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Infection and Immunity, February 2001, p. 996-1001, Vol. 69, No. 2
0019-9567/01/$04.00+0 DOI: 10.1128/IAI.69.2.996-1001.2001
Copyright © 2001, American Society for Microbiology. All rights reserved.
Familial Correlation of Immunoglobulin G
Subclass Responses to Plasmodium falciparum Antigens in
Burkina Faso
Christophe
Aucan,1
Yves
Traoré,2
Francis
Fumoux,1 and
Pascal
Rihet1,*
Université de la
Méditerranée, EA 864, Marseille,
France,1 and Centre Muraz,
O.C.C.G.E., Bobo-Dioulasso, Burkina Faso2
Received 8 August 2000/Accepted 15 November 2000
 |
ABSTRACT |
Host genes are thought to determine the immune response to malaria
infection and the outcome. Cytophilic antibodies have been associated
with protection, whereas noncytophilic antibodies against the same
epitopes may block the protective activity of the protective ones. To
assess the contribution of genetic factors to immunoglobulin G (IgG)
subclass responses against conserved epitopes and Plasmodium falciparum blood-stage extracts, we analyzed the isotypic
distribution of the IgG responses in 366 individuals living in two
differently exposed areas in Burkina Faso. We used one-way analysis of
variance and pairwise estimators to calculate sib-sib and
parent-offspring correlation coefficients, respectively. Familial
patterns of inheritance of IgG subclass responses to defined antigens
and P. falciparum extracts appear to be similar in the
two areas. We observed a sibling correlation for the IgG, IgG1, IgG2,
IgG3, and IgG4 responses directed against ring-infected-erythrocyte
surface antigen, merozoite surface protein 1 (MSP-1), MSP-2, and
P. falciparum extract. Moreover, a parent-offspring
correlation was found for several IgG subclass responses, including the
IgG, IgG1, IgG2, IgG3, and IgG4 responses directed against conserved
MSP-2 epitopes. Our results indicated that the IgG subclass responses
against P. falciparum blood-stage antigens are partly
influenced by host genetic factors. The localization and
identification of these genes may have implications for
immunoepidemiology and vaccine development.
 |
INTRODUCTION |
Plasmodium falciparum
malaria affects more than 2 million people and remains a major public
health problem in many developing countries. Host immune responses are
critical to strategies for the control of both infection and
pathology. In particular, antibody-dependent cellular mechanisms
are thought to be central in the elimination of the parasite
(1, 2, 5), and increased proinflammatory immune response
is associated with severe malaria (11).
Immunoglobulin G1 (IgG1) and IgG3 are considered cytophilic and
protective against P. falciparum, whereas IgG4 is thought to
be neither and to block protective mechanisms. Furthermore, IgG2, which
binds the H131 allelic form of Fc
RIIA, may be involved in human
resistance to malarial infection (2).
In this context, several investigators have sought to determine whether
genetic factors control host immune responses to P. falciparum antigens. Taylor et al. reported that antibody
responses to merozoite surface protein 1 (MSP-1), MSP-2, and Pfs260/230 were similar in identical and nonidentical twins and proposed that
antibody responses to malaria antigens in immune individuals result
from clonal imprinting (30). However, antibody responses to ring-infected-erythrocyte surface antigen (RESA) were found to be
more concordant within monozygotic twin pairs than in dizygotic twin pairs (26). Similarly, Jepson et al. obtained
evidence for genetic control of cell-mediated immune responses and
levels of IgG antibody to various P. falciparum antigens
(12). Furthermore, familial correlation of some IgG
responses against RESA and MSP-2 was found in Papua New
Guinea (28). Therefore, human immune responses to P. falciparum antigens appear to be, at least in part, genetically regulated.
HLA class II-associated nonresponsiveness has been reported for the
candidate malaria vaccine Spf66 (19). In contrast,
antibody responses induced by natural exposure to malaria infection
show little association with HLA expression (25, 30, 32).
