Molecular Characterization of Cryptosporidium spp. among Children in Rural Ghana

BACKGROUND The relevance of Cryptosporidium infections for the burden of childhood diarrhoea in endemic settings has been shown in recent years. This study describes Cryptosporidium subtypes among symptomatic and asymptomatic children in rural Ghana to analyse subtype-specific demographic, geographical, seasonal and clinical differences in order to inform appropriate control measures in endemic areas. METHODOLOGY/PRINCIPAL FINDINGS Stool samples were collected from 2232 children below 14 years of age presenting with and without gastrointestinal symptoms at the Agogo Presbyterian Hospital in the rural Ashanti region of Ghana between May 2007 and September 2008. Samples were screened for Cryptosporidium spp. by PCR and isolates were classified into subtypes based on sequence differences in the gp60 gene. Subtype specific frequencies for age, sex, location and season have been determined and associations with disease symptoms have been analysed within a case-control study. Cryptosporidium infections were diagnosed in 116 of 2232 (5.2%) stool samples. Subtyping of 88 isolates revealed IIcA5G3 (n = 26, 29.6%), IbA13G3 (n = 17, 19.3%) and IaA21R3 (n = 12, 13.6%) as the three most frequent subtypes of the two species C. hominis and C. parvum, known to be transmitted anthroponotically. Infections peak at early rainy season with 67.9% and 50.0% of infections during the months April, May and June for 2007 and 2008 respectively. C. hominis infection was mainly associated with diarrhoea (odds ratio [OR] = 2.4; 95% confidence interval [CI]: 1.2-4.9) whereas C. parvum infection was associated with both diarrhoea (OR = 2.6; CI: 1.2-5.8) and vomiting (OR = 3.1; 95% CI: 1.5-6.1). CONCLUSIONS/SIGNIFICANCE Cryptosporidiosis is characterized by seasonal anthroponotic transmission of strains typically found in Sub-Saharan Africa. The infection mainly affects young infants, with vomiting and diarrhoea being one of the leading symptoms in C. parvum infection. Combining molecular typing and clinical data provides valuable information for physicians and is able to track sources of infections.