1 INTRODUCTION

Forward: Molecular epidemiology

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Molecular epidemiology is a fairly new branch of science that has emerged in the last 20 years in parallel with the development of molecular biology (Tazi et al., 2002). To understand molecular epidemiology, it is worth knowing what epidemiology is. Last (2001) defined it as ‘the study of the distribution and determinants of health-related states or events in specified populations, and the application of this study to control of health problems, in the first place the frequency, distribution and determinants of a disease’. In the case of molecular epidemiology, the definition given by Last (2001) still holds but the addition comes from the integration of molecular approaches into the conventional and classical epidemiologic studies. Molecular epidemiology becomes, then, the application of molecular biology techniques to the study of the distribution and determinants of infections and communicable and non-communicable diseases (Tazi et al., 2002).

In the light of the new definition, several disciplines, such as medicine, molecular biology, epidemiology, biostatistics, genetics and computer science, are conjugated with classical concepts like study designs, case control and cohort studies, and types of analyses, remaining as descriptive and analytical as they are.

1.1 Historical background

Leishmaniasis has been an antique public health problem in South-West Asia and the Arab World reported from time immemorial as the pharaohs ruled in Egypt and Assyrians in Mesopotamia. It was extensively described by Arab-Islamic scientists like Avicenna (Ibn-Sina, 980-1037 A.D.) who wrote a complete chapter in his prominent book entitled Alkanoun Fi El Tebb raising the possibility of mosquitos being involved in the transmission of the disease. Al-Rhazi (AD 850 to 923) already described cutaneous leishmaniasis (CL) as a disease endemic in Balk (Afghanistan) and Baghdad (for review see Bray, 1987; Oumeish, 1999, Morsy, 1996; Cox, 2002). Russell described CL in Aleppo-Syria in 1756 (reviewed by Klaus et al., 1999).

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The city of Jericho is known as an old classic focus for CL, active for at least the last 130 years as confirmed by Robert Ruby’s visit to Palestine who wrote in 1873: ‘’Then you would notice among people in Riha (Arabic name for Jericho) or in dealings with the Bedouins, that almost everyone in the valley had on his hands or face at least one large ugly scar’’. Later on, two scientists, De Bermann, the French, (1910) and Huntemueller, the German, (1914), with the help of Mastermann and Canaan, described cases of leishmaniasis in Jericho where the latter thought that he had made a new discovery and allowed himself to name it as Plasmosoma jerichoense. The people of Jericho called it, and still do, ‘Habat Riha’ (Jericho button or boil).

Adler & Theodor in 1926 (1957) were the first to experimentally prove that the Phlebotomine sand fly, P. papatasi, is the vector for CL in Jericho. They isolated Leishmania parasites, called L. tropica at that time, from this sand fly species. This was confirmed by Naggan et al (1970) and Schlein et al (1982). Gunders et al (1968) showed that in Jericho the reservoir host for Leishmania parasite which he, then, called L. major was Psammomys obesus. Local physicians continued to see CL patients, e.g., in Jerusalem (Al-Quds) (Canaan, 1945) and Nablus (Arda, 1983).

1.2 Clinical symptoms of leishmaniases

Leishmaniases caused by obligate intracellular protozoan parasites of the genus Leishmania, order Kinetoplastida, are, clinically, subdivided into three distinct entities: i) cutaneous leishmaniasis (CL) caused by L. major, L. tropica and, rarely, L. infantum and L. donovani, in the Old World (OW) and L. mexicana in the New World (NW); ii) visceral leishmaniasis (VL) caused by representatives of the L. donovani complex and, rarely, by L. tropica in the OW and, rarely, L. amazonensis in the NW; and iii) mucocutaneous leishmaniasis (MCL) caused by L. braziliensis, L. panamensis, and L. guyanensis, in the NW, with reported cases by L. donovani, L. major, and L. infantum in the OW. Sometimes a special form of CL is described as a fourth independent entity: diffuse cutaneous leishmaniasis (DCL) caused by L. aethiopica in the OW and L. amazonensis in the NW (Sacks et al., 1995; Desjeux, 1996; Herwaldt, 1999; Saliba and Oumeish, 1999; Bulle et al., 2002; Ben Ami et al., 2002).

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CL manifests itself starting from small erythematous papules through nodules and to ulcerative lesions. Unusual clinical manifestations are sporotrichoid patterns, i.e., subcutaneous nodules developing along lymphatics, and hyperkeratosis, i.e., thick adherent scale, as well as leishmaniasis recidivans, also known as lupoid leishmaniasis. In the Middle East, it was very difficult and even impossible to discern by the clinical picture whether cases were caused by L. major or L. tropica (Klaus and Frankenburg, 1999).

Visceral leishmaniasis (VL), or Kala-azar, is associated with prolonged fever, splenomegaly, hepatomegaly, substantial weight loss, progressive anemia, pancytopenia, and hypergammaglobulinemia. It can be impaired by serious bacterial infections and is usually fatal if left untreated (Sundar and Rai, 2002). A serious sequel to Kala-azar is post-Kala azar dermal leishmaniasis (PKDL) which appears within months or years of the cure of VL (Ashford, 2000).

Mucocutaneous leishmaniasis (MCL) is a severe form of CL, as it produces disfiguring lesions and mutilations of the face, nose and throat (Desjeux, 1999). They commonly appear in the mouth and nose where they erode underlying tissue and cartilage (Ashford, 2000). If the lesions spread to the roof of the mouth and the larynx, they may prevent speech. Other symptoms include fever, weight loss, and anemia. There is always a substantial danger of bacteria infecting the already open sores.

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Diffuse cutaneous leishmaniasis (DCL) produces disseminated and chronic skin lesions resembling those of lepromatous leprosy. It is difficult to treat (http://www.who.int/tdr/diseases/leish/default.htm, Ashford, 2000).

