Dataset Information

MalHaploFreq: a computer programme for estimating malaria haplotype frequencies from blood samples.

ABSTRACT:

Background

Molecular markers, particularly those associated with drug resistance, are important surveillance tools that can inform policy choice. People infected with falciparum malaria often contain several genetically-distinct clones of the parasite; genotyping the patients' blood reveals whether or not the marker is present (i.e. its prevalence), but does not reveal its frequency. For example a person with four malaria clones may contain both mutant and wildtype forms of a marker but it is not possible to distinguish the relative frequencies of the mutant and wildtypes i.e. 1:3, 2:2 or 3:1.

Methods

An appropriate method for obtaining frequencies from prevalence data is by Maximum Likelihood analysis. A computer programme has been developed that allows the frequency of markers, and haplotypes defined by up to three codons, to be estimated from blood phenotype data.

Results

The programme has been fully documented [see Additional File 1] and provided with a user-friendly interface suitable for large scale analyses. It returns accurate frequencies and 95% confidence intervals from simulated dataset sets and has been extensively tested on field data sets.

Conclusion

The programme is included [see Additional File 2] and/or may be freely downloaded from 1. It can then be used to extract molecular marker and haplotype frequencies from their prevalence in human blood samples. This should enhance the use of frequency data to inform antimalarial drug policy choice.

SUBMITTER: Hastings IM

PROVIDER: S-EPMC2490701 | biostudies-literature | 2008 Jul

REPOSITORIES: biostudies-literature

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Publications

MalHaploFreq: a computer programme for estimating malaria haplotype frequencies from blood samples.

Hastings Ian M IM Smith Thomas A TA

Malaria journal 20080715

<h4>Background</h4>Molecular markers, particularly those associated with drug resistance, are important surveillance tools that can inform policy choice. People infected with falciparum malaria often contain several genetically-distinct clones of the parasite; genotyping the patients' blood reveals whether or not the marker is present (i.e. its prevalence), but does not reveal its frequency. For example a person with four malaria clones may contain both mutant and wildtype forms of a marker but ...[more]

PMID: 18627599

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Project description:BackgroundReliable measures of anti-malarial resistance are crucial for malaria control. Resistance is typically a complex trait: multiple mutations in a single parasite (a haplotype or genotype) are necessary for elaboration of the resistant phenotype. The frequency of a genetic motif (proportion of parasite clones in the parasite population that carry a given allele, haplotype or genotype) is a useful measure of resistance. In areas of high endemicity, malaria patients generally harbour multiple parasite clones; they have multiplicities of infection (MOIs) greater than one. However, most standard experimental procedures only allow measurement of marker prevalence (proportion of patient blood samples that test positive for a given mutation or combination of mutations), not frequency. It is misleading to compare marker prevalence between sites that have different mean MOIs; frequencies are required instead.MethodsA Bayesian statistical model was developed to estimate Plasmodium falciparum genetic motif frequencies from prevalence data collected in the field. To assess model performance and computational speed, a detailed simulation study was implemented. Application of the model was tested using datasets from five sites in Uganda. The datasets included prevalence data on markers of resistance to sulphadoxine-pyrimethamine and an average MOI estimate for each study site.ResultsThe simulation study revealed that the genetic motif frequencies that were estimated using the model were more accurate and precise than conventional estimates based on direct counting. Importantly, the model did not require measurements of the MOI in each patient; it used the average MOI in the patient population. Furthermore, if a dataset included partially genotyped patient blood samples, the model imputed the data that were missing. Using the model and the Ugandan data, genotype frequencies were estimated and four biologically relevant genotypes were identified.ConclusionsThe model allows fast, accurate, reliable estimation of the frequency of genetic motifs associated with resistance to anti-malarials using prevalence data collected from malaria patients. The model does not require per-patient MOI measurements and can easily analyse data from five markers. The model will be a valuable tool for monitoring markers of anti-malarial drug resistance, including markers of resistance to artemisinin derivatives and partner drugs.

