Skip to main content
Download PDF

Significant differences in FcγRIIa, FcγRIIIa and FcγRIIIb genes polymorphism and anti-malarial IgG subclass pattern are associated with severe Plasmodium falciparum malaria in Saudi children

Malaria Journal volume 20, Article number: 376 (2021) Cite this article

Abstract

Background

The FcγRs genotypes have been reported to play a key role in the defence against malaria parasites through both cellular and humoral immunity. This study aimed to investigate the possible correlation between FcγR (IIa, IIIa, and IIIb) genes polymorphism and the clinical outcome for anti‐malarial antibody response of Plasmodium falciparum infection among Saudi children.

Methods

A total of 600 volunteers were enrolled in this study, including 200 malaria-free control (MFC) subjects, 218 patients with uncomplicated malaria (UM) and 182 patients with severe malaria (SM). The FcγR genotypes were analysed using PCR amplification methods, and measurements of immunoglobulin were determined using enzyme-linked immunosorbent assay (ELISA) technique.

Results

The data revealed that the FcγRIIa-R/R131 showed a statistically significant association with SM patients when compared to UM patients. Furthermore, higher levels of IgG1, IgG2, and IgG4 were associated with the FcγRIIa-H/H131 genotype among UM patients. Although the FcγRIIa-F/V176 genotype was not associated with UM, it showed a significant association with severe malaria. Interestingly, the FcγRIIIa-V/V176 genotype offered protection against SM. Moreover, SM patients carrying the FcγRIIIa-F/F genotype showed higher levels of AMA-1-specific IgG2 and IgG4 antibodies. The FcγRIIIb-NA1/NA1 and FcγRIIIb-NA2/NA2 genotypes did not show significant differences between the UM and the MFC groups. However, the genotype FcγRIIIb-NA2/NA2 was statistically significantly associated with SM patients.

Conclusions

The data presented in this study suggest that the influence of the FcγRIIa-R/R131, FcγRIIIa-F/F176 and FcγRIIIb-NA2/NA2 genotypes are statistically significantly associated with SM patients. However, the FcγRIIa-H/H13 and FcγRIIIa-V/V176 genotypes have demonstrated a protective effect against SM when compared to UM patients. The impact of the FcyR (IIa, IIIa and IIIb) gene variants and anti-malaria IgG subclasses play an important role in susceptibility to malaria infection and disease outcome in Saudi children.

Background

Malaria is a parasitic infectious disease caused by five species of Plasmodium that are transmitted to humans via mosquito bites. Of these species, Plasmodium falciparum, which is most prevalent in Africa, and Plasmodium vivax pose the greatest threat to health. In Saudi Arabia, P. falciparum represents about 99% of the total cases of malaria, while only 1% of patients are infected by P. vivax. In 2019, malaria affected about 229 million worldwide and contributed to 409,000 deaths. Children below the age of five were amongst the most vulnerable groups affected by the disease [1]. According to the WHO figures, between 2010–2015 in Saudi Arabia, the number of recorded malaria patients was steadily below 100, but it rose to 272 cases in 2016. This was mostly due to increased migration of people from war zones along the border with Yemen, as well as difficulties in providing adequate medical services in those regions. However, the health service in this country remains vigilant and offers free diagnosis and treatment for all patients.

Given the increase in the number of malaria infections and its apparent threat to people’s lives; there was a call for further studies that can assess individual’s susceptibility. This led to the current study in which the authors looked at genes (FcγR) within the innate immunity that are responsible for receptor expression on immune cells (including macrophages, neutrophils, NK cells). These cell receptors have the ability to recognize certain antibodies that will bind to antigens, such as antigens of P. falciparum.

There are three sub-families of surface receptors for the Fc region of the IgG, designated as FcγRI, II, and III [2]. Most immune cells express Fc receptors that are crucial for determining the specificity of IgG antibodies [3]. FcγR induces monocyte activation features such as phagocytosis, degranulation, superoxide generation, antibody-dependent cell inhibition, cytokine production, and antibody regulation, which are essential for host defence and immune regulation [4, 5]. The effectiveness of IgG‐induced FcγR activity demonstrates inter‐individual heterogeneity due to the genetic polymorphisms of the three subclasses of FcγR; FcγRIIa (CD32a), FcγRIIIa (CD16a), and FcγRIIIb (CD16b) [5].

Previous studies showed that several polymorphisms have been detected in the Fcγ genes encoding these receptors (FcγRs), associated with susceptibility or resistance to malaria outcome in different populations [3, 4, 6,7,8,9,10,11,12]. A recent review by Amiah et al. [13] described the FcγRs polymorphisms and the impact of these variations on the response of the host to infection. It also provided new perspectives for the potential design of an effective malaria vaccine [13].

The present study aimed to investigate the possible relationship between the expression of FcγRIIa (CD32a), FcγRIIIa (CD16a), and FcγRIIIb (CD16b) gene variants and the antibodies against the malarial apical membrane antigen 1 (AMA-1) in association with the susceptibility to malaria infection among Saudi children.