1.3  Epidemiology of leishmaniasis:

1.3.1  Global view

Leishmaniases are parasitic infection caused by a range of Leishmania parasites supported by a wide range of vectors and reservoirs distributed on all inhabited continents (Ashford 1996 and 1999 and 2000). Recently, kangaroos in Australia have been reported to be infected by Leishmania-like parasites (Rose et al., 2004). The diseases are endemic in 88 countries, of which 66 are in the OW, 22 in the NW and 72 in the developing countries. It has been estimated that 350 million people are at risk, with 500,000 new VL cases each year. Confirmed cases of VL have been reported from 66 countries, 90% of the world’s VL burden occurs on the Indian subcontinent (India, Bangladesh and Nepal), East Africa (Sudan, Ethiopia and Kenya) and Brazil (WHO 1991, 1996 and 1998). There are 1.0-1.5 million cases of CL each year, with 90% of CL cases occuring in 7 countries: Afghanistan, Algeria, Brazil, Iran, Peru, Saudi Arabia and Syria, showing that Middle East is a centre focus for CL (Desjeux, 1999; Desjeux, 2004; http://www.who.int/tdr/diseases/leish/default.htm ).

1.3.2 Local view

In Palestine, two forms of leishmaniasis exist. One is the CL caused by L. major or L. tropica and the other is VL caused by L. infantum. Leishmaniasis in general is reported in all Palestinian districts except Gaza strip with an official incidence rate in West Bank of more than 10 per 100,000 in 2003 (Klaus et al., 1994; Baneth et al., 1998; Abdeen et al., 2002; Anders et al., 2002; Al-Jawabreh et al., 2004, Jaffe et al., 2004, Schoenian 2003; Ministry of Health, 2004).

1.4 Leishmaniasis: Public Health Surveillance

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Leishmaniasis is a reportable infection in Palestine (Ministry of Health, 2004) and all neighbouring countries like Jordan, Syria and Saudi Arabia. Ministries of Health collect data for various reasons like therapeutic and control strategies. Despite the law mandate, underreporting is still believed to prevail partly due to passive surveillance, including only cases coming from clinics and hospitals.

Already before 1994 when the health authority was in the hands of the Israeli military rule, there were attempts to improve the reporting system in Palestine (Jaber, 1987). After 1994, the Palestinian Ministry continued the surveillance activity but suffered some disturbances between 2001 and 2005 due to the political turmoil in the area. The current situation depends on passive collection of data from health care providers in all Palestinian districts by the preventive medicine department in the Ministry of Health and presenting them either on the official website or distributing hardcopies to health stake-holders in the regions.

Several definitions for surveillance have been proposed. That by Langmuir (1963) who stated that ”continued watchfulness over the distribution and trends of incidence through the systematic collection, consolidation, and evaluation of morbidity and mortality reports and other relevant data, together with dissemination to those who need to know” is the most common. It is a continuous activity and not simply a study or a survey. The aim of surveillance is to control and prevent diseases, improve epidemiological knowledge and assist policy making. The tripod of this activity is the laboratory, physicians/nurses and epidemiologist/statistician.

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Data collected by active or passive surveillance should be descriptively analyzed in such a way as to provide an early warning system for an existing or coming health problem, i. e epidemic. Three methods are proposed for this purpose:

  1. 1. Shewhart’s Plot: a common technique used for quality control/assurance in medical laboratories to check the performance over a period of time. It was originally designed for industrial control (Shewhart, 1930), then introduced into clinical chemistry and medical laboratories by Levy and Jennings in the 1950s (Levy and Jennings, 1950) to be applied in all clinical laboratories. Later, Westgard et al (1981) modified it by introducing interpretation rules called multi-rule Shewhart that became known as Westgard rules (see Material and Methods, 2.12.4).
  2. 2. Moving average: a statistical tool common in stock markets to spot the trends of the highs and lows of the security prices based on a window time period set by the analyst. This idea can be used to detect outbreaks and trends in disease distribution.
  3. 3. SaTScan software: detects statistically significant disease clusters based on statistical characters (see Materials and Methods, 2.12).

These and other early warning methods would be more effective if there would exist a regional network that would allow free exchange of data between countries of the region such as for instance Eurosurveillance (http://www.eurosurveillance.org), which distributes alerts and regular releases to all European countries.

1.5 Clinical diagnosis and identification

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The conventional methods of clinical diagnosis of CL have ranged from clinical picture and epidemiological data, visualizing the amastigotes by microscopy of stained smears from skin touch specimens or biopsies to in-vitro culturing of the parasite (Reed, 1996; Herwaldt, 1999). These conventional methods are, however, limited in sensitivity, need an experienced hand and do not distinguish between Leishmania species which differ in virulence and, subsequently, may require different therapeutic regimes and control measures. For all this and over the last decade diagnostic tests based on molecular biology techniques i. e PCR, were introduced and proved to be more sensitive and specific (Van Eys et al., 1992; Wilson, 1995; Osman et al., 1998).

The sensitivity of different diagnostic methods was the subject of several studies. PCR protocols were given priority over conventional methods, although few of these studies gave conflicting results (Table 1.1). These discrepancies are due to factors like the different gold standards being used to define a case of CL and sampling methods.

