GWAS stands for Genome Wide Association Studies. It aims to use cutting edge technology to associate genetic polymorphisms to human diseases by analyzing SNPs on genetic markers. It compares populations with a particular disease to normal, to identify statistically significant polymorphisms that could contribute to disease. Here is the link to more information and all the results are stored in a database.


A GWAS study usually uses a case-control study and this can be effectively done only if the genome sequence of the organism is known. Usually, common SNP's are represented on a gene chip (usually a million) and two sets of populations are screened for the relative abundance of markers. In short, it is a fishing expedition and the outcome depends on how well the genetic markers are represented. The odds ratio is then calculated for every allele. It is the ratio of the presence of a specific allele in the control group compared to the case group. If the odds ratio is more than one, that means the allele has a higher frequency in the case group compared to the normal control group. p-value is determined : the lower it is, the significant it is. A plot with negative log of p value is then generated. This plot is called the Manhattan plot which will clearly identify the the statistically significant SNP that is associated with the disease in study.

Sometimes, GWAS studies can involve linkage association mapping and transcript analysis as well. An important complication that questions the significance of a GWAS study involving large groups is population stratification. People of different ethnic groups, age, location will have variability in polymorphisms and gene expression. Here is thelink for more information.

reference: wikipedia


Malaria is a disease caused by the apicomplexan parasite of the genus Plasmodium. It is transmitted via a mosquito vector and is endemic in regions of Africa, South east Asia and South America. Symptoms range from fever, chills to flu-like symptoms to severe anemia and meningitis. More information on the disease is available here. There have been several intitatives taken by the WHO (World Heath Organization) and the Gates Foundation to control this deadly disease with causes over one million deaths of children, pregnant women and immunocompromised patients. Fig1 shows the areas of the world at risk for Malaria which was a part of the Malaria Atlas project (MAP).

Fig1: Malaria Risk Areas

The darker the gradient of yellow, the higher the risk in the indicated areas. Drugs belonging to the 4-aminoquinoline and artemisinin groups are used for treatment but there has been widespread resistance to these family of drugs.Vaccine is available but it is not as effective to control this disease in endemic regions that are poor.

Our genes determine the susceptibility to MalariaEdit

Genes that determine host susceptibility are usually involved in host immune response or host-parasite interaction. This is due to natural selection and co-evolution of the parasite with its host. With the advancements in technology the exact locus and the associated polymorphisms of a few genes have been identified. So far, GWAS studies have identified a number of genes including ones that contribure to sickle cell disease and G6PD deficiency that confer resistance to the human host. Table 1 illustrates a list of genes identified so far. Table 2 shows all the SNPs, chromosomal location

Table 1- Genes involved in resistance to malaria

, gene id, p value and malarial susceptibility. Gene function is also illustrated in the same review. Genes contributing to malarial susceptibility seems to be involved in immune response (cytokine genes), the complement system and endothelial receptors. .(PMID:21929748).
Table 2

Table2: SNPs and genes associated with malarial susceptibility

A genome wide gene expression study, associated genes involved in absolute neutrophil count to malaria susceptibility. These were mainly involved in innate and adaptive immunity. Genome wide linkage analysis in many African populations (Senegal) showed association to chromosomal regions 10p15.3-14 and chromosome 13q. Asymptomatic malaria was linked to chromosomal region 5q31 whereas clinical disease was linked to 5p15 and 13q13. Several ethnic groups from West Africa are known to be resistant to P.falciparum malaria showed a hyper immune response with a possible functional deficiency in T regulatory cells. Studies also show that people with blood group O have more resistance compared to other blood types.

Factors that can influence a GWAS analysis which require careful thought and planning include sample size, its soource, population sub-structure (ethinicty,age, gender), disease severity in locations, type of malaria, sensitivity of the affymetrix chip used, role of co-infections and polymorphisms unique or shared amongst different diseases/phenotypes.

A GWAS study that identified two resistance loci for Severe MalariaEdit

A GWAS analysis was done by collaborating groups from Germany and Ghana in efforts to identify the locus important for resistance against P.falciparum severe malaria. They took a case-control approach, analyzed 1325 Severe Malaria (SM) cases and 828 unaffected individuals using an affymetrix Human SNP Array 6.0 and MACH software for analysis. They looked at a total of 5,010,634 SNPs and adjusted data for gender, age, population stratification. The reference genotypes were used from 174 African people provided by the 1000 genomes project. A duplicate analysis was performed using 1,320 SM cases and 2,222 control cases. 102 SNPs in 41 genomic loci were identified and further narrowed for ethnicity, as the reference had a mix of many. Four loci with significant P value less than 5*10^-8 were identified as shown in fig2. Two of them were novel which included SNP rs4951074 on chromosome 1q32.1 with a recessive mode of inheritence and an intergenic polymorphism on chromosome 16q22.2 lined to theprotein MARVELD3.

Fig2: Manhattan plot showing the results of a GWAS analysis for malaria resistance

They looked at people from Ghana and Gambia. The other two signals identified were consistent with previous studies. These include the sickle cell allele hemoglobin S and SNPs in ABO gene.

Several SNPs showed up for the first unique loci on chromosome1. Linkage disequilibrium analysis narrowed this down to 73 SNPs in the loci. The g ene was identified as ATP2B4. The exons and 1000bp upstream region was screened for promoter and splice variants by high resulotion melting and requencing. The ATP2B4 gene encodes a protein product PMCA4 which is a calcium pump for many cells especially erythrocytes that are infected by malarial parasites. Changes in calcium levels may affect the intracellular growth of the parasites in the erythrocytes. When levels are too low, it affects parasite replication within parasitophorous vacuoles.

The other novel locus identified on chromosome 16q22.2. It has a house keeping gene TAT and a SNP was identified 6.4kb upstream of gene MARVELD3. The gene product is part of the tight junction structures in vascular endothelial cells and epithelial cells. Adherence of infected erythrocytes is very important to avoid detection by immune surveylence. This protein may interfere with adherence and thus contribute to resistance.

This study highlights the interactions between host-pathogen competition for fitness. It shows that GWAS studies can be used to identify such interactions which can contribute to better understand pathogenesis and treatment of a disease.


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