Evidence from a natural experiment that malaria parasitemia is pathogenic in retinopathy-negative cerebral malaria

Malaria is a life-threatening disease caused by a parasite that is transferred between people by infected mosquitoes. Most infected individuals suffer flu-like symptoms, but in rare cases malaria can affect the brain, resulting in brain damage, coma or death.

The World Health Organization defines a person as suffering from cerebral malaria if the person is in a coma, has malaria parasites in his or her blood, and has no known alternative cause of the coma. Patients suffering from cerebral malaria are categorized based on whether they have damage to the back of the eyes known as retinopathy. It had previously been found that children who died of “retinopathy-positive” cerebral malaria (i.e. those who had retinopathy) had malaria parasites stuck in small vessels in their brains, which likely caused the coma. By contrast, children who died of “retinopathy-negative” cerebral malaria lacked this parasitic condition, and often also had other infections that can cause a coma, such as meningitis or sepsis.

Because hospitals in many of the areas most affected by malaria often lack the ability to identify what – other than malaria – caused a coma, it was not clear whether malaria parasites influence how retinopathy-negative cerebral malaria develops.

People with certain genetic variants – such as those that underlie sickle cell disease – are protected against the symptoms of malaria infections, and so these variants should also protect against cerebral malaria cases caused by the parasites. Small et al. therefore looked through data that had been collected over several years from people who had been admitted to a hospital in Malawi for cerebral malaria. This revealed that the genetically inherited sickle cell trait is highly protective against retinopathy-negative (as well as retinopathy-positive) cerebral malaria. Therefore, malaria parasites do play a role in a substantial proportion of cases of retinopathy-negative cerebral malaria.

Although Small et al. provide evidence that malaria parasites play a role in retinopathy-negative cerebral malaria, they may not be the only cause of the coma. In the future, the absence of retinopathy could be used as a sign to look for additional factors that contribute to the coma. Currently, all cerebral malaria patients are treated in the same way. Understanding how malaria parasites interact with other illnesses to produce a coma could lead to the development of targeted treatment plans for retinopathy-negative patients.

Cerebral malaria (CM) is responsible for a substantial proportion of the approximately 500,000 annual malaria deaths and 2,000,000 severe malaria cases (WHO, 2014, WHO, 2015). CM is defined by the World Health Organization (WHO) as unarousable coma with circulating malaria (Plasmodium) parasitemia and no known non-malaria causal explanation (WHO, 2000). Based on the presence or absence of malaria-specific retinal changes, CM can be classified as retinopathy-positive (Ret+) or retinopathy-negative (Ret-) (Lewallen et al., 1999; Beare et al., 2006). Ret- CM is a common and devastating condition – 40% of CM cases in our cohort were Ret- and of these, 12% died and 10% developed neurological problems (Table 1). Autopsy data show that children dying of Ret+ CM have a high degree of sequestration of parasitized red blood cells in cerebral vasculature (Taylor et al., 2004), considered the pathological hallmark of CM. The pathogenesis of Ret- CM has been a puzzle, in particular the role of malaria parasitemia (Postels and Birbeck, 2011). In the only autopsy study among children dying with CM, that we are aware of ( Taylor et al. (2004) with follow-up results in Milner et al. (2015) and Barrera et al. (2015)), among children for whom retinopathy was assessed, 41 of 42 children dying with Ret+ CM had substantial cerebral sequestration of parasitized red blood cells in the cerebral microvasculature (defined as ≥23% of cerebral capillaries had sequestration) and mostly lacked other identified potential causes of death besides the malaria parasitemia, whereas all 15 children dying with Ret- CM lacked substantial cerebral sequestration (<23% of cerebral capillaries had sequestration) and mostly had non-malarial etiologies of death (see Appendix 1 for causes of death); these numbers update those in Taylor et al. (2004) to include patients enrolled after 2004. Incidental malaria parasitemia is common in people living in areas of high malaria transmission. Therefore, it is possible that at least some children with Ret- CM have a non-malarial etiology of coma and an incidental (asymptomatic) malaria parasitemia. The pathogenesis of Ret-CM is therefore unclear, and the role of malaria parasitemia in the etiology of the acute illness is unknown (Postels and Birbeck, 2011). Our aim of the research presented here was to assess the contribution of acute malaria infection in the pathophysiology of Ret- CM.