Table 1.1 Selected studies that compared methods of diagnosis for CL

Culture%

Histopathology%

Smear%

PCR%

Reference

50-biopsy 58-aspirate

14

19

-

Weigle et al., 1987

-

76

48

86

Andresen et al., 1996

-

-

58-wooden toothpick

48- lancet

100

Belli et al., 1998

-

-

84

-

Rajabi et al., 1999

-

33

42

92

Aviles et al., 1999

-

-

90.4

80.8

Ramirez et al., 2000

-

-

95

100

Romero et al., 2001

-

-

85

81

Robinson et al., 2002

80

30

71.5

-

Sharquie et al., 2002

46.5

66.2

67

95.4

Rodrigues et al., 2002

55.3-biopsy

46.3-aspirate

-

46.7

75.7

Weigle et al., 2002

-

-

-

92

Safaei et al., 2002

74

-

77

-

US military, 2002-2003

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In the history of leishmaniasis, several methods were used for classification, characterization and identification of the infecting parasites, reviewed by El-Tai et al (2000). These included simple methods such as geographical classification, e.g. Old World versus New World, and epidemiological and /or clinical criteria. More advanced criteria began to emerge starting with EF serotyping (Schnur et al., 1972, 1977 and 1990), isoenzyme analysis (Miles et al., 1980; Evans et al., 1984; WHO, 1990; Andersen, 1996), and monoclonal antibodies (Noyes et al., 1996). Then molecular techniques were introduced such as RFLP (Restriction Fragment Length Polymorphism), kDNA and nuclear DNA/ Southern hybridization (Jackson et al., 1984; Beverly et al., 1987; Barker, 1989; Van Eys et al., 1989, 1991; El-Tai et al., 2001), fingerprinting ( Macedo et al., 1992), PCR fingerprinting with non-specific primers (Williams et al., 1990; Tibayrenc et al., 1993; Pogue et al., 1995 a, 1995 b; Schoenian et al.,1996, El-Tai et al., 2001), molecular karyotyping (Lighthall and Gianini, 1992), and PCR-SSCP (El-Tai et al., 2001). However, most of these techniques lack discriminatory power or reproducibility and are not easy to compare when used in different laboratories.

1.6 Multilocus enzyme electrophoresis (MLEE)

Multilocus enzyme electrophoresis (MLEE) is considered the ‘gold standard’ and reference method for identification and classification of species and strains, and for studying variability within Leishmania (Rioux et al., 1986; Russell et al., 1999). Promastigote mass cultures isolated from specimens are normally used for this analysis. A panel between 10 and 20 isoenzymes is utilized. The commonly used enzymes are: PGM, phosphoglucomutase, (E.C.2.7.5.1); GPI, glucose-phosphate isomerase (E.C.5.3.1.9); GOT, glutamate-oxaloacetate transaminase (E.C.2.6.1.1); ME, malic enzyme (E.C.1.1.1.40); 6PGD, 6-phosphogluconate dehydrogenase (E.C.1.1.1.49); G6PD, glucose-6-phosphate dehydrogenase (E.C.1.1.1.37); NP, nucleoside purine phosphorylase (E.C.3.2.2.1); MDH, malate dehydrogenase (E.C.1.1.1.37.), MPI, mannose phosphate isomerase (E.C.5.3.1.8); ICD, isocitrate dehydrogenase (E.C.1.1.1.42); DIA, diaphorase nicotinamide adenine dinucleotide (reduced form) (E.C.1.6.2.2); GLUD, glutamate dehydrogenase (E.C.1.4.1.3); FH, fumarate hydratase (E.C.4.2.1.2). In each run, a World Health Organization (WHO) reference strains is used. The techniques and the zymodeme nomenclature adopted are those of Montpellier centre (Le-Blanq et al., 1986I ⅈ Nimri et al., 2002).

MLEE has the advantage of backing a large data set and a well-managed reference laboratory (Rioux et al., 1986). MLEE has some disadvantages. It is expensive, slow and laborious, and it is not easy to compare the raw data from different laboratories. The need of mass in-vitro culture makes it unsuitable for high throughput analyses (Andresen et al., 1996; Noyes et al., 1996; Jamjoom et al., 2002a). A major disadvantage is that it determines phenotypes and not genotypes. In addition, any nucleotide substitution that does not change the amino acid composition remains undetected, and the same is true for changes in the amino acid composition that do not influence the electrophoretic mobility. Another disadvantage is that the house-keeping genes analysed in MLEE are most probably under selective pressure so that mutations observed are not neutral. Furthermore, MLEE relies on the assumption that the parasite’s isoenzyme types (or zymodemes) represent stable multilocus genotypes. This is only true if genetic recombination is almost absent in natural populations of the parasite (Jiménez et al., 1997).

1.7 Microsatellites

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Microsatellites or simple sequence repeats (SSRs), or Short Tandem Repeats (STRs), discovered in 1981, are tandemly repeated motifs of 1-6 nucleotides found in all prokaryotic and eukaryotic genomes. They are present in both coding and non-coding regions (Ellergan 2004). In addition to being highly variable and polymorphic, microsatellites are also easy to genotype and densely distributed throughout eukaryotic genomes, making them the preferred genetic marker for high resolution genetic mapping (Dib et al., 1996; Dietrich et al., 1996; Schuler et al., 1996; Knapik et al. 1998; Cooper et al., 1999).

Dinucleotide repeats dominate, followed by mono- and tetranucleotide repeats, and trinucleotide repeats are least dominant. Repeats of five (penta-) or six (hexa-) nucleotides can also be found. Generally, among dinucleotides, (CA)n repeats are most frequent, followed by (AT)n, (GA)n and (GC)n, the last type of repeat being rare (Ellergan, 2004). Microsatellite loci are characterized by high heterozygosity and the presence of multiple alleles, which is in sharp contrast to unique DNA sequences (Ellergan, 2004). Microsatellites account for 3% of the human genome (International Human Genome Sequencing Consortium, 2001). The genome of Leishmania is relatively rich in microsatellites with about 600 (CA)n loci per haploid genome (Rossi et al., 1994). Currently a Leishmania genome project (http://www.sanger.ac.uk/Projects/L_major/) is being carried out which showed that L. major Friedlin genome, for instance, is 32.8Mb in size, with a karyotype of 36 chromosomes.

There are more applications of microsatellite analyses other than gene mapping which are ancient and forensic DNA studies: e.g. population genetics and conservation/management of biological resources (Jarne & Lagoda 1996), assessment of population subdivision and phylogenetic relatedness (Queller et al., 1993), parentage analysis, phylogenetic studies (Bowcock et al. 1994), studies looking at population differentiation (Paetkau et al., 1995) and measuring inbreeding (Coltman et al., 1998; Coulson et al. 1998).