Twin studies indicate that the genetic contribution of non-HLA genes to
the human immune responses to P. falciparum antigens exceeds that of the HLA genes (12, 26).
Immunogenetic polymorphisms likely affect susceptibility to malaria
infection or disease, and the identification of genes controlling human
immune responses to malaria is of major interest. In urban
subjects in Burkina Faso, we recently detected a linkage between blood
infection levels and chromosome 5q31-q33, which contains numerous
genes encoding immunological molecules (22). In the same
population, moreover, we observed an association between high IgG2 and
low IgG4 levels on the one hand and resistance to P. falciparum malaria on the other (2).
In this study, we focused on the genetic control of the IgG subclass
responses to specific P. falciparum antigens by
investigating 75 families from two differently exposed areas in Burkina
Faso. We evaluated the degree of resemblance among family members with respect to the levels of antibody directed against RESA, MSP-1, and
MSP-2 conserved epitopes and crude P. falciparum antigens. We present here the correlations among sibling pairs and
parent-offspring pairs.
 |
MATERIALS AND METHODS |
Study area, subjects, and plasma samples.
The study
population lived for more than 20 years in an urban district of
Bobo-Dioulasso, Burkina Faso, and in a rural area southwest of the
city. The population structure and the area of parasite exposure were
described extensively elsewhere (21, 31). Informed consent
for multiple immunoparasitological and clinical surveys was obtained
individually from all participants. The Medical Authority of Burkina
Faso approved the study protocol. Malaria transmission was assessed by
determining the number of infective bites per person per year at
different capture sites during 2 years (31). Three and
four capture sites were chosen in the urban district and in the rural
area, respectively. The numbers of infective bites per person per year
calculated in the three urban capture sites were similar, and only
slight differences among the four rural capture sites were recorded.
The number of infective bites per person per year was less than 30 in
the urban area and more than 230 in the village (21).
Seventy-five informative families, which had at least two available
sibs each, were selected for immunoanalyses; 34 and 41 nuclear families
were from the urban area and the rural area, respectively. Blood
samples were taken from 366 individuals by venipuncture in July 1994 (n = 273), at the end of the dry season (P1), and in
December 1994 (n = 334), at the end of the rainy season
(P2). The distributions of available sibship sizes were as follows: 3, 11, 7, 11, and 2 sibships from the urban area contained 2, 3, 4, 5, and
6 sibs, respectively, and 23, 15, 2, and 1 sibships from the rural area
contained 2, 3, 4, and 5 sibs, respectively. The descriptive statistics
for the study subjects are in Table 1.
P. falciparum blood-stage extract and
peptides.
The P. falciparum W2 strain (Southeast Asia)
was maintained and synchronized as previously described
(15). When the parasitemia reached 10%, schizont-infected
red blood cells were treated with 0.15% saponin. Isolated schizonts
were sonicated on ice in phosphate-buffered saline containing protease
inhibitors (50 µM phenylmethylsulfonyl fluoride, 50 µg of
aprotinin/ml, 1 µM pepstatin, 20 µg of leupeptin/ml, 10 µg of
2-macroglobulin/ml). Sonicates were
centrifuged, and the supernatants were filtered through a
0.22-µm-pore-size membrane. These P. falciparum crude
extracts were aliquoted and stored at
70°C until use.
Five synthetic peptides corresponding to highly conserved B-cell
epitopes were used: (i) the epitope (EENV)4 of
the C-terminal part of RESA (20), which is immunodominant
and antibodies to which were associated with resistance to clinical
malaria (23); (ii) the epitope KLYQAQYDLSF, representing
amino acids 277 to 287 of the N-terminal conserved part of MSP-1
(MSP-1-Nt) (18), antibodies to which were significantly
associated with clinical protection (24); (iii) the
epitope KAASNTFINNA, representing amino acids 27 to 34 of the
N-terminal conserved region of MSP-2 (MSP-2-Nt); (iv) the epitope
AAAQHGHMHGS, representing amino acids 199 to 206 of the C-terminal
conserved region of MSP-2 (MSP-2-Ct1); and (v) the epitope AAANTSDSQKE,
representing amino acids 213 to 220 of the C-terminal conserved region
of MSP-2 (MSP-2-Ct2) (13).