Figure 1 depicts three possible pathways to clinically-defined (WHO-defined) CM (Postels and Birbeck, 2011). One pathway is to Ret+ CM for which there is evidence that malaria parasites play a primary role. As noted above, at autopsy, Ret+ CM is associated with the sequestration of parasitized red cells in the cerebral microvasculature (Taylor et al., 2004). Compared to children with Ret- CM, those who are Ret+ have increased concentrations of P. falciparum HRP2, a parasite-produced protein reflecting total body parasite burden (Seydel et al., 2012). Ocular funduscopic findings in Ret+ CM mirror the microvascular pathology observed on fluorescein angiography (MacCormick et al., 2015) and are correlated with the severity of sequestration in both the retina and the brain at autopsy (Barrera et al., 2015). Two pathways to Ret- CM, pathway (a) and pathway (b) are depicted in Figure 1. As noted above, in patients dying with Ret- CM, the cerebral microvasculature does not have substantial sequestered parasitized erythrocytes (<23% of cerebral capillaries have sequestration), plasma concentrations of HRP2 are decreased, and a variety of non-malarial causes of death have been identified (Taylor et al., 2004). For Ret- CM, one potential pathway is asymptomatic parasitemia and another illness that is sufficient, in and of itself, to produce coma (pathway (a) in Figure 1). Another potential pathway is parasitemia leading to uncomplicated malaria illness (e.g., fever) combined with a second insult (innate or acquired), resulting in coma (pathway (b) in Figure 1); the two hits (symptomatic malaria+ innate or acquired second factor) result in the clinical syndrome of Ret- CM. A key unanswered question about the pathogenesis of Ret- CM is, are malaria parasites incidental to coma (only pathway (a) exists) or do they play a role in the pathogenesis of Ret- CM (pathway (b) exists) (Bearden, 2012; Postels and Birbeck, 2011)?

Figure 1

Download asset Open asset

Whether malaria parasites play a role in the pathogenesis of Ret- CM could in principle be tested by a randomized experiment. For example, Smith (2007) considered a hypothetical blood-stage malaria vaccine that reduces parasite density by 50%; the vaccine would reduce malaria illness but not the incidence of parasitemia. If such a vaccine existed, then a way to test whether malaria parasites are pathogenetic in Ret- CM would be to randomize a large number of children to either (i) the blood-stage vaccine or (ii) placebo. If malaria parasites are never pathogenetic in Ret- CM, then we would expect no difference in Ret- CM because the blood stage vaccine would fail to prevent the cause of the development of the Ret- CM whereas if malaria parasites are sometimes pathogenetic in Ret- CM in a way that requires the development of uncomplicated malaria illness, then the blood stage vaccine would prevent the development of Ret- CM in some cases. Such an experiment is not currently feasible because no blood-stage vaccine has reached a Phase III trial (Miura, 2016) and even if an effective blood-stage vaccine was developed, the experiment would require a huge sample size to have power to detect a change in Ret- CM rates.

Though a randomized experiment with a blood-stage malaria vaccine that would have power to detect a difference in Ret- CM rates is not currently feasible, nature provides traits that protect against malaria illness in a random way through genetic inheritance. The general approach of using genetic variation to construct natural experiments is called Mendelian randomization (Smith and Ebrahim, 2003). The sickle cell trait (HbAS) – inheritance of one abnormal allele of the betaglobin gene – protects against symptomatic malaria (Modiano et al., 2001; Taylor et al., 2012; Williams et al., 2005; Willcox et al., 1983). Thus, a person who inherits one abnormal allele of the betaglobin gene has an antimalarial biochemical protection provided by nature. A second inherited trait which affects susceptibility to malaria illness is blood group O (BGO), which protects against CM compared to groups A, B or AB (Cserti and Dzik, 2007; Malaria Genomic Epidemiology Network, 2014). Analogous to the randomized trial described above, possession vs. lack of a malaria protective trait assigns children to an arm in which some malaria illness is prevented vs. not prevented. For possession vs. lack of a trait to be fully analogous to the blood stage vaccine randomized trial described above, possession of the trait cannot affect malaria parasitemia incidence just like assignment to the blood-stage vaccine arm in the randomized trial does not affect malaria parasitemia incidence. If the trait affects malaria parasitemia incidence, then it could decrease the Ret- CM rate not because it decreases coma but because the WHO definition of Ret- CM requires malaria parasitemia; the natural experiment induced by the trait would then be biased for assessing the effect of the trait on coma in the same way that a randomized trial is biased if the treatment could affect the measurement of the outcome (WHO-defined Ret- CM) without affecting the true outcome of interest (coma without malarial retinopathy). For both BGO and HbAS, it is plausible that the traits do not protect against malaria parasitemia incidence as systematic reviews have not found consistent evidence for protection (Uneke, 2007; Taylor et al., 2012); we will assume no protection for our main analysis but do sensitivity analyses that allow for protection. Under the assumptions that a trait does not affect malaria parasitemia incidence and the trait is randomly assigned, then if the trait decreases the probability of developing both Ret+ and Ret- CM, this suggests that malaria parasites contribute to the pathogenesis of both conditions. If the trait decreases the probability of developing Ret+ CM but not Ret- CM, this would suggest that malaria parasites are pathogenetic for Ret+ CM but are either not pathogenetic for Ret-CM or the trait affects an aspect of disease not causal to the development of Ret- CM.

