting for other factors that affect Hb levels.Atkinson and her colleagues first analyzed their study population in terms of theirHp genotype and seasonal childhood anemia may reflect the reduced ability of the Hp2-2 polymer to scavenge free Hb and its bound iron after malaria-induced hemolysis. They also discuss why2Hp, a potentially detrimental allele, should be common in The Gambia, where malaria is endemic.2Hp arose from1Hp about 2 million years ago, and its subsequent spread across the world seems to have been driven by a strong genetic pressure, such as exposure to a life-threatening disease. The authors suggest that malaria may be one of the diseases that helped to select for the2Hp allele; it is possible that the2Hp allele may provide protection from life-threatening malaria, albeit at the expense of impaired hematological recovery from mild and asymptomatic malaria. In a related Perspective , Stephen Rogerson expands on the possible mechanisms of Hp-related anemia, and considers what the wider health implications of this study might be.Atkinson and her colleagues suggest that the association between


Very little clinical research has been conducted on how to manage children with severe malaria, despite it accounting for the deaths of around 1 million children each year in Africa alone.Antimalarial drugs remain the mainstay of treatment , but there is increasing debate around aspects of supportive care and the treatment of complications. No aspect of care has been more controversial in recent years than the initial fluid management of children with severe malaria, particularly given the resource-poor health-care context in which most such children are treated. The debate centres around the role of hypovolaemia  in the pathophysiology of severe malaria. Hypovolaemia has been incriminated as an important cause of metabolic acidosis, which has been shown repeatedly to be associated with a poor prognosis. The key question is whether hypovolaemia contributes to impaired tissue perfusion in severe malaria, contributing to the anaerobic glycolysis and consequent acidosis. Some studies of severe malaria in children have supported this hypothesis by providing indirect evidence  that severely ill patients are commonly hypovolaemic on admission, and that this contributes to the severity of the disease ,2. In feProponents of rapid fluid repletion cite the standards of care applied in resource-rich settings for severely ill children with bacterial sepsis, whilst those advocating caution argue that malaria should be considered differently, particularly given the haemodynamic and circulatory differences from sepsis and the concerns of precipitating or worsening pulmonary or cerebral oedema ,4.It is clear that clinical trials are the only way forward to resolve the debate. There have been several previously published intervention studies, all conducted by Maitland and the Kilifi team on the Kenyan coast, but to date all have been too small and heterogenous to provide conclusive answers.Should children with severe malaria all receive rapid intravenous fluid rehydration? And if so, with what fluid?The largest of these studies did provide, in a sub-group analysis of severely acidotic patients, a tantalising suggestion of a mortality benefit from fluid resuscitation with albumin 4.5%, when compared with saline. But there was no “maintenance fluids only” control group, and as mortality was relatively high in the saline group, a deleterious effect of saline bolus could not be excluded. There is, however, a scientific rationale suggesting that albumin might possibly be beneficial in severe malaria, as it has been shown to have a number of physiological effects other than on colloid oncotic pressure. In particular, there is recent evidence that albumin may be neuroprotective in acute ischemic stroke [Akech et al. have conducted a phase II study  examininp = 0.06). In addition, the authors pool the data from all their trials comparing albumin with other resuscitation fluids, and find that albumin administration is associated with a very significant overall mortality benefit.Though there was no difference between the two groups in terms of the primary outcomes, resolution of shock and of acidosis, there was a suggestion on analysis of the secondary outcomes of a mortality benefit in favour of albumin . Although the safety data are reassuring, the lack of a “maintenance fluids only” control group limits the study's impact on the overall debate over whether aggressive fluid resuscitation should be given at all.In this phase II study, patients were not individually randomised but rather allocated to the treatments in blocks of ten, though it appears from the baseline data that the resulting two groups were evenly matched. This has no implications for the safety data, but puts limitations on the interpretation of the mortality data. In addition, mortality was not a primary endpoint for either this study or any of the previous studies cited in the pooled analysis, so the finding of a mortality benefit from albumin administration should be regarded as hypothesis-generating rather than definitive, despite the impressive Give that severe malaria is such an important disease in terms of morbidity and mortality throughout the tropical world, it is astonishing how few clinical trials have addressed its treatment. This is particularly true for the non-antimalarial-drug aspects of management; few trials have been carried out, and those that exist have often been inadequately powered and of poor quality . No adju


Over nine months follow-up in our original study, there was no evidence that FFM ME-TRAP provided protection against malaria. The incidence of malaria was slightly higher in children who received FFM ME-TRAP, but this was not statistically significant . Although the study was unblinded, another nine months follow-up was planned to monitor the incidence of malaria and other serious adverse events.405 children aged 1–6 yrs were initially randomized to vaccination with either FFM ME-TRAP or control (rabies vaccine). 380 children were still available for follow-up after the first nine months. Children were seen weekly and whenever they were unwell for nine months monitoring. The axillary temperature was measured, and blood films taken when febrile. The primary analysis was time to parasitaemia >2,500/µl. During the second nine months monitoring, 49 events met the primary endpoint  in the Intention To Treat (ITT) group. 23 events occurred among the 189 children in the FFM ME-TRAP group, and 26 among the 194 children in the control group. In the full 18 months of monitoring, there were 63 events in the FFM ME-TRAP group and 60 in the control group . There was no evidence that the HR changed over the 18 months (test for interaction between time and vaccination p = 0.11).Vaccination with FFM ME-TRAP was not protective against malaria in this study. Malaria incidence during 18 months of surveillance was similar in both vaccine groups.ISRCTN88335123Controlled-Trials.com  P. falciparum malaria in 2002 There were 515 million episodes of clinical Although the study was unblinded at 9 months for the primary analysis of efficacy, the analysis plan specified continued surveillance for serious adverse events and malaria for a further period of 9 months.The protocols for this trial and supporting CONSORT checklist are available as supporting information; see The study was randomised, controlled and double blind. Details of ethical approval are described previously 405 children were randomized, and all received at least one dose of vaccine. Children were screened in February 2005, immunised between March 2005 and May 2005, and followed up until February 2006, when the study was unblinded. A further 9 months follow up was conducted on 387 children who were still available, until November 2006. No further cross-sectional bleeds were taken during this time.The participating children were aged 1–6 years old when randomized in February 2005, healthy, and resident in the study area.The study was carried out in Junju sublocation in Kilifi District, on the Kenyan coast, as described previously 7 plaque forming units) followed by MVA ME-TRAP vaccination (1.5×108 plaque forming units), given intradermally. The control was rabies vaccine , administered according to the same timings. Rabies was also given intradermally, at 0.25 IU. Vaccinations were spaced 4 weeks apart (acceptable range 3–5 weeks).The trial