Genetic diversity and population structure of Plasmodium falciparum in the Philippines.

Abstract

In the Philippines, malaria morbidity and mortality have decreased since the 1990s by effective malaria control. Several epidemiological surveys have been performed in the country, but the characteristics of the Plasmodium falciparum populations are not yet fully understood. In this study, the genetic structure of P. falciparum populations in the Philippines was examined.
Population genetic analyses based on polymorphisms of 10 microsatellite loci of the parasite were conducted on 92 isolates from three provinces (Kalinga, Palawan, and Davao del Norte) with different malaria endemicity.
The levels of genetic diversity and the effective population sizes of P. falciparum in the Philippines were similar to those reported in the mainland of Southeast Asia or South America. In the low malaria transmission area (Kalinga), there was a low level of genetic diversity and a strong linkage disequilibrium (LD) when the single-clone haplotype (SCH) was used in the multilocus LD analysis, while in the high malaria transmission areas (Palawan and Davao del Norte), there was a high level of genetic diversity and a weak LD when SCH was used in the multilocus LD analysis. On the other hand, when the unique haplotypes were used in the multilocus LD analysis, no significant LD was observed in the Kalinga and the Palawan populations. The Kalinga and the Palawan populations were, therefore, estimated to have an epidemic population structure. The three populations were moderately differentiated from each other.
In each area, the level of genetic diversity correlates with the local malaria endemicity. These findings confirm that population genetic analyses using microsatellite loci are a useful tool for evaluating malaria endemicity.

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BioMed Central
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Malaria Journal
Open Access
Research
Genetic diversity and population structure of Plasmodium falciparum
in the Philippines
Moritoshi Iwagami1, Pilarita T Rivera2, Elena A Villacorte2, Aleyla D Escueta2,
Toshimitsu Hatabu3, Shin-ichiro Kawazu4, Toshiyuki Hayakawa5,
Kazuyuki Tanabe5 and Shigeyuki Kano*1
Address: 1Department of Appropriate Technology Development and Transfer, Research Institute, International Medical Center of Japan, 1-21-1
Toyama, Shinjuku, Tokyo 162-8665, Japan, 2Department of Parasitology, College of Public Health, University of the Philippines Manila, 625
Pedro Gil street Ermita, Manila, the Philippines, 3Gunma University School of Health Sciences, 3-39-15 Showa-machi, Maebashi 371-8514, Japan,
4National Research Center for Protozoan Diseases, Obihiro University of Agriculture and Veterinary Medicine, Inada 2-13, Obihiro, Hokkaido
080-8555, Japan and 5Laboratory of Malariology, Research Institute for Microbial Diseases, Osaka University, Suita, Osaka 565-0871, Japan
Email: Moritoshi Iwagami - miwagami@ri.imcj.go.jp; Pilarita T Rivera - ptongolrivera@yahoo.com;
Elena A Villacorte - eavillacorte@yahoo.com; Aleyla D Escueta - aleyla_dc@yahoo.com; Toshimitsu Hatabu - hatabu@health.gunma-u.ac.jp;
Shin-ichiro Kawazu - skawazu@obihiro.ac.jp; Toshiyuki Hayakawa - hayakawa@biken.osaka-u.ac.jp; Kazuyuki Tanabe - kztanabe@biken.osaka-
u.ac.jp; Shigeyuki Kano* - kano@ri.imcj.go.jp
* Corresponding author
Abstract
Background: In the Philippines, malaria morbidity and mortality have decreased since the 1990s
by effective malaria control. Several epidemiological surveys have been performed in the country,
but the characteristics of the Plasmodium falciparum populations are not yet fully understood. In this
study, the genetic structure of P. falciparum populations in the Philippines was examined.
Methods: Population genetic analyses based on polymorphisms of 10 microsatellite loci of the
parasite were conducted on 92 isolates from three provinces (Kalinga, Palawan, and Davao del
Norte) with different malaria endemicity.