Using data gathered from 1996 to 2007 in a study of CM pathogenesis in Blantyre, Malawi (Taylor et al., 2004; Seydel et al., 2015) as well as the MalariaGEN consortium (Malaria Genomic Epidemiology Network, 2008), we compared children with CM to two types of controls – (1) community controls; (2) hospital controls, children who were admitted to the Paediatric Research Ward with a known non-malarial cause of illness – meningitis, non-malarial anemia or other non-malaria illness. Table 1 shows admission characteristics of the hospitalized participants. The Blantyre coma score is statistically significantly higher in Ret+ CM patients than Ret- CM patients, but we do not regard the difference as clinically significant. In general, the patients with Ret+ CM were more severely ill than those with Ret- CM (higher lactate, more deep breathing and a higher chance of death). The malaria illness is more severe in Ret+ CM than Ret- CM patients (lower platelet count and more anemia). The higher opening CSF pressures in Ret+ CM patients compared to Ret- CM patients suggests a higher proportion of Ret+CM patients have increased brain volume. Comparing CM cases to non-malaria controls, as expected, laboratory abnormalities associated with malaria infection (e.g. low hematocrit and platelet count) were more frequent in the CM cases.

For each trait t (t=HBAS or blood group O (BGO)), we test the null hypothesis ($H_0^t$) that the trait frequency is the same in controls and true Ret- CM cases vs. the alternative hypothesis ($H_a^t$) that the trait frequency is higher in controls than true Ret- CM cases. Here, true Ret- CM refers to Ret- CM measured without error; in the actual data, retinopathy status may be measured with error and this measurement error is taken into account in the inferences (Materials and methods). Under a model in which the trait does not affect other potential contributors to Ret- CM besides malaria and does not affect which CM cases are admitted to the Paedeatric Research Ward (as compared to dying before reaching the Ward or recovering before being referred to the Ward), the null hypothesis $H_0^t$ implies that malaria parasitemia is an incidental finding in children with Ret- CM and/or the trait affects an aspect of disease not causal to development of Ret- CM, while the alternative hypothesis $H_a^t$ implies that malaria parasitemia is necessary for some Ret- CM cases and the trait reduces the pathogenetic potential of malaria infection for Ret- CM. Note that if either $H_0^{HbAS}$ or $H_0^{BGO}$ is false, this implies that malaria parasitemia plays a pathogenetic role in at least some Ret- CM cases.

We calculated HbAS and BGO proportions in study subjects and made inferences about odds ratios (Table 2) and tested $H_0^{HbAS}$and $H_0^{BGO}$. For both HbAS and BGO, non-malaria hospitalized controls did not differ from community controls (HbAS p-value=0.86; BGO p-value=0.83); therefore, subsequent analyses combined the control groups. Controls had a higher proportion of HbAS than true Ret- CM patients (odds ratio: 14.33, 95% CI: 3.21, 257.24) and true Ret+ CM patients (odds ratio: 1223.22, 95% CI: 9.87,$\infty$). For BGO, the controls were comparable to true Ret- CM patients (odds ratio: 1.03, 95% CI: 0.83, 1.29) but higher than true Ret+ CM patients (odds ratio: 1.23, 95% CI: 1.01, 1.50). There is strong evidence to reject $H_0^{HbAS}$(p-value<0.0001) but not $H_0^{BGO}$ (p-value=0.79); these results are insensitive to different plausible assumptions about the false discovery rate and false omission rate for malarial retinopathy (Appendix 1). Taken together, these tests suggest that malaria parasitemia is pathogenic for a proportion of Ret- CM cases. Sickle cell trait protects against Ret- CM, but blood group O does not.

In Materials and methods, we formulate a sufficient-component cause model (Rothman, 1976) based on Figure 1 and describe how to make inferences about the fraction of Ret- CM cases that are due to pathway (b) in Figure 1, i.e., the malaria parasitemia attributable fraction of Ret- CM (the fraction of Ret- CM cases that would be prevented if malaria parasitemia were eliminated [Benichou et al., 1998]). The fraction itself cannot be estimated without strong biological assumptions (Greenland and Robins, 1988), but a lower bound can be estimated under plausible assumptions. Table 3 shows inferences for this lower bound under the main model that assumes the traits do not protect against malaria parasitemia incidence and sensitivity analyses. Under the main model, the lower bound is estimated to be .93 with 95% confidence interval (.68, 1). For the sensitivity analyses, although the systematic review of Taylor et al. (2012) found no consistent evidence that HbAS reduces malaria parasitemia incidence, some studies reviewed found protection and we consider sensitivity analyses that allow for a small amount of protection (10%) and the largest amount of protection found in all the studies reviewed (41%) (Ntoumi et al., 1997). Also, the sensitivity analyses vary the false discovery rate and false omission rate between 0 and the upper bound estimated in Materials and methods. Under all scenarios considered, we found evidence for a substantial contribution of malaria parasites to the pathogenesis of Ret- CM with lower 95% confidence bounds ranging from .37 to .77 and point estimates for the lower bound ranging from .86 to .95.

