Background
Rapid and accurate diagnosis of
Plasmodium infections is crucial for morbidity and mortality reduction in tropical areas, specially in regions where mixed infections are prevalent such as Papua New Guinea (PNG), where all four parasites infecting humans coexist and mixed species infections are common [
1,
2]. For improving accuracy in large epidemiological studies, molecular diagnostic tools permitting high through put analysis for the identification and quantification of malaria parasites would be of great benefit.
Traditionally, light microscopy (LM) examination of blood smears has been considered the gold standard for the diagnosis of malaria [
3]. LM has clear advantages over molecular typing, since it incurs only low costs, does neither need complex sample preparation nor advanced technology and permits species identification and quantification [
4]. However, the role of LM as a gold standard has been questioned due to false negative results at low parasitemia and frequent errors in species identification in mixed infections [
5,
6].
The availability of commercial rapid diagnostic tests (RDT) has greatly facilitated the in situ diagnosis of malaria infections in the field. The advantages of RDT are that they do not need special preparation of the sample and diagnostic results become immediately available [
7]. However, their use is limited due to lack of sensitivity for
Plasmodium vivax, Plasmodium malariae and
Plasmodium ovale[
8].
Nested PCR (nPCR), first described by Snounou and co-workers [
9], is a widely used method and is considered as a molecular gold standard due to its good performance in detection of mixed species infection. This assay amplifies the multicopy 18 S rRNA genes of the four
Plasmodium species infecting humans. Even though this genotyping technique is now performed in many field laboratories in endemic countries, its use for routine clinical diagnosis is limited, because the analysis is time consuming due to the need of multiple reactions per sample, and the risk of contamination through the requirement for nPCR [
9]. Moreover, the technique is not quantitative.
In recent years, various real time quantitative PCR (qPCR) assays have been developed for the detection of
Plasmodium species, with most assays targeting the 18 S rRNA genes. Two of these methods detect the genus
Plasmodium using generic primers, and thus do not distinguish between species [
10,
11]. Sybergreen reagent has been used by other groups, to identify the four
Plasmodium species infecting humans in a single reaction by melting curve analysis [
8,
12]. The use of TaqMan probes contributed an additional level of specificity to qPCR assays [
13]. However, using a single pair of primers for
Plasmodium genus detection in duplex assays, introduces competition for amplification among species, which likely leads to difficulties in detecting mixed infections [
14]. In order to address this issue, various groups had used different strategies [
15‐
18]. The multiplex PCR-ligase detection reaction-fluorescent microsphere assay (PCR_LDR_FMA) has also been used in molecular epidemiological studies for simultaneously detecting all four
Plasmodium species [
19].
Despite the variety of molecular tools available for the diagnosis of malaria and their wide use for the diagnosis of imported malaria in travel clinics, implementation of these techniques in endemic areas has remained limited until now. Even though the low sensitivity and limited detection of asymptomatic and mixed infections by LM constitutes a critical shortfall for some epidemiological studies, LM remains to date the most frequently used method for the diagnosis of malaria in endemic areas. The transfer of molecular techniques for diagnosis of malaria to laboratories in endemic settings is essential for overcoming the limitations by LM. Moreover, a molecular technique with quantification capacity contributes to correctly estimate the burden of Plasmodium species often found in concomitant infections and will be a valuable tool to explore competition in mixed infections.
A qPCR assay initially developed for malaria diagnosis in returning travellers at a reference laboratory was implemented and validated at the PNG Institute of Medical Research (IMR). This assay was chosen because it detects with high specificity all four Plasmodium species which jointly occur in our study area in PNG. The performance of this qPCR assay in conditions of a field laboratory and on field samples was compared to light microscopy, nPCR and PCR_LDR_FMA results.
Discussion
In preparation of major molecular epidemiological field studies in PNG essential parasite detection techniques were compared under conditions of a laboratory close to the field site and located in a malaria endemic country. The diagnostic requirements were: (i) good performance in the detection of mixed species infections, as all four species concurrently occur in PNG, (ii) recognition of P. malariae and P. ovale variants present in the study area, (iii) high through put capacity and robustness of assay, (iv) quantitative results and (v) reasonable costs. The qPCR assay described here was implemented and validated at the PNG-IMR site in Madang, demonstrating the feasibility of applying state of the art techniques in this context. In the meantime the qPCR assay is routinely implemented for molecular diagnosis in large scale epidemiologic studies at IMR.
As part of test validation in the field, the performance of this qPCR assay for Plasmodium species discrimination was compared to two other PCR-based assays (nPCR and LDR) and to LM. Traditionally, test outcomes for different assays are compared to an established 'gold-standard' in order to calculate sensitivity and specificity estimates and to evaluate the performance of newly developed tests. The classical 'gold standard' for malaria diagnosis has been LM [
3], however, with the appearance of new molecular diagnostic tools, LM has become less suitable for this purpose due to its lower sensitivity than molecular methods [
6]. Even though the nPCR developed by Snounou et al [
9] has been extensively used as 'gold-standard' for molecular diagnosis [
25,
26], the concept of using a 'gold-standard' for the evaluation of new assays is being questioned by various authors, which alternatively propose the use of 'non-gold standard' approaches [
27,
28].
