Malaria continues to select for sickle cell trait in Central Africa

Abstract

Significance
Sickle cell disease (SCD) is a major cause of death for young children in Africa, which the World Health Organization has declared a public health priority. It is increasingly spreading outside of Africa because of population migrations, and, thus, it will become in the near future a global health concern. It is therefore important to understand how this genetic disorder is maintained in human populations. Although the association between Plasmodium falciparum malaria and SCD is well known, the strength of this association is far from known. Using an extensive cohort of 3,959 persons, distributed over the entire Gabonese Republic, this study shows that P. falciparum malaria continues to exert strong selective pressure in favor of the sickle cell allele.

Full text

Malaria continues to select for sickle cell trait in
Central Africa
Eric Elguero
a,1,2
, Lucrèce M. Délicat-Loembet
a,b,1
, Virginie Rougeron
a,b,1
, Céline Arnathau
a
, Benjamin Roche
c
,
Pierre Becquart
a
, Jean-Paul Gonzalez
d
, Dieudonné Nkoghe
b
, Lucas Sica
b
, Eric M. Leroy
a,b
, Patrick Durand
a
,
Francisco J. Ayala
e,2
, Benjamin Ollomo
b
, François Renaud
a,2,3
, and Franck Prugnolle
a,b,2,3
a
Maladies Infectieuses et Vecteurs, Ecologie, Génétique, Evolution et Contrôle (Unité Mixte de Recherche 5290, Centre National de la Recherche
Scientifique, Institut de Recherche pour le Développement, Université de Montpellier), 34295 Montpellier, France;
b
Evolutionary Parasitology Departement,
Centre International de Recherches Médicales de Franceville, BP 769 Franceville, Gabon;
c
Unité de Modélisation Mathématique et Informatique des
Systèmes Complexes, Unité Mixte Internationale 209, Institut de Recherche pour le Développement, Université Pierre et Marie Curie, 93142 Bondy Cedex,
France;
d
METABIOTA Inc., Emerging Diseases & Biosecurity, Silver Spring, MD 20910;
e
Department of Ecology and Evolutionary Biology, University of
California, Irvine, CA 92697
Contributed by Francisco J. Ayala, March 24, 2015 (sent for review January 2, 2015; reviewed by Richard E. Paul and Stephen M. Rich)
Sickle cell disease (SCD) is a genetic disorder that poses a serious
health threat in tropical Africa, which the World Health Organiza-
tion has declared a public health priority. Its persistence in human
populations has been attributed to the resistance it provides to
Plasmodium falciparum malaria in its heterozygous state, called
sickle cell trait (SCT). Because of migration,SCT is becoming common
outside tropical countries: It is now the most important genetic
disorder in France, affecting one birth for every 2,400, and one of
the most common in the United States. We assess the strength of
the association between SCT and malaria, using current data for
both SCT and malaria infections. A total of 3,959 blood samples
from 195 villages distributed over the entire Republic of Gabon
were analyzed. Hemoglobin variants were identified by using
HPLCy (HPLC). Infections by three species of Plasmodium were
detected by PCR followed by sequencing of a 201-bp fragment of
cytochrome b. An increase of 10% in P. falciparum malaria preva-
lence is associated with an increase by 4.3% of SCT carriers. An
increase of 10 y of age is associated with an increase by 5.5% of
SCT carriers. Sex is not associated with SCT. These strong associa-
tions show that malaria remains a selective factor in current human
populations, despite the progress of medicine and the actions un-
dertaken to fight this disease. Our results provide evidence that
evolution is still present in humans, although this is sometimes
questioned by scientific, political, or religious personalities.
sickle cell disease
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Plasmodium falciparum
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human evolution
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Gabon
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natural selection
Sickle cell disease (SCD) is a serious public health concern,
present mainly in tropical countries, especially Africa (1, 2),
but spreading to many other countries with the increasing pop-
ulation migrations (3, 4). It is due to a mutation of the gene coding
for the β-globin, called the hemoglobin (Hb)S mutated allele,
whereas the wild type is called the HbA allele (5). In the homo-
zygous condition (hereafter denoted as HbSS), this mutation cau-
ses a severe disease, sickle cell anemia, which was almost always
lethal before the advent of modern medicine, and still is where
modern medical care is not available (6, 7). In the heterozygous
condition (HbAS), called sickle cell trait (SCT), the mutation re-
sults in a much milder condition to the point that carriers may go
unnoticed, although it has been associated with a variety of con-
ditions or diseases like hematuria, splenic infarction, and exercise-
related sudden death (8).