vaccination regimen was a candidate prime boost malaria vaccination. Details have been described previously The objectives of this extension of the original Phase 2b trial were to describe the distribution of febrile malaria by vaccination group, and to assess any latent safety issues.Efficacy Plasmodium falciparum parasitaemia greater than 2,500 parasites per ul. Episodes of malaria were identified as described previously The primary endpoint was a clinical episode of malaria, defined as an axillary temperature greater than 37.5 degrees centigrade, with a Full details of randomization have been described previously The nurses who administered vaccinations did not take part in any other trial related procedure, and were subsequently based in Kilifi District Hospital rather than the trial site. They drew up vaccinations according to the instructions in the randomisation envelope, and documented the vaccination in notes that were not available to the investigators until after unblindingAfter the first 9 months monitoring the primary analysis was conducted. A cleaned, locked database was transmitted to the DSMB, and the statistician then transmitted the allocation code to the lead investigator, who then implemented the analysis plan. It was planned to conduct a further analysis of episodes of malaria after a further 9 months monitoring, despite having unblinded the trial. The results (no significant efficacy) were fed back to the study participants, and a strong view was expressed that study participants wished to be told which vaccines children had received. This was done. Continued monitoring was supervised by a second investigator, and the lead investigator played no further part in assessment of malaria episodes or collection of data. The second investigator did not have details of vaccination allocation, neither did the laboratory staff who read blood films. Data was cleaned by the second investigator before being locked, following which analysis was conducted by the lead investigator.The analysis plan was approved by the DSMB. The primary analysis was a log rank test comparing the time to the first or only episode of malaria (defined as fever with parasitaemia above 2500/µL) between the vaccination groups, stratified by age group, ITN (insecticide treated net) use and village, analysed by Intention To Treat. The hazard ratio and 95% confidence interval was estimated by Cox's regression adjusted for the same covariates. Age group was a categorical variable with three levels . Village had 5 levels. ITN use was defined as sleeping under a treated net every night, which had less than three holes into which a finger could comfortably fit.Poisson regression was used to estimate the incidence rate ratio taking into account all malaria episodes, adjusted for the same covariates. A period of 28 days after each malaria episode was deducted from the person time at risk, since individuals were assumed not to be at risk of malaria during this period. No further analysis is planned.In order to assess interactions, data from each individual was split according to monitoring period. An interaction between vaccination and time of monitoring (first 9 months vs second 9 months) was then assessed for poisson regression and for survival analysis. Models with this interaction were compared with models without an interaction term using the likelihood ratio test.405 children were randomized in May 2005, and 383 were still available for follow up after the first 9 months . 333 comThe treatment allocation groups at the start of the second 9 months monitoring were still well balanced with respect to baseline characteristics .Of the 383 children followed up in the second 9 months, 342 were from the original According To Protocol analysis group. All 383 were part of the Intention To Treat group.The primary analysis for this study has already been conducted When analysis was restricted According To Protocol, there were 52 events among 170 children in the FFM ME-TRAP group, compared with 54 among 172 children in the rabies control group .The hazard ratio (HR) for the effect of vaccination, estimated using Cox regression, was 1.2  over the full 18 months of monitoring. The HR during the first 9 months was 1.52 , followed by 0.84  during the second 9 months. When analysis was restricted to ATP, the HRs were 1.06 (0.72–1.56 p = 0.94), 1.31  and 0.72  for the full 18 months, first 9 months and second 9 months monitoring, respectively. The difference in HRs between the two time periods was not statistically significant .During 18 months monitoring of the ITT cohort there were 170 episodes of febrile malaria with parasitaemia >2,500/µl among 383 children. This comprised 0.35 episodes per Person Year At Risk among children given FFM ME-TRAP, and 0.29 among children given the control vaccination.The Incidence Rate Ratios for the effect of vaccination were 1.06  during the first 18 months, 1.58  during the first 9 months and 0.8  during the second 9 months. Among the ATP cohort the IRRs were 1.06 , 1.36  and 0.67  for the full 18 months, first 9 months and second 9 months monitoring, respectively. The likelihood ratio test for the interaction between vaccine group and time period gave p = 0.051 and p = 0.093 for ITT and ATP analysis respectively.8 Further serious adverse events were detected during the second 9 months of follow up. Among FFM ME-TRAP vaccinees there were episodes of pneumonia, dysentery, malaria with multiple seizures and a snake bite which required hospital admissions. Among control vaccinees there were two episodes of gastroenteritis with dehydration, an episode of malaria with multiple seizures and a Stevens Johnson reaction (associated with co-trimoxazole use). All adverse events resolved without sequelae, and there were no deaths in either group.We have previously reported the primary analysis after 9 months post-vaccination monitoring for episodes of malaria The primary analysis considers time to first episode. In this analysis children do not contribute further to the analysis after an episode of malaria, which could potentially cause a bias in the estimation of the hazard ratio in the second period. However, similar results were obtained when multiple episodes were analyzed.The primary analysis had already been conducted. The analysis here is therefore considered secondary. Furthermore, these data were acquired after the study had been unblinded. Measures were taken to reduce the impact of this on the integrity of the study; an investigator not involved in the primary analysis oversaw the second 9 months of monitoring, and blood films were read in the laboratory with reference to only study subject numbers without knowledge of vaccination group. The lead investigator who had conducted the primary analysis was not involved in continued follow up, and conducted the analysis presented here after being sent a cleaned database. That no efficacy was seen on the primary analysis was communicated to study participants, and so vaccine allocation was perhaps unlikely to bias health seeking behaviour. A similar number of follow up visits were completed among children allocated to either vaccination , and a similar number presented for assessment of fever between visits , p = 0.58). Nevertheless, a subtle impact on health seeking behaviour cannot be excluded, and our findings here must be treated with appropriate caution.Borderline significance on log likelihood testing for interactions between monitoring period and vaccination was seen. However, this was one of multiple analyses for interactions. The other 3 tests yielded less significant findings, and the study was no longer blind. There is insufficient evidence to conclude there might have been an interaction between vaccination and time . This suggests that the variations in hazard during the monitoring period probably represent chance alone.After the primary analysis of this trial we considered the formal possibility that transforming growth factor β production Protocol S1Protocol Under Which Further 9 Months Follow up was Conducted(4.42 MB PDF)Click here for additional data file.Protocol S2Protocol for ongoing study(4.42 MB DOC)Click here for additional data file.Protocol S3Original protocol(0.31 MB DOC)Click here for additional data file.Analysis Plan S1Analysis Plan for second 9 months follow up(0.03 MB DOC)Click here for additional data file.Checklist S1CONSORT checklist(0.05 MB DOC)Click here for additional data file.