We have studied a natural experiment that alters the level of malaria illness and found evidence that children with genetic traits associated with resistance to malaria illness are underrepresented in admissions with both Ret+ and Ret- CM (HbAS) or in admissions with Ret+ CM only (BGO).

Figure 1 shows a model of how HbAS and BGO affect Ret- and Ret+ CM. HbAS protects children with malaria parasitemia from developing uncomplicated malaria illness (e.g., fever) and severe malaria illness (Taylor et al., 2012). By contrast, current evidence suggests that BGO has no effect on developing uncomplicated malaria illness (Uneke, 2007), but does inhibit the cytoadherence of parasitized red blood cells to endothelial cells in the microcirculation, e.g., by affecting rosetting (Rowe et al., 2007) and physical properties of the red cell membrane (Méndez et al., 2012), thereby preventing severe malaria illness (Cserti and Dzik, 2007; Migot-Nabias et al., 2000; Uneke, 2007). Consistent with this current evidence, in Figure 1, HbAS prevents Ret- CM through pathway (b), which involves two components (uncomplicated malaria illness + other illness), by preventing one of the components, uncomplicated malaria illness, whereas BGO does not protect against Ret- CM through pathway (b) because it does not prevent uncomplicated malaria illness (Figure 1).

In Figure 1 pathway (b), Ret- CM results from an interaction between malaria illness and other illness. While the interactions between malaria parasites and other pathogens are incompletely understood and not well investigated, there is evidence for interaction (Obaro and Greenwood, 2011; Mallewa et al., 2013; Postels and Birbeck, 2011). In studies of sepsis and malaria, the effect of microvascular parasite sequestration on the integrity of the gut mucosa is thought to allow bacterial seeding into the blood stream and hence bacteremia (Scott et al., 2011). Another example is that following antigenic challenge from a Plasmodium falciparum candidate vaccine, children coinfected with schistosomiasis had lower acquired specific immune responses than those not infected (Diallo et al., 2010).

Another way in which malaria parasitemia could play a causal role in Ret- CM besides pathway (b) in Figure 1 is that the parasitemia could be the sole cause of coma. Taylor et al. (2004)’s autopsy study results suggest that among children dying from Ret- CM, malaria parasitemia is typically not the sole cause of death (see Causes of Death in Autopsy study in Appendix 1), but it is possible that in survivors from Ret- CM, malaria parasitemia is the major contributor to acute illness. Whether malarial retinopathy is present or absent in CM could be affected by factors such as the child’s genome, the parasite’s genome and the child’s previous exposures to malaria (Postels and Birbeck, 2011). The protection provided against Ret- CM by HbAS but not BGO could be explained by an interaction between the factor(s) affecting whether malarial retinopathy is present and BGO, e.g., a parasite genotype which causes malarial retinopathy to be absent could interfere with the mechanism by which BGO provides protection against severe malaria.

Our study has several limitations. We only considered the genetic variants of sickle cell trait and blood group because these were the only statistically significant (p<.05) protective variants in the Malawi sample on which malarial retinopathy was measured, but future work could further test the model in Figure 1 by looking at additional genetic variants that have been found to affect the risk of malaria in other sites in Africa (Malaria Genomic Epidemiology Network, 2014). Our study only addresses CM pathogenesis in children. Adult and pediatric CM have important clinical differences and our results may not be generalizable to adults with Ret- CM. Detection of the presence or absence of malarial retinopathy was determined by several ophthalmologists over the 11 year duration of data collection, the sensitivity of detection of retinal changes may have varied between practitioners. Malarial retinopathy was determined on the basis of ophthalmoscopy alone, but since the time of our study, techniques such as optical coherence tomography that may increase sensitivity have been developed (Joshi et al., 2017). We measure malarial retinopathy at the time of admission, but patients are admitted at different points on the disease trajectory. Malarial retinopathy can change over time; it doesn’t resolve during the 2–4 days of hospitalization but can become worse, which is a poor prognostic sign. Although there are limitations in our study to the sensitivity with which malarial retinopathy is measured, even if a moderate number of Ret- CM cases should be Ret+ CM cases in Table 2, e.g., if the false omission rate is .5 and the false discovery rate is 0, there is still strong evidence that HbAS has a protective effect for Ret- CM (p-value=0.007; odds ratio: 6.81, 95% CI: (1.50, $\infty$)). Our main analysis assumed that possession of HbAS or BGO does not affect malaria parasitemia incidence; however, sensitivity analyses showed that our results were not sensitive to plausible violations of this assumption. Our analysis assumed that HbAS and BGO do not have selection effects on which CM cases are admitted to the Paediatric Research Ward as opposed to dying before reaching the Paedieatric Research Ward or being cured before needing to be referred to the ward; another interpretation of our study is that instead of studying ‘cerebral malaria’ as such, we have studied, ‘cerebral malaria mild enough to make it to the ward but severe enough not to recover without being taken to the ward.’ Some of the non-malaria hospital controls had malaria parasitemia; since children can sometimes develop severe malaria with relatively low levels of parasitemia, it is possible that malaria contributed to the illness in these control participants. Furthermore, older non-malaria hospital controls may have a selection bias for HbAS since they have survived to an older age (Ackerman et al., 2005). Our results are robust to considering only the community controls (Appendix 1—table 4) which do not suffer from these potential biases of the non-malaria hospital controls.