Results: The levels of genetic diversity and the effective population sizes of P. falciparum in the
Philippines were similar to those reported in the mainland of Southeast Asia or South America. In
the low malaria transmission area (Kalinga), there was a low level of genetic diversity and a strong
linkage disequilibrium (LD) when the single-clone haplotype (SCH) was used in the multilocus LD
analysis, while in the high malaria transmission areas (Palawan and Davao del Norte), there was a
high level of genetic diversity and a weak LD when SCH was used in the multilocus LD analysis. On
the other hand, when the unique haplotypes were used in the multilocus LD analysis, no significant
LD was observed in the Kalinga and the Palawan populations. The Kalinga and the Palawan
populations were, therefore, estimated to have an epidemic population structure. The three
populations were moderately differentiated from each other.
Conclusion: In each area, the level of genetic diversity correlates with the local malaria
endemicity. These findings confirm that population genetic analyses using microsatellite loci are a
useful tool for evaluating malaria endemicity.
Published: 8 May 2009
Malaria Journal 2009, 8:96doi:10.1186/1475-2875-8-96
Received: 16 January 2009
Accepted: 8 May 2009
This article is available from: http://www.malariajournal.com/content/8/1/96
© 2009 Iwagami et al; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Background
Malaria is still one of the major public health problems in
the Philippines, although the morbidity and the mortality
have decreased in the last decade [1,2]. The Philippine
archipelago comprises 7,109 islands in the western Pacific
Ocean. Out of the 79 provinces, malaria is endemic to 65
provinces [3]. Epidemiological data suggest that malaria
endemicity across the Philippines is quite different from
one area to another. Therefore, it is likely that the parasite
populations in each endemic area differ genetically.
Understanding the genetic structure of malaria parasites is
essential to predict how fast phenotypes of interest, such
as novel antigenic variants or drug resistance, originate
and spread in populations [4,5]. Anderson et al reported a
spectrum of population structures in Plasmodium falci-
parum: in high transmission areas, such as sub-Saharan
Africa, weak linkage disequilibrium, high genetic diversity
and low levels of genetic differentiation between popula-
tions were observed, while in low transmission areas, such
as the Brazilian Amazon, significant linkage disequilib-
rium, low genetic diversity and high levels of genetic dif-
ferentiation between populations were observed [6].
Population genetic analyses of P. falciparum in Southeast
Asia have been reported from Thailand and Malaysian
Borneo [6,7]. In the Philippines, several epidemiological
surveys and some molecular biological studies on drug
resistant malaria and antigenic molecules have been
reported [1,2,8-11]. However, basic genetic analyses of
the parasite populations in the country using multilocus
neutral markers have not been reported so far.
The objective of the present study was to estimate the
genetic structure of P. falciparum populations in the Phil-
ippines using 10 highly polymorphic microsatellite loci
and to discuss the correlation between the levels of genetic
diversity and the level of malaria endemicity in this coun-
try. To investigate P. falciparum populations in the Philip-
pines, the population genetic analyses were conducted
using a method consistent with those used to assess the
genetic structure of the parasite populations in other
countries, so as to enable a comparison of the present data
with others [6,7,12]. The authors also considered the
implications for the emergence of anti-malarial drug
resistance, based on the data of this study and data of the
other populations that were previously reported from
other countries [6,7,12].
Methods
Collection sites and epidemiological data
The study areas, sample sizes (n), and years of the patient
blood collection were as follows: Kalinga province
(Northern part of Luzon Island), n = 22, collected by field
surveys in 2003 through 2005, Palawan province (Pala-
wan Island), n = 40, collected by field surveys in 2003
through 2006, and at Davao Regional Hospital in Tagum
City, Davao del Norte (Southeastern part of Mindanao
Island), n = 30, collected in 1999 through 2001 (Figure 1).
These three study areas are sentinel provinces in the Phil-
ippines, where malaria is endemic perennially, but do not
represent all the P. falciparum endemic foci of the country.