Recent studies have highlighted the over-diagnosis of malaria in clinical settings in Africa. This study assessed the impact of a training programme implemented as part of an intervention trial on diagnostic behaviour of clinicians in a rural district hospital in a low-moderate malaria transmission setting.From the beginning of 2005, a randomized controlled trial (RCT) of intermittent preventive treatment for malaria in infants (IPTi) has been conducted at the study hospital. As part of the RCT, the study team offered laboratory quality assurance, and supervision and training of paediatric ward staff using information on malaria epidemiology in the community. Data on clinical and blood slide confirmed cases of malaria from 2001 to 2005 were extracted from the hospital records.The proportion of blood slides positive for malaria parasites had decreased from 21% in 2001 to 7% in 2005 (p < .01). The proportion of outpatient and inpatient cases diagnosed as malaria ranged between 34% and 28% from 2001 to 2004 and this decreased substantially to 17% after the introduction of the package of training and support in 2005 (p < .01). There was no clear trend in the ratio of blood slide examined versus total diagnosis of malaria.It may be possible to change the diagnostic behaviour of clinicians by rigorous training using local malaria epidemiology data and supportive supervision. Recent studies have highlighted the massive problem of over-diagnosis of malaria in malaria endemic countries -3. Over-This paper reports a case study of rigorous training using local malaria epidemiology data that changed the diagnostic behaviour of clinicians in a rural district hospital in an area of low to moderate malaria transmission.Same District, situated in north-eastern Tanzania, is a plain with an altitude between 600 m and 1,000 m. The lower areas are dry semi desert inter dispersed by large irrigated rice growing areas. In 2001, a cross sectional survey in the district showed that malaria parasite prevalence in under five year olds varied from 25% in the lowlands to 3% in the highlands [A randomized controlled trial of intermittent preventive treatment for malaria in infants (IPTi) has been running in Same district since January 2005 . The primary endpoint of this trial is incidence of malaria confirmed with a blood slide examination. Therefore, infants enrolled onto the study have a research blood slide taken every time the child presents to a health facility. The research laboratory runs a quality assurance scheme to the hospital laboratory that involves training and support with malaria blood slide reading. The study medical team worked closely with the hospital clinicians to diagnose study children correctly. The study medical team visited the paediatric ward daily and offered training and advice to the staff on the care of sick children. The study team noted that the incidence of malaria was very low in the district (0.02 cases/child/year) and shared this information with the clinical staff in the hospital and sensitized them to the fact that the incidence of malaria is very low in the community.Another study at Same District Hospital in 2002 [The impact of the training and supervision as assessed by reviewing hospital records of diagnoses of malaria and laboratory slide results for the years 2001 through to 2005.There was a steady decrease in the proportion of blood slide-positive for malaria parasite during the five year observation period  and the proportion of outpatient and inpatient cases diagnosed as malaria declined from 28% in 2004 to 17% in 2005 (p < .01)  in the proportion of patients diagnosed as having malaria. This fall is probably due to a number of reasons. A major influence is likely to be the hospital management team and their consistent message that malaria is less common than in previous years and it is bad clinical practice to misdiagnose malaria. The strength of the message was helped by continuing external quality assurance of the hospital laboratory by the research laboratory and information of community prevalence of malaria provided by the research team.If clinicians had used the blood slide results consistently to diagnose malaria, all clinically diagnosed malaria would have had a blood slide. However there was no substantial increase in the proportion blood slides examined in the clinically diagnosed case of malaria in 2005. Indeed, the ratio of blood slides examined compared to total cases diagnosed as malaria has been inconsistent over the five year period. In 2001 and 2003, the number of blood slides examined was 30% and 10%, respectively, more than the number of cases diagnosed as malaria. This may be due to the inherent weakness in the clinical diagnosis of malaria, thus, many non-malaria cases had a blood slide examined in these years. Since the data cannot link the slide result to individual records it is not possible to confirm this assumption.As this is an analysis of existing hospital records the observations made are liable for bias arising from complete and inconsistent data. Nevertheless, the remarkable reduction in the proportion of cases diagnosed as malaria following a package of training and support to clinicians in the hospital is unlikely to be erroneous. It is clear that the study hospital is a special case with an on-going malaria research project and cannot be extrapolated to other situations. However, it is an example of a significant reduction in over-diagnosis.This case study shows that behaviour change among clinicians is possible and that the mountain of over diagnosis is climbable and in a short time scale. Studies should examine the best type of continuing education that should be implemented to decrease over-diagnosis of malaria and whether External Quality Assurance Schemes can improve trust in laboratory results.All authors contributed to the idea. PM, WS, RU and JM carried out the training and supervision. RG and DC did the statistical analysis and all authors helped to draft the manuscript.