1.7.1 Mutation mechanism

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Microsatellite sequence variation results from the gain and loss of single repeat units or a single nucleotide. The most plausible explanation of loss of repeat units is slippage of polymerase during DNA replication (Schloetterer & Tautz 1992). This is transient dissociation of the replicating DNA strands followed by misaligned re-association thought to be due to DNA polymerase pausing and then dissociating from the DNA (Levinson & Gutman, 1987; Ellergan, 2004) as shown in figure 1.1. Replication slippage also occurs during PCR amplification of microsatellite sequences in vitro, characterised by the presence of ‘stutter bands’— that is, minor products that differ in size from the main product by missing or additional repeat units (Shinde et al., 2003). It is worth noting that most of these primary mutations in vivo are corrected by the mismatch repair (MMR) system, and only the small fraction that was not repaired ends up in the form of variable microsatellites (Strand et al., 1993, You, 2002).

Figure 1.1 Replication slippage caused by dissociation of the two strands, re-aligning of the nascent strand out of the register (left), and then continued replication as part of the mismatch repair.

This will cause misalignment producing a loop in the nascent strand and increase the repeat length. Alternatively, the same will take place but on the template strand (right) causing decrease of repeat length (Ellergan, 2004).

The emergence of microsatellite variation is explained by the ‘length and point mutation model’. It is based on the existence of two opposing mutational forces operating on microsatellite sequences: length mutations, the rate of which increases with increasing repeat count, whereas point mutations break long repeat arrays into smaller units. At equilibrium, there will be a steady-state distribution of repeat lengths governed by the rate of length mutation and the rate of point mutation (Dieringer & Schlotterer, 2003; Bell, & Jurka, 1997; Ellergan, 2004).

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The rate of mutation at a given microsatellite locus is influenced by various factors: the repeated motif itself, allele size, chromosome position, GC content in flanking DNA, cell division (mitotic vs. meiotic) and the mismatch repair system (e.g. mutations at MMR genes) which is critical for the stability of the STR (You, 2002).

In addition, recombination has been presented as a potential explanation for mutation. Recombination changes the STR length/repeat number by unequal crossing over or by gene conversion (Brohele & Ellegren, 1999; Hancock, 1999; Jakupciak & Wells, 2000; Richard & P.ques, 2000; You, 2002).

1.7.2 Functions of microsatellites

Possible functions of microsatellites are illustrated in figure 1.2 adopted from You et al. (2002). (For more descriptions see: You, 2002 and the references therein).

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Figure 1.2 Possible functions of microsatellites (You et al., 2002)

1.7.3 Application of microsatellites for Leishmania strain typing

To overcome the disadvantages of MLEE and of most molecular approaches used so far, methods based on microsatellite DNA loci have been developed for strain typing and population genetics studies within the genus Leishmania (Rossi et al., 1994; Jamjoom et al., 2002a & b, Schwenkenbecher et al., 2004). Microsatellite analysis yields more polymorphisms (Jamjoom et al., 2002a), exhibits a high level of discrimination and is suitable for characterizing closely related strains like those of L. infantum (Bulle et al., 2002). This method is quantitative and reproducible; the output data are comparable and exchangeable between laboratories. Microsatellite analysis has the potential for high-throughput analyses. At the beginning, Russell et al (1999) successfully used three microsatellite markers for the discrimination of species within the NW subgenus Viannia. In the course of time, more and more polymorphic microsatellite markers were developed to increase the discriminatory power, e.g., 13 markers for L. major by Jamjoom et al. (2002b), 16 for L. tropica by Schwenkenbecher et al. (2004), and 20 markers for L. donovani and L. infantum by Jamjoom et al. (2002a). The main disadvantage of using microsatellites is that these sequences are prone to homoplasy and it is, therefore, necessary to develop a panel of 15-20 independent microsatellite markers. In Leishmania, microsatellite variation was shown to be species-specific (Jamjoom et al., 2002b, Schwenkenbecher et al., 2004), therefore different panels of markers should be designed for each species to be studied.

1.8 Two models for microsatellite evolution

Two different models are used in the literature to explain the evolution of microsatellite sequences.

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The Infinite Allele Model (IAM) was developed for the interpretation of allozyme variation. It supposes that every new mutation gives rise to a new electrophoretically distinguishable allele (or electromorph). IAM has proved very successful in explaining the observed allozyme variation (Nei 1987). Homoplasy in IAM is not accounted for as it never occurs, because mutation always creates new alleles (Rousset, 1996), which is a situation that is very different in microsatellite markers. Homoplasy is the identity between two alleles that are not identical by descent, but by state. For example, one allele has mutated by chance, but not because of a common ancestor, to the same sequence as the other, or, simply, because two different alleles cannot be distinguished by the technique used (Costantine, 2003; De Meeûs, 2004). The majority of mutations at microsatellite loci are stepwise in nature, changing allelic sizes by gaining or loosing single or very few numbers of repeats. Normally, microsatellites tend to expand by gaining new repeats. From a certain number of repeats on natural selection does, however, counteract by decreasing the amount of repeats. Therefore, one particular number of repeats might have been due to the gain of a new repeat unit or to the loss of a repeat due to selection. That means the ancestors can be different. The homoplasy produced during microsatellite evolution leads to an underestimation of the total amount of variation and genetic distance, and to an overestimation of the similarities among populations. To take this into account, distance measures have been designed specifically to apply to microsatellites. The Stepwise Mutation Model (SMM) (Ohta and Kimura, 1973; Weber and Wong, 1993) has been used to simulate this situation, hence favoured when effects of mutation increase (Murray 1996).