The global impact of SCD has been estimated at approximately
275,000 births every year (9) and could reach approximately
400,000 births annually by 2050 according to recent projections
(4). The most affected continent is Africa, where approximately
85% of the cases are located, and where the vast majority of SCD
children do not reach adulthood (10). SCT prevalence is more
than 15% in a great part of Central Africa (7) and reaches 28% in
Gabon (11), with the consequence that on average between 1 and
2% of all born children are affected by SCD.
Besides its importance as a public health threat, SCD holds a
special place in human population biology as a paradigmatic
example of selective advantage of the heterozygotes, leading to
balancing selection. Given that persons carrying the homozygous
HbSS genotype had almost no chance to reproduce, there should
be a steady decrease of the HbS allele frequency with each
generation in the absence of a counteracting force. Thus, the
question arises as to what was the force that maintained the HbS
allele at a high frequency in human populations. Mainly based on
the similarity of the geographical distribution of the two diseases
(malaria and SCD), Haldane (12) hypothesized that SCT could
provide protection against severe forms of malaria. This insight
was substantiated thereafter by Allison (13); see refs. 14 and 15
for historical details and ref. 16 for a review of the proposed
mechanisms of this protective effect. SCD/SCT is now a member
of a set of several other genetic disorders or variants linked to
malaria resistance, as showed by recent studies (17, 18).
Although the principle of SCT protection against severe
malaria as the factor accounting for the high levels of SCT in
some parts of the world is now generally accepted, the details of
Significance
Sickle cell disease (SCD) is a major cause of death for young
children in Africa, which the World Health Organization has
declared a public health priority. It is increasingly spreading
outside of Africa because of population migrations, and, thus, it
will become in the near future a global health concern. It is
therefore important to understand how this genetic disorder is
maintained in human populations. Although the association
between Plasmodium falciparum malaria and SCD is well
known, the strength of this association is far from known. Us-
ing an extensive cohort of 3,959 persons, distributed over the
entire Gabonese Republic, this study shows that P. falciparum
malaria continues to exert strong selective pressure in favor of
the sickle cell allele.
Author contributions:P.B., J.-P.G., L.S., E.M.L., F.R., and F.P.designed research;E.E., L.M.D.-L.,
V.R., C.A., P.B., D.N., E.M.L., P.D., and B.O. performed research; E.E., V.R.,B.R., F.J.A., and F.P.
analyzed data; and E.E., L.M.D.-L., V.R., F.J.A., F.R., and F.P. wrote the paper.
Reviewers: R.E.P., Institut Pasteur; and S.M.R., University of Massachusetts.
The authors declare no conflict of interest.
Freely available online through the PNAS open access option.
1
E.E., L.M.D.-L., and V.R. contributed equally to this work.
2
To whom correspondence may be addressed. Email: fjayala@uci.edu, eric.elguero@ird.fr,
francois.renaud@ird.fr, or franck.prugnolle@ird.fr.
3
F.R. and F.P. contributed equally to this work.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.
1073/pnas.1505665112/-/DCSupplemental.
www.pnas.org/cgi/doi/10.1073/pnas.1505665112 PNAS Early Edition
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EVOLUTION

this interaction are much less known. There is a lack of epi-
demiological studies assessing the strength of the association
between malaria and SCT. Global studies, old (13) or recent (19),
provide compelling evidence in favor of the so-called malaria hy-
pothesis, but are based on historical data of malaria prevalence, and
do not allow a precise estimation of the SCT effect against malaria.