The field isolates were collected in Tabuk, Kalinga prov-
ince, where slide positivity rate (SPR) and annual parasite
incidence (API; per 1,000 people/year) were 4.3 and 3.6
respectively (2004). Other isolates were collected in
Puerto Princesa City, Palawan province where SPR and
API were 18.5 and 16.3 respectively (2004). The other iso-
lates were collected in Davao del Norte province, which
had a 4.5–15.2, SPR and 2.3–7.8, API (1999–2001). APIs
were collected from Annual Reports of the Provincial
Health Offices of Kalinga, Palawan and Davao del Norte.
Based on this epidemiological information, Kalinga can
be classified as hypoendemic, Palawan as mesoendemic,
and Davao del Norte as hypoendemic to mesoendemic.
Information pertaining to entomological inoculation
rates was not available to this study.
Informed consent was obtained from all the patients prior
to the blood collection. This study was given ethical
approval by the University of the Philippines, Manila, and
performed according to the ethical guidelines for epide-
miological studies provided by the Ministry of Education,
Culture, Sports, Science and Technology and the Ministry
of Health, Labour and Welfare of Japan.
DNA extraction, PCR amplification
The patient blood samples were frozen in liquid nitrogen
or preserved on filter papers (IsoCode Stix, Schleicher &
Schuell co., Germany) and kept at room temperature until
examined. The parasite DNA was extracted from frozen
whole blood samples by phenol-chloroform extraction
after proteinase K digestion or from the blood-spot sam-
ples on the filter papers, as per manufacturer's instructions
[13].
Genotyping
Ten microsatellite DNA loci were amplified by semi-
nested PCR. The loci were as follows: TA1 (chromosome
6), TA40 (chromosome 10), Poly α (chromosome 4),
Pfg377 (chromosome 12), PfPK2 (chromosome 12),
TA109 (chromosome 6), TA87 (chromosome 6), TA81
(chromosome 5), TA42 (chromosome 5) and 2490 (chro-
mosome 10). The PCR primer sets and amplification con-
ditions were consistent with the protocol of Anderson et
al using a modified TA40 primer set [14,15]. Sizes of fluo-
rescence-labelled PCR products were measured on an
Applied Biosystems Prism Genetic Analyzer 310 using
Gene Scan version 3.1.2 with a 500 ROX size standard
(ABI, CA, USA).

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Different-sized PCR products amplified using the same
primer set were considered to be individual alleles within
a locus, as size variation among isolates is consistent with
the repeat number in a microsatellite locus [14]. The elec-
tropherogram shows peak profiles for the microsatellite
loci, based on fluorescence intensity of the labelled PCR
products in this analysis. Multiple alleles per locus were
scored if minor peaks were taller than at least one-third
the height of the predominant allele for each locus. Mul-
tiple-genotype infections (MGIs) were defined as those in
which at least one of the 10 loci contained more than one
allele [6].
Data analysis
Expected heterozygosity (H) was calculated for each locus
based on the allele frequencies of the 10 examined micro-
satellite loci. H values were calculated using H = [n/(n -
1)] [1 - ∑pi2], where n corresponds to the number of iso-
lates examined and pi is the frequency of the ith allele.
Effective population size (Ne) was estimated based on H
and the microsatellite mutation rate (μ = 1.59 × 10-4; 95%
confidence interval: 6.98 × 10-5, 3.7 × 10-4) for P. falci-
parum [16-18]. The infinite-alleles model (IAM) and step-
wise mutation model (SMM) were used to estimate Ne.
For the IAM, the formula Neμ = H/4(1 - H) was used,
whereas for the SMM, the formula Neμ = 1/8{[1/(1 - H)]2
- 1} was used [17,18].