The agreement between qPCR and the other techniques was substantial for P. falciparum, but only moderate for P. vivax, P. malariae and P. ovale. In particular, the agreement between qPCR and nPCR for P. falciparum detection was almost perfect. The lower agreement between PCR-LDR and nPCR, together with the higher prevalence shown by PCR-LDR (47.1% compared to 40.9% by qPCR and 43.8% by nPCR), may indicate false positive results by LDR. This is supported by our pairwise analysis and the agreement of two independent PCR based assays, namely nPCR and qPCR. However, in absence of a suitable diagnostic 'gold standard', it remains unclear if those 33 samples positive for LDR but negative by the two alternative molecular methods, represent a greater sensitivity of LDR or simply false positives. This issue cannot be easily resolved in a study involving 'unknown' samples from the field, potentially infected by four different Plasmodium species.
P. vivax prevalence was higher by nPCR than by both, qPCR and PCR-LDR (73.2% by nPCR, 65.7% by qPCR and 67.5% by PCR-LDR). This again could reflect false postitives by nPCR or lower sensitivity by both other molecular methods. Our observations in qPCR validation using plasmid template suggested that qPCR of
P. vivax is lightly compromised by performing a duplex
Pf/Pv reaction. nPCR involves a very high number of cycles (55 cycles by nPCR versus 45 cycles by qPCR and 35 cycles by LDR), and therefore is expected to show maximal sensitivity. Despite measurements taken over 45 cycles in qPCR, we followed the consensus rule for considering a sample positive, i.e. a Ct value < 40 [
23]. In our samples this led to the loss of 9 samples with Ct values for
P. vivax between 40 and 43.6 cycles, which otherwise would have increased the sensitivity of the assay. Further analysis was performed on samples with discrepant results for
P. vivax (
P. vivax negative samples by qPCR and positive by nPCR). Most of these samples were mixed infections by nPCR and harboured
P. falciparum with more than 10,000 copies/μl. Thus competition for amplification at the beginning of the PCR due to
P. falciparum high densities may be precluding
P. vivax detection [
14]. 14/16 of the remaining samples were also negative by LM. Most likely these very low-grade
P. vivax infections were missed. The scarcity of the template in case of a very low parasite density is expected to lead to imperfect detection. Prevalence for
P. malariae and
P. ovale were low with significant differences between assays, even though the agreement between pairwise compaired methods was moderate. Higher prevalence for
P. malariae detection by LDR is likely to occur as a result of false positive results, probably occurring due to high background noise of the
P. malariae probe used in the assay. Low detection of
P. ovale by nPCR (3.8%) is due to the use of a primer pair with sub-optimal amplification of
P. ovale sequences present in the study area. Finally, LM measured the lowest prevalence for all four
Plasmodium species.
The major advantage of qPCR over the other compared molecular techniques was the quantification of parasite densities. Parasite densities shown as copies of 18 S rRNA template/μL were quantified by converting the threshold cycle (Ct) into template copy number by using the standard curves. When correlating quantification by qPCR with LM counts in samples where both techniques showed positive results, a high correlation for P. falciparum (R2 = 0.8253) and a lower correlation for P. vivax (R2 = 0.5049) was found. But for P. vivax this correlation of parasite densities by qPCR and LM increased when only single infections were taken into account. Therefore, our results suggest a variation in the detection limit in both methods, due to overlooking P. vivax in case of an overwhelming P. falciparum infection. Difficulties in identifying P. vivax by LM arise when this parasite is found at low densities and in mixed infections. The high P. falciparum densities found in the samples identified as mixed infection by qPCR (> 10000 target copies/μl) further supports this explanation. The correlation for P. malariae and P. ovale could not be analysed due to poor detection of both species by LM.
The qPCR assay was found optimal for both tasks, detection of all four Plasmodium species and quantification. The latter could only be analyzed for P. falciparum and P. vivax. Overall qPCR shows substantial agreement with other molecular techniques for the detecting prevalence of P. falciparum and P. vivax, while moderate agreement was observed for P. malariae and P. ovale. It is clear, that sensitivity of our qPCR assay can be increased by simply performing independent reactions of each Plasmodium species. However, this would substantially increase costs. Limiting factors, such as duplex assays, need to be balanced against costs or work load. The specific research objectives of a particular study should guide the choice of experimental procedures.
Overall, the superior performance of PCR based methodologies over LM has been clearly demonstrated by these results and others. In a recent study conducted in Benin, a high number of children (between 27% and 44%) aged 5 or above, who initially had negative RDT tests (most also with negative blood slides), were later found to be infected with
P. falciparum using PCR [
29]. These undetected submicroscopic infections have an enormous impact for malaria transmission in endemic areas. In a time where malaria erradication has become the primary goal of malaria agendas, the accurate estimation of the burden of malaria infection is imperative to control transmission.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
DM and IF conceived and designed qPCR assay and AR coordinated the study. DM validated qPCR in the reference lab and AR in the endemic seating. IB and AR participated in the sample collection. JI did the DNA extractions from the blood samples. CB performed the PCR-LDR-FMA. AR performed qPCR and nPCR methods, statistical analysis and interpretation of the data. AR, IF and IM draft the manuscript. PZ and HP critically reviewed the manuscript. All authors have read and approved the final manuscript.