While many individual genes have been identified that confer protection against malaria, the overall impact of host genetics on malarial risk remains unknown.We have used pedigree-based genetic variance component analysis to determine the relative contributions of genetic and other factors to the variability in incidence of malaria and other infectious diseases in two cohorts of children living on the coast of Kenya. In the first, we monitored the incidence of mild clinical malaria and other febrile diseases through active surveillance of 640 children 10 y old or younger, living in 77 different households for an average of 2.7 y. In the second, we recorded hospital admissions with malaria and other infectious diseases in a birth cohort of 2,914 children for an average of 4.1 y. Mean annual incidence rates for mild and hospital-admitted malaria were 1.6 and 0.054 episodes per person per year, respectively. Twenty-four percent and 25% of the total variation in these outcomes was explained by additively acting host genes, and household explained a further 29% and 14%, respectively. The haemoglobin S gene explained only 2% of the total variation. For nonmalarial infections, additive genetics explained 39% and 13% of the variability in fevers and hospital-admitted infections, while household explained a further 9% and 30%, respectively.Genetic and unidentified household factors each accounted for around one quarter of the total variability in malaria incidence in our study population. The genetic effect was well beyond that explained by the anticipated effects of the haemoglobinopathies alone, suggesting the existence of many protective genes, each individually resulting in small population effects. While studying these genes may well provide insights into pathogenesis and resistance in human malaria, identifying and tackling the household effects must be the more efficient route to reducing the burden of disease in malaria-endemic areas. Genetic factors accounted for one quarter of the total variability in malaria incidence in this study population, slightly less than household-specific environmental factors. Plasmodium falciparum malaria, the contribution of each gene, or of all the genes combined, relative to the many environmental factors that also influence malarial risk, has rarely been estimated [While a growing number of genes have been described that are associated with protection from infection and severe disease due to stimated ,2. PuttiIt is difficult to estimate the overall contribution of genetic factors (“heritability”) to the between-person variation in the incidence of infectious diseases in the field because it requires both longitudinal data on individual patients sufficient to obtain adequate measures of their risk and also the identification of genetic relatedness between these patients. Furthermore, because related individuals often share a common environment (such as a house), and environmental factors play a major role in the risk of infectious diseases, environmental and genetic effects are inseparable in most field study designs . InP. falciparum parasites at any density, and nonmalarial fevers as those in which the blood slide was negative for malarial parasites. We used verbal interview of mothers or key representatives of the household to obtain information on genetic relationships between study children, their parents, and sometimes their grandparents, and to identify genetic links between households . From this information, we created a three-column “pedigree” list  of all individuals identified as being related to at least one child in the study. This list was then used to build up a square matrix  containing coefficients of relationship among all pairs of individuals in the study and among their parents or more distant ancestors where such links were identified [We analysed data from two separate studies, one addressing “mild,” uncomplicated clinical malaria, and the second addressing malaria resulting in admission to hospital, as described in detail previously ,9. Briefentified .A household typically comprised a group of 3–6 adjacent houses, each occupied by one woman and her children whose husbands were full-sib or half-sib brothers and who sometimes had more than one wife. Thus, within each household, the children generally formed several full-sib, half-sib, and first cousin groups.In study 2—the birth cohort study—we monitored the incidence of admission to hospital with malaria and other diseases through passive surveillance of a birth cohort of 2,914 children 5 y old or younger, residing in a wider geographical area that encompassed Ngerenya (study 1) within 16 km of Kilifi District Hospital between May 1992 and December 1997. The birth cohort was recruited from a continuous demographic surveillance system used to monitor child survival. For the purpose of this analysis, we classified admissions into three categories: (i) malaria, (ii) other infectious diseases , or (iii) accidents. In this paper we use the term “hospitalised malaria” to refer to hospital admissions with malaria, but do not distinguish between the severity of disease within this class . In this study, we identified full-sibs, but did not record other information on genetic relationships.10(x + 1) transformations.For study 1, we calculated the annual incidence of malarial and nonmalarial fevers for each child separately as the number of episodes divided by the total number of weeks of surveillance, multiplied by 52. We performed this calculation both for each child over the entire period spent in the study (method 1), and for each age year the child spent in the study . We excluded records for 3 wk following treatment for an episode of malaria. We also excluded data from patients with less than 30 records per year in order to standardise the measurement variation in incidence and, in the case of infants, to minimise the influence of maternally acquired immunity. Finally, we analysed data, including and excluding data from extreme children who suffered more than ten episodes of malaria or more than ten episodes of nonmalarial fever per year, on the basis that these were possibly manifestations of additional health problems. As the distribution of malaria incidence data was skewed, and because we expected heterogeneous variances across different age groups and years associated with their different means, we analysed our data both before and after applyingHbAA; heterozygote, HbAS). The random effects fitted were for household and additive genetic value of each child. We separated additive genetic from other effects pertaining to an individual  by incorporating an “additive genetic relationship matrix” into our model [We analysed our incidence data using a mixed linear model that incorporated genetic relationships to partition the total variation in disease incidence into its genetic, household, systematic, and other causes. The fixed effects fitted were age range , year (one level for each year of study based on the average for the record in question), sex , use of mosquito nets over beds at night , ethnic group , and haemoglobin S genotype , to the total variation in the trait  from the ANOVA table, by dividing the type 3 sum of squares by the total sum of squares. Contributions of additive genetics (h2) and household (c2) were calculated from the ratio of their estimates of variance (AV and CV) to P.V Approximate standard errors of h2 and c2 were calculated from the information matrix around the maximum of the likelihood surface [We calculated the contribution of each of the fixed effects, and their sum  using the above model (method 1). However, since different children spent different periods of time in the study, and because variances might differ across ages and years in association with their different means, we were concerned that the model's assumption of homogeneous errors would