IAM estimators are highly favoured and more accurate than SMM when populations have been only separated for a short period of time (300 generations) in which the effect of mutation is minimal (no homoplasy) and most of the allele frequency /genetic difference should be the result of genetic drift. Also, when the alleles contain no relevant history of mutational events, as might be the case for composite microsatellites, the IAM based estimators perform better than the SMM estimators (Murray, 1996).

1.9 Genetic distance measures used in microsatellite analyses

Measurement of genetic distances can be based on proportion of shared alleles (distance of shared alleles: Dps), which is the negative logarithm of the proportion of shared alleles (Bowcock et al. 1994). Dps is based on the IAM model. Dps distance measure can be calculated between individuals or between populations (Chakraborty and Jin, 1993). It can be used to construct dendrograms based on microsatellite data, to correlate genetic similarity with geographic location, and to place unknown individuals into the correct subpopulations (Estoup et al., 1995b).

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Another measure of genetic distance is delta mu squared, Ddm, was developed by Goldstein et al. (1995b) specifically for microsatellite markers and is based on the SMM model of evolution. Loci with high mutation rates are expected to yield larger Ddm values than those with lower mutation rates. The Ddm computer simulations suggest that it is robust to fluctuations in population size (Takezaki and Nei, 1996). An advantage of using Ddm is that it is independent of the assumption of symmetry in the mutation rate (Goldstein and Pollock, 1997). However, it was shown that when using microsatellite data, distance of shared alleles (Dps) is still superior to Ddm for closely related populations (Goldstein et al., 1995b).

Due to the complexity of the evolutionary process of the microsatellites themselves, there is no single estimator that is superior in all situations. Other distance measures that are useful in microsatellite analyses are:

  1. 1. Nei's standard distance Ds = -ln(id). The unbiased version for small sample sizes defined in subtracts unity from each of the estimates in the numerator and denominator (Nei, 1978).
  2. 2. Dsw: The stepwise weighted genetic distance measure (Shriver et al., 1995) is "an extension of Nei's minimum genetic distance" and is based on frequency-weighted means of the absolute value of the difference in number of repeats over pairs of alleles i and j, both within and between populations.
  3. 3. Dkf: The kinship coefficient kf is defined as the probability for a gene taken at random from I, at a given locus, to be identical by descent to a gene taken at random from J at the same locus (Cavalli-Sforza & Bodmer, 1971).
  4. 4. Ds or Gst: Nei's identity for two taxa (Slatkin, 1995).
  5. 5. Dfs: The fuzzy set similarity measure (Dubois and Prade, 1980) is calculated by finding the set of alleles found in population A (call it set A), the set found in population B (call it set B), and dividing the cardinality of their intersection by the cardinality of their union,

1.10 L. major and L. tropica

1.10.1 Distribution

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Cutaneous leishmaniasis (CL) caused by L. major or L. tropica is either endemic or epidemic (Ashford 1999). The endemic areas are usually identified by active or passive case reporting while the epidemic areas are usually identified by an early warning system. The distribution and epidemiology of both parasites is governed by several factors. These factors are population migration, urbanization, farming, malnutrition, climatic factors and global warming, notably bioclimatic and vegetation zones, and finally ambiguous rodent population fluctuations (Neoumine, 1996; Klaus et al., 1999, Ashford, 1999; Anis et al., 2001).

L. major and L. tropica are restricted to the Old World (OW), mainly in the Mediterranean basin, East Africa, Indian subcontinent, and West and Central Asia (Table 1.2). L. major CL is found in low lying arid and semiarid deserts (Klaus 1999). L. tropical CL, by contrast, is more common in urban areas and in villages in hilly rural areas (Klaus 1999). Examples for L. major foci are Jericho in Palestine (Jawabreh et al., 2001; Al-Jawabreh et al., 2003 and 2004) and Sidi-Bozaid in Tunisia (Ben Ismail et al., 1997). As reviewed by Jacobson (Jacobson, 2003), examples for urban L. tropica foci are Baghdad in Iraq, Aleppo in Syria, Kabul in Afghanistan and Sanliurfa in South-east Turkey. Within the past decade, the world’s largest L. tropica focus was in Kabul (WHO, 2002). Other smaller foci for L. tropica can be found in Shiraz in Iran, Mosul in Iraq, Ashkhabad in Turkmenistan, and Taza in Morocco.

Table 1.2 Summary of epidemiological and clinical features of L. major and L. tropica

Species

Clinical manifestation

Geographical distribution

Incubation

period

Reservoir

Vector

Resolution

Age/Gender

Distribution

Habitat

L. major

30% multiple sores, 70% on cheeks, arms and legs. Moist appearance. Rare: hyperkeratosis, sporotrichoid pattern: swollen lymph glands

Western and Central and South- west Asia , Africa, India

2-8 weeks

rodents: fat sand rat (Psammomys.obesus), gerbils (Meriones, Rhombomys opimus)

diverse rodents in Africa

Phlebotomus papatasi, North Africa and South -west Asia

Ph. duboseqi in Africa

Ph. salehi in India

Heals in 3–5

months with

scarring

All rural

populations

Semi-arid and salty areas with Chenopodiaceae,

Alluvial and loess deposits.

Sahel savannah

L. tropica

CL, recidivans

57% single sore, slowly

enlarges, crusty appearance

50% cheeks and arms

Western and Central and South- west Asia, North and East Africa, Sub- Saharan Savanna, India

2-24 months

Humans in anthroponosis,

hyraxes in Kenya and near the Lake Tiberias, dogs in Morocco

.

P. sergenti

P. guggisbergi inKenya

P. arabicus inTiberias

Heals over 1–2

years and scars, rarely spreads

Urban and rural children and younger adults.

In cities.

Rocky and semi-arid rural areas.

1.10.2 Clinical features

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In most patients, the skin lesion begins as a small erythematous papule about 2 to 6 weeks after inoculation. Over the following month the papule slowly enlarges, and a crust develops in its centre (Figure 1.3). With time, the crust falls away, exposing a shallow ulcer. If no treatment is given, the nodulous ulcer remains stable for 6 to 12 months before undergoing spontaneous resolution. Usually a shallow depressed scar is left behind.