Methods

Study area

This study was conducted at Bani Malik General Hospital in Jazan Region (BMGHJ), located in the Southern part of the Kingdom of Saudi Arabia (KSA), during three transmission seasons from October 2015 to March 2018. The highlights of this study setting have already been described in related previous studies [3, 14,15,16].

Study design and patients

A prospective case–control study was conducted in children attending the outpatient clinic of BMGHJ, with a confirmed clinically diagnosed P. falciparum infection. Patients with positive thick blood film for P. falciparum asexual parasites were recruited based on the microscopic diagnosis.

Participants with no features of severe malaria were defined as having uncomplicated P. falciparum infection. Children were diagnosed with severe malaria on the basis of one or more of the following: severe malarial anaemia, cerebral malaria, hypoglycaemia, jaundice, acidosis, acute kidney injury (renal impairment), significant bleeding, pulmonary oedema, and shock as described in detailed by the World Health Organization (WHO) [17]. These clinical manifestations occurred in the absence of any identifiable alternative cause other than P. falciparum asexual parasitaemia. Children with cerebral malaria had a Blantyre Coma Score (BCS) < 3 at 4 h post-admission. Children with severe malarial anaemia had a blood haemoglobin concentration of ˂ 5 g/dL or a haematocrit value of < 15% together with a parasite count above 10,000/μL. All other children recruited in the study had a haemoglobin concentration above this level. The control group were selected from the Child and Woman Health Clinics (CWHC) that provide children health services including routine vaccinations, as well as providing seasonal vaccines for children. Once the sample was collected, it was matched for age, gender, and ethnicity. Enrolment to the control group was confirmed following a physical clinical examination to ensure that the children did not have serious illnesses or any signs/symptoms of malaria according to information provided by parents/guardians.

The study excluded children with multiple severe malaria complications or any co-infectious diseases. None of the participants were positive for HIV. All the children were recruited during three malaria transmission seasons from October 2015 to March 2018.

Sample collection

After the diagnosis of malaria and before the start of the pharmacological course of treatment; 100 µL of blood was spotted and dried on filter paper (Qualitative filter paper, Grade 1, circles, diam. 42.5 mm from Whatman®, Sigma-Aldrich®). This collected sample was used for investigating Fcγ receptor gene polymorphism, parasite detection using PCR, and measurement of immunoglobulins as described earlier [18, 19].

Serum elution from filter-paper samples

To elute dried samples from filter-paper, a hole puncher of ϕ 6 mm was used for punching out filter-paper discs and placed in Eppendorf tubes with 100 µL of phosphate-buffered saline (PBS). Subsequently, the discs were transferred onto 10 mL tubes. Then, 500 µL of (PBS) with 0.05% Tween and 0.5% bovine serum albumin (BSA) were added to the tubes and incubated under shaking for 2 h at room temperature. After incubation, the samples were vigorously shaken with a vortex for 30 s, and the supernatants containing the eluted sera were aliquoted in cryotubes (1.5 ml) and stored at − 20 °C till analysis. Each extracted sample contained an approximately 1:100 diluted serum [18].

DNA extraction

DNA was extracted from 50 µL dried drop of blood sample on the filter paper using the QIAamp DNA Mini Kit (Qiagen®, Hamburg, Germany). The extracted DNA was re-suspended in a 150 µL of Tris–borate-EDTA (TBE) buffer.

Parasite genotype

Detection of P. falciparum was based on targeting the AMA-1_3D7 gene using polymerase chain reaction (PCR) from 5 µL of the extracted DNA samples [20].

Enzyme-linked immunosorbent assays (ELISA)

IgG subclass antibodies were measured against the recombinant AMA-1 anti-malarial antigen. The total levels of IgG and its subclasses were measured using enzyme-linked immunosorbent assays (ELISA) as previously described in detail [11, 21], and as recently reported [22].

Genotyping of FcγRs polymorphisms

The FcγRIIa-131R/H (rs1801274, assay ID: C__9077561_20) and FcγRIIIa-176F/V (rs396991, assay ID: C__25815666_10) polymorphisms were genotyped using the high-throughput TaqMan® 5′ allelic discrimination assay-by-design method, as per the instructions of the manufacturer (Applied Biosystems, Foster City, CA, USA). The FcγRIIIb-NA1/NA2 genotyping for the rs448740 (N65S) and rs147574249 (N82D) was carried out in accordance with the formerly described Restriction Fragment Length Polymorphism (RFLP) method [12, 23].

Statistical analysis

Statistical analysis was done by SPSS statistical software version 23 for Windows (IBM© SPSS© statistics). In this study, the median and 25% and 75% quartile of antibody (total IgG and IgG subclasses) levels were analysed using nonparametric (Kruskal–Wallis) tests and the P values were determined. With respect to the risk of malaria infection in children, all values of P < 0.05, 95% confidence interval (CI) for odds ratio (OR) that did not cross 1.00 were considered statistically significant. In the analysis, FcγRIIa-R/H131 polymorphism was used as a reference, due to its utmost prevalence in humans [24]. Using the same software, a 2 × 2 chi-square test was used to compare the overall allele frequency. The Hardy–Weinberg equilibrium (HWE) for genotypic deviation was assessed using a chi-squared statistical test. The logistic regression analysis was performed to test for the association between the FcγRs genotypes related to higher levels of anti-malarial IgG subclass among severe malaria compared to uncomplicated malaria patients. Associations were quantified using OR with 95% CI that did not cross 1.00 with P value < 0.05, defined as statistically significant. As shown below; each IgG subclass was ranked in malaria-free control in two categories based on the levels of anti-malarial antibodies.