be violated. Therefore, we also performed a second analysis using repeated records on the same child, one for each full age year recorded (method 2), in which we fitted a multivariate model treating each age year as a separate, but correlated, trait . This method thus allowed In study 2, our outcomes of interest were rates of admission to hospital with malaria, other infectious diseases, and accidents. We excluded data from children who were alive at the end of the study but who were absent from the district for more than 5 mo during the study period. We included data from children who died during their hospital stay, but excluded data from those who either died outside hospital or at less than 1 mo of age.h2 from c2, but does provide an easy way of calculating an upper limit to heritability from incidence data. In method 4, we analysed the data on the observed (binary) scale under a model fitting random effects for sibship and household, and fixed effects for age, sex, ethnic group, and bednet use. In this model, we did not fit year as it was heavily confounded with age in this study, and no information was available on haemoglobin S genotype. The estimates of h2 and c2 on the observed scale were then transformed to the underlying scale [h2 and c2 estimates were calculated based on method 4 [Given the binary nature of the data, we used threshold models for these analyses. These models assume that there is an underlying normally distributed “liability” trait, with a threshold level above which the disease is manifested. These took three forms. First (method 3), we compared the incidence of malaria admissions to hospital among affected full-sibs to that in the general, unrelated, population: a difference in incidence among relatives reflects a genetic component in the trait on the underlying scale and thus allows an estimation of its heritability . This meng scale . In methng scale . For metmethod 4 .To determine whether genetic and household effects could be adequately separated from the data structure encountered in these studies, we simulated phenotypic data according to the observed pedigree and household structure, assuming a range of values of additive genetic and household variances between 0.1 and 0.5, a phenotypic variance of 1, and either a normal (study 1) or binary distribution (study 2) of the trait. Ten replicate datasets per parameter combination were generated and then analysed under a model fitting household and an additive genetic effect per person as random effects.h2, c2 and f2 from both these studies, and from a previous similar study conducted in Sri Lanka [The study design, and estimates of The final analysis of the mild disease cohort study included data from 640 children living in 77 different households with a total of 1,727 annual age year records (2.7 per child). We identified the parents of 602 of these children  and one or both grandparents of 119. The total pedigree included 1,590 individuals. An average household comprised 8.3 children fathered by an average of 2.3 men, themselves brothers, half-brothers, or first cousins, each with an average of 1.14 wives. Thus there were typically three groups of full-sibs per household who also formed groups of first cousins or half-sibs. The ethnic composition of this population was 84% Giriama, 10% Chonyi, and 6% other Mijikenda.The incidence of nonmalarial fevers decreased rapidly from birth and averaged 1.9 episodes per child per year over the ages 0–10 y . In contHbAS each accounted for around 2% of the variation in malarial fevers and less than 0.4% in nonmalarial fevers, even when additive genetics and household were not included in the model. Age explained a lower proportion of the variation in malarial fevers than nonmalarial fevers, reflecting the age-incidence patterns for each (see h2) explained 24(± 11)% and 39(± 12)% of the variation in malarial and nonmalarial fevers, respectively: the corresponding estimates for household effects (c2) were 29(± 6)% and 9(± 4)%, respectively.In each see . Averagih2 with age. Genetic correlations between incidence at consecutive ages averaged 0.40 and 0.46 for malaria and nonmalaria, respectively. The corresponding “environmental”  correlations were −0.01 and 0.02, and phenotypic correlations were 0.36 and 0.26. Phenotypic, genetic, and environmental correlations between the incidence of malarial and nonmalarial fevers within age years were −0.01, 0.23 and −0.29, respectively, the latter no doubt reflecting the fact that these two traits represent opposite sides of the same coin. When averaged over years, the corresponding values were 0.37, 0.61, and 0.38, suggesting that children share susceptibilities to both types of fever for both genetic and nongenetic (but not household) reasons. The mean correlations between age groups in household effects for malaria and nonmalaria were 0.81 and 0.55, respectively, indicating that household effects were consistent across age groups, especially for malaria.Although phenotypic variances correlated positively with mean incidence at each age, there was no obvious change in During the study, 2,914 children remained resident, their average age at the end of the study or at death (and hence length of time under surveillance) being 4.1 y (range 1 mo–5.7 y). Overall, 33% of these children were admitted to the hospital at least once during the study period. Forty-eight percent of all admissions were due to malaria, while a further 26%, 9%, and 2% of admissions were due to acute respiratory infections, gastrointestinal infections, and accidents, respectively. The incidence of malaria and other infections decreased rapidly with age . The aveh2 and c2 for nonmalarial infections in this study were respectively lower and higher than for malaria, reversing the pattern seen for mild infections in study 1  but that, as expected from some confounding, the sampling correlations between them were −0.5 for study 1 and −0.7 for study 2. This means that if, for sampling reasons, the true h2 was overestimated by 0.2 , c2 would be underestimated by 0.05 in study 1 and by 0.07 in study 2. These simulations also showed that our estimates of standard errors were reasonable.The simulation study showed that estimates of Plasmodium vivax in addition to P. falciparum, a study population consisting mainly of adults, and an entirely different genetic composition to that of Kenya. Nevertheless, the results from both studies are in broad agreement, suggesting that substantial genetic variability for resistance to infection and disease severity is maintained in human populations that have been exposed to the disease for a very long time.Our analyses of data from two independent studies conducted on the coast of Kenya, and a third study conducted in Sri Lanka , each foHbS and α-thalassaemia. For example, in theory [HbAS, which roughly halves the incidence of mild malaria  and is found at a frequency of 0.15 in our population [, which is found in our population at an allele frequency of 0.43, and which reduces the incidence of uncomplicated malaria by around 0.4 of a standard deviation in homozygotes and a little more than half this in heterozygotes , would account for only 2% (1.9% additive and 0.1% dominance) of the total phenotypic variation [HbAS [We could only attribute a small proportion of this variation to the best known of the malaria resistance genes, n theory  we expecpulation ,18, woulariation . For hoson [HbAS . Thus, oon [HbAS –23, malap)2 where p measures the misclassification of paternity [The heritability estimates we report here are almost certainly conservative for several reasons. First, we anticipate that our assessment of paternity will have been subject to error, reducing our observed relative to true estimates by a factor of  suggests that susceptibility to a range of childhood infections might be mediated via mechanisms with a common genetic