Each population was examined for evidence of a recent
genetic bottleneck (ie, a severe decrease in population
size). Heterozygosity excess was used for evidence of
genetic bottlenecks [19,20]. In a population that under-
went a bottleneck, heterozygosity excess is observed, in
which the value of He (the observed Hardy-Weinberg
equilibrium heterozygosity) is greater than that of H
(expected heterozygosity based on the number of alleles
and the sample size). The mode shift in allele frequency
distribution for the presence of rare alleles was also exam-
ined. A normal L-shaped distribution indicates evidence
of a non-bottlenecked population, whereas a shifted
mode of distribution indicates evidence of a bottlenecked
population. The BOTTLENECK program, version 1.2.02,
was used to search for evidence of heterozygosity excess
and mode-shift [19,21]. The Sign Test and the Wilcoxon
Signed-Rank Test were used to evaluate statistical signifi-
cance.
Multilocus linkage disequilibrium was assessed using the
standardized index of association (IAS) [22,23]. This anal-
ysis was performed using the LIAN 3.5 Web interface [24].
IAS was calculated using the formula IAS = (VD/Ve - 1)/(l - 1)
with permutation testing of the null hypothesis of com-
plete linkage equilibrium (IAS = 0), where VD is the
observed mismatch variance, Ve is the expected mismatch
variance, and l is the number of examined loci. Significan-
ces of the observed IAS values were calculated by Monte-
Carlo simulation, using 10,000 random permutations of
the data. This statistic is a variation of the method pro-
posed by Maynard-Smith et al [22]. The results were stand-
ardized by the number of loci, to enable a comparison of
different data sets [6,22]. This test was applied to the data
sets from each population in two ways. First, the mixed-
clone infections were excluded so that only the single-
clone infections were analysed, giving absolute confi-
dence in the haplotype profile. Second, any multilocus
genotype found in more than one isolate was only
counted once in the analysis, ie unique haplotypes only,
reducing the sample size slightly and thereby removing
the possible effect of recent epidemic expansion of partic-
ular clones [6]. Since the LIAN cannot analyse isolates
possessing missing data, the 57 isolates obtaining the
allelic data of 10 loci were used.
The extent of population subdivision between the popu-
lations in the Philippines was estimated using Weir and
Cockerham's Ø estimator for determining F statistics (FST)
[25]. FST were calculated using the FSTAT program version
2.9.3.2 and tested for significant difference from 0, based
on 1,000 random permutations of the data set [26].
Results
Allele frequencies of each locus in the three populations
are shown in Additional File 1. Of the total of 92 isolates
examined, allelic data of the microsatellite loci were
obtained from the 74 isolates (80.4%)(16 from Kalinga,
Study areas in the Philippines
Figure 1
Study areas in the Philippines. Levels of genetic differen-
tiation (FST values) for each pairwise population comparison
are shown with numbers and arrows. All values are signifi-
cantly different from 0 (* P < 0.001).
0.101*
0.144*
0.096*
Kalinga
?
?
?
Palawan
Davao del
Norte
Luzon Island
Palawan Island
Mindanao Island
400 Km

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28 from Palawan and 30 from Davao del Norte), while in
the remaining 18 isolates (19.6%), the allelic data were
not available (6 from Kalinga and 12 from Palawan)
because of failures in acquiring PCR products during the
genotyping. Multiple-genotype infection (MGI) was
observed in some loci in three isolates from the Palawan
population, and two isolates from the Davao del Norte
population. No MGI was observed from the Kalinga pop-
ulation. Data from loci that originated from MGI were
excluded from the analyses.
Genetic diversity
The genetic diversity of each population was assessed by
determining the number of alleles per locus in each pop-
ulation and by calculating the expected heterozygosity
(H) (Table 1). The mean numbers of alleles ± SE of the
Kalinga, Palawan and Davao del Norte populations were
2.40 ± 0.37, 4.80 ± 0.83 and 4.50 ± 0.87, respectively. The
mean of H ± SE of the Kalinga, Palawan and Davao del
Norte populations were 0.39 ± 0.10, 0.60 ± 0.09 and 0.51
± 0.08, respectively.