Specific IgG isotype titration by ELISA.
Enzyme-linked
immunosorbent assay (ELISA) plates (Nunc) were coated either with 1 µg of P. falciparum extract/ml in sodium carbonate buffer
(100 mM, pH 9.6) or with 10 µg of peptides conjugated to
glutaraldehyde-activated poly-L-lysine/ml
(3). Plates were saturated with 3% bovine serum albumin
in phosphate-buffered saline. Serum dilutions were incubated for
16 h at 4°C (1:20 for IgG2 and IgG4, 1:100 for IgG1 and IgG3,
and 1:400 for IgG). The following monoclonal antibodies were used:
anti-IgG1 (clone 8c/6-39; The Binding Site), IgG2 and IgG3 (clone HP
6002 and HP 6050; Clinisciences), and IgG4 (clone RJ4; Immunotech).
Total IgG was detected using a goat F(ab')2
anti-human IgG (Jackson Laboratories). The anti-IgG1 and -IgG were
conjugated to alkaline phosphatase, the anti-IgG2 and -IgG3 were
biotinylated, and the anti-IgG4 was unlabeled. F(ab')2 anti-mouse IgG conjugated to alkaline
phosphatase was used for IgG4 detection. Signal amplification was
performed for IgG2 and IgG3 detection by using streptavidin and
biotinylated alkaline phosphatase (Pierce); the sensitivity of the
assay was 30-fold higher than that of the assay using the same
monoclonal antibodies conjugated to alkaline phosphatase. After 2 h of incubation at room temperature, enzymatic activities were revealed
by p-nitrophenyl phosphate (Sigma) (1 mg/ml) in Tris buffer
(pH 9.6). The optical densities were read at 405 nm using a DIAS
automatic plate reader (Dynex Technology).
Thirty negative reference sera were used to determine the detection
threshold; competition experiments using IgG1, IgG2, IgG3, and IgG4
purified from myeloma were performed to check the specificity and sensitivity of ELISAs. No cross-reaction was observed. A pool of
200 samples was used to draw standard curves. All tests were done in
duplicate, and antibody levels were calculated by using the
standard curve and were expressed as arbitrary units (AU). To allow for
zero values in further analyses, we applied a logarithmic transformation based on log(1+AU) (LAU) to the AU.
Data adjustment and phenotype of interest.
We first compared
the antibody levels measured at P1 and at P2. The correlation was
assessed by Spearman's rank test and linear regression analysis. As
previously described, we detected significant variation of some
antibody levels between P1 and P2 using the paired Student's
t test (2). We therefore took into account the
influence of the date of bleeding in further calculations. The mean LAU
and standard deviation were calculated at P1 and at P2. To correct the
individual LAU for the visit effect, the LAU was standardized at
P1 and at P2, and the mean of adjusted LAU (MALAU) was calculated
for each subject.
The influence of the covariates on MALAU was assessed by analysis of
variance (ANOVA) for categorical variables and by Spearman's rank
correlation and polynomial regression for age. The factors tested were
sex, ethnic group in the urban area, which was classified as one of
four major groups (Mossi, Dafing, Bissa, and others), and age, which
was expressed in years and considered a quantitative variable.
Covariates with a significant effect on MALAU were retained for
adjustment. The standardized residual was used to estimate familial correlations.
Familial correlations.
To assess whether the antibody
response to defined B-cell epitopes and crude antigens was correlated
within families, we estimated sibling-sibling and parent-offspring
correlation coefficients. The methods for measuring such correlations
are detailed elsewhere (8, 9). Briefly, we used the ANOVA
estimator for inferences concerning sibling correlations and the
pairwise estimators for inferences concerning parent-offspring
correlations. Families with sibships having only one member were
excluded from the analysis.
(i) Estimator of sibling correlations.