At a global scale, human populations differ in several respects,
including their genetic backgrounds, lifestyles, and access to
healthcare, among others. Moreover, human populations are im-
mersed in diverse environments, especially concerning pathogen
communities. Thus, there exist numerous potentially confounding
factors, likely to obscure the precise relationship between malaria
and SCT.
The aim of this paper is to provide an epidemiological study
investigating the relationship between present-day malaria and
SCT prevalence, at the scale of an African country, namely the
Republic of Gabon. This scale is relevant to address the question
raised; it is large enough for there to be variation in malaria
circulation, and small enough for its populations to have fairly
similar lifestyles in similar environments.
Results
Blood samples were obtained from 4,359 participants, 15–80 y
old, sampled from 220 randomly selected villages,roughlyevenly
distributed among the nine Gabonese provinces (Fig. 1 Aand B).
Because this study focuses on the Bantu population, samples from
Pygmy villages were not included, thus resulting in a cohort of 3,959
participants, 17–80 y old, from 195 villages. Among the 3,959 blood
samples, 859 (21.7%) had the HbAS (SCT) genotype, one had the
HbAC genotype, the remaining samples having the HbAA (nor-
mal) genotype. No sample had the HbSS genotype, thus confirming
the high mortality in childhood associated with SCD. The HbAC
individual—aforeignerfromGhana—was subsequently removed
from the study, resulting in a sample size of 3,958.
Of the 3,958 samples, 2,061 (52%) were positive for Plasmo-
dium cytochrome b(cytb). Of these 2,061 samples, 572 (28%)
could not be used to determine the species, because of an in-
sufficient cytb amplicon concentration. Among the remaining
1,489 samples, 1,387 (93.1%) had Plasmodium falciparum in-
fection, 326 (21.9%) had Plasmodium malariae infection, and 32
(2.1%) had Plasmodium ovale infection. A total of 234 samples
had two infections and 11 samples had three. Table 1 shows the
distribution of samples according to genotype and Plasmodium
species; Table 2 shows the prevalences of HbAS, Plasmodium sp.,
and Plasmodium falciparum for each 10-y age class; Dataset S1
shows detailed information for each of the 195 villages.
Because P. ovale infections were rare (10 only P. ovale and 11
associated with either P. falciparum or P. malariae), and because
infections by P. falciparum and P. malariae were strongly asso-
ciated (Chi-2 =140 on 1 d.f., Pvalue <1.0e−16), we decided to
exclude the P. ovale association with the HbAS genotype, and to
restrict ourselves to two analyses.
P. Falciparum Malaria. In this analysis, the 572 samples infected by
an undetermined Plasmodium species were discarded. The GLM
model showed that SCT was associated with P. falciparum malaria
prevalence: odds-ratio =1.054; 95% confidence interval (c.i.) =
(1.014–1.096); Pvalue =0.008; and with age: odds-ratio =
1.071, 95% c.i. =(1.012–1.13), Pvalue =0.017. Malaria preva-
lence is taken in units of 10%, and age is taken in units of 10 y.
In other words, the odds-ratio for malaria prevalence is given
for a 10% increase in prevalence, and the odds-ratio for age is
given for a 10-y increase of age. The 1.071 odds-ratio implies
that when age changes from 50 y (the sample median) to 60 y, the
SCT prevalence changes from 18.4% to 19.5%, an increase by
5.5%. SCT was not associated with sex: odds-ratio M vs. F: 0.997,
95% c.i. =(0.85–1.17), Pvalue =0.97. Fig. 1 Aand Bshow the
maps of SCT and P. falciparum prevalence. Fig. 1Cshows the
distribution of village SCT prevalence as a function of village
malaria prevalence, as well as the SCT prevalence predicted by
the statistical model.
All-Plasmodium Malaria. Because it is likely that most of the ex-
cluded 572 undetermined infections were actually P. falciparum
infections, removing them could bias the results. Hence, we
performed a subsidiary analysis. In this analysis, the Plasmodium
species was ignored; infection status was taken as positivity to
Plasmodium cytb. The GLM model showed that SCT was asso-
ciated with Plasmodium sp. malaria prevalence: odds-ratio =
1.058, 95% c.i. =(1.012–1.100), Pvalue =0.005, and with age:
odds-ratio =1.072, 95% c.i. =(1.014–1.134), Pvalue =0.015.