Figure 1.3 Two cases of CL from Palestinian patients in Jericho. The disfigured chin case was caused by L. tropica. A case of L. major shows 3 lesions on the leg of a Chinese worker who lived in Jericho for one year.

CL caused by L. tropica and L. major are indistinguishable on clinical bases as both erupt in the same way, the size of the lesion ranging from a few millimeters to 4 centimeter or more. The site and number of lesions(s) are an indication of the type of CL. L. major usually presents as multiple lesions (≥3) and L. tropica is more often on the nose (Klaus 1999; AL Jawabreh et al., 2004). It was shown that multiplicity is more frequent in L. major infections (30%) than in L. tropica, (19%). Ten percent of L. tropica affect the nose, compared with 4% by L. major, and the chin shows the same pattern. Nonetheless, these sites are not the preferred ones for either species. The preferred sites for L. major are cheeks, arms and legs which account for more than 70% of the cases, while the preferred sites for L. tropica are cheeks and arms forming over 50% (Al-Jawabreh et al., 2004).

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Abnormal manifestations for L. major are the enlargement of regional lymph nodes which is found in about 10% of patients. At times, the infection spreads deeply into subcutaneous tissue and muscle (Al-Gindan et al., 1989; Vardy et al., 1993). Hyperesthesia or anesthesia around the lesion was reported (Satti et al., 1989). Another unusual clinical presentation of L. major CL is a sporotrichoid pattern, in which subcutaneous nodules develop along lymphatics during the course of the infections (Kubba et al., 1987). Other rare varieties include a hyperkeratotic type, in which a thick adherent scale develops over an otherwise unremarkable lesion, and a chronic form in which the skin lesions remain active for two years or more.

CL, generally, is adversely affected by HIV. The adverse effects are shown by diffuse widespread eruption of lesions over the body which may reach up to hundreds (Gillis et al, 1995). A rare form of L. tropica CL is known as Leishmania recidivans, or lupoid leishmaniasis. This is a late manifestation of an L. tropica infection that comes years after the infection has resolved. It presents as boggy papules in or around the scars of primary lesions. The papules transform slowly into a spreading Leishmania recidivans (Momeni et al., 1995; Klaus et al., 1999). There are few reports about L. tropica causing visceral leishmaniasis (Kala-azar) in India (Sacks et al., 1995) and canine VL in Morocco (Lemrani and Nejjar, 2002).

1.10.3 Clinical diagnosis and characterization

The clinical diagnosis of CL, according to the case definition (WHO Recommended Surveillance Standards, 1999), is confirmed by demonstrating amastigotes by stained smear microscopy and/or in-vitro culture. As reviewed by Klaus et al., 1999 and Ashford, 2000, amastigotes are intracellular parasites forms present in monocytes and macrophages, but they can also be found as extracellular parasites (Figure 3.2) Using light microscopy in a Giemsa-stained smear, the amastigotes are seen as pale-blue oval bodies, 2–5 µm in diameter, with a single violet-blue nucleus. The point-shaped kinetoplast is difficult to see under the microscope. In in-vitro culture, the flagellated motile promastigotes which are longer than amastigotes, 10-15µm, are usually seen under light microscopy moving rapidly in a zig-zag motion (Figure 1.4). Promastigotes are the form present in the sand-fly vector.

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Figure 1.4 Promastigotes: flagellated motile forms found in the vector and in culture (x1000).

The two species are two different parasites with each having a distinct transmission pattern. They can not, however, be distinguished by morphology, neither microscopically as amastigotes in smears nor as promastigotes by in-vitro culture. Other techniques were needed to diagnose and characterize these two along with other species of Leishmania. Isoenzyme analysis formed the gold standard for species and strain typing (Le Blancq and Peters 1986, Rioux et al., 1990). It showed that L. tropica is more polymorphic than L. major. Serological techniques like enzyme-linked immunosorbant assay (ELISA) were valueless for diagnosis (Al-Jawabreh et al., 2003) but others like EF serotyping were employed to serotype the two species from cultured promastigotes (Jaffe and Sarfstein 1987, Schnur et al. 1990).

Molecular methods were used for a more sensitive diagnosis and genotyping. PCR techniques like permissively primed intergenic polymorphic-polymerase chain reaction (PPIP-PCR) (Eisenberger and Jaffe 1999) and ITS1-PCR (El-Tai et al., 2001; Schoenian et al., 2003) were able to detect and to identify Leishmania parasites at species level. When these and other techniques, like single-strand conformation polymorphisms of the ribosomal internal transcribed spacer 1 (SSCP-ITS1), were used for strain typing. L. tropica was proven to be a more variable species compared to L. major (Schönian et al., 2001).

1.10.4 Vector

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It is commonly known that L. major is transmitted by females of mainly Phlebotomus papatasi, and L. tropica by mainly P. sergenti (Diptera, Nematocera, Psychodidae, Psychodinae) (Figure 1.5). Sand flies are smaller than 3 mm and spend the day in burrows and cracks to prevent drying out. The female flies are active during the evening, hopping around silently for their blood meals for reproduction. Sand flies have biting season during which they are active in transmission of infection. In the Middle East it extends from April/May to September/October (Killick-Kendrick, 1999; Jacobson, 2003; Wasserberg et al., 2003).

Figure 1.5 Phlebotomus species are the vectors for the Old World Leishmaniasis.

They are small (2–3 mm), hairy, midge-like insects, with long slender legs and rather short mouth parts. They are not strong fliers and usually stay within 200 m of their breeding sites. In cities, they breed in refuse piles, in cracks in the walls, and foundations of buildings and fences. In desert areas they breed within the burrows of rodents (Killick-Kendrick, 1999; Klaus et al., 1999).

