Evaluation of the Dynamics and Immuno-Virology of Human Papillomavirus Infections among Fishermen in Kisumu, Kenya
Location(s): Kenya
Parent Project: UCSF-Gladstone Center for AIDS Research (CFAR)
Description
Human papillomavirus (HPV) is associated with cervical, vulvar, anal and penile cancers. High incidence rates of these cancers are observed in Africa compared to other parts of the world. Severa studies have implicated that the sexual behavior of the male partner is or even more important than women's personal sexual behavior in predicting her risk of HPV associated cancers. Little is known about the natural history of HPV infections among men; thus hampering efforts to control infection in both men and women. Therefore, we propose to conduct a prospective study among a sexually high risk group of men in Kenya -- the fishermen. This will further our understanding of the dynamics and immunology of HPV infections among men, so as to inform development of effective programs to reduce its burden in both men and women. The objective of this study is to evaluate the role of natural HPV immunity on the incidence, persistence or clearance of HPV infections and HPV intra-type genetic variability among fishermen. The null hypotheses are that most HPV infections in fishermen are not transient, therefore there is no difference in immune response between fishermen with persistent and non-persistent HPV infection; and there is no HPV intra-type genetic variability among these men. Consenting 300 fishermen in Kisumu Kenya will be enrolled and followed up every three months for 12 months. Genital swabs for HPV testing will be collected at all visits. 38 ml of blood for peripheral blood mononuclear cells (PBMC) and HPV serology will be drawn at enrollment and exit visits. HPV DNA status will be determined by Roche Linear array genotyping assay, genetic variability by sequencing and HPV serology by ELISA. Interferon gamma immune response evaluated on PBMCs by flow cytometry. Statistical analyses will be performed using SPSS and MEGA 4 software for sequence analysis.