basis. High heritabilities of the immune response to some antigens from malaria parasites and other infectious pathogens ,27,28, mA striking result from this study was the amount of variation that could be attributed to household, particularly in the incidence of mild malaria and nonmalarial hospitalised infections. Children living in the 10% most malarious houses had about twice as many malaria infections (2.39 per year) as those in the 10% least malarious houses (1.14 per year). As our measure of malaria incidence almost certainly includes superinfections, this between-house variability probably reflects variation in transmission intensity due to spatial variation in breeding sites for mosquitoes and other household-related factors such as insecticide and repellant use . We coulThis study shows that despite the inherent stochasticity in malaria transmission, the average risk of malaria in children living in our study area is in large part due to factors that are predetermined, both at the genetic and nongenetic level. While manipulation of the host's genes or their products may not yet seem plausible, determining how specific genes control the protective response may, ultimately, lead to a better understanding of the mechanisms of pathogenesis and host resistance. In the meantime, tackling household-related factors would seem to be a more tractable option for disease control.Humans exposed to malaria get infected and sick to varying degrees, and some of that variation is due to differences in genetic makeup between individuals. Because the disease has killed humans for thousands of years, selection over time has increased protective variants of human genes in regions where malaria was and is common. One well-known example is the sickle-cell variant of the hemoglobin gene, which protects against severe malaria and is more common in people of African descent.Most research has focused on identifying the specific genes whose variants confer susceptibility to or protection from malaria. Some have been identified, but it is also clear that there are many genes involved, most of which contribute a small amount to the overall picture. In this study, the researchers wanted to estimate how much all genetic factors taken together, relative to the many environmental factors that also affect malaria risk, influence the number and severity of malaria cases.The researchers recruited and studied groups of children in rural Kenya. To estimate the overall contribution of genetic factors, they needed to observe the children over a long enough time that they would get a sense of an individual's malaria risk. In addition, they needed to know the genetic relatedness among the children, and the living arrangements needed to be such that children of different degrees of genetic relatedness  shared a common environment. They found that genetic differences among people accounted for about 25% of the variability in malaria risk. This was less than the contribution by “household factors,” which accounted for around 30% of the total variability. Some of these household factors are known ones, such as insecticide use, but most of the 30% in risk variability was due to unidentified household factors.The risk of malaria is strongly predetermined by genetic and nongenetic factors. However, while understanding how specific genes affect malaria risk will ultimately lead to a better understanding of the disease and improve prevention and treatment, genetic factors are not the biggest contributors to malaria. Therefore, in the short term, focusing on identifying and improving household-related factors is more likely to reduce the burden from the disease.General information on the disease from the World Health Organization and links to many other sites:http://www.who.int/malariaThe Wellcome Trust's malaria pages, which include a section on malaria and people that discusses genetic factors:http://www.wellcome.ac.uk/en/malaria/home.htmlThe malaria pages of the Centers for Disease Control and Prevention, which contain a section on geographic distribution and epidemiology:http://www.cdc.gov/malaria/distribution_epi/human_epidemiology.htm


New sources of funding have revitalized efforts to control malaria. An effective vaccine would be a tremendous asset in the fight against this devastating disease and increasing financial and scientific resources are being invested to develop one. A few candidates have been tested in Phase I and II clinical trials, and several others are poised to begin trials soon. Some studies have been promising, and others disappointing.It is difficult to compare the results of these clinical trials; even independent trials of the same vaccine give highly discrepant results. One major obstacle in evaluating malaria vaccines is the difficulty of diagnosing clinical malaria. This analysis evaluates the impact of diagnostic error, particularly that introduced by microscopy, on the outcome of efficacy trials of malaria vaccines and make recommendations for improving future trials. Vaccines which protect against infectious diseases have saved many lives in the past 200 years, have allowed the eradication of smallpox and near-eradication of polio, and are widely regarded as extremely cost-effective interventions. Vaccines against many common diseases, such as measles and pertussis, have become part of routine paediatric care and public health programs worldwide.Malaria is estimated to be the deadliest paediatric disease: hundreds of thousands of children under five succumb to malaria each year. An effective vaccine would be a major advance in public health and is actively being sought. Several candidates have been tested in clinical trials and many more are in various stages of development. Many aspects of vaccine trial design are important in ensuring reliable outcomes, but among the most critical are the choice of primary endpoint and thereby the definition of vaccine efficacy. In practice, clinical endpoints depend on three equally important components of malaria diagnosis – detection, quantification and case definition. The factors which contribute to accuracy in each component, specifically with respect to microscopic diagnosis, and their impact on the calculation of vaccine efficacy for various types of Phase II and III clinical trial endpoints are examined.Malaria vaccine strategies can be categorized by the stage of the parasite life cycle which they target. The target of the vaccine candidate will determine the endpoint that is used to evaluate its efficacy Table . Unlike Vaccine efficacy is calculated as a ratio, which leads to the common misconception that uncertainty  in the numerator and uncertainty in the denominator will cancel or balance. This is not the case, particularly when sensitivity and specificity may differ in the vaccinated and the control groups. The 95% confidence intervals with which VE is typically reported give the range of values within which one can be 95% certain that the true VE lies, based on the observations, but they reflect only one type of uncertainty. They describe the role of random chance in the observations and depend on the sample size and number of observed disease events. They do not reflect measurement error or other types of uncertainty that may be introduced during the trial. The effect of the uncertainty of the measurement technique on the reliability of VE calculations has not been fully evaluated and must be properly incorporated.When making measurements with categorical conclusions, such as the presence or absence of parasites, measurement uncertainty can decrease the sensitivity and specificity of the endpoint. Low sensitivity results in a misclassification of true positives as negatives and may arise as a result of measurement error or a case definition that is too stringent. If the ex ante sensitivity is low, it can be counterbalanced by increasing