In summary, we studied a natural experiment that alters the level of malaria illness experienced by children through genetic variation and found evidence that malaria parasitemia is on the causal pathway to a substantial proportion of Ret- CM cases. Our approach of using genetically inherited traits to study CM pathogenesis could be adapted to illuminate the pathogenesis of other diseases.

1. 1. Malaria Genomic Epidemiology Network

   (2015) Genome-wide study of resistance to severe malaria

   Access to this data is available through application to the MalariaGen Independent Data Access Committee. Please see https://www.malariagen.net/data/terms-use/human-gwas-data for more information.

   https://www.malariagen.net/data/genome-wide-study-resistance-severe-malaria-eleven-populations

1. 1. Ackerman H
   2. Usen S
   3. Jallow M
   4. Sisay-Joof F
   5. Pinder M
   6. Kwiatkowski DP

   (2005) A comparison of case-control and family-based association methods: the example of sickle-cell and malaria

   Annals of Human Genetics 69:559–565.

   https://doi.org/10.1111/j.1529-8817.2005.00180.x

   • PubMed
   • Google Scholar
2. 1. Barrera V
   2. Hiscott PS
   3. Craig AG
   4. White VA
   5. Milner DA
   6. Beare NA
   7. MacCormick IJ
   8. Kamiza S
   9. Taylor TE
   10. Molyneux ME
   11. Harding SP

   (2015) Severity of retinopathy parallels the degree of parasite sequestration in the eyes and brains of malawian children with fatal cerebral malaria

   Journal of Infectious Diseases 211:1977–1986.

   https://doi.org/10.1093/infdis/jiu592

   • PubMed
   • Google Scholar
3. 1. Bearden D

   (2012) Retinopathy in cerebral malaria: new answers, new puzzles

   Neurology 79:1196–1197.

   https://doi.org/10.1212/WNL.0b013e31826aad9d

   • PubMed
   • Google Scholar
4. 1. Beare NA
   2. Southern C
   3. Lochhead J
   4. Molyneux ME
   5. Lewallen S
   6. Harding SP

   (2002) Inter-observer concordance in grading retinopathy in cerebral malaria

   Annals of Tropical Medicine & Parasitology 96:105–108.

   https://doi.org/10.1179/000349802125000565

   • PubMed
   • Google Scholar
5. 1. Beare NA
   2. Taylor TE
   3. Harding SP
   4. Lewallen S
   5. Molyneux ME

   (2006) Malarial retinopathy: a newly established diagnostic sign in severe malaria

   The American Journal of Tropical Medicine and Hygiene 75:790–797.

   https://doi.org/10.4269/ajtmh.2006.75.790

   • PubMed
   • Google Scholar
6. 1. Benichou J
   2. Armitage P
   3. Colton T

   (1998)

   Encyclopedia of Biostatistics

   Attributable Risk, Encyclopedia of Biostatistics, United States, John Wiley & Sons.

   • Google Scholar
7. 1. Berkson J

   (1946) Limitations of the application of fourfold table analysis to hospital data

   Biometrics Bulletin 2:47–53.

   https://doi.org/10.2307/3002000

   • PubMed
   • Google Scholar
8. 1. Cserti CM
   2. Dzik WH

   (2007) The ABO blood group system and plasmodium falciparum malaria

   Blood 110:2250–2258.

   https://doi.org/10.1182/blood-2007-03-077602

   • PubMed
   • Google Scholar
9. 1. Diallo TO
   2. Remoue F
   3. Gaayeb L
   4. Schacht AM
   5. Charrier N
   6. De Clerck D
   7. Dompnier JP
   8. Pillet S
   9. Garraud O
   10. N'Diaye AA
   11. Riveau G

   (2010) Schistosomiasis coinfection in children influences acquired immune response against Plasmodium falciparum malaria antigens

   PLoS One 5:e12764.

   https://doi.org/10.1371/journal.pone.0012764

   • PubMed
   • Google Scholar
10. 1. Greenland S
    2. Robins JM

    (1988) Conceptual problems in the definition and interpretation of attributable fractions

    American Journal of Epidemiology 128:1185–1197.

    https://doi.org/10.1093/oxfordjournals.aje.a115073

    • PubMed
    • Google Scholar
11. 1. Joshi V
    2. Agurto C
    3. Barriga S
    4. Nemeth S
    5. Soliz P
    6. MacCormick IJ
    7. Lewallen S
    8. Taylor TE
    9. Harding SP

    (2017) Automated detection of malarial retinopathy in digital fundus images for improved diagnosis in malawian children with clinically defined cerebral malaria

    Scientific Reports 7:42703.