Results

Classification of the study participants

In this study, demographic data on malaria, parasite density, and disease complication variables were analysed for 600 children of matched gender and age. The 600 subjects were categorised into three different groups. Group I: The malaria-free control [MFC, n = 200 (33.3%) subjects]; included subjects without symptoms of the disease and showed negative results for blood film examination and PCR of the malaria parasites. Group II: Uncomplicated malaria [UM, n = 218 (36.3%) patients]. Group III: severe malaria [SM, n = 182 (30.3%) patients]. Group III included patients with severe malaria [n = 182 (30.3%)], (Table 1). The mean number of parasites in severe malaria patients was significantly higher compared to uncomplicated malaria, P < 0.001 (Table 1). The body temperature was significantly different between the study populations, P < 0.001 (Table 1).

Table 1 Description of study participants
Full size table

Comparison between the distribution of the FcγRIIa genotype and its allelic frequencies among the different study groups

The genotype frequencies for FcγRIIa did not deviate from the expectations of the HWE in each genotype group (Table 2). The frequencies for the individuals carrying the FcγRIIa-R/R131 genotypes in UM group were lower than the ones in MFC. However, the logistic regression analysis revealed that there was no statistically significant difference between UM and MFC amongst both genotypes R/R131 [18.0% in UM versus 15.1% in MFC; OR = 1.39, 95% CI (0.89 to 2.19) and P value = 0.15] (Table 3). In contrast, the genotypes FcγRIIa-H/H131 were statistically significantly higher in UM compared to MFC groups [36.7% in UM versus 30% MFC; OR = 0.92, 95% CI (0.62 to 1.36) and P value = 0.026] using the heterozygotes as the reference group (Table 3). The FcγRIIa-R/R131 genotype was statistically significant associated with SM compared to UM [34.6% in SM versus 15.1% in UM; OR = 2.132, 95% CI (1.287 to 3.533) and P value = 0.003]. In contrast, the FcγRIIa-H/H131 genotype was negatively associated with SM compared to UM [13.7% in SM versus 36.7% in UM; OR = 0.349, 95% CI (0.206 to 0.592) and P value < 0.001] (Table 3). The frequencies of the FcγRIIa-H/R131 genotype were almost the same among the three groups of MFC, UM, and SM (52.0%, 48.2%, and 51.6%, respectively) (Table 2).

Table 2 Distribution of FcγRIIa, FcγRIIIa and FcγRIIIb genotypes and alleles frequency in the different study groups
Full size table
Table 3 Association between individual FcγRIIa, FcγRIIIa and FcγRIIIb genotypes and severity of malaria
Full size table

Comparison between the distribution of FcγRIIIa genotype and its allelic frequencies among the different study groups

The genotype frequencies showed no statistically significant difference among the FcγRIIIa-F/F in UM compared to MFC (Table 2). The logistic regression analysis confirmed the absence of significant differences between UM and MFC among the individuals carrying the FcγRIIIa-F/F genotypes [39% in UM versus 45.5% in MFC; OR = 1.95, 95% CI (0.65 to 2.38) and P value = 0.79]. Similarly, FcγRIIIa-V/V genotype showed no statistically significant association with UM compared to MFC [12.8% in UM versus 14.5% in MFC; OR = 1.72, 95% CI (1.04 to 2.82) and P value = 0.13] using the heterozygotes as a reference group (Tables 2 and 3). On the other hand, FcγRIIIa-F/F genotype was statistically associated with SM compared to UM [72.5% in SM versus 39% in UM; OR = 11.51, 95% CI (6.71 to 19.77) and P value < 0.001] (Tables 2 and 3). In contrast, the FcγRIIIa-V/V genotype was statistically negatively associated with SM compared to UM [3.8% in SM versus 12.8% in UM; OR = 0.20, 95% CI (0.09 to 0.47) and P value < 0.001] (Tables 2 and 3). The frequency analyses also showed differences in the distributions of the heterozygote FcγRIIIa-F/V genotype among the three groups (40% in MFC, 48.2% in UM, and 23.6% in SM) (Table 2).