The phenotype,
defined above as the age-adjusted and standardized residual score from
regression analysis, was used to compute a one-way ANOVA. The
observations were grouped by family to provide estimates for the
variability within families and the variability between families. The
mean squared between-family variance (MSB) and the mean squared
within-family variance (MSW) were calculated, and the ratio of these
variance components was used to measure sibling resemblance. If the
siblings are similar with respect to the phenotype, MSW is small and
MSB is high. The intraclass correlation coefficient
Rss was computed as previously
recommended (9): (MSB
MSW)/(MSB
MSW + koMSW). ko is calculated as
where N is the number of families, K is
the total number of observations, and ki
is the number of sibs in the ith family. We tested the
significance for Rss through the usual
ANOVA F statistic.
(ii) Estimators of parent-offspring correlations.
We used
the pairwise estimator (Rpo) and the
family-weighted pairwise estimator
(Rfw). The former is obtained by
computing the standard Pearson product-moment correlation over all
possible parent-offspring pairs that can be formed from the sample
data. The family-weighted pairwise estimator is obtained by computing the standard Pearson product-moment correlation between the parent phenotype and the average phenotype over all children in a family. This
estimator was more suitable when sibling correlation was fairly large
(Rss > 0.5). The estimators of
parent-offspring correlation (Rpo and
Rfw) were tested for their statistical
significance by computing the ratio (Z) of
Rpo and
Rfw by their estimated large-sample standard error (8, 9). The resulting test statistic that takes into account the sibling correlation is given by an approximate standard normal deviate (8, 9) as follows:
 |
RESULTS |
Presentation of the data and calculation of the phenotypes.
In
the rural area, the IgG subclass levels in July (P1) and in December
(P2) were correlated (data not shown). In the urban area, antibody
responses were also correlated between P1 and P2, except for the IgG4
responses against RESA, MSP-1-Nt, and MSP-2-Ct1. As previously
described (2), the date of bleeding influenced the IgG
subclass levels. We therefore adjusted the IgG subclass levels for the
bleeding effect, and we used the mean of the adjusted IgG subclass
levels in further analyses. In addition, this calculation made the
phenotypes in the two areas comparable.
In the rural and urban areas, there was no significant effect of sex or
ethnic group on the IgG subclass levels whatever the antigen used (data
not shown). In contrast, age had a significant effect on anti-P.
falciparum extract IgG levels of all subclasses (Table
2). Moreover, age was positively
correlated with anti-RESA, -MSP-1, and -MSP-2 IgG, IgG2, and IgG3
levels in the rural and urban areas (Table 2). Age significantly
influenced anti-RESA, -MSP-1, and -MSP-2 IgG4 levels in the rural area.
Where appropriate, age was retained for adjustment and calculation of
the phenotypes.
The IgG subclass responses of sibs are correlated.
Sibling
correlation coefficients are presented in Table
3. In the urban area, significant sib-sib
correlations were found for most of the IgG subclass responses, except
for the IgG3 response against RESA and the IgG2 and IgG responses
against crude extract. The IgG responses against RESA, MSP-1-Nt,
MSP-2-Nt, MSP-2-Ct1, and MSP-2-Ct2 were correlated between sibs. In the
rural area, most of the IgG subclass responses of sibs were also
correlated. Interestingly, the IgG subclass responses, the sibling
correlation of which was not significant, were not the same in the
urban and rural areas. If the two populations are included in the
analysis, all the IgG responses of sibs were correlated, and the
correlation coefficients ranged from 0.13 to 0.39. Furthermore, we also
observed sib-sib correlations when selecting individuals under 7 years old (n = 78), who are of special interest when the
outcome of infection and protective immunity are being studied.
For example, the IgG1, IgG2, IgG3, and IgG4 responses against
MSP-1-Nt, MSP-2-Nt, MSP-2-Ct1, and MSP-2-Ct2 were correlated between
sibs (P < 0.05).
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TABLE 3.
Sib-sib correlation coefficients for the IgG subclass
responses to defined and crude P. falciparum antigensa
|
|
Parent-offspring correlations.