the sample size. However, if the ex post sensitivity  is lower in the vaccinated group than in the control group, a systematic bias is introduced and the VE will be overestimated.False positives may be generated by measurement error or a case definition that is too inclusive. Specificity less than 100% can have a dramatic impact on the ability to accurately measure VE  of microscopy. The LOD is operator-dependent, but is also correlated with parasite density and has been shown to be highly variable at low densities Figure  4]. Thi. Thi4]. Variable sensitivity at low parasite densities complicates the interpretation of Phase IIa challenge studies for pre-erythrocytic vaccines Figure . VaccinaLow sensitivity can have a similar effect on Phase IIb trials which measure time to first infection in naturally exposed populations; high rates of false negatives and variable sensitivity can obscure a difference between the vaccinated and unvaccinated groups. False negatives have less serious consequences for trial interpretation when the time to first clinical episodes is measured by passive case detection. If no parasites are detected at first presentation and patients are not treated for malaria, then presumably symptoms will persist until parasites are detected and the case is counted.The specificity of malaria microscopy is also less than perfect, and rates of false positives can reach 24% . The impQuantifying malaria by microscopy is a difficult task, but theIn a study conducted in Peru and Thailand, thousands of blood smears were read independently by two microscopists following very detailed protocols,11. The When comparing parasite densities in the vaccinated and the control group, uncertainty arising from quantification of the parasite density can be introduced directly into the calculation of VE. Figure Factors other than measurement error can contribute to uncertainty in parasite density measurements. For example, parasite density is reported as parasites per microliter of blood, but because parasites are counted using white blood cells (WBCs) as an index, a conversion factor -generally a uniform approximation of 8,000 WBCs/μl- is usedTemporal fluctuations in parasite density in peripheral blood are common and may have greater consequences for parasite density measurement than uncertainty associated with microscopic quantification. Peaks and troughs of density may arise from sequestration, or immune response and the rise of new antigenic variants. Thus it is seldom clear how to interpret a single measurement of parasite density in an individual. For example, infections quantified 24–48 hours apart in each of 11 patients prior to drug treatment showed an average increase of 5,500 parasites per microliter, with a range of -17,000 to 46,000. A longiIt is worth noting that body temperature can also fluctuate on the timescale of hours. Choosing a temperature threshold to define a febrile malaria episode raises similar issues to choosing a single density threshold.In malaria-endemic areas with moderate to high transmission, the presence of parasites alone or parasites with fever are not adequate indicators of a clinical malaria episode. It is not possible to definitively diagnose clinical malaria; therefore, criteria must be chosen for which a patient will be considered to be experiencing a clinical malaria episode. The uncertainty in definition will lead to misclassification of cases, both false positives and false negatives, resulting in decreased sensitivity and specificity.The fraction of parasitaemic, symptomatic individuals whose malaise is caused by parasites is referred to as the attributable fraction. The attributable fraction can be calculated by comparing the proportion of febrile individuals over a range of parasite densities. Most commonly, a logistic regression model is fit to the data to descrThe logistic regression model for determining attributable fraction has been used to determine the sensitivity and specificity of case definitions in numerous epidemiological settings. The cut-off density which gives a case definition with sufficiently high sensitivity and specificity depends on many interrelated variables. The appropriate case definition changes as a function of transmission intensity, and, thOnce a threshold density has been chosen to define a clinical episode of malaria, the effect of measurement uncertainty inherent in detecting and quantifying the infection can be evaluated. Using the density error model, the fraction of cases which are at risk of being mis-categorized based on the cut-off value can be calculated Figure . The disUnderstanding the sources and impact of uncertainty can lead to more robust endpoint definitions in malaria vaccine trials. The sensitivity and specificity of microscopy are highly reader-dependent. However, particularly in the case of sensitivity, there are intrinsic limitations to microscopy that cannot be completely resolved by improving reader performance. The shape of the density-error relationship amongst the study microscopists should be determined before the study begins. "Over-reading" paradigms, for example having two microscopists read every slide and a third microscopist re-read slides with highly discrepant results, increase the sensitivity and specificity of microscopy and allow on-going, 'real-time' evaluation of the density-error relationship.Density-ratio endpoints seem to be less sensitive to uncertainty than threshold-dependent endpoints, particularly when the majority of cases fall close to the threshold value. To reduce the error of a threshold-dependent endpoint, a cut-off value based on the parasite:leukocyte ratio rather than an absolute density may be used. Evidence indicates that the parasite:leukocyte ratio is bimodal , giving a natural choice for a cut-off value. Deviations from this cutoff value due to experimental error would result in fewer misclassified cases. This observation is consistent with data from other studies which showed that WBC counts were lower in symptomatic, infected individuals compared to those with similar symptoms but no parasites .Another alternative is to use attributable fraction estimates, arrived at by logistic regression22, 27, 28] or other methods [29], to evaluate efficacy. A reduction in the febrile episodes attributable to malaria across all densities would be a more accurate indicator of vaccine efficacy than defining a clinical episode by a cut-off threshold and would partially eliminate the problem of differing sensitivities and specificities in each arm of the trial. Because vaccination is intended to alter immune status, the relationship between density and probability of fever must be determined by a cross-sectional survey or continuous active detection in the vaccinated and unvaccinated cohorts separately. Each febrile episode recorded during the trial is assigned a probability of being a malaria episode, as a function of its density using the logistic regression model [28]. The number of febrile cases attributable to malaria in the vaccinated and unvaccinated cohorts is calculated by summing the relative risk for febrile episodes in each cohort and multiplying by the total number of febrile cases. This definition of vaccine efficacy reflects both the reduction in parasite density and the reduction in the total number of febrile episodes. It allows for changes in the relationship between parasitemia and clinical illness. Although density measurement is required, this technique is less sensitive to error in individual density measurements because the logistic regression model represents smoothing of aggregated data and as such is less sensitive to random measurement error  declare that they have no competing interests.WPO performed analysis, contributed to intellectual content and drafting of manuscript. BFH contributed to intellectual content and drafting of manuscript. FEM contributed to study design, intellectual content and drafting of manuscript.Discussion of malaria detection and diagnostic techniques and alternative endpoints such as severe disease and mortality.Click here for file


