In Ethiopia, even though enormous efforts have been made at national and local levels to control and eventually eliminate malaria, limited molecular data exists on genetic polymorphism of P. falciparum, the most predominant and virulent malaria parasite in the region. The present study aimed to assess genetic polymorphism of P. falciparum clinical isolates from symptomatic patients based on block 2 region msp-1 genotypes and multiplicity of infection. This is the first study that widely investigated the status of P. falciparum genetic diversity from three districts of the study areas in central Ethiopia, and examined the spatial and seasonality of such polymorphism in relation to parasite density and other patient characteristics.
The study revealed that, geometric mean of parasite density abruptly rose up in school age children (SAC) and relatively stable afterwards (Fig. 2). In addition, no statistically significant correlation existed between parasite density and age of the patients (Pearson’s correlation = 0.12, P = 0.6). Even though a number of factors may contribute to the fluctuation of parasitaemia level overtime in symptomatic patients, the geometric mean of microscopically detectable parasitemia levels could be used to explain the finding of this study (Shekalaghe et al., 2005). The major factor that mainly contributed for higher parasitaemia level in SAC is delayed acquisition of protective immunity during this immunological transition age making this age group more vulnerable to malaria infection than adults (Makenga et al., 2020).
In the present study we found that, multiple infections gradually rose up with age group (Fig. 2B), although the variation was not statistically significant (X2 = 0.5). This finding is in congruent with the report from Burkina Faso (Soulama et al., 2009), and Tanzania (Pinkevych et al., 2014), where they explained that episode of infection in children is commonly for very short duration and the duration of episode of infection increases with age contributing to the multiple infections. Other reports suggested that multiple infections vary with parasite density, immunity status, the overall prevalence of infection in the population and transmission intensity as reviewed by (Eldh et al., 2020, Pacheco et al., 2016, Kiwuwa et al., 2013). Other studies have shown an inverse association. Therefore, the relationship between malaria patient age, level of parasitemia, number of clones of infection, transmission intensity and status of immunity to malaria parasite needs further investigation.
In the study we found that, no significant correlation existed between multiple clone infections of P. falciparum with seasonal variation of malaria incidence and travel history of patients (Table 3). In favor this finding, report from south western Ethiopia (Getachew et al., 2015), has shown that no correlation or negative correlation was found between the proportion of multi-clonal infections and parasite prevalence. On the other hand, report from Indonesia (Noviyanti et al., 2015), and Papua New Guinea (Fola et al., 2017), shows the presence of positive correlation between the rate of polyclonal infections and annual parasite incidence. The predominance of policlonality (92%) in those patients having no travel history depicts real features of malaria epidemiology with respect to the genetic marker of msp-1 gene.
In this study, we found that, 26% of the isolates having multiple genotype infection. The overall MOI of 1.3 and the expected heterozygosity of (0.39) (Table 2).This finding differ from the report from north western Ethiopia and south western Ethiopia where Mohammed et al and (Abamecha et al., 2020) reported 75% and 80% frequency of multi-clonal infections, and 1.8 MOI (1.8) with He (0.79), 2.0 MOI and 0.43 He, respectively. This shows that malaria transmission in our study area exhibits slightly lower genetic diversity, compared with north western and south western Ethiopia. This could be due to the ongoing intensified scale up of interventions, differences in local epidemiology, demographic and environmental conditions that might have resulted in observed reduced genetic diversity pattern in Adama and its surroundings. In the present study, from 171 collected sample from field sites 139 (81%) successfully amplified for msp-1 gene; revealing 19 different length polymorphism of msp-1allelic variants; 8 MAD20 (160 -330bp), 6 K-1 (100–270)bp, and 5 RO33 (100 -220bp). This shows the level of size polymorphism of msp-1 alleles in our study area. However, the number of alleles identified may have been under estimated due to a number of limitations like sensitivity of PCR technique used, inability to differentiate minor fragments, the possible existence of similar size fragments and the same size fragment having different amino acid motifs (Abamecha et al., 2020, (Peakall & Smouse, 2012)
Size polymorphism of msp-1 allelic variant identified in the present study is slightly higher than the report from Chewaka district of south western Ethiopia (Abamecha et al.) and Humera of north western Ethiopia (Mohammed et al., 2018). And less diverse than Kolla Shele district of south western part of Ethiopia (Mohammed et al., 2015), and more or less similar to the report from Equatorial Guinea (Chen et al., 2018), Bobo-Dioulasso of Burkina Faso (Somé et al., 2018). The major factor that may account for such variation could be; the scope of study sites covered and local malaria transmission patterns might have contributed. Gel analysis of the present study revealed that; from 139 msp-1 amplicon 103 (74%) were monoclonal infection, whereas the remaining 36 (26%) were poly-allelic type, with 15% for (MAD20 + K-1), 5.7% for (MAD20 + RO33), 2.8% for (K-1 + RO33), and 2.1% were MAD20 + K-1 + RO33 type. The proportion of monoclonal infection was 48% MAD20, 13% K-1 and 13% RO33 (Table 2). This finding differ from the report from south western Ethiopia (Mohammed et al., 2015) and (Abamecha et al.), where they reported that K-1 was the most prevalent allelic family. Similarly, report from Cameroon, Gambia, Nigeria and Gabon has shown that MAD20 allelic variant was least predominant (Metoh et al., 2020, Zakeri et al., 2005). On the other hand, in agreement with the report from north western part of Ethiopia (Mohammed et al.), Sudan by (Mahdi Abdel Hamid et al., 2016), and Equatorial Guinea (Chen et al., 2018) of the three msp-1 gene allelic families MAD20 was the predominant allelic type. Although the deriving forces for such variation needs further investigation; the difference in micro-ecological factors and the local transmission intensity (Yavo et al., 2016, Färnert et al., 2008), could play a significant role. Moreover, evolutionary process like genetic drift resulting uneven reproduction of the parasite lineages, types and rate of mutations, inbreeding, and the contribution of allelic variants in reproductive success are some of the factors that might have contributed for such variation (Escalante, 2020). In addition, in this study when the spatial feature of the distribution of msp-1 gene allelic variant in urban and rural areas (Table 4), were examined no statistically significant (P = 0.2) variation was revealed. This finding could be taken as an evidence to show similarity of malaria epidemiology and the possible crossbreeding of the parasite populations between urban and rural settings in the study area, demanding similar intervention endeavors. Similarly, no statistically significant variation of multi-clonal infection of msp-1 gene with parasite density (P = 0.6), and seasonality (major and minor malaria season) (P = 0.8). This could be due to the characteristic feature of low transmission settings in such malaria endemic regions (Adjah et al., 2018, Mohammed et al., 2017). On the other hand, study sites based distribution of allelic variant has shown a highly significant variation (P = 0.000), (Fig. 3). This could be due to the difference in local micro ecology of the areas, intensity of local transmission pattern, and differences in the age of the study population (Somé et al., 2018, Mwingira et al., 2011), and the relative potential differences and challenges on the ongoing malaria control and elimination endeavors in those sites.