There are other vetors for L. tropica such as P. (Larroussius) guggisbergi in Kenya (Lawyer et al. 1991) with an infection rate of 4.3%, and P. (L.) arabicus in Tiberias (Jacobson et al., 2003) with an infection rate of 5%.

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Vectors are either specific or permissive. Permissive vectors like P. argentipes, P. (L.) arabicus, P. perniciosis and P. halepensis have O-glycosylated receptors on their midgut epithelium supporting the adherence of different Leishmania species. In contrast, specific vectors like P. sergenti and P. papatasi lack these receptors and harbour only single species of Leishmania, L. tropica and L. major, respectively (Peckova et al., 2005). This is in agreement with the finding of Kamhawi et al. (2000) that P. sergenti does not support L. major and L. donovani.

1.10.5 Reservoir

A reservoir host is the ecological system in which an infectious agent survives persistently (Ashford, 1996). CL is either anthroponotic, where infection is transmitted by the vector from man to man, or zoonotic, where an animal reservoir host is involved. L. major is completely zoonotic with various animals being confirmed as reservoirs. In North Africa and South-west Asia it is Psammomys obesus, a rodent living in underground burrows (Klaus 1999, Ashford, 1996) (Figure 1.6.a). In Iran and Central Asia, gerbils are the common reservoirs, either Meriones libycus or Rhombomys opimus. L. major has also been isolated from Meriones shawi and Meriones lybicus (Rioux et al., 1986c; Ben-Ismail et al., 1987a).

Figure 1.6 (a) Psamommys obesus, fat sand rat, the established reservoir for L. major. (b) Rock hyrax from which L. tropica has been isolated

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CL caused by L. tropica is anthroponotic in urban areas and zoonotic in rural villages (Klaus et al., 1999). In several rural areas in Kenya and near Lake Tiberias, L. tropica has been isolated from hyraxes (Procavia capensis) (Figure 1.6.b) (Ashford and Sang, 2001; Jacobson et al., 2003).

1.10.6 Control

As a role of thumb, control measures are the result of breaking one or more elements in the life cycle. There is no single method that can be used for all situations and one method may be successful in one place but not in another. In addition, cost effectiveness has to be considered before adopting a certain method. Moreover, control measures should always be revised and evaluated. Some measures target the reservoir by eliminating the rodents, by destruction of the animals’ food sources, and /or ploughing burrows as in Jordan and Tunisia (Klaus et al., 1999; Ashford, 1996).

The sand fly vector has continuously been the target for control measures. This included the destruction of breeding sites by removing garbage and debris left near houses, and by covering cracks in buildings. In addition, spraying of residual insecticide inside houses and outside under windows were used. Plants like Bougainvillea glabra were shown to decrease the risk for leishmaniasis by reducing the life span for sand flies (Schlein et al., 2001). Impregnated bed nets with various insecticides such as Deltamethrin were applied as control measure with significant reduction in CL incidence rate (Alten et al., 2003).

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The human host was also a means for control either by allowing the patients to be treated 2-3 weeks after the appearance of the lesion, as is the policy in Jericho, to allow immunity to develop or by leishmaniazation as in Iran (Khamesipour et al., 2005). Further, there are attempts to develop Leishmania vaccine, but no definite results have been obtained yet (Valenzuela et al., 2001)

1.10.7 Treatment

Most CL cases heal spontaneously in less than a year. However, living for one year with a lesion in the face which may be disfiguring and may complicate due to secondary bacterial infection is problematic. Treatment is the sole choice for these patients. Dowlati (1996) reviewed types of therapeutic strategies for CL. Among the methods tried with varying degrees of success are thermotherapy, cryotherapy with liquid nitrogen, and surgery (Dowlati, 1996; Al-Majali et al., 1997; Reithinger et al., 2005). The most common treatment in most parts of the world is the intralesional application of pentavalent antimonials, e.g. sodium stibgluconate (WHO, 1990) commercially known as Pentostam (Glaxowellcom). The dose per lesion is 0.2-0.4 ml (100 mg/ml) or 15-20 mg /kg/day for 15-20 times every other day, more or less depending on the lesion and its response to treatment (Croft and Yardley, 2002). Pentostam can be given intramuscularly (IM) or intravenously (IV) depending on the progress and stage of the lesion. In the case of systemic treatment (IV), a patient should be hospitalized and liver enzymes monitored for toxicity. Meglumine antimonate or Glucantime are other forms of antimony compound that was used once.

Topical ointments have been also used. Paromomycin, in combination with methyl benzethonium chloride gave different rates of success when applied in areas where either L. major or L. tropica (Klaus et al., 1999) is endemic. L. tropica tend to be less responsive to therapy. In a few cases it took more than 6 months for large lesions on the nose to heal up (observations from patients in Jericho). To allow development of lasting immunity, patients with lesion(s) less than 3 weeks old are not treated and advised to come back after the 3-week period had elapsed.

1.11 Population genetics of Leishmania parasites

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Population genetics dates back more than one hundred years, yet its modern form emerged only during the 1970s (Wakeley and Takahashi, 2003). Hartl and Clark (1997) defined population as a group of organisms of the same species living within a sufficiently restricted geographical area that any member can potentially mate with any other member. This definition bounds the population by mating of same species in a restricted geography. Population genetics can be defined as ‘the m athematical study of the dynamics of genetic variation within species. Its main purpose is to understand the ways in which the forces of mutation, natural selection, random genetic drift, and population structure interact to produce and maintain the complex patterns of genetic variation that are observed among individuals within a species’ (Wakely, 2005).