The α-thalassaemias are the commonest genetic disorders of humans. It is generally believed that this high frequency reflects selection through a survival advantage against death from malaria; nevertheless, the epidemiological description of the relationships between α-thalassaemia, malaria, and other common causes of child mortality remains incomplete.+-thalassaemia-specific incidence of malaria and other common childhood diseases in two cohorts of children living on the coast of Kenya. We found no associations between α+-thalassaemia and the prevalence of symptomlessPlasmodium falciparum parasitaemia, the incidence of uncomplicatedP. falciparum disease, or parasite densities during mild or severe malaria episodes. However, we found significant negative associations between α+-thalassaemia and the incidence rates of severe malaria and severe anaemia (haemoglobin concentration < 50 g/l). The strongest associations were for severe malaria anaemia  and severe nonmalaria anaemia; the incidence rate ratios and 95% confidence intervals (CIs) for α+-thalassaemia heterozygotes and homozygotes combined compared to normal children were, for severe malaria anaemia, 0.33 , and for severe nonmalaria anaemia, 0.26 .We studied the α+-thalassaemia might be mediated by a specific effect against severe anaemia, an observation that may lead to fresh insights into the aetiology of this important condition. Second, although α+-thalassaemia is strongly protective against severe and fatal malaria, its effects are not detectable at the level of any other malaria outcome; this result provides a cautionary example for studies aimed at testing malaria interventions or identifying new malaria-protective genes.Our observations suggest, first that selection for α +-thalassemia in the population might be mediated by a specific effect against severe anemia.A study of children from the coast of Kenya suggests that selection for α Although malaria causes more than 200 million episodes of fever among young African children every year, fewer than 1% of these episodes are fatal ) of participants during the period of study was 2.38 (1.50) y. The following seven diagnoses accounted for over 90% of consultations: malaria (by definition 1) , upper respiratory tract infection , lower respiratory infection (499 [12%]), gastroenteritis (490 [11%]), skin infection (478 [11%]), fever of unknown cause (135 [3%]), and helminth infection (199 [3%]). Consultations with other diagnoses and hospital admission events were too few to permit meaningful between-genotype comparisons.In the mild disease cohort study, 4,296 clinic visits were made by 382 participants during 520.39 child years of follow-up (cyfu). Of these participants, 96 (25.1%) were of normal α+-thalassaemia genotype, 1,017 (48%) were heterozygotes, and 348 (17%) were homozygotes. Of the 2,104 participants, 309 (15%) were Hb type heterozygotes, HbAS. The mean duration (SD) of follow-up of children contributing data to this analysis was 3.89 (1.02) y. Between them, malaria (434/876 [50%]), lower respiratory tract infections (236 [27%]), and gastroenteritis (68 [8%]) accounted for 85% of all admissions. Amongst the children admitted with malaria, 146/434 (34%) showed one or more signs of severity (as defined above). Of these episodes 60/146 (41%) could be defined according to one of two categories, cerebral malaria or severe malaria anaemia. The number of participants admitted with other diagnoses or malaria syndromes were too few to allow for meaningful comparisons.In the birth cohort study, a total of 876 admissions were recorded among 2,104 participants during 8,181 cyfu. Of this cohort, 739 (35%) participants were of normal α+-thalassaemia on the prevalence of symptomless parasitaemia. During the four cross-sectional surveys combined, the prevalence was 59/320 (18.4%) in normal children, 100/543 (18.4%) in heterozygotes and 23/171 (13.5%) in those with homozygous α+-thalassaemia, giving adjusted odds ratios for parasitaemia of 0.92  and 0.71  for heterozygotes and homozygotes, respectively, compared to normal children. Similarly, although the incidence of uncomplicated malaria (by either definition) was lower in both heterozygotes and homozygotes for α+-thalassaemia than in normal participants involved in the mild disease cohort study, these differences were not significant either individually . Nevertheless, α+-thalassaemia was associated with significant reductions in the rate of admission to hospital with malaria and severe malaria measured through the birth cohort study. Homozygotes were admitted to hospital with malaria, with or without signs of severity, significantly less frequently than normal children  or when clinically apparent (detected through either the mild disease or birth cohort studies) (We found no significant associations between αtudies) . This ob+-thalassaemia genotype and the presence of clinical syndromes other than malaria (p = 0.033]). Whereas in homozygotes, the numbers were too few to reach significance, the IRR for both genotypes combined was 0.26 . Second, the incidence of lower respiratory tract infections, detected during the mild disease cohort, was significantly lower in both heterozygous and homozygous than in normal children  it is d severe ,21,22  severe  malaria, severe ,25. FurP. falciparum malaria that result in hospital admission. In keeping with data from recent case control studies [+-thalassaemia either on parasite density or on the prevalence of symptomless parasite carriage. We did see some evidence towards a reduced incidence of uncomplicated malaria in α+-thalassaemic children  that are an essential part of hemoglobin (the oxygen-carrying protein in the blood) are known to influence how people are affected by malaria. For example, one such change in the beta globin gene causes sickle hemoglobin; when individuals have two copies of the affected gene they can be severely affected with anemia and painful crises, but carrying just one copy seems to make people less susceptible to malaria. Other genetic variants, in the alpha globin gene, cause a condition called alpha-thalassaemia, which can also lead to anemia because of lower amounts of the alpha globin protein being present. People with alpha thalassaemia seem to have some protection against malaria.Both sickle cell and alpha-thalassaemia are very common in Africa. These investigators wanted to investigate whether having alpha-thalassaemia protects against all types of malaria or just the severe type.The authors studied two groups of children living on the coast of Kenya to find out whether they had alpha-thalassaemia. They assessed whether or not having alpha-thalassaemia led to any difference in whether the children were infected with the parasite that causes malaria, whether they had symptoms, and how severe the symptoms were. They found that having alpha-thalassaemia meant that the children were less likely to get severe malaria and severe malarial anemia. However, there was no effect on whether the children got mild malaria or not.These results suggest that over generations the genetic change that causes alpha-thalassaemia has become common in this population, because carrying it protects people against getting severe malaria, especially with anemia. However, the genetic change does not appear to make it more or less likely that children get mild malaria. This result may be important when designing studies to look at the relation between these genetic changes and malaria.Medline Plus has a page of links to malaria:http://www.nlm.nih.gov/medlineplus/malaria.htmland a page discussing thalassaemia:http://www.nlm.nih.gov/medlineplus/ency/article/000587.htm