The genotype analyses showed similar frequencies between UM and MFC for carrying the FcγRIIIb-NA1/NA1 genotypes (Table 2). This was confirmed by logistic regression analysis that revealed the lack of statistically significant difference between these two groups in the FcγRIIIb-NA1/NA1 [15% in UM versus 17.0% in MFC; OR = 0.79, 95% CI (0.48–1.30) and P value = 0.354] (Tables 2 and 3). Furthermore, NA2/NA2 genotype was not statistically significantly different among UM patients compared to MFC [36.7% in UM versus 37.0% in MFC; OR = 1.24, 95% CI (0.85–1.79) and P value = 0.263] using the heterozygotes as a reference group (Tables 2 and 3). Similarly, there was no statistical difference between patients with SM and UM for FcγRIIIb-NA1/NA1 genotype [9.9% in SM versus 15.1% UM; OR = 0.82, 95% CI (0.43 to 1.57) and P value = 0.545] (Tables 2 and 3). However, patients carrying the FcγRIIIb-NA2/NA2 genotype were statistically significantly associated with SM compared to UM [51.6% in SM versus 36.7% in UM; OR = 1.76, 95% CI (1.15- 2.70) and P value = 0.009] (Table 2 and 3). The frequency analyses showed differences in the distributions of the heterozygote FcγRIIIa-NA1/NA2 genotype among the three groups (46% in MFC, 48.2% in UM, and 38.5% in SM) (Table 2).

Specific IgG subclass reactivity in the different study groups

The antibody response for the P. falciparum blood-stage antigen AMA-1 was analysed within the different study groups. The current results showed statistically significant differences among the anti-malarial IgG subclass antibody levels in the different study groups; the overall P value < 0.001 (Table 4). In general, the median value of IgG1 and IgG3 subclass were expressed at higher levels than IgG2 and IgG4 antibodies in the UM group when compared to SM subjects (Table 4). To investigate the potential association between the anti-malarial IgG subclass response and protection against infections; the authors first used a logistic regression model to compare the levels of IgG subclasses between the UM infection and MFC (Table 5). The results showed that a higher level of IgG1 against the AMA-1 antigen was associated with UM patients compared to MFC subjects [OR = 1.04; 95% CI (1.01 to 1.07) and P value = 0.012]. In addition, the levels of AMA-1-specific IgG3 were significantly higher in UM patients compared MFC [OR = 1.70; 95% CI (1.47 to 1.95) and P value < 0.001] (Table 5). There was no observed association for the AMA-1-specific IgG2 and IgG4 responses in UM compared to MFC (Table 5). The second logistic regression model confirmed that the apparent anti-malarial IgG2 and IgG4 antibodies were statistically significantly higher in SM patients when compared to UM patients (Table 5). However, the levels of AMA-1-specific IgG1 and IgG3 were significantly lower in SM group compared to UM patients [for IgG1: OR = 0.89; 95% CI (0.84 to 0.94) and P value < 0.001 and for IgG3: OR = 0.52; 95% CI (0.43 to 0.62) and P value < 0.001)] (Table 5).

Table 4 Comparison of Anti-AMA1 IgG subclasses (µg/mL) among different study groups
Full size table
Table 5 Logistic regression analysis of malaria specific (anti-AMA1) IgG subclasses levels among the different study groups
Full size table

The results indicated that patients carrying the FcγRIIa-H/H131 genotype are significantly associated with higher expression levels of the anti-malarial IgG1, IgG2 and IgG4 antibodies, but not IgG3 in UM patients [for IgG1: OR = 0.3; 95% CI (0.2 to 0.6) and P value < 0.001, for IgG2: OR = 0.5; 95% CI (0.3 to 0.8) and P value = 0.006 and for IgG4: OR = 0.5; 95% CI (0.3 to 0.8) and P value = 0.006] (Table 6). Comparatively, patients harbouring the FcγRIIa-R/R131 genotype show significantly increased levels of anti-malarial IgG2 antibodies and associated with SM compared to UM [OR = 3.7; 95% CI (2.0 to 6.7) and P value < 0.001] (Table 6). However, patients carrying the genotype FcγRIIa-R/R131 are statistically negatively associated with higher levels of AMA-1-specific IgG3 [OR = 0.4; 95% CI (0.2 to 0.6) and P value < 0.001] (Table 6). Independently, the model of the multivariate logistic regression analysis of individuals carrying the FcγRIIIa-F/F genotype is significantly associated with higher levels of AMA-1-specific IgG2 and IgG4 antibodies in SM compared to UM patients [for IgG2: OR = 3.9; 95% CI (2.4 to 6.4) and P value < 0.001 and for IgG4: OR = 3.2; 95% CI (2.1 to 5.3) and P value < 0.001] (Table 6). These results together clearly show that the FcγRIIIa-F/F genotype is negatively associated with higher expression levels of AMA-1-specific IgG3 among SM compared to UM patients [OR = 0.2; 95% CI (0.1 to 0.4) and P value < 0.001] (Table 6). Similarly, our data show that the FcγRIIIa -V/V genotype is negatively associated with higher levels of AMA-1-specific IgG4 in SM compared to UM subjects [OR = 0.4; 95% CI (0.2 to 0.6) and P value < 0.001] (Table 6).

Table 6 Logistic regression analysis of individual carrying FcγRIIa, FcγRIIIa, FcγRIIIb genotypes in relation of the levels specific IgG subclasses associated with uncomplicated compared to severe malaria
Full size table

Furthermore, the analyses of the results show that the FcγRIIIb-NA2/NA2 genotype is significantly associated with a higher level of AMA-1-specific IgG4 among SM compared to UM group [OR = 1.7; 95% CI (1.1 to 2.7) and P value = 0.011] (Table 6). The current results indicate that the FcγRIIIb genotypes are not associated with the independent action of the three IgG subclasses (IgG1, IgG2, and IgG3) of antibodies, and maybe due to the absence of interaction in the logistic regression model.