Effective population size
Ne values of the three populations were calculated from
the mean expected heterozygosity and mutation rates of P.
falciparum microsatellite loci using the IAM and the SMM
(Table 2). The sizes of the Kalinga, Palawan and Davao del
Norte populations were 997, 2388 and 1650, respectively,
based on the IAM, and 1313, 4202 and 2515 respectively,
based on the SMM.
Genetic bottleneck
Evidence of genetic bottlenecks was assessed based on het-
erozygosity (H) excess and patterns of allele frequency dis-
tribution (ie, mode-shift) [19,20]. Table 3 shows the
number of loci that correspond with H excess and defi-
ciency. Statistically high levels of H excess compared with
H deficiency (P < 0.05) were observed in the Kalinga and
the Palawan populations when the IAM was applied to the
analyses, indicating evidence of genetic bottleneck events.
In contrast, there was no significant difference between
the levels of H excess and H deficiency in the Davao del
Norte population when the IAM and the SMM were
applied to the analyses, indicating the absence of a genetic
bottleneck event.
In the Davao del Norte population, the mode-shift indica-
tor test showed a normal L-shaped distribution, indicating
evidence of a non-bottlenecked population. This test
could not be applied to the other two populations due to
small sample sizes (<30) [21].
Multilocus linkage disequilibrium
IAS values were calculated for the three populations, with
permutation testing of the null hypothesis of IAS = 0 (equi-
librium of multilocus frequencies) (Table 4). IAS values of
the three populations were highly variable. When the sin-
gle-clone haplotype was used in the analysis, the IAS values
ranged from 0.043 to 0.104, whereas when the unique
haplotypes were used in the analysis, the IAS values ranged
from 0.003 to 0.029. Significant linkage disequilibrium
was observed in all three populations (P < 0.05) when the
single-clone haplotype was examined using the 10 loci in
the analyses. However, no significant linkage disequilib-
rium was found in the Kalinga and Palawan populations
when the unique haplotypes were examined in the analy-
ses.
Genetic differentiation
Levels of genetic differentiation between each pair of the
three different populations were indicated by FST values
using the Weir and Cockerham estimator [25,26]. The val-
ues for each of the pairwise population comparisons
ranged from 0.096 to 0.144. All values were significantly
different from 0 (P < 0.001) (Figure 1).
Discussion
The failure to obtain allelic data of the 18 isolates might
be due to low parasite density and/or misdiagnosis of
other malaria species such as P. vivax by microscopic
observations in the field during the surveys in Kalinga and
Palawan. The samples of Davao del Norte were collected
at a hospital where more accurate microscopic diagnosis
was feasible. A possibility that differences in sample size
between the Kalinga population and the other two popu-
lations might have affected the results of the analyses can-
not be ruled out, and this could be the limitation of the
study. However, some of the data analyses such as
expected heterozygosity (H), effective population size
(Ne) and multilocus linkage disequilibrium (IAS), were
Table 1: Mean numbers of alleles and expected heterozygosity (H) in the three P. falciparum populations
Population No. of allele mean ± SE Expected heterozygosity (H) mean ± SE
Kalinga 2.40 ± 0.370.39 ± 0.10
Palawan 4.80 ± 0.83 0.60 ± 0.09
Davao del Norte4.50 ± 0.87 0.51 ± 0.08

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corrected for sample size, which enabled an appropriate
comparison of different data sets.
Levels of genetic diversity of the three P. falciparum popu-
lations in the Philippines were different from each other.