    https://doi.org/10.1038/srep42703

    • PubMed
    • Google Scholar
12. 1. Lewallen S
    2. Harding SP
    3. Ajewole J
    4. Schulenburg WE
    5. Molyneux ME
    6. Marsh K
    7. Usen S
    8. White NJ
    9. Taylor TE

    (1999) A review of the spectrum of clinical ocular fundus findings in P. falciparum malaria in African children with a proposed classification and grading system

    Transactions of the Royal Society of Tropical Medicine and Hygiene 93:619–622.

    https://doi.org/10.1016/S0035-9203(99)90071-8

    • PubMed
    • Google Scholar
13. 1. MacCormick IJ
    2. Maude RJ
    3. Beare NA
    4. Borooah S
    5. Glover S
    6. Parry D
    7. Leach S
    8. Molyneux ME
    9. Dhillon B
    10. Lewallen S
    11. Harding SP

    (2015) Grading fluorescein angiograms in malarial retinopathy

    Malaria Journal 14:367.

    https://doi.org/10.1186/s12936-015-0897-7

    • PubMed
    • Google Scholar
14. 1. Malaria Genomic Epidemiology Network

    (2008) A global network for investigating the genomic epidemiology of malaria

    Nature 456:732–737.

    https://doi.org/10.1038/nature07632

    • PubMed
    • Google Scholar
15. 1. Mallewa M
    2. Vallely P
    3. Faragher B
    4. Banda D
    5. Klapper P
    6. Mukaka M
    7. Khofi H
    8. Pensulo P
    9. Taylor T
    10. Molyneux M
    11. Solomon T

    (2013) Viral CNS infections in children from a malaria-endemic area of Malawi: a prospective cohort study

    The Lancet Global Health 1:e153–e160.

    https://doi.org/10.1016/S2214-109X(13)70060-3

    • PubMed
    • Google Scholar
16. 1. Migot-Nabias F
    2. Mombo LE
    3. Luty AJ
    4. Dubois B
    5. Nabias R
    6. Bisseye C
    7. Millet P
    8. Lu CY
    9. Deloron P

    (2000) Human genetic factors related to susceptibility to mild malaria in Gabon

    Genes and Immunity 1:435–441.

    https://doi.org/10.1038/sj.gene.6363703

    • PubMed
    • Google Scholar
17. 1. Milner DA
    2. Lee JJ
    3. Frantzreb C
    4. Whitten RO
    5. Kamiza S
    6. Carr RA
    7. Pradham A
    8. Factor RE
    9. Playforth K
    10. Liomba G
    11. Dzamalala C
    12. Seydel KB
    13. Molyneux ME
    14. Taylor TE

    (2015) Quantitative assessment of multiorgan sequestration of parasites in fatal pediatric cerebral malaria

    Journal of Infectious Diseases 212:1317–1321.

    https://doi.org/10.1093/infdis/jiv205

    • PubMed
    • Google Scholar
18. 1. Miura K

    (2016) Progress and prospects for blood-stage malaria vaccines

    Expert Review of Vaccines 15:765–781.

    https://doi.org/10.1586/14760584.2016.1141680

    • PubMed
    • Google Scholar
19. 1. Modiano D
    2. Luoni G
    3. Sirima BS
    4. Simporé J
    5. Verra F
    6. Konaté A
    7. Rastrelli E
    8. Olivieri A
    9. Calissano C
    10. Paganotti GM
    11. D'Urbano L
    12. Sanou I
    13. Sawadogo A
    14. Modiano G
    15. Coluzzi M

    (2001) Haemoglobin C protects against clinical plasmodium falciparum malaria

    Nature 414:305–308.

    https://doi.org/10.1038/35104556

    • PubMed
    • Google Scholar
20. 1. Méndez D
    2. Hernáez ML
    3. Kamali AN
    4. Diez A
    5. Puyet A
    6. Bautista JM

    (2012) Differential carbonylation of cytoskeletal proteins in blood group O erythrocytes: potential role in protection against severe malaria

    Infection, Genetics and Evolution 12:1780–1787.

    https://doi.org/10.1016/j.meegid.2012.06.013

    • Google Scholar
21. 1. Nedelman J

    (1988) The prevalence of malaria in Garki, Nigeria: double sampling with a fallible expert

    Biometrics 44:635–655.

    https://doi.org/10.2307/2531580

    • PubMed
    • Google Scholar
22. 1. Ntoumi F
    2. Mercereau-Puijalon O
    3. Ossari S
    4. Luty A
    5. Reltien J
    6. Georges A
    7. Millet P

    (1997) Plasmodium falciparum: sickle-cell trait is associated with higher prevalence of multiple infections in gabonese children with asymptomatic infections

    Experimental Parasitology 87:39–46.

    https://doi.org/10.1006/expr.1997.4173

    • PubMed
    • Google Scholar
23. 1. Obaro S
    2. Greenwood B

    (2011) Malaria and bacteraemia in African children

    The Lancet 378:1281–1282.