Discussion

This study aimed to evaluate the possible relationship between the variants of FcγRIIa (CD32a), FcγRIIIa (CD16a), FcγRIIIb (CD16b) gene polymorphism and P. falciparum AMA-1-specific IgG subclass and its importance in the susceptibility to complicated malaria infections among children in Saudi Arabia. This study is the country's first report investigating this association among children.

The data of this investigation suggested that there was no significant impact of the FcγRIIa-R/H131 genotypes polymorphism on the susceptibility to UM infection compared to MFC. This finding is in parallel with the previously published report from Eastern Sudan by Giha and co-workers, which suggested the lack of statistically significant association between FcγRIIa-R/H131 genotypes polymorphism on immunity and susceptibility to UM infection [25]. This may be due to the similarities in malaria epidemiology, malaria transmission, and patient’s semi-immunity to malaria infection [3, 16]. In contrast, the study of Shi et al. demonstrated a protective effect against UM for FcγRIIa-R/R131 compared with the heterozygote FcγRIIa-R/H131 genotype carriers in infants below one year of age [26]. Therefore, there is no general agreement regarding the role of FcγRIIa-R/H131 in UM infection. In the present study, the logistic regression model suggests that the genotypes FcγRIIa-R/R131 are statistically significantly associated with increased susceptibility to SM infection (2.1-fold) when compared to UM patients. In contrast, the current data indicates that the FcγRIIa-H/H131 is negatively associated with SM (0.349-fold decrease) compared to UM patients. Similarly, in a former study, the authors have reported that the FcγRIIa-R/R131 genotypes are associated with SM, while the FcγRIIa-H/H131 genotypes show a significant association with mild malaria among Sudanese patients residing in East Sudan [9]. Previously published case–control investigations have demonstrated that FcγRIIa-R/R131 genotypes are associated with protection against high parasite density [26], and the genotypes of FcγRIIa-H/H131 are correlated with high risk of either severe malaria or placental malaria [27,28,29]. Interestingly, the current study found that the levels of IgG1, IgG2, and IgG4 are associated with FcγRIIa-H/H131 in the UM patients. Nasr et al. have suggested similar results among the Fulani ethnic group that are less susceptible to severe malaria infection [11]. In contrast, previous data on pregnant women with asymptomatic malarial infection (ASM) revealed that the high levels of AMA-1-specific anti-malarial IgG1, IgG2, and IgG4 antibodies are statistically associated with R/R131 carriers rather than the genotype FcγRIIa-H/H131 [3]. This contradiction may be due to the variation in the individual’s genetic background, and variation in study designs.

The results of this study suggest that the relative reduction in malaria infection in the UM group cannot be explained solely by the magnitude and quality of the humoral response to malaria. Additional studies are needed to clarify whether the FcγRIIa-R/H131 polymorphism is a causative factor in the variable predisposition to malaria that is demonstrated among the different groups.

This study also revealed that the FcγRIIIa-F/V176 genotypes are not associated with UM patients compared to MFC. On the other hand, the FcγRIIIa-F/F176 genotype is statistically associated with SM compared to UM patients. However, patients carrying the FcγRIIIa-V/V176 genotypes are statistically associated with protection against SM compared to UM. The latter finding is in line with a recent Kenyan study, which shows that the polymorphisms in the FcγRIIIa-V/V are associated with protection against severe malaria and modulations in circulating IFNγ levels [12]. In contrast, a previous investigation on Thai patients did not show an association between FcγRIIIa-F/V176 genotypes and the severity of the disease [29]. Again, these discrepancies may be attributed to the difference in ethnicity and study design.

The current study suggests that individuals carrying the FcγRIIIa-F/F genotype are significantly expressing higher levels of AMA-1-specific IgG2 and IgG4 antibodies in the SM group compared to patients with UM. In agreement with this finding, Koene et al. have shown that the FcγRIIIa-F/F is significantly less bound to IgG1, IgG3, and IgG4 compared to the FcγRIIIa-V/V genotypes [30].

The study’s results suggest that there are no statistically significant differences between UM and MFC for the FcγRIIIb-NA1/NA1 and FcγRIIIb-NA2/NA2 genotypes. In contrast, the patients carrying the FcγRIIIb-NA2/NA2 genotype are significantly associated with SM compared to patients with UM. Recent work on children living in Western Kenya suggests that the FcγRIIIb-NA1/NA2 gene polymorphisms are not significantly associated with susceptibility to severe malaria [12]. In addition, the study performed by Adu et al. have demonstrates that the FcγRIIIb-NA2/NA2 in Ghanaian children is associated with clinical malaria [4]. In 2010, Adu demonstrated an association between the FcγRIIIb-NA2/NA2 and susceptibility to severe and uncomplicated malaria among Ghanaian children [31]. These contradicting results may be attributed to the different malaria transmission seasons and malaria epidemics. Moreover, different ethnicity associated with variations in the genetic background may significantly contribute to the FcγR gene polymorphism and susceptibility/protection to severe malaria [11].