SCT was not associated with sex: odds-ratio M vs. F: 0.992, 95%
c.i. =(0.85–1.16), Pvalue =0.92.
Discussion
The main finding of this study is a strong association between
P. falciparum malaria and SCT prevalence. The all-Plasmodium
analysis, yielding almost identical estimates to those obtained for
the analysis of P. falciparum alone, shows that the removal of the
undetermined Plasmodium infections did not result in bias, but
because 90% of all Plasmodium infections are P. falciparum, it
Fig. 1. Map of Gabon. (A) SCT prevalence. Pale yellow, prevalence less than
10%; dark red, prevalence more than 10%; blue dots, sampled villages;
dotted lines, province limits. (B) Malaria prevalence. Pale yellow, prevalence
less than 30%; dark red, prevalence more than 30%. To generate these maps
for each cell of a 200 ×200 grid covering the country, prevalence was
computed from the pooled populations of all villages within a 0.5 degree of
latitude/longitude radius. Province names abbreviations: Est, Estuaire; HtOg,
Haut-Ogoouée; MoyOg, Moyen-Ogoouée; Ngo, Ngounié; Nya, Nyanga;
Oglv, Ogouée-Ivindo; OgLo, Ogoouée-Lolo; OgMar, Ogoouée-Maritime;
WolN, Woleu-Ntem. (C) SCT prevalence as a function of P. falciparum
prevalence. Villages have been grouped by 20%-wide intervals of Pf prev-
alence. Boxes extend from the 25% to the 75% of the distribution, whiskers
extend to 1.5 times the interquartile range, and circles show extreme values.
The orange line shows the SCT prevalence prediction of the statistical model
as a function of Pf prevalence alone. Age has been set to its median value
(49 y), and the random effects have been set to zero.
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does not add new information. Translated into prevalence scale,
the observed odds-ratio of 1.054 for P. falciparum alone means
that when, for example, the malaria prevalence changes from
40% (its average value) to 50%, the number of SCT carriers
changes from 21.1 to 22.0%, that is an increase in number of
SCT carriers by 4.3%. The same change in malaria prevalence
(40–50%) would yield, in the absence of bias introduced by ge-
netic counseling, a change in the prevalence of SCD (homozygotes)
newborns from 4.4 to 4.8%, an increase by more than 9%. Using the
formalism of Hartl and Clark (20), if W
AA
,W
AS
,andW
SS
denote
the fitnesses of the three genotypes, we have here W
SS
=0, we can
assume conventionally that W
AS
=1andthenW
AA
=1−s,wheresis
the selection coefficient against the HbAA genotype. It can be
proved that at equilibrium, s=p/(1−p)wherepis the frequency of
the HbS allele. If we take the 21% HbAS average prevalence in
Gabon, it translates to a HbS frequency p=0.105 and to a selection
coefficient s=0.12, 95% c.i. =(0.110–0.125), a figure comparable to
that of 0.11 found by Cavalli-Sforza and Bodmer (21). If we consider
only those villages where the estimated prevalence of P. falciparum
infection is less than 20%, we find s=0.093, 95% c.i. =(0.070–
0.121), and if on the contrary we consider those villages where the
prevalence is above 60%, we find s=0.135, 95% c.i. =(0.116–0.156).
If we now consider the effect of age, taking an average 50% of P.
falciparum prevalence, we find that the selection coefficient varies
from s=0.118, 95% c.i. =(0.117–0.119) for the cohort of persons
who were 20 y old at the time of the survey, to s=0.121, 95% c.i. =
(0.118–0.123) for persons who were 60 y old.