    https://doi.org/10.1016/S0140-6736(11)61146-X

    • Google Scholar
24. 1. Postels DG
    2. Birbeck GL

    (2011) Children with retinopathy-negative cerebral malaria: a pathophysiologic puzzle

    The Pediatric Infectious Disease Journal 30:953–956.

    https://doi.org/10.1097/INF.0b013e3182271c69

    • PubMed
    • Google Scholar
25. Software

    1. R Development Core Team

    (2016)

    R: A Language and Environment for Statistical Computing

    R Foundation for Statistical Computing, Vienna , Austria.
26. 1. Rice JA

    (2007)

    Mathematical Statistics and Data Analysis Vol. 72

    Mathematical Statistics and Data Analysis Vol. 72, 3rd edn, Belmont, CA, United States: Duxbury Press.

    • Google Scholar
27. 1. Malaria Genomic Epidemiology Network

    (2014) Reappraisal of known malaria resistance loci in a large multicenter study

    Nature Genetics 46:1197–1204.

    https://doi.org/10.1038/ng.3107

    • PubMed
    • Google Scholar
28. 1. Rosenbaum PR

    (1987) The role of a second control group in an observational study

    Statistical Science 2:292–306.

    https://doi.org/10.1214/ss/1177013232

    • Google Scholar
29. Book

    1. Rosenbaum P

    (2002) Observational Studies (2nd edn)

    New York: Springer-Verlag.

    https://doi.org/10.1007/978-1-4757-3692-2

    • Google Scholar
30. 1. Rothman KJ

    (1976) Causes

    American Journal of Epidemiology 104:587–592.

    https://doi.org/10.1093/oxfordjournals.aje.a112335

    • PubMed
    • Google Scholar
31. 1. Rowe JA
    2. Handel IG
    3. Thera MA
    4. Deans AM
    5. Lyke KE
    6. Koné A
    7. Diallo DA
    8. Raza A
    9. Kai O
    10. Marsh K
    11. Plowe CV
    12. Doumbo OK
    13. Moulds JM

    (2007) Blood group O protects against severe plasmodium falciparum malaria through the mechanism of reduced rosetting

    PNAS 104:17471–17476.

    https://doi.org/10.1073/pnas.0705390104

    • PubMed
    • Google Scholar
32. 1. Scott JA
    2. Berkley JA
    3. Mwangi I
    4. Ochola L
    5. Uyoga S
    6. Macharia A
    7. Ndila C
    8. Lowe BS
    9. Mwarumba S
    10. Bauni E
    11. Marsh K
    12. Williams TN

    (2011) Relation between falciparum malaria and bacteraemia in kenyan children: a population-based, case-control study and a longitudinal study

    The Lancet 378:1316–1323.

    https://doi.org/10.1016/S0140-6736(11)60888-X

    • PubMed
    • Google Scholar
33. 1. Seydel KB
    2. Fox LL
    3. Glover SJ
    4. Reeves MJ
    5. Pensulo P
    6. Muiruri A
    7. Mpakiza A
    8. Molyneux ME
    9. Taylor TE

    (2012) Plasma concentrations of parasite histidine-rich protein 2 distinguish between retinopathy-positive and retinopathy-negative cerebral malaria in malawian children

    Journal of Infectious Diseases 206:309–318.

    https://doi.org/10.1093/infdis/jis371

    • PubMed
    • Google Scholar
34. 1. Seydel KB
    2. Kampondeni SD
    3. Valim C
    4. Potchen MJ
    5. Milner DA
    6. Muwalo FW
    7. Birbeck GL
    8. Bradley WG
    9. Fox LL
    10. Glover SJ
    11. Hammond CA
    12. Heyderman RS
    13. Chilingulo CA
    14. Molyneux ME
    15. Taylor TE

    (2015) Brain swelling and death in children with cerebral malaria

    New England Journal of Medicine 372:1126–1137.

    https://doi.org/10.1056/NEJMoa1400116

    • PubMed
    • Google Scholar
35. 1. Smith GD
    2. Ebrahim S

    (2003) 'Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease?

    International Journal of Epidemiology 32:1–22.

    https://doi.org/10.1093/ije/dyg070

    • PubMed
    • Google Scholar
36. 1. Smith TA

    (2007) Measures of clinical malaria in field trials of interventions against plasmodium falciparum

    Malaria Journal 6:53.

    https://doi.org/10.1186/1475-2875-6-53

    • PubMed
    • Google Scholar
37. 1. Taylor TE
    2. Fu WJ
    3. Carr RA
    4. Whitten RO
    5. Mueller JS
    6. Fosiko NG
    7. Lewallen S
    8. Liomba NG
    9. Molyneux ME
    10. Mueller JG

    (2004) Differentiating the pathologies of cerebral malaria by postmortem parasite counts

    Nature Medicine 10:143–145.

    https://doi.org/10.1038/nm986

    • PubMed
    • Google Scholar
38. 1. Taylor SM
    2. Parobek CM
    3. Fairhurst RM

    (2012) Haemoglobinopathies and the clinical epidemiology of malaria: a systematic review and meta-analysis

    The Lancet Infectious Diseases 12:457–468.

    https://doi.org/10.1016/S1473-3099(12)70055-5

    • PubMed
    • Google Scholar
39. 1. Uneke CJ

    (2007) Plasmodium falciparum malaria and ABO blood group: is there any relationship?