Strength and limitations

To the best of the authors knowledge, this is the first study in the Kingdom of Saudi Arabia which highlighted the relation between FcγR genotypes polymorphism, IgG subclass and malaria infection among Saudi children. This will hopefully lead to further research in the area. Some of the studies limitations include the small sample size and the fact that the study was performed in one region of Saudi Arabia instead of it being multi-centred. As such findings need to be confirmed in a large sample size from various regions representing the whole endemic area.

Conclusion

This study reveals significant influence of the FcγRIIa-R/R131, FcγRIIIa-F/F176 and the FcγRIIIb-NA2/NA2 genotypes in increasing the susceptibility to severe malaria. Binding between the FcγR genotypes and IgG subclass results in changes in the ability of the immune cells to respond to infection through secretion of inflammatory mediators during P. falciparum infection. Further studies are underway in our laboratory to elucidate if the FcγRIIa, FcγRIIIa and FcγRIIIb genotypes polymorphism contribute to the differential susceptibility to malaria among the different study groups.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author upon request.

Abbreviations

AMA-1:

Apical membrane antigen 1

AMPSJ:

Aledabi Malaria Prevention Station in Jazan

ASRED:

Allele specific restriction enzyme digestion

BMGHJ:

Bani Malik General Hospital in Jazan

FcyR:

Fc-gamma receptors

PCR:

Polymerase chain reaction

References

  1. WHO: World malaria report 2019; 2019. https://appswhoint/iris/bitstream/handle/10665/330011/9789241565721-eng.pdf.

    Google Scholar 

  2. Ravetch JV, Bolland S. IgG Fc receptors. Annu Rev Immunol. 2001;19:275–90.

    Article  CAS  Google Scholar 

  3. Nasr A, Hamid O, Al-Ghamdi A, Allam G. Anti-malarial IgG subclasses pattern and FcgammaRIIa (CD32) polymorphism among pregnancy-associated malaria in semi-immune Saudi women. Malar J. 2013;12:110.

    Article  CAS  PubMed  Google Scholar 

  4. Adu B, Dodoo D, Adukpo S, Hedley PL, Arthur FK, Gerds TA, et al. Fc gamma receptor IIIB (FcgammaRIIIB) polymorphisms are associated with clinical malaria in Ghanaian children. PLoS one. 2012;7:e46197.

    Article  CAS  PubMed  Google Scholar 

  5. van Sorge NM, van der Pol WL, van de Winkel JG. FcgammaR polymorphisms: implications for function, disease susceptibility and immunotherapy. Tissue Antigens. 2003;61:189–202.

    Article  Google Scholar 

  6. Ogoe BM, Wilson MD, Yaa OD, Rogers W, Brown CA, Adu D. Studies on the allotypic variants of IgG receptors Fc gamma RIIA and Fc gamma IIIb and their association with severe clinical malaria among Ghanaian children. The Third MIM Pan-African Malaria Conference 2002, Abstract No: 166:116.

  7. Omi K, Ohashi J, Patarapotikulb J, Hananantachai H, Naka I, Looareesuwan S, et al. Fcgamma receptor IIA and IIIB polymorphisms are associated with susceptibility to cerebral malaria. Parasitol Int. 2002;51:361–6.

    Article  CAS  Google Scholar 

  8. Ntoumi F, Flori L, Mayengue PI, Matondo Maya DW, Issifou S, Deloron P, et al. Influence of carriage of hemoglobin AS and the Fc gamma receptor IIa-R131 allele on levels of immunoglobulin G2 antibodies to Plasmodium falciparum merozoite antigens in Gabonese children. J Infect Dis. 2005;192:1975–80.

    Article  CAS  Google Scholar 

  9. Nasr A, Iriemenam NC, Troye-Blomberg M, Giha HA, Balogun HA, Osman OF, et al. Fc gamma receptor IIa (CD32) polymorphism and antibody responses to asexual blood-stage antigens of Plasmodium falciparum malaria in Sudanese patients. Scand J Immunol. 2007;66:87–96.

    Article  CAS  Google Scholar 

  10. Nasr A, Elghazali G, Giha H, Troye-Blomberg M, Berzins K. Interethnic differences in carriage of haemoglobin AS and Fcgamma receptor IIa (CD32) genotypes in children living in eastern Sudan. Acta Trop. 2008;105:191–5.

    Article  CAS  Google Scholar 

  11. Nasr A, Iriemenam NC, Giha HA, Balogun HA, Anders RF, Troye-Blomberg M, et al. FcgammaRIIa (CD32) polymorphism and anti-malarial IgG subclass pattern among Fulani and sympatric ethnic groups living in eastern Sudan. Malar J. 2009;8:43.

    Article  PubMed  Google Scholar 

  12. Munde EO, Okeyo WA, Raballah E, Anyona SB, Were T, Ong’echa JM, et al. Association between Fcgamma receptor IIA, IIIA and IIIB genetic polymorphisms and susceptibility to severe malaria anemia in children in western Kenya. BMC Infect Dis. 2017;17:289.