Clonality vs sexuality debate

As for any parasite, the mode of reproduction of Leishmania can either be sexual or asexual (clonal). Sexual reproduction means passing half of the genes to the new progeny while asexual or clonal means passing all of the genes to the progeny (Ayala et al., 1998). Natural selection favours asexual reproduction, because given the same number of progeny, the asexual individual has double the fitness of the sexually reproducing one (Ayala et al., 1998; Victoir and Dujardin, 2002). Sexual reproduction has the advantage of creating variability for adaptation to changing environments, but has the disadvantage that advantageous gene combinations may be disrupted (Victoir and Dujardin, 2002). Since sexual recombination in Leishmania seems to be either absent or very rare, the “clonal theory” was proposed to explain the population structure of different Leishmania species (Panton et al., 1991; Tibayrenc et al., 1990; Dujardin et al., 1995). According to this theory, genetic variability is due to gene mutations and their selection along clonal lineages. Clonality, but without solid prove, was preferred by Lanotte et al. (1986) and Lainson and Shaw (1986). Studies on Trypanosoma cruzi, another kinetoplastid parasite, and other parasites concluded that natural populations reproduce predominantly clonally (Tibayrenc & Ayala 1988, Tibayrenc et al., 1990). Yet, parasites can undergo sexual recombination in the laboratory (Tibayrenc et al., 1990 & 1991)

The knowledge of the mode of reproduction, clonal or sexual, is important for answering many clinical, epidemiological and public health questions. Ayala et al., (1998) lists three reasons: First, in a sexually reproducing organism the individual genotype is ephemeral; the entity that persists and evolves is the gene pool, and a few individuals encompass most of the genetic variability of the species. On the contrary, for a clonal organism, the entity that persists and evolves is the clonal lineage and the genetic diversity of the species can be captured only by extensive sampling of distinct lineages. Second, extensive genetic divergence among clonal lineages may reflect diverse biological characteristics, including pathogenicity, resistance to drugs and vaccines and other clinical parameters. Third, in clonal organisms, epidemiological surveys, medical typing and drug development should be based on identification and characterization of clonal lineages, targeting those that are more pathogenic or ubiquitous.

1.12  Genetic diversity and bottleneck theory

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A population bottleneck (or genetic bottleneck) is usually defined as an evolutionary event in which a significant percentage of a population or species is killed or otherwise prevented from reproducing, and the population is reduced by 50% or more. Bottlenecks reduce genetic variation and strongly disrupt the pattern of allele frequencies especially if the population has a low growth rate or high reproductively skew defined as a high variance in the reproductive success of either males or females (Hoelzel, 1999). It increases genetic drift which is inversely proportional to the population size. The overall and lasting result of a bottleneck is the reduction of genetic diversity, redistribution and reduction of allele frequencies and disappearance of rare alleles (Hoelzel 1999 and 2002). The immediate and transient observation following a bottleneck event is, however, the unexpected increase in heterozygosity level (Cornuet & Luikart, 1996) due to sudden and rapid loss of rare alleles and resulting deficit of alleles (Hoezel 2002). The bottleneck phenomenon has a detrimental effect on the population as the loss of genetic diversity and reduced polymorphism hinders the potential of a population to respond to a changing environment (Hoelzel, 1999).

This impact of bottleneck is dependent on two factors: the effective size of the population, and the duration for which the population remains small. However, the duration of the bottleneck effect can be minimized if the growth rate of the population is high (Hoelzel, 1999).

The bottleneck hypothesis was often used to explain observations of low genetic variation (O’Brien et al.1987; Gottelli et al. 1994). An important aspect about bottlenecks is that they may lead to the introduction of new species (Dodd and Powell 1985; Ringo et al. 1985; Meffert and Bryant 1991; Galiana et al. 1993), though it is not the only reason for the rise of new species (Turelli et al. 2001).

1.13 Objectives (Figure 1.7)

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As mentioned above, use of new molecular techniques offers various possibilities for diagnostics, epidemiology and applied genetics.

Dealing with material from an endemic area, there were three main applications we were interested in: use for molecular clinical diagnosis, molecular epidemiology and to study molecular diversity. For each topic a subset of problems were to be solved:

1. Molecular clinical diagnosis :

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a. To apply molecular- based techniques (ITS1- PCR) for detection and identification of Leishmania parasites in new and old archived clinical samples collected in the vicinity of Jericho from patients to re-evaluate the epidemiology of cutaneous leishmaniasis in this area.

So far, detection of Leishmania was based on microscopy and cultivation, both methods being not very sensitive. PCR detection will be used to detect and to identify the parasites at species level in all samples contained in the human clinical sample bank.

b. Performance of the ITS1-PCR method will also be evaluated using two types of clinical samples, unstained tissue scrapings and blood and tissue scrapings on filter paper.

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c. Comparing the performance of the classical diagnostic methods (microscopy and culture) with the ITS1-PCR.

d. Evaluating graded microscopy vs. ITS1-PCR using Giemsa-stained clinical samples.

2. Molecular epidemiology

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a. So far, the frequency, distribution and determinants of CL in the District of Jericho were described based on conventional epidemiology. Molecular-based methods i. e ITS1-PCR and RFLP will be used as epidemiological tools to describe the situation in what is called ‘molecular epidemiology’. This includes correlating the results obtained by molecular methods to demographic and environmental factors that are known to influence the relative abundance of parasites, reservoir hosts and vectors.

b. To check, for a purely public health consideration that includes vector control, for space-time clusters for cases of CL (spatial-temporal clusters).

Not only population growth and movements, introduction of non-immune people into area of endemic foci, enhanced urbanization, but also ecological changes, most probably the effect of global warming, are known to lead to an increase of prevalence of cutaneous leishmaniasis. Changes in the modern demographic and environmental conditions will be recorded and correlated to the molecular epidemiological data obtained in this study.

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3. Molecular Genetic diversity :

To analyse genetic variation in strains of L. major isolated in Jericho area as well as from other geographical locations (Middle East, Africa, and Central Asia) by using microsatellite markers. Ten different microsatellite markers will be applied to assess genetic heterogeneity within L. major. Based on the information obtained, attempts will be made to analyse the genetic structure of different populations of L. major using appropriate software.

Figure 1.7 Study plan


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