Project description:The killer cell immunoglobulin-like receptors (KIR) mediate human natural killer (NK) cell cytotoxicity via activating or inhibiting signals. Although informative and functional haplotype patterns have been reported, most genotyping has been performed at resolutions that are structurally ambiguous. In order to leverage structural information given low-resolution genotypes, we performed experiments to quantify the effects of population variations, reference haplotypes, and genotyping resolutions on population-level haplotype frequency estimations as well as predictions of individual haplotypes. We genotyped 10,157 unrelated individuals in 5 populations (518 African American[AFA], 258 Asian or Pacific Islander[API], 8,245 European[EUR], 1,073 Hispanic[HIS], and 63 Native American[NAM]) for KIR gene presence/absence (PA), and additionally half of the AFA samples for KIR gene copy number variation (CNV). A custom EM algorithm was used to estimate haplotype frequencies for each population by interpretation in the context of three sets of reference haplotypes. The algorithm also assigns each individual the haplotype pairs of maximum likelihood. Generally, our haplotype frequency estimates agree with similar previous publications to within <5% difference for all haplotypes. The exception is that estimates for NAM from the U.S. showed higher frequency association of cB02 with tA01 (+14%) instead of tB01 (-8.5%) compared to a previous study of NAM from south of the U.S. The higher-resolution CNV genotyping on the AFA samples allowed unambiguous haplotype-pair assignments for the majority of individuals, resulting in a 22% higher median typing resolution score (TRS), which measures likelihood of self-match in the context of population-specific haplo- and geno-types. The use of TRS to quantify reduced ambiguity with CNV data clearly revealed the few individuals with ambiguous genotypes as outliers. It is observed that typing resolution and reference haplotype set influence haplotype frequency estimates. For example, PA resolution may be used with reference haplotype sets up to the point where certain haplotypes are gene-content subsets of others. At that point, CNV must be used for all genes.

Project description:BACKGROUND:Malaria continues to be a great public health concern due to the significant mortality and morbidity associated with the disease especially in developing countries. Microparticles (MPs), also called plasma membrane derived extracellular vesicles (PMEVs) are subcellular structures that are generated when they bud off the plasma membrane. They can be found in healthy individuals but the numbers tend to increase in pathological conditions including malaria. Although, various studies have been carried out on the protein content of specific cellular derived MPs, there seems to be paucity of information on the protein content of circulating MPs in malaria and their association with the various signs and symptoms of the disease. The aim of this study was therefore to carry out proteomic analyses of MPs isolated from malaria positive samples and compare them with proteins of MPs from malaria parasite culture supernatant and healthy controls in order to ascertain the role of MPs in malaria infection. METHODS:Plasma samples were obtained from forty-three (43) malaria diagnosed patients (cases) and ten (10) healthy individuals (controls). Malaria parasite culture supernatant was obtained from our laboratory and MPs were isolated from them and confirmed using flow cytometry. 2D LC-MS was done to obtain their protein content. Resultant data were analyzed using SPSS Ver. 21.0 statistical software, Kruskal Wallis test and Spearman's correlation coefficient r. RESULTS:In all, 1806 proteins were isolated from the samples. The MPs from malaria positive samples recorded 1729 proteins, those from culture supernatant were 333 while the control samples recorded 234 proteins. The mean number of proteins in MPs of malaria positive samples was significantly higher than that in the control samples. Significantly, higher quantities of haemoglobin subunits were seen in MPs from malaria samples and culture supernatant compared to control samples. CONCLUSION:A great number of proteins were observed to be carried in the microparticles (MPs) from malaria samples and culture supernatant compared to controls. The greater loss of haemoglobin from erythrocytes via MPs from malaria patients could serve as the initiation and progression of anaemia in P.falciparum infection. Also while some proteins were upregulated in circulating MPs in malaria samples, others were down regulated.

Dataset Information

MalHaploFreq: a computer programme for estimating malaria haplotype frequencies from blood samples.

Background

Methods

Results

Conclusion

Publications

MalHaploFreq: a computer programme for estimating malaria haplotype frequencies from blood samples.

Similar Datasets

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