The positive association between asymptomatic P. falciparum
malaria and SCT prevalence in Bantu villages is consistent with
previous findings, in particular with what Piel et al. observed in
Africa, in a recent and elaborate study (19). There are, however, a
number of differences. First, these authors (19) did not use a
continuous measure of malaria prevalence, but instead a classifi-
cation of endemicity in six levels, from malaria-free to holoen-
demic. Second, they used malaria data from the preintervention
era, which occurred before 1960. Third, having individual data
enabled us to take into account the individual potentially con-
fusing factors of age and sex, although it turned out that only age
was associated with SCT and malaria.
The most significant difference between the present study and
previous ones is that other studies used indices based on clinical
malaria, whereas our estimates of malaria prevalence are based
partly on asymptomatic infections. Indeed, only healthy individuals
were enrolled, but whether the infected individuals were recovering
from a clinical episode, or on the contrary would develop symptoms
sometime after having been sampled, is not known. One could
argue that SCT, by providing protection against clinical malaria (22,
23), should be positively associated with asymptomatic malaria and
negatively associated with clinical malaria. However, mathematical
modeling (24, 25) has shown that, in the long term, high levels of
malaria prevalence select for SCT, and that, in turn, a high SCT
prevalence is associated with a higher prevalence of asymptomatic
malaria, so that SCT prevalence is positively associated with both
asymptomatic and clinical malaria. Hence, our findings demon-
strate a selective effect of P. falciparum malaria on SCT.
The second finding of our study, namely the significant in-
crease of SCT prevalence with age, could be explained by one of
two hypotheses. The first one is thatthesignificantincreaseofSCT
with age could indicate that malariaselectivepressureisrelaxing
with time as a result of improved medical care and prophylaxis, so
that elder people experienced stronger selective pressure in their
youth than today’syoungpeople.Alternatively,theincreaseofSCT
prevalence with age could indicate that the HbAS genotype con-
tinues to provide protection against severe malaria with respect to
the HbAA genotype in adult life.Indeed,contrarytotheonce-
prevailing opinion, immunity to severe malaria is not always ac-
quired in the first years of life (26, 27) and severe malaria is not
uncommon in adults (28, 29).
Sex was not associated with SCT, a result that is not surprising
given that the β-globin gene is autosomal. This lack of associa-
tion between SCT and sex shows that there is no significant
difference in the protection against malaria provided by SCT to
men and women.
The association observed at the level of Gabonese villages
could be of interest from a health management perspective. Vil-
lages with a high level of malaria transmission could be the targets
of coupled antimalaria campaigns and information campaigns
regarding SCD. In any event, malaria and SCD are two entangled
health threats that should be managed synergistically. In Gabon,
given that approximately 21% of the population carries the S al-
lele (11), on average 500 (1%) of the approximately 50,000 chil-
dren born each year in the country (30) will carry the HbSS
genotype and, hence, develop SCD.
The impact of our results goes far beyond the public health
perspectives. To our knowledge, our results constitute one of the
best illustrations that present day humans are still evolving in re-
sponse to the selective pressures imposed by their environment,
notably in the present case, the pathogenic one.
Reports from the scientific, public, and religious communities
have repeatedly claimed that evolution is no longer relevant to
humans and that our species now mostly or only depends on cul-
ture and technology for survival (31). Several studies have provided
clear evidence that selection impacted human evolution after the
agricultural revolution. However, most of the examples are his-
torical (before the industrial era) (see refs. 31 and 32 for reviews)
or concerned populations in the last hundred years (e.g., refs. 33
Table 1. Blood samples classified according to genotype and Plasmodium species
Genotype Not infected Undetermined Plasmodium Pf only Pm only Po only Pf+Pm Pf+Po Pm+Po Pf+Pm+Po Total
HbAA 1,492 446 894 67 10 172 8 2 8 3,099
HbAS 405 126 250 23 0 51 1 0 3 859
Total 1,897 572 1,144 90 10 223 9 2 11 3,958
Pf, Plasmodium falciparum;Pm,Plasmodium malariae;Po,Plasmodium ovale.