The Kalinga population showed a relatively low number
of alleles and low levels of expected heterozygosity (H),
being similar to those of South American populations of
P. falciparum (H: 0.30–0.40) [6,12]. In contrast, the Pala-
wan and the Davao del Norte populations showed inter-
mediate levels of H, being similar to those of mainland
Southeast Asian (H: 0.51), Papua New Guinean (0.62–
0.65), and Malaysian Borneo (0.46–0.63) populations of
P. falciparum [6,7].
The levels of genetic diversity seemed to be correlated with
the levels of malaria endemicity. The API in Kalinga prov-
ince was lower than that of the other 2 provinces. Accord-
ing to the report from the Center for Health
Development-CAR in Kalinga province, the mean of API ±
SD was 4.8 ± 1.9 (1996–2005). According to the report
from the Kilusan Ligtas Malaria in Palawan province, the
mean of API ± SD was 15.6 ± 4.4 (1999–2005). This dif-
ference of malaria endemicity between the two provinces
probably affected the levels of genetic diversity of the two
populations of P. falciparum.
Levels of genetic differentiations (FST) between the popu-
lations of P. falciparum in the Philippines (0.096–0.144)
were moderate, and were similar to those between the
mainland Southeast Asian and Papua New Guinean pop-
ulations of P. falciparum (0.121–0.140), and lower than
those between Sabah and Sarawak populations of P. falci-
parum (0.217–376) in Malaysian Borneo, as previously
reported [6,7].
In the present study, possibilities of genetic bottlenecks
with the Kalinga and the Palawan populations of P. falci-
parum were found. However, the significant heterozygos-
ity excess (evidence of genetic bottlenecks) was observed
only when the IAM was used for the analysis. This result is
not robust because modes of microsatellite mutation the-
oretically fit the SMM. Luikart and Cornuet recommended
that only the SMM should be used for microsatellite data
to test for genetic bottlenecks, because the IAM may detect
heterozygosity excess even in non-bottlenecked popula-
tions [20].
Significant multilocus linkage disequilibrium was
obtained from all three populations of P. falciparum in the
Philippines, when a single clone was used in the analysis
[22-24]. The Kalinga and the Palawan populations
showed decreased linkage disequilibrium with no levels
of significance when the unique haplotypes were included
in the data set. This is because the identical haplotype was
frequently found from two or more isolates (patients)
within the same population in Kalinga and Palawan. In
particular, in the Kalinga population, 57% of the haplo-
types (four out of seven haplotypes) were shared among
two or more isolates (patients). In fact, such isolates were
collected from the same site and on the same day. May-
nard-Smith et al proposed simple methods to distinguish
between "clonal" population structure and "epidemic"
population structure of microbial pathogens [22]. They
Table 2: Effective population sizes (Ne) of the three P. falciparum
populations
Population IAMSMM
Kalinga 997 (428, 2,271) 1,313 (564, 2,991)
Palawan 2,388 (1,026, 5,440)4,202 (1,806, 9,572)
Davao del Norte1,650 (709, 3,758)2,515 (1,081, 5,729)
Table 3: Observed versus expected heterozygosity in the three P. falciparum populations
PopulationNo. of
loci
IAM SMM Mode-shift
H
excess
H
deficiency
PH
excess
H
deficiency
P
Kalinga761
P < 0.0552 NSNA
Palawan981
P < 0.0536 NSNA
Davao del
Norte
1055 NS46 NS Normal
Proportion of loci with excess or deficiency in observed heterozygosities, relative to expected heterozygosities. Data were subject to mutation
drift equilibrium via IAM and SMM, as well as mode-shift analyses. H: heterozygosity. NS: not significant. NA: not applicable. a: sign test, b: Wilcoxon
sign-rank test, normal: normal L-shaped distribution = nonbottlenecked population, shifted: shifted mode = bottlenecked population.

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demonstrated that epidemic population structure could
be identified by treating the multiply-represented haplo-
type as single individuals and then re-examining the link-
age disequilibrium. If a decreased level of linkage
disequilibrium is observed in the second analysis, the
population is estimated to have an epidemic population
structure. The results indicated that the Kalinga and Pala-
wan populations had an epidemic population structure.
On the contrary, the Davao del Norte population per-
sisted with significant linkage disequilibrium (P < 0.05)
even when the multiply-represented haplotype was
treated as single individuals. This result indicated that a
recombination rate was estimated as low in the Davao del
Norte population, and that the population has possibly
not experienced the recent epidemic expansion of a partic-
ular haplotype.