    Article  PubMed  Google Scholar 

  13. Amiah MA, Ouattara A, Okou DT, N’Guetta SPA, Yavo W. Polymorphisms in Fc gamma receptors and susceptibility to malaria in an endemic population. Front Immunol. 2020;11:561142.

    Article  CAS  PubMed  Google Scholar 

  14. Al-Tawfiq JA. Epidemiology of travel-related malaria in a non-malarious area in Saudi Arabia. Saudi Med J. 2006;27:86–9.

    Google Scholar 

  15. Malik GM, Seidi O, El-Taher A, Mohammed AS. Clinical aspects of malaria in the Asir Region, Saudi Arabia. Ann Saudi Med. 1998;18:15–7.

    Article  CAS  Google Scholar 

  16. Nasr A, Allam G, Hamid O, Al-Ghamdi A. IFN-gamma and TNF associated with severe falciparum malaria infection in Saudi pregnant women. Malar J. 2014;13:314.

    Article  PubMed  Google Scholar 

  17. WHO. World malaria report 2019. Geneva: World Health Organization; 2019.

    Google Scholar 

  18. Nasr A, Abushouk A, Hamza A, Siddig E, Fahal AH. Th-1, Th-2 cytokines profile among Madurella mycetomatis eumycetoma patients. PLoS Negl Trop Dis. 2016;10:e0004862.

    Article  PubMed  Google Scholar 

  19. Snijdewind IJ, van Kampen JJ, Fraaij PL, van der Ende ME, Osterhaus AD, Gruters RA. Current and future applications of dried blood spots in viral disease management. Antiviral Res. 2012;93:309–21.

    Article  CAS  Google Scholar 

  20. Coley AM, Gupta A, Murphy VJ, Bai T, Kim H, Anders RF, et al. Structure of the malaria antigen AMA1 in complex with a growth-inhibitory antibody. PLoS Pathog. 2007;3:e138.

    Article  PubMed  Google Scholar 

  21. Iriemenam NC, Khirelsied AH, Nasr A, ElGhazali G, Giha HA, Elhassan AETM, et al. Antibody responses to a panel of Plasmodium falciparum malaria blood-stage antigens in relation to clinical disease outcome in Sudan. Vaccine. 2009;27:62–71.

    Article  CAS  Google Scholar 

  22. Nasr A, Saleh AM, Eltoum M, Abushouk A, Hamza A, Aljada A, et al. Antibody responses to P. falciparum Apical Membrane Antigen 1 (AMA-1) in relation to haemoglobin S (HbS), HbC, G6PD and ABO blood groups among Fulani and Masaleit living in Western Sudan. Acta Trop. 2018;182:115–23.

    Article  CAS  Google Scholar 

  23. Bux J, Stein EL, Santoso S, Mueller-Eckhardt C. NA gene frequencies in the German population, determined by polymerase chain reaction with sequence-specific primers. Transfusion. 1995;35:54–7.

    Article  CAS  Google Scholar 

  24. Rascu A, Repp R, Westerdaal NA, Kalden JR, van de Winkel JG. Clinical relevance of Fc gamma receptor polymorphisms. Ann N Y Acad Sci. 1997;815:282–95.

    Article  CAS  Google Scholar 

  25. Giha HA, Nasr A, Iriemenam NC, Troye-Blomberg M, Berzins K, ElGhazali G. Lack of significant influence for FcgammaRIIa-RH131 or hemoglobin AA/AS polymorphisms on immunity and susceptibility to uncomplicated malaria and existence of marked linkage between the two polymorphisms in Daraweesh. Microbes Infect. 2012;14:537–44.

    Article  CAS  Google Scholar 

  26. Shi YP, Nahlen BL, Kariuki S, Urdahl KB, McElroy PD, Roberts JM, et al. Fcgamma receptor IIa (CD32) polymorphism is associated with protection of infants against high-density Plasmodium falciparum infection. VII. Asembo Bay Cohort Project. J Infect Dis. 2001;184:107–11.

    Article  CAS  Google Scholar 

  27. Brouwer KC, Lal AA, Mirel LB, Otieno J, Ayisi J, Van Eijk AM, et al. Polymorphism of Fc receptor IIa for immunoglobulin G is associated with placental malaria in HIV-1-positive women in western Kenya. J Infect Dis. 2004;190:1192–8.

    Article  CAS  Google Scholar 

  28. Cooke GS, Aucan C, Walley AJ, Segal S, Greenwood BM, Kwiatkowski DP, et al. Association of Fcgamma receptor IIa (CD32) polymorphism with severe malaria in West Africa. Am J Trop Med Hyg. 2003;69:565–8.

    Article  CAS  Google Scholar 

  29. Omi K, Ohashi J, Patarapotikul J, Hananantachai H, Naka I, Looareesuwan S, et al. Fc gamma receptor IIA and IIIB polymorphisms are associated with susceptibility to cerebral malaria. Parasitol Int. 2002;51:361–6.