    Parasitology Research 100:759–765.

    https://doi.org/10.1007/s00436-006-0342-5

    • PubMed
    • Google Scholar
40. 1. WHO

    (2000) Severe falciparum malaria

    Transactions of the Royal Society of Tropical Medicine and Hygiene 94:1–90.

    https://doi.org/10.1016/S0035-9203(00)90300-6

    • Google Scholar
41. 1. WHO

    (2014) Severe malaria

    Tropical Medicine & International Health 19:7–131.

    https://doi.org/10.1111/tmi.12313_2

    • PubMed
    • Google Scholar
42. 1. WHO

    (2015)

    World Malaria Report 2015

    World Malaria Report 2015, 243, 978 92 4 1564403.

    • Google Scholar
43. 1. Westreich D

    (2012) Berkson's bias, selection bias, and missing data

    Epidemiology 23:159–164.

    https://doi.org/10.1097/EDE.0b013e31823b6296

    • PubMed
    • Google Scholar
44. 1. Willcox M
    2. Björkman A
    3. Brohult J
    4. Pehrson PO
    5. Rombo L
    6. Bengtsson E

    (1983) A case-control study in Northern Liberia of plasmodium falciparum malaria in haemoglobin S and beta-thalassaemia traits

    Annals of Tropical Medicine & Parasitology 77:239–246.

    https://doi.org/10.1080/00034983.1983.11811704

    • PubMed
    • Google Scholar
45. 1. Williams TN
    2. Mwangi TW
    3. Wambua S
    4. Alexander ND
    5. Kortok M
    6. Snow RW
    7. Marsh K

    (2005) Sickle cell trait and the risk of plasmodium falciparum malaria and other childhood diseases

    The Journal of Infectious Diseases 192:178–186.

    https://doi.org/10.1086/430744

    • PubMed
    • Google Scholar
46. 1. Wilson EB

    (1927) Probable Inference, the law of Succession, and statistical inference

    Journal of the American Statistical Association 22:209–212.

    https://doi.org/10.1080/01621459.1927.10502953

    • Google Scholar

Author details

1. Dylan S Small

   Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, United States

   Contribution

   DSS, Conceptualization, Software, Formal analysis, Investigation, Methodology, Writing—original draft

   For correspondence

   dsmall@wharton.upenn.edu

   Competing interests

   The authors declare that no competing interests exist.

   "This ORCID iD identifies the author of this article:" 0000-0003-4928-2646

2. Terrie E Taylor

   1. Department of Osteopathic Medical Specialties, College of Osteopathic Medicine, Michigan State University, East Lansing, United States
   2. Blantyre Malaria Project, Blantyre, Malawi

   Contribution

   TET, Conceptualization, Resources, Data curation, Investigation, Project administration, Writing—review and editing

   Competing interests

   The authors declare that no competing interests exist.

3. Douglas G Postels

   Department of Neurology and Ophthalmology, College of Osteopathic Medicine, Michigan State University, East Lansing, United States

   Contribution

   DGP, Investigation, Writing—review and editing

   Competing interests

   The authors declare that no competing interests exist.

4. Nicholas AV Beare

   1. Department of Eye and Vision Science, University of Liverpool, Liverpool, United Kingdom
   2. St. Paul’s Eye Unit, Royal Liverpool University Hospital, Liverpool, United Kingdom

   Contribution

   NAVB, Investigation, Writing—review and editing

   Competing interests

   The authors declare that no competing interests exist.

5. Jing Cheng

   Department of Preventive and Restorative Dental Sciences, University of California, San Francisco, San Francisco, United States

   Contribution

   JC, Methodology, Writing—review and editing

   Competing interests

   The authors declare that no competing interests exist.

6. Ian JC MacCormick

   1. Department of Eye and Vision Science, University of Liverpool, Liverpool, United Kingdom
   2. Malawi-Liverpool-Wellcome Trust Clinical Research Programme, Blantyre, Malawi

   Contribution

   IJCM, Investigation, Writing—review and editing

   Competing interests

   The authors declare that no competing interests exist.

7. Karl B Seydel

   1. Department of Osteopathic Medical Specialties, College of Osteopathic Medicine, Michigan State University, East Lansing, United States
   2. Blantyre Malaria Project, Blantyre, Malawi

   Contribution

   KBS, Conceptualization, Resources, Data curation, Investigation, Project administration, Writing—review and editing

   Competing interests

   The authors declare that no competing interests exist.

• 762

  Page views

• 124

  Downloads

• 15

  Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.