Generally, levels of malaria transmission have a negative
correlation with levels of linkage disequilibrium [6,7,12].
In areas where malaria transmission is high, levels of link-
age disequilibrium are likely to decrease because one
malaria patient can be infected with more than two genet-
ically different clones of the parasite, and a mosquito can
frequently acquire more than two genetically different
clones in the same blood meal. Then, meiotic recombina-
tion of the parasite genomes will occur in the mosquito
midgut and decrease the levels of linkage disequilibrium.
In contrast, in areas where malaria transmission is low,
levels of linkage disequilibrium are likely to increase
because, generally, the frequency of multiple-genotype
infection (MGI) and the number of clones per patient are
lower than those in high transmission areas, and the
chances of acquiring more than two genetically different
clones with one blood feeding by a mosquito will also be
lower than those in high transmission areas.
In the present study, MGI in a patient was observed in the
Palawan (three of 28 isolates: 10.7%) and the Davao del
Norte (two of 30 isolates: 6.7%) populations, but not in
the Kalinga population. MGI is important to the mainte-
nance of genetic diversity of the P. falciparum population.
Without multiple infections, this parasite has no chance
of encountering genetically different clones in a mosquito
midgut. In the present study, a clear correlation between
the levels of genetic diversity (H) and the frequencies of
MGI was found. The H values of the three populations
were elevated as follows: Kalinga (0.39) < Davao del
Norte (0.51) < Palawan (0.60), and the frequencies of
MGI were also elevated as follows: Kalinga (0.0%) <
Davao del Norte (6.7%) < Palawan (10.7%). In contrast,
a negative correlation between the levels of linkage dise-
quilibrium and the frequencies of MGI of the parasite was
found. When single clones were used in the data set for
the linkage disequilibrium analysis (Table 4), the levels of
linkage disequilibrium were elevated as follows: Palawan
< Davao del Norte < Kalinga, while the frequencies of MGI
were elevated as follows: Kalinga (0.0%) < Davao del
Norte (6.7%) < Palawan (10.7%). These results are con-
sistent with the previously reported population genetics
trends of P. falciparum [6,7,12].
However, caution is needed for detecting MGI by micros-
atellite typing, because it is likely to underestimate the
prevalence of MGI of P. falciparum. In Brazil, over 40% of
local isolates were MGI detected by a single-copy antigen-
coding gene (merozoite surface protein-1: msp-1), however
less than 20% of local isolates were MGI detected by mic-
rosatellite typing [6,27]. In fact, nested PCR genotyping of
block 2 of the msp-1 gene and block 3 of msp-2 [28] in the
present samples showed that more than 20% of the iso-
lates of each of the three populations proved to be MGI
(Additional File 2).
The levels of genetic differentiation between the three
populations in the Philippines were moderate, and lower
than those reported in Malaysian Borneo where the para-
site populations were highly fragmented from each other
[7]. High levels of genetic differentiation of the popula-
tions in Malaysian Borneo are considered to be a result of
fragmentation of the population structure owing to an
effective malaria control and low migration rate of people
in the endemic areas. Therefore it is expected that an ele-
vation of FST values between the three populations in the
Philippines will be detected in the near future, with the
onset of effective malaria control.
However, the migration rate of people to the endemic
areas in the Philippines may be different from that in
Malaysian Borneo. In Malaysian Borneo, malaria endemic
areas are typically in remote, isolated mountainous vil-
lages. In contrast, in the Philippines, malaria is not only
endemic in remote areas (e.g. forests, mountainous vil-
lages) but also in relatively big cities or ports (e.g. Puerto
Table 4: Multilocus linkage disequilibrium in the three P.
falciparum Populations
Population Single ClonesUnique Haplotypes Only
No.
IAS
No.