    Article  CAS  Google Scholar 

  30. Koene HR, Kleijer M, Algra J, Roos D, von dem Borne AE, de Haas M. Fc gammaRIIIa-158V/F polymorphism influences the binding of IgG by natural killer cell Fc gammaRIIIa, independently of the Fc gammaRIIIa-48L/R/H phenotype. Blood. 1997;90:1109–14.

    Article  CAS  Google Scholar 

  31. Adu B. Immunological and Genetic Correlates of Immunity to Plasmodium falciparum Malaria. A (MPhil) Thesis Submitted to the Department of Biochemistry and Biotechnology, Kwame Nkrumah University of Science and Technology, Kumasi; 2010, http://ir.knust.edu.gh/handle/123456789/481

Download references

Acknowledgements

The authors are grateful to the patients, control volunteers and their families. We are also grateful to the staff of the Bani Malik General Hospital and Aledabi Malaria Prevention Station in Jazan region (BMGHJ & AMPSJ) of Saudi Arabia, for their sustained cooperation and help in sample collection. The authors are grateful to Dr. Hamza A., Dundee University, United Kingdom, for improving the English language and proofreading the manuscript. This research study is financially supported by the grant number (RC13/246) obtained from King Abdullah International Medical Research Centre (KAIMRC), National Guard Health Affairs, Riyadh, Saudi Arabia.

Funding

This study was financially supported by King Abdullah International Medical Research Centre (KAIMRC), Health Affairs, Ministry of National Guard, Riyadh, Saudi Arabia, (Grant Number: RC13/246).

Author information

Authors and Affiliations

  1. Department of Basic Medical Sciences, College of Medicine, King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS), Riyadh, Kingdom of Saudi Arabia

    Amre Nasr & Ahmad Al-Bawab

  2. Department of Immunology, King Abdullah International Medical Research Centre (KAIMRC), Ministry of National Guard- Health Affairs, Riyadh, Kingdom of Saudi Arabia

    Amre Nasr & Emad Masuadi

  3. Department of Biochemistry and Molecular Medicine, College of Medicine, Alfaisal University, Riyadh, Saudi Arabia

    Ahmad Aljada

  4. Department of Public Health, Jazan Health Affairs- District Ministry of Health, Jazan, Saudi Arabia

    Osama Hamid

  5. Department of Pharmacology, College of Medicine, Taif University, POBox 888, Taif, 21944, Saudi Arabia

    Hatim A. Elsheikh

  6. Department of Medical Education, College of Medicine-Riyadh, King Saud Bin Abdul-Aziz University for Health Sciences, (KSAU-HS), Riyadh, Kingdom of Saudi Arabia

    Emad Masuadi

  7. Infectious Disease Division, Department of Medicine, King Abdulaziz Medical City, National Guard Health Affairs, RiyadhRiyadh, Saudi Arabia

    Themer H. Alenazi

  8. Department of Medicine, College of Medicine, King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS), Riyadh, Kingdom of Saudi Arabia

    Themer H. Alenazi

  9. Department of Basic Medical Sciences, College of Medicine, King Saud Bin Abdul-Aziz University for Health Sciences, Jeddah, Kingdom of Saudi Arabia

    Amir Abushouk

  10. King Abdullah International Medical Research Centre (KAIMRC), National Guard Health Affairs, Jeddah, Kingdom of Saudi Arabia

    Amir Abushouk & Ayman M. Salah

  11. Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Saud Bin Abdulaziz University for Health Sciences (KSAU-HS), Jeddah, Kingdom of Saudi Arabia

    Ayman M. Salah

Authors
  1. Amre Nasr
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ahmad Aljada
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Osama Hamid
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hatim A. Elsheikh
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Emad Masuadi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ahmad Al-Bawab
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Themer H. Alenazi
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Amir Abushouk
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Ayman M. Salah
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

AN, AA and SAM drafted the idea of the research proposal, researched data, and designed the experiments. AN, AA, HO, HAE, ME, AA, ATH, AA, AA and SAM wrote the first draft of the manuscript. AN, AA, HAE, SAM, and AA performed the ELISA and participated in the gene polymorphism analysis. AN and ME conducted the data analysis and contributed to the writing of the statistical components in the study. AN, OH and ATH contributed to patient recruitment, diagnosis management and reviewed the research project protocol. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Amre Nasr.

Ethics declarations

Ethics approval and consent to participate

This study was approved by the Institutional Reviewed Board (IRB) of King Abdulaziz Medical City, Health Affairs, Ministry of National Guard, Riyadh, Saudi Arabia. Prior to participation, informed consent was obtained from children and their parents/guardians.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nasr, A., Aljada, A., Hamid, O. et al. Significant differences in FcγRIIa, FcγRIIIa and FcγRIIIb genes polymorphism and anti-malarial IgG subclass pattern are associated with severe Plasmodium falciparum malaria in Saudi children. Malar J 20, 376 (2021). https://0-doi-org.brum.beds.ac.uk/10.1186/s12936-021-03901-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://0-doi-org.brum.beds.ac.uk/10.1186/s12936-021-03901-0

Keywords

Malaria Journal

ISSN: 1475-2875

Contact us