Table 2. Prevalences of HbAS genotype, Plasmodium sp infection, and P. falciparum infection
by 10-y age class
Age class 15–24 25–34 35–44 45–54 55–64 65+Total
Sample size 351 537 725 846 1022 477 3,958
HbAS 74 (21.1%) 100 (18.6%) 151 (20.8%) 185 (21.9%) 239 (23.3%) 110 (23.1%) 859
Plasmodium sp 197 (56.1%) 288 (53.6%) 407 (56.1%) 460 (54.4%) 504 (49.3%) 205 (43.0%) 2,061
P. falciparum 144 (41.0%) 206 (38.4%) 276 (38.1%) 285 (33.7%) 344 (33.7%) 132 (27.7%) 1,387
Elguero et al. PNAS Early Edition
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EVOLUTION

and 34). Our results concern present day human populations
(persons born 15–80 y ago) and clearly show that, at least in human
populations of low income, such as in our study, where medical
advances remain limited, biological adaptation is still an outcome
driven by evolution to respond to environmental pressures imposed
by pathogens, in particular malaria.
Materials and Methods
Population Under Study. The Republic of Gabon is a Central African country,
with an area of 270,000 square kilometers and a population of 1.5 million
people (30). The Gabonese populations belong mainly to two ethnocultural
backgrounds: the Bantu people, longtime established farmers, and the
Pygmy people, who traditionally lived a nomadic life in the forest and are
now becoming more and more sedentary (35). Because of this difference in
lifestyle and environment, we decided to exclude pygmies from our study.
We therefore are concerned only with the Bantu populations of Gabon.
Data were collected between June 2005 and September 2008, as part of a
project focused on several pathogens in Gabon (36). First, 220 villages were
randomly selected, out of the 2,056 Gabonese villages, so as to cover evenly
the nine Gabonese provinces. In the 220 villages, all healthy volunteers over
the age of 15 who had been residing in the village for more than one year
were included in the study, resulting in 4,349 participants. Fig. 1 Aand B
show the location of the included villages.
Written consent was secured from all participants. In the case of minors,
consent was obtained from at least one parent. Our study was approved by
the Gabonese Ministry of Health on March 15, 2005, with research autho-
rization No. 00093 for our samples.
Detection of Hemoglobin Variants. The presence of abnormal hemoglobin was
ascertained by isoelectric focusing. When an abnormal protein was detected,
HPLCy was used to identify the variant, HbS or HbC (37, 38), according to the
protocol described in ref. 39. Details of the procedures are described (11).
Plasmodium Detection and Species Determination. Plasmodium infection data
were obtained by a two-step process. We first tested the blood samples for
Plasmodium cytb mitochondrial sequences by nested PCR, as described (40). To
identify the Plasmodium species present in each positive sample, we used deep
sequencing. More particularly, we usedthe454GS-FLXTitaniumtechnologyon
pools of several hundreds of samples amplified for a fragment of 201 bp (Table
S1 and Table S2). A sample was considered infected with a given species of
Plasmodium when the proportion of reads attributed to that species was at least
5% of all reads for that sample. Details are given in SI Materials and Methods.
Statistical Analyses. The association between SCT and the intensity of malaria
circulation in the living environment of a given individual was assessed by
logistic regression (41). A proxy for malaria circulation was taken asthe malaria
prevalence in the individual’s village, as estimated by the proportion of carriers
among the sampled individuals. To take into account the hierarchical sam-
pling, we introduced two nested random effects: village and province (42).
Included potential confounders were sex and age. All computations were
performed with the R software and specifically the lme4 package (43, 44).
ACKNOWLEDGMENTS. The authors thank Centre National de la Recherche
Scientifique (CNRS), Centre International de Recherche Médicales de France-
ville (CIRMF) and Institut de Recherche pour le Développement (IRD) for gen-
eral support, International Atomic Energy Agency (IAEA) for the funding of
the Center for sickle-cell screening and for supporting the national program
on neonatal diagnosis in Libreville, Gabon, and Dr. Krishnamoorty Rajagopal
from Institut National de la Santé et de la Recherche Médicale (INSERM) for
initiating research on Sickle Cell Disease at CIRMF. This research was funded by
Agence Nationale de la Recherche (ANR) Grant ORIGIN, JCJC 012.
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