Table
4 shows the parent-offspring correlations
in antibody isotype responses. First, we computed the standard Pearson
product-moment correlation over all possible parent-offspring pairs. In
each area, most of the parent-offspring correlations were not
significant; the mother-offspring correlations were nevertheless
frequently significant. When the individuals from the two populations
were analyzed, the mother-offspring correlations were significant, except for the IgG1, IgG2, IgG3, and IgG4 responses against RESA, the
IgG2 and IgG responses against MSP-1, and the IgG1 and IgG responses
against crude extract. The father-offspring correlations were less
frequently significant, but they generally confirmed most of the
mother-offspring correlations. This difference of significance may be
explained by the smaller number of fathers (n = 56)
than mothers (n = 72).
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TABLE 4.
Parent-offspring correlation coefficients for the IgG
subclass responses to defined and crude P. falciparum antigensa
|
|
We also evaluated the family-weighted estimator by pairing the mean of
the offspring phenotypes with the phenotype of their fathers or mothers
and by computing the Pearson product-moment correlation over the
resulting pairs (data not shown). We confirmed all the parent-offspring
correlations found using the pairwise method. We also found additional
parent-offspring correlations. For example, in the rural area, there
were mother-offspring correlations for the IgG4 responses against RESA
and MSP-2-Nt and father-offspring correlations for the IgG4 response
against MSP-2-Nt and MSP-2-Ct1.
The IgG1, IgG2, IgG3, and IgG responses of spouses were not correlated
except for the IgG1 response against MSP-2-Nt and the IgG response
against RESA. Strikingly, the IgG4 responses of spouses were correlated
(data not shown).
 |
DISCUSSION |
Since particular IgG subclass responses were found to be
associated with resistance to malaria (1, 4, 6, 10, 14, 17,
29), genes controlling such responses may affect the resistance or the susceptibility to malarial infection or disease in humans. In
this study, we evaluated familial correlation of IgG subclass responses
against RESA, MSP-1, and MSP-2 conserved B epitopes and crude P. falciparum antigens in two populations living in differently
exposed areas in Burkina Faso. To overcome the confounding effect of
the antigen polymorphisms, we deliberately focused on conserved protein
sequences commonly expressed by parasites, and we used a P. falciparum strain from Asia to prepare crude extract. We estimated
sib-sib correlations and parent-offspring correlations through the
variance analysis and the pairwise methods, respectively (9). We took into account covariates that significantly
influenced the phenotype.
Age had a strong influence on parasite-specific IgG2 and IgG3 levels in
the rural and urban areas. The influence of age on IgG1 or IgG4 was
less clear. Because the cytophilic IgG2 and IgG3 have been correlated
with resistance to P. falciparum malaria (1, 2,
17), of particular interest is the correlation between age on
the one hand and IgG2 and IgG3 levels on the other. This is consistent
with a slow development of protective immune responses (2,
7).
No difference between ethnic groups was found, and in particular, IgG
subclass levels for the most represented group in the urban area (the
Mossi) were similar to those for the other groups. This result is
consistent with our previous report showing no interethnic difference
in parasitemia in the same area (21). Modiano et al.
(16) reported that the Mossi and Rimaïbe showed similar levels of antibody against RESA and Pf332, whereas the Fulani
living in the same area displayed higher levels of antibody against
both antigens and were also less parasitized. This suggested a genetic
control of the capacity to mount protective immune responses and
emphasized the need to analyze genetic control of IgG subclass responses against malarial antigens.
We obtained strong evidence for genetic regulation of the IgG subclass
responses against several malarial antigens. There was sib-sib
correlation for the IgG responses and the IgG subclass responses
directed against RESA, MSP-1-Nt, MSP-2-Nt, MSP-2-Ct1, MSP-2-Ct2, and
P. falciparum crude extracts. Moreover, parent-offspring correlations were also found for the IgG subclass responses. In particular, for the whole population, there were mother-offspring correlations for the IgG responses and the IgG subclass responses against MSP-2-Nt, MSP-2-Ct1, and MSP-2-Ct2 (Table 4). Father-offspring correlation coefficients were also significant for all the IgG subclass
responses against MSP-2-Ct2. Similarly, Stirnadel et al.