IAS
Kalinga13 0.104***7 0.003
Palawan 160.043**14 0.011
Davao del Norte28 0.052** 240.029*
Single clones show all haplotypes in single-clone infections. Unique
haplotypes show haplotypes excluding duplicates of any multiply
represented infection. No. indicates the number of isolates for each
measure. *P < 0.05, ** P < 0.01, *** P < 0.001

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Malaria Journal 2009, 8:96 http://www.malariajournal.com/content/8/1/96
Page 7 of 8
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Princesa City, Palawan province). For example, in Pala-
wan, malaria is highly endemic in villages near seashores
where fishermen live, and they sail from island to island,
freely catching and selling fish.
Although mechanisms for the emergence of drug resist-
ance have not been fully understood, levels of genetic
diversity and characteristics of population structure of P.
falciparum would be the key factors to estimate a potential
of the emergence of drug resistance. Ariey et al demon-
strated that a metapopulation concept would be applica-
ble to explain the emergence of drug resistant malaria
[29,30]. They showed that the P. falciparum populations
in Southeast Asia and South America, where chloroquine
resistance emerged, were consistent with a typical metap-
opulation structure, ie, parasite populations were differ-
entiated in several subpopulations but not completely
isolated from each other. The levels of genetic diversity
and the characteristics of population structure of P. falci-
parum in the Philippines were similar to those reported in
mainland Southeast Asia or South America where chloro-
quine resistant malaria emerged [6]. Indeed, Chen et al
indicated that some chloroquine resistant mutations
seemed to have emerged in the Philippines [10]. Moreo-
ver, a chloroquine resistant malaria determined by an in
vitro chloroquine susceptibility test has been reported
from Kalinga, Palawan and Davao del Norte [8,9,31]. The
results in this study suggest that the populations in the
Philippines have the potential to make the drug-resistant
mutation(s) spread into different endemic areas in this
country.
Conclusion
The genetic diversity and population structure of P. falci-
parum in the Philippines were examined using 10 highly
polymorphic microsatellite loci of the parasite. The levels
of the genetic diversity and the frequencies of MGI corre-
lated with the local malaria endemicity. On the other
hand, the levels of linkage disequilibrium correlated neg-
atively with the local malaria endemicity. Genetic popula-
tion analyses of P. falciparum using the microsatellite loci
provide insight not only into understanding the basic
biology of this organism, but also the epidemiology and
control of the disease.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
MI carried out the molecular genetic studies, performed
the population genetic analyses and drafted the manu-
script. PTR, EAV, ADE, THat and SIK collected the patients'
blood samples as well as helping with the writing of the
manuscript. THay and KT helped with the population
genetic analyses and helped with the writing of the man-
uscript. SK participated in the design of the study, acquisi-
tion of funding, coordination and writing of the
manuscript.
Additional material
Acknowledgements
Authors would like to thank the following people for kind assistance in
obtaining samples and epidemiological data: Dr. Nao Taguchi, Gunma Uni-
versity School of Health Sciences, Gunma, Japan: Mr. Ray U. Angluben, Mr.
Darius de la Cruz, Mr. Conrado E. Mendoza Jr, Kilusan Ligtas Malaria,
Puerto Princesa City, Palawan province, the Philippines: Dr. Gavino, Provin-
cial Health Officer, Kalinga province, the Philippines: Ms. Norma B. Buna-
ton, Ms. Linda Esquivel, Center for Health Development-CAR, Tabuk City,
Kalinga province, the Philippines: the Dr. Romulo Busuego, Director of
Davao Regional Hospital, Tagum City, Dr. Alfredo Lacerona, Municipal
Health Officer, Kapalong, Davao del Norte province, the Philippines. The
authors also thank Pilipinas Shell Foundation Inc., Palawan, for supporting
the field survey in Palawan province. This work was supported by a Grant-
in-Aid for Scientific Research (B) (16406012, 19406013) from the Ministry
of Education, Culture, Sports, Science and Technology of Japan.
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