(27), in Papua New Guinea, observed significant
heritability for the IgG, IgG1, IgG2, and IgG3 responses against MSP-2.
Unfortunately, the IgG4 response was not analyzed in that study.
Interestingly, the variance of some IgG subclass responses was partly
explained by sharing of HLA class II genotypes. However, the
heritability was low, and segregation analyses indicated that genetic
control in IgG subclass responses was complex. These results are
consistent with previous analyses of genetic control in the IgG
responses to malarial antigens (12, 26). Those analyses
suggested that the genetic contribution of MHC genes is lower than that
of non-MHC genes. This pointed out the possible role of genes which
control B-cell function, such as those encoding interleukin 4 (IL-4), IL-13, or IL-5, and which are located on chromosome 5q31-q33. In
addition, chromosome 5q31-q33 is linked to blood infection levels
(22). Genes located on chromosome 5q31-q33 might influence immunological parameters involved in protection, including some IgG
subclass responses to malarial antigens.
Nevertheless, familial correlations may result partly from shared
environmental factors or shared households, although the malaria
transmission intensities were found to be homogeneous within each study
area. The measure of spouse-spouse resemblance was used to estimate the
influence of shared household on the phenotype. The IgG4 responses of
spouses were correlated, suggesting that shared household influences
the IgG4 responses. However, the absence of correlation among the IgG,
IgG1, IgG2, and IgG3 responses of spouses argues against a strong
influence of shared environmental effect. It should be stressed that
members of nuclear families tend to occupy the same residence. When
using methods for inferences concerning familial correlation, we cannot
estimate the relative contribution of shared household and genetic
components in explaining interfamily variations. Interestingly, sib
pair linkage analyses compare only children from the same nuclear
family and overcome such theoretical problems. Further linkage analyses are required to confirm the genetic control of IgG subclass responses and to localize genes involved.
In summary, we observed sibling correlations in families from two
differently exposed populations living in Burkina Faso. We found
substantial heritability for most of the IgG subclass responses
directed against RESA, MSP-1, and MSP-2 conserved B epitopes and crude
P. falciparum antigens. These results show that linkage and
association studies should be done to localize and identify genes
regulating IgG subclass responses. The identification of such genes may
help in determining the genetic control of susceptibility to malarial
infection and disease. Moreover, polymorphisms of these genes would
have to be considered in the development of vaccines.
 |
ACKNOWLEDGMENTS |
We thank all volunteer families of Bobo-Dioulasso and
Logoforousso for their participation. We thank the medical authority of
Burkina Faso "Ministère de la Santé," Ouagadougou, and
"Direction provinciale de la Santé," Bobo-Dioulasso, for
encouragement during this work. We thank Alain Bourgois for critical
reading of the manuscript and A. S. Traoré and F. Tall for
their encouragement.
This work was supported by research grants from the French Ministry of
Research and Technology, from the AUF LAF 303, and from the Fondation
pour la Recherche Médicale. C.A. was supported by a studentship
from the Fondation pour la Recherche Médicale.
 |
FOOTNOTES |
*
Corresponding author. Mailing address: Université
de la Méditerranée, Faculté de Pharmacie,
Immunogénétique et Pharmacologie du Paludisme (IGPP-EA
864), 27 Bd Jean Moulin, 13385 Marseille Cedex 5, France. Phone: (33) 4 91 80 36 74. Fax: (33) 4 91 80 36 74. E-mail:
rihet{at}luminy.univ-mrs.fr.
Editor:
W. A. Petri Jr.
 |
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Infection and Immunity, February 2001, p. 996-1001, Vol. 69, No. 2
0019-9567/01/$04.00+0 DOI: 10.1128/IAI.69.2.996-1001.2001
Copyright © 2001, American Society for Microbiology. All rights reserved.
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